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Fixed method names and added some crossover methods and tests for floats

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This commit is contained in:
SimpleArt
2020-10-13 21:07:05 -04:00
parent b966b22b04
commit 0090db9dce
7 changed files with 89 additions and 36 deletions
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17
src/EasyGA.py
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@ -6,22 +6,23 @@ from structure import Chromosome as create_chromosome
from structure import Gene as create_gene
# Structure Methods
from fitness_function import Fitness_Examples
from initialization import Initialization_Methods
from fitness_function import Fitness_Examples
from initialization import Initialization_Methods
from termination_point import Termination_Methods
# Parent/Survivor Selection Methods
from parent_selection import Parent_Selection
from parent_selection import Parent_Selection
from survivor_selection import Survivor_Selection
# Genetic Operator Methods
from mutation import Mutation_Methods
from mutation import Mutation_Methods
from crossover import Crossover_Methods
class GA:
def __init__(self):
"""Initialize the GA."""
# Initilization variables
self.chromosome_length = 10
self.population_size = 10
@ -33,7 +34,7 @@ class GA:
# Selection variables
self.parent_ratio = 0.1
self.selection_probability = 0.95
self.selection_probability = 0.75
self.tournament_size_ratio = 0.1
# Termination variables
@ -54,7 +55,7 @@ class GA:
# Methods for accomplishing Parent-Selection -> Crossover -> Survivor_Selection -> Mutation
self.parent_selection_impl = Parent_Selection.Tournament.with_replacement
self.crossover_individual_impl = Crossover_Methods.Individual.single_point_crossover
self.crossover_individual_impl = Crossover_Methods.Individual.single_point
self.crossover_population_impl = Crossover_Methods.Population.random_selection
self.survivor_selection_impl = Survivor_Selection.fill_in_best
self.mutation_individual_impl = Mutation_Methods.Individual.single_gene
@ -82,7 +83,7 @@ class GA:
else:
self.population.reset_mating_pool()
self.set_all_fitness()
self.population.set_all_chromosomes(self.sort_by_best_fitness(self.population.get_all_chromosomes()))
self.population.sort_by_best_fitness(self)
self.parent_selection_impl(self)
next_population = self.crossover_population_impl(self)
self.survivor_selection_impl(self, next_population)
@ -119,7 +120,7 @@ class GA:
"""
# Check each chromosome
for chromosome in self.population.get_all_chromosomes():
for chromosome in self.population.get_chromosome_list():
# Update fitness if needed or asked by the user
if(chromosome.get_fitness() is None or self.update_fitness):