devtools/eigen
1
0
Fork 0
mirror of https://gitlab.com/libeigen/eigen.git synced 2026-04-10 11:34:33 +08:00
Code Issues Packages Projects Releases Wiki Activity

Extend unit test and documentation of SelfAdjointEigenSolver::computeDirect

Browse Source
This commit is contained in:
Gael Guennebaud
2015-06-08 16:16:42 +02:00
parent 913a61870d
commit cd8b996f99
2 changed files with 29 additions and 13 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
View File

@@ -198,17 +198,21 @@ template<typename _MatrixType> class SelfAdjointEigenSolver
EIGEN_DEVICE_FUNC
SelfAdjointEigenSolver& compute(const MatrixType& matrix, int options = ComputeEigenvectors);
/** \brief Computes eigendecomposition of given matrix using a direct algorithm
/** \brief Computes eigendecomposition of given matrix using a closed-form algorithm
*
* This is a variant of compute(const MatrixType&, int options) which
* directly solves the underlying polynomial equation.
*
* Currently only 3x3 matrices for which the sizes are known at compile time are supported (e.g., Matrix3d).
* Currently only 2x2 and 3x3 matrices for which the sizes are known at compile time are supported (e.g., Matrix3d).
*
* This method is usually significantly faster than the QR algorithm
* This method is usually significantly faster than the QR iterative algorithm
* but it might also be less accurate. It is also worth noting that
* for 3x3 matrices it involves trigonometric operations which are
* not necessarily available for all scalar types.
*
* For the 3x3 case, we observed the following worst case relative error regarding the eigenvalues:
* - double: 1e-8
* - float: 1e-3
*
* \sa compute(const MatrixType&, int options)
*/