关于python：NetworkX：如何向现有G.edges()添加权重？

NetworkX: how to add weights to an existing G.edges()?

给定在NetworkX中创建的任何图形G，我希望能够在创建图形后为G.edges()分配一些权重。涉及的图形是网格，erdos-reyni，barabasi-albert等。

鉴于我的G.edges()：

1	[(0, 1), (0, 10), (1, 11), (1, 2), (2, 3), (2, 12), ...]

而我的weights：

1	{(0,1):1.0, (0,10):1.0, (1,2):1.0, (1,11):1.0, (2,3):1.0, (2,12):1.0, ...}

如何为每个边缘分配相关权重？在这种情况下，所有权重均为1。

我试图像这样直接将权重添加到G.edges()

1 2	for i, edge in enumerate(G.edges()): G.edges[i]['weight']=weights[edge]

但是我得到这个错误：

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---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-48-6119dc6b7af0> in <module>()
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11 for i, edge in enumerate(G.edges()):
---> 12 G.edges[i]['weight']=weights[edge]

TypeError: 'instancemethod' object has no attribute '__getitem__'

怎么了？由于G.edges()是一个列表，为什么不能像访问其他列表一样访问其元素？

它失败，因为edges是一种方法。

该文档说要这样做：

1	G[source][target]['weight'] = weight

例如，以下内容对我有用：

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import networkx as nx

G = nx.Graph()

G.add_path([0, 1, 2, 3])

G[0][1]['weight'] = 3

>>> G.get_edge_data(0, 1)
{'weight': 3}

但是，您的代码类型确实失败了：

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G.edges[0][1]['weight'] = 3
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-14-97b10ad2279a> in <module>()
----> 1 G.edges[0][1]['weight'] = 3

TypeError: 'instancemethod' object has no attribute '__getitem__'

就您而言，我建议

1 2	for e in G.edges(): G[e[0]][e[1]] = weights[e]

相关讨论

添加这样的边：

g1.add_edge('Mark', 'Edward', weight = 3)
g1.add_edge('Joseph', 'Michael', weight = 3)
g1.add_edge('Joseph', 'Jason', weight = 4)

然后检查图形是否加权：

nx.is_weighted(g1)

True

按权重的大小对权重进行分类：

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elarge = [(u, v) for (u, v, d) in g1.edges(data=True) if d['weight'] > 4]
esmall = [(u, v) for (u, v, d) in g1.edges(data=True) if d['weight'] <= 4]

接下来显示加权图：

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pos = nx.spring_layout(g1) # positions for all nodes

节点

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nx.draw_networkx_nodes(g1, pos, node_size=100)

边缘

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nx.draw_networkx_edges(g1, pos, edgelist=elarge,
width=5)
nx.draw_networkx_edges(g1, pos, edgelist=esmall,
width=5, alpha=0.5, edge_color='g', style='dashed')