Загрузить файлы в «SmirnovaVYu/docs/data»

SmirnovaVYu/docs/data/models.py

@@ -0,0 +1,79 @@
+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
+    
+    def is_passable(self) -> bool:
+        return not self.is_wall
+    
+    def __eq__(self, other) -> bool:
+        if not isinstance(other, Cell):
+            return False
+        return self.x == other.x and self.y == other.y
+    
+    def __hash__(self):
+        return hash((self.x, self.y))
+    
+    def __repr__(self):
+        return f"Cell({self.x}, {self.y})"
+
+
+class Maze:
+    
+    def __init__(self, width: int, height: int):
+        self.width = width
+        self.height = height
+        self._cells: List[List[Optional[Cell]]] = [[None for _ in range(width)] for _ in range(height)]
+        self.start: Optional[Cell] = None
+        self.exit: Optional[Cell] = None
+    
+    def set_cell(self, x: int, y: int, cell: Cell) -> None:
+        if 0 <= x < self.width and 0 <= y < self.height:
+            self._cells[y][x] = cell
+            if cell.is_start:
+                self.start = cell
+            if cell.is_exit:
+                self.exit = cell
+    
+    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 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
+    
+    def __str__(self) -> str:
+        result = []
+        for y in range(self.height):
+            row = []
+            for x in range(self.width):
+                cell = self.get_cell(x, y)
+                if cell is None:
+                    row.append('?')
+                elif cell.is_start:
+                    row.append('S')
+                elif cell.is_exit:
+                    row.append('E')
+                elif cell.is_wall:
+                    row.append('#')
+                else:
+                    row.append(' ')
+            result.append(''.join(row))
+        return '\n'.join(result)

SmirnovaVYu/docs/data/observers.py

@@ -0,0 +1,66 @@
+from abc import ABC, abstractmethod
+from typing import List, Optional
+from models import Cell, Maze
+
+
+class Observer(ABC):
+    
+    @abstractmethod
+    def update(self, event: str, data: dict) -> None:
+        pass
+
+
+class ConsoleView(Observer):
+    
+    def render(self, maze: Maze, player_position: Optional[Cell] = None, path: Optional[List[Cell]] = None) -> None:
+        path_set = set(path) if path else set()
+        
+        print("\n+" + "-" * maze.width + "+")
+        
+        for y in range(maze.height):
+            row = []
+            for x in range(maze.width):
+                cell = maze.get_cell(x, y)
+                if cell is None:
+                    row.append('?')
+                elif player_position and cell == player_position:
+                    row.append('@')
+                elif cell.is_start:
+                    row.append('S')
+                elif cell.is_exit:
+                    row.append('E')
+                elif cell in path_set:
+                    row.append('*')
+                elif cell.is_wall:
+                    row.append('#')
+                else:
+                    row.append(' ')
+            print("|" + ''.join(row) + "|")
+        
+        print("+" + "-" * maze.width + "+")
+    
+    def update(self, event: str, data: dict) -> None:
+        if event == "maze_loaded":
+            maze = data.get('maze')
+            print("\n Лабиринт загружен:")
+            self.render(maze)
+        
+        elif event == "search_start":
+            algorithm = data.get('algorithm', 'Unknown')
+            print(f"\n Начинаем поиск алгоритмом: {algorithm}")
+        
+        elif event == "path_found":
+            maze = data.get('maze')
+            path = data.get('path')
+            stats = data.get('stats')
+            self.render(maze, path=path)
+        
+        elif event == "no_path":
+            stats = data.get('stats')
+            print(f"\n {stats}")
+        
+        elif event == "player_moved":
+            maze = data.get('maze')
+            player = data.get('player')
+            if player:
+                self.render(maze, player_position=player.current_cell)

SmirnovaVYu/docs/data/solver.py

@@ -0,0 +1,49 @@
+import time
+from dataclasses import dataclass
+from typing import List, Optional, Tuple
+from models import Cell, Maze
+from strategies import PathFindingStrategy
+
+
+@dataclass
+class SearchStats:
+    time_ms: float
+    visited_cells: int
+    path_length: int
+    path_found: bool = True
+    
+    def __str__(self) -> str:
+        if not self.path_found:
+            return f"Путь не найден (время: {self.time_ms:.2f} мс)"
+        return (f"Время: {self.time_ms:.2f} мс, "
+                f"Посещено клеток: {self.visited_cells}, "
+                f"Длина пути: {self.path_length}")
+
+
+class MazeSolver:
+
+    def __init__(self, maze: Maze, strategy: Optional[PathFindingStrategy] = None):
+        self.maze = maze
+        self._strategy = strategy
+    
+    def set_strategy(self, strategy: PathFindingStrategy) -> None:
+        self._strategy = strategy
+    
+    def solve(self) -> Tuple[List[Cell], SearchStats]:
+        if self._strategy is None:
+            raise ValueError("Стратегия не установлена")
+        
+        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
+        
+        stats = SearchStats(
+            time_ms=time_ms,
+            visited_cells=len(path) if path else 0,
+            path_length=len(path) if path else 0,
+            path_found=bool(path)
+        )
+        
+        return path, stats

SmirnovaVYu/docs/data/strategies.py

@@ -0,0 +1,99 @@
+from abc import ABC, abstractmethod
+from collections import deque
+from heapq import heappush, heappop
+from typing import List, Dict, Optional
+from models import Cell, Maze
+
+
+class PathFindingStrategy(ABC):
+    
+    @abstractmethod
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
+        pass
+
+
+class BFSStrategy(PathFindingStrategy):
+    
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
+        queue = deque([start])
+        visited = {start}
+        parent: Dict[Cell, Optional[Cell]] = {start: None}
+        
+        while queue:
+            current = queue.popleft()
+            
+            if current == exit_cell:
+                return self._reconstruct_path(parent, current)
+            
+            for neighbor in maze.get_neighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    parent[neighbor] = current
+                    queue.append(neighbor)
+        
+        return []
+    
+    def _reconstruct_path(self, parent: Dict[Cell, Optional[Cell]], current: Cell) -> List[Cell]:
+        path = []
+        while current is not None:
+            path.append(current)
+            current = parent.get(current)
+        return list(reversed(path))
+
+
+class DFSStrategy(PathFindingStrategy):
+    
+    def find_path(self, maze: Maze, start: Cell, exit_cell: Cell) -> List[Cell]:
+        stack = [(start, [start])]
+        visited = {start}
+        
+        while stack:
+            current, path = stack.pop()
+            
+            if current == exit_cell:
+                return path
+            
+            for neighbor in maze.get_neighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    stack.append((neighbor, path + [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]:
+        counter = 0
+        open_set = [(self._heuristic(start, exit_cell), counter, start)]
+        
+        g_score: Dict[Cell, float] = {start: 0}
+        parent: Dict[Cell, Optional[Cell]] = {start: None}
+        
+        while open_set:
+            _, _, current = heappop(open_set)
+            
+            if current == exit_cell:
+                return self._reconstruct_path(parent, current)
+            
+            for neighbor in maze.get_neighbors(current):
+                tentative_g = g_score[current] + 1
+                
+                if neighbor not in g_score or tentative_g < g_score[neighbor]:
+                    parent[neighbor] = current
+                    g_score[neighbor] = tentative_g
+                    counter += 1
+                    f = tentative_g + self._heuristic(neighbor, exit_cell)
+                    heappush(open_set, (f, counter, neighbor))
+        
+        return []
+    
+    def _reconstruct_path(self, parent: Dict[Cell, Optional[Cell]], current: Cell) -> List[Cell]:
+        path = []
+        while current is not None:
+            path.append(current)
+            current = parent.get(current)
+        return list(reversed(path))

SmirnovaVYu/docs/data/visualize.py

@@ -0,0 +1,77 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+from pathlib import Path
+
+
+def plot_results(csv_file='experiment_results.csv'):
+    
+    if not Path(csv_file).exists():
+        print(f"❌ {csv_file} не найден. Сначала запустите main.py")
+        return
+    
+    df = pd.read_csv(csv_file)
+
+    df = df[df['path_found'] == True]
+    
+    if df.empty:
+        print("Нет данных для графиков")
+        return
+    
+    mazes = [m.replace('.txt', '') for m in df['maze_file'].unique()]
+    strategies = df['strategy'].unique()
+    
+    fig, axes = plt.subplots(1, 3, figsize=(14, 5))
+    fig.suptitle('Сравнение алгоритмов поиска в лабиринте', fontsize=14, fontweight='bold')
+    
+    x = np.arange(len(mazes))
+    width = 0.25
+    colors = {'BFS': '#3498db', 'DFS': '#2ecc71', 'A*': '#e74c3c'}
+    
+    for i, strategy in enumerate(strategies):
+        times, visited, lengths = [], [], []
+        
+        for maze in df['maze_file'].unique():
+            data = df[(df['strategy'] == strategy) & (df['maze_file'] == maze)]
+            if not data.empty:
+                times.append(data['time_mean'].values[0])
+                visited.append(data['visited_mean'].values[0])
+                lengths.append(data['path_length_mean'].values[0])
+            else:
+                times.append(0)
+                visited.append(0)
+                lengths.append(0)
+        
+        axes[0].bar(x + i*width, times, width, label=strategy,
+                    color=colors.get(strategy, 'gray'), alpha=0.7)
+        axes[1].bar(x + i*width, visited, width, label=strategy,
+                    color=colors.get(strategy, 'gray'), alpha=0.7)
+        axes[2].bar(x + i*width, lengths, width, label=strategy,
+                    color=colors.get(strategy, 'gray'), alpha=0.7)
+    
+    axes[0].set_title(' Время выполнения (мс)')
+    axes[0].set_xticks(x + width)
+    axes[0].set_xticklabels(mazes, rotation=45, ha='right')
+    axes[0].legend()
+    axes[0].grid(True, alpha=0.3)
+    
+    axes[1].set_title(' Посещённые клетки')
+    axes[1].set_xticks(x + width)
+    axes[1].set_xticklabels(mazes, rotation=45, ha='right')
+    axes[1].legend()
+    axes[1].grid(True, alpha=0.3)
+    
+    axes[2].set_title(' Длина пути')
+    axes[2].set_xticks(x + width)
+    axes[2].set_xticklabels(mazes, rotation=45, ha='right')
+    axes[2].legend()
+    axes[2].grid(True, alpha=0.3)
+    
+    plt.tight_layout()
+    plt.savefig('experiment_results.png', dpi=150, bbox_inches='tight')
+    plt.show()
+    
+
+
+if __name__ == "__main__":
+    plot_results()