def loop_game(i, start, queue, cache, cf_lock, level, logger):
start = bin2mat(human2bin(start))
game = Game(start, queue, i, level)
board = Array('f', range(16))
board[:] = start.reshape((16,)).tolist()[:]
moves = 0
while True:
p = Process(target=game.run, args=(moves, board, cache, cf_lock, logger))
p.start()
p.join()
del p
moves += 1
def apply(self, b_new, n=None, four=None):
if four is None:
four = random.randint(0, 100) > 90
cell = 2 + (2 * int(four))
c = self.empty(b_new)
if n is None:
if c > 1:
n = random.randint(0, c - 1)
else:
n = 1
t = 0
tb = bin2mat(b_new)
for y in range(4):
for x in range(4):
if t == n and tb[y][x] == 0:
tb[y][x] = cell
t += 1
elif tb[y][x] == 0:
t += 1
return mat2bin(tb)
def empty(self, board):
return len(list(filter(lambda x: x == 0,
bin2mat(board).reshape((16,)).tolist())))
def __init__(self, board):
self.board = bin2mat(board)
def move(self, board, cache, cache_queue, logger):
me = MoveEvaluator(mat2bin(board))
ce = ChaosEvaluator(cache, self.level, cache_queue, logger)
ce_res = ce.eval(mat2bin(board))[0]
return bin2mat(ce.apply(me.sim(np.argmax(ce_res))[0]))