def main():
args = parser.parse_args()
if args.popsize < 1:
print('Must specify a popsize of at least 1.', file=sys.stderr)
return 1
if args.recurrent:
from maw.rbrain import RBrain, brain_constructor
klass = RBrain
else:
from maw.brain import Brain, brain_constructor
klass = Brain
print('Reading ' + str(klass) + ' from stdin...', file=sys.stderr)
model_brain = klass.from_string(sys.stdin.read())
ga = GA(brain_constructor(model_brain.spec()), evaluator.evaluate)
prepop = int(ELITISM * args.popsize)
ga.add_individual(model_brain, prepop)
ga.add_individual(count=args.popsize - prepop) # Random remaining brains
print("# gen minFit maxFit meanFit sdFit", file=sys.stderr)
while ga.generation < args.generations and not exit_early:
ga.step()
print_stats(ga)
sorted_pop = sorted(ga.population, lambda x, y: cmp(x.fitness, y.fitness))
fittest = sorted_pop[-1]
print(fittest)
return 0
def main():
args = parser.parse_args()
if args.recurrent:
from maw.rbrain import brain_constructor
else:
from maw.brain import brain_constructor
ctor = brain_constructor(args.sizes, randomize=not args.zeros)
print(ctor(), end='')
