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我想在高度互连的网络中选择并打印三个节点的路径。从给定节点开始，该函数应选择具有最高度中心性的相邻节点作为第二个节点。

在平局的情况下，我想让程序在这些节点之间随机选择。

这是我到目前为止所拥有的：

import networkx as nx
from random import choice
g =nx.Graph()
g.add_nodes_from(range(1,5))
g.add_edges_from([(1,5),(2,5),(3,5),(4,5), (1,2),(2,3),(3,4),(4,5)])

nx.set_node_attributes(g,'degree_cent',nx.degree_centrality(g))
degree_walk =[]                 

node1=g.nodes()[2]
degree_walk.append(node1)
for node2 in g.neighbors(node1):
    if max(g.node[node2]['degree_cent'],  g.node[node2]['degree_cent'].get):
            node2 = choice(g.neighbors(node1))
            degree_walk.append(node2)
print degree_walk
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1 回答 1

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给你（灵感来自this SO answer on find key value of max value of dictionary）：

# Find all the neighbors with maximum centrality:
highest_centrality = max([g.node[n]['degree_cent'] 
                          for n in g.neighbors(node1)) 
most_central_neighbors = [n for n in g.nodes() 
                          if g.node[n]['degree_cent'] == highest_centrality]
# Pick one at random:
random_central_neighbor = choice([most_central_neighbors])
# Add it to the list:
degree_walk.append(random_central_neighbor)
print degree_walk

请注意，如果您不关心领带（并且很乐意按照原始列表的顺序接受第一个），您可以执行以下操作：

# Find all the neighbors with maximum centrality:
most_central_neighbors = max(g.neighbors(node1), 
                             key=lambda(n): g.node[n]['degree_cent'])
于 2014-02-25T15:07:42.073 回答