diff options
| -rw-r--r-- | Eigen/src/Eigenvalues/GeneralizedEigenSolver.h | 26 | ||||
| -rw-r--r-- | doc/snippets/GeneralizedEigenSolver.cpp | 7 |
2 files changed, 15 insertions, 18 deletions
diff --git a/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h b/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h index 8734bb276..0075880fe 100644 --- a/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h +++ b/Eigen/src/Eigenvalues/GeneralizedEigenSolver.h @@ -18,7 +18,7 @@ namespace Eigen { /** \eigenvalues_module \ingroup Eigenvalues_Module * * - * \class EigenSolver + * \class GeneralizedEigenSolver * * \brief Computes the generalized eigenvalues and eigenvectors of a pair of general matrices * @@ -48,8 +48,9 @@ namespace Eigen { * eigenvectors are computed, they can be retrieved with the eigenvalues() and * eigenvectors() functions. * - * The documentation for GeneralizedEigenSolver(const MatrixType&, const MatrixType&, bool) contains an - * example of the typical use of this class. + * Here is an usage example of this class: + * Example: \include GeneralizedEigenSolver.cpp + * Output: \verbinclude GeneralizedEigenSolver.out * * \sa MatrixBase::eigenvalues(), class ComplexEigenSolver, class SelfAdjointEigenSolver */ @@ -142,9 +143,6 @@ template<typename _MatrixType> class GeneralizedEigenSolver * This constructor calls compute() to compute the generalized eigenvalues * and eigenvectors. * - * Example: \include GeneralizedEigenSolver_GeneralizedEigenSolver_MatrixType.cpp - * Output: \verbinclude GeneralizedEigenSolver_GeneralizedEigenSolver_MatrixType.out - * * \sa compute() */ GeneralizedEigenSolver(const MatrixType& A, const MatrixType& B, bool computeEigenvectors = true) @@ -160,7 +158,7 @@ template<typename _MatrixType> class GeneralizedEigenSolver compute(A, B, computeEigenvectors); } - /** \brief Returns the computed generalized eigenvectors. + /* \brief Returns the computed generalized eigenvectors. * * \returns %Matrix whose columns are the (possibly complex) eigenvectors. * @@ -175,12 +173,9 @@ template<typename _MatrixType> class GeneralizedEigenSolver * matrix returned by this function is the matrix \f$ V \f$ in the * generalized eigendecomposition \f$ A = B V D V^{-1} \f$, if it exists. * - * Example: \include GeneralizedEigenSolver_eigenvectors.cpp - * Output: \verbinclude GeneralizedEigenSolver_eigenvectors.out - * * \sa eigenvalues() */ - //EigenvectorsType eigenvectors() const; +// EigenvectorsType eigenvectors() const; /** \brief Returns an expression of the computed generalized eigenvalues. * @@ -198,9 +193,6 @@ template<typename _MatrixType> class GeneralizedEigenSolver * so there are as many eigenvalues as rows in the matrix. The eigenvalues * are not sorted in any particular order. * - * Example: \include GeneralizedEigenSolver_eigenvalues.cpp - * Output: \verbinclude GeneralizedEigenSolver_eigenvalues.out - * * \sa alphas(), betas(), eigenvectors() */ EigenvalueType eigenvalues() const @@ -253,9 +245,6 @@ template<typename _MatrixType> class GeneralizedEigenSolver * generalized Schur decomposition. * * This method reuses of the allocated data in the GeneralizedEigenSolver object. - * - * Example: \include GeneralizedEigenSolver_compute.cpp - * Output: \verbinclude GeneralizedEigenSolver_compute.out */ GeneralizedEigenSolver& compute(const MatrixType& A, const MatrixType& B, bool computeEigenvectors = true); @@ -310,6 +299,8 @@ GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixTyp if (m_realQZ.info() == Success) { m_matS = m_realQZ.matrixS(); + if (computeEigenvectors) + m_eivec = m_realQZ.matrixZ().transpose(); // Compute eigenvalues from matS m_alphas.resize(A.cols()); @@ -343,7 +334,6 @@ GeneralizedEigenSolver<MatrixType>::compute(const MatrixType& A, const MatrixTyp return *this; } - } // end namespace Eigen #endif // EIGEN_GENERALIZEDEIGENSOLVER_H diff --git a/doc/snippets/GeneralizedEigenSolver.cpp b/doc/snippets/GeneralizedEigenSolver.cpp new file mode 100644 index 000000000..2acda45fa --- /dev/null +++ b/doc/snippets/GeneralizedEigenSolver.cpp @@ -0,0 +1,7 @@ +GeneralizedEigenSolver<MatrixXf> ges; +MatrixXf A = MatrixXf::Random(4,4); +MatrixXf B = MatrixXf::Random(4,4); +ges.compute(A, B); +cout << "The (complex) numerators of the generalzied eigenvalues are: " << ges.alphas().transpose() << endl; +cout << "The (real) denominatore of the generalzied eigenvalues are: " << ges.betas().transpose() << endl; +cout << "The (complex) generalzied eigenvalues are (alphas./beta): " << ges.eigenvalues().transpose() << endl; |