Examples of org.apache.commons.math.linear.QRDecomposition

org.apache.commons.math.linear.QRDecomposition
nist.gov/javanumerics/jama/">JAMA library, with the following changes:
- a {@link #getQT() getQT} method has been added,
- the solve and isFullRank methods have been replaced by a {@link #getSolver() getSolver} method and the equivalent methods provided bythe returned {@link DecompositionSolver}.
@see MathWorld @see Wikipedia @version $Revision: 826627 $ $Date: 2009-10-19 12:27:47 +0200 (lun. 19 oct. 2009) $ @since 1.2

        }
    }


    /** test solve */
    public void testSolve() {
        QRDecomposition decomposition =
            new QRDecompositionImpl(MatrixUtils.createRealMatrix(testData3x3NonSingular));
        DecompositionSolver solver = decomposition.getSolver();
        RealMatrix b = MatrixUtils.createRealMatrix(new double[][] {
                { -102, 12250 }, { 544, 24500 }, { 167, -36750 }
        });
        RealMatrix xRef = MatrixUtils.createRealMatrix(new double[][] {
                { 1, 2515 }, { 2, 422 }, { -3, 898 }

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    }


    private void checkDimension(RealMatrix m) {
        int rows = m.getRowDimension();
        int columns = m.getColumnDimension();
        QRDecomposition qr = new QRDecompositionImpl(m);
        assertEquals(rows,    qr.getQ().getRowDimension());
        assertEquals(rows,    qr.getQ().getColumnDimension());
        assertEquals(rows,    qr.getR().getRowDimension());
        assertEquals(columns, qr.getR().getColumnDimension());        
    }

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        checkAEqualQR(createTestMatrix(r, q, p));


    }


    private void checkAEqualQR(RealMatrix m) {
        QRDecomposition qr = new QRDecompositionImpl(m);
        double norm = qr.getQ().multiply(qr.getR()).subtract(m).getNorm();
        assertEquals(0, norm, normTolerance);
    }

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        checkQOrthogonal(createTestMatrix(r, q, p));


    }


    private void checkQOrthogonal(RealMatrix m) {
        QRDecomposition qr = new QRDecompositionImpl(m);
        RealMatrix eye = MatrixUtils.createRealIdentityMatrix(m.getRowDimension());
        double norm = qr.getQT().multiply(qr.getQ()).subtract(eye).getNorm();
        assertEquals(0, norm, normTolerance);
    }

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            }
        });
    }
    /** test matrices values */
    public void testMatricesValues() {
        QRDecomposition qr =
            new QRDecompositionImpl(MatrixUtils.createRealMatrix(testData3x3NonSingular));
        RealMatrix qRef = MatrixUtils.createRealMatrix(new double[][] {
                { -12.0 / 14.0,   69.0 / 175.0,  -58.0 / 175.0 },
                {  -6.0 / 14.0, -158.0 / 175.0,    6.0 / 175.0 },
                {   4.0 / 14.0,  -30.0 / 175.0, -165.0 / 175.0 }
        });
        RealMatrix rRef = MatrixUtils.createRealMatrix(new double[][] {
                { -14.0,  -21.0, 14.0 },
                {   0.0, -175.0, 70.0 },
                {   0.0,    0.0, 35.0 }
        });
        RealMatrix hRef = MatrixUtils.createRealMatrix(new double[][] {
                { 26.0 / 14.0, 0.0, 0.0 },
                {  6.0 / 14.0, 648.0 / 325.0, 0.0 },
                { -4.0 / 14.0,  36.0 / 325.0, 2.0 }
        });


        // check values against known references
        RealMatrix q = qr.getQ();
        assertEquals(0, q.subtract(qRef).getNorm(), 1.0e-13);
        RealMatrix qT = qr.getQT();
        assertEquals(0, qT.subtract(qRef.transpose()).getNorm(), 1.0e-13);
        RealMatrix r = qr.getR();
        assertEquals(0, r.subtract(rRef).getNorm(), 1.0e-13);
        RealMatrix h = qr.getH();
        assertEquals(0, h.subtract(hRef).getNorm(), 1.0e-13);


        // check the same cached instance is returned the second time
        assertTrue(q == qr.getQ());
        assertTrue(r == qr.getR());
        assertTrue(h == qr.getH());
        
    }

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   */
  @Override
  public QRDecompositionResult evaluate(final DoubleMatrix2D x) {
    Validate.notNull(x);
    final RealMatrix temp = CommonsMathWrapper.wrap(x);
    final QRDecomposition qr = new QRDecompositionImpl(temp);
    return new QRDecompositionCommonsResult(qr);
  }

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