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This documents an unmaintained version of NetworkX. Please upgrade to a maintained version and see the current NetworkX documentation.

# Source code for networkx.algorithms.centrality.degree_alg

```
"""
Degree centrality measures.
"""
# Copyright (C) 2004-2010 by
# Aric Hagberg <hagberg@lanl.gov>
# Dan Schult <dschult@colgate.edu>
# Pieter Swart <swart@lanl.gov>
# All rights reserved.
# BSD license.
__author__ = "\n".join(['Aric Hagberg (hagberg@lanl.gov)',
'Pieter Swart (swart@lanl.gov)',
'Sasha Gutfraind (ag362@cornell.edu)'])
__all__ = ['degree_centrality',
'in_degree_centrality',
'out_degree_centrality']
import networkx as nx
[docs]def degree_centrality(G):
"""Compute the degree centrality for nodes.
The degree centrality for a node v is the fraction of nodes it
is connected to.
Parameters
----------
G : graph
A networkx graph
Returns
-------
nodes : dictionary
Dictionary of nodes with degree centrality as the value.
See Also
--------
betweenness_centrality, load_centrality, eigenvector_centrality
Notes
-----
The degree centrality values are normalized by dividing by the maximum
possible degree in a simple graph n-1 where n is the number of nodes in G.
For multigraphs or graphs with self loops the maximum degree might
be higher than n-1 and values of degree centrality greater than 1
are possible.
"""
centrality={}
s=1.0/(len(G)-1.0)
centrality=dict((n,d*s) for n,d in G.degree_iter())
return centrality
[docs]def in_degree_centrality(G):
"""Compute the in-degree centrality for nodes.
The in-degree centrality for a node v is the fraction of nodes its
incoming edges are connected to.
Parameters
----------
G : graph
A NetworkX graph
Returns
-------
nodes : dictionary
Dictionary of nodes with in-degree centrality as values.
See Also
--------
degree_centrality, out_degree_centrality
Notes
-----
The degree centrality values are normalized by dividing by the maximum
possible degree in a simple graph n-1 where n is the number of nodes in G.
For multigraphs or graphs with self loops the maximum degree might
be higher than n-1 and values of degree centrality greater than 1
are possible.
"""
if not G.is_directed():
raise nx.NetworkXError(\
"in_degree_centrality() not defined for undirected graphs.")
centrality={}
s=1.0/(len(G)-1.0)
centrality=dict((n,d*s) for n,d in G.in_degree_iter())
return centrality
[docs]def out_degree_centrality(G):
"""Compute the out-degree centrality for nodes.
The out-degree centrality for a node v is the fraction of nodes its
outgoing edges are connected to.
Parameters
----------
G : graph
A NetworkX graph
Returns
-------
nodes : dictionary
Dictionary of nodes with out-degree centrality as values.
See Also
--------
degree_centrality, in_degree_centrality
Notes
-----
The degree centrality values are normalized by dividing by the maximum
possible degree in a simple graph n-1 where n is the number of nodes in G.
For multigraphs or graphs with self loops the maximum degree might
be higher than n-1 and values of degree centrality greater than 1
are possible.
"""
if not G.is_directed():
raise nx.NetworkXError(\
"out_degree_centrality() not defined for undirected graphs.")
centrality={}
s=1.0/(len(G)-1.0)
centrality=dict((n,d*s) for n,d in G.out_degree_iter())
return centrality
```