CODEWITHSUNDEEP
python-3.xnetworkximdb
ninja coder
ninja coder

Reputation: 27

Differentiate/Partition between nodes of a graph to compute centrality measures in Python

I am using networkx package to analyse IMDb data to compute centrality(closeness and betweenness). Problem is, the graph has two types of nodes - namely, actors and movies. I want to calculate the centrality with respect to only the actors and not the graph overall.The data(it is subset of the main data

The code -

T = nx.Graph()
T.add_nodes_from(demo_df.primaryName,bipartite=1)
T.add_nodes_from(demo_df.primaryTitle,bipartite=0)
T = nx.from_pandas_edgelist(demo_df,'primaryName','primaryTitle')
nx.closeness_centrality(T)
nx.betweenness_centrality(T)

I don't want it to calculate/display the betweenness and closeness of the movies(Wings of Desire, Dopey Dicks, Studio Stoops). I want it to be calculated only for the actors.

I don't want it to calculate/display the betweenness and closeness of the movies(Wings of Desire, Dopey Dicks, Studio Stoops). I want it to be calculated only for the actors.

Upvotes: 0

Views: 336

Answers (1)

yatu
yatu

Reputation: 88246

For bipartite graphs, you have the networkx.algorithms.bipartite.centrality counterpart. For instance for the closeness_centrality the result will be a dictionary keyed by node with bipartite degree centrality as the value. In the nodes argument specify the nodes in one bipartite node set:

from networkx.algorithms import bipartite

part0_nodes, part1_nodes = bipartite.sets(T)
cs_partition0 = bipartite.centrality.closeness_centrality(T, part0_nodes)

For disconnected graphs, you may try obtaining the nodes from a given partition with:

partition = nx.get_node_attributes(T, 'bipartite')
part0_nodes = [node for node, p in partition.items() if p==0]

Note that the returned dictionary will still contain all nodes even though you've specified the nodes from one partition in nodes. So you can just keep those in just one set using part0_nodes. This is mentioned in the notes section:

The nodes input parameter must contain all nodes in one bipartite node set, but the dictionary returned contains all nodes from both bipartite node sets. See :mod:bipartite documentation <networkx.algorithms.bipartite> for further details on how bipartite graphs are handled in NetworkX.

Upvotes: 1

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