diff --git a/generators/progressive_random.py b/generators/progressive_random.py
index 9914b47..ff2f973 100644
--- a/generators/progressive_random.py
+++ b/generators/progressive_random.py
@@ -5,7 +5,7 @@
 class SequenceGenerator:
     """Generate a sequence progressively according to a predefined TL ratio and an even distribution"""
 
-    def __init__(self, choices, trials, tl=4.0, n=3, targets_ratio=0.2):
+    def __init__(self, choices, trials, tl=4.0, n=3, targets_ratio=0.33):
         """Initialize the genetic algorithm optimizer for n-back sequences.
         :param choices:
         :param trials:
@@ -52,7 +52,7 @@
         for c in list(seq):
             costs[c] += (1.0 if costs.__contains__(c) else 0.0)
         even_ratio = self.trials / len(self.choices)
-        costs = {k: abs(v - even_ratio)/self.trials for k,v in costs.items()}
+        costs = {k: abs(v - even_ratio)/self.trials for k, v in costs.items()}
         return max(list(costs.values()))
 
     def cost(self, seq):
@@ -63,15 +63,15 @@
         :return:
         """
 
-        targets, lures = self.count_targets_and_lures(seq, self.n)
+        targets, lures = self.count_targets_and_lures(seq)
         targets_ratio_cost = 1.0 - self.norm_targets_ratio_dist.pdf(targets/self.trials)
-        tl_ratio_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.calc_tl_ratio(seq, self.n))
+        tl_ratio_cost = 1.0 - self.norm_tl_ratio_dist.pdf(self.calc_tl_ratio(seq))
         even_dist_cost = 1.0 - self.norm_even_dist.pdf(self.calc_even_distribution_distance(seq))
         # print(targets_ratio_cost, tl_ratio_cost, even_dist_cost)
         return targets_ratio_cost + tl_ratio_cost + even_dist_cost
 
-    @staticmethod
-    def count_targets_and_lures(seq, n: int):
+    def count_targets_and_lures(self, seq):
+        n = self.n
         targets = 0.0
         lures = 0.0
         for index in range(n, len(seq)):
@@ -81,9 +81,9 @@
                 lures += 1.0
         return targets, lures
 
-    def calc_tl_ratio(self, seq, n: int):
+    def calc_tl_ratio(self, seq):
         """Calculates the T/L ratio in a block of trials."""
-        targets, lures = self.count_targets_and_lures(seq, n)
+        targets, lures = self.count_targets_and_lures(seq)
         if lures < 0.01:  # avoid division by zero
             lures = 0.01
         return targets/lures
@@ -91,10 +91,14 @@
 
 if __name__ == '__main__':
 
-    n = 3
-    generator = SequenceGenerator(['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h'], trials=128, n=n)
+    alphabetic_choices = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H']
+    generator = SequenceGenerator(alphabetic_choices, trials=128, n=3)
     sq = generator.generate()
-    tl_ratio = generator.calc_tl_ratio(sq, n=n)
+    tl_ratio = generator.calc_tl_ratio(sq)
     even_dist_distance = generator.calc_even_distribution_distance(sq)
 
-    print('Progressively-Optimized Sequence: targets=%d, lures=%d' % generator.count_targets_and_lures(sq, n=n), 'with tl_ratio=%f' % tl_ratio, 'and even_dist_cost=%f' % even_dist_distance)
+    print(
+        'Progressively-Optimized Sequence: targets=%d, lures=%d' % generator.count_targets_and_lures(sq),
+        'with tl_ratio=%f' % tl_ratio,
+        'and even_dist_cost=%f' % even_dist_distance
+    )