/* * EigenDecomposition.java * * Copyright (c) 2002-2015 Alexei Drummond, Andrew Rambaut and Marc Suchard * * This file is part of BEAST. * See the NOTICE file distributed with this work for additional * information regarding copyright ownership and licensing. * * BEAST is free software; you can redistribute it and/or modify * it under the terms of the GNU Lesser General Public License as * published by the Free Software Foundation; either version 2 * of the License, or (at your option) any later version. * * BEAST 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 Lesser General Public License for more details. * * You should have received a copy of the GNU Lesser General Public * License along with BEAST; if not, write to the * Free Software Foundation, Inc., 51 Franklin St, Fifth Floor, * Boston, MA 02110-1301 USA */ package dr.evomodel.substmodel; import java.io.Serializable; /** * @author Andrew Rambaut * @author Alexei Drummond * @Author Marc A. Suchard * @version $Id$ */ public class EigenDecomposition implements Serializable { public EigenDecomposition(double[] evec, double[] ievc, double[] eval) { Evec = evec; Ievc = ievc; Eval = eval; } public EigenDecomposition copy() { double[] evec = Evec.clone(); double[] ievc = Ievc.clone(); double[] eval = Eval.clone(); return new EigenDecomposition(evec, ievc, eval); } /** * This function returns the Eigen vectors. * @return the array */ public final double[] getEigenVectors() { return Evec; } /** * This function returns the inverse Eigen vectors. * @return the array */ public final double[] getInverseEigenVectors() { return Ievc; } /** * This function returns the Eigen values. * @return the Eigen values */ public final double[] getEigenValues() { return Eval; } /** * This function returns the normalization factor * @return normalization factor */ public final double getNormalization() { return normalization; } /** * This function rescales the eigen values; this is more stable than * rescaling the original Q matrix, also O(stateCount) instead of O(stateCount^2) */ public void normalizeEigenValues(double scale) { this.normalization = scale; int dim = Eval.length; for (int i = 0; i < dim; i++) { Eval[i] /= scale; } } // Eigenvalues, eigenvectors, and inverse eigenvectors private final double[] Evec; private final double[] Ievc; private final double[] Eval; private double normalization = 1.0; }