networkX 中无向图的参数传递闭包

Question

I am making an undirected graph from existing edges.

G = nx.Graph()
edge_list = [(1,2),(2,3), (3,4), (4,5),(5,6)]
G.add_edges_from(edge_list)

Now I want to perform transitive closure that is parametrized by level k such that k=1 means following new edges will be added.

new_edge_list = [(1,3),(2,4),(3,5),(4,6)]
G.add_edges_from(new_edge_list)

While k=2 means following new edges would be added.

new_edge_list = [(1,3),(1,4),(2,4),(2,5),(3,5), (3,6),(4,6)]
G.add_edges_from(new_edge_list)

This essentially means that as we keep on increasing the value of k , the graph G would eventually become a clique (ie a transitive closure). However, I want to get a transitive closure at a specific level of k . I am able to get full transitive closure using this answer . But I am struggling with specific level of transitive closure. I am able to achieve k=1 transitive closure by using adjacency representation but that cannot be scaled for k=2 .

PS: It is okay if symmetric edges are also created like [(1,3),(3,1)] during parametric transitive closure.

Answer 1

如果您有一个适用于k = 1情况的工作算法，并且您提到的缩放问题不是由于图本身随着添加更多边而增长而出现的，那么您可以简单地递归使用该算法，作为结果将其应用于k = 1 -case 的输出将是您的k = 2 -case。