Networkx：将多图转换为具有加权边的简单图 [英] Networkx : Convert multigraph into simple graph with weighted edges

问题描述

我有一个多图对象，并希望将其转换为具有加权边的简单图对象。我查看了networkx文档，似乎无法找到实现此功能的内置函数。我只是想知道是否有人知道networkx中的内置函数可以实现这个目标。我查看了to_directed（），to_undirected（）函数，但它们不符合我的目标。 解决方案

通过加权来创建加权多图的加权图：

  import networkx as nx 
＃weighted MultiGraph 
 M = nx.MultiGraph（）
 M.add_edge（1,2，weight = 7）
 M.add_edge（1,2，weight = 19）
 M.add_edge（ 2,3，weight = 42）
 
＃从M $ b $创建加权图G = nx.Graph（）
用于u，v，数据在M.edges（data = True）：
w = data ['weight']如果数据中的'weight'其他1.0 
如果G.has_edge（u，v）：
 G [u] [v] ['weight '] + = w 
 else：
 G.add_edge（u，v，weight = w）
 
 print（G.edges（data = True））
 ＃[（1，2，{'weight'：26}），（2，3，{'weight'：42}）] 
  

I have a multigraph object and would like to convert it to a simple graph object with weighted edges. I have looked through the networkx documentation and can't seem to find a built in function to achieve this. I was just wondering if anyone knew of a built-in function in networkx that could achieve this goal. I looked at the to_directed() , to_undirected() functions but they don't serve my goal.

解决方案

Here is one way to create a weighted graph from a weighted multigraph by summing the weights:

import networkx as nx
# weighted MultiGraph
M = nx.MultiGraph()
M.add_edge(1,2,weight=7)
M.add_edge(1,2,weight=19)
M.add_edge(2,3,weight=42)

# create weighted graph from M
G = nx.Graph()
for u,v,data in M.edges(data=True):
    w = data['weight'] if 'weight' in data else 1.0
    if G.has_edge(u,v):
        G[u][v]['weight'] += w
    else:
        G.add_edge(u, v, weight=w)

print(G.edges(data=True))
# [(1, 2, {'weight': 26}), (2, 3, {'weight': 42})]

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