b6ae77c7ea
Crossover/Mutation: - Split into individual and population subclasses. - Added sequential population crossover selection. - Renamed and reimplemented mutation methods. EasyGA: - Improved make_obj methods for the chromosomes and populations to take arguments. Initialization: - Improved to shorter code. - Fixed repeated error messages Chromosome: - Changed get/set_genes to get/set_gene_list.
37 lines
1.3 KiB
Python
37 lines
1.3 KiB
Python
import random
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from initialization.chromosome_structure.chromosome import Chromosome
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from initialization.population_structure.population import Population
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class Crossover_Methods:
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class Population:
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"""Methods for selecting chromosomes to crossover"""
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def sequential_selection(ga):
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"""Select sequential pairs from the mating pool"""
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mating_pool = ga.population.mating_pool
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return Population([ga.crossover_individual_impl(mating_pool[index], mating_pool[index+1]) for index in range(len(mating_pool)-1)])
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def random_selection(ga):
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"""Select random pairs from the mating pool"""
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mating_pool = ga.population.mating_pool
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return Population([ga.crossover_individual_impl(random.choice(mating_pool), random.choice(mating_pool)) for n in mating_pool])
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class Individual:
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"""Methods for crossing parents"""
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def single_point_crossover(parent_one, parent_two):
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"""Cross two parents by swapping genes at one random point"""
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index = random.randint(0, parent_one.size()-1)
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return Chromosome(parent_one.get_gene_list()[:index] + parent_two.get_gene_list()[index:])
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def multi_point_crossover(parent_one, parent_two):
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"""Cross two parents by swapping genes at multiple points"""
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pass
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