376 lines
10 KiB
Python
376 lines
10 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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class Tile:
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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 = False
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self._exit = False
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@property
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def x(self):
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return self._x
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@property
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def y(self):
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return self._y
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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, v):
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self._wall = v
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@property
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def is_start(self):
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return self._start
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@is_start.setter
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def is_start(self, v):
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self._start = v
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@property
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def is_exit(self):
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return self._exit
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@is_exit.setter
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def is_exit(self, v):
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self._exit = v
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def passable(self):
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return not self._wall
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class Maze:
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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 = [[Tile(x, y) for x in range(w)] for y in range(h)]
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self._start = None
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self._exit = None
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@property
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def width(self):
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return self._w
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@property
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def height(self):
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return self._h
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@property
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def start(self):
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return self._start
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@property
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def exit(self):
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return self._exit
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def get_cell(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_cell(self, x, y, kind):
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c = self.get_cell(x, y)
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if not c:
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return
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if kind == 'wall':
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c.is_wall = True
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elif kind == 'start':
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if self._start:
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self._start.is_start = False
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c.is_start = True
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c.is_wall = False
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self._start = c
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elif kind == 'exit':
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if self._exit:
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self._exit.is_exit = False
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c.is_exit = True
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c.is_wall = False
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self._exit = c
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elif kind == 'path':
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c.is_wall = False
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def neighbours(self, cell):
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res = []
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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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nb = self.get_cell(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 MazeLoader:
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def load(self, fname):
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raise NotImplementedError
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class TextMazeLoader(MazeLoader):
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def load(self, fname):
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with open(fname, 'r') as f:
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lines = [ln.rstrip('\n') for ln in f.readlines()]
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h = len(lines)
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w = max(len(ln) for ln in lines) if h else 0
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cntS = 0
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cntE = 0
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m = Maze(w, h)
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for y, ln in enumerate(lines):
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for x, ch in enumerate(ln):
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if ch == '#':
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m.set_cell(x, y, 'wall')
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elif ch == 'S':
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m.set_cell(x, y, 'start')
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cntS += 1
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elif ch == 'E':
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m.set_cell(x, y, 'exit')
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cntE += 1
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else:
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m.set_cell(x, y, 'path')
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if cntS != 1 or cntE != 1:
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raise ValueError(f"Bad maze: S={cntS}, E={cntE}")
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return m
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class PathFinder:
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def find(self, maze, 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, '_vis', 0)
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class BFS(PathFinder):
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def find(self, maze, start, goal):
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q = deque([start])
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parent = {start: None}
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visited = {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._vis = len(visited)
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return self._reconstruct(parent, start, goal)
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for nb in maze.neighbours(cur):
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if nb not in visited:
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visited.add(nb)
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parent[nb] = cur
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q.append(nb)
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self._vis = len(visited)
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return []
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class DFS(PathFinder):
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def find(self, maze, start, goal):
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stack = [start]
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parent = {start: None}
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visited = {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._vis = len(visited)
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return self._reconstruct(parent, start, goal)
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for nb in maze.neighbours(cur):
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if nb not in visited:
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visited.add(nb)
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parent[nb] = cur
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stack.append(nb)
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self._vis = len(visited)
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return []
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class AStar(PathFinder):
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def _h(self, cell, goal):
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return abs(cell.x - goal.x) + abs(cell.y - goal.y)
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def find(self, maze, start, goal):
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heap = []
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idx = 0
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start_f = self._h(start, goal)
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heapq.heappush(heap, (start_f, idx, start))
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idx += 1
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parent = {}
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g = {start: 0}
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f = {start: start_f}
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visited = set()
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while heap:
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cur_f, _, cur = heapq.heappop(heap)
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visited.add(cur)
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if cur == goal:
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self._vis = len(visited)
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return self._reconstruct(parent, start, goal)
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if cur_f > f.get(cur, float('inf')):
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continue
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for nb in maze.neighbours(cur):
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new_g = g[cur] + 1
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if new_g < g.get(nb, float('inf')):
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parent[nb] = cur
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g[nb] = new_g
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new_f = new_g + self._h(nb, goal)
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f[nb] = new_f
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heapq.heappush(heap, (new_f, idx, nb))
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idx += 1
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self._vis = len(visited)
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return []
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class Solver:
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def __init__(self, maze):
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self._maze = maze
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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 run(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.find(self._maze, self._maze.start, self._maze.exit)
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t1 = time.perf_counter()
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return {
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'time_ms': (t1 - t0) * 1000,
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'visited': self._algo.visited_count(),
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'path_len': len(path)
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}
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def benchmark(maze_file, algorithm, runs=5):
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loader = TextMazeLoader()
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maze = 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(maze)
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s.set_algo(algorithm)
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stats = s.run()
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if stats:
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total_t += stats['time_ms']
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total_v += stats['visited']
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total_l += stats['path_len']
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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 create_plots(results):
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mazes = sorted(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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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_title('Execution time (ms)')
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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(alpha=0.3)
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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_title('Visited cells')
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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(alpha=0.3)
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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_title('Path length')
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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(alpha=0.3)
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plt.tight_layout()
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plt.savefig('performance_comparison_2-nd-exercise.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", BFS()),
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("DFS", DFS()),
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("AStar", AStar())
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]
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all_results = []
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for fname, label in test_mazes:
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print(f"Testing {label}...")
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for name, algo in algorithms:
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try:
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stat = benchmark(fname, algo, runs=3)
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all_results.append({
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'maze': label,
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'strategy': 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" {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" {name}: ERROR - {e}")
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all_results.append({
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'maze': label,
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'strategy': 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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good = [r for r in all_results if r['time_ms'] >= 0]
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with open('experiment_results_2-nd-exercise.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(good)
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if good:
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create_plots(good)
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print("\nResults saved to experiment_results_2-nd-exercise.csv")
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print("Plot saved to performance_comparison_2-nd-exercise.png") |