def test_evolve():
test_values = [random.random() for _ in range(10)]
def evaluate_genome(genomes):
for g in genomes:
net = ctrnn.create_phenotype(g)
fitness = 0.0
for t in test_values:
net.reset()
output = net.serial_activate([t])
expected = t ** 2
error = output[0] - expected
fitness -= error ** 2
g.fitness = fitness
# Load the config file, which is assumed to live in
# the same directory as this script.
local_dir = os.path.dirname(__file__)
config = Config(os.path.join(local_dir, 'ctrnn_config'))
config.node_gene_type = ctrnn.CTNodeGene
config.prob_mutate_time_constant = 0.1
config.checkpoint_time_interval = 0.1
config.checkpoint_gen_interval = 1
pop = population.Population(config)
pop.run(evaluate_genome, 10)
# Save the winner.
print('Number of evaluations: {0:d}'.format(pop.total_evaluations))
winner = pop.statistics.best_genome()
with open('winner_genome', 'wb') as f:
pickle.dump(winner, f)
repr(winner)
str(winner)
for g in winner.node_genes:
repr(g)
str(g)
for g in winner.conn_genes:
repr(g)
str(g)
def main():
local_dir = os.path.dirname(__file__)
config = Config(neat.DefaultGenome, neat.DefaultReproduction,
neat.DefaultSpeciesSet, neat.DefaultStagnation,
os.path.join(local_dir, 'train_config.txt'))
config.save_best = True
config.checkpoint_time_interval = 3
pop = population.Population(config)
stats = neat.StatisticsReporter()
pop.add_reporter(stats)
pop.add_reporter(neat.StdOutReporter(True))
pop.add_reporter(neat.StatisticsReporter())
pop.add_reporter(neat.Checkpointer(2))
winner = pop.run(eval_fitness, 100)
with open('winner.pkl', 'wb') as f:
pickle.dump(winner, f)
def main():
local_dir = os.path.dirname(__file__)
config = Config(neat.DefaultGenome, neat.DefaultReproduction,
neat.DefaultSpeciesSet, neat.DefaultStagnation,
os.path.join(local_dir, 'train_config.txt'))
config.save_best = True
config.checkpoint_time_interval = 3
initial_pop = []
# initial_pop = [138, 74, 40, 84, 97, 133, 127, 60, 102, 70, 0, 1, 2]
for root, dirs, files in os.walk('best'):
for file_name in files:
with open(os.path.join('best', file_name), 'rb') as f:
initial_pop.append(pickle.load(f))
if not initial_pop:
initial_pop = None
pop = population.Population(config, initial_pop)
stats = neat.StatisticsReporter()
pop.add_reporter(stats)
pop.add_reporter(neat.Checkpointer(5))
pop.run(eval_fitness, 100)
