本周的python 图 基础

https://www.jb51.net/article/122927.htm 

 

另一个例子

https://www.jb51.net/article/154766.htm 

import numpy as np
# BFS test 案例 2 

ini_matrix = [
     [0, 1, 1, 0, 1],
     [1, 0, 0, 1, 0],
     [1, 0, 0, 0, 1],
     [0, 1, 0, 0, 0],
     [1, 0, 1, 0, 0]
     ]
 
 
def bfs(matrix_para, start_point_para, end_point_para):
    """
    广度优先搜索
    :param matrix_para 图
    :param start_point_para 起点
    :param end_point_para 终点
    :return: 返回关联度
    """
    matrix = matrix_para
    start_point = start_point_para
    end_point = end_point_para
    
    vertex_num = len(matrix) # 顶点个数
    
    que = np.zeros(vertex_num, dtype=np.int) # 队列， 用于存储遍历过的顶点
    book = np.zeros(vertex_num, dtype=np.int) # 标记顶点i是否已经被访问，1表被访问，0表未被访问
    
    point_step_dict = dict() # key:点，value:起点到该点的步长
    
    # 队列初始化
    head = 0
    tail = 0
    
    # 迭代次数
    count = 0
    
    # 从0号顶点出发，将0号顶点加入队列
    que[tail] = start_point # 等号右边为顶点号（起点）
    tail += 1
    book[start_point] = 1 # book[i] i为顶点号
    
    while head<tail:
      flag = False # 用flag标识结点i是否周围都是被访问过的
      cur = que[head]
      for i in range(vertex_num):
      # 判断从顶点cur到顶点i是否有边，并判断顶点i是否已经被访问过
          if matrix[cur][i] == 1 and book[i] == 0:
              que[tail] = i # 将顶点i放入队列中
              tail += 1 # tail指针往后移
              book[i] = 1 # 标记顶点i为已经访问过
              point_step_dict[i] = count + 1 # 记录步长
              flag = True
          if tail == vertex_num: # 说明所有顶点都被访问过
              break
      if flag:
          count += 1
      head += 1

    for i in range(tail):
        print(que[i])

    try:
        relevancy = point_step_dict[end_point]
        return relevancy
    except KeyError:
        return None

result = bfs(ini_matrix, 0, 3)
print("result:", result)