def pre_calc_distance(gamestate):
gamestate.distance_table = {}
for row in range(gamestate.rows):
for col in range(gamestate.cols):
gamestate.distance_table[(row,col)] = np.zeros((gamestate.rows, gamestate.cols), dtype=int) + 100
for d_row in range(row-5, row+6):
for d_col in range(col-5, col+6):
d_row = d_row % gamestate.rows
d_col = d_col % gamestate.cols
gamestate.distance_table[(row,col)][d_row, d_col] = \
cython_ext2.euclidean_distance2(row, col, d_row, d_col, gamestate.rows, gamestate.cols)
def pre_calc_distance(gamestate):
gamestate.distance_table = {}
for row in range(gamestate.rows):
for col in range(gamestate.cols):
gamestate.distance_table[(row, col)] = np.zeros(
(gamestate.rows, gamestate.cols), dtype=int) + 100
for d_row in range(row - 5, row + 6):
for d_col in range(col - 5, col + 6):
d_row = d_row % gamestate.rows
d_col = d_col % gamestate.cols
gamestate.distance_table[(row,col)][d_row, d_col] = \
cython_ext2.euclidean_distance2(row, col, d_row, d_col, gamestate.rows, gamestate.cols)
def euclidean_distance2(self, loc1, loc2):
row1, col1 = loc1
row2, col2 = loc2
return cython_ext2.euclidean_distance2(row1, col1, row2, col2, self.rows, self.cols)
def euclidean_distance2(self, loc1, loc2):
row1, col1 = loc1
row2, col2 = loc2
return cython_ext2.euclidean_distance2(row1, col1, row2, col2,
self.rows, self.cols)