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/* $Id$Revision: */
/* vim:set shiftwidth=4 ts=8: */
/*************************************************************************
* Copyright (c) 2011 AT&T Intellectual Property
* All rights reserved. This program and the accompanying materials
* are made available under the terms of the Eclipse Public License v1.0
* which accompanies this distribution, and is available at
* http://www.eclipse.org/legal/epl-v10.html
*
* Contributors: See CVS logs. Details at http://www.graphviz.org/
*************************************************************************/
#ifndef MG_H
#define MG_H
typedef struct Multilevel_MQ_Clustering_struct *Multilevel_MQ_Clustering;
struct Multilevel_MQ_Clustering_struct {
int level;/* 0, 1, ... */
int n;
SparseMatrix A; /* n x n matrix */
SparseMatrix P;
SparseMatrix R;
Multilevel_MQ_Clustering next;
Multilevel_MQ_Clustering prev;
int delete_top_level_A;
int *matching; /* dimension n. matching[i] is the clustering assignment of node i */
/*
. |E(i,i)| |E(i,j)|
MQ/2 = (1/k) * \sum_{i=1...k} ------------ - (1/(k*(k-1))) * \sum_{i<j} -------------------
. |V(i)|^2 |V(i)|*|V(j)|
. = mq_in/k - mq_out/(k*(k-1))
*/
real mq;
real mq_in, mq_out;/* mqs(A) = deg_in(A)/|A|^2 - deg_out(A)/|A|/(|V|-|A|) */
int ncluster; /* number of clusters */
real *deg_intra;/* dimension n. deg[i] equal to the sum of edge weights within cluster i */
real *dout;/* dimension n, dout[i] = \sum_{j -- i} a(i,j)/|j| is the scaled sum of outdegree */
real *wgt; /* total vertex weight each coarse grid vertex represent */
};
/* find a clustering of vertices by maximize modularity quality
A: symmetric square matrix n x n. If real value, value will be used as edges weights, otherwise edge weights are considered as 1.
inplace: whether A can e modified. If true, A will be modified by removing diagonal.
maxcluster: used to specify the maximum number of cluster desired, e.g., maxcluster=10 means that a maximum of 10 clusters
. is desired. this may not always be realized, and modularity quality may be low when this is specified. Default: maxcluster = 0 (no limit)
use_value: whether to use the entry value, or treat edge weights as 1.
nclusters: on output the number of clusters
assignment: dimension n. Node i is assigned to cluster "assignment[i]". 0 <= assignment < nclusters.
. If *assignment = NULL on entry, it will be allocated. Otherwise used.
mq: achieve modularity
*/
void mq_clustering(SparseMatrix A, int inplace, int maxcluster, int use_value,
int *nclusters, int **assignment, real *mq, int *flag);
#endif
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