Package org.apache.commons.math.linear

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

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     * columns representing variable values.
     *
     * @param covariance Covariance instance
     */
    public PearsonsCorrelation(Covariance covariance) {
        RealMatrix covarianceMatrix = covariance.getCovarianceMatrix();
        if (covarianceMatrix == null) {
            throw new NullArgumentException(LocalizedFormats.COVARIANCE_MATRIX);
        }
        nObs = covariance.getN();
        correlationMatrix = covarianceToCorrelation(covarianceMatrix);
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     * @param matrix matrix with columns representing variables to correlate
     * @return correlation matrix
     */
    public RealMatrix computeCorrelationMatrix(RealMatrix matrix) {
        int nVars = matrix.getColumnDimension();
        RealMatrix outMatrix = new BlockRealMatrix(nVars, nVars);
        for (int i = 0; i < nVars; i++) {
            for (int j = 0; j < i; j++) {
              double corr = correlation(matrix.getColumn(i), matrix.getColumn(j));
              outMatrix.setEntry(i, j, corr);
              outMatrix.setEntry(j, i, corr);
            }
            outMatrix.setEntry(i, i, 1d);
        }
        return outMatrix;
    }
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     * @param covarianceMatrix the covariance matrix
     * @return correlation matrix
     */
    public RealMatrix covarianceToCorrelation(RealMatrix covarianceMatrix) {
        int nVars = covarianceMatrix.getColumnDimension();
        RealMatrix outMatrix = new BlockRealMatrix(nVars, nVars);
        for (int i = 0; i < nVars; i++) {
            double sigma = FastMath.sqrt(covarianceMatrix.getEntry(i, i));
            outMatrix.setEntry(i, i, 1d);
            for (int j = 0; j < i; j++) {
                double entry = covarianceMatrix.getEntry(i, j) /
                       (sigma * FastMath.sqrt(covarianceMatrix.getEntry(j, j)));
                outMatrix.setEntry(i, j, entry);
                outMatrix.setEntry(j, i, entry);
            }
        }
        return outMatrix;
    }
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        checkAEqualQTQt(MatrixUtils.createRealMatrix(testSquare3));
    }

    private void checkAEqualQTQt(RealMatrix matrix) {
        TriDiagonalTransformer transformer = new TriDiagonalTransformer(matrix);
        RealMatrix q  = transformer.getQ();
        RealMatrix qT = transformer.getQT();
        RealMatrix t  = transformer.getT();
        double norm = q.multiply(t).multiply(qT).subtract(matrix).getNorm();
        assertEquals(0, norm, 4.0e-15);
    }
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        double[][] modifiedData = new double[data.length][];
        for (int i = 0; i < data.length; ++i) {
            modifiedData[i] = data[i].clone();
            Arrays.fill(modifiedData[i], 0, i, Double.NaN);
        }
        RealMatrix matrix = MatrixUtils.createRealMatrix(modifiedData);
        TriDiagonalTransformer transformer = new TriDiagonalTransformer(matrix);
        RealMatrix q  = transformer.getQ();
        RealMatrix qT = transformer.getQT();
        RealMatrix t  = transformer.getT();
        double norm = q.multiply(t).multiply(qT).subtract(MatrixUtils.createRealMatrix(data)).getNorm();
        assertEquals(0, norm, 4.0e-15);
    }
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        suite.setName("EigenDecompositionImpl Tests");
        return suite;
    }

    public void testDimension1() {
        RealMatrix matrix =
            MatrixUtils.createRealMatrix(new double[][] { { 1.5 } });
        EigenDecomposition ed = new EigenDecompositionImpl(matrix, MathUtils.SAFE_MIN);
        assertEquals(1.5, ed.getRealEigenvalue(0), 1.0e-15);
    }
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        EigenDecomposition ed = new EigenDecompositionImpl(matrix, MathUtils.SAFE_MIN);
        assertEquals(1.5, ed.getRealEigenvalue(0), 1.0e-15);
    }

    public void testDimension2() {
        RealMatrix matrix =
            MatrixUtils.createRealMatrix(new double[][] {
                    { 59.0, 12.0 },
                    { 12.0, 66.0 }
            });
        EigenDecomposition ed = new EigenDecompositionImpl(matrix, MathUtils.SAFE_MIN);
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        assertEquals(75.0, ed.getRealEigenvalue(0), 1.0e-15);
        assertEquals(50.0, ed.getRealEigenvalue(1), 1.0e-15);
    }

    public void testDimension3() {
        RealMatrix matrix =
            MatrixUtils.createRealMatrix(new double[][] {
                                   {  39632.0, -4824.0, -16560.0 },
                                   {  -4824.0,  8693.0,   7920.0 },
                                   { -16560.0,  7920.0,  17300.0 }
                               });
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        assertEquals(12500.0, ed.getRealEigenvalue(1), 3.0e-11);
        assertEquals( 3125.0, ed.getRealEigenvalue(2), 3.0e-11);
    }

    public void testDimension4WithSplit() {
        RealMatrix matrix =
            MatrixUtils.createRealMatrix(new double[][] {
                                   {  0.784, -0.288,  0.000,  0.000 },
                                   { -0.288,  0.616,  0.000,  0.000 },
                                   {  0.000,  0.000,  0.164, -0.048 },
                                   {  0.000,  0.000, -0.048,  0.136 }
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        assertEquals(0.2, ed.getRealEigenvalue(2), 1.0e-15);
        assertEquals(0.1, ed.getRealEigenvalue(3), 1.0e-15);
    }

    public void testDimension4WithoutSplit() {
        RealMatrix matrix =
            MatrixUtils.createRealMatrix(new double[][] {
                                   {  0.5608, -0.2016,  0.1152, -0.2976 },
                                   { -0.2016,  0.4432, -0.2304,  0.1152 },
                                   {  0.1152, -0.2304,  0.3088, -0.1344 },
                                   { -0.2976,  0.1152, -0.1344,  0.3872 }
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