def test_population_size_after_crossover_net12_2(self): list_of_demands = get_demands_from_file(net12_2_string_demands) first_population = generate_first_population(list_of_demands) first_population_length = len(first_population) new_population = crossover_chromosomes(first_population, 1) if len(first_population) % 2 == 0: self.assertEqual(first_population_length * 2, len(new_population)) else: self.assertEqual(first_population_length * 2 - 1, len(new_population))
# List for holdings Link objects, get Link objects from txt string list_of_links = Parser.get_links_list_from_file(net_string_links) # print(Parser.get_number_of_links(net_string_links)) # print(Parser.get_number_of_demands(net_string_demands)) list_of_demands = Parser.get_demands_from_file(net_string_demands) # for x in range(0, len(list_of_links)): # list_of_links[x].print_link_properties() # for y in range(0, len(list_of_demands)): # list_of_demands[y].print_demand_properties() first_population = generate_first_population(list_of_demands, initial_population_size) current_population = first_population calculate_fitness(list_of_links, list_of_demands, current_population) for item in first_population: print('Genes of current chromosome') for gene in item.list_of_genes: print(gene.list_of_alleles) print("DAP:" + str(item.fitness_dap)) print("DDAP:" + str(item.fitness_ddap)) while check_if_stop(): start = time.time() old_ddap = current_population[0].fitness_ddap old_dap = current_population[0].fitness_dap
def test_demand_volumes_on_chromosome_list_of_genes_net12_2(self): list_of_demands = get_demands_from_file(net12_2_string_demands) first_population = generate_first_population(list_of_demands) for chromosome in first_population: for gene in chromosome.list_of_genes: self.assertEqual(gene.demand_volume, sum(gene.list_of_alleles))