2026-rff_mp/BorisovMI/lab_2/docs/data/maze.py

from abc import ABC, abstractclassmethod
from collections import deque
import heapq
import time
import os
import time
import csv
import random
class Cell:
    def __init__(self, x, y):
        self.x = x
        self.y = y
        self.isWall = False
        self.isStart = False
        self.isExit = False
    
    
    def __eq__(self, other):
        if other is None:
            return False
        return self.x == other.x and self.y == other.y
    def __lt__(self, other):
        
        if other is None:
            return False
        return (self.x, self.y) < (other.x, other.y)
    def __hash__(self):
        
        return hash((self.x, self.y))
    
    def __repr__(self):
        return f"Cell({self.x}, {self.y})"
    def isPassable(self):
        return not self.isWall

class Maze:
    def __init__(self, width, height):
        self.width = width
        self.height = height
        self.grid = [[Cell(x, y) for y in range(height)] for x in range(width)]
        self.start = None
        self.exit = None
    
    def getCell(self, x, y):
        if 0 <= x < self.width and 0 <= y < self.height:
            return self.grid[x][y]
        return None
    
    def getNeighbors(self, cell):
        neighbors = []
        directions = [(0, 1), (0, -1), (1, 0), (-1, 0)]  
        for dx, dy in directions:
            neighbor = self.getCell(cell.x + dx, cell.y + dy)
            if neighbor and neighbor.isPassable():
                neighbors.append(neighbor)
        return neighbors
    
    def setStart(self, x, y):
        cell = self.getCell(x, y)
        if cell:
            cell.isStart = True
            self.start = cell
    
    def setExit(self, x, y):
        cell = self.getCell(x, y)
        if cell:
            cell.isExit = True
            self.exit = cell

class MazeBuilder(ABC):
    
    def buildFromFile(self, filename):
        pass

class TextileMazeBuilder(MazeBuilder):
    def buildFromFile(self, filename):
        with open(filename, 'r', encoding='utf-8') as f:
            lines = f.readlines()
        
        
        lines = [line.rstrip('\n\r') for line in lines]
        
        height = len(lines)
        width = len(lines[0]) if height > 0 else 0
        
        
        for line in lines:
            if len(line) != width:
                raise ValueError("все строки одинаковой длины")
        
       
        maze = Maze(width, height)
        
        
        for y in range(height):
            for x in range(width):
                char = lines[y][x]
                cell = maze.getCell(x, y)
                
                if char == '#':
                    cell.isWall = True
                elif char == ' ':
                    cell.isWall = False
                elif char == 's':
                    cell.isWall = False
                    cell.isStart = True
                    maze.start = cell
                elif char == 'e':
                    cell.isWall = False
                    cell.isExit = True
                    maze.exit = cell
                else:
                    raise ValueError(f"неизв сим")
        
        
        if maze.start is None:
            raise ValueError("в лабиринте не найден старт")
        if maze.exit is None:
            raise ValueError("в лабиринте не найден выход")
        
        return maze

class PathFindingStrategy:
    def findPath(self, maze, start, exit):
        pass


class BFSStrategy(PathFindingStrategy):
    def findPath(self, maze, start, exit):
        if exit is None:
            return []
        queue = deque([start])
        visited = {start}
        parent = {start: None}
        
        while queue:
            current = queue.popleft()
            
            if current == exit:
                return self._reconstruct_path(parent, start, exit)
            
            for neighbor in maze.getNeighbors(current):
                if neighbor not in visited:
                    visited.add(neighbor)
                    parent[neighbor] = current
                    queue.append(neighbor)
        
        return []  
    
    def _reconstruct_path(self, parent, start, exit):
        path = []
        current = exit
        while current is not None:
            path.append(current)
            current = parent[current]
        path.reverse()
        return path


class DFSStrategy(PathFindingStrategy):
    def findPath(self, maze, start, exit):
        if exit is None:
            return []
        stack = [start]
        visited = {start}
        parent = {start: None}
        
        while stack:
            current = stack.pop()
            
            if current == exit:
                return self._reconstruct_path(parent, start, exit)
            
            for neighbor in maze.getNeighbors(current):
                if neighbor not in visited:
                    visited.add(neighbor)
                    parent[neighbor] = current
                    stack.append(neighbor)
        
        return []
    
    def _reconstruct_path(self, parent, start, exit):
        path = []
        current = exit
        while current is not None:
            path.append(current)
            current = parent[current]
        path.reverse()
        return path


class AStrategy(PathFindingStrategy):
    def _heuristic(self, cell, exit):
        if exit is None:
            return 0
        return abs(cell.x - exit.x) + abs(cell.y - exit.y)
    
    def findPath(self, maze, start, exit):
        if exit is None:
            return []
        open_set = []
        heapq.heappush(open_set, (0, start))
        
        came_from = {start: None}
        g_score = {start: 0}
        
        while open_set:
            current = heapq.heappop(open_set)[1]
            
            if current == exit:
                return self._reconstruct_path(came_from, start, exit)
            
            for neighbor in maze.getNeighbors(current):
                tentative_g = g_score[current] + 1
                
                if neighbor not in g_score or tentative_g < g_score[neighbor]:
                    came_from[neighbor] = current
                    g_score[neighbor] = tentative_g
                    f_score = tentative_g + self._heuristic(neighbor, exit)
                    heapq.heappush(open_set, (f_score, neighbor))
        
        return []
    
    def _reconstruct_path(self, came_from, start, exit):
        path = []
        current = exit
        while current is not None:
            path.append(current)
            current = came_from[current]
        path.reverse()
        return path


class SearchStats:
    def __init__(self, time_ms=0, visited_cells=0, path_length=0):
        self.time_ms = time_ms
        self.visited_cells = visited_cells
        self.path_length = path_length
    
    def __str__(self):
        return f"Время: {self.time_ms:.3f} мс | Посещено: {self.visited_cells} | Длина пути: {self.path_length}"


class MazeSolver:
    def __init__(self, maze):
        self.maze = maze
        self.strategy = None
    
    def setStrategy(self, strategy):
        self.strategy = strategy
    
    def solve(self):
        if self.strategy is None:
            raise ValueError("Стратегия не установлена")
        
        
        start_time = time.perf_counter()
        path = self.strategy.findPath(self.maze, self.maze.start, self.maze.exit)
        
        end_time = time.perf_counter()
        elapsed_ms = (end_time - start_time) * 1000
        
       
        stats = SearchStats(
            time_ms=elapsed_ms,
            visited_cells=len(path),  
            path_length=len(path)
        )
        
        return path, stats