用户:JesseM1024

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):

   '''

   grid: 2d np array, only 0, 1

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

   returns the depth 2d array

   '''

   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

crafter_array = np.array([[0,0,0,0,1,0,0,0,0],

                         [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

ava_start = edge_detector(crafter_array)

cur_minimum_steps = np.inf

result = None

start = None

edge_result = np.ones((crafter_array.shape[0],crafter_array.shape[1]))

edge_result = edge_result*-1

for start_pos in ava_start:

   arr = bfs_depth(crafter_array,start_pos)

   temp_step = np.max(arr)

   edge_result[start_pos[0],start_pos[1]] = temp_step

   if temp_step < cur_minimum_steps:

       cur_minimum_steps = temp_step

       result = arr

       start = start_pos

print('minimum steps =',cur_minimum_steps,'and start at ',start)

print(result)

plt.figure()

plt.imshow(result, cmap='viridis', aspect='auto')

plt.colorbar()

plt.title('crafter depth matrix')

plt.xlabel('X')

plt.ylabel('Y')

plt.show()

运行2：边缘结果绘制

print(edge_result)

plt.figure()

plt.imshow(edge_result, cmap='viridis', aspect='auto')

plt.colorbar()

plt.title('all output step matrix')

plt.xlabel('X')

plt.ylabel('Y')

plt.show()