181 lines
5.0 KiB
Python
181 lines
5.0 KiB
Python
from abc import ABC, abstractmethod
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from collections import deque
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import heapq
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import time
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class Cell:
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def __init__(self, x, y):
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self.x = x
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self.y = y
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self.is_wall = False
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self.is_start = False
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self.is_exit = False
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def is_passable(self):
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return not self.is_wall
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def __repr__(self):
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return f"Cell({self.x},{self.y})"
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class Maze:
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def __init__(self, width, height):
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self.width = width
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self.height = height
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self.cells = []
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self.start = None
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self.exit = None
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for y in range(height):
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row = []
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for x in range(width):
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row.append(Cell(x, y))
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self.cells.append(row)
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def get_cell(self, x, y):
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if 0 <= x < self.width and 0 <= y < self.height:
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return self.cells[y][x]
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return None
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def get_neighbors(self, cell):
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neighbors = []
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for dx, dy in [(0, -1), (0, 1), (-1, 0), (1, 0)]:
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nx, ny = cell.x + dx, cell.y + dy
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neighbor = self.get_cell(nx, ny)
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if neighbor and neighbor.is_passable():
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neighbors.append(neighbor)
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return neighbors
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class TextFileMazeBuilder:
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def build_from_file(self, filename):
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with open(filename, 'r') as f:
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lines = [line.rstrip() for line in f.readlines()]
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height = len(lines)
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width = len(lines[0])
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maze = Maze(width, height)
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for y, line in enumerate(lines):
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for x, ch in enumerate(line):
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cell = maze.get_cell(x, y)
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if ch == '#':
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cell.is_wall = True
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elif ch == 'S':
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maze.start = cell
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cell.is_start = True
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elif ch == 'E':
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maze.exit = cell
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cell.is_exit = True
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return maze
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class PathFindingStrategy(ABC):
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@abstractmethod
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def find_path(self, maze, start, exit):
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pass
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class BFSStrategy(PathFindingStrategy):
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def find_path(self, maze, start, exit):
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if not start or not exit:
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return [], 0
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queue = deque([(start, [start])])
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visited = {start}
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while queue:
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current, path = queue.popleft()
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if current == exit:
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return path, len(visited)
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for neighbor in maze.get_neighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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queue.append((neighbor, path + [neighbor]))
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return [], len(visited)
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class DFSStrategy(PathFindingStrategy):
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def find_path(self, maze, start, exit):
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if not start or not exit:
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return [], 0
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stack = [(start, [start])]
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visited = {start}
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while stack:
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current, path = stack.pop()
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if current == exit:
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return path, len(visited)
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for neighbor in maze.get_neighbors(current):
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if neighbor not in visited:
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visited.add(neighbor)
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stack.append((neighbor, path + [neighbor]))
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return [], len(visited)
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class AStarStrategy(PathFindingStrategy):
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def _heuristic(self, a, b):
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return abs(a.x - b.x) + abs(a.y - b.y)
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def find_path(self, maze, start, exit):
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if not start or not exit:
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return [], 0
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heap = [(self._heuristic(start, exit), 0, start, [start])]
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g_score = {start: 0}
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visited = set()
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counter = 1
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while heap:
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_, _, current, path = heapq.heappop(heap)
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if current in visited:
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continue
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visited.add(current)
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if current == exit:
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return path, len(visited)
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for neighbor in maze.get_neighbors(current):
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tentative_g = g_score[current] + 1
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if neighbor not in g_score or tentative_g < g_score[neighbor]:
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g_score[neighbor] = tentative_g
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f = tentative_g + self._heuristic(neighbor, exit)
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heapq.heappush(heap, (f, counter, neighbor, path + [neighbor]))
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counter += 1
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return [], len(visited)
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class SearchStats:
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def __init__(self, path, time_ms, visited_count):
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self.path = path
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self.time_ms = time_ms
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self.visited_count = visited_count
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self.path_length = len(path) if path else 0
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class MazeSolver:
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def __init__(self, maze, strategy=None):
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self.maze = maze
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self.strategy = strategy
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def set_strategy(self, strategy):
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self.strategy = strategy
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def solve(self):
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start_time = time.perf_counter()
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path, visited = self.strategy.find_path(self.maze, self.maze.start, self.maze.exit)
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end_time = time.perf_counter()
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return SearchStats(path, (end_time - start_time) * 1000, visited)
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