370 lines
11 KiB
Python
370 lines
11 KiB
Python
import sys
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import csv
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from collections import deque
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import heapq
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import time
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import matplotlib.pyplot as plt
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import numpy as np
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# ---------- Модель ----------
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class Node:
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def __init__(self, x, y):
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self.x = x
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self.y = y
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self.wall = False
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self.start_flag = False
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self.exit_flag = False
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@property
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def is_wall(self):
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return self.wall
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@is_wall.setter
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def is_wall(self, val):
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self.wall = val
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@property
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def is_start(self):
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return self.start_flag
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@is_start.setter
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def is_start(self, val):
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self.start_flag = val
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@property
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def is_exit(self):
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return self.exit_flag
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@is_exit.setter
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def is_exit(self, val):
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self.exit_flag = val
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def passable(self):
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return not self.wall
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class Grid:
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def __init__(self, w, h):
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self.w = w
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self.h = h
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self.cells = [[Node(x, y) for x in range(w)] for y in range(h)]
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self.start_node = None
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self.exit_node = None
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def get(self, x, y):
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if 0 <= x < self.w and 0 <= y < self.h:
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return self.cells[y][x]
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return None
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def set_type(self, x, y, typ):
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cell = self.get(x, y)
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if not cell:
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return
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if typ == 'wall':
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cell.is_wall = True
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elif typ == 'start':
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if self.start_node:
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self.start_node.is_start = False
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cell.is_start = True
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cell.is_wall = False
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self.start_node = cell
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elif typ == 'exit':
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if self.exit_node:
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self.exit_node.is_exit = False
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cell.is_exit = True
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cell.is_wall = False
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self.exit_node = cell
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elif typ == 'path':
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cell.is_wall = False
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def neighbors(self, node):
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res = []
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dirs = [(0, -1), (0, 1), (-1, 0), (1, 0)]
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for dx, dy in dirs:
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nx, ny = node.x + dx, node.y + dy
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nb = self.get(nx, ny)
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if nb and nb.passable():
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res.append(nb)
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return res
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class Loader:
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def load(self, fname):
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raise NotImplementedError
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class TxtLoader(Loader):
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def load(self, fname):
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with open(fname, 'r') as f:
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lines = [line.rstrip('\n') for line in f.readlines()]
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h = len(lines)
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w = max(len(line) for line in lines) if h > 0 else 0
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start_cnt = 0
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exit_cnt = 0
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grid = Grid(w, h)
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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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grid.set_type(x, y, "wall")
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elif ch == "S":
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grid.set_type(x, y, "start")
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start_cnt += 1
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elif ch == "E":
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grid.set_type(x, y, "exit")
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exit_cnt += 1
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else:
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grid.set_type(x, y, 'path')
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if start_cnt != 1 or exit_cnt != 1:
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raise ValueError(f"Bad maze: S={start_cnt}, E={exit_cnt}")
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return grid
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# ---------- Поисковые стратегии ----------
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class SearchAlgo:
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def search(self, grid, start, goal):
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raise NotImplementedError
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def _reconstruct(self, parent, start, goal):
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path = []
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cur = goal
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while cur:
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path.append(cur)
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cur = parent.get(cur)
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path.reverse()
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return path
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def visited_count(self):
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return getattr(self, '_visited_num', 0)
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class BFSAlgo(SearchAlgo):
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def search(self, grid, start, goal):
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q = deque([start])
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parent = {start: None}
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seen = {start}
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while q:
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cur = q.popleft()
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if cur == goal:
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self._visited_num = len(seen)
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return self._reconstruct(parent, start, goal)
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for nb in grid.neighbors(cur):
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if nb not in seen:
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seen.add(nb)
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parent[nb] = cur
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q.append(nb)
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self._visited_num = len(seen)
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return []
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class DFSAlgo(SearchAlgo):
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def search(self, grid, start, goal):
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stack = [start]
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parent = {start: None}
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seen = {start}
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while stack:
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cur = stack.pop()
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if cur == goal:
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self._visited_num = len(seen)
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return self._reconstruct(parent, start, goal)
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for nb in grid.neighbors(cur):
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if nb not in seen:
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seen.add(nb)
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parent[nb] = cur
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stack.append(nb)
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self._visited_num = len(seen)
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return []
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class AStarAlgo(SearchAlgo):
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def _h(self, a, b):
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return abs(a.x - b.x) + abs(a.y - b.y)
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def search(self, grid, start, goal):
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heap = []
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cnt = 0
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start_f = self._h(start, goal)
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heapq.heappush(heap, (start_f, cnt, start))
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cnt += 1
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parent = {}
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g_score = {start: 0}
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f_score = {start: start_f}
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seen = set()
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while heap:
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cur_f, _, cur = heapq.heappop(heap)
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seen.add(cur)
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if cur == goal:
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self._visited_num = len(seen)
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return self._reconstruct(parent, start, goal)
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if cur_f > f_score.get(cur, float('inf')):
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continue
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for nb in grid.neighbors(cur):
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tentative_g = g_score[cur] + 1
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if tentative_g < g_score.get(nb, float('inf')):
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parent[nb] = cur
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g_score[nb] = tentative_g
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new_f = tentative_g + self._h(nb, goal)
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f_score[nb] = new_f
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heapq.heappush(heap, (new_f, cnt, nb))
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cnt += 1
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self._visited_num = len(seen)
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return []
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class Solver:
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def __init__(self, grid):
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self.grid = grid
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self.algo = None
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def set_algo(self, algo):
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self.algo = algo
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def solve(self):
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if not self.algo:
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return None
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t0 = time.perf_counter()
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path = self.algo.search(self.grid, self.grid.start_node, self.grid.exit_node)
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t1 = time.perf_counter()
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elapsed = (t1 - t0) * 1000
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return {
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'time_ms': elapsed,
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'visited_cells': self.algo.visited_count(),
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'path_length': len(path)
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}
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def experiment(maze_file, algo, runs=5):
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loader = TxtLoader()
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grid = loader.load(maze_file)
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total_t = 0.0
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total_v = 0
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total_l = 0
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for _ in range(runs):
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s = Solver(grid)
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s.set_algo(algo)
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stats = s.solve()
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if stats:
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total_t += stats['time_ms']
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total_v += stats['visited_cells']
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total_l += stats['path_length']
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return {
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'time_ms': total_t / runs,
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'visited_cells': total_v / runs,
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'path_length': total_l / runs
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}
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def make_plots(results):
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mazes = list(set(r['maze'] for r in results))
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algos = ['BFS', 'DFS', 'AStar']
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fig, axes = plt.subplots(1, 3, figsize=(15, 5))
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x = np.arange(len(mazes))
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width = 0.25
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# Время
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for i, algo in enumerate(algos):
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times = []
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for m in mazes:
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val = next((r['time_ms'] for r in results if r['maze'] == m and r['strategy'] == algo), 0)
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times.append(val)
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axes[0].bar(x + i * width, times, width, label=algo)
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axes[0].set_xlabel('Maze')
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axes[0].set_ylabel('Time (ms)')
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axes[0].set_title('Execution time')
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axes[0].set_xticks(x + width)
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axes[0].set_xticklabels(mazes, rotation=45, ha='right')
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axes[0].legend()
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axes[0].grid(True, alpha=0.3)
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# Посещённые клетки
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for i, algo in enumerate(algos):
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visited = []
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for m in mazes:
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val = next((r['visited_cells'] for r in results if r['maze'] == m and r['strategy'] == algo), 0)
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visited.append(val)
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axes[1].bar(x + i * width, visited, width, label=algo)
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axes[1].set_xlabel('Maze')
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axes[1].set_ylabel('Visited cells')
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axes[1].set_title('Visited cells comparison')
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axes[1].set_xticks(x + width)
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axes[1].set_xticklabels(mazes, rotation=45, ha='right')
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axes[1].legend()
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axes[1].grid(True, alpha=0.3)
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# Длина пути
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for i, algo in enumerate(algos):
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lengths = []
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for m in mazes:
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val = next((r['path_length'] for r in results if r['maze'] == m and r['strategy'] == algo), 0)
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lengths.append(val)
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axes[2].bar(x + i * width, lengths, width, label=algo)
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axes[2].set_xlabel('Maze')
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axes[2].set_ylabel('Path length')
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axes[2].set_title('Path length comparison')
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axes[2].set_xticks(x + width)
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axes[2].set_xticklabels(mazes, rotation=45, ha='right')
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axes[2].legend()
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axes[2].grid(True, alpha=0.3)
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plt.tight_layout()
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plt.savefig('performance_plot.png', dpi=150, bbox_inches='tight')
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plt.show()
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if __name__ == "__main__":
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test_mazes = [
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("maze1.txt", "Small 10x6"),
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("maze10x10.txt", "Medium 10x10"),
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("maze20x20.txt", "Large 20x20"),
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("maze_empty.txt", "Empty 15x15"),
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("maze_no_exit.txt", "No exit 10x10")
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]
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algorithms = [
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("BFS", BFSAlgo()),
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("DFS", DFSAlgo()),
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("AStar", AStarAlgo())
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]
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results = []
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for fname, name in test_mazes:
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print(f"Benchmarking {name}...")
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for algo_name, algo in algorithms:
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try:
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stat = experiment(fname, algo, runs=3)
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results.append({
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'maze': name,
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'strategy': algo_name,
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'time_ms': stat['time_ms'],
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'visited_cells': stat['visited_cells'],
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'path_length': stat['path_length']
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})
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print(f" {algo_name}: time={stat['time_ms']:.3f}ms, visited={stat['visited_cells']:.0f}, length={stat['path_length']:.0f}")
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except Exception as e:
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print(f" {algo_name}: failed - {e}")
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results.append({
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'maze': name,
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'strategy': algo_name,
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'time_ms': -1,
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'visited_cells': -1,
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'path_length': -1
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})
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valid = [r for r in results if r['time_ms'] >= 0]
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with open('experiment_data.csv', 'w', newline='', encoding='utf-8') as f:
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writer = csv.DictWriter(f, fieldnames=['maze', 'strategy', 'time_ms', 'visited_cells', 'path_length'])
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writer.writeheader()
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writer.writerows(valid)
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if valid:
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make_plots(valid)
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print("\nData saved to experiment_data.csv")
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print("Plot saved to performance_plot.png") |