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Using random.sample for efficiency

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This commit is contained in:
SimpleArt
2020-11-27 22:17:13 -05:00
parent 5407e2ea63
commit d25ea314ac
1 changed files with 32 additions and 29 deletions
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61
src/mutation/mutation_methods.py
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@ -35,29 +35,38 @@ def check_gene_mutation_rate(individual_method):
return new_method
def loop_selections(population_method):
"""Runs the population method until enough chromosomes are mutated."""
def loop_random_selections(population_method):
"""Runs the population method until enough chromosomes are mutated.
Provides the indexes of selected chromosomes to mutate using
random.sample to get all indexes fast.
"""
def new_method(ga):
sample_space = range(len(ga.population))
sample_size = ceil(len(ga.population)*ga.chromosome_mutation_rate)
# Loop the population method until enough chromosomes are mutated.
for _ in range(ceil(len(ga.population)*ga.chromosome_mutation_rate)):
population_method(ga)
for index in random.sample(sample_space, sample_size):
population_method(ga, index)
return new_method
def loop_mutations(individual_method):
def loop_random_mutations(individual_method):
"""Runs the individual method until enough
genes are mutated on the indexed chromosome.
"""
# Change input from index to chromosome.
def new_method(ga, index):
def new_method(ga, chromosome):
sample_space = range(len(chromosome))
sample_size = ceil(len(chromosome)*ga.gene_mutation_rate)
# Loop the individual method until enough genes are mutated.
for _ in range(ceil(len(ga.population[index])*ga.gene_mutation_rate)):
individual_method(ga, ga.population[index])
for index in random.sample(sample_space, sample_size):
individual_method(ga, chromosome, index)
return new_method
@ -67,44 +76,38 @@ class Mutation_Methods:
# Private method decorators, see above.
_check_chromosome_mutation_rate = check_chromosome_mutation_rate
_check_gene_mutation_rate = check_gene_mutation_rate
_loop_selections = loop_selections
_loop_mutations = loop_mutations
_loop_random_selections = loop_random_selections
_loop_random_mutations = loop_random_mutations
class Population:
"""Methods for selecting chromosomes to mutate"""
@check_chromosome_mutation_rate
@loop_selections
def random_selection(ga):
@loop_random_selections
def random_selection(ga, index):
"""Selects random chromosomes."""
index = random.randrange(len(ga.population))
ga.mutation_individual_impl(ga, index)
ga.mutation_individual_impl(ga, ga.population[index])
@check_chromosome_mutation_rate
@loop_selections
def random_avoid_best(ga):
@loop_random_selections
def random_avoid_best(ga, index):
"""Selects random chromosomes while avoiding the best chromosomes. (Elitism)"""
index = random.randrange(
ceil(ga.percent_converged*len(ga.population)*3/16),
len(ga.population)
)
ga.mutation_individual_impl(ga, index)
if index > ga.percent_converged*len(ga.population)*3/16:
ga.mutation_individual_impl(ga, ga.population[index])
class Individual:
"""Methods for mutating a single chromosome."""
@check_gene_mutation_rate
@loop_mutations
def individual_genes(ga, chromosome):
@loop_random_mutations
def individual_genes(ga, chromosome, index):
"""Mutates a random gene in the chromosome."""
index = random.randrange(len(chromosome))
# Using the chromosome_impl
if ga.chromosome_impl is not None:
chromosome[index] = ga.make_gene(ga.chromosome_impl()[index])
@ -123,13 +126,13 @@ class Mutation_Methods:
by changing the order of the genes."""
@check_gene_mutation_rate
@loop_mutations
def swap_genes(ga, chromosome):
@loop_random_mutations
def swap_genes(ga, chromosome, index):
"""Swaps two random genes in the chromosome."""
# Indexes of genes to swap
index_one = random.randrange(len(chromosome))
index_two = random.randrange(len(chromosome))
index_one = index
index_two = random.randrange(index_one)
# Swap genes
chromosome[index_one], chromosome[index_two] = chromosome[index_two], chromosome[index_one]