查看“用户:JesseM1024”的源代码

代码备份如下

== 机械动力动力合成器矩阵周期最小化.ipynb ==

=== 调包 ===
import numpy as np

import matplotlib.pyplot as plt

from collections import deque

=== 函数定义 ===
def bfs_depth(grid, ini_pos):

   <nowiki>'''</nowiki>

   grid: 2d np array, only 0, 1

   ini_pos: 2-len python int list, position vec [a,b]

   returns the depth 2d array

   <nowiki>'''</nowiki>

   if not grid.size:

       return np.array([], dtype=int).reshape(0, 0)

   

   # 初始化访问数组并全部填充为-1

   visited = np.full_like(grid, -1, dtype=int)

   temp = ini_pos.copy()

   temp.append(0)

   # 起始点

   queue = deque([tuple(temp)])  # (row, col, depth)

   

   # 定义四个方向的移动

   directions = [(0, 1), (1, 0), (0, -1), (-1, 0)]

   

   while queue:

       row, col, depth = queue.popleft()

       

       # 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

       if grid[row, col] != 0:

           visited[row, col] = depth

           

           # 检查相邻的点

           for dx, dy in directions:

               new_row, new_col = row + dx, col + dy

               

               # 如果相邻点在网格内且未被访问

               if 0 <= new_row < grid.shape[0] and 0 <= new_col < grid.shape[1] and visited[new_row, new_col] == -1:

                   queue.append((new_row, new_col, depth + 1))

   

   return visited



def edge_detector(grid):

   row, col = grid.shape[0], grid.shape[1]

   ava_out_pos_list = []

   directions = [(0, 1), (1, 0), (0, -1), (-1, 0)]

   

   for i in range(row):

       for j in range(col):

           if grid[i,j]==1:

               if i==0 or i==row-1 or j==0 or j==col-1:

                   ava_out_pos_list.append([i,j])

               else:

                   exist_0 = False

                   for dx, dy in directions:

                       new_row, new_col = i + dx, j + dy

                       if grid[new_row, new_col] == 0:

                           exist_0 = True

                           break

                   if exist_0 :

                       ava_out_pos_list.append([i,j])

   return ava_out_pos_list

=== 参数定义 ===
<code>crafter_array = np.array([[0,0,0,0,1,0,0,0,0],</code>
                          [0,0,0,1,1,1,0,0,0],
                          [1,1,1,1,1,1,1,1,1],
                          [1,1,1,1,1,1,1,1,1],
                          [0,1,1,1,1,1,1,1,0],
                          [0,0,1,1,1,1,1,0,0],
                          [0,1,1,1,1,1,1,1,0],
                          [1,1,1,1,0,1,1,1,1],
                          [1,1,1,0,0,0,1,1,1]
                         ])

=== 运行1：最优结果绘制 ===
<code>ava_start = edge_detector(crafter_array)</code>

<code>cur_minimum_steps = np.inf</code>

<code>result = None</code>

<code>start = None</code>

<code>edge_result = np.ones((crafter_array.shape[0],crafter_array.shape[1]))</code>

<code>edge_result = edge_result*-1</code>

<code>for start_pos in ava_start:</code>

<code>   arr = bfs_depth(crafter_array,start_pos)</code>

<code>   temp_step = np.max(arr)</code>

<code>   edge_result[start_pos[0],start_pos[1]] = temp_step</code>

<code>   if temp_step < cur_minimum_steps:</code>

<code>       cur_minimum_steps = temp_step</code>

<code>       result = arr</code>

<code>       start = start_pos</code>

<code>print('minimum steps =',cur_minimum_steps,'and start at ',start)</code>

<code>print(result)</code>

<code>plt.figure()</code>

<code>plt.imshow(result, cmap='viridis', aspect='auto')</code>

<code>plt.colorbar()</code>

<code>plt.title('crafter depth matrix')</code>

<code>plt.xlabel('X')</code>

<code>plt.ylabel('Y')</code>

<code>plt.show()</code>

=== 运行2：边缘结果绘制 ===
<code>print(edge_result)</code>

<code>plt.figure()</code>

<code>plt.imshow(edge_result, cmap='viridis', aspect='auto')</code>

<code>plt.colorbar()</code>

<code>plt.title('all output step matrix')</code>

<code>plt.xlabel('X')</code>

<code>plt.ylabel('Y')</code>

<code>plt.show()</code>