Package org.ejml.data

Examples of org.ejml.data.D1Submatrix64F

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            BlockMatrix64F Ub = BlockMatrixOps.convert(U.getMatrix(),r);
            BlockMatrix64F Vb = BlockMatrixOps.convert(V.getMatrix(),r);

            SimpleMatrix expected = A.plus(U.transpose().mult(V));

            TridiagonalDecompositionBlockHouseholder.multPlusTransA(r,new D1Submatrix64F(Ub)
                    ,new D1Submatrix64F(Vb),new D1Submatrix64F(Ab));


            for( int i = r; i < width; i++ ) {
                for( int j = i; j < width; j++ ) {
                    assertEquals(i+" "+j,expected.get(i,j),Ab.get(i,j),1e-8);
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        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));
        BlockInnerRankUpdate.rankNUpdate(N,alpha,subA,subB);

        assertTrue(GenericMatrixOps.isEquivalent(expected.getMatrix(),blockA,1e-8));
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        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));
        BlockInnerRankUpdate.symmRankNMinus_U(N,subA,subB);

        assertTrue(GenericMatrixOps.isEquivalentTriangle(true,expected.getMatrix(),blockA,1e-8));
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        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));
        BlockInnerRankUpdate.symmRankNMinus_L(N,subA,subB);

//        expected.print();
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        QRDecompositionHouseholderTran algTest = new QRDecompositionHouseholderTran();
        assertTrue(algTest.decompose(A));

        double gammas[] = new double[A.numCols];
        BlockHouseHolder.decomposeQR_block_col(r,new D1Submatrix64F(Ab),gammas);

        DenseMatrix64F expected = CommonOps.transpose(algTest.getQR(),null);

        assertTrue(GenericMatrixOps.isEquivalent(expected,Ab,1e-8));
    }
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        SimpleMatrix V = A.extractMatrix(0,A.numRows(),2,3);
        SimpleMatrix expected = V.minus(U.mult(U.transpose().mult(V)).scale(gamma));

        BlockMatrix64F Ab = BlockMatrixOps.convert(A.getMatrix(),r);

        BlockHouseHolder.rank1UpdateMultR_Col(r,new D1Submatrix64F(Ab),1,gamma);

        for( int i = 1; i < expected.numRows(); i++ ) {
            assertEquals(expected.get(i,0),Ab.get(i,2),1e-8);
        }
    }
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        U.set(0,0,0);
        U.set(1,0,1);

        BlockMatrix64F Ab = BlockMatrixOps.convert(A.getMatrix(),r);

        BlockHouseHolder.rank1UpdateMultR_TopRow(r,new D1Submatrix64F(Ab),1,gamma);

        // check all the columns now
        for( int i = 0; i < r; i++ ) {
            for( int j = r; j < A.numCols(); j++ ) {
                SimpleMatrix V = A.extractMatrix(0,A.numRows(),j,j+1);
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            SimpleMatrix A = SimpleMatrix.wrap(RandomMatrices.createSymmetric(width,-1,1,rand));

            TridiagonalDecompositionHouseholderOrig decomp = new TridiagonalDecompositionHouseholderOrig();
            decomp.decompose(A.getMatrix());

            D1Submatrix64F Ab = insertIntoBlock(offX,offY,A,r);
            D1Submatrix64F V = new D1Submatrix64F(new BlockMatrix64F(r,offX+A.numCols(),r));
            V.col0 = offX;
            V.row1 = Ab.row1-Ab.row0;
            int gammaOffset = offX;
            double gammas[] = new double[gammaOffset+A.numCols()];
            TridiagonalBlockHelper.tridiagUpperRow(r,Ab,gammas,V);
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        SimpleMatrix expected = A.minus( A.mult(U).mult(U.transpose()).scale(gamma) );

        BlockMatrix64F Ab = BlockMatrixOps.convert(A.getMatrix(),r);

        BlockHouseHolder.rank1UpdateMultL_Row(r,new D1Submatrix64F(Ab),1,1,gamma);

        for( int j = 1; j < expected.numCols(); j++ ) {
            assertEquals(expected.get(2,j),Ab.get(2,j),1e-8);
        }
    }
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            // now compute it using the block matrix stuff
            BlockMatrix64F Ab = BlockMatrixOps.convert(A.getMatrix(),r);
            BlockMatrix64F Wb = new BlockMatrix64F(Ab.numRows,Ab.numCols,r);

            D1Submatrix64F Ab_sub = new D1Submatrix64F(Ab);
            D1Submatrix64F Wb_sub = new D1Submatrix64F(Wb);

            TridiagonalBlockHelper.computeW_row(r,Ab_sub,Wb_sub,betas,0);

            // see if the result is the same
            assertTrue(GenericMatrixOps.isEquivalent(Wb,W.getMatrix(),1e-8));
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Related Classes of org.ejml.data.D1Submatrix64F

  • org.ejml.alg.block.BlockMatrixOps
  • org.ejml.alg.block.BlockTriangularSolver
  • org.ejml.alg.block.decomposition.chol.BlockCholeskyOuterForm
  • 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.TestBlockHouseHolder
  • org.ejml.alg.block.linsol.chol.BlockCholeskyOuterSolver
  • org.ejml.alg.block.linsol.qr.BlockQrHouseHolderSolver
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