Example usage for org.apache.commons.math3.linear QRDecomposition getH

Introduction

In this page you can find the example usage for org.apache.commons.math3.linear QRDecomposition getH.

Prototype

public RealMatrix getH() 

Source Link

Document

Returns the Householder reflector vectors.

Usage

From source file:com.ibm.bi.dml.runtime.matrix.data.LibCommonsMath.java

/**
 * Function to perform QR decomposition on a given matrix.
 * //from   w  ww  .j a v a  2s.co  m
 * @param in
 * @return
 * @throws DMLRuntimeException
 */
private static MatrixBlock[] computeQR(MatrixObject in) throws DMLRuntimeException {
    Array2DRowRealMatrix matrixInput = DataConverter.convertToArray2DRowRealMatrix(in);

    // Perform QR decomposition
    QRDecomposition qrdecompose = new QRDecomposition(matrixInput);
    RealMatrix H = qrdecompose.getH();
    RealMatrix R = qrdecompose.getR();

    // Read the results into native format
    MatrixBlock mbH = DataConverter.convertToMatrixBlock(H.getData());
    MatrixBlock mbR = DataConverter.convertToMatrixBlock(R.getData());

    return new MatrixBlock[] { mbH, mbR };
}

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From source file:com.joptimizer.algebra.QRSparseFactorizationTest.java

public void testDecompose() throws Exception {
    log.debug("testDecompose");
    final double[][] A = new double[][] { { 1, 0, 0, 2 }, { 0, 0, 2, 0 }, { 2, 3, 0, 0 }, { 0, 0, 4, 4 } };

    double[][] EQ = { { 0.447214, -0.894427, 0., 0. }, { 0., 0., 0.447214, -0.894427 },
            { 0.894427, 0.447214, 0., 0. }, { 0., 0., 0.894427, 0.447214 } };
    double[][] ER = { { 2.23607, 2.68328, 0., 0.894427 }, { 0., 1.34164, 0., -1.78885 },
            { 0., 0., 4.47214, 3.57771 }, { 0., 0., 0., 1.78885 } };

    QRDecomposition dFact = new QRDecomposition(new Array2DRowRealMatrix(A));
    RealMatrix Q = dFact.getQ();/*from w  w  w.j ava 2 s  . c o m*/
    RealMatrix R = dFact.getR();
    RealMatrix H = dFact.getH();
    log.debug("Q: " + ArrayUtils.toString(Q.getData()));
    log.debug("R: " + ArrayUtils.toString(R.getData()));
    //log.debug("H: " + ArrayUtils.toString(H.getData()));

    SparseDoubleMatrix2D S = new SparseDoubleMatrix2D(A);
    QRSparseFactorization qr = new QRSparseFactorization(S);
    qr.factorize();
    log.debug("R: " + ArrayUtils.toString(qr.getR().toArray()));
    for (int i = 0; i < R.getRowDimension(); i++) {
        for (int j = 0; j < R.getColumnDimension(); j++) {
            assertEquals(ER[i][j], qr.getR().getQuick(i, j), 1.e-5);
        }
    }
    assertTrue(qr.hasFullRank());
}

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