def play_game(sample_size):
bb = Baraja()
bb.revolver()
A = bb.approx_best_move(sample_size=sample_size)
prize = bb.play(A[0]).value
logging.debug('%s -- %s -- %s' % (bb.preview(), act.actions[A[0]], prize))
return prize
def batching(size):
print('running batching')
xbat = []
ybat = []
b = Baraja()
for _ in range(size):
b.revolver()
xbat.append(b.one_hot())
ybat.append(b.approx_best_move(sample_size=150)[0])
return xbat, ybat
def test_approx_best_move(self):
b = Baraja()
b.start_with(map(Naipe, ['AS', 'QS', 'JS', 'KS', '10S']))
self.assertEqual(b.approx_best_move(sample_size=200)[0], 31)
# %load_ext autoreload
# %autoreload 2
import actions as act
from collections import Counter
from baraja import Naipe, Mano, Baraja, Prize
# #%run ~/code/EfedEquis/Efedequis/poquer/baraja/baraja
# %%time
b = Baraja()
b.start_with(map(Naipe,['6D', 'QH', '7H', '7S', '10C']))
#b.evaluate(13, sample_size=5000000)
prize_counter = Counter()
for _ in range(1000):
prize_counter.update([b.play(13)])
print(prize_counter.most_common())
b.approx_best_move(sample_size=300)
# %%time
b = Baraja()
b.start_with(map(Naipe,['3S', 'QS', 'JD', '7S', '6S']))
res = []
for i in range(32):
res.append((act.actions[i], b.evaluate_eff(i, sample_size=10)))
{k: v for k, v in sorted(res, key=lambda item: -item[1])}
best = b.approx_best_move(sample_size=100)
act.actions[best[0]],best[1]
# +
#b = Baraja()
#b.revolver()