Examples of org.ejml.factory.EigenDecomposition

org.ejml.factory.EigenDecomposition

This is a generic interface for computing the eigenvalues and eigenvectors of a matrix. Eigenvalues and eigenvectors have the following property:

A*v=λ*v

where A is a square matrix and v is an eigenvector associated with the eigenvalue λ.

In general, both eigenvalues and eigenvectors can be complex numbers. For symmetric matrices the eigenvalues and eigenvectors are always real numbers. EJML does not support complex matrices but it does have minimal support for complex numbers. As a result complex eigenvalues are found, but only the real eigenvectors are computed.

To create a new instance of {@link EigenDecomposition} use {@link DecompositionFactory}. If the matrix is known to be symmetric be sure to use the symmetric decomposition, which is much faster and more accurate than the general purpose one.
@author Peter Abeles

        checkSymmetricMatrix(alg,1,1,1,2);
    }


    public void checkWithSingularSymm() {


        EigenDecomposition alg = createDecomposition();


        checkSymmetricMatrix(alg,1,0,1,2);
    }

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    }


    public void checkSmallValue( boolean symmetric) {


//        System.out.println("Symmetric = "+symmetric);
        EigenDecomposition alg = createDecomposition();


        for( int i = 0; i < 20; i++ ) {
            DenseMatrix64F A = symmetric ?
                    RandomMatrices.createSymmetric(4,-1,1,rand) :
                    RandomMatrices.createRandom(4,4,-1,1,rand);

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        }
    }


    public void checkLargeValue( boolean symmetric) {


        EigenDecomposition alg = createDecomposition();


        for( int i = 0; i < 20; i++ ) {
            DenseMatrix64F A = symmetric ?
                    RandomMatrices.createSymmetric(4,-1,1,rand) :
                    RandomMatrices.createRandom(4,4,-1,1,rand);

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        System.out.println("done");
    }


    public void checkRandomMatrices( int N ) {
        System.out.println("N = "+N);
        EigenDecomposition decomp = DecompositionFactory.eig(N,true);


        DenseMatrix64F A = new DenseMatrix64F(N,N);


        for( int i = 0; i < 1000; i++ ) {
            long seed = rand.nextLong();
            System.out.print("Date = "+new Date()+" Seed = "+seed);


            Random localRand = new Random(seed);


            RandomMatrices.createSymmetric(A,-1,1,localRand);


            if( !decomp.decompose(A) ) {
                System.out.println("Decomposition failed");
                return;
            }


            double error = DecompositionFactory.quality(A,decomp);

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Related Classes of org.ejml.factory.EigenDecomposition

org.ejml.alg.dense.decomposition.eig.GeneralEigenDecompositionCheck

org.ejml.alg.dense.decomposition.eig.symm.SymmetricEigenStressTest

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