483 lines
19 KiB
Python
483 lines
19 KiB
Python
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import heapq
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import time
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import os
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import csv
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from collections import deque
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from abc import ABC, abstractmethod
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import matplotlib.pyplot as plt
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import numpy as np
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class Cell:
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def __init__(self, x, y, is_wall=False):
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self.x = x
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self.y = y
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self.is_wall = is_wall
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self.is_start = False
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self.is_exit = False
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def is_passable(self):
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return not self.is_wall
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class Maze:
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def __init__(self, width, height):
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self.width = width
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self.height = height
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self.grid = [[Cell(x, y, True) for y in range(height)] for x in range(width)]
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self.start = None
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self.exit = None
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def get_cell(self, x, y):
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if 0 <= x < self.width and 0 <= y < self.height:
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return self.grid[x][y]
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return None
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def get_neighbors(self, cell):
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neighbors = []
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for dx, dy in [(0, 1), (0, -1), (1, 0), (-1, 0)]:
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nx, ny = cell.x + dx, cell.y + dy
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neighbor = self.get_cell(nx, ny)
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if neighbor and neighbor.is_passable():
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neighbors.append(neighbor)
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return neighbors
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class MazeBuilder(ABC):
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@abstractmethod
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def build_from_file(self, filename):
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pass
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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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height = len(lines)
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width = max(len(line) for line in lines) if height > 0 else 0
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maze = Maze(width, height)
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for y, line in enumerate(lines):
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for x, char in enumerate(line):
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if char == '#':
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maze.grid[x][y] = Cell(x, y, True)
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else:
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cell = Cell(x, y, False)
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if char == 'S':
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cell.is_start = True
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maze.start = cell
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elif char == 'E':
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cell.is_exit = True
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maze.exit = cell
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maze.grid[x][y] = cell
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if not maze.start or not maze.exit:
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raise ValueError("Лабиринт должен содержать старт (S) и выход (E)")
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return maze
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class PathFindingStrategy(ABC):
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@abstractmethod
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def find_path(self, maze, start, exit_cell):
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pass
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class BFSPathFinding(PathFindingStrategy):
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def find_path(self, maze, start, exit_cell):
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queue = deque([start])
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visited = {start: None}
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visited_count = 0
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while queue:
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current = queue.popleft()
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visited_count += 1
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if exit_cell is not None and current == exit_cell:
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path = []
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while current:
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path.append(current)
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current = visited[current]
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return path[::-1], visited_count
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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[neighbor] = current
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queue.append(neighbor)
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return [], visited_count
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class DFSPathFinding(PathFindingStrategy):
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def find_path(self, maze, start, exit_cell):
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stack = [start]
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visited = {start: None}
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visited_count = 0
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while stack:
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current = stack.pop()
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visited_count += 1
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if exit_cell is not None and current == exit_cell:
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path = []
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while current:
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path.append(current)
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current = visited[current]
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return path[::-1], visited_count
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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[neighbor] = current
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stack.append(neighbor)
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return [], visited_count
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class AStarPathFinding(PathFindingStrategy):
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def heuristic(self, a, b):
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if b is None:
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return 0
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return abs(a.x - b.x) + abs(a.y - b.y)
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def find_path(self, maze, start, exit_cell):
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open_set = [(0, 0, start, None)]
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heapq.heapify(open_set)
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g_score = {start: 0}
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came_from = {}
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visited_count = 0
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while open_set:
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_, _, current, parent = heapq.heappop(open_set)
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if current in came_from:
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continue
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visited_count += 1
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came_from[current] = parent
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if exit_cell is not None and current == exit_cell:
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path = []
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while current:
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path.append(current)
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current = came_from[current]
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return path[::-1], visited_count
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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 neighbor not in g_score or tentative_g < g_score[neighbor]:
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g_score[neighbor] = tentative_g
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f_score = tentative_g + self.heuristic(neighbor, exit_cell)
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heapq.heappush(open_set, (f_score, id(neighbor), neighbor, current))
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return [], visited_count
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class SearchStats:
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def __init__(self, path, visited_count, time_ms):
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self.path = path
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self.path_length = len(path)
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self.visited_count = visited_count
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self.time_ms = time_ms
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class Observer(ABC):
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@abstractmethod
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def update(self, event):
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pass
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class ConsoleView(Observer):
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def update(self, event):
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if event['type'] == 'path_found':
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self.render(event['maze'], event.get('player_pos'), event['path'])
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elif event['type'] == 'maze_loaded':
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print(f"Лабиринт загружен: {event['maze'].width}x{event['maze'].height}")
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elif event['type'] == 'search_start':
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print(f"Поиск пути алгоритмом {event['strategy']}...")
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elif event['type'] == 'search_end':
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print(
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f"Путь найден: длина {event['stats'].path_length}, посещено клеток {event['stats'].visited_count}, время {event['stats'].time_ms:.3f}мс")
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def render(self, maze, player_pos=None, path=None):
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os.system('cls' if os.name == 'nt' else 'clear')
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path_set = set((c.x, c.y) for c in path) if path else set()
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for y in range(maze.height):
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for x in range(maze.width):
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cell = maze.get_cell(x, y)
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if player_pos and (x, y) == (player_pos.x, player_pos.y):
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print('P', end='')
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elif cell.is_start:
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print('S', end='')
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elif cell.is_exit:
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print('E', end='')
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elif (x, y) in path_set:
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print('.', end='')
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elif cell.is_wall:
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print('#', end='')
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else:
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print(' ', end='')
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print()
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class MazeSolver:
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def __init__(self, maze, strategy=None):
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self.maze = maze
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self.strategy = strategy
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self.observers = []
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def set_strategy(self, strategy):
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self.strategy = strategy
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def add_observer(self, observer):
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self.observers.append(observer)
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def notify(self, event):
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for observer in self.observers:
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observer.update(event)
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def solve(self):
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if not self.strategy:
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raise ValueError("Стратегия не задана")
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self.notify({'type': 'search_start', 'strategy': type(self.strategy).__name__})
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start_time = time.perf_counter()
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if self.maze.exit is None:
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path, visited = self.strategy.find_path(self.maze, self.maze.start, None)
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else:
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path, visited = 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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stats = SearchStats(path, visited, time_ms)
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self.notify({'type': 'search_end', 'stats': stats, 'strategy': type(self.strategy).__name__})
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self.notify({'type': 'path_found', 'maze': self.maze, 'path': path})
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return stats
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def is_path_exists(maze):
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if maze.exit is None:
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return False
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queue = deque([maze.start])
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visited = {maze.start}
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while queue:
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current = queue.popleft()
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if current == maze.exit:
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return True
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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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queue.append(neighbor)
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return False
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def generate_maze(width, height, wall_density=0.3, seed=42):
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np.random.seed(seed)
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maze = Maze(width, height)
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for x in range(width):
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for y in range(height):
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if x == 0 or x == width - 1 or y == 0 or y == height - 1:
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maze.grid[x][y] = Cell(x, y, True)
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else:
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is_wall = np.random.random() < wall_density
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maze.grid[x][y] = Cell(x, y, is_wall)
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maze.start = maze.get_cell(1, 1)
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maze.start.is_wall = False
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maze.start.is_start = True
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maze.grid[1][1] = maze.start
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maze.grid[1][2] = Cell(1, 2, False)
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maze.grid[2][1] = Cell(2, 1, False)
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maze.exit = maze.get_cell(width - 2, height - 2)
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maze.exit.is_wall = False
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maze.exit.is_exit = True
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maze.grid[width - 2][height - 3] = Cell(width - 2, height - 3, False)
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maze.grid[width - 3][height - 2] = Cell(width - 3, height - 2, False)
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if not is_path_exists(maze):
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for x in range(1, width - 1):
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for y in range(1, height - 1):
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if np.random.random() < 0.5:
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maze.grid[x][y].is_wall = False
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if not is_path_exists(maze):
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for x in range(1, width - 1):
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for y in range(1, height - 1):
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if x == 1 and y == 1:
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continue
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if x == width - 2 and y == height - 2:
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continue
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maze.grid[x][y].is_wall = False
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return maze
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def generate_empty_maze(width, height):
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maze = Maze(width, height)
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for x in range(width):
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for y in range(height):
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maze.grid[x][y] = Cell(x, y, False)
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maze.start = maze.get_cell(0, 0)
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maze.start.is_start = True
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maze.exit = maze.get_cell(width - 1, height - 1)
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maze.exit.is_exit = True
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return maze
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def generate_no_exit_maze(width, height):
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maze = Maze(width, height)
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np.random.seed(123)
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for x in range(width):
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for y in range(height):
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if x == 0 or x == width - 1 or y == 0 or y == height - 1:
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maze.grid[x][y] = Cell(x, y, True)
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else:
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is_wall = np.random.random() < 0.3
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maze.grid[x][y] = Cell(x, y, is_wall)
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maze.start = maze.get_cell(1, 1)
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maze.start.is_wall = False
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maze.start.is_start = True
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maze.grid[1][1] = maze.start
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maze.grid[1][2] = Cell(1, 2, False)
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maze.grid[2][1] = Cell(2, 1, False)
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maze.exit = None
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return maze
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def save_maze_to_file(maze, filename):
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with open(filename, 'w') as f:
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for y in range(maze.height):
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for x in range(maze.width):
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cell = maze.get_cell(x, y)
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if cell.is_start:
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f.write('S')
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elif cell.is_exit:
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f.write('E')
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elif cell.is_wall:
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f.write('#')
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else:
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f.write(' ')
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f.write('\n')
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def visualize_maze(maze, path=None, title="Лабиринт", ax=None):
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grid = np.zeros((maze.height, maze.width))
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for y in range(maze.height):
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for x in range(maze.width):
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cell = maze.get_cell(x, y)
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if cell.is_wall:
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grid[y, x] = 1
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elif cell.is_start:
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grid[y, x] = 2
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elif cell.is_exit:
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grid[y, x] = 3
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if ax is None:
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fig, ax = plt.subplots(figsize=(8, 8))
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cmap = plt.cm.colors.ListedColormap(['white', 'black', 'green', 'red'])
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ax.imshow(grid, cmap=cmap, interpolation='nearest')
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if path:
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path_x = [cell.x for cell in path]
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path_y = [cell.y for cell in path]
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ax.plot(path_x, path_y, 'b-', linewidth=2, label='Путь')
|
|||
|
|
ax.set_title(title)
|
|||
|
|
ax.set_xticks([])
|
|||
|
|
ax.set_yticks([])
|
|||
|
|
|
|||
|
|
def run_experiments():
|
|||
|
|
mazes_data = {
|
|||
|
|
"Маленький (10x10)": generate_maze(10, 10, 0.2, 10),
|
|||
|
|
"Средний (50x50)": generate_maze(50, 50, 0.3, 20),
|
|||
|
|
"Большой (100x100)": generate_maze(100, 100, 0.3, 30),
|
|||
|
|
"Пустой (50x50)": generate_empty_maze(50, 50),
|
|||
|
|
"Без выхода (50x50)": generate_no_exit_maze(50, 50)
|
|||
|
|
}
|
|||
|
|
os.makedirs("mazes", exist_ok=True)
|
|||
|
|
for name, maze in mazes_data.items():
|
|||
|
|
filename = f"mazes/{name.replace(' ', '_').replace('(', '').replace(')', '')}.txt"
|
|||
|
|
save_maze_to_file(maze, filename)
|
|||
|
|
print(f"Сохранён {filename}")
|
|||
|
|
strategies = {
|
|||
|
|
"BFS": BFSPathFinding(),
|
|||
|
|
"DFS": DFSPathFinding(),
|
|||
|
|
"A*": AStarPathFinding()
|
|||
|
|
}
|
|||
|
|
results = []
|
|||
|
|
runs = 5
|
|||
|
|
fig_mazes, axes_mazes = plt.subplots(len(mazes_data), len(strategies) + 1, figsize=(18, 4 * len(mazes_data)))
|
|||
|
|
if len(mazes_data) == 1:
|
|||
|
|
axes_mazes = [axes_mazes]
|
|||
|
|
for row_idx, (maze_name, maze) in enumerate(mazes_data.items()):
|
|||
|
|
visualize_maze(maze, title=f"{maze_name}", ax=axes_mazes[row_idx][0])
|
|||
|
|
for col_idx, (strat_name, strategy) in enumerate(strategies.items()):
|
|||
|
|
solver = MazeSolver(maze, strategy)
|
|||
|
|
times = []
|
|||
|
|
visited_counts = []
|
|||
|
|
path_lengths = []
|
|||
|
|
best_path = None
|
|||
|
|
for _ in range(runs):
|
|||
|
|
stats = solver.solve()
|
|||
|
|
times.append(stats.time_ms)
|
|||
|
|
visited_counts.append(stats.visited_count)
|
|||
|
|
path_lengths.append(stats.path_length)
|
|||
|
|
if stats.path:
|
|||
|
|
best_path = stats.path
|
|||
|
|
avg_time = np.mean(times)
|
|||
|
|
avg_visited = np.mean(visited_counts)
|
|||
|
|
avg_path = np.mean(path_lengths)
|
|||
|
|
results.append([maze_name, strat_name, avg_time, avg_visited, avg_path])
|
|||
|
|
print(f"{maze_name} - {strat_name}: Время={avg_time:.3f}мс, Посещено={avg_visited:.0f}, Длина пути={avg_path:.0f}")
|
|||
|
|
visualize_maze(maze, best_path, f"{maze_name} - {strat_name}", ax=axes_mazes[row_idx][col_idx + 1])
|
|||
|
|
plt.tight_layout()
|
|||
|
|
plt.savefig('mazes_visualization.png')
|
|||
|
|
plt.close()
|
|||
|
|
with open('results.csv', 'w', newline='', encoding='utf-8-sig') as f:
|
|||
|
|
writer = csv.writer(f)
|
|||
|
|
writer.writerow(["Лабиринт", "Стратегия", "Время_мс", "Посещено", "Длина_пути"])
|
|||
|
|
writer.writerows(results)
|
|||
|
|
print("\nРезультаты сохранены в results.csv")
|
|||
|
|
return results
|
|||
|
|
|
|||
|
|
def plot_results(results):
|
|||
|
|
strategies = ["BFS", "DFS", "A*"]
|
|||
|
|
mazes = ["Маленький (10x10)", "Средний (50x50)", "Большой (100x100)", "Пустой (50x50)", "Без выхода (50x50)"]
|
|||
|
|
data = {}
|
|||
|
|
for strat in strategies:
|
|||
|
|
data[strat] = {"times": [], "visited": [], "paths": []}
|
|||
|
|
for row in results:
|
|||
|
|
maze, strat, time_ms, visited, path_len = row
|
|||
|
|
data[strat]["times"].append(time_ms)
|
|||
|
|
data[strat]["visited"].append(visited)
|
|||
|
|
data[strat]["paths"].append(path_len)
|
|||
|
|
|
|||
|
|
fig, axes = plt.subplots(1, 3, figsize=(18, 6))
|
|||
|
|
x = np.arange(len(mazes))
|
|||
|
|
width = 0.25
|
|||
|
|
colors = {'BFS': 'skyblue', 'DFS': 'lightgreen', 'A*': 'salmon'}
|
|||
|
|
|
|||
|
|
for i, strat in enumerate(strategies):
|
|||
|
|
offset = (i - 1) * width
|
|||
|
|
times_display = [t if t > 0 else 0.001 for t in data[strat]["times"]]
|
|||
|
|
bars = axes[0].bar(x + offset, times_display, width, label=strat, color=colors[strat])
|
|||
|
|
for bar, val in zip(bars, data[strat]["times"]):
|
|||
|
|
if val > 0:
|
|||
|
|
axes[0].text(bar.get_x() + bar.get_width() / 2, bar.get_height() * 1.1,
|
|||
|
|
f'{val:.2f}', ha='center', va='bottom', fontsize=8, rotation=90)
|
|||
|
|
axes[0].set_title("Время выполнения (мс)")
|
|||
|
|
axes[0].set_xticks(x)
|
|||
|
|
axes[0].set_xticklabels(mazes, rotation=15, ha='right')
|
|||
|
|
axes[0].set_ylabel("Время (мс)")
|
|||
|
|
axes[0].set_yscale('log')
|
|||
|
|
axes[0].legend()
|
|||
|
|
axes[0].grid(axis='y', alpha=0.3)
|
|||
|
|
|
|||
|
|
for i, strat in enumerate(strategies):
|
|||
|
|
offset = (i - 1) * width
|
|||
|
|
visited_display = [v if v > 0 else 1 for v in data[strat]["visited"]]
|
|||
|
|
bars = axes[1].bar(x + offset, visited_display, width, label=strat, color=colors[strat])
|
|||
|
|
for bar, val in zip(bars, data[strat]["visited"]):
|
|||
|
|
if val > 0:
|
|||
|
|
axes[1].text(bar.get_x() + bar.get_width() / 2, bar.get_height() * 1.1,
|
|||
|
|
f'{val:.0f}', ha='center', va='bottom', fontsize=8, rotation=90)
|
|||
|
|
axes[1].set_title("Посещено клеток")
|
|||
|
|
axes[1].set_xticks(x)
|
|||
|
|
axes[1].set_xticklabels(mazes, rotation=15, ha='right')
|
|||
|
|
axes[1].set_ylabel("Количество клеток")
|
|||
|
|
axes[1].set_yscale('log')
|
|||
|
|
axes[1].legend()
|
|||
|
|
axes[1].grid(axis='y', alpha=0.3)
|
|||
|
|
|
|||
|
|
for i, strat in enumerate(strategies):
|
|||
|
|
offset = (i - 1) * width
|
|||
|
|
paths_display = [p if p > 0 else 1 for p in data[strat]["paths"]]
|
|||
|
|
bars = axes[2].bar(x + offset, paths_display, width, label=strat, color=colors[strat])
|
|||
|
|
for bar, val in zip(bars, data[strat]["paths"]):
|
|||
|
|
height = bar.get_height()
|
|||
|
|
axes[2].text(bar.get_x() + bar.get_width() / 2, height * 1.1,
|
|||
|
|
f'{val:.0f}', ha='center', va='bottom', fontsize=8, rotation=90)
|
|||
|
|
axes[2].set_title("Длина найденного пути")
|
|||
|
|
axes[2].set_xticks(x)
|
|||
|
|
axes[2].set_xticklabels(mazes, rotation=15, ha='right')
|
|||
|
|
axes[2].set_ylabel("Длина пути")
|
|||
|
|
axes[2].set_yscale('log')
|
|||
|
|
axes[2].legend()
|
|||
|
|
axes[2].grid(axis='y', alpha=0.3)
|
|||
|
|
|
|||
|
|
plt.tight_layout()
|
|||
|
|
plt.savefig('comparative_results.png')
|
|||
|
|
plt.show()
|
|||
|
|
print("Сравнительные графики сохранены в comparative_results.png")
|
|||
|
|
|
|||
|
|
if __name__ == "__main__":
|
|||
|
|
print("\nГенерация лабиринтов и запуск экспериментов\n")
|
|||
|
|
results = run_experiments()
|
|||
|
|
print("\nСоздание графиков")
|
|||
|
|
plot_results(results)
|
|||
|
|
print("\nЭксперименты завершены")
|
|||
|
|
print("\nСозданные файлы:")
|
|||
|
|
print(" - 5 текстовых файлов с лабиринтами")
|
|||
|
|
print(" - mazes_visualization.png: Визуализация всех лабиринтов с путями")
|
|||
|
|
print(" - results.csv: Таблица с числовыми результатами")
|
|||
|
|
print(" - comparative_results.png: Сравнительные графики (Время, Посещено, Длина пути)")
|
|||
|
|
print("\nСводка результатов:")
|
|||
|
|
for row in results:
|
|||
|
|
maze, strat, time_ms, visited, path_len = row
|
|||
|
|
print(f"{maze:20s} | {strat:5s} | Время: {time_ms:8.3f}мс | Посещено: {visited:6.0f} | Путь: {path_len:4.0f}")
|