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 G,我希望能够在创建图 之后将一些权重分配给 G.edges() 。涉及的图有grids、erdos-reyni、barabasi-albert等。

鉴于我的 G.edges():

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

还有我的weights

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

如何为每条边分配相关权重?在这个简单的例子中,所有权重都是 1。

我试过像这样直接将权重添加到 G.edges()

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

但是我得到这个错误:

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-48-6119dc6b7af0> in <module>()
     10 
     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? 因为 G.edges() 是一个列表,为什么我不能像访问任何其他列表一样访问它的元素?

它失败了,因为 edges 是一个方法。

documentation 说要这样做:

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

例如,以下对我有用:

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,您的代码确实失败了:

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__'

对于你的情况,我建议

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

像这样添加边:

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

然后检查图形是否被加权:

nx.is_weighted(g1)

True

按大小对权重进行分类:

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:

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

节点

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

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')

来自docs

  • 您可以使用
  • 一次将所有边权重设置为相同的值
nx.set_edge_attributes(G, values = 1, name = 'weight')
  • 给定一个字典,其中的键对应于边元组(你的weights), 您可以使用
  • 将边权重分配给该字典中的值
nx.set_edge_attributes(G, values = weights, name = 'weight')
  • 查看并验证这些边缘属性是否已设置
G.edges(data = True)