获取包含一定数量节点的networkx子图

Question

我有一个networkx DiGraph，我想提取包含一定数量节点的子图。例如，有向图为0-1-2-3-4-5。我想获得所有包含3个节点的子图。结果应该是：0-1-2，1-2-3，2-3-4，3-4-5。我该怎么做？

Answer 1

我不完全确定我是否理解正确：你的例子暗示你只想要连通的子图？在有向图中，存在不止一种连通性(弱连通性和强连通性(。所以你必须决定你要找哪一个。

这可能有效：

import networkx as nx
from itertools import combinations
# The graph in your example (as I understand it)
G = nx.DiGraph((i, i+1) for i in range(5))
num_of_nodes = 3 # Number of nodes in the subgraphs (here 3, as in your example)
subgraphs = [] # List for collecting the required subgraphs
for nodes in combinations(G.nodes, num_of_nodes):
G_sub = G.subgraph(nodes) # Create subgraph induced by nodes
# Check for weak connectivity
if nx.is_weakly_connected(G_sub):
subgraphs.append(G_sub)

CCD_ 1在CCD_ 2的所有唯一组合上迭代来自CCD_ 3的许多节点。

所选的子图正是你提到的：

print([H.nodes for H in subgraphs])
print([H.edges for H in subgraphs])

显示

[NodeView((0, 1, 2)), NodeView((1, 2, 3)), NodeView((2, 3, 4)), NodeView((3, 4, 5))]
[OutEdgeView([(0, 1), (1, 2)]), OutEdgeView([(1, 2), (2, 3)]), OutEdgeView([(2, 3), (3, 4)]), OutEdgeView([(3, 4), (4, 5)])]

如果您的图形是

G = nx.DiGraph([(i, i+1) for i in range(5)] + [(i+1, i) for i in range(5)])

如果你正在寻找强大的连接，那么你必须使用

...
# Check for strong connectivity
if nx.is_strongly_connected(G_sub):
...

(通常的警告：G.subgraph()只提供视图。(