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Rewrote default GA methods format

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SimpleArt
2021-01-06 10:22:26 -05:00
parent 411e26ab7c
commit 8d90056c92
1 changed files with 51 additions and 107 deletions
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158
src/attributes.py
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@ -39,6 +39,50 @@ class Attributes:
been set then they will fall back onto the default attribute. All been set then they will fall back onto the default attribute. All
attributes have been catigorized to explain sections in the ga process.""" attributes have been catigorized to explain sections in the ga process."""
#=====================#
# Default GA methods: #
#=====================#
# Default EasyGA implimentation structure
fitness_function_impl = Fitness_Examples.is_it_5
make_population = make_population
make_chromosome = make_chromosome
make_gene = make_gene
# Methods for accomplishing Parent-Selection -> Crossover -> Survivor_Selection -> Mutation -> Termination
parent_selection_impl = Parent.Rank.tournament
crossover_individual_impl = Crossover.Individual.single_point
crossover_population_impl = Crossover.Population.sequential
survivor_selection_impl = Survivor.fill_in_best
mutation_individual_impl = Mutation.Individual.individual_genes
mutation_population_impl = Mutation.Population.random_avoid_best
termination_impl = Termination.fitness_generation_tolerance
def dist(self, chromosome_1, chromosome_2):
"""Default distance lambda. Returns the square root of the difference in fitnesses."""
return math.sqrt(abs(chromosome_1.fitness - chromosome_2.fitness))
def weighted_random(self, weight):
"""Returns a random value between 0 and 1. Returns values between the weight and the
nearest of 0 and 1 less frequently than between weight and the farthest of 0 and 1."""
rand_num = random.random()
if rand_num < weight:
return (1-weight) * rand_num / weight
else:
return 1 - weight * (1-rand_num) / (1-weight)
def gene_impl(self, *args, **kwargs):
"""Default gene implementation. Returns a random integer from 1 to 10."""
return random.randint(1, 10)
chromosome_impl = None
#=====================================# #=====================================#
# Special built-in class __methods__: # # Special built-in class __methods__: #
#=====================================# #=====================================#
@ -52,8 +96,6 @@ class Attributes:
chromosome_length = 10, chromosome_length = 10,
population_size = 10, population_size = 10,
chromosome_impl = None,
gene_impl = None,
population = None, population = None,
target_fitness_type = 'max', target_fitness_type = 'max',
update_fitness = False, update_fitness = False,
@ -84,22 +126,6 @@ class Attributes:
max_gene_mutation_rate = 0.15, max_gene_mutation_rate = 0.15,
min_gene_mutation_rate = 0.01, min_gene_mutation_rate = 0.01,
dist = None,
fitness_function_impl = None,
make_population = make_population,
make_chromosome = make_chromosome,
make_gene = make_gene,
parent_selection_impl = None,
crossover_individual_impl = None,
crossover_population_impl = None,
survivor_selection_impl = None,
mutation_individual_impl = None,
mutation_population_impl = None,
termination_impl = None,
Database = sql_database.SQL_Database, Database = sql_database.SQL_Database,
database_name = 'database.db', database_name = 'database.db',
sql_create_data_structure = """CREATE TABLE IF NOT EXISTS data ( sql_create_data_structure = """CREATE TABLE IF NOT EXISTS data (
@ -110,7 +136,9 @@ class Attributes:
chromosome TEXT chromosome TEXT
); """, ); """,
Graph = matplotlib_graph.Matplotlib_Graph Graph = matplotlib_graph.Matplotlib_Graph,
**kwargs
): ):
# Keep track of the current run # Keep track of the current run
@ -119,8 +147,6 @@ class Attributes:
# Initilization variables # Initilization variables
self.chromosome_length = chromosome_length self.chromosome_length = chromosome_length
self.population_size = population_size self.population_size = population_size
self.chromosome_impl = chromosome_impl
self.gene_impl = gene_impl
self.population = population self.population = population
self.target_fitness_type = target_fitness_type self.target_fitness_type = target_fitness_type
self.update_fitness = update_fitness self.update_fitness = update_fitness
@ -155,26 +181,6 @@ class Attributes:
self.max_gene_mutation_rate = max_gene_mutation_rate self.max_gene_mutation_rate = max_gene_mutation_rate
self.min_gene_mutation_rate = min_gene_mutation_rate self.min_gene_mutation_rate = min_gene_mutation_rate
# Distance between two chromosomes
self.dist = dist
# Default EasyGA implimentation structure
self.fitness_function_impl = fitness_function_impl
self.make_population = make_population
self.make_chromosome = make_chromosome
self.make_gene = make_gene
# Methods for accomplishing Parent-Selection -> Crossover -> Survivor_Selection -> Mutation
self.parent_selection_impl = parent_selection_impl
self.crossover_individual_impl = crossover_individual_impl
self.crossover_population_impl = crossover_population_impl
self.survivor_selection_impl = survivor_selection_impl
self.mutation_individual_impl = mutation_individual_impl
self.mutation_population_impl = mutation_population_impl
# The type of termination to impliment
self.termination_impl = termination_impl
# Database varibles # Database varibles
self.database = Database() self.database = Database()
self.database_name = database_name self.database_name = database_name
@ -183,6 +189,10 @@ class Attributes:
# Graphing variables # Graphing variables
self.graph = Graph(self.database) self.graph = Graph(self.database)
# Any other custom kwargs?
for name, value in kwargs.items():
self.__setattr__(name, value)
def __setattr__(self, name, value): def __setattr__(self, name, value):
"""Custom setter for using """Custom setter for using
@ -214,72 +224,6 @@ class Attributes:
self.__dict__[name] = value self.__dict__[name] = value
#===========================#
# Default built-in methods: #
#===========================#
def weighted_random(self, weight):
"""Returns a random value between 0 and 1. Returns values between the weight and the
nearest of 0 and 1 less frequently than between weight and the farthest of 0 and 1.
"""
rand_num = random.random()
if rand_num < weight:
return (1-weight) * rand_num / weight
else:
return 1 - weight * (1-rand_num) / (1-weight)
def dist(self, chromosome_1, chromosome_2):
"""Default distance lambda. Returns the square root of the difference in fitnesses."""
return math.sqrt(abs(chromosome_1.fitness - chromosome_2.fitness))
def gene_impl(self, *args, **kwargs):
"""Default gene implementation. Returns a random integer from 1 to 10."""
return random.randint(1, 10)
def fitness_function_impl(self, *args, **kwargs):
"""Default fitness function. Returns the number of genes that are 5."""
return Fitness_Examples.is_it_5(*args, **kwargs)
def parent_selection_impl(self, *args, **kwargs):
"""Default parent selection method using tournament selection."""
return Parent.Rank.tournament(self, *args, **kwargs)
def crossover_individual_impl(self, *args, **kwargs):
"""Default individual crossover method using single point crossover."""
return Crossover.Individual.single_point(self, *args, **kwargs)
def crossover_population_impl(self, *args, **kwargs):
"""Default population crossover method using sequential selection."""
return Crossover.Population.sequential(self, *args, **kwargs)
def survivor_selection_impl(self, *args, **kwargs):
"""Default survivor selection method using the fill in best method."""
return Survivor.fill_in_best(self, *args, **kwargs)
def mutation_individual_impl(self, *args, **kwargs):
"""Default individual mutation method by randomizing individual genes."""
return Mutation.Individual.individual_genes(self, *args, **kwargs)
def mutation_population_impl(self, *args, **kwargs):
"""Default population mutation method selects chromosomes randomly while avoiding the best."""
return Mutation.Population.random_avoid_best(self, *args, **kwargs)
def termination_impl(self, *args, **kwargs):
"""Default termination method by testing the fitness, generation, and tolerance goals."""
return Termination.fitness_generation_tolerance(self, *args, **kwargs)
#============================# #============================#
# Built-in database methods: # # Built-in database methods: #
#============================# #============================#