forked from UNN/2026-rff_mp
Загрузить файлы в «SmirnovaVYu/docs/data»
This commit is contained in:
parent
1da6c3f5a8
commit
8cb368fdd4
79
SmirnovaVYu/docs/data/models.py
Normal file
79
SmirnovaVYu/docs/data/models.py
Normal file
|
|
@ -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)
|
||||
66
SmirnovaVYu/docs/data/observers.py
Normal file
66
SmirnovaVYu/docs/data/observers.py
Normal file
|
|
@ -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)
|
||||
49
SmirnovaVYu/docs/data/solver.py
Normal file
49
SmirnovaVYu/docs/data/solver.py
Normal file
|
|
@ -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
|
||||
99
SmirnovaVYu/docs/data/strategies.py
Normal file
99
SmirnovaVYu/docs/data/strategies.py
Normal file
|
|
@ -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))
|
||||
77
SmirnovaVYu/docs/data/visualize.py
Normal file
77
SmirnovaVYu/docs/data/visualize.py
Normal file
|
|
@ -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()
|
||||
Loading…
Reference in New Issue
Block a user