Package org.ejml.data

Examples of org.ejml.data.BlockMatrix64F

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    @Test
    public void innerProdRow() {
        DenseMatrix64F A = RandomMatrices.createRandom(r*3-1,r*2+r-1,-1,1,rand);
        BlockMatrix64F Ab = BlockMatrixOps.convert(A,r);

        int zeroOffset = 1;
        for( int rowBlock = 0; rowBlock < r*2; rowBlock+=r) {
            int rowA = 2;
            int rowB = 1;
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    @Test
    public void divideElementsCol() {

        double div = 1.5;
        int col = 1;
        BlockMatrix64F A = BlockMatrixOps.createRandom(r*2+r-1,r,-1,1,rand,r);
        BlockMatrix64F A_orig = A.copy();

        BlockHouseHolder.divideElementsCol(r,new D1Submatrix64F(A),col,div);

        for( int i = col+1; i < A.numRows; i++ ) {
            assertEquals(A_orig.get(i,col)/div , A.get(i,col),1e-8);
        }
    }
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    @Test
    public void scale_row() {

        double div = 1.5;
        int row = 1;
        BlockMatrix64F A = BlockMatrixOps.createRandom(r*2+r-1,r*2+1,-1,1,rand,r);
        BlockMatrix64F A_orig = A.copy();

        BlockHouseHolder.scale_row(r,new D1Submatrix64F(A),new D1Submatrix64F(A),row,1,div);

        // check the one
        assertEquals(div,A.get(row,row+1),1e-8);
        // check the rest
        for( int i = row+2; i < A.numCols; i++ ) {
            assertEquals(A_orig.get(row,i)*div , A.get(row,i),1e-8);
        }
    }
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//            System.out.println("width "+width);
            int end = width;

            SimpleMatrix A = SimpleMatrix.random(r,width,-1,1,rand);
            SimpleMatrix B = SimpleMatrix.random(r,width,-1,1,rand);
            BlockMatrix64F Ab = BlockMatrixOps.convert(A.getMatrix(),r);
            BlockMatrix64F Bb = BlockMatrixOps.convert(B.getMatrix(),r);
            BlockMatrix64F Cb = Ab.copy();

            // turn A into householder vectors
            for( int i = 0; i < A.numRows(); i++ ) {
                for( int j = 0; j <= i; j++ ) {
                    if( A.isInBounds(i,j))
                        A.set(i,j,0);
                }
                if( A.isInBounds(i,i+1) )
                    A.set(i,i+1,1);
            }

            SimpleMatrix a = A.extractVector(true,rowA).scale(alpha);
            SimpleMatrix b = B.extractVector(true,rowB).scale(beta);
            SimpleMatrix c = a.plus(b);

            BlockHouseHolder.add_row(r,
                    new D1Submatrix64F(Ab),rowA, alpha,
                    new D1Submatrix64F(Bb),rowB, beta ,
                    new D1Submatrix64F(Cb),rowC, 1,end);

            // skip over the zeros
            for( int j = rowA+1; j < end; j++ ) {
                assertEquals(c.get(j), Cb.get(rowC,j),1e-8);
            }
        }
    }
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    @Test
    public void computeTauAndDivideCol() {

        double max = 1.5;
        int col = 1;
        BlockMatrix64F A = BlockMatrixOps.createRandom(r*2+r-1,r,-1,1,rand,r);
        BlockMatrix64F A_orig = A.copy();

        // manual alg
        double expected = 0;
        for( int i = col; i < A.numRows; i++ ) {
            double val = A.get(i,col)/max;
            expected += val*val;
        }
        expected = Math.sqrt(expected);

        double found = BlockHouseHolder.computeTauAndDivideCol(r,new D1Submatrix64F(A),col,max);

        assertEquals(expected,found,1e-8);

        for( int i = col; i < A.numRows; i++ ) {
            assertEquals(A_orig.get(i,col)/max , A.get(i,col),1e-8);
        }

    }
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    @Test
    public void computeTauAndDivideRow() {
        double max = 1.5;
        int row = 1;
        int colStart = row+1;
        BlockMatrix64F A = BlockMatrixOps.createRandom(r*2+r-1,r*2+1,-1,1,rand,r);
        BlockMatrix64F A_orig = A.copy();

        // manual alg
        double expected = 0;
        for( int j = colStart; j < A.numCols; j++ ) {
            double val = A.get(row,j)/max;
            expected += val*val;
        }
        expected = Math.sqrt(expected);

        double found = BlockHouseHolder.computeTauAndDivideRow(r,new D1Submatrix64F(A),row,colStart,max);

        assertEquals(expected,found,1e-8);

        for( int j = colStart; j < A.numCols; j++ ) {
            assertEquals(A_orig.get(row,j)/max , A.get(row,j),1e-8);
        }
    }
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    private void checkRankNUpdate(int lengthA, int heightB) {
        double alpha = -2.0;
        SimpleMatrix origA = SimpleMatrix.random(lengthA,lengthA,-1,1,rand);
        SimpleMatrix origB = SimpleMatrix.random(heightB,lengthA,-1,1,rand);

        BlockMatrix64F blockA = BlockMatrixOps.convert(origA.getMatrix(),N);
        BlockMatrix64F blockB = BlockMatrixOps.convert(origB.getMatrix(),N);

        D1Submatrix64F subA = new D1Submatrix64F(blockA,0, origA.numRows(), 0, origA.numCols());
        D1Submatrix64F subB = new D1Submatrix64F(blockB,0, origB.numRows(), 0, origB.numCols());

        SimpleMatrix expected = origA.plus(origB.transpose().mult(origB).scale(alpha));
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        }
    }

    @Test
    public void testFindMaxCol() {
        BlockMatrix64F A = BlockMatrixOps.createRandom(r*2+r-1,r,-1,1,rand,r);

        // make sure it ignores the first element
        A.set(0,1,100000);
        A.set(5,1,-2346);

        double max = BlockHouseHolder.findMaxCol(r,new D1Submatrix64F(A),1);

        assertEquals(2346,max,1e-8);
    }
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    private void checkSymmRankNMinus_U(int lengthA, int heightB) {
        SimpleMatrix origA = SimpleMatrix.wrap(RandomMatrices.createSymmPosDef(lengthA,rand));
        SimpleMatrix origB = SimpleMatrix.random(heightB,lengthA,-1,1,rand);

        BlockMatrix64F blockA = BlockMatrixOps.convert(origA.getMatrix(),N);
        BlockMatrix64F blockB = BlockMatrixOps.convert(origB.getMatrix(),N);

        D1Submatrix64F subA = new D1Submatrix64F(blockA,0, origA.numRows(), 0, origA.numCols());
        D1Submatrix64F subB = new D1Submatrix64F(blockB,0, origB.numRows(), 0, origB.numCols());

        SimpleMatrix expected = origA.plus(origB.transpose().mult(origB).scale(-1));
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    private void checkSymmRankNMinus_L(int lengthA, int widthB) {
        SimpleMatrix origA = SimpleMatrix.wrap(RandomMatrices.createSymmPosDef(lengthA,rand));
        SimpleMatrix origB = SimpleMatrix.random(lengthA,widthB,-1,1,rand);

        BlockMatrix64F blockA = BlockMatrixOps.convert(origA.getMatrix(),N);
        BlockMatrix64F blockB = BlockMatrixOps.convert(origB.getMatrix(),N);

        D1Submatrix64F subA = new D1Submatrix64F(blockA,0, origA.numRows(), 0, origA.numCols());
        D1Submatrix64F subB = new D1Submatrix64F(blockB,0, origB.numRows(), 0, origB.numCols());

        SimpleMatrix expected = origA.plus(origB.mult(origB.transpose()).scale(-1));
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Related Classes of org.ejml.data.BlockMatrix64F

  • org.ejml.alg.block.BenchmarkBlockTranspose
  • org.ejml.alg.block.BlockMatrixOps
  • org.ejml.alg.block.decomposition.chol.TestBlockCholeskyOuterForm
  • org.ejml.alg.block.decomposition.hessenberg.TestTridiagonalBlockHelper
  • org.ejml.alg.block.decomposition.hessenberg.TestTridiagonalDecompositionBlockHouseholder
  • org.ejml.alg.block.decomposition.hessenberg.TridiagonalDecompositionBlockHouseholder
  • org.ejml.alg.block.decomposition.qr.BlockMatrix64HouseholderQR
  • org.ejml.alg.block.decomposition.qr.GenericBlock64QrDecompositionTests
  • org.ejml.alg.block.decomposition.qr.TestBlockHouseHolder
  • org.ejml.alg.block.linsol.chol.BlockCholeskyOuterSolver
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