def solve(self, start, end, algorithm):
"""Solves a maze from start to finish."""
if self.maze is None:
raise utils.MazeError(
"Maze is not assigned.\n"
"Use the \"create\" or \"load_maze\" method to create or load a maze."
)
start = start if start else (0, 0)
end = end if end else (self.row_count - 1, self.col_count - 1)
if not (0 <= start[0] < self.row_count and 0 <= start[1] < self.col_count):
raise utils.MazeError("Start point <{}> is out of range.".format(start))
if not (0 <= end[0] < self.row_count and 0 <= end[1] < self.col_count):
raise utils.MazeError("End point <{}> is out of range.".format(end))
start = tuple([2 * x + 1 for x in start])
end = tuple([2 * x + 1 for x in end])
self.solution = self.maze.copy()
if algorithm == Maze.Solve.C:
return self._depth_first_search_c(start, end)
if algorithm == Maze.Solve.DEPTH:
return self._depth_first_search(start, end)
if algorithm == Maze.Solve.BREADTH:
return self._breadth_first_search(start, end)
raise utils.MazeError(
"Wrong algorithm <{}>.\n"
"Use \"Algorithm.Solve.<algorithm>\" to choose an algorithm.".format(algorithm)
)
def create(self, row_count, col_count, algorithm):
"""Creates a maze for a given row and column count."""
if (row_count or col_count) <= 0:
raise utils.MazeError(
"Row or column count cannot be smaller than zero.")
self.maze = np.ones((row_count, col_count), dtype=np.uint8) * -1
if algorithm == Maze.Create.BACKTRACKING or algorithm == 0:
return self._recursive_backtracking()
# if algorithm == Maze.Create.HUNT:
# return self._hunt_and_kill()
if algorithm == Maze.Create.ELLER or algorithm == 1:
return self._eller()
if algorithm == Maze.Create.SIDEWINDER or algorithm == 2:
return self._sidewinder()
if algorithm == Maze.Create.PRIM or algorithm == 3:
return self._prim()
if algorithm == Maze.Create.KRUSKAL or algorithm == 4:
return self._kruskal()
if algorithm == Maze.Create.RANDOM or algorithm == 5:
return self._randomGenerate()
raise utils.MazeError(
"Wrong algorithm <{}>.\n"
"Use \"Maze.Create.<algorithm>\" to choose an algorithm.".format(
algorithm))
def create(self, col_count,row_count, algorithm):
"""Creates a maze for a given row and column count."""
if (row_count or col_count) <= 0:
raise utils.MazeError("Row or column count cannot be smaller than zero.")
self.maze = np.zeros((2 * row_count + 1, 2 * col_count + 1, 3), dtype=np.uint8)
if algorithm == Maze.Create.C:
return self._recursive_backtracking_c()
if algorithm == Maze.Create.BACKTRACKING:
return self._recursive_backtracking()
if algorithm == Maze.Create.HUNT:
return self._hunt_and_kill()
if algorithm == Maze.Create.ELLER:
return self._eller()
if algorithm == Maze.Create.SIDEWINDER:
return self._sidewinder()
if algorithm == Maze.Create.PRIM:
return self._prim()
if algorithm == Maze.Create.KRUSKAL:
return self._kruskal()
raise utils.MazeError(
"Wrong algorithm <{}>.\n"
"Use \"Maze.Create.<algorithm>\" to choose an algorithm.".format(algorithm)
)
def load_maze(self, file_name="maze.png"):
"""Loads the maze from png."""
if not os.path.isfile(file_name):
raise util.MazeError(
"Cannot load maze because <{}> does not exist.".format(
file_name))
self.maze = util.downscale(np.array(Image.open(file_name)))
def save_solution(self, file_name="solution.png", scale=3):
"""Saves the solution as png."""
if self.solution is None:
raise util.MazeError(
"Cannot save solution because it is not assigned.\n"
"Use the \"solve\" method to solve a maze."
)
Image.fromarray(util.upscale(self.solution, scale), "RGB").save(file_name, "png")
def save_maze(self, file_name="maze.png", scale=3):
"""Saves the maze as png."""
if self.maze is None:
raise util.MazeError(
"Cannot save maze because it is not assigned.\n"
"Use the \"create\" or \"load_maze\" method to create or load a maze."
)
Image.fromarray(util.upscale(self.maze, scale), "RGB").save(file_name, "png")
def save_maze(self, file_name="maze.png", line=5, path=15):
"""Saves the maze as png."""
if self.maze is None:
raise util.MazeError(
"Cannot save maze because it is not assigned.\n"
"Use the \"create\" or \"load_maze\" method to create or load a maze."
)
img = Image.fromarray(util.upscale(self.maze, line, path), "RGB")
img.save("uncropped.png")
print(img)
img = PIL.ImageOps.invert(img).convert("L")
newImage = Image.new("L", (1085, 720))
newImage.paste(img, (0, 7, 1085, 7 + 705))
newImage.save(file_name, "png")
return newImage
def _depth_first_search(self, start, end):
"""Solves a maze using depth-first search."""
visited = self.maze.copy() # List of visited cells, value of visited cell is 0
stack = collections.deque() # List of visited cells [(x, y), ...]
x, y = start
visited[x, y, 0] = 0 # Mark as visited
while x and y:
while x and y:
stack.append((x, y))
if (x, y) == end: # Stop if end has been found
return utils.draw_path(self.solution, stack)
x, y = self._solve_walk(x, y, visited)
x, y = self._solve_backtrack(stack, visited)
raise utils.MazeError("No solution found.")
def _breadth_first_search(self, start, end):
"""Solves a maze using breadth-first search."""
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.")
