如何通过指定规则改变边缘的权重? [英] How to change edges' weight by designated rule?
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问题描述
我有一个加权图:
F=nx.path_graph(10)
G=nx.Graph()
for (u, v) in F.edges():
G.add_edge(u,v,weight=1)
获取节点列表:
[(0, 1), (1, 2), (2, 3), (3, 4), (4, 5), (5, 6), (6, 7), (7, 8), (8, 9)]
我想通过此规则更改每个边缘的权重:
I want to change each edge's weight by this rule:
删除一个节点,例如节点5,显然,边缘(4, 5)
和(5, 6)
将被删除,并且每个边缘的权重将变为:
Remove one node, such as node 5, clearly, edge (4, 5)
, and (5, 6)
will be delete, and the weight of each edge will turn to:
{# these edges are nearby the deleted edge (4, 5) and (5, 6)
(3,4):'weight'=1.1,
(6,7):'weight'=1.1,
#these edges are nearby the edges above mentioned
(2,3):'weight'=1.2,
(7,8):'weight'=1.2,
#these edges are nearby the edges above mentioned
(1,2):'weight'=1.3,
(8,9):'weight'=1.3,
# this edge is nearby (1,2)
(0,1):'weight'=1.4}
如何编写此算法?
path_graph
只是一个示例.我需要一个适合任何图形类型的程序.此外,该程序必须是可迭代的,这意味着我每次都可以从原始图中删除一个节点.
path_graph
is just an example. I need a program to suit any graph type. Furthermore, the program need to be iterable, it means I can remove one node from the origin graph each time.
推荐答案
您可以将边缘权重作为G [u] [v] ['weight']或通过遍历边缘数据来访问.这样您就可以
You can access the edge weight as G[u][v]['weight'] or by iterating over the edge data. So you can e.g.
In [1]: import networkx as nx
In [2]: G=nx.DiGraph()
In [3]: G.add_edge(1,2,weight=10)
In [4]: G.add_edge(2,3,weight=20)
In [5]: G[2][3]['weight']
Out[5]: 20
In [6]: G[2][3]['weight']=200
In [7]: G[2][3]['weight']
Out[7]: 200
In [8]: G.edges(data=True)
Out[8]: [(1, 2, {'weight': 10}), (2, 3, {'weight': 200})]
In [9]: for u,v,d in G.edges(data=True):
...: d['weight']+=7
...:
...:
In [10]: G.edges(data=True)
Out[10]: [(1, 2, {'weight': 17}), (2, 3, {'weight': 207})]
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