diff options
Diffstat (limited to 'Eigen/src/QR/Tridiagonalization.h')
| -rw-r--r-- | Eigen/src/QR/Tridiagonalization.h | 9 |
1 files changed, 5 insertions, 4 deletions
diff --git a/Eigen/src/QR/Tridiagonalization.h b/Eigen/src/QR/Tridiagonalization.h index a9635c961..a4fa32ed4 100644 --- a/Eigen/src/QR/Tridiagonalization.h +++ b/Eigen/src/QR/Tridiagonalization.h @@ -26,6 +26,7 @@ #define EIGEN_TRIDIAGONALIZATION_H /** \ingroup QR_Module + * \nonstableyet * * \class Tridiagonalization * @@ -219,7 +220,7 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& // i.e., A = H' A H where H = I - h v v' and v = matA.col(i).end(n-i-1) matA.col(i).coeffRef(i+1) = 1; - + /* This is the initial algorithm which minimize operation counts and maximize * the use of Eigen's expression. Unfortunately, the first matrix-vector product * using Part<Lower|Selfadjoint> is very very slow */ @@ -284,7 +285,7 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& hCoeffs.end(n-i-1) += (h * Scalar(-0.5) * matA.col(i).end(n-i-1).dot(hCoeffs.end(n-i-1))) * matA.col(i).end(n-i-1); - + const Scalar* EIGEN_RESTRICT pb = &matA.coeffRef(0,i); const Scalar* EIGEN_RESTRICT pa = (&hCoeffs.coeffRef(0)) - 1; for (int j1=i+1; j1<n; ++j1) @@ -295,11 +296,11 @@ void Tridiagonalization<MatrixType>::_compute(MatrixType& matA, CoeffVectorType& { int alignedStart = (starti) + ei_alignmentOffset(&matA.coeffRef(starti,j1), n-starti); alignedEnd = alignedStart + ((n-alignedStart)/PacketSize)*PacketSize; - + for (int i1=starti; i1<alignedStart; ++i1) matA.coeffRef(i1,j1) -= matA.coeff(i1,i)*ei_conj(hCoeffs.coeff(j1-1)) + hCoeffs.coeff(i1-1)*ei_conj(matA.coeff(j1,i)); - + Packet tmp0 = ei_pset1(hCoeffs.coeff(j1-1)); Packet tmp1 = ei_pset1(matA.coeff(j1,i)); Scalar* pc = &matA.coeffRef(0,j1); |