Merge pull request '[1] 1-st exercise' (#342) from agafonovdm/2026-rff_mp:agafonovdm into develop

Reviewed-on: #342

agafonovdm/docs/data/1zad/1-st_ex.py

@@ -0,0 +1,292 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+
+import time
+import random
+import csv
+import sys
+sys.setrecursionlimit(30000)
+
+def ll_create_node(name, phone):
+    return {'name': name, 'phone': phone, 'next': None}
+
+def ll_insert(head, name, phone):
+    if head is None:
+        return ll_create_node(name, phone)
+    
+    if head['name'] == name:
+        head['phone'] = phone
+        return head
+    
+    current = head
+    while current['next'] is not None:
+        if current['next']['name'] == name:
+            current['next']['phone'] = phone
+            return head
+        current = current['next']
+    
+    current['next'] = ll_create_node(name, phone)
+    return head
+
+def ll_find(head, name):
+    current = head
+    while current is not None:
+        if current['name'] == name:
+            return current['phone']
+        current = current['next']
+    return None
+
+def ll_delete(head, name):
+    if head is None:
+        return None
+    
+    if head['name'] == name:
+        return head['next']
+    
+    current = head
+    while current['next'] is not None:
+        if current['next']['name'] == name:
+            current['next'] = current['next']['next']
+            return head
+        current = current['next']
+    
+    return head
+
+def ll_list_all(head):
+    records = []
+    current = head
+    while current is not None:
+        records.append((current['name'], current['phone']))
+        current = current['next']
+    records.sort(key=lambda x: x[0])
+    return records
+
+def hash_function(name, table_size):
+    return sum(ord(c) for c in name) % table_size
+
+def ht_create_table(size=2000):
+    return [None] * size
+
+def ht_insert(table, name, phone):
+    index = hash_function(name, len(table))
+    table[index] = ll_insert(table[index], name, phone)
+
+def ht_find(table, name):
+    index = hash_function(name, len(table))
+    return ll_find(table[index], name)
+
+def ht_delete(table, name):
+    index = hash_function(name, len(table))
+    table[index] = ll_delete(table[index], name)
+
+def ht_list_all(table):
+    all_records = []
+    for bucket in table:
+        if bucket is not None:
+            current = bucket
+            while current is not None:
+                all_records.append((current['name'], current['phone']))
+                current = current['next']
+    all_records.sort(key=lambda x: x[0])
+    return all_records
+
+def bst_create_node(name, phone):
+    return {'name': name, 'phone': phone, 'left': None, 'right': None}
+
+def bst_insert(root, name, phone):
+    if root is None:
+        return bst_create_node(name, phone)
+    
+    current = root
+    while True:
+        if name < current['name']:
+            if current['left'] is None:
+                current['left'] = bst_create_node(name, phone)
+                break
+            else:
+                current = current['left']
+        elif name > current['name']:
+            if current['right'] is None:
+                current['right'] = bst_create_node(name, phone)
+                break
+            else:
+                current = current['right']
+        else:
+            current['phone'] = phone
+            break
+    
+    return root
+
+def bst_find(root, name):
+    current = root
+    while current is not None:
+        if name < current['name']:
+            current = current['left']
+        elif name > current['name']:
+            current = current['right']
+        else:
+            return current['phone']
+    return None
+
+def bst_find_min(node):
+    current = node
+    while current['left'] is not None:
+        current = current['left']
+    return current
+
+def bst_delete(root, name):
+    if root is None:
+        return None
+    
+    parent = None
+    current = root
+    
+    while current is not None and current['name'] != name:
+        parent = current
+        if name < current['name']:
+            current = current['left']
+        else:
+            current = current['right']
+    
+    if current is None:
+        return root
+    
+    if current['left'] is None or current['right'] is None:
+        if current['left'] is not None:
+            child = current['left']
+        else:
+            child = current['right']
+        
+        if parent is None:
+            return child
+        
+        if parent['left'] == current:
+            parent['left'] = child
+        else:
+            parent['right'] = child
+    else:
+        successor_parent = current
+        successor = current['right']
+        
+        while successor['left'] is not None:
+            successor_parent = successor
+            successor = successor['left']
+        
+        current['name'] = successor['name']
+        current['phone'] = successor['phone']
+        
+        if successor_parent['left'] == successor:
+            successor_parent['left'] = successor['right']
+        else:
+            successor_parent['right'] = successor['right']
+    
+    return root
+
+def bst_list_all(root):
+    records = []
+    stack = []
+    current = root
+    
+    while stack or current is not None:
+        while current is not None:
+            stack.append(current)
+            current = current['left']
+        current = stack.pop()
+        records.append((current['name'], current['phone']))
+        current = current['right']
+    
+    return records
+
+def generate_data(n=10000):
+    records = [(f"User_{i:05d}", f"+7-999-{i:06d}") for i in range(n)]
+    records_shuffled = records.copy()
+    random.shuffle(records_shuffled)
+    records_sorted = sorted(records, key=lambda x: x[0])
+    return records_shuffled, records_sorted
+
+def run_experiment(structure_name, insert_func, find_func, delete_func, 
+                   list_all_func, init_func, records, n_find=100):
+    
+    data = init_func()
+    names = [r[0] for r in records]
+    
+    start = time.perf_counter()
+    for name, phone in records:
+        if structure_name == "HashTable":
+            insert_func(data, name, phone)
+        else:
+            data = insert_func(data, name, phone)
+    insert_time = time.perf_counter() - start
+    
+    find_names = random.sample(names, min(n_find, len(names)))
+    missing_names = [f"None_{i}" for i in range(10)]
+    all_find_names = find_names + missing_names
+    
+    start = time.perf_counter()
+    for name in all_find_names:
+        if structure_name == "HashTable":
+            find_func(data, name)
+        else:
+            find_func(data, name)
+    find_time = time.perf_counter() - start
+    
+    delete_names = random.sample(names, min(50, len(names)))
+    start = time.perf_counter()
+    for name in delete_names:
+        if structure_name == "HashTable":
+            delete_func(data, name)
+        else:
+            data = delete_func(data, name)
+    delete_time = time.perf_counter() - start
+    
+    return insert_time, find_time, delete_time
+
+def main():
+    print("Generating test data...")
+    records_shuffled, records_sorted = generate_data(10000)
+    
+    results = []
+    
+    structures = [
+        ("LinkedList", ll_insert, ll_find, ll_delete, ll_list_all, lambda: None),
+        ("HashTable", ht_insert, ht_find, ht_delete, ht_list_all, lambda: ht_create_table(2000)),
+        ("BST", bst_insert, bst_find, bst_delete, bst_list_all, lambda: None)
+    ]
+    
+    for mode_name, records in [("random", records_shuffled), ("sorted", records_sorted)]:
+        print(f"\nMode: {mode_name}")
+        
+        for struct_name, insert_f, find_f, delete_f, list_f, init_f in structures:
+            print(f"  Testing {struct_name}...")
+            
+            times = []
+            for run in range(5):
+                insert_t, find_t, delete_t = run_experiment(
+                    struct_name, insert_f, find_f, delete_f, list_f, init_f, records
+                )
+                times.append((insert_t, find_t, delete_t))
+                print(f"    Run {run+1}: insert={insert_t:.4f}s, find={find_t:.4f}s, delete={delete_t:.4f}s")
+            
+            avg_insert = sum(t[0] for t in times) / 5
+            avg_find = sum(t[1] for t in times) / 5
+            avg_delete = sum(t[2] for t in times) / 5
+            
+            results.append([struct_name, mode_name, "insert", avg_insert])
+            results.append([struct_name, mode_name, "find", avg_find])
+            results.append([struct_name, mode_name, "delete", avg_delete])
+    
+    with open("results.csv", "w", newline="", encoding="utf-8") as f:
+        writer = csv.writer(f)
+        writer.writerow(["Structure", "Mode", "Operation", "Time_seconds"])
+        writer.writerows(results)
+    
+    print("\n" + "="*60)
+    print("RESULTS (average over 5 runs):")
+    print("="*60)
+    for row in results:
+        print(f"{row[0]:12} | {row[1]:8} | {row[2]:8} | {row[3]:.6f} sec")
+    
+    print("\nResults saved to results.csv")
+
+if __name__ == "__main__":
+    main()

agafonovdm/docs/data/1zad/results.csv

@@ -0,0 +1,19 @@
+Structure,Mode,Operation,Time_seconds
+LinkedList,random,insert,3.115811080000276
+LinkedList,random,find,0.02396312000018952
+LinkedList,random,delete,0.016048219999720458
+HashTable,random,insert,0.18448304000012286
+HashTable,random,find,0.0012929600005008978
+HashTable,random,delete,0.0009329200001957361
+BST,random,insert,0.017231119999996734
+BST,random,find,0.00014155999961076304
+BST,random,delete,9.299999983340968e-05
+LinkedList,sorted,insert,2.780292439999903
+LinkedList,sorted,find,0.02136590000045544
+LinkedList,sorted,delete,0.014907859999584615
+HashTable,sorted,insert,0.16707750000023225
+HashTable,sorted,find,0.0012113199998566415
+HashTable,sorted,delete,0.0008899600001313956
+BST,sorted,insert,3.844869280000421
+BST,sorted,find,0.031808019999880345
+BST,sorted,delete,0.016554539999560802

agafonovdm/docs/data/2zad/2-nd_ex.py

@@ -0,0 +1,589 @@
+import time
+import heapq
+from collections import deque
+from typing import List, Optional, Dict, Tuple
+from abc import ABC, abstractmethod
+import csv
+import random
+
+
+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
+
+
+class Maze:
+    def __init__(self, width: int, height: int):
+        self.width = width
+        self.height = height
+        self.cells = [[Cell(x, y) for y in range(height)] for x in range(width)]
+        self.start: Optional[Cell] = None
+        self.exit: Optional[Cell] = None
+
+    def get_cell(self, x: int, y: int) -> Optional[Cell]:
+        if 0 <= x < self.width and 0 <= y < self.height:
+            return self.cells[x][y]
+        return None
+
+    def get_neighbors(self, cell: Cell) -> List[Cell]:
+        neighbors = []
+        for dx, dy in [(-1, 0), (1, 0), (0, -1), (0, 1)]:
+            nx, ny = cell.x + dx, cell.y + dy
+            nb = self.get_cell(nx, ny)
+            if nb and nb.is_passable():
+                neighbors.append(nb)
+        return neighbors
+
+
+class MazeBuilder(ABC):
+    @abstractmethod
+    def build_from_file(self, filename: str) -> Maze:
+        pass
+
+
+class TextFileMazeBuilder(MazeBuilder):
+    def build_from_file(self, filename: str) -> Maze:
+        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) if height > 0 else 0
+        maze = Maze(width, height)
+
+        for y, line in enumerate(lines):
+            for x, ch in enumerate(line):
+                cell = maze.get_cell(x, y)
+                if cell is None:
+                    continue
+                if ch == '#':
+                    cell.is_wall = True
+                elif ch == 'S':
+                    cell.is_start = True
+                    maze.start = cell
+                elif ch == 'E':
+                    cell.is_exit = True
+                    maze.exit = cell
+                elif ch == ' ':
+                    pass
+                else:
+                    raise ValueError(f"Unknown character '{ch}' at ({x},{y})")
+
+        if maze.start is None or maze.exit is None:
+            raise ValueError("Maze must have start (S) and exit (E)")
+        return maze
+
+
+class PathFindingStrategy(ABC):
+    @abstractmethod
+    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
+        pass
+    
+    @abstractmethod
+    def get_name(self) -> str:
+        pass
+
+
+class BFSStrategy(PathFindingStrategy):
+    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
+        queue = deque([start])
+        came_from = {start: None}
+        
+        while queue:
+            current = queue.popleft()
+            if current == exit:
+                break
+            for nb in maze.get_neighbors(current):
+                if nb not in came_from:
+                    came_from[nb] = current
+                    queue.append(nb)
+        
+        if exit not in came_from:
+            return []
+        
+        path = []
+        cur = exit
+        while cur:
+            path.append(cur)
+            cur = came_from[cur]
+        path.reverse()
+        return path
+    
+    def get_name(self) -> str:
+        return "BFS"
+
+
+class DFSStrategy(PathFindingStrategy):
+    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
+        stack = [start]
+        came_from = {start: None}
+        
+        while stack:
+            current = stack.pop()
+            if current == exit:
+                break
+            for nb in maze.get_neighbors(current):
+                if nb not in came_from:
+                    came_from[nb] = current
+                    stack.append(nb)
+        
+        if exit not in came_from:
+            return []
+        
+        path = []
+        cur = exit
+        while cur:
+            path.append(cur)
+            cur = came_from[cur]
+        path.reverse()
+        return path
+    
+    def get_name(self) -> str:
+        return "DFS"
+
+
+class AStarStrategy(PathFindingStrategy):
+    def _heuristic(self, a: Cell, b: Cell) -> int:
+        return abs(a.x - b.x) + abs(a.y - b.y)
+    
+    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
+        open_set = []
+        heapq.heappush(open_set, (0, id(start), start))
+        came_from = {}
+        g_score = {start: 0}
+        f_score = {start: self._heuristic(start, exit)}
+        
+        while open_set:
+            _, _, current = heapq.heappop(open_set)
+            
+            if current == exit:
+                path = []
+                cur = exit
+                while cur in came_from:
+                    path.append(cur)
+                    cur = came_from[cur]
+                path.append(start)
+                path.reverse()
+                return path
+            
+            for neighbor in maze.get_neighbors(current):
+                tentative_g = g_score[current] + 1
+                if tentative_g < g_score.get(neighbor, float('inf')):
+                    came_from[neighbor] = current
+                    g_score[neighbor] = tentative_g
+                    f_score[neighbor] = tentative_g + self._heuristic(neighbor, exit)
+                    heapq.heappush(open_set, (f_score[neighbor], id(neighbor), neighbor))
+        
+        return []
+    
+    def get_name(self) -> str:
+        return "A*"
+
+
+class DijkstraStrategy(PathFindingStrategy):
+    def find_path(self, maze: Maze, start: Cell, exit: Cell) -> List[Cell]:
+        pq = [(0, id(start), start)]
+        distances = {start: 0}
+        came_from = {start: None}
+        
+        while pq:
+            dist, _, current = heapq.heappop(pq)
+            
+            if current == exit:
+                break
+            
+            if dist > distances[current]:
+                continue
+            
+            for neighbor in maze.get_neighbors(current):
+                new_dist = dist + 1
+                if new_dist < distances.get(neighbor, float('inf')):
+                    distances[neighbor] = new_dist
+                    came_from[neighbor] = current
+                    heapq.heappush(pq, (new_dist, id(neighbor), neighbor))
+        
+        if exit not in came_from:
+            return []
+        
+        path = []
+        cur = exit
+        while cur:
+            path.append(cur)
+            cur = came_from[cur]
+        path.reverse()
+        return path
+    
+    def get_name(self) -> str:
+        return "Dijkstra"
+
+
+class SearchStats:
+    def __init__(self, time_ms: float, visited_cells: int, path_length: int):
+        self.time_ms = time_ms
+        self.visited_cells = visited_cells
+        self.path_length = path_length
+    
+    def __str__(self):
+        return f"Time: {self.time_ms:.2f}ms, Visited: {self.visited_cells}, Path: {self.path_length}"
+
+
+class MazeSolver:
+    def __init__(self, maze: Maze, strategy: PathFindingStrategy):
+        self.maze = maze
+        self.strategy = strategy
+    
+    def set_strategy(self, strategy: PathFindingStrategy):
+        self.strategy = strategy
+    
+    def solve(self) -> Tuple[List[Cell], SearchStats]:
+        visited_before = set()
+        for x in range(self.maze.width):
+            for y in range(self.maze.height):
+                cell = self.maze.get_cell(x, y)
+                if cell and cell.is_passable():
+                    visited_before.add(cell)
+        
+        start_time = time.perf_counter()
+        path = self.strategy.find_path(self.maze, self.maze.start, self.maze.exit)
+        end_time = time.perf_counter()
+        
+        visited_after = set()
+        for x in range(self.maze.width):
+            for y in range(self.maze.height):
+                cell = self.maze.get_cell(x, y)
+                if cell and cell.is_passable():
+                    visited_after.add(cell)
+        
+        visited_cells = len(visited_after)
+        
+        stats = SearchStats(
+            time_ms=(end_time - start_time) * 1000,
+            visited_cells=visited_cells,
+            path_length=len(path) if path else 0
+        )
+        
+        return path, stats
+
+
+class Player:
+    def __init__(self, start_cell: Cell):
+        self.current_cell = start_cell
+        self.previous_cell = None
+    
+    def move_to(self, cell: Cell) -> bool:
+        if cell.is_passable():
+            self.previous_cell = self.current_cell
+            self.current_cell = cell
+            return True
+        return False
+    
+    def undo(self):
+        if self.previous_cell:
+            self.current_cell, self.previous_cell = self.previous_cell, None
+            return True
+        return False
+
+
+class Command(ABC):
+    @abstractmethod
+    def execute(self) -> bool:
+        pass
+    
+    @abstractmethod
+    def undo(self):
+        pass
+
+
+class MoveCommand(Command):
+    def __init__(self, player: Player, maze: Maze, direction: str):
+        self.player = player
+        self.maze = maze
+        self.direction = direction
+        self.executed = False
+    
+    def execute(self) -> bool:
+        dx, dy = 0, 0
+        if self.direction == 'W' or self.direction == 'w':
+            dy = -1
+        elif self.direction == 'S' or self.direction == 's':
+            dy = 1
+        elif self.direction == 'A' or self.direction == 'a':
+            dx = -1
+        elif self.direction == 'D' or self.direction == 'd':
+            dx = 1
+        
+        new_x = self.player.current_cell.x + dx
+        new_y = self.player.current_cell.y + dy
+        new_cell = self.maze.get_cell(new_x, new_y)
+        
+        if new_cell and new_cell.is_passable():
+            self.executed = self.player.move_to(new_cell)
+            return self.executed
+        return False
+    
+    def undo(self):
+        if self.executed:
+            self.player.undo()
+            self.executed = False
+
+
+class ConsoleView:
+    @staticmethod
+    def render(maze: Maze, player: Optional[Player] = None, path: Optional[List[Cell]] = None):
+        path_set = set()
+        if path:
+            path_set = set(path)
+        
+        for y in range(maze.height):
+            line = ""
+            for x in range(maze.width):
+                cell = maze.get_cell(x, y)
+                if not cell:
+                    line += " "
+                elif player and player.current_cell == cell:
+                    line += "P"
+                elif cell.is_start:
+                    line += "S"
+                elif cell.is_exit:
+                    line += "E"
+                elif cell.is_wall:
+                    line += "#"
+                elif path and cell in path_set:
+                    line += "."
+                else:
+                    line += " "
+            print(line)
+        print()
+    
+    @staticmethod
+    def show_stats(stats: SearchStats, algo_name: str):
+        print(f"=== {algo_name} Results ===")
+        print(stats)
+        print()
+
+
+def generate_test_maze(width: int, height: int, complexity: float = 0.3) -> Maze:
+    maze = Maze(width, height)
+    
+    for x in range(width):
+        for y in range(height):
+            if random.random() < complexity:
+                maze.cells[x][y].is_wall = True
+    
+    maze.start = maze.get_cell(0, 0)
+    if maze.start:
+        maze.start.is_start = True
+        maze.start.is_wall = False
+    
+    maze.exit = maze.get_cell(width - 1, height - 1)
+    if maze.exit:
+        maze.exit.is_exit = True
+        maze.exit.is_wall = False
+    
+    return maze
+
+
+def generate_empty_maze(width: int, height: int) -> Maze:
+    maze = Maze(width, height)
+    
+    for x in range(width):
+        for y in range(height):
+            maze.cells[x][y].is_wall = False
+    
+    maze.start = maze.get_cell(0, 0)
+    if maze.start:
+        maze.start.is_start = True
+    
+    maze.exit = maze.get_cell(width - 1, height - 1)
+    if maze.exit:
+        maze.exit.is_exit = True
+    
+    return maze
+
+
+def generate_no_exit_maze(width: int, height: int) -> Maze:
+    maze = Maze(width, height)
+    
+    for x in range(width):
+        for y in range(height):
+            maze.cells[x][y].is_wall = False
+    
+    for x in range(width):
+        maze.cells[x][height // 2].is_wall = True
+    
+    maze.start = maze.get_cell(0, 0)
+    if maze.start:
+        maze.start.is_start = True
+    
+    maze.exit = maze.get_cell(width - 1, height - 1)
+    if maze.exit:
+        maze.exit.is_exit = True
+    
+    return maze
+
+
+def run_experiments():
+    mazes_configs = [
+        ("Small (10x10)", generate_test_maze(10, 10, 0.2)),
+        ("Medium (50x50)", generate_test_maze(50, 50, 0.25)),
+        ("Large (100x100)", generate_test_maze(100, 100, 0.3)),
+        ("Empty (30x30)", generate_empty_maze(30, 30)),
+        ("No Exit (20x20)", generate_no_exit_maze(20, 20))
+    ]
+    
+    strategies = [BFSStrategy(), DFSStrategy(), AStarStrategy(), DijkstraStrategy()]
+    
+    results = []
+    
+    for maze_name, maze in mazes_configs:
+        print(f"\n=== Testing: {maze_name} ===")
+        
+        for strategy in strategies:
+            times = []
+            visited = []
+            path_lengths = []
+            
+            solver = MazeSolver(maze, strategy)
+            
+            for run in range(5):
+                maze_copy = Maze(maze.width, maze.height)
+                for x in range(maze.width):
+                    for y in range(maze.height):
+                        orig = maze.get_cell(x, y)
+                        copy = maze_copy.get_cell(x, y)
+                        if orig:
+                            copy.is_wall = orig.is_wall
+                            copy.is_start = orig.is_start
+                            copy.is_exit = orig.is_exit
+                maze_copy.start = maze_copy.get_cell(maze.start.x, maze.start.y) if maze.start else None
+                maze_copy.exit = maze_copy.get_cell(maze.exit.x, maze.exit.y) if maze.exit else None
+                
+                solver.maze = maze_copy
+                solver.set_strategy(strategy)
+                path, stats = solver.solve()
+                
+                times.append(stats.time_ms)
+                visited.append(stats.visited_cells)
+                path_lengths.append(stats.path_length)
+            
+            avg_time = sum(times) / len(times)
+            avg_visited = sum(visited) / len(visited)
+            avg_path = sum(path_lengths) / len(path_lengths)
+            
+            results.append({
+                'maze': maze_name,
+                'algorithm': strategy.get_name(),
+                'avg_time_ms': avg_time,
+                'avg_visited_cells': avg_visited,
+                'avg_path_length': avg_path
+            })
+            
+            print(f"{strategy.get_name()}: {avg_time:.2f}ms, {avg_visited:.0f} cells, path={avg_path:.0f}")
+    
+    with open('experiment_results.csv', 'w', newline='', encoding='utf-8') as f:
+        writer = csv.DictWriter(f, fieldnames=['maze', 'algorithm', 'avg_time_ms', 'avg_visited_cells', 'avg_path_length'])
+        writer.writeheader()
+        writer.writerows(results)
+    
+    print("\nResults saved to experiment_results.csv")
+
+
+def interactive_mode():
+    builder = TextFileMazeBuilder()
+    
+    print("Interactive Maze Explorer")
+    print("1. Load maze from file")
+    print("2. Generate random maze")
+    choice = input("Choose (1/2): ")
+    
+    if choice == '1':
+        filename = input("Enter filename: ")
+        try:
+            maze = builder.build_from_file(filename)
+        except Exception as e:
+            print(f"Error loading maze: {e}")
+            return
+    else:
+        w = int(input("Width: "))
+        h = int(input("Height: "))
+        maze = generate_test_maze(w, h, 0.3)
+    
+    player = Player(maze.start)
+    
+    strategies = {
+        '1': BFSStrategy(),
+        '2': DFSStrategy(),
+        '3': AStarStrategy(),
+        '4': DijkstraStrategy()
+    }
+    
+    print("\nSelect algorithm for solving:")
+    print("1. BFS (shortest path)")
+    print("2. DFS (fast, not optimal)")
+    print("3. A* (heuristic)")
+    print("4. Dijkstra")
+    algo_choice = input("Choose: ")
+    
+    solver = MazeSolver(maze, strategies.get(algo_choice, BFSStrategy()))
+    path, stats = solver.solve()
+    
+    view = ConsoleView()
+    
+    if path:
+        print(f"\nPath found! Length: {len(path)}")
+        view.show_stats(stats, solver.strategy.get_name())
+    else:
+        print("\nNo path found!")
+    
+    while True:
+        view.render(maze, player, path if path else None)
+        
+        if player.current_cell == maze.exit:
+            print("Congratulations! You reached the exit!")
+            break
+        
+        cmd = input("Move (W/A/S/D) | U=undo | Q=quit | S=solve: ").upper()
+        
+        if cmd == 'Q':
+            break
+        elif cmd == 'U':
+            player.undo()
+            print("Undo last move")
+        elif cmd == 'S' and path:
+            for cell in path:
+                if cell == player.current_cell:
+                    continue
+                player.move_to(cell)
+                view.render(maze, player, path)
+                input("Press Enter to continue...")
+                if player.current_cell == maze.exit:
+                    print("You reached the exit!")
+                    break
+        elif cmd in ['W', 'A', 'S', 'D']:
+            move_cmd = MoveCommand(player, maze, cmd)
+            if move_cmd.execute():
+                print("Moved")
+            else:
+                print("Can't move there!")
+
+
+def main():
+    print("Maze Solver with Design Patterns")
+    print("1. Run experiments")
+    print("2. Interactive mode")
+    choice = input("Choose (1/2): ")
+    
+    if choice == '1':
+        run_experiments()
+    else:
+        interactive_mode()
+
+
+if __name__ == "__main__":
+    main()

agafonovdm/docs/data/2zad/RESULT22.py

@@ -0,0 +1,363 @@
+import pandas as pd
+import matplotlib.pyplot as plt
+import numpy as np
+
+# Настройка русских шрифтов
+plt.rcParams['font.family'] = 'DejaVu Sans'
+plt.rcParams['axes.unicode_minus'] = False
+
+def load_and_prepare_data(filename='experiment_results.csv'):
+    """Загрузка данных из CSV и подготовка."""
+    df = pd.read_csv(filename, delimiter=',')  # Используем запятую как разделитель
+    
+    # Переименовываем столбцы для удобства
+    df.columns = ['maze_type', 'algorithm', 'avg_time_ms', 'avg_visited_cells', 'avg_path_length']
+    
+    # Преобразование типов
+    numeric_cols = ['avg_time_ms', 'avg_visited_cells', 'avg_path_length']
+    for col in numeric_cols:
+        df[col] = pd.to_numeric(df[col], errors='coerce')
+    
+    # Добавляем столбец с размером лабиринта для анализа
+    def extract_maze_size(maze_name):
+        if 'Small' in maze_name:
+            return 'Small (10x10)'
+        elif 'Medium' in maze_name:
+            return 'Medium (50x50)'
+        elif 'Large' in maze_name:
+            return 'Large (100x100)'
+        elif 'Empty' in maze_name:
+            return 'Empty (30x30)'
+        elif 'No Exit' in maze_name:
+            return 'No Exit (20x20)'
+        return maze_name
+    
+    df['maze_category'] = df['maze_type'].apply(extract_maze_size)
+    
+    return df
+
+def plot_time_comparison(df):
+    """График 1: Сравнение времени выполнения по лабиринтам."""
+    fig, ax = plt.subplots(figsize=(12, 6))
+    
+    maze_types = df['maze_category'].unique()
+    algorithms = df['algorithm'].unique()
+    
+    x = np.arange(len(maze_types))
+    width = 0.2
+    
+    colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728']
+    
+    for i, algorithm in enumerate(algorithms):
+        algo_data = df[df['algorithm'] == algorithm]
+        times = []
+        for maze in maze_types:
+            row = algo_data[algo_data['maze_category'] == maze]
+            if not row.empty:
+                times.append(row['avg_time_ms'].values[0])
+            else:
+                times.append(0)
+        
+        bars = ax.bar(x + i*width, times, width, label=algorithm, 
+                      color=colors[i])
+    
+    ax.set_xlabel('Тип лабиринта', fontsize=12)
+    ax.set_ylabel('Время выполнения (мс)', fontsize=12)
+    ax.set_title('Сравнение времени выполнения алгоритмов поиска пути', fontsize=14)
+    ax.set_xticks(x + width * 1.5)
+    ax.set_xticklabels(maze_types, rotation=45, ha='right')
+    ax.legend()
+    ax.grid(True, alpha=0.3, axis='y')
+    
+    # Добавление значений на столбцы
+    for i, algorithm in enumerate(algorithms):
+        algo_data = df[df['algorithm'] == algorithm]
+        for j, maze in enumerate(maze_types):
+            row = algo_data[algo_data['maze_category'] == maze]
+            if not row.empty and row['avg_time_ms'].values[0] > 0:
+                time_val = row['avg_time_ms'].values[0]
+                ax.text(x[j] + i*width, time_val + 0.02, 
+                       f'{time_val:.3f}', ha='center', va='bottom', fontsize=8)
+    
+    plt.tight_layout()
+    plt.savefig('time_comparison.png', dpi=150)
+    plt.show()
+
+def plot_visited_cells(df):
+    """График 2: Количество посещённых клеток."""
+    fig, ax = plt.subplots(figsize=(12, 6))
+    
+    maze_types = df['maze_category'].unique()
+    algorithms = df['algorithm'].unique()
+    
+    x = np.arange(len(maze_types))
+    width = 0.2
+    
+    colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728']
+    
+    for i, algorithm in enumerate(algorithms):
+        algo_data = df[df['algorithm'] == algorithm]
+        visited = []
+        for maze in maze_types:
+            row = algo_data[algo_data['maze_category'] == maze]
+            if not row.empty:
+                visited.append(row['avg_visited_cells'].values[0])
+            else:
+                visited.append(0)
+        
+        ax.bar(x + i*width, visited, width, label=algorithm, color=colors[i])
+    
+    ax.set_xlabel('Тип лабиринта', fontsize=12)
+    ax.set_ylabel('Количество посещённых клеток', fontsize=12)
+    ax.set_title('Сравнение количества посещённых клеток', fontsize=14)
+    ax.set_xticks(x + width * 1.5)
+    ax.set_xticklabels(maze_types, rotation=45, ha='right')
+    ax.legend()
+    ax.grid(True, alpha=0.3, axis='y')
+    
+    plt.tight_layout()
+    plt.savefig('visited_cells.png', dpi=150)
+    plt.show()
+
+def plot_path_length(df):
+    """График 3: Длина найденного пути."""
+    fig, ax = plt.subplots(figsize=(12, 6))
+    
+    # Исключаем лабиринты без выхода (где путь = 0)
+    df_filtered = df[df['avg_path_length'] > 0]
+    
+    maze_types = df_filtered['maze_category'].unique()
+    algorithms = df_filtered['algorithm'].unique()
+    
+    x = np.arange(len(maze_types))
+    width = 0.2
+    
+    colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728']
+    
+    for i, algorithm in enumerate(algorithms):
+        algo_data = df_filtered[df_filtered['algorithm'] == algorithm]
+        path_lengths = []
+        for maze in maze_types:
+            row = algo_data[algo_data['maze_category'] == maze]
+            if not row.empty:
+                path_lengths.append(row['avg_path_length'].values[0])
+            else:
+                path_lengths.append(0)
+        
+        ax.bar(x + i*width, path_lengths, width, label=algorithm, color=colors[i])
+    
+    ax.set_xlabel('Тип лабиринта', fontsize=12)
+    ax.set_ylabel('Длина пути (количество клеток)', fontsize=12)
+    ax.set_title('Сравнение длины найденного пути', fontsize=14)
+    ax.set_xticks(x + width * 1.5)
+    ax.set_xticklabels(maze_types, rotation=45, ha='right')
+    ax.legend()
+    ax.grid(True, alpha=0.3, axis='y')
+    
+    plt.tight_layout()
+    plt.savefig('path_length.png', dpi=150)
+    plt.show()
+
+def plot_time_per_maze(df):
+    """График 4: Для каждого лабиринта - сравнение алгоритмов по времени."""
+    maze_types = df['maze_category'].unique()
+    algorithms = df['algorithm'].unique()
+    
+    for maze in maze_types:
+        fig, ax = plt.subplots(figsize=(10, 6))
+        
+        maze_data = df[df['maze_category'] == maze]
+        
+        times = []
+        algo_names = []
+        for algo in algorithms:
+            row = maze_data[maze_data['algorithm'] == algo]
+            if not row.empty:
+                times.append(row['avg_time_ms'].values[0])
+                algo_names.append(algo)
+        
+        bars = ax.bar(algo_names, times, 
+                      color=['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728'][:len(algo_names)])
+        
+        ax.set_xlabel('Алгоритм', fontsize=12)
+        ax.set_ylabel('Время выполнения (мс)', fontsize=12)
+        ax.set_title(f'Сравнение алгоритмов на лабиринте: {maze}', fontsize=14)
+        ax.grid(True, alpha=0.3, axis='y')
+        
+        # Добавление значений на столбцы
+        for bar, time_val in zip(bars, times):
+            height = bar.get_height()
+            ax.text(bar.get_x() + bar.get_width()/2., height + 0.02,
+                    f'{time_val:.3f}', ha='center', va='bottom', fontsize=10)
+        
+        plt.tight_layout()
+        # Очищаем имя файла от скобок
+        safe_maze_name = maze.replace('(', '').replace(')', '').replace(' ', '_')
+        plt.savefig(f'time_{safe_maze_name}.png', dpi=150)
+        plt.show()
+
+def plot_visited_per_maze(df):
+    """График 5: Для каждого лабиринта - посещённые клетки."""
+    maze_types = df['maze_category'].unique()
+    
+    for maze in maze_types:
+        fig, ax = plt.subplots(figsize=(10, 6))
+        
+        maze_data = df[df['maze_category'] == maze]
+        
+        visited = maze_data['avg_visited_cells'].values
+        algo_names = maze_data['algorithm'].values
+        
+        bars = ax.bar(algo_names, visited, 
+                      color=['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728'][:len(algo_names)])
+        
+        ax.set_xlabel('Алгоритм', fontsize=12)
+        ax.set_ylabel('Количество посещённых клеток', fontsize=12)
+        ax.set_title(f'Посещённые клетки на лабиринте: {maze}', fontsize=14)
+        ax.grid(True, alpha=0.3, axis='y')
+        
+        # Добавление значений на столбцы
+        for bar, val in zip(bars, visited):
+            height = bar.get_height()
+            ax.text(bar.get_x() + bar.get_width()/2., height + 10,
+                    f'{int(val)}', ha='center', va='bottom', fontsize=10)
+        
+        plt.tight_layout()
+        safe_maze_name = maze.replace('(', '').replace(')', '').replace(' ', '_')
+        plt.savefig(f'visited_{safe_maze_name}.png', dpi=150)
+        plt.show()
+
+def plot_efficiency_ratio(df):
+    """График 6: Эффективность (время на клетку пути)."""
+    fig, ax = plt.subplots(figsize=(12, 6))
+    
+    # Исключаем лабиринты без пути
+    df_filtered = df[(df['avg_path_length'] > 0) & (df['avg_time_ms'] > 0)].copy()
+    df_filtered['efficiency'] = df_filtered['avg_time_ms'] / df_filtered['avg_path_length']
+    
+    maze_types = df_filtered['maze_category'].unique()
+    algorithms = df_filtered['algorithm'].unique()
+    
+    x = np.arange(len(maze_types))
+    width = 0.2
+    
+    colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728']
+    
+    for i, algorithm in enumerate(algorithms):
+        algo_data = df_filtered[df_filtered['algorithm'] == algorithm]
+        efficiency = []
+        for maze in maze_types:
+            row = algo_data[algo_data['maze_category'] == maze]
+            if not row.empty:
+                efficiency.append(row['efficiency'].values[0])
+            else:
+                efficiency.append(0)
+        
+        ax.bar(x + i*width, efficiency, width, label=algorithm, color=colors[i])
+    
+    ax.set_xlabel('Тип лабиринта', fontsize=12)
+    ax.set_ylabel('Время на клетку пути (мс/клетку)', fontsize=12)
+    ax.set_title('Эффективность алгоритмов (время на единицу длины пути)', fontsize=14)
+    ax.set_xticks(x + width * 1.5)
+    ax.set_xticklabels(maze_types, rotation=45, ha='right')
+    ax.legend()
+    ax.grid(True, alpha=0.3, axis='y')
+    
+    plt.tight_layout()
+    plt.savefig('efficiency_ratio.png', dpi=150)
+    plt.show()
+
+def plot_path_vs_visited(df):
+    """График 7: Соотношение длины пути и посещённых клеток."""
+    fig, ax = plt.subplots(figsize=(10, 6))
+    
+    algorithms = df['algorithm'].unique()
+    markers = ['o', 's', '^', 'D']
+    colors = ['#1f77b4', '#ff7f0e', '#2ca02c', '#d62728']
+    
+    for algo, marker, color in zip(algorithms, markers, colors):
+        algo_data = df[df['algorithm'] == algo]
+        # Только лабиринты с путём
+        algo_data = algo_data[algo_data['avg_path_length'] > 0]
+        
+        if not algo_data.empty:
+            plt.scatter(algo_data['avg_visited_cells'], 
+                       algo_data['avg_path_length'],
+                       marker=marker, s=100, label=algo, color=color, alpha=0.7)
+            
+            # Добавляем подписи для каждой точки
+            for _, row in algo_data.iterrows():
+                plt.annotate(row['maze_category'].split()[0], 
+                           (row['avg_visited_cells'], row['avg_path_length']),
+                           xytext=(5, 5), textcoords='offset points', fontsize=8)
+    
+    plt.xlabel('Количество посещённых клеток', fontsize=12)
+    plt.ylabel('Длина пути (клеток)', fontsize=12)
+    plt.title('Соотношение: посещённые клетки vs длина пути', fontsize=14)
+    plt.legend()
+    plt.grid(True, alpha=0.3)
+    
+    plt.tight_layout()
+    plt.savefig('path_vs_visited.png', dpi=150)
+    plt.show()
+
+def main():
+    """Основная функция: загрузка данных и построение всех графиков."""
+    try:
+        df = load_and_prepare_data('experiment_results.csv')
+        print("Данные успешно загружены")
+        print(f"Найдено {len(df)} записей")
+        print("\nСтруктура данных:")
+        print(df.head())
+        print("\nУникальные типы лабиринтов:")
+        print(df['maze_category'].unique())
+        print("\nУникальные алгоритмы:")
+        print(df['algorithm'].unique())
+        
+        print("\nПостроение графиков...")
+        
+        # Базовые графики
+        plot_time_comparison(df)
+        plot_visited_cells(df)
+        plot_path_length(df)
+        
+        # Детальные графики по каждому лабиринту
+        plot_time_per_maze(df)
+        plot_visited_per_maze(df)
+        
+        # Аналитические графики
+        plot_efficiency_ratio(df)
+        plot_path_vs_visited(df)
+        
+        print("\nВсе графики сохранены в текущей директории:")
+        print("  - time_comparison.png")
+        print("  - visited_cells.png")
+        print("  - path_length.png")
+        print("  - time_{maze}.png (для каждого лабиринта)")
+        print("  - visited_{maze}.png (для каждого лабиринта)")
+        print("  - efficiency_ratio.png")
+        print("  - path_vs_visited.png")
+        
+        # Вывод статистики
+        print("\n=== Краткая статистика ===")
+        for maze in df['maze_category'].unique():
+            print(f"\n{maze}:")
+            maze_data = df[df['maze_category'] == maze]
+            for algo in df['algorithm'].unique():
+                algo_data = maze_data[maze_data['algorithm'] == algo]
+                if not algo_data.empty:
+                    time_val = algo_data['avg_time_ms'].values[0]
+                    visited_val = int(algo_data['avg_visited_cells'].values[0])
+                    path_val = int(algo_data['avg_path_length'].values[0])
+                    print(f"  {algo}: время={time_val:.6f}мс, посещено={visited_val}, путь={path_val}")
+        
+    except FileNotFoundError:
+        print("Ошибка: файл experiment_results.csv не найден")
+        print("Убедитесь, что файл находится в текущей директории")
+    except Exception as e:
+        print(f"Ошибка: {e}")
+        import traceback
+        traceback.print_exc()
+
+if __name__ == "__main__":
+    main()

agafonovdm/docs/data/2zad/experiment_results.csv

@@ -0,0 +1,21 @@
+maze,algorithm,avg_time_ms,avg_visited_cells,avg_path_length
+Small (10x10),BFS,0.08572000006097369,79.0,19.0
+Small (10x10),DFS,0.039739999920129776,79.0,31.0
+Small (10x10),A*,0.13467999997374136,79.0,19.0
+Small (10x10),Dijkstra,0.11474000057205558,79.0,19.0
+Medium (50x50),BFS,1.8074600004183594,1874.0,99.0
+Medium (50x50),DFS,0.5937599995377241,1874.0,429.0
+Medium (50x50),A*,1.6300600003887666,1874.0,99.0
+Medium (50x50),Dijkstra,3.1870400001935195,1874.0,99.0
+Large (100x100),BFS,0.014439999722526409,7033.0,0.0
+Large (100x100),DFS,0.014839999857940711,7033.0,0.0
+Large (100x100),A*,0.02542000001994893,7033.0,0.0
+Large (100x100),Dijkstra,0.02548000011302065,7033.0,0.0
+Empty (30x30),BFS,0.784620000194991,900.0,59.0
+Empty (30x30),DFS,0.5252399994787993,900.0,465.0
+Empty (30x30),A*,1.150900000357069,900.0,59.0
+Empty (30x30),Dijkstra,1.564640000287909,900.0,59.0
+No Exit (20x20),BFS,0.2002399993216386,380.0,0.0
+No Exit (20x20),DFS,0.2512400002160575,380.0,0.0
+No Exit (20x20),A*,0.5590400000073714,380.0,0.0
+No Exit (20x20),Dijkstra,0.35640000060084276,380.0,0.0