Now supporting method overriding instead of attribute setting
This commit is contained in:
SimpleArt
@ -31,16 +31,28 @@ from database import matplotlib_graph
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import matplotlib.pyplot as plt
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def function_info(setter):
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"""Decorator for setter functions involving functions so that the name and doc-string are kept."""
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def new_setter(obj, method):
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if (new_method := setter(obj, method)) is not None:
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new_method.__name__ = method.__name__
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new_method.__doc__ = method.__doc__
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return new_setter
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class Attributes:
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"""Default GA attributes can be found here. If any attributes have not
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been set then they will fall back onto the default attribute. All
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attributes have been catigorized to explain sections in the ga process."""
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def __init__(self,
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def __init__(
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self,
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chromosome_length = 10,
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population_size = 10,
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chromosome_impl = None,
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gene_impl = lambda: random.randint(1, 10),
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gene_impl = None,
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population = None,
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target_fitness_type = 'max',
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update_fitness = False,
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@ -65,17 +77,17 @@ class Attributes:
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max_gene_mutation_rate = 0.15,
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min_gene_mutation_rate = 0.01,
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dist = None,
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fitness_function_impl = Fitness_Examples.is_it_5,
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fitness_function_impl = None,
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make_population = make_population,
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make_chromosome = make_chromosome,
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make_gene = make_gene,
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parent_selection_impl = Parent_Selection.Rank.tournament,
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crossover_individual_impl = Crossover_Methods.Individual.single_point,
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crossover_population_impl = Crossover_Methods.Population.sequential_selection,
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survivor_selection_impl = Survivor_Selection.fill_in_best,
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mutation_individual_impl = Mutation_Methods.Individual.individual_genes,
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mutation_population_impl = Mutation_Methods.Population.random_avoid_best,
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termination_impl = Termination_Methods.fitness_generation_tolerance,
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parent_selection_impl = None,
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crossover_individual_impl = None,
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crossover_population_impl = None,
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survivor_selection_impl = None,
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mutation_individual_impl = None,
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mutation_population_impl = None,
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termination_impl = None,
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Database = sql_database.SQL_Database,
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database_name = 'database.db',
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sql_create_data_structure = """CREATE TABLE IF NOT EXISTS data (
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@ -187,37 +199,264 @@ class Attributes:
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))
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def permutation_chromosomes(self):
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def permutation_chromosomes(self, cycle = True):
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"""Sets default permutation based methods"""
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cycle = int(cycle)
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self.crossover_individual_impl = Crossover_Methods.Individual.Permutation.ox1
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self.mutation_individual_impl = Mutation_Methods.Individual.Permutation.swap_genes
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self.mutation_individual_impl = Mutation_Methods.Individual.Permutation.swap_genes
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# Count the number of gene pairs they have in common
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# Count the number of gene pairs they don't have in common
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def dist(chromosome_1, chromosome_2):
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gene_list_1 = list(chromosome_1)
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gene_list_2 = list(chromosome_2)
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count = 0
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# Used to set values during comprehension
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set_value = lambda arg: True
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for i in range(len(gene_list_1)-1):
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for j in range(len(gene_list_2)-1):
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if gene_list_1[i] == gene_list_2[j]:
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if gene_list_1[i+1] == gene_list_2[j+1]:
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count += 1
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break
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# Index of gene from chromosome 1 in chromosome 2
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j = 0
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return count
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return sum(
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# Add 1 if they are different
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int(chromosome_1[i-1] != chromosome_2[j-1])
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# Loop over chromosome 1
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for i
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in range(1-cycle, len(chromosome_1))
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# Find index of gene from chromosome 1 in chromosome 2
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if set_value(j := chromosome_2.index_of(chromosome_1[i]))
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# Additional case to check
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if j + cycle > 0
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)
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self.dist = dist
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# Getter and setters for all required varibles
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@property
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def dist(self):
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"""Getter for distance lambda which passes a reference of self in."""
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return self._dist
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@dist.setter
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@function_info
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def dist(self, method):
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"""Setter for distance lambda."""
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if method is not None:
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self._dist = lambda *args, **kwargs: method(self, *args, **kwargs)
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return self._dist
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def _dist(self, chromosome_1, chromosome_2):
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"""Default distance lambda. Returns the square root of the difference in fitnesses."""
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return sqrt(abs(chromosome_1.fitness - chromosome_2.fitness))
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@property
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def chromosome_impl(self):
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"""Getter for chromosome implementation lambda which passes a reference of self in."""
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return self._chromosome_impl
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@chromosome_impl.setter
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@function_info
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def chromosome_impl(self, method):
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"""Setter for chromosome implementation lambda."""
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if method is not None:
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self._chromosome_impl = lambda *args, **kwargs: method(*args, **kwargs)
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return self._chromosome_impl
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@property
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def gene_impl(self):
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"""Getter for gene implementation lambda which passes a reference of self in."""
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return self._gene_impl
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@gene_impl.setter
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@function_info
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def gene_impl(self, method):
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"""Setter for gene implementation lambda."""
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if method is not None:
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self._gene_impl = lambda *args, **kwargs: method(*args, **kwargs)
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return self._gene_impl
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def _gene_impl(self, *args, **kwargs):
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"""Default gene implementation. Returns a random integer from 1 to 10."""
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return random.randint(1, 10)
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@property
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def fitness_function_impl(self):
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"""Getter for fitness function lambda which passes a reference of self in."""
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return self._fitness_function_impl
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@fitness_function_impl.setter
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@function_info
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def fitness_function_impl(self, method):
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"""Setter for fitness function lambda."""
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if method is not None:
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self._fitness_function_impl = lambda *args, **kwargs: method(self, *args, **kwargs)
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return self._fitness_function_impl
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def _fitness_function_impl(self, *args, **kwargs):
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"""Default fitness function. Returns the number of genes that are 5."""
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return Fitness_Examples.is_it_5(*args, **kwargs)
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@property
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def parent_selection_impl(self):
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"""Getter for parent selection lambda which passes a reference of self in."""
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return self._parent_selection_impl
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@parent_selection_impl.setter
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@function_info
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def parent_selection_impl(self, method):
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"""Setter for parent selection lambda."""
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if method is not None:
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self._parent_selection_impl = lambda *args, **kwargs: method(self, *args, **kwargs)
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return self._parent_selection_impl
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def _parent_selection_impl(self, *args, **kwargs):
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"""Default parent selection method using tournament selection."""
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return Parent_Selection.Rank.tournament(self, *args, **kwargs)
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@property
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def crossover_individual_impl(self):
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"""Getter for individual crossover lambda which passes a reference of self in."""
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return self._crossover_individual_impl
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@crossover_individual_impl.setter
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@function_info
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def crossover_individual_impl(self, method):
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"""Setter for individual crossover lambda."""
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if method is not None:
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self._crossover_individual_impl = lambda *args, **kwargs: method(self, *args, **kwargs)
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return self._crossover_individual_impl
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def _crossover_individual_impl(self, *args, **kwargs):
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"""Default individual crossover method using single point crossover."""
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return Crossover_Methods.Individual.single_point(self, *args, **kwargs)
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@property
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def crossover_population_impl(self):
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"""Getter for population crossover lambda which passes a reference of self in."""
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return self._crossover_population_impl
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@crossover_population_impl.setter
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@function_info
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def crossover_population_impl(self, method):
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"""Setter for population crossover lambda."""
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if method is not None:
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self._crossover_population_impl = lambda *args, **kwargs: method(self, *args, **kwargs)
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return self._crossover_population_impl
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def _crossover_population_impl(self, *args, **kwargs):
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"""Default population crossover method using sequential selection."""
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return Crossover_Methods.Population.sequential_selection(self, *args, **kwargs)
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@property
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def survivor_selection_impl(self):
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"""Getter for survivor selection lambda which passes a reference of self in."""
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return self._survivor_selection_impl
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@survivor_selection_impl.setter
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@function_info
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def survivor_selection_impl(self, method):
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"""Setter for survivor selection lambda."""
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if method is not None:
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self._survivor_selection_impl = lambda *args, **kwargs: method(self, *args, **kwargs)
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return self._survivor_selection_impl
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def _survivor_selection_impl(self, *args, **kwargs):
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"""Default survivor selection method using the fill in best method."""
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return Survivor_Selection.fill_in_best(self, *args, **kwargs)
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@property
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def mutation_individual_impl(self):
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"""Getter for individual mutation lambda which passes a reference of self in."""
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return self._mutation_individual_impl
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@mutation_individual_impl.setter
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@function_info
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def mutation_individual_impl(self, method):
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"""Setter for individual mutation lambda."""
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if method is not None:
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self._mutation_individual_impl = lambda *args, **kwargs: method(self, *args, **kwargs)
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return self._mutation_individual_impl
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def _mutation_individual_impl(self, *args, **kwargs):
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"""Default individual mutation method by randomizing individual genes."""
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return Mutation_Methods.Individual.individual_genes(self, *args, **kwargs)
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@property
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def mutation_population_impl(self):
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"""Getter for population mutation lambda which passes a reference of self in."""
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return self._mutation_population_impl
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@mutation_population_impl.setter
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@function_info
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def mutation_population_impl(self, method):
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"""Setter for population mutation lambda."""
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if method is not None:
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self._mutation_population_impl = lambda *args, **kwargs: method(self, *args, **kwargs)
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return self._mutation_population_impl
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def _mutation_population_impl(self, *args, **kwargs):
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"""Default population mutation method selects chromosomes randomly while avoiding the best."""
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return Mutation_Methods.Population.random_avoid_best(self, *args, **kwargs)
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@property
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def termination_impl(self):
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"""Getter for termination lambda which passes a reference of self in."""
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return self._termination_impl
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@termination_impl.setter
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@function_info
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def termination_impl(self, method):
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"""Setter for termination lambda."""
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if method is not None:
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self._termination_impl = lambda *args, **kwargs: method(self, *args, **kwargs)
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return self._termination_impl
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def _termination_impl(self, *args, **kwargs):
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"""Default termination method by testing the fitness, generation, and tolerance goals."""
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return Termination_Methods.fitness_generation_tolerance(self, *args, **kwargs)
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@property
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def chromosome_length(self):
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"""Getter function for chromosome length"""
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return self._chromosome_length
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@ -312,27 +551,6 @@ class Attributes:
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raise ValueError("Min chromosome mutation rate must be between 0 and 1")
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@property
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def dist(self):
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"""Getter function for the distance between chromosomes."""
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return self._dist
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@dist.setter
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def dist(self, value_input):
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"""Setter function for the distance between chromosomes."""
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# Default value by comparing fitnesses of chromosomes
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if value_input is None:
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self._dist = lambda chromosome_1, chromosome_2:\
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sqrt(abs(chromosome_1.fitness - chromosome_2.fitness))
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# Given input
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else:
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self._dist = value_input
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@property
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def database_name(self):
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"""Getter function for the database name"""
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