finish to print the 42

a_maze_ing.py

@@ -7,11 +7,13 @@ import src.amaz_lib as g
 def main(maze_gen: MazeGenerator) -> None:
     # try:
     maze = Maze(maze=None)
-    gen = maze_gen.generator(100, 100)
-    for alg in gen:
+    for alg in maze_gen.generator(10, 10):
         maze.set_maze(alg)
         os.system("clear")
-        maze.ascii_print()
+    maze.ascii_print()
+    # solver = AStar((1, 1), (14, 18))
+    # print(solver.solve(maze))
+
 
 # except Exception as err:
 # print(err)

src/amaz_lib/Maze.py

@@ -26,15 +26,14 @@ class Maze:
         return res
 
     def ascii_print(self) -> None:
+        for cell in self.maze[0]:
+            print("_", end="")
+            if cell.get_north():
+                print("__", end="")
+            else:
+                print("  ", end="")
+        print("_")
         for line in self.maze:
-            if line is self.maze[0]:
-                for cell in line:
-                    print("_", end="")
-                    if cell.get_north():
-                        print("__", end="")
-                    else:
-                        print("  ", end="")
-                print()
             for cell in line:
                 if cell is line[0] and cell.get_west():
                     print("|", end="")

src/amaz_lib/MazeGenerator.py

@@ -1,5 +1,5 @@
 from abc import ABC, abstractmethod
-from typing import Generator
+from typing import Generator, Set
 import numpy as np
 from .Cell import Cell
 import math
@@ -8,14 +8,46 @@ import math
 class MazeGenerator(ABC):
     @abstractmethod
     def generator(
-        self, height: int, width: int
+        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: list[tuple[int, int]], height: int, width: int
+        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)]
@@ -36,94 +68,115 @@ class Kruskal(MazeGenerator):
                 if x == height - 1:
                     maze[x][y].set_south(True)
                 if y == 0:
-                    maze[x][y].set_est(True)
-                if y == width - 1:
                     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: list[list[int]], wall: tuple[int, int]) -> bool:
+    def is_in_same_set(sets: Sets, wall: tuple[int, int]) -> bool:
         a, b = wall
-        for set in sets:
-            if a in set and b in set:
+        for set in sets.sets:
+            if a in set.cells and b in set.cells:
                 return True
-            if a in set or b in set:
+            elif a in set.cells or b in set.cells:
                 return False
         return False
 
     @staticmethod
-    def merge_sets(sets: list[list[int]], wall: tuple[int, int]) -> None:
+    def merge_sets(sets: Sets, wall: tuple[int, int]) -> None:
         a, b = wall
         base_set = None
-        for set in sets:
-            if base_set is None and (a in set or b in set):
-                base_set = set
-            elif base_set and (a in set or b in set):
-                base_set += set
-                sets.remove(set)
+        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")
 
     def generator(
-        self, height: int, width: int
+        self, height: int, width: int, seed: int = None
     ) -> Generator[np.ndarray, None, np.ndarray]:
-        sets = [[i] for i in range(height * width)]
+        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 w in range(width):
-            for h in range(height - 1):
-                walls += [(w + (width * h), w + (width * h) + width)]
+        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)
-        for wall in walls:
-            if not self.is_in_same_set(sets, wall):
-                self.merge_sets(sets, wall)
-                walls.remove(wall)
-                yield self.walls_to_maze(walls, height, width)
+        while len(sets.sets) > 1:
+            for wall in walls:
+                if not self.is_in_same_set(sets, wall):
+                    self.merge_sets(sets, wall)
+                    walls.remove(wall)
+                    yield self.walls_to_maze(walls, height, width)
+                if len(sets.sets) == 1:
+                    break
+        print(f"nb sets: {len(sets.sets)}")
         return self.walls_to_maze(walls, height, width)
 
 
 class DepthFirstSearch(MazeGenerator):
 
-    def generator(self, width: int, height: int
-                  ) -> Generator[np.ndarray, None, np.ndarray]:
-        maze = DepthFirstSearch.init_maze(width, height)
+    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 = True
+        first_iteration = True
+
+        while path or first_iteration:
+            first_iteration = False
 
-        while path or first:
-            first = False
             visited[y, x] = True
-            path = DepthFirstSearch.add_cell_visited(coord, path)
-            random_c = DepthFirstSearch.random_cells(visited, coord, w_h)
-            if len(random_c) == 0:
-                path = DepthFirstSearch.back_on_step(path, w_h, visited)
-                if path:
-                    coord = path[-1]
-                random_c = DepthFirstSearch.random_cells(visited, coord, w_h)
-                x, y = coord
+            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 = DepthFirstSearch.next_step(random_c)
-            maze[y][x] = DepthFirstSearch.broken_wall(maze[y][x], wall)
+            wall = self.next_step(random_c)
+            maze[y][x] = self.broken_wall(maze[y][x], wall)
 
-            coord = DepthFirstSearch.next_cell(x, y, wall)
-            wall_r = DepthFirstSearch.reverse_path(wall)
+            coord = self.next_cell(x, y, wall)
+            wall_r = self.reverse_path(wall)
             x, y = coord
-            maze[y][x] = DepthFirstSearch.broken_wall(maze[y][x], wall_r)
+            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)])
+        maze = np.array(
+            [[Cell(value=15) for _ in range(width)] for _ in range(height)]
+        )
         return maze
 
     @staticmethod
@@ -168,34 +221,27 @@ class DepthFirstSearch(MazeGenerator):
 
     @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)
-        }
+        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(next: str) -> str:
-        reverse = {
-            "N": "S",
-            "S": "N",
-            "W": "E",
-            "E": "W"
-        }
-        return reverse[next]
+    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:
-        last = path[-1]
-        r_cells = DepthFirstSearch.random_cells(visited,  last, w_h)
-        while len(path) > 0:
-            path.pop()
-            if path:
-                last = path[-1]
-            r_cells = DepthFirstSearch.random_cells(visited,  last, w_h)
-            if r_cells:
+        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

src/amaz_lib/MazeSolver.py

@@ -53,25 +53,25 @@ class AStar(MazeSolver):
         print(actual)
         path = {
             "N": (
-                self.f((actual[0], actual[1] - 1))
-                if not maze[actual[0]][actual[1]].get_north() and actual[1] > 0
+                self.f((actual[1] - 1, actual[0]))
+                if not maze[actual[1]][actual[0]].get_north() and actual[0] > 0
                 else None
             ),
             "E": (
-                self.f((actual[0] + 1, actual[1]))
-                if not maze[actual[0]][actual[1]].get_est()
-                and actual[0] < len(maze) - 1
+                self.f((actual[1], actual[0] + 1))
+                if not maze[actual[1]][actual[0]].get_est()
+                and actual[1] < len(maze) - 1
                 else None
             ),
             "S": (
-                self.f((actual[0], actual[1] + 1))
-                if not maze[actual[0]][actual[1]].get_south()
-                and actual[1] < len(maze[0]) - 1
+                self.f((actual[1] + 1, actual[0]))
+                if not maze[actual[1]][actual[0]].get_south()
+                and actual[0] < len(maze) - 1
                 else None
             ),
             "W": (
-                self.f((actual[0] - 1, actual[1]))
-                if not maze[actual[0]][actual[1]].get_west() and actual[0] > 0
+                self.f((actual[1], actual[0] - 1))
+                if not maze[actual[1]][actual[0]].get_west() and actual[1] > 0
                 else None
             ),
         }
@@ -107,23 +107,10 @@ class AStar(MazeSolver):
             case _:
                 return actual
 
-    def get_path(
-        self, actual: tuple[int, int], maze: np.ndarray, pre: str | None
-    ) -> str | None:
-        if actual == self.end:
-            return ""
-        paths = self.best_path(maze, actual)
-        for path in paths:
-            if paths[path] is None:
-                continue
-            if path != pre:
-                temp = self.get_path(
-                    self.get_next_pos(path, actual),
-                    maze,
-                    self.get_opposit(path),
-                )
-                if not temp is None:
-                    return path + temp
+    def get_path(self, maze: np.ndarray) -> str | None:
+        actual = self.start
+        path = ""
+
         return None
 
     def solve(self, maze: Maze) -> str: