[2] add stats(time of compliting maze)
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57c743c253
commit
133d076666
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@ -1,11 +1,12 @@
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import sys
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from collections import deque
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import heapq
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from typing import List, Dict, Optional
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import time
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from typing import List, Optional
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class Cell:
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def __init__(self, x, y):
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def __init__(self, x: int, y: int):
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self._x = x
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self._y = y
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self._is_wall = False
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@ -13,43 +14,46 @@ class Cell:
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self._is_exit = False
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@property
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def x(self):
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def x(self) -> int:
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return self._x
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@property
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def y(self):
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def y(self) -> int:
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return self._y
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@property
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def is_wall(self):
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def is_wall(self) -> bool:
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return self._is_wall
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@is_wall.setter
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def is_wall(self, value):
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def is_wall(self, value: bool) -> None:
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self._is_wall = value
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@property
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def is_start(self):
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def is_start(self) -> bool:
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return self._is_start
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@is_start.setter
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def is_start(self, value):
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def is_start(self, value: bool) -> None:
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self._is_start = value
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@property
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def is_exit(self):
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def is_exit(self) -> bool:
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return self._is_exit
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@is_exit.setter
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def is_exit(self, value):
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def is_exit(self, value: bool) -> None:
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self._is_exit = value
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def is_passable(self):
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def is_passable(self) -> bool:
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return not self._is_wall
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def __repr__(self) -> str:
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return f"Cell({self._x}, {self._y})"
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class Maze:
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def __init__(self, width, height):
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def __init__(self, width: int, height: int):
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self._width = width
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self._height = height
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self._cells = [[Cell(x, y) for x in range(width)] for y in range(height)]
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@ -57,27 +61,27 @@ class Maze:
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self._exit = None
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@property
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def width(self):
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def width(self) -> int:
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return self._width
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@property
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def height(self):
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def height(self) -> int:
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return self._height
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@property
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def start(self):
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def start(self) -> Optional[Cell]:
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return self._start
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@property
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def exit(self):
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def exit(self) -> Optional[Cell]:
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return self._exit
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def get_cell(self, x, y):
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def get_cell(self, x: int, y: int) -> Optional[Cell]:
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if 0 <= x < self._width and 0 <= y < self._height:
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return self._cells[y][x]
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return None
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def set_cell(self, x, y, cell_type):
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def set_cell(self, x: int, y: int, cell_type: str) -> None:
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cell = self.get_cell(x, y)
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if cell is None:
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return
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@ -99,7 +103,7 @@ class Maze:
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elif cell_type == 'path':
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cell.is_wall = False
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def get_neighbors(self, cell):
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def get_neighbors(self, cell: Cell) -> List[Cell]:
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neighbors = []
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directions = [(0, -1), (0, 1), (-1, 0), (1, 0)]
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for dx, dy in directions:
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@ -111,118 +115,136 @@ class Maze:
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class MazeBuilder:
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def build_from_file(self, filename):
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raise NotImplementedError("Need to realise in calss")
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def build_from_file(self, filename: str) -> Maze:
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raise NotImplementedError("Need to implement in subclass")
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class TextFileMazeBuilder(MazeBuilder):
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def build_from_file(self, filename):
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with open(filename, 'r') as f:
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lines = [line.rstrip('\n')for line in f.readlines()]
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def build_from_file(self, filename: str) -> Maze:
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with open(filename, 'r', encoding='utf-8') as f:
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lines = [line.rstrip('\n') for line in f.readlines()]
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if not lines:
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raise ValueError("Файл пуст")
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height = len(lines)
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width = max(len(line) for line in lines) if height > 0 else 0
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start_en = 0
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exit_en = 0
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width = max(len(line) for line in lines)
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start_count = 0
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exit_count = 0
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maze = Maze(width, height)
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for y,line in enumerate(lines):
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for y, line in enumerate(lines):
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for x, ch in enumerate(line):
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if ch == "#":
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maze.set_cell(x,y,"wall")
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elif ch == "S":
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maze.set_cell(x,y,"start")
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start_en+=1
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elif ch == "E":
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maze.set_cell(x,y,"exit")
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exit_en+=1
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if x >= width:
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continue
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if ch == '#':
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maze.set_cell(x, y, "wall")
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elif ch == 'S':
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maze.set_cell(x, y, "start")
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start_count += 1
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elif ch == 'E':
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maze.set_cell(x, y, "exit")
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exit_count += 1
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else:
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maze.set_cell(x, y, 'path')
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if start_en > 1 or exit_en > 1 or start_en==0 or exit_en ==0:
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sys.exit("Error while reading file(you have too many or no match start and exits)")
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if start_count != 1 or exit_count != 1:
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raise ValueError(
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f"Лабиринт должен иметь ровно один S и один E. "
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f"Найдено: S={start_count}, E={exit_count}"
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)
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return maze
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class PathFindingStrategy:
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def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
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raise NotImplementedError("Subclasses must implement find_path")
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def _reconstruct_path(self, came_from: dict, start: Cell, exit_cell: Cell) -> List[Cell]:
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path = []
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current = exit_cell
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while current is not None:
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path.append(current)
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current = came_from.get(current)
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path.reverse()
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return path
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class BFSStrategy:
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def find_path(self, maze, start, exit):
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class BFSStrategy(PathFindingStrategy):
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def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
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queue = deque()
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queue.append(start)
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came_from={}
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came_from[start]=None
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visited = set()
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visited.add(start)
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came_from = {start: None}
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visited = {start}
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while queue:
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current = queue.popleft()
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if current == exit:
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return self._reconstruct_path(came_from,start,exit)
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for neighbors in maze.get_neighbors(current):
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if neighbors not in visited:
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visited.add(neighbors)
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came_from[neighbors] = current
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queue.append(neighbors)
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if current == exit_cell:
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return self._reconstruct_path(came_from, start, exit_cell)
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for neighbor in maze.get_neighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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came_from[neighbor] = current
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queue.append(neighbor)
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return []
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def _reconstruct_path(self, came_from, start, exit_cell):
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path = []
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current = exit_cell
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while current is not None:
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path.append(current)
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current = came_from.get(current)
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path.reverse()
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return path
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class DFSStrategy:
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def find_path(self,maze,start,exit):
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stack =[]
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stack.append(start)
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came_from={}
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came_from[start]=None
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visited = set()
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visited.add(start)
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class DFSStrategy(PathFindingStrategy):
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def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
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stack = [start]
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came_from = {start: None}
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visited = {start}
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while stack:
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current = stack.pop()
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if current == exit:
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return self._reconstruct_path(came_from,start,exit)
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for neighbors in maze.get_neighbors(current):
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if neighbors not in visited:
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visited.add(neighbors)
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came_from[neighbors]= current
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stack.append(neighbors)
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if current == exit_cell:
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return self._reconstruct_path(came_from, start, exit_cell)
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for neighbor in maze.get_neighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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came_from[neighbor] = current
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stack.append(neighbor)
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return []
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def _reconstruct_path(self, came_from, start, exit_cell):
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path = []
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current = exit_cell
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while current is not None:
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path.append(current)
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current = came_from.get(current)
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path.reverse()
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return path
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class AStarStrategy:
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def _heuristic(self, cell,exit_cell):
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return abs(cell.x -exit_cell.x)+abs(cell.y-exit_cell.y)
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def find_path(self,maze, start, exit_cell):
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class AStarStrategy(PathFindingStrategy):
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def _heuristic(self, cell: Cell, exit_cell: Cell) -> int:
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return abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y)
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def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
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heap = []
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counter = 0
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start_f = 0 + self._heuristic(start,exit_cell)
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start_f = self._heuristic(start, exit_cell)
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heapq.heappush(heap, (start_f, counter, start))
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counter +=1
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counter += 1
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came_from = {}
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g_score = {start: 0}
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f_score = {start: start_f}
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while heap:
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current_f, _, current = heapq.heappop(heap)
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if current==exit_cell:
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if current == exit_cell:
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return self._reconstruct_path(came_from, start, exit_cell)
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if current_f>f_score.get(current, float("inf")):
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if current_f > f_score.get(current, float('inf')):
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continue
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for neighbor in maze.get_neighbors(current):
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tentative_g = g_score[current] + 1
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if tentative_g < g_score.get(neighbor, float('inf')):
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came_from[neighbor] = current
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g_score[neighbor] = tentative_g
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@ -230,28 +252,65 @@ class AStarStrategy:
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f_score[neighbor] = new_f
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heapq.heappush(heap, (new_f, counter, neighbor))
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counter += 1
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return []
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def _reconstruct_path(self, came_from, start, exit_cell):
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path = []
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current = exit_cell
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while current is not None:
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path.append(current)
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current = came_from.get(current)
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path.reverse()
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return path
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class SearchStats:
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def __init__(self, time_ms: float, visited_cells: int, path_length: int):
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self.time_ms = time_ms
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self.visited_cells = visited_cells
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self.path_length = path_length
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def __repr__(self) -> str:
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return f"SearchStats(time={self.time_ms:.3f}ms, visited={self.visited_cells}, path_length={self.path_length})"
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class MazeSolver:
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def __init__(self, maze: Maze):
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self._maze = maze
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self._strategy = None
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def set_strategy(self, strategy: PathFindingStrategy) -> None:
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self._strategy = strategy
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def solve(self) -> Optional[SearchStats]:
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if self._strategy is None:
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print("Ошибка: стратегия не установлена")
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return None
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start_time = time.perf_counter()
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path = self._strategy.find_path(self._maze, self._maze.start, self._maze.exit)
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end_time = time.perf_counter()
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time_ms = (end_time - start_time) * 1000
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visited_cells = 0
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return SearchStats(time_ms, visited_cells, len(path))
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if __name__ == "__main__":
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builder = TextFileMazeBuilder()
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maze = builder.build_from_file("maze1.txt")
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print(f"Лабиринт {maze.width}x{maze.height}")
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print(f"Старт: ({maze.start.x}, {maze.start.y})")
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print(f"Выход: ({maze.exit.x}, {maze.exit.y})")
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bfs = BFSStrategy()
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path = bfs.find_path(maze, maze.start, maze.exit)
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print(f"BFS: путь найден, длина = {len(path)}")
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dfs = DFSStrategy()
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path = dfs.find_path(maze, maze.start, maze.exit)
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print(f"DFS: путь найден, длинна = {len(path)}")
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astar = AStarStrategy()
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path = astar.find_path(maze, maze.start, maze.exit)
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print(f"A*: путь найден, длина = {len(path)}")
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print("-" * 40)
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solver = MazeSolver(maze)
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solver.set_strategy(BFSStrategy())
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stats = solver.solve()
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print(f"BFS: {stats}")
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solver.set_strategy(DFSStrategy())
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stats = solver.solve()
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print(f"DFS: {stats}")
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solver.set_strategy(AStarStrategy())
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stats = solver.solve()
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print(f"A*: {stats}")
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