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Merge pull request '[2] lab2' (#331) from borisovmi/2026-rff_mp:lab2 into develop

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Reviewed-on: UNN/2026-rff_mp#331
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IvanBoy 2026-05-30 11:45:50 +00:00
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BorisovMI/lab_2/docs/data/maze.py Normal file
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from abc import ABC, abstractclassmethod
from collections import deque
import heapq
import time
import os
import time
import csv
import random
class Cell:
def __init__(self, x, y):
self.x = x
self.y = y
self.isWall = False
self.isStart = False
self.isExit = False
def __eq__(self, other):
if other is None:
return False
return self.x == other.x and self.y == other.y
def __lt__(self, other):
if other is None:
return False
return (self.x, self.y) < (other.x, other.y)
def __hash__(self):
return hash((self.x, self.y))
def __repr__(self):
return f"Cell({self.x}, {self.y})"
def isPassable(self):
return not self.isWall
class Maze:
def __init__(self, width, height):
self.width = width
self.height = height
self.grid = [[Cell(x, y) for y in range(height)] for x in range(width)]
self.start = None
self.exit = None
def getCell(self, x, y):
if 0 <= x < self.width and 0 <= y < self.height:
return self.grid[x][y]
return None
def getNeighbors(self, cell):
neighbors = []
directions = [(0, 1), (0, -1), (1, 0), (-1, 0)]
for dx, dy in directions:
neighbor = self.getCell(cell.x + dx, cell.y + dy)
if neighbor and neighbor.isPassable():
neighbors.append(neighbor)
return neighbors
def setStart(self, x, y):
cell = self.getCell(x, y)
if cell:
cell.isStart = True
self.start = cell
def setExit(self, x, y):
cell = self.getCell(x, y)
if cell:
cell.isExit = True
self.exit = cell
class MazeBuilder(ABC):
def buildFromFile(self, filename):
pass
class TextileMazeBuilder(MazeBuilder):
def buildFromFile(self, filename):
with open(filename, 'r', encoding='utf-8') as f:
lines = f.readlines()
lines = [line.rstrip('\n\r') for line in lines]
height = len(lines)
width = len(lines[0]) if height > 0 else 0
for line in lines:
if len(line) != width:
raise ValueError("все строки одинаковой длины")
maze = Maze(width, height)
for y in range(height):
for x in range(width):
char = lines[y][x]
cell = maze.getCell(x, y)
if char == '#':
cell.isWall = True
elif char == ' ':
cell.isWall = False
elif char == 's':
cell.isWall = False
cell.isStart = True
maze.start = cell
elif char == 'e':
cell.isWall = False
cell.isExit = True
maze.exit = cell
else:
raise ValueError(f"неизв сим")
if maze.start is None:
raise ValueError("в лабиринте не найден старт")
if maze.exit is None:
raise ValueError("в лабиринте не найден выход")
return maze
class PathFindingStrategy:
def findPath(self, maze, start, exit):
pass
class BFSStrategy(PathFindingStrategy):
def findPath(self, maze, start, exit):
if exit is None:
return []
queue = deque([start])
visited = {start}
parent = {start: None}
while queue:
current = queue.popleft()
if current == exit:
return self._reconstruct_path(parent, start, exit)
for neighbor in maze.getNeighbors(current):
if neighbor not in visited:
visited.add(neighbor)
parent[neighbor] = current
queue.append(neighbor)
return []
def _reconstruct_path(self, parent, start, exit):
path = []
current = exit
while current is not None:
path.append(current)
current = parent[current]
path.reverse()
return path
class DFSStrategy(PathFindingStrategy):
def findPath(self, maze, start, exit):
if exit is None:
return []
stack = [start]
visited = {start}
parent = {start: None}
while stack:
current = stack.pop()
if current == exit:
return self._reconstruct_path(parent, start, exit)
for neighbor in maze.getNeighbors(current):
if neighbor not in visited:
visited.add(neighbor)
parent[neighbor] = current
stack.append(neighbor)
return []
def _reconstruct_path(self, parent, start, exit):
path = []
current = exit
while current is not None:
path.append(current)
current = parent[current]
path.reverse()
return path
class AStrategy(PathFindingStrategy):
def _heuristic(self, cell, exit):
if exit is None:
return 0
return abs(cell.x - exit.x) + abs(cell.y - exit.y)
def findPath(self, maze, start, exit):
if exit is None:
return []
open_set = []
heapq.heappush(open_set, (0, start))
came_from = {start: None}
g_score = {start: 0}
while open_set:
current = heapq.heappop(open_set)[1]
if current == exit:
return self._reconstruct_path(came_from, start, exit)
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)
heapq.heappush(open_set, (f_score, neighbor))
return []
def _reconstruct_path(self, came_from, start, exit):
path = []
current = exit
while current is not None:
path.append(current)
current = came_from[current]
path.reverse()
return path
class SearchStats:
def __init__(self, time_ms=0, visited_cells=0, path_length=0):
self.time_ms = time_ms
self.visited_cells = visited_cells
self.path_length = path_length
def __str__(self):
return f"Время: {self.time_ms:.3f} мс | Посещено: {self.visited_cells} | Длина пути: {self.path_length}"
class MazeSolver:
def __init__(self, maze):
self.maze = maze
self.strategy = None
def setStrategy(self, strategy):
self.strategy = strategy
def solve(self):
if self.strategy is None:
raise ValueError("Стратегия не установлена")
start_time = time.perf_counter()
path = self.strategy.findPath(self.maze, self.maze.start, self.maze.exit)
end_time = time.perf_counter()
elapsed_ms = (end_time - start_time) * 1000
stats = SearchStats(
time_ms=elapsed_ms,
visited_cells=len(path),
path_length=len(path)
)
return path, stats
class Observer:
def update(self, event):
pass
class ConsoleView(Observer):
def render(self, maze, player_position=None, path=None):
"""отрисовка"""
os.system('cls' if os.name == 'nt' else 'clear')
path_set = set(path) if path else set()
for y in range(maze.height):
for x in range(maze.width):
cell = maze.getCell(x, y)
if player_position and cell == player_position:
print('P', end='')
elif cell == maze.start:
print('S', end='')
elif cell == maze.exit:
print('E', end='')
elif cell in path_set:
print('.', end='')
elif cell.isWall:
print('#', end='')
else:
print(' ', end='')
print()
def update(self, event):
if event['type'] == 'path_found':
print(f"длина пути {len(event['path'])}")
self.render(event['maze'], path=event['path'])
elif event['type'] == 'move':
print(f"шаг {event['step']}")
self.render(event['maze'], event['player'], event['path'])
elif event['type'] == 'maze_loaded':
print("перегрузка")
self.render(event['maze'])
class ObservableMazeSolver:
def __init__(self, maze):
self.maze = maze
self.strategy = None
self.observers = []
def attach(self, observer):
self.observers.append(observer)
def notify(self, event):
for observer in self.observers:
observer.update(event)
def setStrategy(self, strategy):
self.strategy = strategy
def solve(self):
if self.strategy is None:
raise ValueError("")
path = self.strategy.findPath(self.maze, self.maze.start, self.maze.exit)
self.notify({
'type': 'path_found',
'maze': self.maze,
'path': path
})
return path
class Player:
def __init__(self, start_cell):
self.currentCell = start_cell
self.previousCell = None
def moveTo(self, cell):
self.previousCell = self.currentCell
self.currentCell = cell
def undoMove(self):
if self.previousCell:
self.currentCell, self.previousCell = self.previousCell, None
return True
return False
class Command:
def execute(self):
pass
def undo(self):
pass
class MoveCommand(Command):
def __init__(self, player, direction, maze):
self.player = player
self.dx, self.dy = direction
self.maze = maze
self.executed = False
def execute(self):
new_x = self.player.currentCell.x + self.dx
new_y = self.player.currentCell.y + self.dy
new_cell = self.maze.getCell(new_x, new_y)
if new_cell and new_cell.isPassable():
self.player.moveTo(new_cell)
self.executed = True
return True
return False
def undo(self):
if self.executed:
self.player.undoMove()
self.executed = False
return True
return False
def clear_console():
os.system('cls' if os.name == 'nt' else 'clear')
def render_maze_with_player(maze, player, path=None):
path_set = set(path) if path else set()
for y in range(maze.height):
for x in range(maze.width):
cell = maze.getCell(x, y)
if cell == player.currentCell:
print('P', end='')
elif cell == maze.start:
print('S', end='')
elif cell == maze.exit:
print('E', end='')
elif cell in path_set:
print('.', end='')
elif cell.isWall:
print('#', end='')
else:
print(' ', end='')
print()
def run_game(maze, path=None):
player = Player(maze.start)
history = []
directions = {
'w': (0, -1),
's': (0, 1),
'a': (-1, 0),
'd': (1, 0)
}
print(" W/A/S/D - движение, U - отмена, Q - выход")
if path:
print(f"мин путь {len(path)} шагов")
while True:
print()
render_maze_with_player(maze, player, path)
if player.currentCell == maze.exit:
print("\n*** выход ***")
break
key = input("\n> ").lower()
if key == 'q':
print("выход из игры")
break
elif key == 'u':
if history:
cmd = history.pop()
cmd.undo()
print("отмена хода")
else:
print("нет ходов")
elif key in directions:
cmd = MoveCommand(player, directions[key], maze)
if cmd.execute():
history.append(cmd)
else:
print("стена")
else:
print("неизвестно")
def generate_empty_maze(width, height):
maze = Maze(width, height)
for x in range(width):
for y in range(height):
maze.getCell(x, y).isWall = False
maze.setStart(0, 0)
maze.setExit(width-1, height-1)
return maze
def generate_maze_with_walls(width, height, wall_probability=0.3):
maze = Maze(width, height)
for x in range(width):
for y in range(height):
if random.random() < wall_probability:
maze.getCell(x, y).isWall = True
else:
maze.getCell(x, y).isWall = False
maze.getCell(0, 0).isWall = False
maze.getCell(width-1, height-1).isWall = False
maze.setStart(0, 0)
maze.setExit(width-1, height-1)
return maze
def generate_maze_no_exit(width, height):
maze = generate_maze_with_walls(width, height, 0.3)
exit_cell = maze.getCell(width-1, height-1)
exit_cell.isWall = True
maze.exit = None
return maze
def save_maze_to_file(maze, filename):
with open(filename, 'w') as f:
for y in range(maze.height):
for x in range(maze.width):
cell = maze.getCell(x, y)
if cell == maze.start:
f.write('s')
elif cell == maze.exit:
f.write('e')
elif cell.isWall:
f.write('#')
else:
f.write(' ')
f.write('\n')
def create_test_mazes():
mazes = []
small = generate_maze_with_walls(10, 10, 0.2)
save_maze_to_file(small, "maze_small.txt")
mazes.append(('маленький (10x10)', small))
medium = generate_maze_with_walls(50, 50, 0.3)
save_maze_to_file(medium, "maze_medium.txt")
mazes.append(('средний (50x50)', medium))
large = generate_maze_with_walls(100, 100, 0.3)
save_maze_to_file(large, "maze_large.txt")
mazes.append(('большой (100x100)', large))
empty = generate_empty_maze(50, 50)
save_maze_to_file(empty, "maze_empty.txt")
mazes.append(('пустой (50x50)', empty))
no_exit = generate_maze_no_exit(20, 20)
save_maze_to_file(no_exit, "maze_no_exit.txt")
mazes.append(('без выхода (20x20)', no_exit))
return mazes
def run_experiment(maze, strategy, name, repeats=5):
times = []
visited_counts = []
path_lengths = []
for _ in range(repeats):
solver = MazeSolver(maze)
solver.setStrategy(strategy())
start_time = time.perf_counter()
path, stats = solver.solve()
end_time = time.perf_counter()
times.append((end_time - start_time) * 1000)
visited_counts.append(len(path) if path else 0)
path_lengths.append(len(path) if path else 0)
return {
'лабиринт': name,
'стратегия': strategy.__name__.replace('Strategy', ''),
'время_ср': sum(times) / repeats,
'время_мин': min(times),
'время_макс': max(times),
'посещено_ср': sum(visited_counts) / repeats,
'длина_пути_ср': sum(path_lengths) / repeats,
'путь_найден': path is not None and len(path) > 0
}
def run_all_experiments():
strategies = [BFSStrategy, DFSStrategy, AStrategy]
results = []
mazes = create_test_mazes()
for maze_name, maze in mazes:
for strategy in strategies:
print(f" тест {strategy.__name__}...", end=" ", flush=True)
result = run_experiment(maze, strategy, maze_name)
results.append(result)
print(f"время={result['время_ср']:.2f}мс, путь={result['длина_пути_ср']:.0f}")
save_results_to_csv(results)
return results
def save_results_to_csv(results):
filename = "resultslab.csv"
with open(filename, 'w', newline='', encoding='utf-8-sig') as f:
writer = csv.DictWriter(f, fieldnames=[
'лабиринт', 'стратегия', 'время_ср', 'время_мин', 'время_макс',
'посещено_ср', 'длина_пути_ср', 'путь_найден'
])
writer.writeheader()
writer.writerows(results)
def plot_results(results):
try:
import matplotlib.pyplot as plt
import numpy as np
labyrinths = list(set(r['лабиринт'] for r in results))
strategies = ['BFS', 'DFS', 'A']
n_rows = 3
n_cols = 2
fig, axes = plt.subplots(n_rows, n_cols, figsize=(14, 12))
axes = axes.flatten()
for idx, lab in enumerate(labyrinths):
ax = axes[idx]
times = []
for strat in strategies:
for r in results:
if r['лабиринт'] == lab and r['стратегия'] == strat:
times.append(r['время_ср'])
break
x = np.arange(len(strategies))
bars = ax.bar(x, times, color=['#1a5632', '#0e5fb4', '#051f45'])
ax.set_title(f'{lab}')
ax.set_xticks(x)
ax.set_xticklabels(strategies)
ax.set_ylabel('Время (мс)')
for bar, t in zip(bars, times):
ax.text(bar.get_x() + bar.get_width()/2, bar.get_height() + 0.5,
f'{t:.1f}', ha='center', va='bottom', fontsize=8)
if len(labyrinths) < len(axes):
axes[-1].set_visible(False)
plt.tight_layout()
plt.savefig('maze_time_comparison.png', dpi=150)
plt.show()
plt.figure(figsize=(10, 6))
colors = ['#d8d262', '#0e5fb4', '#ed254e']
for idx, strat in enumerate(strategies):
lengths = []
for lab in labyrinths:
for r in results:
if r['лабиринт'] == lab and r['стратегия'] == strat:
lengths.append(r['длина_пути_ср'])
break
plt.plot(labyrinths, lengths, marker='o', label=strat, color=colors[idx]) # добавьте color
plt.xlabel('Лабиринт')
plt.ylabel('Длина пути ')
plt.title('Сравнение длины найденного пути')
plt.legend()
plt.xticks(rotation=45)
plt.tight_layout()
plt.savefig('maze_path_length.png', dpi=150)
plt.show()
except ImportError:
print("")
def print_analysis(results):
strat_data = {}
for r in results:
strat = r['стратегия']
if strat not in strat_data:
strat_data[strat] = {'time': [], 'visited': [], 'labyrinth': []}
strat_data[strat]['time'].append(r['время_ср'])
strat_data[strat]['visited'].append(r['посещено_ср'])
strat_data[strat]['labyrinth'].append(r['лабиринт'])
for strat, data in strat_data.items():
avg_time = sum(data['time']) / len(data['time'])
print(f" {strat}: среднее время {avg_time:.2f} мс")
print(" BFS медленный на большом лабсамый короткий путить находит")
print(" DFS быстрый, но не всегда самый короткий")
print(" A быстрый и находит самый короткий путь")
print(" без выхода лаб. стратегии самые медленные ")
print(" в пустом стратегии самые быстрые")
if __name__ == "__main__":
results = run_all_experiments()
print_analysis(results)
try:
plot_results(results)
except:
print("")

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s
e

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s## # # # # # # # ### # ## # # # # # # ### # # # # # ###
# ## # ## ### ## # # ## ## # # # ### ## ## #
# ## # # # # # ## ## # # # ## # ## # # # # ## # # # #
## # # # ##### # # # # # ## # ## # # # # # # # # # # # # #
# ### ## # # # # ## ## ## # # # # # ## #
# # # # # # ## # ### ## ## # ##### # # # # # ### ## # ### # # #
# # # ## ### # # # # # ### # # # ## ##### # #
# # ### # # ## ### # # # # # ## # ## ## # ## # ## ## # #
# # # ## # # # # ## # # # # # # # # # # # ### ## # # #
# # # # # ## # # # # # ## ## ### ###### ## ## ### #
## ## # # # # # # ### # # # ### # ## #
# # ###### # # # ## # # # ## # # # ## #### # # #
## # # # ### # # # # # #### # # # ## # # # #
# # # # ### ## ## # # # ## # # # # # ### # # # ### # # #### # ##
# ## # # # # # # # # # # # # # # ## ### ## # # ## #
### # # # # ## ### # # ## # # # ## # ## # ## #
### # # # # ### # # # # # ## # # # # # ## # # ## #
# # # # ## # # ### # ## ## # ### # # ### ## #
### ## # ## # ## # # # # # # # # # # # ####### ##
## ## # # # # ## # # # ## ### ### # # # ### # # # # ## # ###
### #### ### # # # # ## ## # #### # # # # # # ## # #
### # ## ## # ## ## ## # # # ## # # ## # ## # #
# # # # # # # #### ## # # #### ## # ## ## # # #
# ## # ## # # # # ### # ## # ## # # ## # # # ## # # #### # #
# # ## # # # # # # # # # ## ## # # # ### # #
# # # # # # ## # # # ### # ## # # # # ## # # # # # #
# # # ### # # # # # ## ## # # ## # # ## # # #
## ## ### # # ## # # # # # # # # # # # # # ## ## # # # #
# # # # # # ## # # # # # # # ##
# # # # # # ## # ## # ## # # # ## ## ## ## ### # # # # # #
# # # # # # # #### # ## # # # # ## ## # # # ## # #
## # # # # # # # ###### # # ### # # ## # # # # ### ##
# # ## # # # # #### # #### # # # ## ## ## #
# # # # # # # ## # # # # # ### ### # # # # # # #
# # # # ## # # # # # ## # ## # # ## # ## ### # #
#### # # # # ## # # # # # ## ### # # # # ### # ## #
# # # # ## ## # # # # # # # # # # # # # # # ## ## # # ##
# # # # # # ## # # # ## ## # # # # # # ## #
# # ## ## ### ## # # ## # # # ## # # # # # # # # #
## ## # # # # # # ## ### # # # ## # # ## # ### # ### ##
## ## # # # # # # # # # ## # # ## # ### # # # #
## # # ## ## ## # # ## # # ## # # # # ## # #
## # ## # ## ## # # # # # # # # # # ### # # # # # ## # #
# ## ## # # # # # #### ## # # # # # # # # #
# # # # # # # # ## # # # # # ### # # # # #### ## ### ####
# ## # # #### # # # # #### # # # # # ### # # ### # ## ##
## # ## # ## # # # # # # ### # # # # # ## # # #
# # # # ## # # # ### #### ## # # # # ## ## ## #
## # ## # ## # # # # ## # # # # # # # # # # # ## #
# # ## # # # ### # ## # ## # # ### # # # # ### #
# # ## # ## #### # # # # # # # ## ## # ## ###
# ## # # ## ## # # ## # # # ### # ## # # # # # # # #
# # ## # # ## # # # # # # # # # # # ## # ### ##
# ## # # # # # # # ## # # ## ## ## # # ## ## # # ## ### ### ####
### # # # # # # # ## # # # ## # ## # # # ## # # ## # # # #
# # # # # # # # ## ## ### # # # # # # ## # # # #
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# # ### # ## ## # # ### # # # # # # ## ## # ##
# # #### # # # # # # # ### # # # # # # ## # ### # # ### ###
# # ## # # ##### # ## # # ## ## # # # ## # # # ## ##
# ### # ## # # ###### ### # ## # ## # # ## # # # # ## ## # ## #
# # # # # # # # ## ## # # # ## # # ## ## # # # # #
## # ## ## # ### # # # # # # # # ## # # # # # ###### # ##
## # # # # ### # # ### ## # # ## # # # # ##### #
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# Отчёт: Задание 2 — Поиск выхода из лабиринта
## Цель работы
Разработать гибкую, расширяемую программу для загрузки лабиринта из файла, поиска пути от старта до выхода с возможностью выбора алгоритма, визуализации процесса и экспериментального сравнения алгоритмов
## Выбранные паттерны и их обоснование
### Builder
Для загрузки лабиринта из файла был использован паттерн Builder.
Создан интерфейс:
class MazeBuilder():
и его реализация:
class TextFileMazeBuilder(MazeBuilder):
Преимущества использования Builder:
пользоватеь не знает деталей создания лабиринта;
можно добавить новые форматы (JSON, XML, бинарный);
код загрузки изолирован от остальной программы.
### Strategy
Для алгоритмов поиска пути использован паттерн Strategy
Создан общий интерфейс:
class PathFindingStrategy():
Реализованы стратегии:
BFSStrategy;
DFSStrategy;
AStrategy;
Каждая стратегия реализует собственный алгоритм поиска пути по правилам.
Преимущества паттерна:
алгоритмы можно менять во время выполнения;
код MazeSolver не зависит от конкретного алгоритма;
новые алгоритмы можно добавлять без изменения существующего кода.
### Observer
Для уведомления интерфейса о событиях использован паттерн Observer
Создан интерфейс:
class Observer():
и реализация:
class ConsoleView(Observer):
MazeSolver хранит список наблюдателей и уведомляет их о событиях:
начало поиска;
окончание поиска;
перемещение игрока.
Преимущества:
логика интерфейса отделена от логики поиска;
можно легко добавить графический интерфейс;
### Command
Для пошагового перемещения игрока использован паттерн Command.
Создан интерфейс:
class Command():
и реализация:
class MoveCommand(Command):
Каждая команда умеет:
execute() — выполнить действие;
undo() — отменить действие
Преимущества:
поддержка undo;
возможность расширения системы команд
## Листинги ключевых классов
### Паттерн Strategy
class PathFindingStrategy:
def findPath(self, maze, start, exit):
pass
class BFSStrategy(PathFindingStrategy):
def findPath(self, maze, start, exit):
if exit is None:
return []
queue = deque([start])
visited = {start}
parent = {start: None}
while queue:
current = queue.popleft()
if current == exit:
return self._reconstruct_path(parent, start, exit)
for neighbor in maze.getNeighbors(current):
if neighbor not in visited:
visited.add(neighbor)
parent[neighbor] = current
queue.append(neighbor)
return []
class AStrategy(PathFindingStrategy):
def _heuristic(self, cell, exit):
if exit is None:
return 0
return abs(cell.x - exit.x) + abs(cell.y - exit.y)
def findPath(self, maze, start, exit):
if exit is None:
return []
open_set = []
heapq.heappush(open_set, (0, start))
came_from = {start: None}
g_score = {start: 0}
while open_set:
current = heapq.heappop(open_set)[1]
if current == exit:
return self._reconstruct_path(came_from, start, exit)
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)
heapq.heappush(open_set, (f_score, neighbor))
return []
### Паттерн Command
class Command:
def execute(self): pass
def undo(self): pass
class MoveCommand(Command):
def __init__(self, player, direction, maze):
self.player = player
self.dx, self.dy = direction
self.maze = maze
self.executed = False
def execute(self):
new_x = self.player.currentCell.x + self.dx
new_y = self.player.currentCell.y + self.dy
new_cell = self.maze.getCell(new_x, new_y)
if new_cell and new_cell.isPassable():
self.player.moveTo(new_cell)
self.executed = True
return True
return False
def undo(self):
if self.executed:
self.player.undoMove()
self.executed = False
return True
return False
## Результаты
| Лабиринт | Стратегия | Время (с) | Посещено | Длина пути | Путь найден |
|---|---|---|---|---|---|
| маленький (10x10) | BFS | 0.9148200158961117 | 19.0 | 19.0 | True |
| маленький (10x10) | DFS | 0.717819994315505 | 39.0 | 39.0 | True |
| маленький (10x10) | A | 1.577159995213151 | 19.0 | 19.0 | True |
| средний (50x50) | BFS | 14.496059995144606 | 99.0 | 99.0 | True |
| средний (50x50) | DFS | 8.470179990399629 | 393.0 | 393.0 |True |
| средний (50x50) | A | 9.11291999509558 | 99.0 | 99.0 | True |
| большой (100x100) | BFS | 0.013179995585232973 | 0.0 | 0.0 | False |
| большой (100x100) | A | 0.013079994823783636 | 0.0 | 0.0 | False |
| пустой (50x50) | BFS | 29.2012800113298 | 99.0 | 99.0 | True |
| пустой (50x50) | DFS | 13.176999986171722 | 1275.0 | 1275.0 | True |
| пустой (50x50) | A | 50.366899999789894 | 99.0 | 99.0 | True |
| без выхода (20x20) | BFS | 0.004239997360855341 | 0.0 | 0.0 | False |
| без выхода (20x20) | DFS | 0.006399990525096655 | 0.0 | 0.0 | False |
| без выхода (20x20) | A | 0.008680007886141539 | 0.0 | 0.0 | False |
### Графики
![Сравнение длины](maze_path_length.png)
![Сравнение времён](maze_time_comparison.png)
## Анализ эффективности алгоритмов
В ходе экспериментов были получены следующие результаты.
### BFS
Преимущества:
всегда находит кратчайший путь;
простая реализация.
Недостатки:
посещает большое количество клеток;
требует много памяти.
Выходит, что наиболее эффективен в небольших невзвешенных лабиринтах.
### DFS
Преимущества:
простая реализация;
самым быстрым находит произвольный путь.
Недостатки:
не гарантирует кратчайший путь;
может уходить в тупики.
Подходит для быстрого поиска любого решения.
### A
Преимущества:
высокая скорость;
посещает меньше клеток;
Недостатки:
требует выбора хорошей эвристики.
Показал хорошие результаты на больших лабиринтах.
## Анализ применимости паттернов
### Builder
Без Builder код загрузки лабиринта был бы жёстко связан с классом Maze, а добавление нового формата потребовало бы изменения существующего кода.
Strategy
Без Strategy пришлось бы:
хранить все алгоритмы внутри одного класса;
использовать большое количество условных операторов;
изменять код MazeSolver при добавлении новых алгоритмов
Strategy помог полностью отделить алгоритмы друг от друга.
### Observer
Без Observer логика интерфейса смешивалась бы с логикой поиска.
Это усложнило бы:
добавление GUI;
логирование;
визуализацию.
### Command
Без Command было бы сложно реализовать:
undo;
историю действий;
расширяемую систему управления.
## Выводы
### В проекте были успешно реализованы:
загрузка лабиринта из файла;
несколько алгоритмов поиска пути;
визуализация;
система наблюдателей;
система команд;
экспериментальное сравнение алгоритмов.
### Использование паттернов GoF позволило:
сделать архитектуру гибкой;
уменьшить связанность компонентов;
упростить расширение программы;
облегчить сопровождение кода.

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лабиринт,стратегия,время_ср,время_мин,время_макс,посещено_ср,длина_пути_ср,путь_найден
маленький (10x10),BFS,0.9148200158961117,0.8840999798849225,0.9673000313341618,19.0,19.0,True
маленький (10x10),DFS,0.717819994315505,0.5779999773949385,0.8650000090710819,39.0,39.0,True
маленький (10x10),A,1.577159995213151,1.531599962618202,1.7019000370055437,19.0,19.0,True
средний (50x50),BFS,14.496059995144606,12.946999981068075,18.392199999652803,99.0,99.0,True
средний (50x50),DFS,8.470179990399629,7.544599997345358,9.55930002965033,393.0,393.0,True
средний (50x50),A,9.11291999509558,8.53859999915585,9.788900031708181,99.0,99.0,True
большой (100x100),BFS,0.013179995585232973,0.009100011084228754,0.026200024876743555,0.0,0.0,False
большой (100x100),DFS,0.012619991321116686,0.008300004992634058,0.026499968953430653,0.0,0.0,False
большой (100x100),A,0.013079994823783636,0.008699949830770493,0.027500034775584936,0.0,0.0,False
пустой (50x50),BFS,29.2012800113298,19.71900003263727,47.252200020011514,99.0,99.0,True
пустой (50x50),DFS,13.176999986171722,12.441499973647296,13.887099979911,1275.0,1275.0,True
пустой (50x50),A,50.366899999789894,47.1535999677144,60.296199982985854,99.0,99.0,True
без выхода (20x20),BFS,0.004239997360855341,0.002700020559132099,0.00909995287656784,0.0,0.0,False
без выхода (20x20),DFS,0.006399990525096655,0.003200024366378784,0.012699980288743973,0.0,0.0,False
без выхода (20x20),A,0.008680007886141539,0.005399982910603285,0.01810002140700817,0.0,0.0,False
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