algorithm edited but nothing better

Makefile

@@ -18,8 +18,5 @@ lint-strict:
 	uv run flake8 .
 	uv run mypy . --strict
 
-run_test_parsing:
-	PYTHONPATH=src uv run pytest tests/test_parsing.py
-
-run_test_dfs:
-	PYTHONPATH=src uv run pytest tests/test_Depth.py
+run_test:
+	uv run pytest

a_maze_ing.py

@@ -1,17 +1,19 @@
 import os
 from numpy import ma
-from src.amaz_lib import MazeGenerator
+from src.amaz_lib import MazeGenerator, Kruskal, AStar
 from src.amaz_lib import Maze
 
 
 def main() -> None:
     # try:
-    maze = Maze(maze=None, start=(1, 1), end=(16, 15))
-    for alg in MazeGenerator.Kruskal.kruskal(20, 20):
+    maze = Maze(maze=None)
+    generator = Kruskal()
+    for alg in generator.generator(20, 20):
         maze.set_maze(alg)
-        os.system("clear")
+        # os.system("clear")
         maze.ascii_print()
-    maze.export_maze("test.txt")
+    # solver = AStar((1, 1), (14, 18))
+    # print(solver.solve(maze))
 
 
 # except Exception as 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

@@ -1,9 +1,9 @@
 from abc import ABC, abstractmethod
-from typing import Generator
+from dataclasses import dataclass
+from typing import Generator, Set
 import numpy as np
 from .Cell import Cell
 import math
-import random
 
 
 class MazeGenerator(ABC):
@@ -14,9 +14,13 @@ class MazeGenerator(ABC):
 
 
 class Kruskal(MazeGenerator):
+    class Set:
+        def __init__(self, cells: list[int]) -> None:
+            self.cells: list[int] = cells
+
     @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)]
@@ -37,43 +41,46 @@ 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: np.ndarray, wall: tuple[int, int]) -> bool:
         a, b = wall
         for set in sets:
-            if a in set and b in set:
+            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: np.ndarray, 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)):
+            if base_set is None and (a in sets[i].cells or b in sets[i].cells):
+                base_set = sets[i]
+            elif base_set and (a in sets[i].cells or b in sets[i].cells):
+                base_set.cells += sets[i].cells
+                np.delete(sets, i)
+                return
+        raise Exception("two sets not found")
 
     def generator(
         self, height: int, width: int
     ) -> Generator[np.ndarray, None, np.ndarray]:
-        sets = [[i] for i in range(height * width)]
+        sets = np.array([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)
@@ -82,114 +89,5 @@ class Kruskal(MazeGenerator):
                 self.merge_sets(sets, wall)
                 walls.remove(wall)
                 yield self.walls_to_maze(walls, height, width)
+        print(f"nb sets: {len(sets)}")
         return self.walls_to_maze(walls, height, width)
-
-
-class DepthFirstSearch:
-
-    @staticmethod
-    def generator(width: int, height: int) -> np.ndarray:
-        maze = DepthFirstSearch.init_maze(width, height)
-        visited = []
-        path = []
-        w_h = (width, height)
-        coord = (0, 0)
-        while len(visited) < width * height:
-            x, y = coord
-            rand_steps = DepthFirstSearch.random_cells(visited, coord, w_h)
-            if len(rand_steps) == 0:
-                path = DepthFirstSearch.back_on_step(path, w_h)
-                coord = DepthFirstSearch.last(path)
-                rand_steps = DepthFirstSearch.random_cells(path, coord, w_h)
-                x, y = coord
-            wall = DepthFirstSearch.next_step(rand_steps)
-            wall_r = DepthFirstSearch.reverse_path(wall)
-            maze[y][x] = DepthFirstSearch.broken_wall(maze[y][x], wall)
-            visited = DepthFirstSearch.add_cell_visited(coord, visited)
-            path = DepthFirstSearch.add_cell_visited(coord, path)
-            coord = DepthFirstSearch.next_cell(x, y, wall)
-            x, y = coord
-            maze[y][x] = DepthFirstSearch.broken_wall(maze[y][x], wall_r)
-        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, visited: list = []) -> list:
-        visited.append(coord)
-        return visited
-
-    @staticmethod
-    def random_cells(visited: list, coord: tuple, w_h: tuple) -> list:
-        rand_cell = []
-        x, y = coord
-        width, height = w_h
-        # NORTH
-        if y - 1 >= 0 and (x, y - 1) not in visited:
-            rand_cell.append("N")
-
-        # SOUTH
-        if y + 1 < height and (x, y + 1) not in visited:
-            rand_cell.append("S")
-
-        # WEST
-        if x - 1 >= 0 and (x - 1, y) not in visited:
-            rand_cell.append("W")
-
-        # EAST
-        if x + 1 < width and (x + 1, y) not in visited:
-            rand_cell.append("E")
-        return rand_cell
-
-    @staticmethod
-    def next_step(rand_cell: list) -> str:
-        return 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)
-
-    def reverse_path(next: str) -> str:
-        reverse = {
-            "N": "S",
-            "S": "N",
-            "W": "E",
-            "E": "W"
-        }
-        return reverse[next]
-
-    @staticmethod
-    def last(path: list):
-        return path[len(path) - 1]
-
-    def back_on_step(path: list, w_h: tuple) -> list:
-        last = DepthFirstSearch.last(path)
-        r_cells = DepthFirstSearch.random_cells(path,  last, w_h)
-        while len(r_cells == 0):
-            path.pop(len(path) - 1)
-            last = DepthFirstSearch.last(path)
-            r_cells = DepthFirstSearch.random_cells(path,  last, w_h)
-        return path

src/amaz_lib/MazeSolver.py

@@ -1,7 +1,134 @@
 from abc import ABC, abstractmethod
 from .Maze import Maze
+import numpy as np
 
 
 class MazeSolver(ABC):
+    def __init__(self, start: tuple[int, int], end: tuple[int, int]) -> None:
+        self.start = (start[0] - 1, start[1] - 1)
+        self.end = (end[0] - 1, end[1] - 1)
+
     @abstractmethod
     def solve(self, maze: Maze) -> str: ...
+
+
+class AStar(MazeSolver):
+
+    def __init__(self, start: tuple[int, int], end: tuple[int, int]) -> None:
+        super().__init__(start, end)
+
+    def f(self, n):
+        def g(n: tuple[int, int]) -> int:
+            res = 0
+            if n[0] < self.start[0]:
+                res += self.start[0] - n[0]
+            else:
+                res += n[0] - self.start[0]
+            if n[1] < self.start[1]:
+                res += self.start[1] - n[1]
+            else:
+                res += n[1] - self.start[1]
+            return res
+
+        def h(n: tuple[int, int]) -> int:
+            res = 0
+            if n[0] < self.end[0]:
+                res += self.end[0] - n[0]
+            else:
+                res += n[0] - self.end[0]
+            if n[1] < self.end[1]:
+                res += self.end[1] - n[1]
+            else:
+                res += n[1] - self.end[1]
+            return res
+
+        try:
+            return g(n) + h(n)
+        except Exception:
+            return 1000
+
+    def best_path(
+        self, maze: np.ndarray, actual: tuple[int, int]
+    ) -> dict[str, int | None]:
+        print(actual)
+        path = {
+            "N": (
+                self.f((actual[0], actual[1] - 1))
+                if not maze[actual[0]][actual[1]].get_north() and actual[1] > 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
+                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
+                else None
+            ),
+            "W": (
+                self.f((actual[0] - 1, actual[1]))
+                if not maze[actual[0]][actual[1]].get_west() and actual[0] > 0
+                else None
+            ),
+        }
+        return {
+            k: v for k, v in sorted(path.items(), key=lambda item: item[0])
+        }
+
+    def get_opposit(self, dir: str) -> str:
+        match dir:
+            case "N":
+                return "S"
+            case "E":
+                return "W"
+            case "S":
+                return "N"
+            case "W":
+                return "E"
+            case _:
+                return ""
+
+    def get_next_pos(
+        self, dir: str, actual: tuple[int, int]
+    ) -> tuple[int, int]:
+        match dir:
+            case "N":
+                return (actual[0], actual[1] - 1)
+            case "E":
+                return (actual[0] + 1, actual[1])
+            case "S":
+                return (actual[0], actual[1] + 1)
+            case "W":
+                return (actual[0] - 1, actual[1])
+            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
+        return None
+
+    def solve(self, maze: Maze) -> str:
+        print(maze)
+        res = self.get_path(self.start, maze.get_maze(), None)
+        if res is None:
+            raise Exception("Path not found")
+        return res

src/amaz_lib/__init__.py

@@ -1,8 +1,8 @@
 from .Cell import Cell
 from .Maze import Maze
-from .MazeGenerator import MazeGenerator, DepthFirstSearch
-from .MazeSolver import MazeSolver
+from .MazeGenerator import MazeGenerator, Kruskal
+from .MazeSolver import MazeSolver, AStar
 
 __version__ = "1.0.0"
 __author__ = "us"
-__all__ = ["Cell", "Maze", "MazeGenerator", "MazeSolver", "DepthFirstSearch"]
+__all__ = ["Cell", "Maze", "MazeGenerator", "MazeSolver", "AStar", "Kruskal"]

tests/test_Depth.py

@@ -1,33 +0,0 @@
-from amaz_lib.MazeGenerator import DepthFirstSearch
-from amaz_lib.Cell import Cell
-
-
-class TestDepth:
-
-    def test_init_maze(self) -> None:
-        maze = DepthFirstSearch.init_maze(10, 10)
-        cell = Cell(value=15)
-        maze[1][1].set_est(False)
-        assert maze[0][0].value == cell.value
-
-    def test_rand_cells(self) -> None:
-        w_h = (10, 10)
-        lst = DepthFirstSearch.add_cell_visited((0, 0))
-        rand_cells = DepthFirstSearch.random_cells(lst, (0, 1), w_h)
-        assert len(rand_cells) == 2
-
-    def test_next_cell(self) -> None:
-        coord = (5, 4)
-        x, y = coord
-        assert DepthFirstSearch.next_cell(x, y, "N") == (5, 3)
-
-    def test_reverse_path(self) -> None:
-        assert DepthFirstSearch.reverse_path("N") == "S"
-
-    def test_last(self) -> None:
-        lst = [(0, 0), (1, 1)]
-        assert DepthFirstSearch.last(lst) == (1, 1)
-
-    def test_BOS(self) -> None:
-        path = [(0, 0), (0, 2), (1, 1)]
-        assert len(DepthFirstSearch.random_cells(path, (0, 1), (10, 10))) == 0

tests/test_Maze.py

@@ -15,7 +15,7 @@ def test_maze_setter_getter() -> None:
     )
 
     maze.set_maze(test)
-    assert numpy.array_equal(maze.get_maze(), test) is True
+    assert numpy.array_equal(maze.get_maze(), test) == True
 
 
 def test_maze_str() -> None:

tests/test_MazeSolver.py

@@ -0,0 +1,19 @@
+from amaz_lib.Cell import Cell
+import numpy as np
+from amaz_lib import AStar, Maze, MazeSolver
+
+
+def test_solver() -> None:
+    maze = Maze(
+        np.array(
+            [
+                [Cell(value=13), Cell(value=3), Cell(value=11)],
+                [Cell(value=9), Cell(value=4), Cell(value=6)],
+                [Cell(value=12), Cell(value=5), Cell(value=7)],
+            ]
+        )
+    )
+    print(maze)
+    solver = AStar((1, 1), (3, 3))
+    res = solver.solve(maze)
+    assert res == "ESWSEE"