forked from UNN/2026-rff_mp
403 lines
12 KiB
Python
403 lines
12 KiB
Python
import sys
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import csv
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from collections import deque
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import heapq
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import time
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import matplotlib.pyplot as plt
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import numpy as np
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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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@property
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def x(self):
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return self._x
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@property
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def y(self):
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return self._y
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@property
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def is_wall(self):
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return self._is_wall
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@is_wall.setter
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def is_wall(self, value):
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self._is_wall = value
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@property
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def is_start(self):
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return self._is_start
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@is_start.setter
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def is_start(self, value):
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self._is_start = value
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@property
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def is_exit(self):
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return self._is_exit
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@is_exit.setter
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def is_exit(self, value):
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self._is_exit = value
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def is_passable(self):
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return not self._is_wall
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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 = [[Cell(x, y) for x in range(width)] for y in range(height)]
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self._start = None
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self._exit = None
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@property
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def width(self):
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return self._width
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@property
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def height(self):
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return self._height
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@property
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def start(self):
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return self._start
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@property
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def exit(self):
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return self._exit
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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 set_cell(self, x, y, cell_type):
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cell = self.get_cell(x, y)
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if cell is None:
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return
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if cell_type == 'wall':
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cell.is_wall = True
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elif cell_type == 'start':
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if self._start:
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self._start.is_start = False
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cell.is_start = True
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cell.is_wall = False
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self._start = cell
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elif cell_type == 'exit':
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if self._exit:
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self._exit.is_exit = False
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cell.is_exit = True
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cell.is_wall = False
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self._exit = cell
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elif cell_type == 'path':
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cell.is_wall = False
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def get_neighbors(self, cell):
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neighbors = []
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directions = [(0, -1), (0, 1), (-1, 0), (1, 0)]
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for dx, dy in directions:
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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 MazeBuilder:
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def build_from_file(self, filename):
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raise NotImplementedError
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class TextFileMazeBuilder(MazeBuilder):
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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('\n') for line in f.readlines()]
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height = len(lines)
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width = max(len(line) for line in lines) if height > 0 else 0
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start_en = 0
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exit_en = 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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if ch == "#":
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maze.set_cell(x, y, "wall")
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elif ch == "S":
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maze.set_cell(x, y, "start")
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start_en += 1
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elif ch == "E":
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maze.set_cell(x, y, "exit")
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exit_en += 1
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else:
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maze.set_cell(x, y, 'path')
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if start_en != 1 or exit_en != 1:
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raise ValueError(f"Invalid maze: S={start_en}, E={exit_en}")
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return maze
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class PathFindingStrategy:
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def find_path(self, maze, start, exit_cell):
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raise NotImplementedError
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def _reconstruct_path(self, came_from, start, exit_cell):
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path = []
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current = exit_cell
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while current is not None:
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path.append(current)
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current = came_from.get(current)
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path.reverse()
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return path
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def get_visited_count(self):
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return getattr(self, '_visited_count', 0)
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class BFSStrategy(PathFindingStrategy):
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def find_path(self, maze, start, exit_cell):
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queue = deque()
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queue.append(start)
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came_from = {start: None}
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visited = {start}
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while queue:
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current = queue.popleft()
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if current == exit_cell:
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self._visited_count = len(visited)
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return self._reconstruct_path(came_from, start, exit_cell)
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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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came_from[neighbor] = current
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queue.append(neighbor)
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self._visited_count = len(visited)
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return []
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class DFSStrategy(PathFindingStrategy):
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def find_path(self, maze, start, exit_cell):
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stack = [start]
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came_from = {start: None}
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visited = {start}
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while stack:
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current = stack.pop()
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if current == exit_cell:
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self._visited_count = len(visited)
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return self._reconstruct_path(came_from, start, exit_cell)
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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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came_from[neighbor] = current
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stack.append(neighbor)
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self._visited_count = len(visited)
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return []
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class AStarStrategy(PathFindingStrategy):
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def _heuristic(self, cell, exit_cell):
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return abs(cell.x - exit_cell.x) + abs(cell.y - exit_cell.y)
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def find_path(self, maze, start, exit_cell):
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heap = []
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counter = 0
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start_f = self._heuristic(start, exit_cell)
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heapq.heappush(heap, (start_f, counter, start))
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counter += 1
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came_from = {}
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g_score = {start: 0}
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f_score = {start: start_f}
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visited = set()
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while heap:
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current_f, _, current = heapq.heappop(heap)
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visited.add(current)
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if current == exit_cell:
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self._visited_count = len(visited)
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return self._reconstruct_path(came_from, start, exit_cell)
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if current_f > f_score.get(current, float('inf')):
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continue
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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 tentative_g < g_score.get(neighbor, float('inf')):
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came_from[neighbor] = current
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g_score[neighbor] = tentative_g
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new_f = tentative_g + self._heuristic(neighbor, exit_cell)
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f_score[neighbor] = new_f
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heapq.heappush(heap, (new_f, counter, neighbor))
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counter += 1
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self._visited_count = len(visited)
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return []
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class MazeSolver:
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def __init__(self, maze):
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self._maze = maze
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self._strategy = None
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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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if self._strategy is None:
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return None
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start_time = time.perf_counter()
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path = 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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time_ms = (end_time - start_time) * 1000
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return {
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'time_ms': time_ms,
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'visited_cells': self._strategy.get_visited_count(),
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'path_length': len(path)
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}
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def run_experiment(maze_file, strategy, runs=5):
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builder = TextFileMazeBuilder()
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maze = builder.build_from_file(maze_file)
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total_time = 0
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total_visited = 0
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total_length = 0
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for _ in range(runs):
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solver = MazeSolver(maze)
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solver.set_strategy(strategy)
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stats = solver.solve()
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if stats:
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total_time += stats['time_ms']
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total_visited += stats['visited_cells']
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total_length += stats['path_length']
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return {
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'time_ms': total_time / runs,
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'visited_cells': total_visited / runs,
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'path_length': total_length / runs
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}
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def generate_plots(results):
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mazes = list(set([r['maze'] for r in results]))
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strategies = ['BFS', 'DFS', 'AStar']
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fig, axes = plt.subplots(1, 3, figsize=(15, 5))
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x = np.arange(len(mazes))
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width = 0.25
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for i, strat in enumerate(strategies):
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times = []
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for maze in mazes:
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val = next((r['time_ms'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
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times.append(val)
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axes[0].bar(x + i*width, times, width, label=strat)
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axes[0].set_xlabel('Maze')
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axes[0].set_ylabel('Time (ms)')
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axes[0].set_title('Execution Time Comparison')
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axes[0].set_xticks(x + width)
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axes[0].set_xticklabels(mazes, rotation=45, ha='right')
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axes[0].legend()
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axes[0].grid(True, alpha=0.3)
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for i, strat in enumerate(strategies):
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visited = []
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for maze in mazes:
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val = next((r['visited_cells'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
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visited.append(val)
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axes[1].bar(x + i*width, visited, width, label=strat)
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axes[1].set_xlabel('Maze')
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axes[1].set_ylabel('Visited Cells')
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axes[1].set_title('Visited Cells Comparison')
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axes[1].set_xticks(x + width)
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axes[1].set_xticklabels(mazes, rotation=45, ha='right')
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axes[1].legend()
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axes[1].grid(True, alpha=0.3)
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for i, strat in enumerate(strategies):
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lengths = []
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for maze in mazes:
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val = next((r['path_length'] for r in results if r['maze'] == maze and r['strategy'] == strat), 0)
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lengths.append(val)
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axes[2].bar(x + i*width, lengths, width, label=strat)
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axes[2].set_xlabel('Maze')
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axes[2].set_ylabel('Path Length')
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axes[2].set_title('Path Length Comparison')
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axes[2].set_xticks(x + width)
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axes[2].set_xticklabels(mazes, rotation=45, ha='right')
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axes[2].legend()
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axes[2].grid(True, alpha=0.3)
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plt.tight_layout()
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plt.savefig('performance_comparison_2-nd-exercise.png', dpi=150, bbox_inches='tight')
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plt.show()
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if __name__ == "__main__":
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mazes = [
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("maze1.txt", "Small 10x6"),
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("maze10x10.txt", "Medium 10x10"),
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("maze20x20.txt", "Large 20x20"),
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("maze_empty.txt", "Empty 15x15"),
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("maze_no_exit.txt", "No exit 10x10")
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]
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strategies = [
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("BFS", BFSStrategy()),
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("DFS", DFSStrategy()),
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("AStar", AStarStrategy())
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]
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results = []
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for maze_file, maze_name in mazes:
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print(f"Testing {maze_name}...")
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for strat_name, strat in strategies:
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try:
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stats = run_experiment(maze_file, strat, runs=3)
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results.append({
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'maze': maze_name,
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'strategy': strat_name,
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'time_ms': stats['time_ms'],
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'visited_cells': stats['visited_cells'],
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'path_length': stats['path_length']
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})
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print(f" {strat_name}: time={stats['time_ms']:.3f}ms, visited={stats['visited_cells']:.0f}, length={stats['path_length']:.0f}")
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except Exception as e:
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print(f" {strat_name}: ERROR - {e}")
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results.append({
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'maze': maze_name,
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'strategy': strat_name,
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'time_ms': -1,
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'visited_cells': -1,
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'path_length': -1
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})
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valid_results = [r for r in results if r['time_ms'] >= 0]
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with open('experiment_results_2-nd-exercise.csv', 'w', newline='', encoding='utf-8') as f:
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writer = csv.DictWriter(f, fieldnames=['maze', 'strategy', 'time_ms', 'visited_cells', 'path_length'])
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writer.writeheader()
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writer.writerows(valid_results)
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if valid_results:
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generate_plots(valid_results)
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print("\nResults saved to experiment_results_2-nd-exercise.csv")
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print("Plot saved to performance_comparison_2-nd-exercise.png")
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