def printStatsPredators(self,pop,gen):
fits = [ind.fitness.values[0] for ind in pop]
mean = sum(fits) / len(pop)
stats.add("predator_fitness.avg",mean)
stats.add("predator_fitness.min",min(fits))
stats.add("predator_fitness.max",max(fits))
return ("(%3i): Max: %6.2f, Avg: %6.2f, Min: %5.2f" % (gen, max(fits), mean, min(fits)))
def printStatsPredators(self, pop, gen):
fits = [ind.fitness.values[0] for ind in pop]
mean = sum(fits) / len(pop)
stats.add("predator_fitness.avg", mean)
stats.add("predator_fitness.min", min(fits))
stats.add("predator_fitness.max", max(fits))
return ("(%3i): Max: %6.2f, Avg: %6.2f, Min: %5.2f" %
(gen, max(fits), mean, min(fits)))
def _record_stats(self, world):
stats.add(self._game_type(), int(world.time / 1000))
.format(e, EPISODES, agent.epsilon, quality, len(agent.memory), len(agent.memory_done), time_sum/100.0)
print(msg_str)
logger.info(msg_str)
print("quality: {:0.2f}".format(quality))
if quality_max < quality:
quality_max = quality
# if quality_max > 15.0:
# logger.info("Saving weights @ episode: {}/{}, quality: {:0.2f}".format(e, EPISODES, quality))
# agent.save("/tmp/" + thisName + ".h5")
time_sum = 0.0
score_sum = 0.0
score_cnt = 0.0
time.sleep(2)
break
stats.add(e, game.moves, game.score, game.score / 100.0, agent.epsilon,
len(agent.memory_done))
if int(e / 100) * 100 == e:
stats.flush()
steps_wo_r = 0
if len(agent.memory) > BATCH_SIZE:
#print "agent.replay.."
agent.replay(BATCH_SIZE)
for elem in stats_arr:
e = elem[0]
v = elem[1]
i = int(v)
sys.stdout.write("# %-10i | %s (%0.2f)\n" % (e, '=' * i, v))
def _record_stats(self, world):
stats.add(self._game_type(), int(world.time / 1000))
def printStatsCreatures(self, pop, gen, dba, dbb, dbp):
fits = [ind.fitness.values[0] for ind in pop]
mean = sum(fits) / len(pop)
reds = [funcs.gene2color(genome[-1]) for genome in pop]
greens = [funcs.gene2color(genome[-2]) for genome in pop]
blues = [funcs.gene2color(genome[-3]) for genome in pop]
stats.add("creature_fitness.avg", mean)
stats.add("creature_fitness.min", min(fits))
stats.add("creature_fitness.max", max(fits))
stats.add("creature.death_by_bush_procent",
dbb * 1.0 / (dbb + dba + dbp))
stats.add("creature.death_by_predator_procent",
dbp * 1.0 / (dbb + dba + dbp))
stats.add("creature_color.red", sum(reds) / len(reds))
stats.add("creature_color.blue", sum(blues) / len(blues))
stats.add("creature_color.green", sum(greens) / len(greens))
return ("(%3i): Max: %6.2f, Avg: %6.2f, Min: %5.2f, DBBP: %.2f" %
(gen, max(fits), mean, min(fits), dbb * 1.0 /
(dbb + dbp + dba)))
def printStatsCreatures(self,pop,gen,dba,dbb,dbp):
fits = [ind.fitness.values[0] for ind in pop]
mean = sum(fits) / len(pop)
reds = [funcs.gene2color(genome[-1]) for genome in pop]
greens = [funcs.gene2color(genome[-2]) for genome in pop]
blues = [funcs.gene2color(genome[-3]) for genome in pop]
stats.add("creature_fitness.avg",mean)
stats.add("creature_fitness.min",min(fits))
stats.add("creature_fitness.max",max(fits))
stats.add("creature.death_by_bush_procent",dbb*1.0/(dbb+dba+dbp))
stats.add("creature.death_by_predator_procent",dbp*1.0/(dbb+dba+dbp))
stats.add("creature_color.red", sum(reds)/len(reds))
stats.add("creature_color.blue", sum(blues)/len(blues))
stats.add("creature_color.green", sum(greens)/len(greens))
return ("(%3i): Max: %6.2f, Avg: %6.2f, Min: %5.2f, DBBP: %.2f" % (gen, max(fits), mean, min(fits),dbb*1.0/(dbb+dbp+dba)))