001/*
002 * Copyright 2006 - 2013
003 *     Stefan Balev     <stefan.balev@graphstream-project.org>
004 *     Julien Baudry    <julien.baudry@graphstream-project.org>
005 *     Antoine Dutot    <antoine.dutot@graphstream-project.org>
006 *     Yoann Pigné      <yoann.pigne@graphstream-project.org>
007 *     Guilhelm Savin   <guilhelm.savin@graphstream-project.org>
008 * 
009 * This file is part of GraphStream <http://graphstream-project.org>.
010 * 
011 * GraphStream is a library whose purpose is to handle static or dynamic
012 * graph, create them from scratch, file or any source and display them.
013 * 
014 * This program is free software distributed under the terms of two licenses, the
015 * CeCILL-C license that fits European law, and the GNU Lesser General Public
016 * License. You can  use, modify and/ or redistribute the software under the terms
017 * of the CeCILL-C license as circulated by CEA, CNRS and INRIA at the following
018 * URL <http://www.cecill.info> or under the terms of the GNU LGPL as published by
019 * the Free Software Foundation, either version 3 of the License, or (at your
020 * option) any later version.
021 * 
022 * This program is distributed in the hope that it will be useful, but WITHOUT ANY
023 * WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
024 * PARTICULAR PURPOSE.  See the GNU Lesser General Public License for more details.
025 * 
026 * You should have received a copy of the GNU Lesser General Public License
027 * along with this program.  If not, see <http://www.gnu.org/licenses/>.
028 * 
029 * The fact that you are presently reading this means that you have had
030 * knowledge of the CeCILL-C and LGPL licenses and that you accept their terms.
031 */
032package org.graphstream.algorithm;
033
034import org.apache.commons.math3.linear.Array2DRowRealMatrix;
035import org.apache.commons.math3.linear.EigenDecomposition;
036import org.apache.commons.math3.linear.RealMatrix;
037import org.graphstream.algorithm.generator.BarabasiAlbertGenerator;
038import org.graphstream.graph.Edge;
039import org.graphstream.graph.Graph;
040import org.graphstream.graph.implementations.AdjacencyListGraph;
041
042public class Spectrum implements Algorithm {
043
044        public static enum EigenValuesAlgorithm {
045                POWER_ITERATION, INVERSE_ITERATION
046        }
047
048        protected EigenValuesAlgorithm mode;
049        protected Graph graph;
050        protected EigenDecomposition decomposition;
051
052        /*
053         * (non-Javadoc)
054         * 
055         * @see
056         * org.graphstream.algorithm.Algorithm#init(org.graphstream.graph.Graph)
057         */
058        public void init(Graph graph) {
059                if (graph == null)
060                        throw new NullPointerException();
061
062                this.graph = graph;
063        }
064
065        /*
066         * (non-Javadoc)
067         * 
068         * @see org.graphstream.algorithm.Algorithm#compute()
069         */
070        public void compute() {
071                if (graph == null)
072                        throw new NotInitializedException(this);
073
074                int m = graph.getNodeCount();
075                RealMatrix a = new Array2DRowRealMatrix(m, m);
076                Edge e;
077
078                for (int idx1 = 0; idx1 < m; idx1++)
079                        for (int idx2 = 0; idx2 < m; idx2++) {
080                                e = graph.getNode(idx1).getEdgeToward(idx2);
081                                a.setEntry(idx1, idx2, e != null ? 1 : 0);
082                        }
083
084                decomposition = new EigenDecomposition(a, 0);
085        }
086
087        public int getEigenvaluesCount() {
088                double[] values = decomposition.getRealEigenvalues();
089                return values == null ? 0 : values.length;
090        }
091
092        public double getEigenvalue(int i) {
093                return decomposition.getRealEigenvalue(i);
094        }
095
096        public double[] getEigenvalues() {
097                return decomposition.getRealEigenvalues();
098        }
099        
100        public double[] getEigenvector(int i) {
101                return decomposition.getEigenvector(i).toArray();
102        }
103
104        public double getLargestEigenvalue() {
105                double[] values = decomposition.getRealEigenvalues();
106                double max = Double.MIN_VALUE;
107
108                if (values != null)
109                        for (int i = 0; i < values.length; i++)
110                                max = Math.max(max, values[i]);
111
112                return max;
113        }
114
115        public static void main(String... args) {
116                Graph g = new AdjacencyListGraph("g");
117
118                BarabasiAlbertGenerator gen = new BarabasiAlbertGenerator();
119                gen.addSink(g);
120                gen.begin();
121                for (int i = 0; i < 200; i++)
122                        gen.nextEvents();
123                gen.end();
124
125                Spectrum spectrum = new Spectrum();
126                spectrum.init(g);
127                spectrum.compute();
128
129        }
130}