Files
amazing/src/amaz_lib/MazeGenerator.py
T
2026-03-25 15:27:39 +01:00

267 lines
8.4 KiB
Python

from abc import ABC, abstractmethod
from typing import Generator, Set
import numpy as np
from .Cell import Cell
import math
class MazeGenerator(ABC):
@abstractmethod
def generator(
self, height: int, width: int, seed: int = None
) -> Generator[np.ndarray, None, np.ndarray]: ...
@staticmethod
def get_cell_ft(width: int, height: int) -> set:
forty_two = set()
y, x = (int(height / 2), int(width / 2))
forty_two.add((y, x - 1))
forty_two.add((y, x - 2))
forty_two.add((y, x - 3))
forty_two.add((y - 1, x - 3))
forty_two.add((y - 2, x - 3))
forty_two.add((y + 1, x - 1))
forty_two.add((y + 2, x - 1))
forty_two.add((y, x + 1))
forty_two.add((y, x + 2))
forty_two.add((y, x + 3))
forty_two.add((y - 1, x + 3))
forty_two.add((y - 2, x + 3))
forty_two.add((y - 2, x + 2))
forty_two.add((y - 2, x + 1))
forty_two.add((y + 1, x + 1))
forty_two.add((y + 2, x + 1))
forty_two.add((y + 2, x + 2))
forty_two.add((y + 2, x + 3))
return forty_two
class Kruskal(MazeGenerator):
class Set:
def __init__(self, cells: list[int]) -> None:
self.cells: list[int] = cells
class Sets:
def __init__(self, sets: list[Set]) -> None:
self.sets = sets
@staticmethod
def walls_to_maze(
walls: np.ndarray, height: int, width: int
) -> np.ndarray:
maze: np.ndarray = np.array(
[[Cell(value=0) for _ in range(width)] for _ in range(height)]
)
for wall in walls:
x, y = wall
match y - x:
case 1:
maze[math.trunc((x / width))][x % width].set_est(True)
maze[math.trunc((y / width))][y % width].set_west(True)
case width:
maze[math.trunc((x / width))][x % width].set_south(True)
maze[math.trunc((y / width))][y % width].set_north(True)
for x in range(height):
for y in range(width):
if x == 0:
maze[x][y].set_north(True)
if x == height - 1:
maze[x][y].set_south(True)
if y == 0:
maze[x][y].set_west(True)
if y == width - 1:
maze[x][y].set_est(True)
return maze
@staticmethod
def is_in_same_set(sets: Sets, wall: tuple[int, int]) -> bool:
a, b = wall
for set in sets.sets:
if a in set.cells and b in set.cells:
return True
elif a in set.cells or b in set.cells:
return False
return False
@staticmethod
def merge_sets(sets: Sets, wall: tuple[int, int]) -> None:
a, b = wall
base_set = None
for i in range(len(sets.sets)):
if base_set is None and (
a in sets.sets[i].cells or b in sets.sets[i].cells
):
base_set = sets.sets[i]
elif base_set and (
a in sets.sets[i].cells or b in sets.sets[i].cells
):
base_set.cells += sets.sets[i].cells
sets.sets.pop(i)
return
raise Exception("two sets not found")
@staticmethod
def touch_ft(
width: int,
wall: tuple[int, int],
cells_ft: None | set[tuple[int, int]],
) -> bool:
if cells_ft is None:
return False
s1 = (wall[0] / width, wall[0] % width)
s2 = (wall[1] / width, wall[1] % width)
return s1 in cells_ft or s2 in cells_ft
def generator(
self, height: int, width: int, seed: int = None
) -> Generator[np.ndarray, None, np.ndarray]:
cells_ft = None
if height > 10 and width > 10:
cells_ft = self.get_cell_ft(width, height)
if seed is not None:
np.random.seed(seed)
sets = self.Sets([self.Set([i]) for i in range(height * width)])
walls = []
for h in range(height):
for w in range(width - 1):
walls += [(w + (width * h), w + (width * h) + 1)]
for h in range(height - 1):
for w in range(width):
walls += [(w + (width * h), w + (width * (h + 1)))]
print(walls)
np.random.shuffle(walls)
yield self.walls_to_maze(walls, height, width)
while len(sets.sets) != 1 and (len(sets.sets) != 19 and cells_ft not None):
for wall in walls:
if not self.is_in_same_set(sets, wall) and not self.touch_ft(
width, wall, cells_ft
):
self.merge_sets(sets, wall)
walls.remove(wall)
yield self.walls_to_maze(walls, height, width)
if len(sets.sets) == 19:
break
print(f"nb sets: {len(sets.sets)}")
return self.walls_to_maze(walls, height, width)
class DepthFirstSearch(MazeGenerator):
def generator(
self, height: int, width: int, seed: int = None
) -> Generator[np.ndarray, None, np.ndarray]:
if seed is not None:
np.random.seed(seed)
maze = self.init_maze(width, height)
forty_two = self.get_cell_ft(width, height)
visited = np.zeros((height, width), dtype=bool)
visited = self.lock_cell_ft(visited, forty_two)
path = list()
w_h = (width, height)
coord = (0, 0)
x, y = coord
first_iteration = True
while path or first_iteration:
first_iteration = False
visited[y, x] = True
path = self.add_cell_visited(coord, path)
random_c = self.random_cells(visited, coord, w_h)
if not random_c:
path = self.back_on_step(path, w_h, visited)
if not path:
break
coord = path[-1]
random_c = self.random_cells(visited, coord, w_h)
x, y = coord
wall = self.next_step(random_c)
maze[y][x] = self.broken_wall(maze[y][x], wall)
coord = self.next_cell(x, y, wall)
wall_r = self.reverse_path(wall)
x, y = coord
maze[y][x] = self.broken_wall(maze[y][x], wall_r)
yield maze
return maze
@staticmethod
def init_maze(width: int, height: int) -> np.ndarray:
maze = np.array(
[[Cell(value=15) for _ in range(width)] for _ in range(height)]
)
return maze
@staticmethod
def add_cell_visited(coord: tuple, path: set) -> list:
path.append(coord)
return path
@staticmethod
def random_cells(visited: np.array, coord: tuple, w_h: tuple) -> list:
rand_cell = []
x, y = coord
width, height = w_h
if y - 1 >= 0 and not visited[y - 1][x]:
rand_cell.append("N")
if y + 1 < height and not visited[y + 1][x]:
rand_cell.append("S")
if x - 1 >= 0 and not visited[y][x - 1]:
rand_cell.append("W")
if x + 1 < width and not visited[y][x + 1]:
rand_cell.append("E")
return rand_cell
@staticmethod
def next_step(rand_cell: list) -> str:
return np.random.choice(rand_cell)
@staticmethod
def broken_wall(cell: Cell, wall: str) -> Cell:
if wall == "N":
cell.set_north(False)
elif wall == "S":
cell.set_south(False)
elif wall == "W":
cell.set_west(False)
elif wall == "E":
cell.set_est(False)
return cell
@staticmethod
def next_cell(x: int, y: int, next: str) -> tuple:
next_step = {"N": (0, -1), "S": (0, 1), "W": (-1, 0), "E": (1, 0)}
add_x, add_y = next_step[next]
return (x + add_x, y + add_y)
@staticmethod
def reverse_path(direction: str) -> str:
return {"N": "S", "S": "N", "W": "E", "E": "W"}[direction]
@staticmethod
def back_on_step(path: list, w_h: tuple, visited: np.array) -> list:
while path:
last = path[-1]
if DepthFirstSearch.random_cells(visited, last, w_h):
break
path.pop()
return path
@staticmethod
def lock_cell_ft(
visited: np.ndarray, forty_two: set[tuple[int]]
) -> np.ndarray:
tab = [cell for cell in forty_two]
for cell in tab:
visited[cell] = True
return visited