2026-rff_mp/BudakovIS/docs/data/2-nd-exercize/main.py

317 lines
9.2 KiB
Python

import sys
from collections import deque
import heapq
import time
from typing import List, Optional
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
@property
def x(self) -> int:
return self._x
@property
def y(self) -> int:
return self._y
@property
def is_wall(self) -> bool:
return self._is_wall
@is_wall.setter
def is_wall(self, value: bool) -> None:
self._is_wall = value
@property
def is_start(self) -> bool:
return self._is_start
@is_start.setter
def is_start(self, value: bool) -> None:
self._is_start = value
@property
def is_exit(self) -> bool:
return self._is_exit
@is_exit.setter
def is_exit(self, value: bool) -> None:
self._is_exit = value
def is_passable(self) -> bool:
return not self._is_wall
def __repr__(self) -> str:
return f"Cell({self._x}, {self._y})"
class Maze:
def __init__(self, width: int, height: int):
self._width = width
self._height = height
self._cells = [[Cell(x, y) for x in range(width)] for y in range(height)]
self._start = None
self._exit = None
@property
def width(self) -> int:
return self._width
@property
def height(self) -> int:
return self._height
@property
def start(self) -> Optional[Cell]:
return self._start
@property
def exit(self) -> Optional[Cell]:
return self._exit
def get_cell(self, x: int, y: int) -> Optional[Cell]:
if 0 <= x < self._width and 0 <= y < self._height:
return self._cells[y][x]
return None
def set_cell(self, x: int, y: int, cell_type: str) -> None:
cell = self.get_cell(x, y)
if cell is None:
return
if cell_type == 'wall':
cell.is_wall = True
elif cell_type == 'start':
if self._start:
self._start.is_start = False
cell.is_start = True
cell.is_wall = False
self._start = cell
elif cell_type == 'exit':
if self._exit:
self._exit.is_exit = False
cell.is_exit = True
cell.is_wall = False
self._exit = cell
elif cell_type == 'path':
cell.is_wall = False
def get_neighbors(self, cell: Cell) -> List[Cell]:
neighbors = []
directions = [(0, -1), (0, 1), (-1, 0), (1, 0)]
for dx, dy in directions:
nx, ny = cell.x + dx, cell.y + dy
neighbor = self.get_cell(nx, ny)
if neighbor and neighbor.is_passable():
neighbors.append(neighbor)
return neighbors
class MazeBuilder:
def build_from_file(self, filename: str) -> Maze:
raise NotImplementedError("Need to implement in subclass")
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()]
if not lines:
raise ValueError("Файл пуст")
height = len(lines)
width = max(len(line) for line in lines)
start_count = 0
exit_count = 0
maze = Maze(width, height)
for y, line in enumerate(lines):
for x, ch in enumerate(line):
if x >= width:
continue
if ch == '#':
maze.set_cell(x, y, "wall")
elif ch == 'S':
maze.set_cell(x, y, "start")
start_count += 1
elif ch == 'E':
maze.set_cell(x, y, "exit")
exit_count += 1
else:
maze.set_cell(x, y, 'path')
if start_count != 1 or exit_count != 1:
raise ValueError(
f"Лабиринт должен иметь ровно один S и один E. "
f"Найдено: S={start_count}, E={exit_count}"
)
return maze
class PathFindingStrategy:
def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
raise NotImplementedError("Subclasses must implement find_path")
def _reconstruct_path(self, came_from: dict, start: Cell, exit_cell: Cell) -> List[Cell]:
path = []
current = exit_cell
while current is not None:
path.append(current)
current = came_from.get(current)
path.reverse()
return path
class BFSStrategy(PathFindingStrategy):
def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
queue = deque()
queue.append(start)
came_from = {start: None}
visited = {start}
while queue:
current = queue.popleft()
if current == exit_cell:
return self._reconstruct_path(came_from, start, exit_cell)
for neighbor in maze.get_neighbors(current):
if neighbor not in visited:
visited.add(neighbor)
came_from[neighbor] = current
queue.append(neighbor)
return []
class DFSStrategy(PathFindingStrategy):
def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
stack = [start]
came_from = {start: None}
visited = {start}
while stack:
current = stack.pop()
if current == exit_cell:
return self._reconstruct_path(came_from, start, exit_cell)
for neighbor in maze.get_neighbors(current):
if neighbor not in visited:
visited.add(neighbor)
came_from[neighbor] = current
stack.append(neighbor)
return []
class AStarStrategy(PathFindingStrategy):
def _heuristic(self, cell: Cell, exit_cell: Cell) -> int:
return abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y)
def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
heap = []
counter = 0
start_f = self._heuristic(start, exit_cell)
heapq.heappush(heap, (start_f, counter, start))
counter += 1
came_from = {}
g_score = {start: 0}
f_score = {start: start_f}
while heap:
current_f, _, current = heapq.heappop(heap)
if current == exit_cell:
return self._reconstruct_path(came_from, start, exit_cell)
if current_f > f_score.get(current, float('inf')):
continue
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
new_f = tentative_g + self._heuristic(neighbor, exit_cell)
f_score[neighbor] = new_f
heapq.heappush(heap, (new_f, counter, neighbor))
counter += 1
return []
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 __repr__(self) -> str:
return f"SearchStats(time={self.time_ms:.3f}ms, visited={self.visited_cells}, path_length={self.path_length})"
class MazeSolver:
def __init__(self, maze: Maze):
self._maze = maze
self._strategy = None
def set_strategy(self, strategy: PathFindingStrategy) -> None:
self._strategy = strategy
def solve(self) -> Optional[SearchStats]:
if self._strategy is None:
print("Ошибка: стратегия не установлена")
return None
start_time = time.perf_counter()
path = self._strategy.find_path(self._maze, self._maze.start, self._maze.exit)
end_time = time.perf_counter()
time_ms = (end_time - start_time) * 1000
visited_cells = 0
return SearchStats(time_ms, visited_cells, len(path))
if __name__ == "__main__":
builder = TextFileMazeBuilder()
maze = builder.build_from_file("maze1.txt")
print(f"Лабиринт {maze.width}x{maze.height}")
print(f"Старт: ({maze.start.x}, {maze.start.y})")
print(f"Выход: ({maze.exit.x}, {maze.exit.y})")
print("-" * 40)
solver = MazeSolver(maze)
solver.set_strategy(BFSStrategy())
stats = solver.solve()
print(f"BFS: {stats}")
solver.set_strategy(DFSStrategy())
stats = solver.solve()
print(f"DFS: {stats}")
solver.set_strategy(AStarStrategy())
stats = solver.solve()
print(f"A*: {stats}")