Package org.ejml.alg.dense.decomposition.chol

Source Code of org.ejml.alg.dense.decomposition.chol.StabilityCholeksyDecomposition

/*
* Copyright (c) 2009-2012, Peter Abeles. All Rights Reserved.
*
* This file is part of Efficient Java Matrix Library (EJML).
*
* EJML 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 3
* of the License, or (at your option) any later version.
*
* EJML 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 EJML.  If not, see <http://www.gnu.org/licenses/>.
*/

package org.ejml.alg.dense.decomposition.chol;

import org.ejml.EjmlParameters;
import org.ejml.data.DenseMatrix64F;
import org.ejml.factory.CholeskyDecomposition;
import org.ejml.factory.DecompositionFactory;
import org.ejml.ops.CommonOps;
import org.ejml.ops.RandomMatrices;
import org.ejml.simple.SimpleMatrix;

import java.util.Random;


/**
* Compare the speed of various algorithms at inverting square matrices
*
* @author Peter Abeles
*/
public class StabilityCholeksyDecomposition {


    public static double evaluate( CholeskyDecomposition<DenseMatrix64F> alg , DenseMatrix64F orig ) {

        if( !DecompositionFactory.decomposeSafe(alg,orig)) {
            return Double.NaN;
        }

        SimpleMatrix T = SimpleMatrix.wrap(alg.getT(null));

        SimpleMatrix A_found = T.mult(T.transpose());
        SimpleMatrix A = SimpleMatrix.wrap(orig);

        double top = A_found.minus(A).normF();
        double bottom = A.normF();

        return top/bottom;
    }

    private static void runAlgorithms( DenseMatrix64F mat  )
    {
        System.out.println("basic             = "+ evaluate(new CholeskyDecompositionInner(),mat));
        System.out.println("block             = "+ evaluate(new CholeskyDecompositionBlock(EjmlParameters.BLOCK_WIDTH_CHOL),mat));
        System.out.println("block64           = "+ evaluate(new CholeskyDecompositionBlock64(true),mat));

    }

    public static void main( String args [] ) {
        Random rand = new Random(23423);

        EjmlParameters.BLOCK_SIZE = 5;

        for( int size = 5; size <= 15; size += 5 ) {
            double scales[] = new double[]{1,0.1,1e-20,1e-100,1e-200,1e-300,1e-304,1e-308,1e-319,1e-320,1e-321,Double.MIN_VALUE};

            // results vary significantly depending if it starts from a small or large matrix
            for( int i = 0; i < scales.length; i++ ) {
                System.out.printf("Decomposition size %3d for %e scale\n",size,scales[i]);
                DenseMatrix64F mat = RandomMatrices.createSymmPosDef(size,rand);
                CommonOps.scale(scales[i],mat);
                runAlgorithms(mat);
            }
        }
        System.out.println("  Done.");
    }
}
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