novikovsd
dbd088daff
реализован запуск эксперимента с сохранением результатов в csv файле и png графиков в папке lab2_result
493 lines
16 KiB
Python
493 lines
16 KiB
Python
import sys
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import time
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import csv
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from collections import deque
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from heapq import heappush, heappop
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from abc import ABC, abstractmethod
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from typing import List, Optional, Tuple, Dict, Any
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import os
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RESULTS_DIR = "lab2_results"
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class Cell:
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def __init__(self, x: int, y: int, is_wall: bool = 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) -> bool:
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return not self.is_wall
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def __repr__(self):
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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: int, height: int):
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self.width = width
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self.height = height
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self.cells: List[List[Cell]] = []
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self.start: Optional[Cell] = None
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self.exit: Optional[Cell] = None
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def set_cell(self, x: int, y: int, cell: Cell):
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if not self.cells:
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self.cells = [[None] * self.width for _ in range(self.height)]
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self.cells[y][x] = cell
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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 get_neighbors(self, cell: Cell) -> List[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: str) -> Maze:
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pass
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class TextFileMazeBuilder(MazeBuilder):
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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)
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maze = Maze(width, height)
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start_cell = None
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exit_cell = None
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for y, line in enumerate(lines):
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for x, ch in enumerate(line):
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is_wall = (ch == '#')
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cell = Cell(x, y, is_wall)
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if ch == 'S':
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cell.is_start = True
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start_cell = cell
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elif ch == 'E':
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cell.is_exit = True
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exit_cell = cell
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maze.set_cell(x, y, cell)
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if start_cell is None or exit_cell is None:
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for y in range(height):
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for x in range(width):
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cell = maze.get_cell(x, y)
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if cell and cell.is_start:
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start_cell = cell
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if cell and cell.is_exit:
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exit_cell = cell
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if start_cell is None:
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raise ValueError("Нет стартовой клетки (S)")
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if exit_cell is None:
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raise ValueError("Нет выходной клетки (E)")
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maze.start = start_cell
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maze.exit = exit_cell
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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: Maze, start: Cell, exit: Cell) -> List[Cell]:
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pass
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class BFSStrategy(PathFindingStrategy):
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def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
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if start == exit:
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self.last_visited = 1
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return [start]
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queue = deque()
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queue.append(start)
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parent = {start: None}
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visited = {start}
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visited_count = 1
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while queue:
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current = queue.popleft()
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if current == exit:
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break
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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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visited_count += 1
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parent[neighbor] = current
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queue.append(neighbor)
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self.last_visited = visited_count
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if exit not in parent:
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return []
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path = []
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cur = exit
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while cur is not None:
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path.append(cur)
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cur = parent[cur]
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path.reverse()
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return path
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class DFSStrategy(PathFindingStrategy):
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def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
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stack = [(start, [start])]
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visited = {start}
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visited_count = 1
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while stack:
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current, path = stack.pop()
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if current == exit:
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self.last_visited = visited_count
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return path
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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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visited_count += 1
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stack.append((neighbor, path + [neighbor]))
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self.last_visited = visited_count
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return []
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class AStarStrategy(PathFindingStrategy):
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def heuristic(self, a: Cell, b: Cell) -> int:
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return abs(a.x - b.x) + abs(a.y - b.y)
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def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
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open_set = []
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counter = 0
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heappush(open_set, (0, counter, start))
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came_from = {}
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g_score = {start: 0}
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f_score = {start: self.heuristic(start, exit)}
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visited_count = 0
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while open_set:
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_, _, current = heappop(open_set)
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visited_count += 1
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if current == exit:
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path = []
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while current in came_from:
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path.append(current)
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current = came_from[current]
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path.append(start)
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path.reverse()
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self.last_visited = visited_count
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return path
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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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came_from[neighbor] = current
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g_score[neighbor] = tentative_g
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f = tentative_g + self.heuristic(neighbor, exit)
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f_score[neighbor] = f
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counter += 1
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heappush(open_set, (f, counter, neighbor))
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self.last_visited = visited_count
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return []
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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):
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return f"Stats(time={self.time_ms:.2f}ms, visited={self.visited_cells}, path_len={self.path_length})"
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class MazeSolver:
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def __init__(self, maze: Maze, strategy: PathFindingStrategy):
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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: PathFindingStrategy):
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self.strategy = strategy
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def attach(self, observer):
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self.observers.append(observer)
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def detach(self, observer):
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self.observers.remove(observer)
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def notify(self, event: str, data: Any = None):
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for obs in self.observers:
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obs.update(event, data)
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def solve(self) -> Tuple[List[Cell], SearchStats]:
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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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elapsed_ms = (end_time - start_time) * 1000.0
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visited_cells = getattr(self.strategy, 'last_visited', len(path) if path else 0)
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stats = SearchStats(elapsed_ms, visited_cells, len(path))
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self.notify("solved", {"path": path, "stats": stats})
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return path, stats
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class Observer(ABC):
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@abstractmethod
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def update(self, event: str, data: Any):
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pass
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class ConsoleView(Observer):
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def __init__(self):
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self.player_pos = None
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self.path = []
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def update(self, event: str, data: Any):
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if event == "maze_loaded":
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self.maze = data["maze"]
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self.render()
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elif event == "player_moved":
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self.player_pos = data["player_cell"]
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self.render()
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elif event == "path_found":
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self.path = data["path"]
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self.render()
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elif event == "solved":
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self.path = data["path"]
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self.render()
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def render(self, maze: Maze = None, player_cell: Cell = None, path: List[Cell] = None):
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if maze:
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self.maze = maze
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if player_cell:
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self.player_pos = player_cell
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if path is not None:
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self.path = path
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if not hasattr(self, 'maze'):
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print("Нет лабиринта для отображения")
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return
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for y in range(self.maze.height):
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row = ""
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for x in range(self.maze.width):
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cell = self.maze.get_cell(x, y)
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if cell is None:
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row += " "
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continue
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if self.player_pos and cell == self.player_pos:
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row += "P"
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elif cell == self.maze.start:
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row += "S"
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elif cell == self.maze.exit:
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row += "E"
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elif self.path and cell in self.path:
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row += "."
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elif cell.is_wall:
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row += "#"
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else:
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row += " "
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print(row)
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print()
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class MoveCommand(ABC):
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@abstractmethod
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def execute(self):
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pass
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@abstractmethod
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def undo(self):
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pass
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class Player:
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def __init__(self, start_cell: Cell):
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self.current_cell = start_cell
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def move_to(self, cell: Cell):
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self.current_cell = cell
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class MoveCommandImpl(MoveCommand):
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def __init__(self, player: Player, direction: str, maze: Maze):
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self.player = player
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self.direction = direction
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self.maze = maze
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self.previous_cell = player.current_cell
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def execute(self):
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dx, dy = 0, 0
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if self.direction == 'w':
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dy = -1
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elif self.direction == 's':
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dy = 1
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elif self.direction == 'a':
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dx = -1
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elif self.direction == 'd':
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dx = 1
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else:
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return False
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new_x = self.player.current_cell.x + dx
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new_y = self.player.current_cell.y + dy
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new_cell = self.maze.get_cell(new_x, new_y)
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if new_cell and new_cell.is_passable():
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self.player.move_to(new_cell)
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return True
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return False
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def undo(self):
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self.player.move_to(self.previous_cell)
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def ensure_results_dir():
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if not os.path.exists(RESULTS_DIR):
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os.makedirs(RESULTS_DIR)
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print(f"Создана папка: {RESULTS_DIR}")
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def generate_test_maze_file(filename: str, maze_type: str):
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full_path = os.path.join(RESULTS_DIR, filename)
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if maze_type == "small":
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lines = [
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"##########",
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"#S #",
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"# #",
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"# #",
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"# #",
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"# #",
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"# #",
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"# #",
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"# E#",
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"##########"
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]
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elif maze_type == "medium":
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height, width = 50, 50
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lines = []
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for y in range(height):
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row = []
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for x in range(width):
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if y == 0 or y == height-1 or x == 0 or x == width-1:
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row.append('#')
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elif (y % 5 == 0 and x % 7 == 0) or (y % 8 == 0 and x % 3 == 0):
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row.append('#')
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else:
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row.append(' ')
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row_str = ''.join(row)
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lines.append(row_str)
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lines[1] = 'S' + lines[1][1:]
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lines[height-2] = lines[height-2][:width-2] + 'E' + lines[height-2][width-1:]
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elif maze_type == "large":
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import random
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height, width = 100, 100
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random.seed(42)
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lines = []
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for y in range(height):
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row = []
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for x in range(width):
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if y == 0 or y == height-1 or x == 0 or x == width-1:
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row.append('#')
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else:
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if random.random() < 0.2:
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row.append('#')
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else:
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row.append(' ')
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lines.append(''.join(row))
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lines[1] = 'S' + lines[1][1:]
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lines[height-2] = lines[height-2][:width-2] + 'E' + lines[height-2][width-1:]
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elif maze_type == "empty":
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height, width = 50, 50
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lines = []
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for y in range(height):
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if y == 0 or y == height-1:
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lines.append('#' * width)
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else:
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lines.append('#' + ' ' * (width-2) + '#')
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lines[1] = 'S' + lines[1][1:]
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lines[height-2] = lines[height-2][:width-2] + 'E' + lines[height-2][width-1:]
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elif maze_type == "no_exit":
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lines = [
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"##########",
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"#S #",
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"# #",
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"# #",
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"# #",
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"# #",
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"# #",
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"# #",
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"# #",
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"##########"
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]
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else:
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raise ValueError("Unknown maze type")
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with open(full_path, 'w', encoding='utf-8') as f:
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f.write('\n'.join(lines))
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def run_experiment():
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ensure_results_dir()
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maze_types = ["small", "medium", "large", "empty", "no_exit"]
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strategies = {
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"BFS": BFSStrategy(),
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"DFS": DFSStrategy(),
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"AStar": AStarStrategy()
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}
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results = []
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for maze_type in maze_types:
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filename = f"maze_{maze_type}.txt"
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generate_test_maze_file(filename, maze_type)
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full_path = os.path.join(RESULTS_DIR, filename)
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builder = TextFileMazeBuilder()
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try:
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maze = builder.build_from_file(full_path)
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except ValueError as e:
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print(f"Лабиринт {maze_type} пропущен: {e}")
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continue
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for strat_name, strat_obj in strategies.items():
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times = []
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path_lengths = []
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visited_counts = []
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for run in range(5):
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solver = MazeSolver(maze, strat_obj)
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path, stats = solver.solve()
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times.append(stats.time_ms)
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path_lengths.append(stats.path_length)
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visited_counts.append(stats.visited_cells)
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avg_time = sum(times) / len(times)
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avg_path_len = sum(path_lengths) / len(path_lengths)
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avg_visited = sum(visited_counts) / len(visited_counts)
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results.append({
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"maze": maze_type,
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"strategy": strat_name,
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"avg_time_ms": avg_time,
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"avg_visited": avg_visited,
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"avg_path_length": avg_path_len
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})
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print(f"{maze_type} / {strat_name}: время={avg_time:.2f}ms, посещено={avg_visited:.1f}, путь={avg_path_len:.1f}")
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csv_path = os.path.join(RESULTS_DIR, "experiment_results.csv")
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with open(csv_path, "w", newline='', encoding='utf-8') as f:
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writer = csv.DictWriter(f, fieldnames=["maze", "strategy", "avg_time_ms", "avg_visited", "avg_path_length"])
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writer.writeheader()
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writer.writerows(results)
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try:
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import matplotlib.pyplot as plt
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for maze_type in ["small", "medium", "large", "empty"]:
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data = [r for r in results if r["maze"] == maze_type]
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if not data:
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continue
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names = [d["strategy"] for d in data]
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times = [d["avg_time_ms"] for d in data]
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visited = [d["avg_visited"] for d in data]
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fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 4))
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ax1.bar(names, times)
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ax1.set_title(f"Время (мс) - {maze_type}")
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ax2.bar(names, visited)
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ax2.set_title(f"Посещено клеток - {maze_type}")
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plt.tight_layout()
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plot_path = os.path.join(RESULTS_DIR, f"plot_{maze_type}.png")
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plt.savefig(plot_path)
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plt.close()
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print(f"Графики сохранены в папку {RESULTS_DIR}")
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except ImportError:
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print("matplotlib не установлен. Графики не построены.") |