def test_place_workers(self):
positions = self.player.place_workers(self.initial_board)
self.assertEqual(positions, [Position(0, 0), Position(0, 4)])
initial_board2 = Board(self.INITIAL_BOARD2)
positions2 = self.player.place_workers(initial_board2)
self.assertEqual(positions2, [Position(4, 4), Position(4, 0)])
def __init__(self):
self.color = ''
self.strategy = Strategy()
self.starting_positions = [Position(0, 0), Position(0, 4), Position(4, 4), Position(4, 0)]
self.RuleChecker = RuleChecker()
self.game_state = 'start'
self.name = 'Kanye'
self.last_board = Board([[0, 0, 0, 0, 0], [0, 0, 0, 0, 0], [0, 0, 0, 0, 0],
[0, 0, 0, 0, 0], [0, 0, 0, 0, 0]])
def __init__(self, color):
self.color = color
self.strategy = Strategy()
self.starting_positions = [
Position(0, 0),
Position(0, 4),
Position(4, 4),
Position(4, 0)
]
def execute(self, input):
command = input[0]
if not self.check_input(input):
return self.error_message()
if command == 'Register' and self.game_state == 0:
self.game_state = 1
return self.name
if command == 'Place' and self.game_state == 1:
self.color = str(input[1])
b = Board(input[2])
self.last_board = b
if not self.RuleChecker.validate_initial_board(b, self.color):
return self.error_message()
self.game_state = 2
posns = self.place_workers(b)
self.last_board.worker_locations[self.color + '1'] = Position(
posns[0][0], posns[0][1])
self.last_board.worker_locations[self.color + '2'] = Position(
posns[1][0], posns[1][1])
return posns
if command == 'Play' and self.game_state == 2:
b = Board(input[1])
if not self.is_possible_board(b):
return self.error_message()
self.last_board = b
if not self.RuleChecker.validate_board(b):
return self.error_message()
play_options = self.get_plays(b)
if play_options:
index = random.randint(0, len(play_options) - 1)
playmade = self.format_plays(play_options)[index]
else:
play_options = self.strategy.get_legal_plays(self.color, b)
if play_options:
index = random.randint(0, len(play_options) - 1)
playmade = self.format_plays(play_options)[index]
else:
playmade = []
if playmade:
if len(playmade) == 3:
Playmade = Play(playmade[0], playmade[1], playmade[2])
else:
Playmade = Play(playmade[0], playmade[1])
self.last_board = Playmade.resulting_board(self.last_board)
return playmade
if command == 'Game Over':
self.game_state = 0
self.last_board = Board([[0, 0, 0, 0, 0], [0, 0, 0, 0, 0],
[0, 0, 0, 0, 0], [0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]])
self.color = ''
return 'OK'
return self.error_message()
def __init__(self):
self.color = ''
self.strategy = Strategy()
self.starting_positions = [
Position(0, 0),
Position(0, 4),
Position(4, 4),
Position(4, 0)
]
self.RuleChecker = RuleChecker()
self.game_state = 0
self.name = ''.join(
random.choice(string.ascii_uppercase) for _ in range(5))
self.last_board = Board([[0, 0, 0, 0, 0], [0, 0, 0, 0, 0],
[0, 0, 0, 0, 0], [0, 0, 0, 0, 0],
[0, 0, 0, 0, 0]])
def act(self, board):
player = board.turn()
actions = board.list_moves()
scored_actions = []
middle = board.width // 2
for action in actions:
row = board.row(action)
pos = Position(row, action)
score = 0
if board.would_win(pos, player):
score += 1000000
if board.would_win(pos, 3 - player):
score += 1000
score += middle - abs(middle - action)
scored_actions.append((action, score))
scored_actions.sort(key=lambda value: -value[1])
best_score = scored_actions[0][1]
best_moves = [
action for action, score in scored_actions if score == best_score
]
return random.choice(best_moves)
def drawBoard(self, squareSize=100):
widthOffset = (WIDTH - squareSize * 8) / 2
heightOffset = (HEIGHT - squareSize * 8) / 2
black = True
for row in range(8):
black = not black
for col in range(8):
pos = Position(
left=widthOffset + squareSize * col,
top=heightOffset + squareSize * row,
)
square = BoardSquare(
position=pos,
width=squareSize,
piece=None,
filled=None,
location=(row, col),
)
grid[row][col] = square
rect = pygame.Rect(square.position.left, square.position.top,
100, 100)
if black:
pygame.draw.rect(WIN, colors.BOARD_GREEN, rect)
else:
pygame.draw.rect(WIN, colors.BOARD_WHITE, rect)
black = not black
def random_to_random():
win_num = 0
for j in range(10000):
pos = Position(empty_board,'A',0,-1)
step = 0
while True:
try:
index = pos.pick_move()[0]
except Exception:
win_num+=0.5
break
pos = pos.move(index)
if pos.reward()!=0:
win_num+=1
break
try:
index2 = pos.pick_move()[0]
except Exception:
win_num+=0.5
break
pos = pos.move(index2)
if pos.reward()!=0:
break
step+=1
if step>=N*N:
win_num+=0.5
pos.show()
return win_num/100.0
def load_map(file_name):
walls, goals = set(), set()
boxes, player = set(), None
with open(file_name, 'r') as f:
num_lines = int(f.readline())
for y, line in enumerate(f.readlines()):
if line:
for x, char in enumerate(line):
pos = Position(x, y)
if char in WALL:
walls.add(pos)
if char in GOAL:
goals.add(pos)
if char in BOX:
boxes.add(pos)
if char in PLAYER:
player = pos
else:
break
board = Board(num_lines, walls, goals)
return board, boxes, player
def play_and_train(net,i,batches_per_game=2):
positions = []
tree = TreeNode(net=net,pos=Position(empty_board,'A',0,-1))
tree.expand()
while True:
# tree search move one step
next_tree = tree_search(tree,N_SIMS)
positions.append((tree.pos,tree.distribution()))
tree = next_tree
#tree.pos.show()
#print 'Number of A is %d, number of a is %d' % (tree.pos.board.count('A'),tree.pos.board.count('a'))
reward = tree.pos.reward()
if reward!=0.0:
# attention!!!
print 'attention reward is ',reward
if tree.pos.turn=='A':
score = -1.0
else:
score = 1.0
#tree.expand()
#next_tree = tree_search(tree,N_SIMS)
#positions.append((tree.pos,tree.distribution()))
break
if tree.pos.step > N*N*2:
score = 0.0
break
#print 'Begin fit_game=================='
X_positions = [encode_position(pos) for pos,dist in positions]
X_dists = [dist for pos,dist in positions]
net.fit_game(X_positions,X_dists,score)
X_positions = [encode_position(pos,board_transform='flip_vert') for pos,dist in positions]
X_dists = [dist for pos,dist in positions]
net.fit_game(X_positions,X_dists,score)
X_positions = [encode_position(pos,board_transform='flip_horiz') for pos,dist in positions]
X_dists = [dist for pos,dist in positions]
net.fit_game(X_positions,X_dists,score)
X_positions = [encode_position(pos,board_transform='flip_both') for pos,dist in positions]
X_dists = [dist for pos,dist in positions]
net.fit_game(X_positions,X_dists,score)
X_positions = [encode_position(pos,board_transform='flip_clock') for pos,dist in positions]
X_dists = [dist for pos,dist in positions]
net.fit_game(X_positions,X_dists,score)
X_positions = [encode_position(pos,board_transform='flip_reverse_clock') for pos,dist in positions]
X_dists = [dist for pos,dist in positions]
net.fit_game(X_positions,X_dists,score)
X_positions = [encode_position(pos,board_transform='flip_clock2') for pos,dist in positions]
X_dists = [dist for pos,dist in positions]
net.fit_game(X_positions,X_dists,score)
X_positions = [encode_position(pos,board_transform='flip_reverse_clock2') for pos,dist in positions]
X_dists = [dist for pos,dist in positions]
net.fit_game(X_positions,X_dists,score)
def placement(self, coord1, coord2):
worker1 = self.turn + '1'
worker2 = self.turn + '2'
worker1_Pos = Position(coord1[0], coord1[1])
worker2_Pos = Position(coord2[0], coord2[1])
if not self.board._is_in_bounds(
worker1_Pos) or not self.board._is_in_bounds(worker2_Pos):
return self._opponent_wins(self.turn)
if self.board.is_cell_occupied(
worker1_Pos) or self.board.is_cell_occupied(worker2_Pos):
return self._opponent_wins(self.turn)
self.board.worker_locations[worker1] = worker1_Pos
self.board.worker_locations[worker2] = worker2_Pos
self.turn = self._opponent_color(self.turn)
return self.board
def test_battle_process():
start_timestamp = 1510000000
board = Board(piece_shape_set_generate())
battle = Battle(start_timestamp, 5, 2, board)
for player_id in range(4):
assert battle.try_join_player(start_timestamp, player_id,
{"user_id": player_id})
assert battle.try_drop_piece(start_timestamp, 0, 0, Position())
def add_to_board(self, board):
moves = {}
for row in range(1, board.rows + 1):
for column in range(1, board.columns + 1):
p = Position(row, column, board, self.verbosity.verbose_int)
possible_positions = []
for i in self.moves:
possible_position = p.get_new_position(i[0], i[1])
if possible_position.fits_on_board:
possible_positions.append(possible_position)
moves[p.coordinate] = possible_positions
Knight.all_possible_moves = moves
def execute(self, input):
command = input[0]
if not self.check_input(input):
return self.error_message()
if command == 'Register' and self.game_state == 0:
self.game_state = 1
return 'Kanye'
if command == 'Place' and self.game_state == 1:
self.color = str(input[1])
b = Board(input[2])
self.last_board = b
if not self.RuleChecker.validate_initial_board(b, self.color):
return self.error_message()
self.game_state = 2
posns = self.place_workers(b)
self.last_board.worker_locations[self.color + '1'] = Position(
posns[0][0], posns[0][1])
self.last_board.worker_locations[self.color + '2'] = Position(
posns[1][0], posns[1][1])
return posns
if command == 'Play' and self.game_state == 2:
b = Board(input[1])
if not self.is_possible_board(b):
return self.error_message()
self.last_board = b
if not self.RuleChecker.validate_board(b):
return self.error_message()
play_options = self.get_plays(b)
if play_options:
return self.format_plays(play_options)[0]
else:
play_options = self.strategy.get_legal_plays(self.color, b)
if play_options:
return self.format_plays(play_options)[0]
else:
return []
if command == 'Game Over' and self.game_state == 2:
self.game_state = 3
return 'OK'
return self.error_message()
def is_possible_board(self, b):
opponent_possible_boards = []
l_board = self.last_board
if len(l_board.worker_locations.keys()) < 2:
grid = b.height_grid
for row in grid:
for cell in row:
if cell > 0:
return False
return True
if len(l_board.worker_locations.keys()) < 4:
grid = b.height_grid
sum = 0
for row in grid:
for cell in row:
sum = sum + cell
if sum == 1:
return True
return False
oldgrid = l_board.height_grid
newgrid = b.height_grid
oldworkers = l_board.worker_locations
newworkers = b.worker_locations
heightchange = []
movedworkers = []
for i in range(len(oldgrid)):
for j in range(len(oldgrid[0])):
if oldgrid[i][j] != newgrid[i][j]:
if newgrid[i][j] - oldgrid[i][j] != 1:
return False
heightchange.append(Position(i, j))
if len(heightchange) > 2:
return False
for worker in oldworkers.keys():
if oldworkers[worker] != newworkers[worker]:
if not oldworkers[worker].near(newworkers[worker]):
return False
movedworkers.append(worker)
found = 0
if len(movedworkers) > 2:
return False
if movedworkers[0][:-1] == movedworkers[1][:-1]:
return False
for worker in movedworkers:
newpos = newworkers[worker]
if newpos.near(heightchange[0]):
heightchange[0] = heightchange[1]
found = found + 1
elif newpos.near(heightchange[1]):
heightchange[1] = heightchange[0]
found = found + 1
return found == 2
def placement(self, p):
rsp = p.execute(['Place', self.turn, self.board.format_board()])
coords = rsp
if isinstance(coords, (basestring, str)):
return self.otherplayerwins()
coord1 = coords[0]
coord2 = coords[1]
worker1 = self.turn + '1'
worker2 = self.turn + '2'
worker1_Pos = Position(coord1[0], coord1[1])
worker2_Pos = Position(coord2[0], coord2[1])
if not self.board._is_in_bounds(
worker1_Pos) or not self.board._is_in_bounds(worker2_Pos):
return self.otherplayerwins()
if self.board.is_cell_occupied(
worker1_Pos) or self.board.is_cell_occupied(worker2_Pos):
return self.otherplayerwins()
self.board.worker_locations[worker1] = worker1_Pos
self.board.worker_locations[worker2] = worker2_Pos
self.turn = self.other_color(self.turn)
return self.board
def _generate_start_position(self, start_position):
error1 = "The %s value of your start position must be an integer. Please enter the starting location in the following format: 4.5"
error2 = "the %s (the %s value of the starting position) does not fit on the board"
row_column = start_position.split(".")
assert len(row_column) is 2, "start position must contain exactly one '.' period"
try:
row = int(row_column[0])
except ValueError:
print error1 %("first")
exit(1)
try:
column = int(row_column[1])
except ValueError:
print error1 %("second")
exit(1)
assert 0 < row <= self.board.rows, error2 %("row","first")
assert 0 < column <= self.board.columns, error2 %("column","second")
return Position(row, column, self.board, self.verbosity.verbose_int)
def evaluate_random(net):
win_num = 0
for j in range(100):
pos = Position(empty_board,'A',0,-1)
step = 0
while True:
pos_array = encode_position(pos)
pos_array_new = np.expand_dims(pos_array,axis=0)
dis = net.predict_distribution(pos_array_new)
index = np.argmax(dis)
while index<N*N and pos.board[index]!='.':
dis[index] = 0.0
index = np.argmax(dis)
if index == N*N:
index = pos.pick_move()[0]
if pos.board[index]!='.':
win_num+=0.5
break
pos = pos.move(index)
if pos.reward()!=0:
win_num+=1
break
try:
index2 = pos.pick_move()[0]
except Exception:
win_num+=0.5
break
pos = pos.move(index2)
if pos.reward()!=0:
break
step+=1
if step>=N*N:
win_num+=0.5
pos.show()
return win_num/100.0
def main():
img = get_image()
squares = get_squares(img)
walls, goals = set(), set()
boxes, player = set(), None
num_lines = len(squares)
for y, line in enumerate(squares):
for x, s in enumerate(line):
char = detect(s)
pos = Position(x, y)
if char in WALL:
walls.add(pos)
if char in GOAL:
goals.add(pos)
if char in BOX:
boxes.add(pos)
if char in PLAYER:
player = pos
if len(boxes) - len(goals) == 1:
goals.add(player)
board = Board(num_lines, walls, goals)
board.print_board(boxes, player)
path = Astar_search(board, boxes, player)
idx = 0
for boxes, player in path[::-1]:
idx += 1
subprocess.call('clear')
board.print_board(boxes, player)
input()
def test_is_in_bounds(self):
self.assertFalse(self.board._is_in_bounds(Position(0, 5)))
self.assertFalse(self.board._is_in_bounds(Position(5, 3)))
self.assertFalse(self.board._is_in_bounds(Position(0, -1)))
self.assertTrue(self.board._is_in_bounds(Position(3, 2)))
#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Sun Oct 7 16:56:36 2018 @author: ubuntu """ from board import make_board, Position, empty_board p0 = Position(empty_board, 'A', 0, -1) p0.show() print '===========' p1 = p0.move(0) p1.show() print '===========' p2 = p1.move(1) p2.show() print '===========' p3 = p2.move(2) p3.show() print '===========' board = make_board(empty_board) p4 = Position(board, 'A', 10, -1) p4.show() p5 = p4.flip_clock() print '===========' p5.show() print '===========' p6 = p4.flip_reverse_clock() p6.show()
#!/usr/bin/env python2 # -*- coding: utf-8 -*- """ Created on Sun Oct 7 17:12:14 2018 @author: ubuntu """ from mcts import encode_position, TreeNode from board import Position, make_board, empty_board from net import GobangModel p0 = Position(make_board(empty_board), 'a', 0, -1) p0.show() x = encode_position(p0) print x[10:15, 0, 0] print x[10:15, 0, 1] print x[10:15, 0, 2] p1 = p0.move(18) y = encode_position(p1) print y[10:15, 0, 0] print y[10:15, 0, 1] print y[10:15, 0, 2] p2 = p1.move(37) z = encode_position(p2) print z[10:15, 0, 0] print z[10:15, 0, 1] print z[10:15, 0, 2]
def is_satisfying(self):
return self._is_satisfying(Position(self.rows, self.cols), self.tree)
def would_win(self, action, player):
row = self.board.row(action)
pos = Position(row, action)
return self.board.would_win(pos, player)