如何将一个图的边权重添加到 NetworkX 中不同图中的匹配边？答案

【问题标题】：How to add edge weights from one graph to matching edges in a different graph in NetworkX?如何将一个图的边权重添加到 NetworkX 中不同图中的匹配边？
【发布时间】：2021-05-22 20:55:34
【问题描述】：

我在 networkx 中有两个不同的图，一个图有边的总集合。另一个图是总边的子集。如何从边图的总集合中获取权重并将它们添加到新图中的匹配边？

#total edge collection
G.edges(data = True)

OutEdgeDataView([(1, 2, {'weight': 10}), (2, 3, {'weight': 0}), (2, 5, {'weight': 0}), (2, 6, {'weight': 0}), 
(2, 1, {'weight': 0}), (3, 4, {'weight': 10}), (3, 7, {'weight': 0}), (3, 8, {'weight': 0}), (3, 2, {'weight': 0}), (4, 3, {'weight': 0}), (5, 2, {'weight': 0}), (6, 2, {'weight': 0}), 
(7, 3, {'weight': 0}), (8, 3, {'weight': 0})])

T = nx.Graph()
T.add_edges_from([(1, 2), (2, 3), (2, 5), (2, 6), (3, 8), (3, 4), (3, 7)])
T.edges(data = True)

EdgeDataView([(1, 2, {}), (2, 3, {}), (2, 5, {}), (2, 6, {}), (3, 8, {}), (3, 4, {}), (3, 7, {})])

我希望 T EdgeDataView 看起来像

EdgeDataView([(1, 2, {'weight':10}), (2, 3, {'weight': 0}), (2, 5, {'weight': 0}), (2, 6, {'weight': 0}),
 (3, 8, {'weight': 0}), (3, 4, {'weight': 10}), (3, 7, {'weight': 0})])

任何想法都将不胜感激，

【问题讨论】：

标签： python graph nodes networkx edges

【解决方案1】：

你可以试试networkx Graph.edge_subgraph function。

以您为例。
首先创建图表：

G = nx.DiGraph()
G.add_edges_from([(1, 2, {'weight': 10}), (2, 3, {'weight': 0}), (2, 5, {'weight': 0}), (2, 6, {'weight': 0}), 
(2, 1, {'weight': 0}), (3, 4, {'weight': 10}), (3, 7, {'weight': 0}), (3, 8, {'weight': 0}), (3, 2, {'weight': 0}), (4, 3, {'weight': 0}), (5, 2, {'weight': 0}), (6, 2, {'weight': 0}), 
(7, 3, {'weight': 0}), (8, 3, {'weight': 0})])

接下来，选择您要添加到新图表中的节点：

edge_set = [(1, 2), (2, 3), (2, 5), (2, 6), (3, 8), (3, 4), (3, 7)]

然后，从一个图形中提取边到另一个图形：

Di_T = G.edge_subgraph(edge_set)

请注意，由于G 被定向，T 也将被定向，所以：

T = Di_T.to_undirected()    # see NOTE in the end

结果

>>> T.edges(data = True)

EdgeDataView([ (1, 2, {'weight': 10}),
               (2, 3, {'weight': 0}),
               (2, 5, {'weight': 0}),
               (2, 6, {'weight': 0}),
               (3, 4, {'weight': 10}),
               (3, 7, {'weight': 0}),
               (3, 8, {'weight': 0})])

完整代码：

# example graph

G = nx.DiGraph()
G.add_edges_from([(1, 2, {'weight': 10}), (2, 3, {'weight': 0}), (2, 5, {'weight': 0}), (2, 6, {'weight': 0}), (2, 1, {'weight': 0}), (3, 4, {'weight': 10}), (3, 7, {'weight': 0}), (3, 8, {'weight': 0}), (3, 2, {'weight': 0}), (4, 3, {'weight': 0}), (5, 2, {'weight': 0}), (6, 2, {'weight': 0}), (7, 3, {'weight': 0}), (8, 3, {'weight': 0})])


# example edge set

edge_set = [(1, 2), (2, 3), (2, 5), (2, 6), (3, 8), (3, 4), (3, 7)]


# solution

T = G.edge_subgraph(edge_set).to_undirected()
T.edges(data = True)

注意：

通常由G.edge_subgraph(edge_set) 制作副本（使用.copy）为了获得图形的新副本而不是原始图的参考（见the notes in the Docs）。
但是，.to_undirected 已经制作了图的深层副本所以不需要.copy，检查G.edge_subgraph 和 .to_undirected 文档了解更多信息

【讨论】：