/* $Revision$ $Author$ $Date$
*
* Copyright (C) 2005-2007 Violeta Labarta <vlabarta@users.sf.net>
*
* Contact: cdk-devel@lists.sourceforge.net
*
* This program 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 2.1
* of the License, or (at your option) any later version.
* All we ask is that proper credit is given for our work, which includes
* - but is not limited to - adding the above copyright notice to the beginning
* of your source code files, and to any copyright notice that you may distribute
* with programs based on this work.
*
* This program 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 this program; if not, write to the Free Software
* Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA.
*/
package org.openscience.cdk.modeling.forcefield;
import javax.vecmath.GMatrix;
import javax.vecmath.GVector;
import org.openscience.cdk.tools.ILoggingTool;
import org.openscience.cdk.tools.LoggingToolFactory;
import Jama.Matrix;
/**
* Methods of Newton-Raphson approach.
*
* @author vlabarta
* @cdk.created 2005-06-01
* @cdk.module forcefield
* @cdk.githash
*
* @cdk.keyword Newton-Raphson
*/
public class NewtonRaphsonMethod {
GVector gradientPerInverseHessianVector = null;
Matrix matrixForDeterminatCalculation = null;
private static ILoggingTool logger =
LoggingToolFactory.createLoggingTool(NewtonRaphsonMethod.class);
/**
* Constructor for the NR object
*/
public NewtonRaphsonMethod() {
}
/**
* Calculate the eigen values for the hessian matrix.
*
*@param forMatrix Hessian matrix
*@param size coordinates dimension
*/
public void hessianEigenValues(double[] forMatrix, int size) {
Matrix A = new Matrix(forMatrix, size);
Matrix As = A.plus(A.transpose()); // Simetric matrix: As = 1/2 * (A + AT);
As.timesEquals(0.5);
//logger.debug("Simetric matrix Hs = 1/2 * (H + HT) = ");
//As.print(As.getRowDimension(), As.getColumnDimension());
double[] realEigenvalues = As.eig().getRealEigenvalues();
double[] imagEigenvalues = As.eig().getImagEigenvalues();
System.out.println(" ");
System.out.println("Hs EigenValues :");
for (int i=0; i < As.getColumnDimension(); i++) {
System.out.println("Eigen value " + i + ": real part = " + realEigenvalues[i]);
System.out.println(", imaginary part = " + imagEigenvalues[i]);
}
}
public void determinat(GVector gradientk, GMatrix hessiank) {
//logger.debug(" ");
//logger.debug("calculate hessian determinat: ");
double[][] forDeterminatCalculation = new double[gradientk.getSize()][];
for (int i = 0; i < gradientk.getSize(); i++) {
forDeterminatCalculation[i] = new double[gradientk.getSize()];
for (int j = 0; j < forDeterminatCalculation[i].length; j++) {
forDeterminatCalculation[i][j] = hessiank.getElement(i, j);
}
}
//logger.debug("gradientk.getSize() = " + gradientk.getSize());
/*
* if (gradientk.getSize() == 36) {
* logger.debug();
* for (int i = 0; i < forDeterminatCalculation.length; i++) {
* for (int j = 0; j < forDeterminatCalculation[i].length; j++) {
* logger.debug(forDeterminatCalculation[i][j] + " ");
* }
* logger.debug();
* }
* }
*/
matrixForDeterminatCalculation = new Matrix(forDeterminatCalculation);
//matrixForDeterminatCalculation.print(gradientk.getSize(), gradientk.getSize());
//logger.debug("matrixForDeterminatCalculation.det() = " + matrixForDeterminatCalculation.det());
return;
}
public void gradientPerInverseHessian(GVector gradientk, GMatrix hessiank) {
this.determinat(gradientk, hessiank);
if (matrixForDeterminatCalculation.det() != 0) {
hessiank.invert();
//logger.debug("hessiank.invert() = " + hessiank);
gradientPerInverseHessianVector = new GVector(gradientk.getSize());
gradientPerInverseHessianVector.mul(gradientk, hessiank);
} else {
logger.debug("The Newton-Raphson method can't be execute because the hessian can't be inverted");
}
return;
}
/**
* Gets the gradientPerInverseHessian attribute of the NewtonRaphsonMethod
* object
*
*@return The gradientPerInverseHessian value
*/
public GVector getGradientPerInverseHessian() {
return gradientPerInverseHessianVector;
}
}