Changed __setattr__ for clean inheritance approach
No longer necessary to prepend built-in method names with _ when defining bound class methods
This commit is contained in:
SimpleArt
@ -31,24 +31,18 @@ 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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#=====================================#
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# Special built-in class __methods__: #
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#=====================================#
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def __init__(
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self,
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*,
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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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@ -168,6 +162,96 @@ class Attributes:
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self.graph = Graph(self.database)
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def __setattr__(self, name, value):
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"""Custom setter for using
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self.name = value
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which follows the following guidelines:
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- if self.name is a property, the specific property setter is used
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- else if value is callable, self is passed in as the first parameter
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- else if value is not None or self.name is not set, assign it like normal
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"""
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# Check for property
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if hasattr(type(self), name) \
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and isinstance((prop := getattr(type(self), name)), property):
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if name == 'dist': print("property")
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prop.fset(self, value)
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# Check for function
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elif callable(value):
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foo = lambda *args, **kwargs: value(self, *args, **kwargs)
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# Reassign name and doc-string for documentation
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foo.__name__ = value.__name__
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foo.__doc__ = value.__doc__
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self.__dict__[name] = foo
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# Assign like normal unless None or undefined self.name
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elif value is not None or not hasattr(self, name):
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self.__dict__[name] = value
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#===========================#
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# Default built-in methods: #
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#===========================#
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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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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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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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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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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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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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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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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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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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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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#============================#
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# Built-in database methods: #
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#============================#
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def save_population(self):
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"""Saves the current population to the database."""
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self.database.insert_current_population(self)
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@ -178,6 +262,11 @@ class Attributes:
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self.database.insert_current_chromosome(self.current_generation, chromosome)
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#===================#
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# Built-in options: #
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#===================#
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def numeric_chromosomes(self):
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"""Sets default numerical based methods"""
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@ -191,7 +280,7 @@ class Attributes:
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self.mutation_individual_impl = Mutation_Methods.Individual.Arithmetic.average
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# Euclidean norm
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self.dist = lambda chromosome_1, chromosome_2:\
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self.dist = lambda self, chromosome_1, chromosome_2:\
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sqrt(sum(
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(gene_1.value - gene_2.value) ** 2
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for gene_1, gene_2
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@ -208,7 +297,7 @@ class Attributes:
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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 don't have in common
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def dist(chromosome_1, chromosome_2):
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def dist(self, chromosome_1, chromosome_2):
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# Used to set values during comprehension
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set_value = lambda arg: True
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@ -234,224 +323,69 @@ class Attributes:
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self.dist = dist
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# Getter and setters for all required varibles
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#===========================#
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# Getter/setter properties: #
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#===========================#
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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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def make_population(self):
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"""Getter function for making populations."""
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return self._make_population
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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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@make_population.setter
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def make_population(self, method):
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"""Setter function for making populations."""
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self.__dict__['_make_population'] = method
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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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def make_chromosome(self):
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"""Getter function for making chromosomes."""
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return self._make_chromosome
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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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@make_chromosome.setter
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def make_chromosome(self, method):
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"""Setter function for making chromosomes."""
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self.__dict__['_make_chromosome'] = method
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@property
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def make_gene(self):
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"""Getter function for making genes."""
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return self._make_gene
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@make_gene.setter
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def make_gene(self, method):
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"""Setter function for making genes."""
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self.__dict__['_make_gene'] = method
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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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"""Getter function for making randomized genes."""
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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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"""Setter function for making randomized genes."""
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self.__dict__['_gene_impl'] = method
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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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def chromosome_impl(self):
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"""Getter function for making randomized chromosomes."""
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return self._chromosome_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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@chromosome_impl.setter
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def chromosome_impl(self, method):
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"""Setter function for making randomized chromosomes."""
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self.__dict__['_chromosome_impl'] = method
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@property
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