1/* $Id$Revision: */
2/* vim:set shiftwidth=4 ts=8: */
3
4/*************************************************************************
5 * Copyright (c) 2011 AT&T Intellectual Property
6 * All rights reserved. This program and the accompanying materials
7 * are made available under the terms of the Eclipse Public License v1.0
8 * which accompanies this distribution, and is available at
9 * http://www.eclipse.org/legal/epl-v10.html
10 *
11 * Contributors: See CVS logs. Details at http://www.graphviz.org/
12 *************************************************************************/
13
14#ifndef CLUSTERING_H
15#define CLUSTERING_H
16
17typedef struct Multilevel_Modularity_Clustering_struct *Multilevel_Modularity_Clustering;
18
19struct Multilevel_Modularity_Clustering_struct {
20 int level;/* 0, 1, ... */
21 int n;
22 SparseMatrix A; /* n x n matrix */
23 SparseMatrix P;
24 SparseMatrix R;
25 Multilevel_Modularity_Clustering next;
26 Multilevel_Modularity_Clustering prev;
27 int delete_top_level_A;
28 int *matching; /* dimension n. matching[i] is the clustering assignment of node i */
29 real modularity;
30 real deg_total; /* total edge weights, including self-edges */
31 real *deg;/* dimension n. deg[i] equal to the sum of edge weights connected to vertex i. I.e., sum of row i */
32 int agglomerate_regardless;/* whether to agglomerate nodes even if this causes modularity reduction. This is used if we want to force
33 agglomeration so as to get less clusters
34 */
35
36
37};
38
39enum {CLUSTERING_MODULARITY = 0, CLUSTERING_MQ};
40
41/* find a clustering of vertices by maximize modularity
42 A: symmetric square matrix n x n. If real value, value will be used as edges weights, otherwise edge weights are considered as 1.
43 inplace: whether A can e modified. If true, A will be modified by removing diagonal.
44
45 maxcluster: used to specify the maximum number of cluster desired, e.g., maxcluster=10 means that a maximum of 10 clusters
46 . is desired. this may not always be realized, and modularity may be low when this is specified. Default: maxcluster = 0 (no limit)
47
48 use_value: whether to use the entry value, or treat edge weights as 1.
49 nclusters: on output the number of clusters
50 assignment: dimension n. Node i is assigned to cluster "assignment[i]". 0 <= assignment < nclusters.
51 . If *assignment = NULL on entry, it will be allocated. Otherwise used.
52 modularity: achieve modularity
53*/
54void modularity_clustering(SparseMatrix A, int inplace, int maxcluster, int use_value,
55 int *nclusters, int **assignment, real *modularity, int *flag);
56
57#endif
58