diff --git a/pomelovsd/ExitMaze/Core/Maze.py b/pomelovsd/ExitMaze/Core/Maze.py index 16fe36f..0534194 100644 --- a/pomelovsd/ExitMaze/Core/Maze.py +++ b/pomelovsd/ExitMaze/Core/Maze.py @@ -1,26 +1,22 @@ -class Maze: - def __init__(self, grid, start = None, exit = None): - self.grid = grid - self.start = start - self.exit = exit +class Maze: + def __init__(self, grid, start=None, exit=None): + self.grid = grid + self.start = start + self.exit = exit self.height = len(grid) self.width = len(grid[0]) if grid else 0 - # Создание новой ячейки - def getCell(self, x, y): - if 0 <= x < self.height and 0 <= y < self.width: - return self.grid[x][y] + def getCell(self, x, y): + if 0 <= x < self.width and 0 <= y < self.height: + return self.grid[y][x] return None - # Ищет соседние проходимые клетки def getNeighbors(self, cell): directions = [(0,1),(1,0),(0,-1),(-1,0)] result = [] - for dx, dy in directions: nx, ny = cell.x + dx, cell.y + dy neighbor = self.getCell(nx, ny) if neighbor and neighbor.isPassable(): result.append(neighbor) - - return result \ No newline at end of file + return result \ No newline at end of file diff --git a/pomelovsd/ExitMaze/Mazes/empty.txt b/pomelovsd/ExitMaze/Mazes/empty.txt index 0874bd5..db91695 100644 --- a/pomelovsd/ExitMaze/Mazes/empty.txt +++ b/pomelovsd/ExitMaze/Mazes/empty.txt @@ -1 +1,10 @@ -S E +########## +#S # +# # +# # +# # +# # +# # +# # +# E# +########## \ No newline at end of file diff --git a/pomelovsd/ExitMaze/Mazes/large.txt b/pomelovsd/ExitMaze/Mazes/large.txt index 4dd6a74..ea0442b 100644 --- a/pomelovsd/ExitMaze/Mazes/large.txt +++ b/pomelovsd/ExitMaze/Mazes/large.txt @@ -1,31 +1,103 @@ -############################################################ -#S # # # # # # # # -# ### ##### ##### ### ##### ### ### ##### ### ##### ### ### # -# # # # # # # # # # # # # -### ##### ##### ### ##### ######### ### ### ### ####### ### # -# # # # # # # # # # # # # -# ### # ##### ### ##### ####### # ### ### ######### ##### # # -# # # # # # # # # # # # # # -########### # # ### # ####### # ### ### ######### # # # ##### -# # # # # # # # # # # # # # -# ####### # # ########### ### ### ####### ##### # # # ##### # -# # # # # # # # # # # # # # # # # -# # ### # # ####### # ##### ### ### ### # # # # # # ##### # # -# # # # # # # # # # # # # # # # # # # # # # -# # # ### ####### # ##### # # ##### # # # # # # # # # # # # # -# # # # # # # # # # # # # # # # # # # # -# # ### ####### # ##### # # ##### # # ##### ##### # # # ##### -# # # # # # # # # # # # # # # # # -# ### # # ########### # # # # # # # ##### ######### # ##### # -# # # # # # # # # # # # # # # # # # -### # # # # ##### # ### # ##### # ##### # # ##### # ##### # # -# # # # # # # # # # # # # # # # # # # -# ####### ##### # # # ### # ######### # # ##### # # # # # # # -# # # # # # # # # # # # # # # # # # # # # -####### # # # # # # # # ######### # ### # # # # # # # # # # # -# # # # # # # # # # # # # # # # # # # # # # # # # -# ### # # # # # # # # # # ##### # ### # # # # # # # # # # # # -# # # # # # # # # # # # # # # # # # # # # # # # # # # -# # ### # # # # # # # # ##### # # # ### # # # # # # # # # # # -# # # # # # # # # # # # # # # -###########################################################E# +####################################################################################################### +#S # # # # # # # # # # # # # # +# ### ##### # ##### # # ### ### ####### ####### # # ### ### ### # ### ### ### ### # ### # # # ######### +# # # # # # # # # # # # # # # # # # # # # # # # # # +### ### ##### # ##### ### # # ##### ####### ### ### # # # ####### # ### # # ### # ### ### ##### # ### # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ### ### # # # # ### ### # ### ##### # ### # # # # # ####### # # ##### ### # ### ### # ##### ### # # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ### ####### # ######### ##### # # ### # ### ### ### # ####### # # ### # ##### ##### ########### # # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ##### ### # ##### # ####### ### # # # ##### # ##### ##### # ######### # # # # # # ### ### # ### # ### +# # # # # # # # # # # # # # # # # # # # # # # # # # # # +# # ####### # ##### # ### ##### ##### # ####### ######### # ##### # # # # # ### # ### # # # ### ### # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ##### ######### ##### # # # # # # ##### ##### ### # # # ### ####### ########### # # # # ### # ### # # +# # # # # # # # # # # # # # # # # # # # # +####### # ####### ### ##### # # # # # # # ######### ##### # # # # ####### # ### ### # ### ########### # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ### # # # ####### # # # ##### ### # ### # ### ### # ### ####### ### # # ### ##### ### ### ######### # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ### ### # ##### # ### ####### # ####### ##### # # # # # # # # # # ######### # ########### # ### # # # +# # # # # # # # # # # # # # # # # # # # # # # # +# # # ####### ### ####### ### # ##### # ##### ### # # # # # # # # ### # # ####### ### ### # ### ### ### +# # # # # # # # # # # # # # # # # # # # # # # # # # # +##### ### ##### ####### # # ### ### ##### ### ############# ### ### ### ####### ##### ####### # # ##### +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ######### ##### # # ### ### ### ####### ##### # ### ### ### # # # # # # # ##### # # # # # # ### # # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ####### ### ### ### ##### # # # # ####### # ##### ############# ### ### ### # # # # # ######### ### # +# # # # # # # # # # # # # # # # # # # # # # # # # # # +# ### # ### ### # ### ##### ### # ##### # ####### # ### ### ##### ### # ######### # ### # ### ### # # # +# # # # # # # # # # # # # # # # # # # # # # # +### # ### ######### # ##### # ### ### ### # # ##### # # # ### # # ####### # # ### ##### ### # ##### # # +# # # # # # # # # # # # # # # # # # # # # # # # # +### # ### ##### # ########### ##### ####### ########### # ### ######### # ### # # # # ### # # ##### # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # +### ##### # # ### # # ##### ### # ### # ##### # # # ##### ### # # # ##### ####### ##### ### # ### ### # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# # # # ############# ##### # # ### ### ### ### ### # # ####### # ### ### ##### ### ### ### ### # # # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# # ##### # # # # # # # ### ### # ### # ##### # ### ### ### ##### # ### ### ### ### ### ##### # ### ### +# # # # # # # # # # # # # # # # # # # # # # # # # # +### ### ### ### # ### ### ##### ### # # # # ### # ##### ##### # # # # ### ######### ### # # # ##### ### +# # # # # # # # # # # # # # # # # # # # # # # # # # # # +# # # # ### # ########### # # ### ######### # # ### # # # ##### # ### ##### # # ### ##### ##### # # # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # +# # ##### ### ### # # # ####### ############# ##### # ### ############### ##### # ##### ##### # # ##### +# # # # # # # # # # # # # # # # # # # # # # # # # # # +# ### ####### # ##### ### # # # # # # # # ##### # ##### ### ##### # # ##### # ### # # ### # # ### ##### +# # # # # # # # # # # # # # # # # # # # # # # # # # # +### # ##### # ### ### ### ##### # # # ### # ### ### ##### # ### ### ##### # # ####### # ### ### # ### # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# # # ####### # ### # # # ### ####### # ################# # # ##### # # ### # # ### # # # ##### ### # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # +### ##### # ### ### ### # # ########### # # # ##### ##### ##### ### ############# # # ### ### ### # # # +# # # # # # # # # # # # # # # # # # # # # # # +##### ### ##### ### ### # ############# ### # ##### # # # ######### ### ### ### ### # ##### ### ####### +# # # # # # # # # # # # # # # # # # # # # # # # # # # # +################# ### # ### # # ### # ####### ### ### ### ### # ####### # # # ### ##### # # ######### # +# # # # # # # # # # # # # # # # # # # # # # # # +####### ##### ##### # ### ### ######### ### # # ######### ### ### ### ##### # ### # # # ### # ##### ### +# # # # # # # # # # # # # # # # # # # # # # # # # # +# ### ##### ##### ### # ### # # # # ### ### # # ##### ##### ### # # ##### # # # ######### # ##### # # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # +# # ####### ### # ##### ####### # ####### ####### # # ######### ### ####### ##### ### # ######### ### # +# # # # # # # # # # # # # # # # # # # # # # # # +# ### ### ##### ##### # ##### ### # ### # ########### # ### # ### # ######### # ### # ##### ### ### ### +# # # # # # # # # # # # # # # # # # # # # # +### ### ####### # # # ##### ##### ########### # # # # ####### # # # # # ########### # # # ######### ### +# # # # # # # # # # # # # # # # # # # # # # # # # # # +# ##### # # ### # # ### # ##### ### # ### ### ##### ### # ### ##### # ### # # ############### ####### # +# # # # # # # # # # # # # # # # # # # # # # # # # # +# # # # ##### # # # ##### # ######### # # ####### ##### ### # ### ### # # # ### # ####### ### # ### # # +# # # # # # # # # # # # # # # # # # # # # # # # # +##### ##### # ### # ### # ##### ##### ##### ##### ##### # # ########### ##### ############# ### ##### # +# # # # # # # # # # # # # # # # # # # +### ### # # ############### # # ### # # ####### ### ### # ### ### # # ##### # # # ####### ####### # ### +# # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ####### ##### # ### # # # ##### ### # ### # ### # ########### ### # # ##### # ##### ####### # ##### # +# # # # # # # # # # # # # # # # # # # # # # # # # # +########### # ######### # ### # ### ### ### # ### ####################### # ### # ####### # ### # ### # +# # # # # # # # # # # # # # # # # # # # # # # +# # ### ####### # ### ### ### ### ########### # ##### # ##### ### ### # ### # ##### # ########### # # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # +### ### # ####### # # # ### ### # # # ### # # # ### # ##### # # ########### ######### # ### ### # ### # +# # # # # # # # # # # # # # # # # # # # # # # # # # +# # # ####### # ### # # # ### # ### ### ### ######### # ### # ### # ### # # ### ##### ####### ### # # # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # +### ##### ##### # # # # # # ##### # ### # ### ####### ####### ##### ### # ### ##### # # ### # # ####### +# # # # # # # # # # # # # # # # # # # # # # # # +# # # ### # ####### # ####### # ##### # ### # ### # # ####### ##### # ##### ##### # ### # # ### ##### # +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # +### # ######### # ##### # ### ##### ### # ##### ##### ### # ##### ### # # ############# # # ### # ### # +# # # # # # # # # # # # # # # # # # # # # # # # # # # +# ### # # # # # ### # # ### ### ##### ### # # # ### ### # # # # # ### # ### # # # # # # ##### # ### ### +# # # # # # # # # # # # # # # # # # # # # # # # # # # # # +# ####### ### # ### # ### # ### # # ####### # ##### # ### ### ##### # # # # ### # ### ### # ### ##### # +# # # # # # # # # # # # # # # # # # # # # # # # # # # +# ### ##### ### # # # ##### ############### ### # ### # # ### ##### ### # ##### ### ### ### ### # ##### +# # # # # # # # # # # # # # # # # # # # # # # # # # +### # ### ####### ### ### ##### # # # ##### ##### ######### ### ##### # ####### # # ### ### # ### ##### +# # # # # # # # # # # # # # # # E# +####################################################################################################### diff --git a/pomelovsd/ExitMaze/Mazes/medium.txt b/pomelovsd/ExitMaze/Mazes/medium.txt index e67a3ea..f2c0b22 100644 --- a/pomelovsd/ExitMaze/Mazes/medium.txt +++ b/pomelovsd/ExitMaze/Mazes/medium.txt @@ -1,5 +1,53 @@ -################################################## -#S # # # # # # E# -# ## # #### # ### # ##### # #### # ##### # ##### # -# # # # # # # # # # # # # # -################################################## +##################################################### +#S # # # # # # # # # +# ### # ### ########### # ### ### # ### # ########### +# # # # # # # # # # +### ### # # ### ### ##### # ##### ### ### ##### ### # +# # # # # # # # # # # # # +# ######### ##### # # ### ####### # ####### # ##### # +# # # # # # # # # # # # # # # # +# ### # ##### # # ### # ### # # ##### ##### # ##### # +# # # # # # # # # # # # # # # +### ### # # ### # ### ### # ### # # # ##### # # # ### +# # # # # # # # # # # # # # # +# ##### ####### ### ### ##### ### # ### # ### ### ### +# # # # # # # # # # # # # # +# ### ####### ### ### # ##### ######### ### ##### # # +# # # # # # # # # # # # # # # # +# # # ### ### # # # ####### # # # ######### ### ### # +# # # # # # # # # # # # # # # # # # +### ####### # # ### # # ### ### # ### # ##### # # # # +# # # # # # # # # # # # # # +# ####### # # # ### # # # # # ### # # ### # # ### # # +# # # # # # # # # # # # # # # +### ### ### ##### ### ### ### ### ##### ### ####### # +# # # # # # # # # # # +##### # # # ### # # ####### ### # ##### ### # ### ### +# # # # # # # # # # # # # # # # # +# ####### ### ### # ########### # # ##### # ### ### # +# # # # # # # # # # # # # # # # # +# # ### ### ### ### ### ### # # ### # # ### ##### # # +# # # # # # # # # # # # # # # # # +# ### # ##### ### ##### ##### # # ### # ### ### ### # +# # # # # # # # # # # # # +# ##### ######### ### # ### # ### # ### ####### ##### +# # # # # # # # +### # # ##### ##### ########### # ### ### # ### ##### +# # # # # # # # # # # # # # +# # # ### ##### ##### # ############# ##### # ##### # +# # # # # # # # # # # +# ### # # # ### ### ### ##### # # ##### ##### ####### +# # # # # # # # # # # # # +### # ##### ### # ####### ####### # # # # ##### # ### +# # # # # # # # # # # # # # # # # +### ### ### ####### ####### # ### # ### # # ### ### # +# # # # # # # # # # # # # # # # # +# # # # ### # # # # ##### ### ####### # # # ### # # # +# # # # # # # # # # # # # # # # # # # # +# # # ### ### # ##### # ### # # ### # ##### # # ### # +# # # # # # # # # # # # +### # # # # # # ##### # ### ### ##### ### # ##### ### +# # # # # # # # # # # # # # # # # +# # # ### ### ####### # ### # ### # ### ### ### ### # +# # # # # # # # # #E# +##################################################### diff --git a/pomelovsd/ExitMaze/Mazes/no_exit.txt b/pomelovsd/ExitMaze/Mazes/no_exit.txt index ba5f89a..3dc8a6b 100644 --- a/pomelovsd/ExitMaze/Mazes/no_exit.txt +++ b/pomelovsd/ExitMaze/Mazes/no_exit.txt @@ -1,3 +1,10 @@ -##### -#S### -##### +########## +#S # +# # # +# # # +# # # +# # # +# # # +# # # +# # +########## \ No newline at end of file diff --git a/pomelovsd/ExitMaze/Mazes/small.txt b/pomelovsd/ExitMaze/Mazes/small.txt index 8964116..76aa11a 100644 --- a/pomelovsd/ExitMaze/Mazes/small.txt +++ b/pomelovsd/ExitMaze/Mazes/small.txt @@ -1,5 +1,10 @@ ########## -#S #E# -# ### ## # +#S # +# # # +# # # # # # -########## +# # # +# # # +# # # +# E# +########## \ No newline at end of file diff --git a/pomelovsd/ExitMaze/Strategies/AStar.py b/pomelovsd/ExitMaze/Strategies/AStar.py index 12ded7a..5de7317 100644 --- a/pomelovsd/ExitMaze/Strategies/AStar.py +++ b/pomelovsd/ExitMaze/Strategies/AStar.py @@ -8,6 +8,9 @@ class AStar(PathFindingStrategy): return abs(a.x - b.x) + abs(a.y - b.y) def findPath(self, maze, start, exit): + if exit is None: + return [], 0 + heap = [] counter = 0 heapq.heappush(heap, (0, counter, start)) @@ -18,7 +21,7 @@ class AStar(PathFindingStrategy): visited = set() while heap: - _, _, current = heapq.heappop(heap) # распаковка трёх элементов + _, _, current = heapq.heappop(heap) if current == exit: break diff --git a/pomelovsd/ExitMaze/Strategies/BFS.py b/pomelovsd/ExitMaze/Strategies/BFS.py index 3aa876a..ec39a2a 100644 --- a/pomelovsd/ExitMaze/Strategies/BFS.py +++ b/pomelovsd/ExitMaze/Strategies/BFS.py @@ -3,7 +3,10 @@ from Strategies.path import restore from collections import deque class BFS(PathFindingStrategy): - def findPath(self, maze, start, exit): + def findPath(self, maze, start, exit): + if exit is None: + return [], 0 + queue = deque([start]) visited = {start} parent = {} @@ -18,6 +21,6 @@ class BFS(PathFindingStrategy): if n not in visited: visited.add(n) parent[n] = current - queue.append(n) + queue.append(n) return restore(parent, start, exit), len(visited) \ No newline at end of file diff --git a/pomelovsd/ExitMaze/Strategies/DFS.py b/pomelovsd/ExitMaze/Strategies/DFS.py index d523b9b..19ef836 100644 --- a/pomelovsd/ExitMaze/Strategies/DFS.py +++ b/pomelovsd/ExitMaze/Strategies/DFS.py @@ -1,9 +1,11 @@ from Strategies.strat import PathFindingStrategy from Strategies.path import restore - class DFS(PathFindingStrategy): def findPath(self, maze, start, exit): + if exit is None: + return [], 0 + stack = [start] visited = {start} parent = {} @@ -20,4 +22,4 @@ class DFS(PathFindingStrategy): parent[n] = current stack.append(n) - return restore(parent, start, exit), len(visited) \ No newline at end of file + return restore(parent, start, exit), len(visited) \ No newline at end of file diff --git a/pomelovsd/ExitMaze/Strategies/path.py b/pomelovsd/ExitMaze/Strategies/path.py index ba7f3bf..567e3c5 100644 --- a/pomelovsd/ExitMaze/Strategies/path.py +++ b/pomelovsd/ExitMaze/Strategies/path.py @@ -1,11 +1,11 @@ def restore(parent, start, exit): if exit not in parent and start != exit: - return[] + return [] path = [] - current = exit + current = exit - while current != start: + while current != start: path.append(current) current = parent[current] diff --git a/pomelovsd/ExitMaze/analysis.png b/pomelovsd/ExitMaze/analysis.png index 80117d3..1d9699e 100644 Binary files a/pomelovsd/ExitMaze/analysis.png and b/pomelovsd/ExitMaze/analysis.png differ diff --git a/pomelovsd/ExitMaze/main.ipynb b/pomelovsd/ExitMaze/main.ipynb index 3fa579a..21e7aa7 100644 --- a/pomelovsd/ExitMaze/main.ipynb +++ b/pomelovsd/ExitMaze/main.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 80, + "execution_count": 1, "id": "a1dff6b4", "metadata": {}, "outputs": [], @@ -16,7 +16,7 @@ }, { "cell_type": "code", - "execution_count": 81, + "execution_count": 2, "id": "66bfd079", "metadata": {}, "outputs": [], @@ -32,7 +32,7 @@ }, { "cell_type": "code", - "execution_count": 82, + "execution_count": 3, "id": "50c7010d", "metadata": {}, "outputs": [], @@ -50,7 +50,7 @@ }, { "cell_type": "code", - "execution_count": 83, + "execution_count": 4, "id": "7326fe7d", "metadata": {}, "outputs": [], @@ -64,7 +64,7 @@ }, { "cell_type": "code", - "execution_count": 84, + "execution_count": 5, "id": "8d47b4cf", "metadata": {}, "outputs": [ @@ -74,39 +74,52 @@ "text": [ "Лабиринт: small\n", "Testing BFS\n", - "BFS: time=0.05052728504649297 ms | visited=8.0 \n", + "BFS: time=0.21313328579708468 ms | visited=58.0 | path_len=15.0\n", "Testing DFS\n", - "DFS: time=0.02667414290564401 ms | visited=8.0 \n", + "DFS: time=0.0768381428965118 ms | visited=31.0 | path_len=19.0\n", "Testing A*\n", - "A*: time=0.04907028570804479 ms | visited=8.0 \n", + "A*: time=0.2827478572596322 ms | visited=57.0 | path_len=15.0\n", "Лабиринт: medium\n", "Testing BFS\n", - "BFS: time=0.03876400062706255 ms | visited=10.0 \n", + "BFS: time=5.220513428477196 ms | visited=1263.0 | path_len=173.0\n", "Testing DFS\n", - "DFS: time=0.03143985668430105 ms | visited=10.0 \n", + "DFS: time=4.18784342861857 ms | visited=1229.0 | path_len=173.0\n", "Testing A*\n", - "A*: time=0.042394856791361235 ms | visited=10.0 \n", + "A*: time=4.219951571420617 ms | visited=806.0 | path_len=173.0\n", "Лабиринт: large\n", "Testing BFS\n", - "BFS: time=0.9620827144577301 ms | visited=197.0 \n", + "BFS: time=11.833781999874711 ms | visited=3918.0 | path_len=269.0\n", "Testing DFS\n", - "DFS: time=0.8404238573608122 ms | visited=197.0 \n", + "DFS: time=5.629428999977141 ms | visited=1905.0 | path_len=269.0\n", "Testing A*\n", - "A*: time=1.04237128575083 ms | visited=197.0 \n", + "A*: time=10.02670385716036 ms | visited=2040.0 | path_len=269.0\n", "Лабиринт: empty\n", "Testing BFS\n", - "BFS: time=0.010339713948529347 ms | visited=2.0 \n", + "BFS: time=0.19871557131929357 ms | visited=64.0 | path_len=15.0\n", "Testing DFS\n", - "DFS: time=0.007900571810231278 ms | visited=2.0 \n", + "DFS: time=0.13947814282541263 ms | visited=64.0 | path_len=29.0\n", "Testing A*\n", - "A*: time=0.009533572145820861 ms | visited=2.0 \n", + "A*: time=0.28600042846197277 ms | visited=63.0 | path_len=15.0\n", "Лабиринт: no_exit\n", "Testing BFS\n", - "BFS: time=0.00666371410521346 ms | visited=1.0 \n", + "BFS: time=0.18080571427552578 ms | visited=58.0 | path_len=0.0\n", "Testing DFS\n", - "DFS: time=0.005225571450344952 ms | visited=1.0 \n", - "Testing A*\n", - "A*: time=0.006098571507858911 ms | visited=1.0 \n" + "DFS: time=0.19448514272621 ms | visited=58.0 | path_len=0.0\n", + "Testing A*\n" + ] + }, + { + "ename": "AttributeError", + "evalue": "'NoneType' object has no attribute 'x'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[5], line 19\u001b[0m\n\u001b[1;32m 16\u001b[0m solver \u001b[38;5;241m=\u001b[39m MazeSolver(maze, strategy)\n\u001b[1;32m 18\u001b[0m start_time \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mperf_counter()\n\u001b[0;32m---> 19\u001b[0m stats, path \u001b[38;5;241m=\u001b[39m \u001b[43msolver\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43msolve\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 20\u001b[0m end_time \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mperf_counter()\n\u001b[1;32m 22\u001b[0m elapsed_ms \u001b[38;5;241m=\u001b[39m (end_time \u001b[38;5;241m-\u001b[39m start_time) \u001b[38;5;241m*\u001b[39m \u001b[38;5;241m1000\u001b[39m\n", + "File \u001b[0;32m~/2026-rff_mp/pomelovsd/ExitMaze/MazeSolver/Solver.py:16\u001b[0m, in \u001b[0;36mMazeSolver.solve\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m 13\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21msolve\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[1;32m 14\u001b[0m start \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mperf_counter()\n\u001b[0;32m---> 16\u001b[0m path, visited \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstrategy\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfindPath\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmaze\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmaze\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstart\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmaze\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mexit\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 18\u001b[0m end \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mperf_counter()\n\u001b[1;32m 20\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m SearchStats((end\u001b[38;5;241m-\u001b[39mstart)\u001b[38;5;241m*\u001b[39m\u001b[38;5;241m1000\u001b[39m, visited, \u001b[38;5;28mlen\u001b[39m(path)), path\n", + "File \u001b[0;32m~/2026-rff_mp/pomelovsd/ExitMaze/Strategies/AStar.py:33\u001b[0m, in \u001b[0;36mAStar.findPath\u001b[0;34m(self, maze, start, exit)\u001b[0m\n\u001b[1;32m 31\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m n \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;129;01min\u001b[39;00m g \u001b[38;5;129;01mor\u001b[39;00m tentative \u001b[38;5;241m<\u001b[39m g[n]:\n\u001b[1;32m 32\u001b[0m g[n] \u001b[38;5;241m=\u001b[39m tentative\n\u001b[0;32m---> 33\u001b[0m priority \u001b[38;5;241m=\u001b[39m tentative \u001b[38;5;241m+\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mheuristic\u001b[49m\u001b[43m(\u001b[49m\u001b[43mn\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mexit\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m 34\u001b[0m heapq\u001b[38;5;241m.\u001b[39mheappush(heap, (priority, counter, n))\n\u001b[1;32m 35\u001b[0m counter \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m \u001b[38;5;241m1\u001b[39m\n", + "File \u001b[0;32m~/2026-rff_mp/pomelovsd/ExitMaze/Strategies/AStar.py:8\u001b[0m, in \u001b[0;36mAStar.heuristic\u001b[0;34m(self, a, b)\u001b[0m\n\u001b[1;32m 7\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21mheuristic\u001b[39m(\u001b[38;5;28mself\u001b[39m, a, b):\n\u001b[0;32m----> 8\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mabs\u001b[39m(a\u001b[38;5;241m.\u001b[39mx \u001b[38;5;241m-\u001b[39m \u001b[43mb\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mx\u001b[49m) \u001b[38;5;241m+\u001b[39m \u001b[38;5;28mabs\u001b[39m(a\u001b[38;5;241m.\u001b[39my \u001b[38;5;241m-\u001b[39m b\u001b[38;5;241m.\u001b[39my)\n", + "\u001b[0;31mAttributeError\u001b[0m: 'NoneType' object has no attribute 'x'" ] } ], @@ -116,52 +129,51 @@ "N = 7\n", "\n", "for maze_name, maze in mazes.items():\n", - "\n", " print(f\"Лабиринт: {maze_name}\")\n", "\n", " for strategy_name, strategy in strategies.items():\n", - "\n", " total_time = 0\n", " total_visited = 0\n", + " total_path_len = 0\n", "\n", " print(f\"Testing {strategy_name}\")\n", "\n", " for _ in range(N):\n", - "\n", " solver = MazeSolver(maze, strategy)\n", "\n", " start_time = time.perf_counter()\n", - "\n", " stats, path = solver.solve()\n", - "\n", " end_time = time.perf_counter()\n", "\n", " elapsed_ms = (end_time - start_time) * 1000\n", "\n", " total_time += elapsed_ms\n", - " total_visited += stats.visited_cells\n", - "\n", + " total_visited += stats.visited_cells \n", + " total_path_len += len(path) \n", "\n", " avg_time = total_time / N\n", " avg_visited = total_visited / N\n", + " avg_path_len = total_path_len / N\n", "\n", " results.append({\n", " \"maze\": maze_name,\n", " \"strategy\": strategy_name,\n", " \"time_ms\": round(avg_time, 3),\n", - " \"visited_cells\": int(avg_visited),\n", + " \"visited_cells\": int(avg_visited), \n", + " \"path_length\": int(avg_path_len), \n", " })\n", "\n", " print(\n", " f\"{strategy_name}: \"\n", " f\"time={avg_time} ms | \"\n", - " f\"visited={avg_visited} \"\n", + " f\"visited={avg_visited} | \"\n", + " f\"path_len={avg_path_len}\"\n", " )" ] }, { "cell_type": "code", - "execution_count": 85, + "execution_count": null, "id": "347cb7be", "metadata": {}, "outputs": [ @@ -186,6 +198,7 @@ " \"strategy\",\n", " \"time_ms\",\n", " \"visited_cells\",\n", + " \"path_length\"\n", " ])\n", "\n", " for row in results:\n", @@ -194,6 +207,7 @@ " row[\"strategy\"],\n", " row[\"time_ms\"],\n", " row[\"visited_cells\"],\n", + " row[\"path_length\"]\n", " ])\n", "\n", "print(f\"\\nCSV saved: {csv_file}\")" @@ -201,7 +215,7 @@ }, { "cell_type": "code", - "execution_count": 86, + "execution_count": null, "id": "4b6fb0b0", "metadata": {}, "outputs": [ @@ -210,20 +224,20 @@ "output_type": "stream", "text": [ "Результаты:\n", - "small | BFS | 0.051 ms | 8 visited \n", - "small | DFS | 0.027 ms | 8 visited \n", - "small | A* | 0.049 ms | 8 visited \n", - "medium | BFS | 0.039 ms | 10 visited \n", - "medium | DFS | 0.031 ms | 10 visited \n", - "medium | A* | 0.042 ms | 10 visited \n", - "large | BFS | 0.962 ms | 197 visited \n", - "large | DFS | 0.84 ms | 197 visited \n", - "large | A* | 1.042 ms | 197 visited \n", - "empty | BFS | 0.01 ms | 2 visited \n", - "empty | DFS | 0.008 ms | 2 visited \n", - "empty | A* | 0.01 ms | 2 visited \n", + "small | BFS | 0.029 ms | 17 visited \n", + "small | DFS | 0.018 ms | 14 visited \n", + "small | A* | 0.033 ms | 16 visited \n", + "medium | BFS | 0.018 ms | 10 visited \n", + "medium | DFS | 0.019 ms | 10 visited \n", + "medium | A* | 0.024 ms | 10 visited \n", + "large | BFS | 0.292 ms | 198 visited \n", + "large | DFS | 0.201 ms | 198 visited \n", + "large | A* | 0.277 ms | 198 visited \n", + "empty | BFS | 0.014 ms | 10 visited \n", + "empty | DFS | 0.015 ms | 10 visited \n", + "empty | A* | 0.021 ms | 9 visited \n", "no_exit | BFS | 0.007 ms | 1 visited \n", - "no_exit | DFS | 0.005 ms | 1 visited \n", + "no_exit | DFS | 0.006 ms | 1 visited \n", "no_exit | A* | 0.006 ms | 1 visited \n" ] } @@ -250,18 +264,9 @@ "outputs": [ { "data": { - "image/png": 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"text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "
" + "
" ] }, "metadata": {}, @@ -269,24 +274,24 @@ } ], "source": [ - "# Список лабиринтов в том же порядке, что и в results (уникальные)\n", "maze_names = [\"small\", \"medium\", \"large\", \"empty\", \"no_exit\"]\n", "strategies = [\"BFS\", \"DFS\", \"A*\"]\n", "\n", - "# Цвета для стратегий (можно взять из вашего примера или задать свои)\n", "colors = {\"BFS\": \"#EEDC82\", \"DFS\": \"#88D94C\", \"A*\": \"#FF43A4\"}\n", "\n", "# Подготовим данные для графиков\n", "time_data = {maze: {s: None for s in strategies} for maze in maze_names}\n", "visited_data = {maze: {s: None for s in strategies} for maze in maze_names}\n", + "path_data = {maze: {s: None for s in strategies} for maze in maze_names}\n", "\n", "for row in results:\n", " maze = row[\"maze\"]\n", " strat = row[\"strategy\"]\n", " time_data[maze][strat] = row[\"time_ms\"]\n", " visited_data[maze][strat] = row[\"visited_cells\"]\n", + " path_data[maze][strat] = row[\"path_length\"]\n", "\n", - "fig, (ax1, ax2) = plt.subplots(2, 1, figsize=(12, 10))\n", + "fig, (ax1, ax2, ax3) = plt.subplots(3, 1, figsize=(12, 14))\n", "\n", "x = np.arange(len(maze_names))\n", "width = 0.25 \n", @@ -295,7 +300,7 @@ "for strategy in strategies:\n", " values = [time_data[maze][strategy] for maze in maze_names]\n", " offset = width * multiplier\n", - " bars = ax1.bar(x + offset, values, width, label=strategy, color=colors[strategy])\n", + " ax1.bar(x + offset, values, width, label=strategy, color=colors[strategy])\n", " multiplier += 1\n", "\n", "ax1.set_xticks(x + width, maze_names)\n", @@ -304,7 +309,6 @@ "ax1.legend()\n", "ax1.grid(axis='y', alpha=0.5, linestyle='--')\n", "\n", - "\n", "multiplier = 0\n", "for strategy in strategies:\n", " values = [visited_data[maze][strategy] for maze in maze_names]\n", @@ -313,15 +317,27 @@ " multiplier += 1\n", "\n", "ax2.set_xticks(x + width, maze_names)\n", - "ax2.set_ylabel(\"Количество посещённых клеток\")\n", - "ax2.set_title(\"Сравнение количества посещённых клеток\")\n", + "ax2.set_ylabel(\"Количество исследованных клеток\")\n", + "ax2.set_title(\"Сравнение количества исследованных клеток\")\n", "ax2.legend()\n", "ax2.grid(axis='y', alpha=0.5, linestyle='--')\n", "\n", + "multiplier = 0\n", + "for strategy in strategies:\n", + " values = [path_data[maze][strategy] for maze in maze_names]\n", + " offset = width * multiplier\n", + " ax3.bar(x + offset, values, width, label=strategy, color=colors[strategy])\n", + " multiplier += 1\n", + "\n", + "ax3.set_xticks(x + width, maze_names)\n", + "ax3.set_ylabel(\"Длина пути\")\n", + "ax3.set_title(\"Сравнение длины найденного пути\")\n", + "ax3.legend()\n", + "ax3.grid(axis='y', alpha=0.5, linestyle='--')\n", + "\n", "plt.tight_layout()\n", "plt.savefig('analysis.png')\n", - "plt.show()\n", - "\n" + "plt.show()" ] } ], diff --git a/pomelovsd/ExitMaze/mermaid.png b/pomelovsd/ExitMaze/mermaid.png new file mode 100644 index 0000000..db96194 Binary files /dev/null and b/pomelovsd/ExitMaze/mermaid.png differ diff --git a/pomelovsd/ExitMaze/result maze.md b/pomelovsd/ExitMaze/result maze.md new file mode 100644 index 0000000..aa0ca93 --- /dev/null +++ b/pomelovsd/ExitMaze/result maze.md @@ -0,0 +1,173 @@ + # Структура: +- **Описание задачи и выбранных паттернов** (с диаграммой классов из Mermaid). +- **Листинги ключевых классов** (можно выборочно) **или ссылка на репозиторий**. +- **Результаты экспериментов** (таблицы, графики). +- **Анализ эффективности алгоритмов и применимости паттернов**. +- **Выводы: как ООП и паттерны помогли сделать код гибким и расширяемым. Что было бы сложно изменить без них**. +### Выводы: +#### 1) **Описание задачи и выбранных паттернов** +![[mermaid.png]] +>Диаграмма классов + +| Паттерн | Реализация в проекте | Обоснование | +| ------------ | --------------------------------------------------------------------------------- | ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | +| **Builder** | `MazeBuilders` (интерфейс)
`TextFileMazeBuilder` | Создание лабиринта из текстового файла.
Позволяя легко добавить другие форматы без изменения `Maze` | +| **Strategy** | `PathFindingStrategy` (интерфейс)
`BFS`
`DFS`
`AStar` | Алгоритмы поиска пути взаимозаменяемы
Strategy позволяет переключать их через `MazeSolver.setStrategy()` и добавлять новые (например, Дейкстра) без изменения кода | +| **Observer** | `Observer` (интерфейс)
`ConsoleView` | Отделяет визуализацию от логики поиска
`MazeSolver` может уведомлять подписчиков о событиях (начало/конец поиска), а `ConsoleView` реагирует на них
Легко добавить другие виды отображения (GUI, лог-файл) | +| **Command** | `Command` (интерфейс)
`Observer` (интерфейс)
`MoveCommand`
`ConsoleView` | Обеспечивает пошаговое наблюдение и отслеживание с возможностью отмены | +| | | | + +#### 2) **Листинги ключевых классов**: +**Core:** +```python +class Cell: + +def __init__(self, x = 0, y = 0, isWall = False, isStart = False, isExit = False): + +self.x = x + +self.y = y + +self.isWall = isWall + +self.isStart = isStart + +self.isExit = isExit + +# Возращает True, если посаседству стена + +def isPassable(self): + +return not self.isWall + +class Maze: + +def __init__(self, grid, start = None, exit = None): + +self.grid = grid + +self.start = start + +self.exit = exit + +self.height = len(grid) + +self.width = len(grid[0]) if grid else 0 + + + +# Создание новой ячейки + +def getCell(self, x, y): + +if 0 <= x < self.height and 0 <= y < self.width: + +return self.grid[x][y] + +return None + + + +# Ищет соседние проходимые клетки + +def getNeighbors(self, cell): + +directions = [(0,1),(1,0),(0,-1),(-1,0)] + +result = [] + + + +for dx, dy in directions: + +nx, ny = cell.x + dx, cell.y + dy + +neighbor = self.getCell(nx, ny) + +if neighbor and neighbor.isPassable(): + +result.append(neighbor) + + + +return result +``` +**Builder:** +```python +from abc import ABC, abstractmethod + +class MazeBuilders(ABC): + +@abstractmethod + +def build_from_file(self, filename): + +pass + + + +from Core.Cell import Cell + +from Core.Maze import Maze + +from Builder.BuilderInterface import MazeBuilders + + + +class TextFileMazeBuilder(MazeBuilders): + + + +def build_from_file(self, filename): + +grid = [] + +start = None + +exit = None + + + +with open(filename, "r", encoding="utf-8") as f: + +lines = [line.rstrip("\n") for line in f] + +for y, line in enumerate(lines): + +row = [] + +for x, ch in enumerate(line): + +cell = Cell(x, y, isWall = (ch == "#"), isStart = (ch == "S"), isExit = (ch == "E")) + +if (ch == "S"): + +start = cell + +if (ch == "E"): + +exit = cell + +row.append(cell) + + + +grid.append(row) + +return Maze(grid, start, exit) +``` + + +#### 3) **Результаты экспериментов**: + ![[analysis 3.png]] +>График созданный на основе 5 попыток замеров и их усреднения +### 4) **Анализ эффективности алгоритмов и применимости паттернов:** +- **BFS** + Работает медленно и обходит гораздо больше клеток, но гарантирует кратчайший маршерут +- **DFS** + Работает быстро, но за это приходиться платить не самыми оптимальными путями и количеством обходимых маршерутов(из-за чего растёт время работы) +- **A**** + Является золотой серединой между DFS и BFS ищет маршерут хуже BFS, но лучше чем DFS, обратная зависимость наблюдается в измерении времени +#### 5)**Выводы: как ООП и паттерны помогли сделать код гибким и расширяемым? Что было бы сложно изменить без них?** +ООП и паттерны помогли систематизировать код и написать единый код для 3 структур, так же легко масштабировать проект, за счёт единых функций применимых для разных алгоритмов +Сложно было бы изменить файлы лабиринтов, алгоритмы поиска пути, \ No newline at end of file diff --git a/pomelovsd/ExitMaze/results.csv b/pomelovsd/ExitMaze/results.csv index 971607a..1641f0d 100644 --- a/pomelovsd/ExitMaze/results.csv +++ b/pomelovsd/ExitMaze/results.csv @@ -1,16 +1,16 @@ -maze,strategy,time_ms,visited_cells -small,BFS,0.031,8 -small,DFS,0.027,8 -small,A*,0.039,8 -medium,BFS,0.033,10 -medium,DFS,0.031,10 -medium,A*,0.044,10 -large,BFS,0.641,197 -large,DFS,0.574,197 -large,A*,1.016,197 -empty,BFS,0.01,2 -empty,DFS,0.008,2 -empty,A*,0.01,2 -no_exit,BFS,0.006,1 -no_exit,DFS,0.005,1 -no_exit,A*,0.006,1 +maze,strategy,time_ms,visited_cells,path_length +small,BFS,0.379,58,15 +small,DFS,0.076,31,19 +small,A*,0.298,57,15 +medium,BFS,5.197,1263,173 +medium,DFS,3.898,1229,173 +medium,A*,4.109,806,173 +large,BFS,17.886,3918,269 +large,DFS,7.197,1905,269 +large,A*,10.377,2040,269 +empty,BFS,0.195,64,15 +empty,DFS,0.135,64,29 +empty,A*,0.288,63,15 +no_exit,BFS,0.007,0,0 +no_exit,DFS,0.007,0,0 +no_exit,A*,0.007,0,0