Examples of org.apache.commons.math.linear.RealMatrix.subtract()

Class org.apache.commons.math.linear.RealMatrix

Examples of org.apache.commons.math.linear.RealMatrix.subtract()

org.apache.commons.math.linear.RealMatrix.subtract()
Compute this minus m. @param m matrix to be subtracted @return this - m @throws IllegalArgumentException if m is not the same size as this

            }
        });


        // despite perturbation, the least square solution should be pretty good
        RealMatrix x = new QRDecompositionImpl(a).getSolver().solve(b);
        assertEquals(0, x.subtract(xRef).getNorm(), 0.01 * noise * p * q);


    }


    public void testUnderdetermined() {
        final Random r    = new Random(42185006424567123l);

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        });
        int[] pivotRef = { 1, 2, 0 };


        // check values against known references
        RealMatrix l = lu.getL();
        assertEquals(0, l.subtract(lRef).getNorm(), 1.0e-13);
        RealMatrix u = lu.getU();
        assertEquals(0, u.subtract(uRef).getNorm(), 1.0e-13);
        RealMatrix p = lu.getP();
        assertEquals(0, p.subtract(pRef).getNorm(), 1.0e-13);
        int[] pivot = lu.getPivot();

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        // check values against known references
        RealMatrix l = lu.getL();
        assertEquals(0, l.subtract(lRef).getNorm(), 1.0e-13);
        RealMatrix u = lu.getU();
        assertEquals(0, u.subtract(uRef).getNorm(), 1.0e-13);
        RealMatrix p = lu.getP();
        assertEquals(0, p.subtract(pRef).getNorm(), 1.0e-13);
        int[] pivot = lu.getPivot();
        for (int i = 0; i < pivotRef.length; ++i) {
            assertEquals(pivotRef[i], pivot[i]);

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        RealMatrix l = lu.getL();
        assertEquals(0, l.subtract(lRef).getNorm(), 1.0e-13);
        RealMatrix u = lu.getU();
        assertEquals(0, u.subtract(uRef).getNorm(), 1.0e-13);
        RealMatrix p = lu.getP();
        assertEquals(0, p.subtract(pRef).getNorm(), 1.0e-13);
        int[] pivot = lu.getPivot();
        for (int i = 0; i < pivotRef.length; ++i) {
            assertEquals(pivotRef[i], pivot[i]);
        }

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        });
        int[] pivotRef = { 2, 1, 0 };


        // check values against known references
        RealMatrix l = lu.getL();
        assertEquals(0, l.subtract(lRef).getNorm(), 1.0e-13);
        RealMatrix u = lu.getU();
        assertEquals(0, u.subtract(uRef).getNorm(), 1.0e-13);
        RealMatrix p = lu.getP();
        assertEquals(0, p.subtract(pRef).getNorm(), 1.0e-13);
        int[] pivot = lu.getPivot();

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        // check values against known references
        RealMatrix l = lu.getL();
        assertEquals(0, l.subtract(lRef).getNorm(), 1.0e-13);
        RealMatrix u = lu.getU();
        assertEquals(0, u.subtract(uRef).getNorm(), 1.0e-13);
        RealMatrix p = lu.getP();
        assertEquals(0, p.subtract(pRef).getNorm(), 1.0e-13);
        int[] pivot = lu.getPivot();
        for (int i = 0; i < pivotRef.length; ++i) {
            assertEquals(pivotRef[i], pivot[i]);

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        RealMatrix l = lu.getL();
        assertEquals(0, l.subtract(lRef).getNorm(), 1.0e-13);
        RealMatrix u = lu.getU();
        assertEquals(0, u.subtract(uRef).getNorm(), 1.0e-13);
        RealMatrix p = lu.getP();
        assertEquals(0, p.subtract(pRef).getNorm(), 1.0e-13);
        int[] pivot = lu.getPivot();
        for (int i = 0; i < pivotRef.length; ++i) {
            assertEquals(pivotRef[i], pivot[i]);
        }

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         * Verify that residuals computed using the hat matrix are close to 
         * what we get from direct computation, i.e. r = (I - H) y
         */
        double[] residuals = model.estimateResiduals();
        RealMatrix I = MatrixUtils.createRealIdentityMatrix(10);
        double[] hatResiduals = I.subtract(hat).operate(model.Y).getData();
        TestUtils.assertEquals(residuals, hatResiduals, 10e-12);    
    }
}

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        TriDiagonalTransformer transformer =
            new TriDiagonalTransformer(MatrixUtils.createRealMatrix(matrix));


        // check values against known references
        RealMatrix q = transformer.getQ();
        assertEquals(0, q.subtract(MatrixUtils.createRealMatrix(qRef)).getNorm(), 1.0e-14);


        RealMatrix t = transformer.getT();
        double[][] tData = new double[mainDiagnonal.length][mainDiagnonal.length];
        for (int i = 0; i < mainDiagnonal.length; ++i) {
            tData[i][i] = mainDiagnonal[i];

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            }
            if (i < secondaryDiagonal.length) {
                tData[i][i + 1] = secondaryDiagonal[i];
            }
        }
        assertEquals(0, t.subtract(MatrixUtils.createRealMatrix(tData)).getNorm(), 1.0e-14);


        // check the same cached instance is returned the second time
        assertTrue(q == transformer.getQ());
        assertTrue(t == transformer.getT());

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