Cross Reference: /external/eigen/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h

Lines Matching refs:eigenvalues
27     return ComplexEigenSolver<PlainObject>(m_eval, false).eigenvalues();
39     return EigenSolver<PlainObject>(m_eval, false).eigenvalues();
45 /** \brief Computes the eigenvalues of a matrix 
46   * \returns Column vector containing the eigenvalues.
49   * This function computes the eigenvalues with the help of the EigenSolver
53   * The eigenvalues are repeated according to their algebraic multiplicity,
54   * so there are as many eigenvalues as rows in the matrix.
62   * \sa EigenSolver::eigenvalues(), ComplexEigenSolver::eigenvalues(),
63   *     SelfAdjointView::eigenvalues()
67 MatrixBase<Derived>::eigenvalues() const
73 /** \brief Computes the eigenvalues of a matrix
74   * \returns Column vector containing the eigenvalues.
77   * This function computes the eigenvalues with the help of the
78   * SelfAdjointEigenSolver class.  The eigenvalues are repeated according to
79   * their algebraic multiplicity, so there are as many eigenvalues as rows in
85   * \sa SelfAdjointEigenSolver::eigenvalues(), MatrixBase::eigenvalues()
89 SelfAdjointView<MatrixType, UpLo>::eigenvalues() const
93   return SelfAdjointEigenSolver<PlainObject>(thisAsMatrix, false).eigenvalues();
110   * The current implementation uses the eigenvalues of \f$ A^*A \f$, as computed
111   * by SelfAdjointView::eigenvalues(), to compute the operator norm of a
118   * \sa SelfAdjointView::eigenvalues(), SelfAdjointView::operatorNorm()
126   // FIXME if it is really guaranteed that the eigenvalues are already sorted,
131 		 .eigenvalues()
143   * The current implementation uses the eigenvalues of the matrix, as computed
144   * by eigenvalues(), to compute the operator norm of the matrix.
149   * \sa eigenvalues(), MatrixBase::operatorNorm()
155   return eigenvalues().cwiseAbs().maxCoeff();