def report():
print "\nNumber of runs: {0!s}\n".format(sys.argv[2])
print "\t Gen. \t Nodes \t Conn. \t Evals. \t Score \n"
print "average {0:3.2f} \t {1:2.2f} \t {2:2.2f} \t {3:2.2f} \t {4:2.2f}".format(
mean(total_gens), mean(total_nodes), mean(total_conns),
mean(total_evals), mean(total_score))
print "stdev {0:3.2f} \t {1:2.2f} \t {2:2.2f} \t {3:2.2f} \t {4:2.2f}".format(
stdev(total_gens), stdev(total_nodes), stdev(total_conns),
stdev(total_evals), stdev(total_score))
def get_average_fitness(self):
"""Get the per-generation average fitness."""
avg_fitness = []
for stats in self.generation_statistics:
scores = []
for fitness in stats.values():
scores.extend(fitness)
avg_fitness.append(mean(scores))
return avg_fitness
def post_evaluate(self, population, species, best):
fit_mean = mean([c.fitness for c in population])
fit_std = stdev([c.fitness for c in population])
print('Population\'s average fitness: {0:3.5f} stdev: {1:3.5f}'.format(fit_mean, fit_std))
print('Best fitness: {0:3.5f} - size: {1!r} - species {2} - id {3}'.format(best.fitness, best.size(),
best.species_id, best.ID))
print('Species length: {0:d} totaling {1:d} individuals'.format(len(species), sum(
[len(s.members) for s in species])))
print('Species ID : {0!s}'.format([s.ID for s in species]))
print('Species size : {0!s}'.format([len(s.members) for s in species]))
print('Species age : {0}'.format([s.age for s in species]))
def get_species_fitness(population, null_value=''):
all_species = set()
for gen_data in population.generation_statistics:
all_species = all_species.union(gen_data.keys())
max_species = max(all_species)
species_fitness = []
for gen_data in population.generation_statistics:
member_fitness = [gen_data.get(sid, []) for sid in range(1, max_species + 1)]
fitness = []
for mf in member_fitness:
if mf:
fitness.append(mean(mf))
else:
fitness.append(null_value)
species_fitness.append(fitness)
return species_fitness
def get_species_fitness(population, null_value=''):
all_species = set()
for gen_data in population.generation_statistics:
all_species = all_species.union(gen_data.keys())
max_species = max(all_species)
species_fitness = []
for gen_data in population.generation_statistics:
member_fitness = [
gen_data.get(sid, []) for sid in range(1, max_species + 1)
]
fitness = []
for mf in member_fitness:
if mf:
fitness.append(mean(mf))
else:
fitness.append(null_value)
species_fitness.append(fitness)
return species_fitness
def report():
print "\nNumber of runs: {0!s}\n".format(sys.argv[2])
print "\t Gen. \t Nodes \t Conn. \t Evals. \t Score \n"
print "average {0:3.2f} \t {1:2.2f} \t {2:2.2f} \t {3:2.2f} \t {4:2.2f}".format(mean(total_gens), mean(total_nodes), mean(total_conns), mean(total_evals), mean(total_score))
print "stdev {0:3.2f} \t {1:2.2f} \t {2:2.2f} \t {3:2.2f} \t {4:2.2f}".format(stdev(total_gens), stdev(total_nodes), stdev(total_conns), stdev(total_evals), stdev(total_score))
def species_mean_fitness(species):
return mean([m.fitness for m in species.members])
def species_mean_fitness(species):
return mean([m.fitness for m in species.members])