Examples of org.ejml.alg.block.linsol.qr.BlockQrHouseHolderSolver

org.ejml.alg.block.linsol.qr.BlockQrHouseHolderSolver

A solver for {@link BlockMatrix64HouseholderQR}. Systems are solved for using the standard QR decomposition method, sketched below.

A = Q*R
A*x = b
Q*R*x = b
R*x = y = Q^Tb
x = R^-1y

Where A is the m by n matrix being decomposed. Q is an orthogonal matrix. R is upper triangular matrix.
@author Peter Abeles

    @Test
    public void modifiesA(){
        BlockMatrix64F A = createMatrixSPD(4);
        BlockMatrix64F A_orig = A.copy();


        BlockQrHouseHolderSolver solver = new BlockQrHouseHolderSolver();


        assertTrue(solver.setA(A));


        boolean modified = !MatrixFeatures.isEquals(A,A_orig);


        assertTrue(modified == solver.modifiesA());
    }

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    @Test
    public void modifiesB(){
        BlockMatrix64F A = createMatrixSPD(4);


        BlockQrHouseHolderSolver solver = new BlockQrHouseHolderSolver();


        assertTrue(solver.setA(A));


        BlockMatrix64F B = BlockMatrixOps.createRandom(4,2,-1,1,rand,3);
        BlockMatrix64F B_orig = B.copy();
        BlockMatrix64F X = new BlockMatrix64F(A.numRows,B.numCols,3);


        solver.solve(B,X);


        boolean modified = !MatrixFeatures.isEquals(B_orig,B);


        assertTrue(modified == solver.modifiesB());
    }

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 * @author Peter Abeles
 */
public class LinearSolverQrBlock64 extends WrapLinearSolverBlock64 {


    public LinearSolverQrBlock64() {
        super(new BlockQrHouseHolderSolver());
    }

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Related Classes of org.ejml.alg.block.linsol.qr.BlockQrHouseHolderSolver

org.ejml.alg.block.linsol.chol.TestBlockCholeskyOuterSolver

org.ejml.alg.dense.linsol.qr.LinearSolverQrBlock64

org.ejml.data.D1Submatrix64F

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