Examples of SymmetricQRAlgorithmDecomposition

mikera.matrixx.decompose.impl.eigen.SymmetricQRAlgorithmDecomposition

Computes the eigenvalues and eigenvectors of a real symmetric matrix using the symmetric implicit QR algorithm. Inside each iteration a QR decomposition of A_i-p_iI is implicitly computed.

This implementation is based on the algorithm is sketched out in:
David S. Watkins, "Fundamentals of Matrix Computations," Second Edition. page 377-385
@author Peter Abeles
org.ejml.alg.dense.decomposition.eig.SymmetricQRAlgorithmDecomposition

Computes the eigenvalues and eigenvectors of a real symmetric matrix using the symmetric implicit QR algorithm. Inside each iteration a QR decomposition of A_i-p_iI is implicitly computed.

This implementation is based on the algorithm is sketched out in:
David S. Watkins, "Fundamentals of Matrix Computations," Second Edition. page 377-385
@see org.ejml.alg.dense.decomposition.eig.symm.SymmetricQrAlgorithm @see org.ejml.alg.dense.decomposition.hessenberg.TridiagonalDecompositionHouseholder @author Peter Abeles

Examples of mikera.matrixx.decompose.impl.eigen.SymmetricQRAlgorithmDecomposition

     * @param A The input matrix. It must be a square symmetric matrix.
     * @param computeVectors Should it compute the eigenvectors or just eigenvalues.
     * @return an IEigenResult object that represents the solution to the decomposition.
     */
    public static IEigenResult decomposeSymmetric(AMatrix A, boolean computeVectors) {
        SymmetricQRAlgorithmDecomposition alg = new SymmetricQRAlgorithmDecomposition(computeVectors);
        return alg.decompose(A);
    }

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Examples of org.ejml.alg.dense.decomposition.eig.SymmetricQRAlgorithmDecomposition

     */
    public static EigenDecomposition<DenseMatrix64F> eig( int matrixSize , boolean computeVectors ,
                                                          boolean isSymmetric ) {
        if( isSymmetric ) {
            TridiagonalSimilarDecomposition<DenseMatrix64F> decomp = DecompositionFactory.tridiagonal(matrixSize);
            return new SymmetricQRAlgorithmDecomposition(decomp,computeVectors);
        } else
            return new WatchedDoubleStepQRDecomposition(computeVectors);
    }

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Examples of org.ejml.alg.dense.decomposition.eig.SymmetricQRAlgorithmDecomposition

    }


    private static void runAlgorithms( DenseMatrix64F mat  )
    {
        TridiagonalSimilarDecomposition<DenseMatrix64F> decomp = DecompositionFactory.tridiagonal(0);
        System.out.println("qr ult           = "+ evaluate(new SymmetricQRAlgorithmDecomposition(decomp,true),mat));
    }

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Examples of org.ejml.alg.dense.decomposition.eig.SymmetricQRAlgorithmDecomposition

    public static long symmTogether( DenseMatrix64F orig , int numTrials ) {


        long prev = System.currentTimeMillis();


        TridiagonalSimilarDecomposition<DenseMatrix64F> decomp =  DecompositionFactory.tridiagonal(orig.numRows);
        SymmetricQRAlgorithmDecomposition alg = new SymmetricQRAlgorithmDecomposition(decomp,true);


        alg.setComputeVectorsWithValues(true);


        for( long i = 0; i < numTrials; i++ ) {
            if( !DecompositionFactory.decomposeSafe(alg,orig) ) {
                throw new RuntimeException("Bad matrix");
            }

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Examples of org.ejml.alg.dense.decomposition.eig.SymmetricQRAlgorithmDecomposition

    public static long symmSeparate( DenseMatrix64F orig , int numTrials ) {


        long prev = System.currentTimeMillis();


        TridiagonalSimilarDecomposition<DenseMatrix64F> decomp =  DecompositionFactory.tridiagonal(orig.numRows);
        SymmetricQRAlgorithmDecomposition alg = new SymmetricQRAlgorithmDecomposition(decomp,true);


        alg.setComputeVectorsWithValues(false);


        for( long i = 0; i < numTrials; i++ ) {
            if( !DecompositionFactory.decomposeSafe(alg,orig) ) {
                throw new RuntimeException("Bad matrix");
            }

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Examples of org.ejml.alg.dense.decomposition.eig.SymmetricQRAlgorithmDecomposition

        return System.currentTimeMillis() - prev;
    }


    public static long standardTridiag( DenseMatrix64F orig , int numTrials ) {
        TridiagonalSimilarDecomposition<DenseMatrix64F> decomp = new TridiagonalDecompositionHouseholder();
        SymmetricQRAlgorithmDecomposition alg = new SymmetricQRAlgorithmDecomposition(decomp,true);


        long prev = System.currentTimeMillis();


        for( long i = 0; i < numTrials; i++ ) {
            if( !DecompositionFactory.decomposeSafe(alg,orig) ) {

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Examples of org.ejml.alg.dense.decomposition.eig.SymmetricQRAlgorithmDecomposition

    }


    public static long blockTridiag( DenseMatrix64F orig , int numTrials ) {


        TridiagonalSimilarDecomposition<DenseMatrix64F> decomp = new TridiagonalDecompositionBlock();
        SymmetricQRAlgorithmDecomposition alg = new SymmetricQRAlgorithmDecomposition(decomp,true);


        long prev = System.currentTimeMillis();


        for( long i = 0; i < numTrials; i++ ) {
            if( !DecompositionFactory.decomposeSafe(alg,orig) ) {

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