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This commit is contained in:
danielwilczak101
2020-12-03 02:16:10 -05:00
parent 85855c2746
commit 5fb26545d4
1 changed files with 13 additions and 8 deletions
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21
src/crossover/crossover_methods.py
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@ -22,7 +22,8 @@ def _check_weight(individual_method):
if 0 < weight < 1: if 0 < weight < 1:
return individual_method(ga, parent_1, parent_2, weight) return individual_method(ga, parent_1, parent_2, weight)
else: else:
raise ValueError("Weight must be between 0 and 1 when using the given crossover method.") raise ValueError("""Weight must be between 0 and 1 when using
the given crossover method.""")
return new_method return new_method
@ -75,7 +76,7 @@ class Crossover_Methods:
for index in range(len(mating_pool)): # for each parent in the mating pool for index in range(len(mating_pool)): # for each parent in the mating pool
yield ga.crossover_individual_impl( # apply crossover to yield ga.crossover_individual_impl( # apply crossover to
ga, # ga, #
mating_pool[index], # the parent and mating_pool[index], # the parent and
mating_pool[index-1], # the previous parent mating_pool[index-1], # the previous parent
0.5 # with equal weight 0.5 # with equal weight
@ -90,7 +91,7 @@ class Crossover_Methods:
for parent in mating_pool: # for each parent in the mating pool for parent in mating_pool: # for each parent in the mating pool
yield ga.crossover_individual_impl( # apply crossover to yield ga.crossover_individual_impl( # apply crossover to
ga, # ga, #
parent, # the parent and parent, # the parent and
random.choice(mating_pool), # a random parent random.choice(mating_pool), # a random parent
0.5 # with equal weight 0.5 # with equal weight
@ -106,16 +107,20 @@ class Crossover_Methods:
def single_point(ga, parent_1, parent_2, weight = 0.5): def single_point(ga, parent_1, parent_2, weight = 0.5):
"""Cross two parents by swapping genes at one random point.""" """Cross two parents by swapping genes at one random point."""
minimum_parent_length = min(len(parent_1), len(parent_2))
# Equally weighted indexes # Equally weighted indexes
if weight == 0.5: if weight == 0.5:
swap_index = random.randrange(N) swap_index = random.randrange(minimum_parent_length)
# Use weighted random index. # Use weighted random index.
else: else:
n = min(len(parent_1), len(parent_2)) weight_conversion = 2*weight if (weight < 0.5) else 0.5 / (1-weight)
t = 2*weight if (weight < 0.5) else 0.5 / (1-weight) rand_num = random.random()
x = random.random() swap_index = int(
swap_index = int(n * (1-(1-x)**t)**(1/t)) minimum_parent_length *
(1-(1-rand_num)**weight_conversion)**(1/weight_conversion)
)
# Randomly choose which parent's genes are selected first. # Randomly choose which parent's genes are selected first.
if random.choice([True, False]): if random.choice([True, False]):