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Corrections using new names

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SimpleArt
2020-12-30 16:22:09 -05:00
parent 7c55bf431b
commit 827d86e3b1
2 changed files with 20 additions and 20 deletions
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12
src/EasyGA.py
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@ -27,16 +27,16 @@ from structure import Chromosome as make_chromosome
from structure import Gene as make_gene from structure import Gene as make_gene
# Misc. Methods # Misc. Methods
from fitness_function import Fitness_Examples from fitness_examples import Fitness_Examples
from termination_point import Termination_Methods from termination import Termination
# Parent/Survivor Selection Methods # Parent/Survivor Selection Methods
from parent_selection import Parent_Selection from parent import Parent
from survivor_selection import Survivor_Selection from survivor import Survivor
# Genetic Operator Methods # Genetic Operator Methods
from crossover import Crossover_Methods from crossover import Crossover
from mutation import Mutation_Methods from mutation import Mutation
# Default Attributes for the GA # Default Attributes for the GA
from attributes import Attributes from attributes import Attributes

28
src/attributes.py
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@ -14,16 +14,16 @@ from structure import Chromosome as make_chromosome
from structure import Gene as make_gene from structure import Gene as make_gene
# Misc. Methods # Misc. Methods
from fitness_function import Fitness_Examples from fitness_examples import Fitness_Examples
from termination_point import Termination_Methods from termination import Termination
# Parent/Survivor Selection Methods # Parent/Survivor Selection Methods
from parent_selection import Parent_Selection from parent import Parent
from survivor_selection import Survivor_Selection from survivor import Survivor
# Genetic Operator Methods # Genetic Operator Methods
from crossover import Crossover_Methods from crossover import Crossover
from mutation import Mutation_Methods from mutation import Mutation
# Database class # Database class
from database import sql_database from database import sql_database
@ -225,44 +225,44 @@ class Attributes:
return random.randint(1, 10) return random.randint(1, 10)
def _fitness_function_impl(self, *args, **kwargs): def fitness_function_impl(self, *args, **kwargs):
"""Default fitness function. Returns the number of genes that are 5.""" """Default fitness function. Returns the number of genes that are 5."""
return Fitness_Examples.is_it_5(*args, **kwargs) return Fitness_Examples.is_it_5(*args, **kwargs)
def parent_selection_impl(self, *args, **kwargs): def parent_selection_impl(self, *args, **kwargs):
"""Default parent selection method using tournament selection.""" """Default parent selection method using tournament selection."""
return Parent_Selection.Rank.tournament(self, *args, **kwargs) return Parent.Rank.tournament(self, *args, **kwargs)
def crossover_individual_impl(self, *args, **kwargs): def crossover_individual_impl(self, *args, **kwargs):
"""Default individual crossover method using single point crossover.""" """Default individual crossover method using single point crossover."""
return Crossover_Methods.Individual.single_point(self, *args, **kwargs) return Crossover.Individual.single_point(self, *args, **kwargs)
def crossover_population_impl(self, *args, **kwargs): def crossover_population_impl(self, *args, **kwargs):
"""Default population crossover method using sequential selection.""" """Default population crossover method using sequential selection."""
return Crossover_Methods.Population.sequential_selection(self, *args, **kwargs) return Crossover.Population.sequential(self, *args, **kwargs)
def survivor_selection_impl(self, *args, **kwargs): def survivor_selection_impl(self, *args, **kwargs):
"""Default survivor selection method using the fill in best method.""" """Default survivor selection method using the fill in best method."""
return Survivor_Selection.fill_in_best(self, *args, **kwargs) return Survivor.fill_in_best(self, *args, **kwargs)
def mutation_individual_impl(self, *args, **kwargs): def mutation_individual_impl(self, *args, **kwargs):
"""Default individual mutation method by randomizing individual genes.""" """Default individual mutation method by randomizing individual genes."""
return Mutation_Methods.Individual.individual_genes(self, *args, **kwargs) return Mutation.Individual.individual_genes(self, *args, **kwargs)
def mutation_population_impl(self, *args, **kwargs): def mutation_population_impl(self, *args, **kwargs):
"""Default population mutation method selects chromosomes randomly while avoiding the best.""" """Default population mutation method selects chromosomes randomly while avoiding the best."""
return Mutation_Methods.Population.random_avoid_best(self, *args, **kwargs) return Mutation.Population.random_avoid_best(self, *args, **kwargs)
def termination_impl(self, *args, **kwargs): def termination_impl(self, *args, **kwargs):
"""Default termination method by testing the fitness, generation, and tolerance goals.""" """Default termination method by testing the fitness, generation, and tolerance goals."""
return Termination_Methods.fitness_generation_tolerance(self, *args, **kwargs) return Termination.fitness_generation_tolerance(self, *args, **kwargs)
#============================# #============================#