For using igraph from Python
Home  Trees  Indices  Help 



Classes related to graph clustering.
License: Copyright (C) 20062012 Tamás Nepusz <ntamas@gmail.com> Pázmány Péter sétány 1/a, 1117 Budapest, Hungary This program is free software; you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation; either version 2 of the License, or (at your option) any later version. This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program; if not, write to the Free Software Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 021101301 USA


Clustering Class representing a clustering of an arbitrary ordered set. 

VertexClustering The clustering of the vertex set of a graph. 

Dendrogram The hierarchical clustering (dendrogram) of some dataset. 

VertexDendrogram The dendrogram resulting from the hierarchical clustering of the vertex set of a graph. 

Cover Class representing a cover of an arbitrary ordered set. 

VertexCover The cover of the vertex set of a graph. 

CohesiveBlocks The cohesive block structure of a graph. 







__package__ =

Imports: deepcopy, izip, pi, StringIO, community_to_membership, property, Configuration, UniqueIdGenerator, ClusterColoringPalette, Histogram, _get_wrapper_for_width, str_to_orientation

Compares two community structures using various distance measures.
Reference:

Calculates the splitjoin distance between two community structures. The splitjoin distance is a distance measure defined on the space of partitions of a given set. It is the sum of the projection distance of one partition from the other and vice versa, where the projection number of A from B is if calculated as follows:
Note that the projection distance is asymmetric, that's why it has to
be calculated in both directions and then added together. This function
returns the projection distance of
Reference: van Dongen D: Performance criteria for graph clustering and Markov cluster experiments. Technical Report INSR0012, National Research Institute for Mathematics and Computer Science in the Netherlands, Amsterdam, May 2000. See Also:
compare_communities() with 
Home  Trees  Indices  Help 


Generated by Epydoc 3.0.1 on Fri May 10 10:51:13 2019  http://epydoc.sourceforge.net 