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Rewrote data_list to __iter__

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This commit is contained in:
SimpleArt
2020-11-19 10:17:22 -05:00
parent 857e248034
commit 6e95ff5d9d
3 changed files with 25 additions and 22 deletions
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32
src/crossover/crossover_methods.py
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@ -69,9 +69,9 @@ class Crossover_Methods:
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(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
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(iter(parent_1), iter(parent_2))]) # each parents' genes
def int_weighted(ga, parent_1, parent_2):
@ -80,19 +80,19 @@ 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(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
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(iter(parent_1), iter(parent_2))]) # 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(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
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(iter(parent_1), iter(parent_2))]) # from each parents' genes
def float_weighted(ga, parent_one, parent_two):
@ -101,8 +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*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
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(iter(parent_1), iter(parent_2))]) # from each parents' genes