diff options
Diffstat (limited to 'Eigen/src/Eigenvalues')
-rw-r--r-- | Eigen/src/Eigenvalues/ComplexEigenSolver.h | 6 | ||||
-rw-r--r-- | Eigen/src/Eigenvalues/RealSchur.h | 12 |
2 files changed, 16 insertions, 2 deletions
diff --git a/Eigen/src/Eigenvalues/ComplexEigenSolver.h b/Eigen/src/Eigenvalues/ComplexEigenSolver.h index ec3b1633e..dc5fae06a 100644 --- a/Eigen/src/Eigenvalues/ComplexEigenSolver.h +++ b/Eigen/src/Eigenvalues/ComplexEigenSolver.h @@ -250,7 +250,7 @@ template<typename _MatrixType> class ComplexEigenSolver EigenvectorType m_matX; private: - void doComputeEigenvectors(const RealScalar& matrixnorm); + void doComputeEigenvectors(RealScalar matrixnorm); void sortEigenvalues(bool computeEigenvectors); }; @@ -284,10 +284,12 @@ ComplexEigenSolver<MatrixType>::compute(const EigenBase<InputType>& matrix, bool template<typename MatrixType> -void ComplexEigenSolver<MatrixType>::doComputeEigenvectors(const RealScalar& matrixnorm) +void ComplexEigenSolver<MatrixType>::doComputeEigenvectors(RealScalar matrixnorm) { const Index n = m_eivalues.size(); + matrixnorm = numext::maxi(matrixnorm,(std::numeric_limits<RealScalar>::min)()); + // Compute X such that T = X D X^(-1), where D is the diagonal of T. // The matrix X is unit triangular. m_matX = EigenvectorType::Zero(n, n); diff --git a/Eigen/src/Eigenvalues/RealSchur.h b/Eigen/src/Eigenvalues/RealSchur.h index d6a339f07..f5c86041d 100644 --- a/Eigen/src/Eigenvalues/RealSchur.h +++ b/Eigen/src/Eigenvalues/RealSchur.h @@ -248,12 +248,24 @@ template<typename MatrixType> template<typename InputType> RealSchur<MatrixType>& RealSchur<MatrixType>::compute(const EigenBase<InputType>& matrix, bool computeU) { + const Scalar considerAsZero = (std::numeric_limits<Scalar>::min)(); + eigen_assert(matrix.cols() == matrix.rows()); Index maxIters = m_maxIters; if (maxIters == -1) maxIters = m_maxIterationsPerRow * matrix.rows(); Scalar scale = matrix.derived().cwiseAbs().maxCoeff(); + if(scale<considerAsZero) + { + m_matT.setZero(matrix.rows(),matrix.cols()); + if(computeU) + m_matU.setIdentity(matrix.rows(),matrix.cols()); + m_info = Success; + m_isInitialized = true; + m_matUisUptodate = computeU; + return *this; + } // Step 1. Reduce to Hessenberg form m_hess.compute(matrix.derived()/scale); |