def dict_sum(a: defaultdict, b: dict, inplace: bool = True) -> defaultdict:
"""
Calculate a + b, key-by-key.
"""
if not inplace:
result = a.copy()
else:
result = a
for key, value in b.items():
result[key] += value
return result
def process_tiles(tiles: defaultdict) -> defaultdict:
tiles_copy = tiles.copy()
relevant_tiles = [get_relevant_tiles(coord) for coord in tiles.keys()]
relevant_tiles = set(reduce(add, relevant_tiles))
for tile_coord in relevant_tiles:
neighbor_value = get_black_neighbors(tiles, tile_coord)
black_color = tile_coord in tiles.keys()
if (black_color and (neighbor_value == 0 or neighbor_value > 2)
or not black_color and neighbor_value == 2):
tiles_copy = switch_color(tiles_copy, tile_coord)
return tiles_copy
def to_next_inter(pos, cmds: list, blocked: defaultdict, turn, dir):
blocked = blocked.copy()
cmds = cmds.copy()
# print(pos, cmds, turn, dir)
if turn:
dir = dir_turn(dir, turn)
move_dir = directions[dir]
pathlen = 0
done = False
# print(new_dir, move_dir)
if len(cmds) >= 18:
pathlist.append(cmds)
return
if pos == goal:
pathlist.append(cmds)
return
while not done:
nb = pos[0] + move_dir[0], pos[1] + move_dir[1]
pathlen += 1
blocked[pos] = True
if nb in corners or nb in intersections:
done = True
cmds.extend([turn, pathlen])
new_pos = [(a, b) for a, b in get_nbs(nb)
if (a, b) != pos and grid[(
a, b)] == SCAFFOLD and not blocked[(a, b)]]
if len(new_pos) == 0:
return
for new in new_pos:
if dir == U:
turn = 'R' if nb[0] < new[0] else 'L'
turn = None if nb[1] > new[1] else turn
elif dir == R:
turn = 'R' if nb[1] < new[1] else 'L'
# turn = None if nb[1] > new[1] else turn
elif dir == D:
turn = 'R' if nb[0] > new[0] else 'L'
elif dir == L:
turn = 'R' if nb[1] > new[1] else 'L'
# print("TURN", turn, pos, new)
print(pos, cmds)
to_next_inter(nb, cmds, blocked, turn, dir)
pos = nb
def normalise_dict(num_value_dict: defaultdict) -> defaultdict:
norm = sum(num_value_dict.values())
normed_res = num_value_dict.copy()
for k, v in normed_res.items():
normed_res[k] = v / norm
return normed_res
def __init__(self, actions: List[str], moves: defaultdict):
self.__actions = actions.copy()
self.__moves = moves.copy()
self.__action_index, self.__action_value = self.__make_action_index_n_value(
)
return
