diff --git a/Ezhovnd/1 задание.py b/Ezhovnd/2 задание.py
similarity index 97%
rename from Ezhovnd/1 задание.py
rename to Ezhovnd/2 задание.py
index de06630..d327aff 100644
--- a/Ezhovnd/1 задание.py	
+++ b/Ezhovnd/2 задание.py	
@@ -1,285 +1,285 @@
-import csv
-import time
-import os
-import random
-from collections import deque
-import heapq
-import matplotlib.pyplot as plt
-import pandas as pd
-
-class Cell:
-    def __init__(self, x, y):
-        self.x = x
-        self.y = y
-        self.is_wall = False
-        self.is_start = False
-        self.is_exit = False
-
-    def isPassable(self):
-        return not self.is_wall
-
-class Maze:
-    def __init__(self, width, height):
-        self.width = width
-        self.height = height
-        self.cells = []
-        self.start = None
-        self.exit = None
-
-    def getCell(self, x, y):
-        if 0 <= x < self.width and 0 <= y < self.height:
-            return self.cells[y][x]
-        return None
-
-    def getNeighbors(self, cell):
-        neighbors = []
-        for dx, dy in [(-1, 0), (1, 0), (0, -1), (0, 1)]:
-            neighbor = self.getCell(cell.x + dx, cell.y + dy)
-            if neighbor and neighbor.isPassable():
-                neighbors.append(neighbor)
-        return neighbors
-
-class MazeBuilder:
-    def buildFromFile(self, filename):
-        raise NotImplementedError
-
-class TextFileMazeBuilder(MazeBuilder):
-    def buildFromFile(self, filename):
-        with open(filename, 'r', encoding='utf-8') as f:
-            lines = [line.rstrip('\n') for line in f.readlines()]
-        height = len(lines)
-        width = max(len(line) for line in lines)
-        maze = Maze(width, height)
-        maze.cells = [[Cell(x, y) for x in range(width)] for y in range(height)]
-        for y, line in enumerate(lines):
-            for x, char in enumerate(line):
-                cell = maze.cells[y][x]
-                if char == '#':
-                    cell.is_wall = True
-                elif char == 'S':
-                    cell.is_start = True
-                    maze.start = cell
-                elif char == 'E':
-                    cell.is_exit = True
-                    maze.exit = cell
-        if maze.start is None or maze.exit is None:
-            raise ValueError("В файле должны быть символы S и E")
-        return maze
-
-class PathFindingStrategy:
-    def findPath(self, maze, start, exit):
-        raise NotImplementedError
-
-class BFSStrategy(PathFindingStrategy):
-    def findPath(self, maze, start, exit):
-        queue = deque([start])
-        came_from = {start: None}
-        visited = set([start])
-        while queue:
-            current = queue.popleft()
-            if current == exit:
-                break
-            for neighbor in maze.getNeighbors(current):
-                if neighbor not in visited:
-                    visited.add(neighbor)
-                    queue.append(neighbor)
-                    came_from[neighbor] = current
-        path = self._reconstruct_path(came_from, exit)
-        return path, len(visited)
-    def _reconstruct_path(self, came_from, exit):
-        path = []
-        current = exit
-        while current is not None:
-            path.append(current)
-            current = came_from.get(current)
-        path.reverse()
-        return path if path and path[0] == came_from.get(exit) or path[0] == exit else []
-
-class DFSStrategy(PathFindingStrategy):
-    def findPath(self, maze, start, exit):
-        stack = [start]
-        came_from = {start: None}
-        visited = set([start])
-        while stack:
-            current = stack.pop()
-            if current == exit:
-                break
-            for neighbor in maze.getNeighbors(current):
-                if neighbor not in visited:
-                    visited.add(neighbor)
-                    stack.append(neighbor)
-                    came_from[neighbor] = current
-        path = self._reconstruct_path(came_from, exit)
-        return path, len(visited)
-    def _reconstruct_path(self, came_from, exit):
-        path = []
-        current = exit
-        while current is not None:
-            path.append(current)
-            current = came_from.get(current)
-        path.reverse()
-        return path
-
-class AStarStrategy(PathFindingStrategy):
-    def heuristic(self, a, b):
-        return abs(a.x - b.x) + abs(a.y - b.y)
-    def findPath(self, maze, start, exit):
-        open_set = []
-        counter = 0
-        heapq.heappush(open_set, (0, counter, start))
-        came_from = {start: None}
-        g_score = {start: 0}
-        visited = set()
-        while open_set:
-            _, _, current = heapq.heappop(open_set)
-            if current in visited:
-                continue
-            visited.add(current)
-            if current == exit:
-                break
-            for neighbor in maze.getNeighbors(current):
-                tentative_g = g_score[current] + 1
-                if neighbor not in g_score or tentative_g < g_score[neighbor]:
-                    came_from[neighbor] = current
-                    g_score[neighbor] = tentative_g
-                    f_score = tentative_g + self.heuristic(neighbor, exit)
-                    counter += 1
-                    heapq.heappush(open_set, (f_score, counter, neighbor))
-        path = self._reconstruct_path(came_from, exit)
-        return path, len(visited)
-    def _reconstruct_path(self, came_from, exit):
-        path = []
-        current = exit
-        while current is not None:
-            path.append(current)
-            current = came_from.get(current)
-        path.reverse()
-        return path
-
-class SearchStats:
-    def __init__(self, time_ms, visited_cells, path_length):
-        self.time_ms = time_ms
-        self.visited_cells = visited_cells
-        self.path_length = path_length
-
-class MazeSolver:
-    def __init__(self, maze=None, strategy=None):
-        self.maze = maze
-        self.strategy = strategy
-    def setStrategy(self, strategy):
-        self.strategy = strategy
-    def solve(self):
-        if not self.maze or not self.strategy:
-            return None
-        start_time = time.perf_counter()
-        path, visited_count = self.strategy.findPath(self.maze, self.maze.start, self.maze.exit)
-        end_time = time.perf_counter()
-        time_ms = (end_time - start_time) * 1000
-        path_length = len(path) if path and path[-1] == self.maze.exit else 0
-        return SearchStats(round(time_ms, 4), visited_count, path_length)
-
-def create_maze_with_walls(size, wall_probability=0.3):
-    maze = Maze(size, size)
-    maze.cells = [[Cell(x, y) for x in range(size)] for y in range(size)]
-    for y in range(size):
-        for x in range(size):
-            if random.random() < wall_probability:
-                maze.cells[y][x].is_wall = True
-    maze.start = maze.cells[0][0]
-    maze.exit = maze.cells[size-1][size-1]
-    maze.start.is_start = True
-    maze.exit.is_exit = True
-    maze.start.is_wall = False
-    maze.exit.is_wall = False
-    return maze
-
-def create_empty_maze(size):
-    maze = Maze(size, size)
-    maze.cells = [[Cell(x, y) for x in range(size)] for y in range(size)]
-    maze.start = maze.cells[0][0]
-    maze.exit = maze.cells[size-1][size-1]
-    maze.start.is_start = True
-    maze.exit.is_exit = True
-    return maze
-
-def create_no_exit_maze(size, wall_probability=0.3):
-    maze = create_maze_with_walls(size, wall_probability)
-    maze.exit.is_wall = True
-    return maze
-
-def run_experiment():
-    maze_configs = {
-        "10x10_simple": {"size": 10, "type": "normal", "wall_prob": 0.1},
-        "50x50_with_deadends": {"size": 50, "type": "normal", "wall_prob": 0.3},
-        "100x100_complex": {"size": 100, "type": "normal", "wall_prob": 0.35},
-        "empty": {"size": 30, "type": "empty"},
-        "no_exit": {"size": 30, "type": "no_exit", "wall_prob": 0.3},
-    }
-    strategies = {
-        "BFS": BFSStrategy(),
-        "DFS": DFSStrategy(),
-        "AStar": AStarStrategy()
-    }
-    results = []
-    for maze_name, config in maze_configs.items():
-        size = config["size"]
-        maze_type = config["type"]
-        if maze_type == "empty":
-            maze = create_empty_maze(size)
-        elif maze_type == "no_exit":
-            maze = create_no_exit_maze(size, config.get("wall_prob", 0.3))
-        else:
-            maze = create_maze_with_walls(size, config.get("wall_prob", 0.3))
-        for strat_name, strategy in strategies.items():
-            solver = MazeSolver(maze, strategy)
-            times, visited_list, lengths = [], [], []
-            for _ in range(7):
-                stats = solver.solve()
-                times.append(stats.time_ms)
-                visited_list.append(stats.visited_cells)
-                lengths.append(stats.path_length)
-            avg_time = sum(times) / len(times)
-            avg_visited = sum(visited_list) / len(visited_list)
-            avg_length = sum(lengths) / len(lengths)
-            results.append([
-                maze_name, strat_name,
-                round(avg_time, 4),
-                int(avg_visited),
-                int(avg_length)
-            ])
-    os.makedirs("results", exist_ok=True)
-    csv_path = "results/results.csv"
-    with open(csv_path, "w", newline="", encoding="utf-8") as f:
-        writer = csv.writer(f)
-        writer.writerow(["лабиринт", "стратегия", "время_мс", "посещено_клеток", "длина_пути"])
-        writer.writerows(results)
-    df = pd.read_csv(csv_path)
-    plt.figure(figsize=(12, 6))
-    for strat in df["стратегия"].unique():
-        subset = df[df["стратегия"] == strat]
-        plt.plot(subset["лабиринт"], subset["время_мс"], marker='o', label=strat)
-    plt.title("Сравнение времени работы алгоритмов")
-    plt.xlabel("Лабиринт")
-    plt.ylabel("Время (мс)")
-    plt.legend()
-    plt.grid(True)
-    plt.xticks(rotation=45)
-    plt.tight_layout()
-    plt.savefig("results/time_comparison.png")
-    plt.close()
-    plt.figure(figsize=(12, 6))
-    for strat in df["стратегия"].unique():
-        subset = df[df["стратегия"] == strat]
-        plt.plot(subset["лабиринт"], subset["посещено_клеток"], marker='o', label=strat)
-    plt.title("Количество посещённых клеток")
-    plt.xlabel("Лабиринт")
-    plt.ylabel("Посещено клеток")
-    plt.legend()
-    plt.grid(True)
-    plt.xticks(rotation=45)
-    plt.tight_layout()
-    plt.savefig("results/visited_comparison.png")
-    plt.close()
-
-if __name__ == "__main__":
+import csv
+import time
+import os
+import random
+from collections import deque
+import heapq
+import matplotlib.pyplot as plt
+import pandas as pd
+
+class Cell:
+    def __init__(self, x, y):
+        self.x = x
+        self.y = y
+        self.is_wall = False
+        self.is_start = False
+        self.is_exit = False
+
+    def isPassable(self):
+        return not self.is_wall
+
+class Maze:
+    def __init__(self, width, height):
+        self.width = width
+        self.height = height
+        self.cells = []
+        self.start = None
+        self.exit = None
+
+    def getCell(self, x, y):
+        if 0 <= x < self.width and 0 <= y < self.height:
+            return self.cells[y][x]
+        return None
+
+    def getNeighbors(self, cell):
+        neighbors = []
+        for dx, dy in [(-1, 0), (1, 0), (0, -1), (0, 1)]:
+            neighbor = self.getCell(cell.x + dx, cell.y + dy)
+            if neighbor and neighbor.isPassable():
+                neighbors.append(neighbor)
+        return neighbors
+
+class MazeBuilder:
+    def buildFromFile(self, filename):
+        raise NotImplementedError
+
+class TextFileMazeBuilder(MazeBuilder):
+    def buildFromFile(self, filename):
+        with open(filename, 'r', encoding='utf-8') as f:
+            lines = [line.rstrip('\n') for line in f.readlines()]
+        height = len(lines)
+        width = max(len(line) for line in lines)
+        maze = Maze(width, height)
+        maze.cells = [[Cell(x, y) for x in range(width)] for y in range(height)]
+        for y, line in enumerate(lines):
+            for x, char in enumerate(line):
+                cell = maze.cells[y][x]
+                if char == '#':
+                    cell.is_wall = True
+                elif char == 'S':
+                    cell.is_start = True
+                    maze.start = cell
+                elif char == 'E':
+                    cell.is_exit = True
+                    maze.exit = cell
+        if maze.start is None or maze.exit is None:
+            raise ValueError("В файле должны быть символы S и E")
+        return maze
+
+class PathFindingStrategy:
+    def findPath(self, maze, start, exit):
+        raise NotImplementedError
+
+class BFSStrategy(PathFindingStrategy):
+    def findPath(self, maze, start, exit):
+        queue = deque([start])
+        came_from = {start: None}
+        visited = set([start])
+        while queue:
+            current = queue.popleft()
+            if current == exit:
+                break
+            for neighbor in maze.getNeighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    queue.append(neighbor)
+                    came_from[neighbor] = current
+        path = self._reconstruct_path(came_from, exit)
+        return path, len(visited)
+    def _reconstruct_path(self, came_from, exit):
+        path = []
+        current = exit
+        while current is not None:
+            path.append(current)
+            current = came_from.get(current)
+        path.reverse()
+        return path if path and path[0] == came_from.get(exit) or path[0] == exit else []
+
+class DFSStrategy(PathFindingStrategy):
+    def findPath(self, maze, start, exit):
+        stack = [start]
+        came_from = {start: None}
+        visited = set([start])
+        while stack:
+            current = stack.pop()
+            if current == exit:
+                break
+            for neighbor in maze.getNeighbors(current):
+                if neighbor not in visited:
+                    visited.add(neighbor)
+                    stack.append(neighbor)
+                    came_from[neighbor] = current
+        path = self._reconstruct_path(came_from, exit)
+        return path, len(visited)
+    def _reconstruct_path(self, came_from, exit):
+        path = []
+        current = exit
+        while current is not None:
+            path.append(current)
+            current = came_from.get(current)
+        path.reverse()
+        return path
+
+class AStarStrategy(PathFindingStrategy):
+    def heuristic(self, a, b):
+        return abs(a.x - b.x) + abs(a.y - b.y)
+    def findPath(self, maze, start, exit):
+        open_set = []
+        counter = 0
+        heapq.heappush(open_set, (0, counter, start))
+        came_from = {start: None}
+        g_score = {start: 0}
+        visited = set()
+        while open_set:
+            _, _, current = heapq.heappop(open_set)
+            if current in visited:
+                continue
+            visited.add(current)
+            if current == exit:
+                break
+            for neighbor in maze.getNeighbors(current):
+                tentative_g = g_score[current] + 1
+                if neighbor not in g_score or tentative_g < g_score[neighbor]:
+                    came_from[neighbor] = current
+                    g_score[neighbor] = tentative_g
+                    f_score = tentative_g + self.heuristic(neighbor, exit)
+                    counter += 1
+                    heapq.heappush(open_set, (f_score, counter, neighbor))
+        path = self._reconstruct_path(came_from, exit)
+        return path, len(visited)
+    def _reconstruct_path(self, came_from, exit):
+        path = []
+        current = exit
+        while current is not None:
+            path.append(current)
+            current = came_from.get(current)
+        path.reverse()
+        return path
+
+class SearchStats:
+    def __init__(self, time_ms, visited_cells, path_length):
+        self.time_ms = time_ms
+        self.visited_cells = visited_cells
+        self.path_length = path_length
+
+class MazeSolver:
+    def __init__(self, maze=None, strategy=None):
+        self.maze = maze
+        self.strategy = strategy
+    def setStrategy(self, strategy):
+        self.strategy = strategy
+    def solve(self):
+        if not self.maze or not self.strategy:
+            return None
+        start_time = time.perf_counter()
+        path, visited_count = self.strategy.findPath(self.maze, self.maze.start, self.maze.exit)
+        end_time = time.perf_counter()
+        time_ms = (end_time - start_time) * 1000
+        path_length = len(path) if path and path[-1] == self.maze.exit else 0
+        return SearchStats(round(time_ms, 4), visited_count, path_length)
+
+def create_maze_with_walls(size, wall_probability=0.3):
+    maze = Maze(size, size)
+    maze.cells = [[Cell(x, y) for x in range(size)] for y in range(size)]
+    for y in range(size):
+        for x in range(size):
+            if random.random() < wall_probability:
+                maze.cells[y][x].is_wall = True
+    maze.start = maze.cells[0][0]
+    maze.exit = maze.cells[size-1][size-1]
+    maze.start.is_start = True
+    maze.exit.is_exit = True
+    maze.start.is_wall = False
+    maze.exit.is_wall = False
+    return maze
+
+def create_empty_maze(size):
+    maze = Maze(size, size)
+    maze.cells = [[Cell(x, y) for x in range(size)] for y in range(size)]
+    maze.start = maze.cells[0][0]
+    maze.exit = maze.cells[size-1][size-1]
+    maze.start.is_start = True
+    maze.exit.is_exit = True
+    return maze
+
+def create_no_exit_maze(size, wall_probability=0.3):
+    maze = create_maze_with_walls(size, wall_probability)
+    maze.exit.is_wall = True
+    return maze
+
+def run_experiment():
+    maze_configs = {
+        "10x10_simple": {"size": 10, "type": "normal", "wall_prob": 0.1},
+        "50x50_with_deadends": {"size": 50, "type": "normal", "wall_prob": 0.3},
+        "100x100_complex": {"size": 100, "type": "normal", "wall_prob": 0.35},
+        "empty": {"size": 30, "type": "empty"},
+        "no_exit": {"size": 30, "type": "no_exit", "wall_prob": 0.3},
+    }
+    strategies = {
+        "BFS": BFSStrategy(),
+        "DFS": DFSStrategy(),
+        "AStar": AStarStrategy()
+    }
+    results = []
+    for maze_name, config in maze_configs.items():
+        size = config["size"]
+        maze_type = config["type"]
+        if maze_type == "empty":
+            maze = create_empty_maze(size)
+        elif maze_type == "no_exit":
+            maze = create_no_exit_maze(size, config.get("wall_prob", 0.3))
+        else:
+            maze = create_maze_with_walls(size, config.get("wall_prob", 0.3))
+        for strat_name, strategy in strategies.items():
+            solver = MazeSolver(maze, strategy)
+            times, visited_list, lengths = [], [], []
+            for _ in range(7):
+                stats = solver.solve()
+                times.append(stats.time_ms)
+                visited_list.append(stats.visited_cells)
+                lengths.append(stats.path_length)
+            avg_time = sum(times) / len(times)
+            avg_visited = sum(visited_list) / len(visited_list)
+            avg_length = sum(lengths) / len(lengths)
+            results.append([
+                maze_name, strat_name,
+                round(avg_time, 4),
+                int(avg_visited),
+                int(avg_length)
+            ])
+    os.makedirs("results", exist_ok=True)
+    csv_path = "results/results.csv"
+    with open(csv_path, "w", newline="", encoding="utf-8") as f:
+        writer = csv.writer(f)
+        writer.writerow(["лабиринт", "стратегия", "время_мс", "посещено_клеток", "длина_пути"])
+        writer.writerows(results)
+    df = pd.read_csv(csv_path)
+    plt.figure(figsize=(12, 6))
+    for strat in df["стратегия"].unique():
+        subset = df[df["стратегия"] == strat]
+        plt.plot(subset["лабиринт"], subset["время_мс"], marker='o', label=strat)
+    plt.title("Сравнение времени работы алгоритмов")
+    plt.xlabel("Лабиринт")
+    plt.ylabel("Время (мс)")
+    plt.legend()
+    plt.grid(True)
+    plt.xticks(rotation=45)
+    plt.tight_layout()
+    plt.savefig("results/time_comparison.png")
+    plt.close()
+    plt.figure(figsize=(12, 6))
+    for strat in df["стратегия"].unique():
+        subset = df[df["стратегия"] == strat]
+        plt.plot(subset["лабиринт"], subset["посещено_клеток"], marker='o', label=strat)
+    plt.title("Количество посещённых клеток")
+    plt.xlabel("Лабиринт")
+    plt.ylabel("Посещено клеток")
+    plt.legend()
+    plt.grid(True)
+    plt.xticks(rotation=45)
+    plt.tight_layout()
+    plt.savefig("results/visited_comparison.png")
+    plt.close()
+
+if __name__ == "__main__":
     run_experiment()
\ No newline at end of file