"""
Gathers (via the reporting interface) and provides (to callers and/or a file)
the most-fit genomes and information on genome/species fitness and species sizes.
"""
import copy
import csv
from neat.math_util import mean, stdev, median2
from neat.reporting import BaseReporter
# TODO: Make a version of this reporter that doesn't continually increase memory usage.
# (Maybe periodically write blocks of history to disk, or log stats in a database?)
[docs]class StatisticsReporter(BaseReporter):
"""
Gathers (via the reporting interface) and provides (to callers and/or a file)
the most-fit genomes and information on genome/species fitness and species sizes.
"""
def __init__(self):
BaseReporter.__init__(self)
self.most_fit_genomes = []
self.generation_statistics = []
[docs] def post_evaluate(self, config, population, species, best_genome):
self.most_fit_genomes.append(copy.deepcopy(best_genome))
# Store the fitnesses of the members of each currently active species.
species_stats = {}
for sid, s in species.species.items():
species_stats[sid] = dict((k, v.fitness) for k, v in s.members.items())
self.generation_statistics.append(species_stats)
[docs] def get_fitness_stat(self, f):
stat = []
for stats in self.generation_statistics:
scores = []
for species_stats in stats.values():
scores.extend(species_stats.values())
stat.append(f(scores))
return stat
[docs] def get_fitness_mean(self):
"""Get the per-generation mean fitness."""
return self.get_fitness_stat(mean)
[docs] def get_fitness_stdev(self):
"""Get the per-generation standard deviation of the fitness."""
return self.get_fitness_stat(stdev)
[docs] def best_unique_genomes(self, n):
"""Returns the most n fit genomes, with no duplication."""
best_unique = {}
for g in self.most_fit_genomes:
best_unique[g.key] = g
best_unique_list = list(best_unique.values())
def key(genome):
return genome.fitness
return sorted(best_unique_list, key=key, reverse=True)[:n]
[docs] def best_genomes(self, n):
"""Returns the n most fit genomes ever seen."""
def key(g):
return g.fitness
return sorted(self.most_fit_genomes, key=key, reverse=True)[:n]
[docs] def best_genome(self):
"""Returns the most fit genome ever seen."""
return self.best_genomes(1)[0]
[docs] def save(self):
self.save_genome_fitness()
self.save_species_count()
self.save_species_fitness()
[docs] def save_genome_fitness(self,
delimiter=' ',
filename='fitness_history.csv'):
""" Saves the population's best and average fitness. """
with open(filename, 'w') as f:
w = csv.writer(f, delimiter=delimiter)
best_fitness = [c.fitness for c in self.most_fit_genomes]
avg_fitness = self.get_fitness_mean()
for best, avg in zip(best_fitness, avg_fitness):
w.writerow([best, avg])
[docs] def save_species_count(self, delimiter=' ', filename='speciation.csv'):
""" Log speciation throughout evolution. """
with open(filename, 'w') as f:
w = csv.writer(f, delimiter=delimiter)
for s in self.get_species_sizes():
w.writerow(s)
[docs] def save_species_fitness(self, delimiter=' ', null_value='NA', filename='species_fitness.csv'):
""" Log species' average fitness throughout evolution. """
with open(filename, 'w') as f:
w = csv.writer(f, delimiter=delimiter)
for s in self.get_species_fitness(null_value):
w.writerow(s)
[docs] def get_species_sizes(self):
all_species = set()
for gen_data in self.generation_statistics:
all_species = all_species.union(gen_data.keys())
max_species = max(all_species)
species_counts = []
for gen_data in self.generation_statistics:
species = [len(gen_data.get(sid, [])) for sid in range(1, max_species + 1)]
species_counts.append(species)
return species_counts
[docs] def get_species_fitness(self, null_value=''):
all_species = set()
for gen_data in self.generation_statistics:
all_species = all_species.union(gen_data.keys())
max_species = max(all_species)
species_fitness = []
for gen_data in self.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