Added blank lines and fixed run_testing
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@ -5,7 +5,9 @@ from initialization.population_structure.population import Population
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from initialization.chromosome_structure.chromosome import Chromosome
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class Parent_Selection:
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class Tournament:
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def with_replacement(ga):
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"""
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Will make tournaments of size tournament_size and choose the winner (best fitness) from the tournament and use it as a parent for the next generation
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@ -33,7 +35,9 @@ class Parent_Selection:
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if random.uniform(0, 1) < selection_probability * pow(1-selection_probability, index):
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ga.population.mating_pool.append(tournament_group[index])
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class Roulette:
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def roulette_selection(ga):
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"""Roulette selection works based off of how strong the fitness is of the
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chromosomes in the population. The stronger the fitness the higher the probability
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@ -41,22 +45,23 @@ class Parent_Selection:
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Where the chromosomes are the numbers to be selected and the board size for
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those numbers are directly proportional to the chromosome's current fitness. Where
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the ball falls is a randomly generated number between 0 and 1"""
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total_fitness = sum(ga.population.chromosome_list[i].get_fitness() for i in range(ga.population.size()))
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rel_fitnesses = []
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for chromosome in ga.population.chromosome_list:
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if (total_fitness != 0):
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rel_fitnesses.append(float(chromosome.fitness)/total_fitness)
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probability = [sum(rel_fitnesses[:i+1]) for i in range(len(rel_fitnesses))]
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while (len(ga.population.mating_pool) < ga.population.size()*ga.parent_ratio):
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rand_number = random.random()
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# Loop through the list of probabilities
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for i in range(len(probability)):
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# If the probability is greater than the random_number, then select that chromosome
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if (probability[i] >= rand_number):
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ga.population.mating_pool.append(ga.population.chromosome_list[i])
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# print (f'Selected chromosome : {i}')
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break
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break
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