def main(multicore, NGEN, POP, refmap, MUTPB, mu_mean, mu_sigma, verb, grid,
graph):
creator.create("FitnessMax", base.Fitness, weights=(1.0, ))
creator.create("Individual", list, fitness=creator.FitnessMax)
toolbox = base.Toolbox()
toolbox.register("attr_trans", random.uniform, TRANS_MIN, TRANS_MAX)
toolbox.register("attr_rot", random.uniform, ROT_MIN, ROT_MAX)
toolbox.register(
"individual",
tools.initCycle,
creator.Individual,
(toolbox.attr_trans, toolbox.attr_trans, toolbox.attr_rot),
n=1)
toolbox.register("population", tools.initRepeat, list, toolbox.individual)
if grid:
pop = initPop(POP, refmap, creator.Individual)
else:
pop = toolbox.population(n=POP)
toolbox.register("select", tools.selNSGA2)
toolbox.register("mate", tools.cxOnePoint)
toolbox.register("evaluate", evaluate)
if multicore:
pool = multiprocessing.Pool()
toolbox.register("map", pool.map)
hof = tools.HallOfFame(5)
stats = tools.Statistics(lambda ind: ind.fitness.values)
stats.register("max", np.max)
stats.register("min", np.min)
stats.register("avg", np.mean)
stats.register("std", np.std)
random.seed()
record, log = eaMuPlusLambdaZeno(pop,
toolbox,
mu=int(POP * elite),
lambda_=int(POP * (1 - elite)),
cxpb=CXPB,
mutpb=MUTPB,
ngen=NGEN,
mu_mean=mu_mean,
mu_sigma=mu_sigma,
stats=stats,
halloffame=hof,
verbose=args.v,
graph=graph)
expr = tools.selBest(pop, 1)[0]
if verb:
print "Best individual:", expr
print "Fitness:", evaluate_solution(expr[0], expr[1], expr[2],
errorscan.posx, errorscan.posy,
errorscan.rot)
best_result = evaluate_solution(expr[0], expr[1], expr[2], errorscan.posx,
errorscan.posy, errorscan.rot)
return best_result, record, log, expr
def main(multicore, NGEN, POP, scan, map, CXPB, MUTPB, verb, graph):
creator.create("FitnessMax", base.Fitness, weights=(1.0, ))
creator.create("Individual", list, fitness=creator.FitnessMax)
toolbox = base.Toolbox()
toolbox.register("attr_trans", random.uniform, TRANS_MIN, TRANS_MAX)
toolbox.register("attr_rot", random.uniform, ROT_MIN, ROT_MAX)
toolbox.register(
"individual",
tools.initCycle,
creator.Individual,
(toolbox.attr_trans, toolbox.attr_trans, toolbox.attr_rot),
n=1)
toolbox.register("population", tools.initRepeat, list, toolbox.individual)
toolbox.register("mutate",
tools.mutGaussian,
sigma=0.125 / 4,
mu=0,
indpb=MUTPB)
toolbox.register("select", tools.selTournament, tournsize=3)
toolbox.register("mate", tools.cxOnePoint)
toolbox.register("evaluate", evaluate)
if multicore:
pool = multiprocessing.Pool()
toolbox.register("map", pool.map)
pop = toolbox.population(n=POP)
hof = tools.HallOfFame(5)
stats = tools.Statistics(lambda ind: ind.fitness.values)
stats.register("max", np.max)
stats.register("min", np.min)
stats.register("avg", np.mean)
stats.register("std", np.std)
random.seed()
record, log = eaSimple(pop,
toolbox,
cxpb=CXPB,
mutpb=MUTPB,
ngen=NGEN,
stats=stats,
halloffame=hof,
verbose=args.v,
graph=args.graph)
expr = tools.selBest(pop, 1)[0]
if verb:
print "Best individual:", expr
print "Fitness:", evaluate_solution(expr[0], expr[1], expr[2],
errorscan.posx, errorscan.posy,
errorscan.rot)
best_result = evaluate_solution(expr[0], expr[1], expr[2], errorscan.posx,
errorscan.posy, errorscan.rot)
return best_result, record, log, expr