Structure change to make it easier for users to clone and use the repository.

mutation/Mutation.py

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+import random
+from math import ceil
+
+# Import all mutation decorators
+from decorators import _check_chromosome_mutation_rate, _check_gene_mutation_rate, _reset_fitness, _loop_random_mutations
+
+
+class Population:
+    """Methods for selecting chromosomes to mutate"""
+
+    @_check_chromosome_mutation_rate
+    def random_selection(ga):
+        """Selects random chromosomes."""
+
+        sample_space = range(len(ga.population))
+        sample_size  = ceil(len(ga.population)*ga.chromosome_mutation_rate)
+
+        # Loop the individual method until enough genes are mutated.
+        for index in random.sample(sample_space, sample_size):
+            ga.mutation_individual_impl(ga.population[index])
+
+
+    @_check_chromosome_mutation_rate
+    def random_avoid_best(ga):
+        """Selects random chromosomes while avoiding the best chromosomes. (Elitism)"""
+
+        sample_space = range(ceil(ga.percent_converged*len(ga.population)*3/16), len(ga.population))
+        sample_size  = ceil(ga.chromosome_mutation_rate*len(ga.population))
+
+        for index in random.sample(sample_space, sample_size):
+            ga.mutation_individual_impl(ga.population[index])
+
+
+    @_check_chromosome_mutation_rate
+    def best_replace_worst(ga):
+        """Selects the best chromosomes, copies them, and replaces the worst chromosomes."""
+
+        mutation_amount = ceil(ga.chromosome_mutation_rate*len(ga.population))
+
+        for i in range(mutation_amount):
+            ga.population[-i-1] = ga.make_chromosome(ga.population[i])
+            ga.mutation_individual_impl(ga.population[-i-1])
+
+
+class Individual:
+    """Methods for mutating a single chromosome."""
+
+    @_check_gene_mutation_rate
+    @_reset_fitness
+    @_loop_random_mutations
+    def individual_genes(ga, chromosome, index):
+        """Mutates random genes by making completely new genes."""
+
+        # Using the chromosome_impl
+        if ga.chromosome_impl is not None:
+            chromosome[index] = ga.make_gene(ga.chromosome_impl()[index])
+
+        # Using the gene_impl
+        elif ga.gene_impl is not None:
+            chromosome[index] = ga.make_gene(ga.gene_impl())
+
+        # Exit because no gene creation method specified
+        else:
+            raise Exception("Did not specify any initialization constraints.")
+
+
+    class Arithmetic:
+        """Methods for mutating a chromosome by numerically modifying the genes."""
+
+        @_check_gene_mutation_rate
+        @_reset_fitness
+        @_loop_random_mutations
+        def average(ga, chromosome, index):
+            """Mutates random genes by making completely new genes
+            and then averaging them with the old genes. May cause
+            premature convergence. Weight is the reciprocal of the
+            number of generations run."""
+
+            weight = 1/max(1, ga.current_generation)
+
+            # Using the chromosome_impl
+            if ga.chromosome_impl is not None:
+                new_value = ga.chromosome_impl()[index]
+
+            # Using the gene_impl
+            elif ga.gene_impl is not None:
+                new_value = ga.gene_impl()
+
+            # Exit because no gene creation method specified
+            else:
+                raise Exception("Did not specify any initialization constraints.")
+
+            chromosome[index] = ga.make_gene((1-weight)*chromosome[index].value + weight*new_value)
+
+
+        @_check_gene_mutation_rate
+        @_reset_fitness
+        @_loop_random_mutations
+        def reflect_genes(ga, chromosome, index):
+            """Reflects genes against the best chromosome.
+            Requires large genetic variety to work well but
+            when it does it may be very fast."""
+
+            difference = ga.population[0][index].value - chromosome[index].value
+            value = ga.population[0][index].value + 2*difference
+            chromosome[index] = ga.make_gene(value)
+
+
+    class Permutation:
+        """Methods for mutating a chromosome by changing the order of the genes."""
+
+        @_check_gene_mutation_rate
+        @_reset_fitness
+        @_loop_random_mutations
+        def swap_genes(ga, chromosome, index):
+            """Swaps two random genes in the chromosome."""
+
+            # Indexes of genes to swap
+            index_one = index
+            index_two = random.randrange(len(chromosome))
+
+            # Swap genes
+            chromosome[index_one], chromosome[index_two] = chromosome[index_two], chromosome[index_one]
+
+
+        @_check_gene_mutation_rate
+        @_reset_fitness
+        def swap_segments(ga, chromosome):
+            """Splits the chromosome into 3 segments and shuffle them."""
+
+            # Chromosome too short to mutate
+            if len(chromosome) < 3:
+                return
+
+            # Indexes to split the chromosome
+            index_two = random.randrange(2, len(chromosome))
+            index_one = random.randrange(1, index_two)
+
+            # Extract segments and shuffle them
+            segments = [chromosome[:index_one], chromosome[index_one:index_two], chromosome[index_two:]]
+            random.shuffle(segments)
+
+            # Put segments back together
+            chromosome.gene_list = segments[0] + segments[1] + segments[2]

mutation/README.md

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+# Mutation functions