[4] 2-nd_ex

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agafonovdm 2026-05-25 13:10:22 +03:00
parent 153f2a092c
commit 9a8a82a978
2 changed files with 610 additions and 0 deletions

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import time
import heapq
from collections import deque
from typing import List, Optional, Dict, Tuple
from abc import ABC, abstractmethod
import csv
import random
class Cell:
def __init__(self, x: int, y: int):
self.x = x
self.y = y
self.is_wall = False
self.is_start = False
self.is_exit = False
def is_passable(self) -> bool:
return not self.is_wall
class Maze:
def __init__(self, width: int, height: int):
self.width = width
self.height = height
self.cells = [[Cell(x, y) for y in range(height)] for x in range(width)]
self.start: Optional[Cell] = None
self.exit: Optional[Cell] = None
def get_cell(self, x: int, y: int) -> Optional[Cell]:
if 0 <= x < self.width and 0 <= y < self.height:
return self.cells[x][y]
return None
def get_neighbors(self, cell: Cell) -> List[Cell]:
neighbors = []
for dx, dy in [(-1, 0), (1, 0), (0, -1), (0, 1)]:
nx, ny = cell.x + dx, cell.y + dy
nb = self.get_cell(nx, ny)
if nb and nb.is_passable():
neighbors.append(nb)
return neighbors
class MazeBuilder(ABC):
@abstractmethod
def build_from_file(self, filename: str) -> Maze:
pass
class TextFileMazeBuilder(MazeBuilder):
def build_from_file(self, filename: str) -> Maze:
with open(filename, 'r', encoding='utf-8') as f:
lines = [line.rstrip('\n') for line in f.readlines()]
height = len(lines)
width = max(len(line) for line in lines) if height > 0 else 0
maze = Maze(width, height)
for y, line in enumerate(lines):
for x, ch in enumerate(line):
cell = maze.get_cell(x, y)
if cell is None:
continue
if ch == '#':
cell.is_wall = True
elif ch == 'S':
cell.is_start = True
maze.start = cell
elif ch == 'E':
cell.is_exit = True
maze.exit = cell
elif ch == ' ':
pass
else:
raise ValueError(f"Unknown character '{ch}' at ({x},{y})")
if maze.start is None or maze.exit is None:
raise ValueError("Maze must have start (S) and exit (E)")
return maze
class PathFindingStrategy(ABC):
@abstractmethod
def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
pass
@abstractmethod
def get_name(self) -> str:
pass
class BFSStrategy(PathFindingStrategy):
def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
queue = deque([start])
came_from = {start: None}
while queue:
current = queue.popleft()
if current == exit:
break
for nb in maze.get_neighbors(current):
if nb not in came_from:
came_from[nb] = current
queue.append(nb)
if exit not in came_from:
return []
path = []
cur = exit
while cur:
path.append(cur)
cur = came_from[cur]
path.reverse()
return path
def get_name(self) -> str:
return "BFS"
class DFSStrategy(PathFindingStrategy):
def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
stack = [start]
came_from = {start: None}
while stack:
current = stack.pop()
if current == exit:
break
for nb in maze.get_neighbors(current):
if nb not in came_from:
came_from[nb] = current
stack.append(nb)
if exit not in came_from:
return []
path = []
cur = exit
while cur:
path.append(cur)
cur = came_from[cur]
path.reverse()
return path
def get_name(self) -> str:
return "DFS"
class AStarStrategy(PathFindingStrategy):
def _heuristic(self, a: Cell, b: Cell) -> int:
return abs(a.x - b.x) + abs(a.y - b.y)
def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
open_set = []
heapq.heappush(open_set, (0, id(start), start))
came_from = {}
g_score = {start: 0}
f_score = {start: self._heuristic(start, exit)}
while open_set:
_, _, current = heapq.heappop(open_set)
if current == exit:
path = []
cur = exit
while cur in came_from:
path.append(cur)
cur = came_from[cur]
path.append(start)
path.reverse()
return path
for neighbor in maze.get_neighbors(current):
tentative_g = g_score[current] + 1
if tentative_g < g_score.get(neighbor, float('inf')):
came_from[neighbor] = current
g_score[neighbor] = tentative_g
f_score[neighbor] = tentative_g + self._heuristic(neighbor, exit)
heapq.heappush(open_set, (f_score[neighbor], id(neighbor), neighbor))
return []
def get_name(self) -> str:
return "A*"
class DijkstraStrategy(PathFindingStrategy):
def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
pq = [(0, id(start), start)]
distances = {start: 0}
came_from = {start: None}
while pq:
dist, _, current = heapq.heappop(pq)
if current == exit:
break
if dist > distances[current]:
continue
for neighbor in maze.get_neighbors(current):
new_dist = dist + 1
if new_dist < distances.get(neighbor, float('inf')):
distances[neighbor] = new_dist
came_from[neighbor] = current
heapq.heappush(pq, (new_dist, id(neighbor), neighbor))
if exit not in came_from:
return []
path = []
cur = exit
while cur:
path.append(cur)
cur = came_from[cur]
path.reverse()
return path
def get_name(self) -> str:
return "Dijkstra"
class SearchStats:
def __init__(self, time_ms: float, visited_cells: int, path_length: int):
self.time_ms = time_ms
self.visited_cells = visited_cells
self.path_length = path_length
def __str__(self):
return f"Time: {self.time_ms:.2f}ms, Visited: {self.visited_cells}, Path: {self.path_length}"
class MazeSolver:
def __init__(self, maze: Maze, strategy: PathFindingStrategy):
self.maze = maze
self.strategy = strategy
def set_strategy(self, strategy: PathFindingStrategy):
self.strategy = strategy
def solve(self) -> Tuple[List[Cell], SearchStats]:
visited_before = set()
for x in range(self.maze.width):
for y in range(self.maze.height):
cell = self.maze.get_cell(x, y)
if cell and cell.is_passable():
visited_before.add(cell)
start_time = time.perf_counter()
path = self.strategy.find_path(self.maze, self.maze.start, self.maze.exit)
end_time = time.perf_counter()
visited_after = set()
for x in range(self.maze.width):
for y in range(self.maze.height):
cell = self.maze.get_cell(x, y)
if cell and cell.is_passable():
visited_after.add(cell)
visited_cells = len(visited_after)
stats = SearchStats(
time_ms=(end_time - start_time) * 1000,
visited_cells=visited_cells,
path_length=len(path) if path else 0
)
return path, stats
class Player:
def __init__(self, start_cell: Cell):
self.current_cell = start_cell
self.previous_cell = None
def move_to(self, cell: Cell) -> bool:
if cell.is_passable():
self.previous_cell = self.current_cell
self.current_cell = cell
return True
return False
def undo(self):
if self.previous_cell:
self.current_cell, self.previous_cell = self.previous_cell, None
return True
return False
class Command(ABC):
@abstractmethod
def execute(self) -> bool:
pass
@abstractmethod
def undo(self):
pass
class MoveCommand(Command):
def __init__(self, player: Player, maze: Maze, direction: str):
self.player = player
self.maze = maze
self.direction = direction
self.executed = False
def execute(self) -> bool:
dx, dy = 0, 0
if self.direction == 'W' or self.direction == 'w':
dy = -1
elif self.direction == 'S' or self.direction == 's':
dy = 1
elif self.direction == 'A' or self.direction == 'a':
dx = -1
elif self.direction == 'D' or self.direction == 'd':
dx = 1
new_x = self.player.current_cell.x + dx
new_y = self.player.current_cell.y + dy
new_cell = self.maze.get_cell(new_x, new_y)
if new_cell and new_cell.is_passable():
self.executed = self.player.move_to(new_cell)
return self.executed
return False
def undo(self):
if self.executed:
self.player.undo()
self.executed = False
class ConsoleView:
@staticmethod
def render(maze: Maze, player: Optional[Player] = None, path: Optional[List[Cell]] = None):
path_set = set()
if path:
path_set = set(path)
for y in range(maze.height):
line = ""
for x in range(maze.width):
cell = maze.get_cell(x, y)
if not cell:
line += " "
elif player and player.current_cell == cell:
line += "P"
elif cell.is_start:
line += "S"
elif cell.is_exit:
line += "E"
elif cell.is_wall:
line += "#"
elif path and cell in path_set:
line += "."
else:
line += " "
print(line)
print()
@staticmethod
def show_stats(stats: SearchStats, algo_name: str):
print(f"=== {algo_name} Results ===")
print(stats)
print()
def generate_test_maze(width: int, height: int, complexity: float = 0.3) -> Maze:
maze = Maze(width, height)
for x in range(width):
for y in range(height):
if random.random() < complexity:
maze.cells[x][y].is_wall = True
maze.start = maze.get_cell(0, 0)
if maze.start:
maze.start.is_start = True
maze.start.is_wall = False
maze.exit = maze.get_cell(width - 1, height - 1)
if maze.exit:
maze.exit.is_exit = True
maze.exit.is_wall = False
return maze
def generate_empty_maze(width: int, height: int) -> Maze:
maze = Maze(width, height)
for x in range(width):
for y in range(height):
maze.cells[x][y].is_wall = False
maze.start = maze.get_cell(0, 0)
if maze.start:
maze.start.is_start = True
maze.exit = maze.get_cell(width - 1, height - 1)
if maze.exit:
maze.exit.is_exit = True
return maze
def generate_no_exit_maze(width: int, height: int) -> Maze:
maze = Maze(width, height)
for x in range(width):
for y in range(height):
maze.cells[x][y].is_wall = False
for x in range(width):
maze.cells[x][height // 2].is_wall = True
maze.start = maze.get_cell(0, 0)
if maze.start:
maze.start.is_start = True
maze.exit = maze.get_cell(width - 1, height - 1)
if maze.exit:
maze.exit.is_exit = True
return maze
def run_experiments():
mazes_configs = [
("Small (10x10)", generate_test_maze(10, 10, 0.2)),
("Medium (50x50)", generate_test_maze(50, 50, 0.25)),
("Large (100x100)", generate_test_maze(100, 100, 0.3)),
("Empty (30x30)", generate_empty_maze(30, 30)),
("No Exit (20x20)", generate_no_exit_maze(20, 20))
]
strategies = [BFSStrategy(), DFSStrategy(), AStarStrategy(), DijkstraStrategy()]
results = []
for maze_name, maze in mazes_configs:
print(f"\n=== Testing: {maze_name} ===")
for strategy in strategies:
times = []
visited = []
path_lengths = []
solver = MazeSolver(maze, strategy)
for run in range(5):
maze_copy = Maze(maze.width, maze.height)
for x in range(maze.width):
for y in range(maze.height):
orig = maze.get_cell(x, y)
copy = maze_copy.get_cell(x, y)
if orig:
copy.is_wall = orig.is_wall
copy.is_start = orig.is_start
copy.is_exit = orig.is_exit
maze_copy.start = maze_copy.get_cell(maze.start.x, maze.start.y) if maze.start else None
maze_copy.exit = maze_copy.get_cell(maze.exit.x, maze.exit.y) if maze.exit else None
solver.maze = maze_copy
solver.set_strategy(strategy)
path, stats = solver.solve()
times.append(stats.time_ms)
visited.append(stats.visited_cells)
path_lengths.append(stats.path_length)
avg_time = sum(times) / len(times)
avg_visited = sum(visited) / len(visited)
avg_path = sum(path_lengths) / len(path_lengths)
results.append({
'maze': maze_name,
'algorithm': strategy.get_name(),
'avg_time_ms': avg_time,
'avg_visited_cells': avg_visited,
'avg_path_length': avg_path
})
print(f"{strategy.get_name()}: {avg_time:.2f}ms, {avg_visited:.0f} cells, path={avg_path:.0f}")
with open('experiment_results.csv', 'w', newline='', encoding='utf-8') as f:
writer = csv.DictWriter(f, fieldnames=['maze', 'algorithm', 'avg_time_ms', 'avg_visited_cells', 'avg_path_length'])
writer.writeheader()
writer.writerows(results)
print("\nResults saved to experiment_results.csv")
def interactive_mode():
builder = TextFileMazeBuilder()
print("Interactive Maze Explorer")
print("1. Load maze from file")
print("2. Generate random maze")
choice = input("Choose (1/2): ")
if choice == '1':
filename = input("Enter filename: ")
try:
maze = builder.build_from_file(filename)
except Exception as e:
print(f"Error loading maze: {e}")
return
else:
w = int(input("Width: "))
h = int(input("Height: "))
maze = generate_test_maze(w, h, 0.3)
player = Player(maze.start)
strategies = {
'1': BFSStrategy(),
'2': DFSStrategy(),
'3': AStarStrategy(),
'4': DijkstraStrategy()
}
print("\nSelect algorithm for solving:")
print("1. BFS (shortest path)")
print("2. DFS (fast, not optimal)")
print("3. A* (heuristic)")
print("4. Dijkstra")
algo_choice = input("Choose: ")
solver = MazeSolver(maze, strategies.get(algo_choice, BFSStrategy()))
path, stats = solver.solve()
view = ConsoleView()
if path:
print(f"\nPath found! Length: {len(path)}")
view.show_stats(stats, solver.strategy.get_name())
else:
print("\nNo path found!")
while True:
view.render(maze, player, path if path else None)
if player.current_cell == maze.exit:
print("Congratulations! You reached the exit!")
break
cmd = input("Move (W/A/S/D) | U=undo | Q=quit | S=solve: ").upper()
if cmd == 'Q':
break
elif cmd == 'U':
player.undo()
print("Undo last move")
elif cmd == 'S' and path:
for cell in path:
if cell == player.current_cell:
continue
player.move_to(cell)
view.render(maze, player, path)
input("Press Enter to continue...")
if player.current_cell == maze.exit:
print("You reached the exit!")
break
elif cmd in ['W', 'A', 'S', 'D']:
move_cmd = MoveCommand(player, maze, cmd)
if move_cmd.execute():
print("Moved")
else:
print("Can't move there!")
def main():
print("Maze Solver with Design Patterns")
print("1. Run experiments")
print("2. Interactive mode")
choice = input("Choose (1/2): ")
if choice == '1':
run_experiments()
else:
interactive_mode()
if __name__ == "__main__":
main()

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maze,algorithm,avg_time_ms,avg_visited_cells,avg_path_length
Small (10x10),BFS,0.08572000006097369,79.0,19.0
Small (10x10),DFS,0.039739999920129776,79.0,31.0
Small (10x10),A*,0.13467999997374136,79.0,19.0
Small (10x10),Dijkstra,0.11474000057205558,79.0,19.0
Medium (50x50),BFS,1.8074600004183594,1874.0,99.0
Medium (50x50),DFS,0.5937599995377241,1874.0,429.0
Medium (50x50),A*,1.6300600003887666,1874.0,99.0
Medium (50x50),Dijkstra,3.1870400001935195,1874.0,99.0
Large (100x100),BFS,0.014439999722526409,7033.0,0.0
Large (100x100),DFS,0.014839999857940711,7033.0,0.0
Large (100x100),A*,0.02542000001994893,7033.0,0.0
Large (100x100),Dijkstra,0.02548000011302065,7033.0,0.0
Empty (30x30),BFS,0.784620000194991,900.0,59.0
Empty (30x30),DFS,0.5252399994787993,900.0,465.0
Empty (30x30),A*,1.150900000357069,900.0,59.0
Empty (30x30),Dijkstra,1.564640000287909,900.0,59.0
No Exit (20x20),BFS,0.2002399993216386,380.0,0.0
No Exit (20x20),DFS,0.2512400002160575,380.0,0.0
No Exit (20x20),A*,0.5590400000073714,380.0,0.0
No Exit (20x20),Dijkstra,0.35640000060084276,380.0,0.0
1 maze algorithm avg_time_ms avg_visited_cells avg_path_length
2 Small (10x10) BFS 0.08572000006097369 79.0 19.0
3 Small (10x10) DFS 0.039739999920129776 79.0 31.0
4 Small (10x10) A* 0.13467999997374136 79.0 19.0
5 Small (10x10) Dijkstra 0.11474000057205558 79.0 19.0
6 Medium (50x50) BFS 1.8074600004183594 1874.0 99.0
7 Medium (50x50) DFS 0.5937599995377241 1874.0 429.0
8 Medium (50x50) A* 1.6300600003887666 1874.0 99.0
9 Medium (50x50) Dijkstra 3.1870400001935195 1874.0 99.0
10 Large (100x100) BFS 0.014439999722526409 7033.0 0.0
11 Large (100x100) DFS 0.014839999857940711 7033.0 0.0
12 Large (100x100) A* 0.02542000001994893 7033.0 0.0
13 Large (100x100) Dijkstra 0.02548000011302065 7033.0 0.0
14 Empty (30x30) BFS 0.784620000194991 900.0 59.0
15 Empty (30x30) DFS 0.5252399994787993 900.0 465.0
16 Empty (30x30) A* 1.150900000357069 900.0 59.0
17 Empty (30x30) Dijkstra 1.564640000287909 900.0 59.0
18 No Exit (20x20) BFS 0.2002399993216386 380.0 0.0
19 No Exit (20x20) DFS 0.2512400002160575 380.0 0.0
20 No Exit (20x20) A* 0.5590400000073714 380.0 0.0
21 No Exit (20x20) Dijkstra 0.35640000060084276 380.0 0.0