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Simplified a lot of code by zipping data lists

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SimpleArt
2020-11-19 09:54:17 -05:00
parent f1105f4df0
commit 857e248034
1 changed files with 25 additions and 38 deletions
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63
src/crossover/crossover_methods.py
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@ -46,8 +46,8 @@ class Crossover_Methods:
def single_point(ga, parent_one, parent_two):
"""Cross two parents by swapping genes at one random point."""
index = random.randint(0, parent_one.size()-1)
return ga.make_chromosome(parent_one.get_gene_list()[:index] + parent_two.get_gene_list()[index:])
swap_index = random.randint(0, parent_one.size()-1)
return ga.make_chromosome(parent_one.get_gene_list()[:swap_index] + parent_two.get_gene_list()[swap_index:])
def multi_point(ga, parent_one, parent_two):
@ -55,56 +55,44 @@ class Crossover_Methods:
pass
def uniform(ga, parent_one, parent_two):
def uniform(ga, parent_1, parent_2):
"""Cross two parents by swapping all genes randomly."""
return ga.make_chromosome([ # Make a new chromosome
random.choice([ # by selecting random genes from
parent_one.get_gene(i), # each parent
parent_two.get_gene(i) #
]) #
for i in range(parent_one.size())]) # for each gene
return ga.make_chromosome([ # Make a new chromosome
random.choice([gene_1, gene_2]) # by randomly selecting genes
for gene_1, gene_2 in zip(parent_1.gene_list, parent_2.gene_list)]) # from each parent
class Arithmetic:
"""Crossover methods for numerical genes."""
def int_random(ga, parent_one, parent_two):
def int_random(ga, parent_1, parent_2):
"""Cross two parents by taking a random integer value between each of the genes."""
return ga.make_chromosome([ # Make a new chromosome
ga.make_gene( # filled with new genes
random.randint(*sorted([ # by choosing random integers between
parent_one.get_gene(i).get_value(), # the parents' genes
parent_two.get_gene(i).get_value() #
]))) #
for i in range(parent_one.size())]) # for each gene
return ga.make_chromosome([ # Make a new chromosome
ga.make_gene(random.randint(*sorted([data_1, data_2]))) # by randomly selecting integer genes between
for data_1, data_2 in zip(parent_1.data_list(), parent_2.data_list())]) # each parents' genes
def int_weighted(ga, parent_one, parent_two):
def int_weighted(ga, parent_1, parent_2):
"""Cross two parents by taking a a weighted average of the genes."""
# the percentage of genes taken from the first gene
weight = 0.25
return ga.make_chromosome([ # Make a new chromosome
ga.make_gene(int( # filled with new integer genes
weight*parent_one.get_gene(i).get_value()+ # with weight% from parent one and
(1-weight)*parent_two.get_gene(i).get_value() # (100-weight)% from parent two
)) #
for i in range(parent_one.size())]) # for each gene
return ga.make_chromosome([ # Make a new chromosome
ga.make_gene(int( # filled with new integer genes
weight*data_1+(1-weight)*data_2 # with weight% from gene 1 and
)) # (100-weight)% from gene 2
for data_1, data_2 in zip(parent_1.data_list(), parent_2.data_list())]) # from each parents' genes
def float_random(ga, parent_one, parent_two):
"""Cross two parents by taking a random numeric value between each of the genes."""
return ga.make_chromosome([ # Make a new chromosome
ga.make_gene( # filled with new genes
random.uniform( # by taking a random float between
parent_one.get_gene(i).get_value(), # the parents' genes
parent_two.get_gene(i).get_value() #
) #
) #
for i in range(parent_one.size())]) # for each gene
return ga.make_chromosome([ # Make a new chromosome
ga.make_gene(random.uniform([data_1, data_2])) # by randomly selecting integer genes between
for data_1, data_2 in zip(parent_1.data_list(), parent_2.data_list())]) # from each parents' genes
def float_weighted(ga, parent_one, parent_two):
@ -113,9 +101,8 @@ class Crossover_Methods:
# the percentage of genes taken from the first gene
weight = 0.25
return ga.make_chromosome([ # Make a new chromosome
ga.make_gene( # filled with new float genes
weight*parent_one.get_gene(i).get_value()+ # with weight% from parent one and
(1-weight)*parent_two.get_gene(i).get_value() # (100-weight)% from parent two
) #
for i in range(parent_one.size())]) # for each gene
return ga.make_chromosome([ # Make a new chromosome
ga.make_gene( # filled with new float genes
weight*data_1+(1-weight)*data_2 # with weight% from gene 1 and
) # (100-weight)% from gene 2
for data_1, data_2 in zip(parent_1.data_list(), parent_2.data_list())]) # from each parents' genes