diff options
Diffstat (limited to 'Eigen/src/Eigenvalues/EigenSolver.h')
| -rw-r--r-- | Eigen/src/Eigenvalues/EigenSolver.h | 6 |
1 files changed, 3 insertions, 3 deletions
diff --git a/Eigen/src/Eigenvalues/EigenSolver.h b/Eigen/src/Eigenvalues/EigenSolver.h index f98e54712..3f9e30a6e 100644 --- a/Eigen/src/Eigenvalues/EigenSolver.h +++ b/Eigen/src/Eigenvalues/EigenSolver.h @@ -225,7 +225,7 @@ void EigenSolver<MatrixType>::orthes(MatrixType& matH, RealVectorType& ort) for (int m = low+1; m <= high-1; ++m) { // Scale column. - RealScalar scale = matH.block(m, m-1, high-m+1, 1).cwise().abs().sum(); + RealScalar scale = matH.block(m, m-1, high-m+1, 1).cwiseAbs().sum(); if (scale != 0.0) { // Compute Householder transformation. @@ -312,7 +312,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) // Store roots isolated by balanc and compute matrix norm // FIXME to be efficient the following would requires a triangular reduxion code - // Scalar norm = matH.upper().cwise().abs().sum() + matH.corner(BottomLeft,n,n).diagonal().cwise().abs().sum(); + // Scalar norm = matH.upper().cwiseAbs().sum() + matH.corner(BottomLeft,n,n).diagonal().cwiseAbs().sum(); Scalar norm = 0.0; for (int j = 0; j < nn; ++j) { @@ -321,7 +321,7 @@ void EigenSolver<MatrixType>::hqr2(MatrixType& matH) { m_eivalues.coeffRef(j) = Complex(matH.coeff(j,j), 0.0); } - norm += matH.row(j).segment(std::max(j-1,0), nn-std::max(j-1,0)).cwise().abs().sum(); + norm += matH.row(j).segment(std::max(j-1,0), nn-std::max(j-1,0)).cwiseAbs().sum(); } // Outer loop over eigenvalue index |