Files
EasyGA/src/mutation/mutation_methods.py
SimpleArt 7e0134e785 Fixed bug
Potentially 0 mutations occur
2020-11-12 18:46:09 -05:00

80 lines
3.1 KiB
Python

import random
from math import ceil
class Mutation_Methods:
class Population:
"""Methods for selecting chromosomes to mutate"""
def random_selection(ga):
"""Selects random chromosomes"""
# Loop until enough mutations occur
for n in range(ceil(ga.population.size()*ga.chromosome_mutation_rate)):
index = random.randint(0, ga.population.size()-1)
ga.population.set_chromosome(ga.mutation_individual_impl(ga, ga.population.get_chromosome(index)), index)
def random_selection_then_cross(ga):
"""Selects random chromosomes and self-crosses with parent"""
# Loop until enough mutations occur
for n in range(ceil(ga.population.size()*ga.chromosome_mutation_rate)):
index = random.randint(0, ga.population.size()-1)
chromosome = ga.population.get_chromosome(index)
ga.population.set_chromosome(
ga.crossover_individual_impl(ga, chromosome, ga.mutation_individual_impl(ga, chromosome)),
index
)
class Individual:
"""Methods for mutating a single chromosome"""
def individual_genes(ga, old_chromosome):
"""Mutates a random gene in the chromosome and resets the fitness."""
chromosome = ga.make_chromosome(old_chromosome.get_gene_list())
# Loops until enough mutations occur
for n in range(ceil(chromosome.size()*ga.gene_mutation_rate)):
index = random.randint(0, chromosome.size()-1)
# Using the chromosome_impl
if ga.chromosome_impl is not None:
chromosome.set_gene(ga.make_gene(ga.chromosome_impl()[index]), index)
# Using the gene_impl
elif ga.gene_impl is not None:
chromosome.set_gene(ga.make_gene(ga.gene_impl()), index)
# Exit because no gene creation method specified
else:
print("You did not specify any initialization constraints.")
break
return chromosome
class Permutation:
"""Methods for mutating a chromosome
by changing the order of the genes."""
def swap_genes(ga, old_chromosome):
"""Mutates a random gene in the chromosome and resets the fitness."""
chromosome = ga.make_chromosome(old_chromosome.get_gene_list())
# Loops until enough mutations occur
for n in range(ceil(chromosome.size()*ga.gene_mutation_rate)):
index_one = random.randint(0, chromosome.size()-1)
index_two = random.randint(0, chromosome.size()-1)
gene_one = chromosome.get_gene(index_one)
gene_two = chromosome.get_gene(index_two)
chromosome.set_gene(gene_one, index_two)
chromosome.set_gene(gene_two, index_one)
return chromosome