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-rw-r--r--Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h10
1 files changed, 7 insertions, 3 deletions
diff --git a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
index 1830b99c1..27a014a96 100644
--- a/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
+++ b/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h
@@ -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)
*/