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@ -99,3 +99,184 @@ class TextFileMazeBuilder(MazeBuilder):
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raise ValueError(f"Ошибка: S={start_count}, E={exit_count} (нужно по одному)")
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raise ValueError(f"Ошибка: S={start_count}, E={exit_count} (нужно по одному)")
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return maze
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return maze
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class SearchStats:
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"""статистика поиска"""
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def __init__(self, time_ms=0, visited_cells=0, path_length=0):
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self.time_ms = time_ms
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self.visited_cells = visited_cells
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self.path_length = path_length
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def __str__(self):
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return f"Время: {self.time_ms:.2f} мс, Посещено: {self.visited_cells}, Длина пути: {self.path_length}"
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class PathFindingStrategy:
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"""интерфейс стратегии поиска пути"""
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def findPath(self, maze, start, exit):
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raise NotImplementedError
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def get_name(self):
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raise NotImplementedError
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class BFSStrategy(PathFindingStrategy):
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"""BFS - гарантирует кратчайший путь"""
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def get_name(self):
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return "BFS (Поиск в ширину)"
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def findPath(self, maze, start, exit):
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from collections import deque
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if not start or not exit:
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return [], 0
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queue = deque([(start, [start])])
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visited = {start}
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while queue:
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current, path = queue.popleft()
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if current == exit:
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return path, len(visited)
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for neighbor in maze.get_neighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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queue.append((neighbor, path + [neighbor]))
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return [], len(visited)
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class DFSStrategy(PathFindingStrategy):
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"""DFS - быстрый, но не обязательно кратчайший"""
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def get_name(self):
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return "DFS (Поиск в глубину)"
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def findPath(self, maze, start, exit):
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if not start or not exit:
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return [], 0
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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 == exit:
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return path, len(visited)
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for neighbor in maze.get_neighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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stack.append((neighbor, path + [neighbor]))
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return [], len(visited)
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class AStarStrategy(PathFindingStrategy):
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"""алгоритм A Star - оптимальный и быстрый с эвристикой"""
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def get_name(self):
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return "A Star"
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def _heuristic(self, a, b):
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return abs(a.x - b.x) + abs(a.y - b.y)
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def findPath(self, maze, start, exit):
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if not start or not exit:
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return [], 0
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import heapq
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heap = []
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counter = 0
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start_f = self._heuristic(start, exit)
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heapq.heappush(heap, (start_f, counter, start))
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came_from = {}
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g_score = {start: 0}
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f_score = {start: start_f}
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visited = set()
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visited.add(start)
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while heap:
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current_f, _, current = heapq.heappop(heap)
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if current == exit:
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path = []
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while current in came_from:
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path.append(current)
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current = came_from[current]
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path.append(start)
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path.reverse()
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return path, len(visited)
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if current_f > f_score.get(current, float('inf')):
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continue
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for neighbor in maze.get_neighbors(current):
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tentative_g = g_score[current] + 1
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if tentative_g < g_score.get(neighbor, float('inf')):
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came_from[neighbor] = current
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g_score[neighbor] = tentative_g
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new_f = tentative_g + self._heuristic(neighbor, exit)
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f_score[neighbor] = new_f
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counter += 1
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heapq.heappush(heap, (new_f, counter, neighbor))
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visited.add(neighbor)
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return [], len(visited)
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class DijkstraStrategy(PathFindingStrategy):
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"""алгоритм Дейкстры"""
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def get_name(self):
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return "Дейкстра (Dijkstra)"
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def findPath(self, maze, start, exit):
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if not start or not exit:
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return [], 0
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import heapq
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heap = []
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counter = 0
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heapq.heappush(heap, (0, counter, start))
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distances = {start: 0}
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came_from = {}
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visited = set()
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visited.add(start)
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while heap:
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current_dist, _, current = heapq.heappop(heap)
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if current == exit:
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path = []
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while current in came_from:
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path.append(current)
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current = came_from[current]
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path.append(start)
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path.reverse()
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return path, len(visited)
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if current_dist > distances.get(current, float('inf')):
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continue
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for neighbor in maze.get_neighbors(current):
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new_dist = current_dist + 1
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if new_dist < distances.get(neighbor, float('inf')):
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distances[neighbor] = new_dist
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came_from[neighbor] = current
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counter += 1
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heapq.heappush(heap, (new_dist, counter, neighbor))
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visited.add(neighbor)
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return [], len(visited)
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