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

org.apache.commons.math.linear.BiDiagonalTransformer
Class transforming any matrix to bi-diagonal shape.
Any m × n matrix A can be written as the product of three matrices: A = U × B × V^T with U an m × m orthogonal matrix, B an m × n bi-diagonal matrix (lower diagonal if m < n, upper diagonal otherwise), and V an n × n orthogonal matrix.

Transformation to bi-diagonal shape is often not a goal by itself, but it is an intermediate step in more general decomposition algorithms like {@link SingularValueDecomposition Singular Value Decomposition}. This class is therefore intended for internal use by the library and is not public. As a consequence of this explicitly limited scope, many methods directly returns references to internal arrays, not copies.
@version $Revision: 990655 $ $Date: 2010-08-29 23:49:40 +0200 (dim. 29 août 2010) $ @since 2.0

        Assert.assertEquals(0, mTm.subtract(id).getNorm(), 1.0e-14);
    }


    @Test
    public void testBBiDiagonal() {
        checkBiDiagonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testSquare)).getB());
        checkBiDiagonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testNonSquare)).getB());
        checkBiDiagonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testNonSquare).transpose()).getB());
    }

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        }
    }


    @Test
    public void testSingularMatrix() {
       BiDiagonalTransformer transformer =
            new BiDiagonalTransformer(MatrixUtils.createRealMatrix(new double[][] {
                { 1.0, 2.0, 3.0 },
                { 2.0, 3.0, 4.0 },
                { 3.0, 5.0, 7.0 }
            }));
       final double s3  = Math.sqrt(3.0);
       final double s14 = Math.sqrt(14.0);
       final double s1553 = Math.sqrt(1553.0);
       RealMatrix uRef = MatrixUtils.createRealMatrix(new double[][] {
           {  -1.0 / s14,  5.0 / (s3 * s14),  1.0 / s3 },
           {  -2.0 / s14, -4.0 / (s3 * s14),  1.0 / s3 },
           {  -3.0 / s14,  1.0 / (s3 * s14), -1.0 / s3 }
       });
       RealMatrix bRef = MatrixUtils.createRealMatrix(new double[][] {
           { -s14, s1553 / s14,   0.0 },
           {  0.0, -87 * s3 / (s14 * s1553), -s3 * s14 / s1553 },
           {  0.0, 0.0, 0.0 }
       });
       RealMatrix vRef = MatrixUtils.createRealMatrix(new double[][] {
           { 1.0,   0.0,         0.0        },
           { 0.0,  -23 / s1553,  32 / s1553 },
           { 0.0,  -32 / s1553, -23 / s1553 }
       });


       // check values against known references
       RealMatrix u = transformer.getU();
       Assert.assertEquals(0, u.subtract(uRef).getNorm(), 1.0e-14);
       RealMatrix b = transformer.getB();
       Assert.assertEquals(0, b.subtract(bRef).getNorm(), 1.0e-14);
       RealMatrix v = transformer.getV();
       Assert.assertEquals(0, v.subtract(vRef).getNorm(), 1.0e-14);


       // check the same cached instance is returned the second time
       Assert.assertTrue(u == transformer.getU());
       Assert.assertTrue(b == transformer.getB());
       Assert.assertTrue(v == transformer.getV());


    }

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    }


    @Test
    public void testMatricesValues() {
       BiDiagonalTransformer transformer =
            new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testSquare));
       final double s17 = Math.sqrt(17.0);
        RealMatrix uRef = MatrixUtils.createRealMatrix(new double[][] {
                {  -8 / (5 * s17), 19 / (5 * s17) },
                { -19 / (5 * s17), -8 / (5 * s17) }
        });
        RealMatrix bRef = MatrixUtils.createRealMatrix(new double[][] {
                { -3 * s17 / 5, 32 * s17 / 85 },
                {      0.0,     -5 * s17 / 17 }
        });
        RealMatrix vRef = MatrixUtils.createRealMatrix(new double[][] {
                { 1.0,  0.0 },
                { 0.0, -1.0 }
        });


        // check values against known references
        RealMatrix u = transformer.getU();
        Assert.assertEquals(0, u.subtract(uRef).getNorm(), 1.0e-14);
        RealMatrix b = transformer.getB();
        Assert.assertEquals(0, b.subtract(bRef).getNorm(), 1.0e-14);
        RealMatrix v = transformer.getV();
        Assert.assertEquals(0, v.subtract(vRef).getNorm(), 1.0e-14);


        // check the same cached instance is returned the second time
        Assert.assertTrue(u == transformer.getU());
        Assert.assertTrue(b == transformer.getB());
        Assert.assertTrue(v == transformer.getV());


    }

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    }


    @Test
    public void testUpperOrLower() {
        Assert.assertTrue(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testSquare)).isUpperBiDiagonal());
        Assert.assertTrue(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testNonSquare)).isUpperBiDiagonal());
        Assert.assertFalse(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testNonSquare).transpose()).isUpperBiDiagonal());
    }

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    }


    private void checkdimensions(RealMatrix matrix) {
        final int m = matrix.getRowDimension();
        final int n = matrix.getColumnDimension();
        BiDiagonalTransformer transformer = new BiDiagonalTransformer(matrix);
        Assert.assertEquals(m, transformer.getU().getRowDimension());
        Assert.assertEquals(m, transformer.getU().getColumnDimension());
        Assert.assertEquals(m, transformer.getB().getRowDimension());
        Assert.assertEquals(n, transformer.getB().getColumnDimension());
        Assert.assertEquals(n, transformer.getV().getRowDimension());
        Assert.assertEquals(n, transformer.getV().getColumnDimension());


    }

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        checkAEqualUSVt(MatrixUtils.createRealMatrix(testNonSquare));
        checkAEqualUSVt(MatrixUtils.createRealMatrix(testNonSquare).transpose());
    }


    private void checkAEqualUSVt(RealMatrix matrix) {
        BiDiagonalTransformer transformer = new BiDiagonalTransformer(matrix);
        RealMatrix u = transformer.getU();
        RealMatrix b = transformer.getB();
        RealMatrix v = transformer.getV();
        double norm = u.multiply(b).multiply(v.transpose()).subtract(matrix).getNorm();
        Assert.assertEquals(0, norm, 1.0e-14);
    }

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        Assert.assertEquals(0, norm, 1.0e-14);
    }


    @Test
    public void testUOrthogonal() {
        checkOrthogonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testSquare)).getU());
        checkOrthogonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testNonSquare)).getU());
        checkOrthogonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testNonSquare).transpose()).getU());
    }

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        checkOrthogonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testNonSquare).transpose()).getU());
    }


    @Test
    public void testVOrthogonal() {
        checkOrthogonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testSquare)).getV());
        checkOrthogonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testNonSquare)).getV());
        checkOrthogonal(new BiDiagonalTransformer(MatrixUtils.createRealMatrix(testNonSquare).transpose()).getV());
    }

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    }


    private void checkdimensions(RealMatrix matrix) {
        final int m = matrix.getRowDimension();
        final int n = matrix.getColumnDimension();
        BiDiagonalTransformer transformer = new BiDiagonalTransformer(matrix);
        Assert.assertEquals(m, transformer.getU().getRowDimension());
        Assert.assertEquals(m, transformer.getU().getColumnDimension());
        Assert.assertEquals(m, transformer.getB().getRowDimension());
        Assert.assertEquals(n, transformer.getB().getColumnDimension());
        Assert.assertEquals(n, transformer.getV().getRowDimension());
        Assert.assertEquals(n, transformer.getV().getColumnDimension());


    }

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        checkAEqualUSVt(MatrixUtils.createRealMatrix(testNonSquare));
        checkAEqualUSVt(MatrixUtils.createRealMatrix(testNonSquare).transpose());
    }


    private void checkAEqualUSVt(RealMatrix matrix) {
        BiDiagonalTransformer transformer = new BiDiagonalTransformer(matrix);
        RealMatrix u = transformer.getU();
        RealMatrix b = transformer.getB();
        RealMatrix v = transformer.getV();
        double norm = u.multiply(b).multiply(v.transpose()).subtract(matrix).getNorm();
        Assert.assertEquals(0, norm, 1.0e-14);
    }

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