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| （未显示同一用户的10个中间版本） |
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第1行： |
| 代码备份如下
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| == 机械动力动力合成器矩阵周期最小化.ipynb ==
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| === 调包 ===
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| <code>import numpy as np</code>
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|
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| <code>import matplotlib.pyplot as plt</code>
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|
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| <code>from collections import deque</code>
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|
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| === 函数定义 ===
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| <code>def bfs_depth(grid, ini_pos):</code>
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|
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| <code> <nowiki>'''</nowiki></code>
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|
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| <code> grid: 2d np array, only 0, 1</code>
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|
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| <code> ini_pos: 2-len python int list, position vec [a,b]</code>
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|
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| <code> returns the depth 2d array</code>
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|
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| <code> <nowiki>'''</nowiki></code>
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|
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| <code> if not grid.size:</code>
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|
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| <code> return np.array([], dtype=int).reshape(0, 0)</code>
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|
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| <code> </code>
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|
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| <code> # 初始化访问数组并全部填充为-1</code>
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|
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| <code> visited = np.full_like(grid, -1, dtype=int)</code>
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|
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| <code> temp = ini_pos.copy()</code>
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|
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| <code> temp.append(0)</code>
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|
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| <code> # 起始点</code>
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|
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| <code> queue = deque([tuple(temp)]) # (row, col, depth)</code>
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|
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| <code> </code>
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|
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| <code> # 定义四个方向的移动</code>
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|
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| <code> directions = [(0, 1), (1, 0), (0, -1), (-1, 0)]</code>
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|
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| <code> </code>
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|
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| <code> while queue:</code>
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|
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| <code> row, col, depth = queue.popleft()</code>
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|
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| <code> </code>
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|
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| <code> # 如果当前点不是障碍物（假设0表示障碍物），则更新访问数组</code>
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|
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| <code> if grid[row, col] != 0:</code>
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|
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| <code> visited[row, col] = depth</code>
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|
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| <code> </code>
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|
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| <code> # 检查相邻的点</code>
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|
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| <code> for dx, dy in directions:</code>
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|
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| <code> new_row, new_col = row + dx, col + dy</code>
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|
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| <code> </code>
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|
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| <code> # 如果相邻点在网格内且未被访问</code>
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|
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| <code> if 0 <= new_row < grid.shape[0] and 0 <= new_col < grid.shape[1] and visited[new_row, new_col] == -1:</code>
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|
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| <code> queue.append((new_row, new_col, depth + 1))</code>
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|
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| <code> </code>
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|
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| <code> return visited</code>
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|
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|
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|
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| <code>def edge_detector(grid):</code>
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|
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| <code> row, col = grid.shape[0], grid.shape[1]</code>
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|
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| <code> ava_out_pos_list = []</code>
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|
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| <code> directions = [(0, 1), (1, 0), (0, -1), (-1, 0)]</code>
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|
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| <code> </code>
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|
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| <code> for i in range(row):</code>
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|
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| <code> for j in range(col):</code>
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|
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| <code> if grid[i,j]==1:</code>
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|
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| <code> if i==0 or i==row-1 or j==0 or j==col-1:</code>
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|
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| <code> ava_out_pos_list.append([i,j])</code>
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|
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| <code> else:</code>
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|
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| <code> exist_0 = False</code>
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|
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| <code> for dx, dy in directions:</code>
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|
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| <code> new_row, new_col = i + dx, j + dy</code>
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|
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| <code> if grid[new_row, new_col] == 0:</code>
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|
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| <code> exist_0 = True</code>
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|
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| <code> break</code>
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|
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| <code> if exist_0 :</code>
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|
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| <code> ava_out_pos_list.append([i,j])</code>
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|
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| <code> return ava_out_pos_list</code>
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|
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| === 参数定义 ===
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| <code>crafter_array = np.array([[0,0,0,0,1,0,0,0,0],</code>
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| [0,0,0,1,1,1,0,0,0],
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| [1,1,1,1,1,1,1,1,1],
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| [1,1,1,1,1,1,1,1,1],
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| [0,1,1,1,1,1,1,1,0],
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| [0,0,1,1,1,1,1,0,0],
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| [0,1,1,1,1,1,1,1,0],
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| [1,1,1,1,0,1,1,1,1],
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| [1,1,1,0,0,0,1,1,1]
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| ])
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|
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| === 运行1：最优结果绘制 ===
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| <code>ava_start = edge_detector(crafter_array)</code>
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|
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| <code>cur_minimum_steps = np.inf</code>
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|
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| <code>result = None</code>
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|
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| <code>start = None</code>
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|
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| <code>edge_result = np.ones((crafter_array.shape[0],crafter_array.shape[1]))</code>
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|
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| <code>edge_result = edge_result*-1</code>
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|
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| <code>for start_pos in ava_start:</code>
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|
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| <code> arr = bfs_depth(crafter_array,start_pos)</code>
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|
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| <code> temp_step = np.max(arr)</code>
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|
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| <code> edge_result[start_pos[0],start_pos[1]] = temp_step</code>
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|
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| <code> if temp_step < cur_minimum_steps:</code>
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|
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| <code> cur_minimum_steps = temp_step</code>
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|
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| <code> result = arr</code>
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|
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| <code> start = start_pos</code>
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| <code>print('minimum steps =',cur_minimum_steps,'and start at ',start)</code>
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| <code>print(result)</code>
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|
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| <code>plt.figure()</code>
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|
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| <code>plt.imshow(result, cmap='viridis', aspect='auto')</code>
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|
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| <code>plt.colorbar()</code>
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|
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| <code>plt.title('crafter depth matrix')</code>
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|
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| <code>plt.xlabel('X')</code>
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|
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| <code>plt.ylabel('Y')</code>
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|
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| <code>plt.show()</code>
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|
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| === 运行2：边缘结果绘制 ===
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| <code>print(edge_result)</code>
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|
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| <code>plt.figure()</code>
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|
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| <code>plt.imshow(edge_result, cmap='viridis', aspect='auto')</code>
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|
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| <code>plt.colorbar()</code>
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|
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| <code>plt.title('all output step matrix')</code>
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|
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| <code>plt.xlabel('X')</code>
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|
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| <code>plt.ylabel('Y')</code>
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| <code>plt.show()</code>
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