def score_generation(gen):
"""score the generation over a period from start to end"""
periods = [random.randint(61,550) for n in xrange(10)]
scores = []
for bot in gen:
avg_score = 0.0
for period in periods:
score = simulator.simulate_bot(bot, period, period+5, simulator.data)
avg_score += score
avg_score = avg_score/float(len(periods))
scores.append((avg_score, bot))
scores.sort(key=lambda e:e[0])
scores.reverse()
return scores
def score_generation(gen):
"""score the generation over a period from start to end"""
periods = [random.randint(61, 550) for n in xrange(10)]
scores = []
for bot in gen:
avg_score = 0.0
for period in periods:
score = simulator.simulate_bot(bot, period, period + 5,
simulator.data)
avg_score += score
avg_score = avg_score / float(len(periods))
scores.append((avg_score, bot))
scores.sort(key=lambda e: e[0])
scores.reverse()
return scores
def optimize(pop_size, num_gens, num_survivors, verbose = True):
"""Use an asexual genetic algo to optimize the bots."""
standard_period = 40 #standardize one testing period, to track progress
gen = initialize_population(pop_size)
num_children = int(pop_size/num_survivors)-1
for n in tqdm.tqdm(range(num_gens)):
scores = score_generation(gen)
survivors = [e[1] for e in scores[:num_survivors]]
if verbose == True:
score = scores[0][0]
std_score = simulator.simulate_bot(scores[0][1], standard_period, standard_period+5, simulator.data)
print "Generation {},\tScore:{}\tStd score:{}".format(n+1,score,std_score)
#print survivors
gen = make_generation(survivors,num_children)
return scores
def optimize(pop_size, num_gens, num_survivors, verbose=True):
"""Use an asexual genetic algo to optimize the bots."""
standard_period = 40 #standardize one testing period, to track progress
gen = initialize_population(pop_size)
num_children = int(pop_size / num_survivors) - 1
for n in tqdm.tqdm(range(num_gens)):
scores = score_generation(gen)
survivors = [e[1] for e in scores[:num_survivors]]
if verbose == True:
score = scores[0][0]
std_score = simulator.simulate_bot(scores[0][1], standard_period,
standard_period + 5,
simulator.data)
print "Generation {},\tScore:{}\tStd score:{}".format(
n + 1, score, std_score)
#print survivors
gen = make_generation(survivors, num_children)
return scores
