1
我正在使用引用网络,我想计算随机游走访问网络中任何其他节点的给定节点的概率的总和。我的理解是,currentflow_betweeness_centrality是度量类似于这样的想法,但它似乎不直接grpahs工作:使用networkx定向图的current_flow_betweenness_centrality?
import networkx as nx
import pandas as pd
df = pd.read_csv(open("PATH TO CSV","rb"))
DG = nx.DiGraph()
DG.add_edges_from(zip(df.citing.values, df.cited.values))
largest_component = nx.weakly_connected_component_subgraphs(DG)[0]
random_walk = nx.current_flow_betweenness_centrality(largest_component)
由于outout,我得到:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "/Library/Frameworks/EPD64.framework/Versions/7.3/lib/python2.7/site-packages/networkx/algorithms/centrality/current_flow_betweenness.py", line 223, in current_flow_betweenness_centrality
'not defined for digraphs.')
networkx.exception.NetworkXError: ('current_flow_betweenness_centrality() ', 'not defined for digraphs.')
如何任何想法为什么这个限制存在?