def count_adjacent(self, player, xy, game_=None):
if game_ is None:
board = self.game.board
else:
board = game_.board
x, y = xy
other = ""
total = ""
lr_index = [0, 1, 1, 1, 0, -1, -1, -1]
ud_index = [1, 1, 0, -1, -1, -1, 0, 1]
has_enemy = False
for i in range(8):
ij = x + lr_index[i], y + ud_index[i]
if tokens.out_of_board(ij) or board.is_cell_empty(ij):
other += "0"
total += "0"
continue
total += "1"
if board.get_colour(ij) == player:
other += "0"
else:
other += "1"
has_enemy = True
if not has_enemy:
return other, other
return other, total
def pieces_threatened(game_state, player):
other = game.other_player(player)
home_b = count_pieces(game_state[player])
pieces = 0
for enemy in game_state[other]:
xy = enemy[1], enemy[2]
for move in tokens.available_moves(other):
if move == "Boom":
continue
for dist in range(enemy[0]):
dist = enemy[0] - dist
xy2 = game.dir_to_xy(xy, move, dist)
temp_game = game.Game(game_state)
if tokens.out_of_board(
xy2) or not temp_game.board.is_cell_empty(xy2):
continue
temp_game.move_token(1, xy, move, dist, other)
temp_game.boom(xy2, other)
home_a = count_pieces(temp_game.get_game_state()[player])
pieces += home_b - home_a
return pieces
def boom_area(pieces):
locs = []
for piece in pieces:
x, y = piece[1], piece[2]
for i in range(x - 1, x + 1 + 1):
for j in range(y - 1, y + 1 + 1):
ij = (i, j)
if tokens.out_of_board(ij):
continue
if ij not in locs:
locs.append(ij)
return len(locs)
def has_potential_threat(self, xy, player):
if not xy:
return False
else:
x, y = xy
for i in range(x - 1, x + 1 + 1):
for j in range(y - 1, y + 1 + 1):
ij = i, j
if tokens.out_of_board(ij) or ij == xy:
continue
if not self.game.board.is_cell_empty(
ij) and self.game.board.get_colour(ij) == player:
return True
return False
def get_nearest_corner(self, ally_xy, enemy_xy):
from math import sqrt, pow
closest = None
min_dist = float("inf")
horizontal = [-1, 1]
vertical = [-1, 1]
for i in horizontal:
for j in vertical:
ij = enemy_xy[0] + i, enemy_xy[1] + j
if tokens.out_of_board(ij):
continue
dist = sqrt(
pow(ally_xy[0] - ij[0], 2) + pow(ally_xy[1] - ij[1], 2))
if dist < min_dist:
min_dist = dist
closest = ij
return closest