solverMaze_solver

MininaVD/docs2/data2/solverMaze_solver.ipynb

@@ -0,0 +1,129 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1ef30a86-b41f-49eb-84c3-5d425614cbdd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import time\n",
+    "from typing import List, Optional\n",
+    "from dataclasses import dataclass, field\n",
+    "from modelsMaze import Maze\n",
+    "from modelsCell import Cell\n",
+    "from strategiesPathfinding_strategy import PathFindingStrategy\n",
+    "from visualizationObserver import Observer\n",
+    "\n",
+    "@dataclass\n",
+    "class SearchStats:\n",
+    "    \"\"\"Статистика поиска.\"\"\"\n",
+    "    algorithm_name: str\n",
+    "    time_ms: float\n",
+    "    visited_cells: int\n",
+    "    path_length: int\n",
+    "    path_found: bool = True\n",
+    "\n",
+    "class MazeSolver:\n",
+    "    \"\"\"\n",
+    "    Оркестратор для решения лабиринта.\n",
+    "    Использует паттерн Strategy для алгоритмов поиска.\n",
+    "    Поддерживает Observer для уведомлений.\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    def __init__(self, maze: Maze, strategy: Optional[PathFindingStrategy] = None):\n",
+    "        self.maze = maze\n",
+    "        self._strategy = strategy\n",
+    "        self._observers: List[Observer] = []\n",
+    "        self._last_path: List[Cell] = []\n",
+    "        self._last_stats: Optional[SearchStats] = None\n",
+    "    \n",
+    "    def set_strategy(self, strategy: PathFindingStrategy) -> None:\n",
+    "        \"\"\"Динамическая смена стратегии.\"\"\"\n",
+    "        self._strategy = strategy\n",
+    "        self._notify(f\"Стратегия изменена на {strategy.name}\")\n",
+    "    \n",
+    "    def attach(self, observer: Observer) -> None:\n",
+    "        \"\"\"Подписать наблюдателя.\"\"\"\n",
+    "        self._observers.append(observer)\n",
+    "    \n",
+    "    def detach(self, observer: Observer) -> None:\n",
+    "        \"\"\"Отписать наблюдателя.\"\"\"\n",
+    "        if observer in self._observers:\n",
+    "            self._observers.remove(observer)\n",
+    "    \n",
+    "    def _notify(self, event: str) -> None:\n",
+    "        \"\"\"Уведомить всех наблюдателей.\"\"\"\n",
+    "        for observer in self._observers:\n",
+    "            observer.update(event)\n",
+    "    \n",
+    "    def solve(self) -> List[Cell]:\n",
+    "        \"\"\"\n",
+    "        Выполнить поиск пути с текущей стратегией.\n",
+    "        Возвращает путь (список клеток).\n",
+    "        \"\"\"\n",
+    "        if self._strategy is None:\n",
+    "            raise ValueError(\"Стратегия не установлена\")\n",
+    "        \n",
+    "        if not self.maze.start_cell or not self.maze.exit_cell:\n",
+    "            raise ValueError(\"Лабиринт не имеет старта или выхода\")\n",
+    "        \n",
+    "        self._notify(f\"Начинаем поиск пути с использованием {self._strategy.name}...\")\n",
+    "        \n",
+    "        start_time = time.perf_counter()\n",
+    "        path = self._strategy.find_path(self.maze, self.maze.start_cell, self.maze.exit_cell)\n",
+    "        end_time = time.perf_counter()\n",
+    "        \n",
+    "        time_ms = (end_time - start_time) * 1000\n",
+    "        \n",
+    "        # Получаем количество посещённых клеток из стратегии\n",
+    "        visited_cells = getattr(self._strategy, 'last_visited_count', 0)\n",
+    "        \n",
+    "        self._last_path = path\n",
+    "        self._last_stats = SearchStats(\n",
+    "            algorithm_name=self._strategy.name,\n",
+    "            time_ms=time_ms,\n",
+    "            visited_cells=visited_cells,\n",
+    "            path_length=len(path),\n",
+    "            path_found=len(path) > 0\n",
+    "        )\n",
+    "        \n",
+    "        if path:\n",
+    "            self._notify(f\"Путь найден! Длина: {len(path)}, время: {time_ms:.2f} мс, посещено: {visited_cells}\")\n",
+    "        else:\n",
+    "            self._notify(f\"Путь не найден! Время: {time_ms:.2f} мс, посещено: {visited_cells}\")\n",
+    "        \n",
+    "        return path\n",
+    "    \n",
+    "    @property\n",
+    "    def last_path(self) -> List[Cell]:\n",
+    "        return self._last_path\n",
+    "    \n",
+    "    @property\n",
+    "    def last_stats(self) -> Optional[SearchStats]:\n",
+    "        return self._last_stats"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python [conda env:base] *",
+   "language": "python",
+   "name": "conda-base-py"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.9"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}