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

org.apache.commons.math.linear.LUDecomposition
nist.gov/javanumerics/jama/">JAMA library.
- a {@link #getP() getP} method has been added,
- the det method has been renamed as {@link #getDeterminant() getDeterminant},
- the getDoublePivot method has been removed (but the int based {@link #getPivot() getPivot} method has been kept),
- the solve and isNonSingular methods have been replaced by a {@link #getSolver() getSolver} method and the equivalent methods provided bythe returned {@link DecompositionSolver}.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 2.0

    }


    /** test dimensions */
    public void testDimensions() {
        RealMatrix matrix = MatrixUtils.createRealMatrix(testData);
        LUDecomposition LU = new LUDecompositionImpl(matrix);
        assertEquals(testData.length, LU.getL().getRowDimension());
        assertEquals(testData.length, LU.getL().getColumnDimension());
        assertEquals(testData.length, LU.getU().getRowDimension());
        assertEquals(testData.length, LU.getU().getColumnDimension());
        assertEquals(testData.length, LU.getP().getRowDimension());
        assertEquals(testData.length, LU.getP().getColumnDimension());


    }

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    }


    /** test PA = LU */
    public void testPAEqualLU() {
        RealMatrix matrix = MatrixUtils.createRealMatrix(testData);
        LUDecomposition lu = new LUDecompositionImpl(matrix);
        RealMatrix l = lu.getL();
        RealMatrix u = lu.getU();
        RealMatrix p = lu.getP();
        double norm = l.multiply(u).subtract(p.multiply(matrix)).getNorm();
        assertEquals(0, norm, normTolerance);


        matrix = MatrixUtils.createRealMatrix(testDataMinus);
        lu = new LUDecompositionImpl(matrix);
        l = lu.getL();
        u = lu.getU();
        p = lu.getP();
        norm = l.multiply(u).subtract(p.multiply(matrix)).getNorm();
        assertEquals(0, norm, normTolerance);


        matrix = MatrixUtils.createRealIdentityMatrix(17);
        lu = new LUDecompositionImpl(matrix);
        l = lu.getL();
        u = lu.getU();
        p = lu.getP();
        norm = l.multiply(u).subtract(p.multiply(matrix)).getNorm();
        assertEquals(0, norm, normTolerance);


        matrix = MatrixUtils.createRealMatrix(singular);
        lu = new LUDecompositionImpl(matrix);
        assertFalse(lu.getSolver().isNonSingular());
        assertNull(lu.getL());
        assertNull(lu.getU());
        assertNull(lu.getP());


        matrix = MatrixUtils.createRealMatrix(bigSingular);
        lu = new LUDecompositionImpl(matrix);
        assertFalse(lu.getSolver().isNonSingular());
        assertNull(lu.getL());
        assertNull(lu.getU());
        assertNull(lu.getP());


    }

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    }




    /** test singular */
    public void testSingular() {
        LUDecomposition lu =
            new LUDecompositionImpl(MatrixUtils.createRealMatrix(testData));
        assertTrue(lu.getSolver().isNonSingular());
        lu = new LUDecompositionImpl(MatrixUtils.createRealMatrix(singular));
        assertFalse(lu.getSolver().isNonSingular());
        lu = new LUDecompositionImpl(MatrixUtils.createRealMatrix(bigSingular));
        assertFalse(lu.getSolver().isNonSingular());
    }

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        assertFalse(lu.getSolver().isNonSingular());
    }


    /** test matrices values */
    public void testMatricesValues1() {
       LUDecomposition lu =
            new LUDecompositionImpl(MatrixUtils.createRealMatrix(testData));
        RealMatrix lRef = MatrixUtils.createRealMatrix(new double[][] {
                { 1.0, 0.0, 0.0 },
                { 0.5, 1.0, 0.0 },
                { 0.5, 0.2, 1.0 }
        });
        RealMatrix uRef = MatrixUtils.createRealMatrix(new double[][] {
                { 2.0,  5.0, 3.0 },
                { 0.0, -2.5, 6.5 },
                { 0.0,  0.0, 0.2 }
        });
        RealMatrix pRef = MatrixUtils.createRealMatrix(new double[][] {
                { 0.0, 1.0, 0.0 },
                { 0.0, 0.0, 1.0 },
                { 1.0, 0.0, 0.0 }
        });
        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();
        for (int i = 0; i < pivotRef.length; ++i) {
            assertEquals(pivotRef[i], pivot[i]);
        }


        // check the same cached instance is returned the second time
        assertTrue(l == lu.getL());
        assertTrue(u == lu.getU());
        assertTrue(p == lu.getP());
        
    }

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    }


    /** test matrices values */
    public void testMatricesValues2() {
       LUDecomposition lu =
            new LUDecompositionImpl(MatrixUtils.createRealMatrix(luData));
        RealMatrix lRef = MatrixUtils.createRealMatrix(new double[][] {
                {    1.0,    0.0, 0.0 },
                {    0.0,    1.0, 0.0 },
                { 1.0 / 3.0, 0.0, 1.0 }
        });
        RealMatrix uRef = MatrixUtils.createRealMatrix(new double[][] {
                { 6.0, 9.0,    8.0    },
                { 0.0, 5.0,    7.0    },
                { 0.0, 0.0, 1.0 / 3.0 }
        });
        RealMatrix pRef = MatrixUtils.createRealMatrix(new double[][] {
                { 0.0, 0.0, 1.0 },
                { 0.0, 1.0, 0.0 },
                { 1.0, 0.0, 0.0 }
        });
        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();
        for (int i = 0; i < pivotRef.length; ++i) {
            assertEquals(pivotRef[i], pivot[i]);
        }


        // check the same cached instance is returned the second time
        assertTrue(l == lu.getL());
        assertTrue(u == lu.getU());
        assertTrue(p == lu.getP());
        
    }

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  @Override
  public double getDeterminant(final Matrix<?> m) {
    Validate.notNull(m, "m");
    if (m instanceof DoubleMatrix2D) {
      final RealMatrix temp = CommonsMathWrapper.wrap((DoubleMatrix2D) m);
      final LUDecomposition lud = new LUDecompositionImpl(temp);
      return lud.getDeterminant();
    }
    throw new IllegalArgumentException("Can only find determinant of DoubleMatrix2D; have " + m.getClass());
  }

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   */
  @Override
  public LUDecompositionResult evaluate(final DoubleMatrix2D x) {
    Validate.notNull(x);
    final RealMatrix temp = CommonsMathWrapper.wrap(x);
    final LUDecomposition lu = new LUDecompositionImpl(temp);
    return new LUDecompositionCommonsResult(lu);
  }

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