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))