如何通过指定规则改变边缘的权重?
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【中文标题】如何通过指定规则改变边缘的权重?【英文标题】:How to change edges' weight by designated rule? 【发布时间】:2011-04-27 07:02:24 【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)]
我想通过这条规则改变每条边的权重:
删除一个节点,比如节点5,很明显,边(4, 5)
和(5, 6)
会被删除,每条边的权重会变成:
# 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
这个算法怎么写?
path_graph
只是一个例子。我需要一个适合任何图形类型的程序。此外,程序需要是可迭代的,这意味着我每次可以从原始图中删除一个节点。
【问题讨论】:
我不懂重新分配权重的规则 【参考方案1】:您可以通过 G[u][v]['weight'] 或通过迭代边缘数据来访问边缘权重。所以你可以例如
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)]
【讨论】:
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