具有随机幂律分布权重的网络

Question

如何将幂律分布中的权重随机分配给具有大量节点的网络.

我写

import networkx as nx
import numpy as np
from networkx.utils import powerlaw_sequence

z=nx.utils.create_degree_sequence(200,nx.utils.powerlaw_sequence,exponent=1.9)
nx.is_valid_degree_sequence(z) 
G=nx.configuration_model(z)
Gcc=nx.connected_component_subgraphs(G)[0]

edgelist=[nx.utils.powerlaw_sequence(nx.number_of_edges(Gcc),exponent=2.0)]

我知道我使用以下方法通过元组字典(node1,node2,weight)为边缘分配权重:

nx.from_edgelist(edgelist,create_using=None)

但是当我只想获得权重是幂律分布的加权网络时,还有另一种更短的方法吗？

Answer 1

您可以直接使用 G[u][v]['weight'] 分配权重，例如

In [1]: import networkx as nx

In [2]: import random

In [3]: G = nx.path_graph(10)

In [4]: for u,v in G.edges():
   ...:     G[u][v]['weight'] = random.paretovariate(2)
   ...:     
   ...:     

In [5]: print G.edges(data=True)
[(0, 1, {'weight': 1.6988521989583232}), (1, 2, {'weight': 1.0749963615177736}), (2, 3, {'weight': 1.1503859779558812}), (3, 4, {'weight': 1.675436575683888}), (4, 5, {'weight': 1.1948608572552846}), (5, 6, {'weight': 1.080152340891444}), (6, 7, {'weight': 1.0296667672332183}), (7, 8, {'weight': 2.0014384064255446}), (8, 9, {'weight': 2.2691612212058447})]

我使用 Python 的 random.paretovariate() 来选择权重，但当然，您可以将任何您想要的东西放在那里。