[2] 3-rd version of maze solver(with rxpirement and other things) ;)

This commit is contained in:
root 2026-09-03 02:21:05 +03:00
parent d37835d9dd
commit b0fccd4611
3 changed files with 288 additions and 19 deletions

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@ -1,6 +1,11 @@
import time
import random
import csv
import os
from collections import deque
import heapq
import matplotlib.pyplot as plt
import numpy as np
class Cell:
def __init__(self, x, y, is_wall=False, is_start=False, is_exit=False):
@ -165,10 +170,21 @@ class MazeSolver:
def __init__(self, maze, strategy=None):
self.maze = maze
self.strategy = strategy
self.observers = [] # для Observer
def set_strategy(self, strategy):
self.strategy = strategy
def attach(self, observer):
self.observers.append(observer)
def detach(self, observer):
self.observers.remove(observer)
def notify(self, event):
for obs in self.observers:
obs.update(event)
def solve(self):
if self.strategy is None:
raise ValueError("Стратегия не установлена")
@ -176,30 +192,249 @@ class MazeSolver:
exit_cell = self.maze.exit_cell
if start is None or exit_cell is None:
raise ValueError("Лабиринт не содержит старта или выхода")
self.notify("Поиск начат")
start_time = time.perf_counter()
path = self.strategy.find_path(self.maze, start, exit_cell)
end_time = time.perf_counter()
elapsed_ms = (end_time - start_time) * 1000
self.notify("Поиск завершён")
return path, elapsed_ms
# Test search
class Observer:
def update(self, event):
raise NotImplementedError
class ConsoleView(Observer):
def __init__(self, maze):
self.maze = maze
def update(self, event):
if event == "Поиск начат":
print("=== Поиск начат ===")
elif event == "Поиск завершён":
print("=== Поиск завершён ===")
def render(self, path=None):
path_set = set(path) if path else set()
for y in range(self.maze.height):
row = ''
for x in range(self.maze.width):
cell = self.maze.get_cell(x, y)
if cell.is_wall:
row += '#'
elif cell.is_start:
row += 'S'
elif cell.is_exit:
row += 'E'
elif cell in path_set:
row += '*'
else:
row += ' '
print(row)
print()
class Command:
def execute(self):
raise NotImplementedError
def undo(self):
raise NotImplementedError
class MoveCommand(Command):
def __init__(self, player, dx, dy):
self.player = player
self.dx = dx
self.dy = dy
self.prev_x = player.x
self.prev_y = player.y
def execute(self):
new_x = self.player.x + self.dx
new_y = self.player.y + self.dy
maze = self.player.maze
cell = maze.get_cell(new_x, new_y)
if cell and cell.is_passable():
self.player.x = new_x
self.player.y = new_y
self.player.current_cell = cell
return True
return False
def undo(self):
self.player.x = self.prev_x
self.player.y = self.prev_y
self.player.current_cell = self.player.maze.get_cell(self.prev_x, self.prev_y)
class Player:
def __init__(self, maze, start_cell):
self.maze = maze
self.x = start_cell.x
self.y = start_cell.y
self.current_cell = start_cell
# EEEEEEEEEKSPERIMENTY
def generate_empty_maze(width, height):
maze = Maze(width, height)
start = maze.get_cell(0, 0)
exit_cell = maze.get_cell(width-1, height-1)
start.is_start = True
exit_cell.is_exit = True
maze.start_cell = start
maze.exit_cell = exit_cell
return maze
def generate_random_maze(width, height, wall_prob=0.3):
maze = Maze(width, height)
for x in range(width):
for y in range(height):
cell = maze.get_cell(x, y)
if random.random() < wall_prob:
cell.is_wall = True
start = maze.get_cell(0, 0)
exit_cell = maze.get_cell(width-1, height-1)
start.is_wall = False
start.is_start = True
exit_cell.is_wall = False
exit_cell.is_exit = True
maze.start_cell = start
maze.exit_cell = exit_cell
return maze
def generate_maze_with_dead_ends(width, height):
maze = Maze(width, height)
for x in range(width):
for y in range(height):
maze.get_cell(x, y).is_wall = True
x, y = 0, 0
while x < width and y < height:
cell = maze.get_cell(x, y)
cell.is_wall = False
if x == width-1 and y == height-1:
break
if y+1 < height and (x == width-1 or random.choice([True, False])):
y += 1
else:
x += 1
start = maze.get_cell(0, 0)
exit_cell = maze.get_cell(width-1, height-1)
start.is_start = True
exit_cell.is_exit = True
maze.start_cell = start
maze.exit_cell = exit_cell
return maze
def generate_maze_no_exit(width, height):
maze = generate_random_maze(width, height, 0.2)
exit_cell = maze.get_cell(width-1, height-1)
for dx, dy in [(-1,0), (1,0), (0,-1), (0,1)]:
nx, ny = exit_cell.x + dx, exit_cell.y + dy
neighbor = maze.get_cell(nx, ny)
if neighbor:
neighbor.is_wall = True
start = maze.get_cell(0, 0)
start.is_wall = False
start.is_start = True
maze.start_cell = start
maze.exit_cell = exit_cell
return maze
def run_experiment():
os.makedirs("results", exist_ok=True)
maze_generators = [
("empty_10x10", lambda: generate_empty_maze(10, 10)),
("empty_50x50", lambda: generate_empty_maze(50, 50)),
("empty_100x100", lambda: generate_empty_maze(100, 100)),
("random_10x10", lambda: generate_random_maze(10, 10, 0.3)),
("random_50x50", lambda: generate_random_maze(50, 50, 0.3)),
("random_100x100", lambda: generate_random_maze(100, 100, 0.3)),
("dead_ends_10x10", lambda: generate_maze_with_dead_ends(10, 10)),
("dead_ends_50x50", lambda: generate_maze_with_dead_ends(50, 50)),
("dead_ends_100x100", lambda: generate_maze_with_dead_ends(100, 100)),
("no_exit_10x10", lambda: generate_maze_no_exit(10, 10)),
("no_exit_50x50", lambda: generate_maze_no_exit(50, 50)),
]
strategies = [
("BFS", BFSStrategy()),
("DFS", DFSStrategy()),
("AStar", AStarStrategy())
]
repeats = 5
all_results = []
for maze_name, gen_func in maze_generators:
print(f"Тестирование лабиринта: {maze_name}")
maze = gen_func()
solver = MazeSolver(maze)
for strat_name, strat in strategies:
solver.set_strategy(strat)
total_time = 0
total_path_len = 0
path = []
for rep in range(repeats):
path, elapsed_ms = solver.solve()
total_time += elapsed_ms
total_path_len += len(path) if path else 0
avg_time = total_time / repeats
avg_len = total_path_len / repeats
all_results.append({
"Maze": maze_name,
"Strategy": strat_name,
"AvgTime_ms": avg_time,
"AvgPathLen": avg_len,
"PathFound": len(path) > 0 if path else False
})
print(f" {strat_name}: время {avg_time:.3f} мс, длина пути {avg_len:.1f}")
# Сохраняем CSV
csv_path = "results/experiment_results.csv"
with open(csv_path, 'w', newline='', encoding='utf-8') as f:
fieldnames = ["Maze", "Strategy", "AvgTime_ms", "AvgPathLen", "PathFound"]
writer = csv.DictWriter(f, fieldnames=fieldnames)
writer.writeheader()
writer.writerows(all_results)
print(f"Результаты сохранены в {csv_path}")
# Построение графика
maze_names = sorted(set(r["Maze"] for r in all_results))
strategy_names = ["BFS", "DFS", "AStar"]
data = {maze: {s: None for s in strategy_names} for maze in maze_names}
for r in all_results:
data[r["Maze"]][r["Strategy"]] = r["AvgTime_ms"]
fig, ax = plt.subplots(figsize=(14, 6))
x = np.arange(len(maze_names))
width = 0.25
colors = ['skyblue', 'lightgreen', 'salmon']
for i, strat in enumerate(strategy_names):
times = [data[maze][strat] if data[maze][strat] is not None else 0 for maze in maze_names]
ax.bar(x + i*width, times, width, label=strat, color=colors[i])
ax.set_xlabel('Лабиринт')
ax.set_ylabel('Среднее время (мс)')
ax.set_title('Сравнение стратегий поиска пути')
ax.set_xticks(x + width)
ax.set_xticklabels(maze_names, rotation=45, ha='right')
ax.legend()
plt.tight_layout()
plt.savefig("results/performance.png", dpi=150)
plt.show()
print("График сохранён в results/performance.png")
if __name__ == '__main__':
builder = TextFileMazeBuilder()
maze = builder.build_from_file('test_maze.txt')
solver = MazeSolver(maze)
solver.set_strategy(BFSStrategy())
path, ms = solver.solve()
print("BFS путь:", [f"({c.x},{c.y})" for c in path])
print(f"Время: {ms:.3f} мс")
solver.set_strategy(DFSStrategy())
path, ms = solver.solve()
print("DFS путь:", [f"({c.x},{c.y})" for c in path])
print(f"Время: {ms:.3f} мс")
solver.set_strategy(AStarStrategy())
path, ms = solver.solve()
print("A* путь:", [f"({c.x},{c.y})" for c in path])
print(f"Время: {ms:.3f} мс")
run_experiment()

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@ -0,0 +1,34 @@
Maze,Strategy,AvgTime_ms,AvgPathLen,PathFound
empty_10x10,BFS,0.13590119997388683,19.0,True
empty_10x10,DFS,0.0658330000078422,55.0,True
empty_10x10,AStar,0.12148100004196749,19.0,True
empty_50x50,BFS,4.080367400092655,99.0,True
empty_50x50,DFS,1.490334600021015,1275.0,True
empty_50x50,AStar,4.539874399961263,99.0,True
empty_100x100,BFS,11.864865199822816,199.0,True
empty_100x100,DFS,6.421647800107166,4951.0,True
empty_100x100,AStar,13.146192800104473,199.0,True
random_10x10,BFS,0.08931020001909928,19.0,True
random_10x10,DFS,0.0637794000795111,23.0,True
random_10x10,AStar,0.08288600010928349,19.0,True
random_50x50,BFS,2.3307791999286565,0.0,False
random_50x50,DFS,2.358275200094795,0.0,False
random_50x50,AStar,3.1945947999702184,0.0,False
random_100x100,BFS,8.76705820001007,0.0,False
random_100x100,DFS,8.292441200046596,0.0,False
random_100x100,AStar,13.397702600013872,0.0,False
dead_ends_10x10,BFS,0.023798799975338625,19.0,True
dead_ends_10x10,DFS,0.024454199865431292,19.0,True
dead_ends_10x10,AStar,0.02576019996922696,19.0,True
dead_ends_50x50,BFS,0.10447879994899267,99.0,True
dead_ends_50x50,DFS,0.1395262001096853,99.0,True
dead_ends_50x50,AStar,0.1517965998573345,99.0,True
dead_ends_100x100,BFS,0.27448000000731554,199.0,True
dead_ends_100x100,DFS,0.2607183998406981,199.0,True
dead_ends_100x100,AStar,0.42436699995960225,199.0,True
no_exit_10x10,BFS,0.09290340003644815,0.0,False
no_exit_10x10,DFS,0.09840180009632604,0.0,False
no_exit_10x10,AStar,0.11763999991671881,0.0,False
no_exit_50x50,BFS,2.5957402001040464,0.0,False
no_exit_50x50,DFS,2.327834000061557,0.0,False
no_exit_50x50,AStar,4.334011999981158,0.0,False
1 Maze Strategy AvgTime_ms AvgPathLen PathFound
2 empty_10x10 BFS 0.13590119997388683 19.0 True
3 empty_10x10 DFS 0.0658330000078422 55.0 True
4 empty_10x10 AStar 0.12148100004196749 19.0 True
5 empty_50x50 BFS 4.080367400092655 99.0 True
6 empty_50x50 DFS 1.490334600021015 1275.0 True
7 empty_50x50 AStar 4.539874399961263 99.0 True
8 empty_100x100 BFS 11.864865199822816 199.0 True
9 empty_100x100 DFS 6.421647800107166 4951.0 True
10 empty_100x100 AStar 13.146192800104473 199.0 True
11 random_10x10 BFS 0.08931020001909928 19.0 True
12 random_10x10 DFS 0.0637794000795111 23.0 True
13 random_10x10 AStar 0.08288600010928349 19.0 True
14 random_50x50 BFS 2.3307791999286565 0.0 False
15 random_50x50 DFS 2.358275200094795 0.0 False
16 random_50x50 AStar 3.1945947999702184 0.0 False
17 random_100x100 BFS 8.76705820001007 0.0 False
18 random_100x100 DFS 8.292441200046596 0.0 False
19 random_100x100 AStar 13.397702600013872 0.0 False
20 dead_ends_10x10 BFS 0.023798799975338625 19.0 True
21 dead_ends_10x10 DFS 0.024454199865431292 19.0 True
22 dead_ends_10x10 AStar 0.02576019996922696 19.0 True
23 dead_ends_50x50 BFS 0.10447879994899267 99.0 True
24 dead_ends_50x50 DFS 0.1395262001096853 99.0 True
25 dead_ends_50x50 AStar 0.1517965998573345 99.0 True
26 dead_ends_100x100 BFS 0.27448000000731554 199.0 True
27 dead_ends_100x100 DFS 0.2607183998406981 199.0 True
28 dead_ends_100x100 AStar 0.42436699995960225 199.0 True
29 no_exit_10x10 BFS 0.09290340003644815 0.0 False
30 no_exit_10x10 DFS 0.09840180009632604 0.0 False
31 no_exit_10x10 AStar 0.11763999991671881 0.0 False
32 no_exit_50x50 BFS 2.5957402001040464 0.0 False
33 no_exit_50x50 DFS 2.327834000061557 0.0 False
34 no_exit_50x50 AStar 4.334011999981158 0.0 False

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