/*
* 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;
}