def test_be_born(self):
num_features = 10
max_individual_size = 5
values_handler = Values_Handler(Probability_Handler(num_features))
factory = Individual(num_features=num_features,
max_individual_size=max_individual_size,
values_handler=values_handler)
dna_dict = factory.be_born()
size_individual = dna_dict[constants.DNA_SIZE_STR]
self.assertTrue(1 <= size_individual <= max_individual_size)
size_indices = len(dna_dict[constants.DNA_FEATURES_STR])
self.assertTrue(1 <= size_indices <= max_individual_size)
self.assertTrue(np.all(0 <= np.array(size_indices) <= num_features))
size_tree_values = len(dna_dict[constants.DNA_WEIGHTS_STR])
self.assertTrue(1 <= size_tree_values <= max_individual_size)
self.assertTrue(0 <= np.min(dna_dict[constants.DNA_WEIGHTS_STR]))
self.assertTrue(np.max(dna_dict[constants.DNA_WEIGHTS_STR]) <= 1)
size_parentheses_binary_vec = len(
dna_dict[constants.DNA_PARENTHESES_STR])
self.assertTrue(
1 <= size_parentheses_binary_vec <= max_individual_size)
self.assertTrue(
np.all(0 <= np.array(dna_dict[constants.DNA_PARENTHESES_STR])))
self.assertTrue(
np.all(np.array(dna_dict[constants.DNA_PARENTHESES_STR]) <= 1))
size_action_vector = len(dna_dict[constants.DNA_ACTIONS_STR])
self.assertTrue(1 <= size_action_vector <= max_individual_size)
self.assertTrue(
np.all(0 <= np.array(dna_dict[constants.DNA_ACTIONS_STR])))
self.assertTrue(
np.all(
np.array(dna_dict[constants.DNA_ACTIONS_STR]) <
constants.MAX_SIZE_INDIVIDUAL))
class Population_Handler():
def __init__(self, probability_handler, max_individual_size = 10):
self.probability_handler = probability_handler
self.max_individual_size = max_individual_size
self.population = []
self.values_handler = Values_Handler(probability_handler)
self.individual = Individual(self.probability_handler.max_feature_number, self.max_individual_size, self.values_handler)
self.mh = Mutation_Handler(self.probability_handler, self.values_handler)
def create_individual(self):
return self.individual.be_born()
def create_population(self, population_size = 10):
self.population = np.empty([population_size]).astype(object)
for i in range(population_size):
self.population[i] = self.create_individual()
def mutate_population(self):
for individual in self.population[1:]: ## dont mutate the top best
self.mh.mutate(individual)
def mutate_population_paralal(self):
p = Pool(constants.NUM_POOL)
paralal_input = list(self.population)
paralal_result = p.map(self.mh.mutate_paralal, paralal_input)
p.close()
p.join()
self.population = np.array(paralal_result)
def cross_over_population(self):
pass
def get_population(self):
return self.population
def set_population(self, new_generation):
self.population = new_generation
