Examples of DenseMatrix64F

org.ejml.data.DenseMatrix64F

DenseMatrix64F is a dense matrix with elements that are 64-bit floats (doubles). A matrix is the fundamental data structure in linear algebra. Unlike a sparse matrix, there is no compression in a dense matrix and every element is stored in memory. This allows for fast reads and writes to the matrix.

To keep the code manageable and the library easier to use only basic functions for accessing and editing elements are provided in this class. The numerous operations which can be performed on DenseMatrix64F are contained in various other classes, where the most common operations can be found in the {@link org.ejml.ops.CommonOps} and {@link org.ejml.ops.SpecializedOps} classes.

The matrix is stored internally in a row-major 1D array format:

data[ y*numCols + x ] = data[y][x]

For example:
data =

a₁₁ a₁₂ a₁₃ a₁₄ a₂₁ a₂₂ a₂₃ a₂₄ a₃₁ a₃₂ a₃₃ a₃₄ a₄₁ a₄₂ a₄₃ a₄₄

An alternative to working directly with DenseMatrix64 is {@link org.ejml.simple.SimpleMatrix}. SimpleMatrix is a wrapper around DenseMatrix64F that provides an easier to use object oriented way of manipulating matrices, at the cost of efficiency.
@see org.ejml.ops.CommonOps @see org.ejml.ops.SpecializedOps @see org.ejml.simple.SimpleMatrix @author Peter Abeles

Examples of org.ejml.data.DenseMatrix64F

    @Test
    public void testParseMatrix() {
        String a = "-0.779094   1.682750\n" +
                 "   1.304014  -1.880739\n";


        DenseMatrix64F m = UtilEjml.parseMatrix(a,2);


        assertEquals(2,m.numCols);
        assertEquals(2,m.numRows);
        assertEquals(-0.779094 , m.get(0,0) , 1e-5);
        assertEquals(1.682750  , m.get(0,1)  , 1e-5);
        assertEquals(1.304014  , m.get(1,0)  , 1e-5);
        assertEquals(-1.880739 , m.get(1,1) , 1e-5);


        // give it a matrix with a space in the first element, see if that screws it up
        a = " -0.779094   1.682750  5\n" +
           "   1.304014  -1.880739  8\n";


        m = UtilEjml.parseMatrix(a,3);
        assertEquals(3,m.numCols);
        assertEquals(2,m.numRows);
        assertEquals(-0.779094 , m.get(0,0) , 1e-5);
    }

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Examples of org.ejml.data.DenseMatrix64F


    Random rand = new Random(234234);


    @Test
    public void square() {
        DenseMatrix64F mat = RandomMatrices.createRandom(5,5,rand);
        DenseMatrix64F matTran = mat.copy();


        TransposeAlgs.square(matTran);


        assertEquals(mat.getNumCols(),matTran.getNumRows());
        assertEquals(mat.getNumRows(),matTran.getNumCols());


        EjmlUnitTests.assertEqualsTrans(mat,matTran,0);
    }

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Examples of org.ejml.data.DenseMatrix64F

    @Test
    public void block() {
        // check various shapes to make sure blocking is handled correctly
        for( int numRows = 1; numRows < 15; numRows += 2 ) {
            for( int numCols = 1; numCols < 15; numCols += 2) {
                DenseMatrix64F mat = RandomMatrices.createRandom(numRows,numCols,rand);
                DenseMatrix64F matTran = new DenseMatrix64F(numCols,numRows);


                TransposeAlgs.block(mat,matTran,7);


                assertEquals(numCols,matTran.getNumRows());
                assertEquals(numRows,matTran.getNumCols());


                EjmlUnitTests.assertEqualsTrans(mat,matTran,0);
            }
        }
    }

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Examples of org.ejml.data.DenseMatrix64F

        }
    }


    @Test
    public void standard() {
        DenseMatrix64F mat = RandomMatrices.createRandom(5,7,rand);
        DenseMatrix64F matTran = new DenseMatrix64F(7,5);


        TransposeAlgs.standard(mat,matTran);


        assertEquals(mat.getNumCols(),matTran.getNumRows());
        assertEquals(mat.getNumRows(),matTran.getNumCols());


        EjmlUnitTests.assertEqualsTrans(mat,matTran,0);
    }

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Examples of org.ejml.data.DenseMatrix64F

    Random rand = new Random(234234);


    @Test
    public void quality_eig() {
        // I'm assuming it can process this matrix with no problems
        DenseMatrix64F A = RandomMatrices.createSymmetric(5,-1,1,rand);


        EigenDecomposition<DenseMatrix64F> eig = DecompositionFactory.eig(A.numRows,true);


        assertTrue(eig.decompose(A));

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Examples of org.ejml.data.DenseMatrix64F

    }


    @Test
    public void quality_svd() {
        // I'm assuming it can process this matrix with no problems
        DenseMatrix64F A = RandomMatrices.createRandom(4,5,rand);


        SingularValueDecomposition<DenseMatrix64F> svd = DecompositionFactory.svd(A.numRows,A.numCols,true,true,false);


        assertTrue(svd.decompose(A));

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Examples of org.ejml.data.DenseMatrix64F

//        checkSolutionRandom(10,4,3);
    }


    @Test
    public void testSingular() {
        DenseMatrix64F A = new DenseMatrix64F(3,4,true,1,2,3,4,3,5,6,7,2,4,6,8,-3,4,9,3);


        DenseMatrix64F found = A.copy();
        alg.reduce(found,3);


        checkRref(found,3);


        DenseMatrix64F A1 = CommonOps.extract(A,0,3,0,3);
        DenseMatrix64F X = CommonOps.extract(found,0,3,3,4);
        DenseMatrix64F B = new DenseMatrix64F(3,1);


        CommonOps.mult(A1,X,B);


        for( int i = 0; i < 3; i++ )
            assertEquals(A.get(i,3),B.get(i,0),1e-8);
    }

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Examples of org.ejml.data.DenseMatrix64F

    /**
     * Feed it specific matrices and see if it dies a horrible death
     */
    @Test
    public void spotTests() {
        DenseMatrix64F A = new DenseMatrix64F(4,6,true,
                0,0,1,-1,-1,4,
                2,4,2,4,2,4,
                2,4,3,3,3,4,
                3,6,6,3,6,6);

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Examples of org.ejml.data.DenseMatrix64F

        alg.reduce(A,5);
        checkRref(A,5);
    }


    private void checkFormatRandom(int numRows, int numCols) {
        DenseMatrix64F A = RandomMatrices.createRandom(numRows,numCols,-1,1,rand);
        DenseMatrix64F found = A.copy();


        alg.reduce(found,numCols);


        checkRref(found, numCols);
    }

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Examples of org.ejml.data.DenseMatrix64F


        checkRref(found, numCols);
    }


    private void checkSolutionRandom(int numRows, int numCols , int solWidth ) {
        DenseMatrix64F A = RandomMatrices.createRandom(numRows,numCols,-1,1,rand);
        DenseMatrix64F found = A.copy();


        alg.reduce(found,solWidth);


        checkRref(found,solWidth);


        DenseMatrix64F A1 = CommonOps.extract(A,0,numRows,0,solWidth);
        DenseMatrix64F X = CommonOps.extract(found,0,solWidth,solWidth,numCols);
        DenseMatrix64F B = new DenseMatrix64F(numRows,numCols-solWidth);


        CommonOps.mult(A1,X,B);


        for( int i = 0; i < numRows; i++ )
            for( int j = 0; j < numCols-solWidth; j++ )
                assertEquals(A.get(i,j+solWidth),B.get(i,j),1e-8);
    }

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