def test_flatten(self):
self.assertEqual(utils.flatten_coords((0, 0)), 0)
self.assertEqual(utils.flatten_coords((0, 3)), 3)
self.assertEqual(utils.flatten_coords((3, 0)), 27)
self.assertEqual(utils.unflatten_coords(27), (3, 0))
self.assertEqual(utils.unflatten_coords(10), (1, 1))
self.assertEqual(utils.unflatten_coords(80), (8, 8))
self.assertEqual(utils.flatten_coords(utils.unflatten_coords(10)), 10)
self.assertEqual(utils.unflatten_coords(utils.flatten_coords((5, 4))), (5, 4))
def test_flatten(self):
self.assertEqual(utils.flatten_coords((0, 0)), 0)
self.assertEqual(utils.flatten_coords((0, 3)), 3)
self.assertEqual(utils.flatten_coords((3, 0)), 27)
self.assertEqual(utils.unflatten_coords(27), (3, 0))
self.assertEqual(utils.unflatten_coords(10), (1, 1))
self.assertEqual(utils.unflatten_coords(80), (8, 8))
self.assertEqual(utils.flatten_coords(utils.unflatten_coords(10)), 10)
self.assertEqual(utils.unflatten_coords(utils.flatten_coords((5, 4))), (5, 4))
def make_onehot(coords):
num_positions = len(coords)
output = np.zeros([num_positions, go.N**2], dtype=np.uint8)
for i, coord in enumerate(coords):
if coord:
output[i, utils.flatten_coords(coord)] = 1
else:
continue
return output
def make_onehot(coords): #onehot则是顾名思义，一个长度为n的数组，蜂窝煤矩阵，只有一个元素是1，其他元素是0
print("生成坐标棋谱图")
num_positions = len(coords) #有多少步？
output = np.zeros([num_positions, go.N ** 2], dtype=np.uint8) #返回给定形状和类型的矩阵，用0填充。uint8是专门用于存储各种图像的 现在是生成多少步，第步有361个点
#print(output)
for i, coord in enumerate(coords): #遍历矩阵
output[i, utils.flatten_coords(coord)] = 1 #放置坐标 将每一步落子转换成一位数组 flatten即降维 Flatten层用来将输入“压平”，即把多维的输入一维化，常用在从卷积层到全连接层的过渡
#将第i手,坐标置1
#display(i,output[i].reshape(go.N,go.N)) #升维成棋盘显示
return output
def suggest_move(self, board, caps):
if caps:
for m in caps:
self.ills[m] = 0
if board.n > 30:
self.t = 0.05
if board.n > 0:
self.root = self.get_node(board)
if not self.root:
move_probs, win_rate = self.policy_network.run(board)
self.root = MCTSNode.root_node(board, move_probs, self.ills)
else:
win_rate = self.root.Q
print('使用上次的node')
start = time.time()
ts = self.select_child(start)
if random.randint(0, 1000) > 997:
print('第%d手，搜索了%d次' % (board.n, ts))
#self.printmsg("Searched for %s seconds" % (time.time() - start))
#sorted_moves = sorted(self.root.children.keys(), key=lambda move, rt=self.root: rt.children[move].N, reverse=True)
self.would_pass = 0
winnode = None
pi = np.zeros(go.N * go.N + 1, dtype=np.float32)
if self.can_pass and self.root.children:
if board.n > 100 and board.recent[-1].move == go.PASS:
self.would_pass += 2
if (win_rate + 1) / 2 < config.vresign or (win_rate + 1) / 2 > (
1 - config.vresign):
self.would_pass += 2
winnode = max(self.root.children.values(), key=lambda x: x.Q)
if (winnode.Q * board.to_play + 1) / 2 < config.vresign or (
winnode.Q * board.to_play + 1) / 2 > (1 - config.vresign):
self.would_pass += 2
self.would_pass += board.n // 100
if not self.root.children or (self.can_pass and self.would_pass > 5):
pi[go.N * go.N] = 1
return go.PASS, pi, winnode.Q if winnode else 0
alln = reduce(lambda x, y: x + y.N, self.root.children.values(), 0)
if alln == 0:
alln = 1
for m, node in self.root.children.items():
ind = utils.flatten_coords(m)
pi[ind] = node.N**(1 / self.t) / alln**(1 / self.t)
maxnode = max(self.root.children.values(),
key=lambda x: x.N**(1 / self.t) / alln**(1 / self.t))
#if self.root.Q<self.vresign and select_node.Q<self.vresign:
# return go.PASS, 0, 0
return maxnode.move, pi, maxnode.Q #黑棋胜率
def make_onehot(coords):
num_positions = len(coords)
output = np.zeros([num_positions, go.N ** 2], dtype=np.uint8)
for i, coord in enumerate(coords):
output[i, utils.flatten_coords(coord)] = 1
return output
def make_onehot(coord):
output = np.zeros([N**2], dtype=np.uint8)
output[utils.flatten_coords(coord)] = 1
return output
