fix conflict

.gitignore

@@ -214,4 +214,5 @@ __marimo__/
 
 # Streamlit
 .streamlit/secrets.toml
+test.txt
 

Makefile

@@ -5,6 +5,9 @@ install:
 run: install
 	uv run python3 a_maze_ing.py config.txt
 
+run_windows:
+	.venv\Scripts\python -m a_maze_ing config.txt
+
 debug:
 	uv pdb python3 a_maze_ing.py config.txt
 

src/AMazeIng.py

@@ -8,8 +8,8 @@ from src.amaz_lib import Maze, MazeGenerator, MazeSolver
 class AMazeIng(BaseModel):
     model_config = ConfigDict(arbitrary_types_allowed=True)
 
-    width: int = Field(ge=3)
-    height: int = Field(ge=3)
+    width: int = Field(ge=4)
+    height: int = Field(ge=4)
     entry: tuple[int, int]
     exit: tuple[int, int]
     output_file: str = Field(min_length=3)

src/amaz_lib/MazeGenerator.py

@@ -6,6 +6,11 @@ import math
 
 
 class MazeGenerator(ABC):
+    def __init__(self, start: tuple, end: tuple, perfect: bool) -> None:
+        self.start = (start[0] - 1, start[1] - 1)
+        self.end = (end[0] - 1, end[1] - 1)
+        self.perfect = perfect
+
     @abstractmethod
     def generator(
         self, height: int, width: int, seed: int | None = None
@@ -35,8 +40,60 @@ class MazeGenerator(ABC):
         forty_two.add((y + 2, x + 3))
         return forty_two
 
+    @staticmethod
+    def unperfect_maze(width: int, height: int,
+                       maze: np.ndarray, forty_two: set | None,
+                       prob: float = 0.1
+                       ) -> Generator[np.ndarray, None, np.ndarray]:
+        directions = {
+            "N": (0, -1),
+            "S": (0, 1),
+            "W": (-1, 0),
+            "E": (1, 0)
+        }
+
+        reverse = {
+            "N": "S",
+            "S": "N",
+            "W": "E",
+            "E": "W"
+        }
+        min_break = 2
+        while True:
+            count = 0
+            for y in range(height):
+                for x in range(width):
+                    if forty_two and (x, y) in forty_two:
+                        continue
+                    for direc, (dx, dy) in directions.items():
+                        nx, ny = x + dx, y + dy
+                        if forty_two and (
+                            (y, x) in forty_two
+                            or (ny, nx) in forty_two
+                        ):
+                            continue
+                        if not (0 <= nx < width and 0 < ny < height):
+                            continue
+                        if direc in ["S", "E"]:
+                            continue
+                        if np.random.random() < prob:
+                            count += 1
+                            cell = maze[y][x]
+                            cell_n = maze[ny][nx]
+                            cell = DepthFirstSearch.broken_wall(cell, direc)
+                            cell_n = DepthFirstSearch.broken_wall(cell_n,
+                                                                  reverse[
+                                                                    direc])
+                            maze[y][x] = cell
+                            maze[ny][nx] = cell_n
+                            yield maze
+            if count > min_break:
+                break
+        return maze
+
 
 class Kruskal(MazeGenerator):
+
     class Set:
         def __init__(self, cells: list[int]) -> None:
             self.cells: list[int] = cells
@@ -118,6 +175,8 @@ class Kruskal(MazeGenerator):
         cells_ft = None
         if height > 10 and width > 10:
             cells_ft = self.get_cell_ft(width, height)
+        if cells_ft and (self.start in cells_ft or self.end in cells_ft):
+            cells_ft = None
 
         if seed is not None:
             np.random.seed(seed)
@@ -146,10 +205,23 @@ class Kruskal(MazeGenerator):
                     len(sets.sets) == 19 and cells_ft is not None
                 ):
                     break
-        return self.walls_to_maze(walls, height, width)
+        print(f"nb sets: {len(sets.sets)}")
+        maze = self.walls_to_maze(walls, height, width)
+        if self.perfect is False:
+            gen = Kruskal.unperfect_maze(width, height, maze,
+                                         cells_ft)
+            for res in gen:
+                maze = res
+                yield maze
+        return maze
 
 
 class DepthFirstSearch(MazeGenerator):
+    def __init__(self, start: bool, end: bool, perfect: bool) -> None:
+        self.start = (start[0] - 1, start[1] - 1)
+        self.end = (end[0] - 1, end[1] - 1)
+        self.perfect = perfect
+        self.forty_two: set | None = None
 
     def generator(
         self, height: int, width: int, seed: int = None
@@ -157,9 +229,15 @@ class DepthFirstSearch(MazeGenerator):
         if seed is not None:
             np.random.seed(seed)
         maze = self.init_maze(width, height)
-        forty_two = self.get_cell_ft(width, height)
+        if width > 9 and height > 9:
+            self.forty_two = self.get_cell_ft(width, height)
         visited = np.zeros((height, width), dtype=bool)
-        visited = self.lock_cell_ft(visited, forty_two)
+        if (
+            self.forty_two
+            and self.start not in self.forty_two
+            and self.end not in self.forty_two
+        ):
+            visited = self.lock_cell_ft(visited, self.forty_two)
         path = list()
         w_h = (width, height)
         coord = (0, 0)
@@ -190,6 +268,12 @@ class DepthFirstSearch(MazeGenerator):
             x, y = coord
             maze[y][x] = self.broken_wall(maze[y][x], wall_r)
             yield maze
+        if self.perfect is False:
+            gen = DepthFirstSearch.unperfect_maze(width, height, maze,
+                                                  self.forty_two)
+            for res in gen:
+                maze = res
+                yield maze
         return maze
 
     @staticmethod
@@ -250,7 +334,7 @@ class DepthFirstSearch(MazeGenerator):
         return {"N": "S", "S": "N", "W": "E", "E": "W"}[direction]
 
     @staticmethod
-    def back_on_step(path: list, w_h: tuple, visited: np.array) -> list:
+    def back_on_step(path: list, w_h: tuple, visited: np.ndarray) -> list:
         while path:
             last = path[-1]
             if DepthFirstSearch.random_cells(visited, last, w_h):

src/amaz_lib/MazeSolver.py

@@ -9,7 +9,8 @@ class MazeSolver(ABC):
         self.end = (end[1] - 1, end[0] - 1)
 
     @abstractmethod
-    def solve(self, maze: Maze) -> str: ...
+    def solve(self, maze: Maze, height: int = None,
+              width: int = None) -> str: ...
 
 
 class AStar(MazeSolver):
@@ -156,3 +157,81 @@ class AStar(MazeSolver):
         if res is None:
             raise Exception("Path not found")
         return res
+
+
+class DepthFirstSearchSolver(MazeSolver):
+    def __init__(self, start, end):
+        self.start = (start[1] - 1, start[0] - 1)
+        self.end = (end[1] - 1, end[0] - 1)
+
+    def solve(self, maze: Maze, height: int = None,
+              width: int = None) -> str:
+        path_str = ""
+        visited = np.zeros((height, width), dtype=bool)
+        path = list()
+        move = list()
+        maze_s = maze.get_maze()
+        coord = self.start
+        h_w = (height, width)
+        while coord != self.end:
+            visited[coord] = True
+            path.append(coord)
+            rand_p = self.random_path(visited, coord, maze_s, h_w)
+
+            if not rand_p:
+                path, move = self.back_on_step(path, visited, maze_s, h_w,
+                                               move)
+                if not path:
+                    break
+                coord = path[-1]
+                rand_p = self.random_path(visited, coord, maze_s, h_w)
+            next = self.next_path(rand_p)
+            move.append(next)
+            coord = self.next_cell(coord, next)
+        for m in move:
+            path_str += m
+        if not path:
+            raise Exception("Path not found")
+        return path_str
+
+    @staticmethod
+    def random_path(visited: np.ndarray, coord: tuple,
+                    maze: np.ndarray, h_w: tuple) -> list:
+        random_p = []
+        h, w = h_w
+        y, x = coord
+
+        if y - 1 >= 0 and not maze[y][x].get_north() and not visited[y - 1][x]:
+            random_p.append("N")
+
+        if y + 1 < h and not maze[y][x].get_south() and not visited[y + 1][x]:
+            random_p.append("S")
+
+        if x - 1 >= 0 and not maze[y][x].get_west() and not visited[y][x - 1]:
+            random_p.append("W")
+
+        if x + 1 < w and not maze[y][x].get_est() and not visited[y][x + 1]:
+            random_p.append("E")
+        return random_p
+
+    @staticmethod
+    def next_path(rand_path: list) -> str:
+        return np.random.choice(rand_path)
+
+    @staticmethod
+    def back_on_step(path: list, visited: np.ndarray,
+                     maze: np.ndarray, h_w: tuple, move: list) -> list:
+        while path:
+            last = path[-1]
+            if DepthFirstSearchSolver.random_path(visited, last, maze, h_w):
+                break
+            path.pop()
+            move.pop()
+        return path, move
+
+    @staticmethod
+    def next_cell(coord: tuple, next: str) -> tuple:
+        y, x = coord
+        next_step = {"N": (-1, 0), "S": (1, 0), "W": (0, -1), "E": (0, 1)}
+        add_y, add_x = next_step[next]
+        return (y + add_y, x + add_x)

src/amaz_lib/__init__.py

@@ -2,9 +2,9 @@ from .Cell import Cell
 from .Maze import Maze
 from .MazeGenerator import MazeGenerator, DepthFirstSearch
 from .MazeGenerator import Kruskal
-from .MazeSolver import MazeSolver, AStar
+from .MazeSolver import MazeSolver, AStar, DepthFirstSearchSolver
 
 __version__ = "1.0.0"
 __author__ = "us"
-__all__ = ["Cell", "Maze", "MazeGenerator",
+__all__ = ["Cell", "Maze", "MazeGenerator", "DepthFirstSearchSolver",
            "MazeSolver", "AStar", "Kruskal", "DepthFirstSearch"]

src/parsing/Parsing.py

@@ -54,12 +54,14 @@ class DataMaze:
             res.update({key: DataMaze.convert_bool(data[key])})
         res.update({"OUTPUT_FILE": data["OUTPUT_FILE"]})
         res.update(
-            DataMaze.get_solver_generator(data, res["ENTRY"], res["EXIT"])
+            DataMaze.get_solver_generator(data, res["ENTRY"], res["EXIT"],
+                                          res["PERFECT"])
         )
         return res
 
     @staticmethod
-    def get_solver_generator(data: dict, entry: int, exit: int) -> dict:
+    def get_solver_generator(data: dict, entry: tuple, exit: tuple,
+                             perfect: bool) -> dict:
         available_generator = {
             "Kruskal": Kruskal,
             "DFS": DepthFirstSearch,
@@ -68,7 +70,8 @@ class DataMaze:
             "AStar": AStar,
         }
         res = {}
-        res["GENERATOR"] = available_generator[data["GENERATOR"]]()
+        res["GENERATOR"] = available_generator[data["GENERATOR"]](entry, exit,
+                                                                  perfect)
         res["SOLVER"] = available_solver[data["SOLVER"]](entry, exit)
         return res
 

tests/test_MazeGenerator.py

@@ -1,14 +1,18 @@
 import numpy
-from amaz_lib.MazeGenerator import DepthFirstSearch
+from amaz_lib.MazeGenerator import DepthFirstSearch, MazeGenerator
 
 
 class TestMazeGenerator:
 
     def test_generator(self) -> None:
-        w_h = (300, 300)
+        w_h = (10, 10)
         maze = numpy.array([])
-        generator = DepthFirstSearch().generator(*w_h)
+        generator = DepthFirstSearch((1, 1), (2, 2), True).generator(*w_h)
         for output in generator:
             maze = output
 
         assert maze.shape == w_h
+
+    def test_gen_broken(self) -> None:
+        test = MazeGenerator.gen_broken_set(50, 50)
+        assert len(test) > 0