def _breadth_first_search(self, start, end):
"""
Solves a maze using breadth-first search.
:param start: tuple with start coordinates
:param end: tuple with end coordinates
:return: None
"""
visited = self.maze.copy(
) # List of visited cells, value of visited cell is 0
queue = collections.deque() # List of cells [cell, ...]
cell = utils.stack_empty(
) # Tuple of current cell with according stack ((x, y), stack)
x, y = start
cell = utils.stack_push(cell, (x, y))
queue.append(cell)
visited[x, y, 0] = 0 # Mark as visited
while queue:
self._enqueue(queue, visited)
if queue[0][0] == end: # Stop if end has been found
cell = utils.stack_push(queue[0], end) # Push end into cell
return utils.draw_path(self.solution, utils.stack_deque(cell))
raise utils.MazeError("No solution found.")
def _enqueue(self, queue, visited):
"""Queues next cells."""
cell = queue.popleft()
x, y = cell[0]
for idx in range(4): # Check adjacent cells
bx, by = self._dir_one[idx](x, y)
if visited[bx, by, 0] == 255: # Check if unvisited
tx, ty = self._dir_two[idx](x, y)
visited[bx, by, 0] = visited[tx, ty, 0] = 0 # Mark as visited
queue.append(utils.stack_push(cell, (tx, ty)))
