86 lines
3.2 KiB
Python
86 lines
3.2 KiB
Python
from abc import ABC, abstractmethod
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from collections import deque
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from typing import List, Tuple, Dict, Optional
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import heapq
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from maze import Maze, Cell
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class PathFindingStrategy(ABC):
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@abstractmethod
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def find_path(self, maze: Maze, start: Cell, exit: Cell) -> Tuple[List[Cell], int]:
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"""Возвращает (путь_список_клеток, количество_посещённых_клеток)"""
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pass
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class BFSStrategy(PathFindingStrategy):
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def find_path(self, maze: Maze, start: Cell, exit: Cell) -> Tuple[List[Cell], int]:
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queue = deque([start])
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visited = {start}
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parent = {start: None}
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while queue:
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current = queue.popleft()
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if current is exit:
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return self._reconstruct_path(parent, exit), len(visited)
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for nb in maze.get_neighbors(current):
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if nb not in visited:
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visited.add(nb)
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parent[nb] = current
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queue.append(nb)
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return [], len(visited)
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def _reconstruct_path(self, parent: Dict[Cell, Optional[Cell]], end: Cell) -> List[Cell]:
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path = []
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cur = end
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while cur is not None:
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path.append(cur)
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cur = parent[cur]
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path.reverse()
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return path
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class DFSStrategy(PathFindingStrategy):
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def find_path(self, maze: Maze, start: Cell, exit: Cell) -> Tuple[List[Cell], int]:
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stack = [(start, [start])]
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visited = {start}
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while stack:
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current, path = stack.pop()
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if current is exit:
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return path, len(visited)
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for nb in maze.get_neighbors(current):
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if nb not in visited:
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visited.add(nb)
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stack.append((nb, path + [nb]))
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return [], len(visited)
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class AStarStrategy(PathFindingStrategy):
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@staticmethod
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def heuristic(a: Cell, b: Cell) -> int:
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return abs(a.x - b.x) + abs(a.y - b.y)
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def find_path(self, maze: Maze, start: Cell, exit: Cell) -> Tuple[List[Cell], int]:
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open_set = []
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heapq.heappush(open_set, (0, start))
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came_from = {}
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g_score = {start: 0}
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f_score = {start: self.heuristic(start, exit)}
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visited_count = 0
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while open_set:
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_, current = heapq.heappop(open_set)
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visited_count += 1
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if current is exit:
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path = self._reconstruct_path(came_from, exit)
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return path, visited_count
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for nb in maze.get_neighbors(current):
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tentative_g = g_score[current] + 1
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if nb not in g_score or tentative_g < g_score[nb]:
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came_from[nb] = current
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g_score[nb] = tentative_g
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f_score[nb] = tentative_g + self.heuristic(nb, exit)
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heapq.heappush(open_set, (f_score[nb], nb))
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return [], visited_count
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def _reconstruct_path(self, came_from: Dict[Cell, Cell], current: Cell) -> List[Cell]:
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path = [current]
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while current in came_from:
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current = came_from[current]
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path.append(current)
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path.reverse()
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return path |