141 lines
3.5 KiB
Python
141 lines
3.5 KiB
Python
# Copyright (C) 2004-2019 by
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# Aric Hagberg <hagberg@lanl.gov>
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# Dan Schult <dschult@colgate.edu>
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# Pieter Swart <swart@lanl.gov>
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# All rights reserved.
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# BSD license.
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#
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# Authors: Aric Hagberg (hagberg@lanl.gov)
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# Pieter Swart (swart@lanl.gov)
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# Sasha Gutfraind (ag362@cornell.edu)
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"""Degree centrality measures."""
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import networkx as nx
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from networkx.utils.decorators import not_implemented_for
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__all__ = ['degree_centrality',
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'in_degree_centrality',
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'out_degree_centrality']
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def degree_centrality(G):
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"""Compute the degree centrality for nodes.
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The degree centrality for a node v is the fraction of nodes it
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is connected to.
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Parameters
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----------
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G : graph
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A networkx graph
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Returns
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-------
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nodes : dictionary
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Dictionary of nodes with degree centrality as the value.
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See Also
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--------
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betweenness_centrality, load_centrality, eigenvector_centrality
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Notes
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-----
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The degree centrality values are normalized by dividing by the maximum
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possible degree in a simple graph n-1 where n is the number of nodes in G.
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For multigraphs or graphs with self loops the maximum degree might
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be higher than n-1 and values of degree centrality greater than 1
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are possible.
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"""
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if len(G) <= 1:
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return {n: 1 for n in G}
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s = 1.0 / (len(G) - 1.0)
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centrality = {n: d * s for n, d in G.degree()}
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return centrality
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@not_implemented_for('undirected')
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def in_degree_centrality(G):
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"""Compute the in-degree centrality for nodes.
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The in-degree centrality for a node v is the fraction of nodes its
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incoming edges are connected to.
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Parameters
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----------
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G : graph
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A NetworkX graph
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Returns
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-------
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nodes : dictionary
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Dictionary of nodes with in-degree centrality as values.
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Raises
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------
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NetworkXNotImplemented:
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If G is undirected.
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See Also
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--------
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degree_centrality, out_degree_centrality
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Notes
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-----
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The degree centrality values are normalized by dividing by the maximum
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possible degree in a simple graph n-1 where n is the number of nodes in G.
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For multigraphs or graphs with self loops the maximum degree might
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be higher than n-1 and values of degree centrality greater than 1
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are possible.
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"""
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if len(G) <= 1:
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return {n: 1 for n in G}
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s = 1.0 / (len(G) - 1.0)
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centrality = {n: d * s for n, d in G.in_degree()}
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return centrality
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@not_implemented_for('undirected')
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def out_degree_centrality(G):
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"""Compute the out-degree centrality for nodes.
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The out-degree centrality for a node v is the fraction of nodes its
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outgoing edges are connected to.
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Parameters
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----------
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G : graph
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A NetworkX graph
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Returns
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-------
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nodes : dictionary
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Dictionary of nodes with out-degree centrality as values.
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Raises
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------
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NetworkXNotImplemented:
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If G is undirected.
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See Also
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--------
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degree_centrality, in_degree_centrality
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Notes
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-----
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The degree centrality values are normalized by dividing by the maximum
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possible degree in a simple graph n-1 where n is the number of nodes in G.
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For multigraphs or graphs with self loops the maximum degree might
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be higher than n-1 and values of degree centrality greater than 1
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are possible.
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"""
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if len(G) <= 1:
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return {n: 1 for n in G}
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s = 1.0 / (len(G) - 1.0)
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centrality = {n: d * s for n, d in G.out_degree()}
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return centrality
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