diff options
Diffstat (limited to 'extern/Eigen3/Eigen/src/Eigenvalues')
-rw-r--r-- | extern/Eigen3/Eigen/src/Eigenvalues/EigenSolver.h | 9 | ||||
-rw-r--r-- | extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h | 12 |
2 files changed, 12 insertions, 9 deletions
diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/EigenSolver.h b/extern/Eigen3/Eigen/src/Eigenvalues/EigenSolver.h index ac4c4242dd4..f57353c065f 100644 --- a/extern/Eigen3/Eigen/src/Eigenvalues/EigenSolver.h +++ b/extern/Eigen3/Eigen/src/Eigenvalues/EigenSolver.h @@ -291,7 +291,7 @@ template<typename _MatrixType> class EigenSolver ComputationInfo info() const { - eigen_assert(m_isInitialized && "ComplexEigenSolver is not initialized."); + eigen_assert(m_isInitialized && "EigenSolver is not initialized."); return m_realSchur.info(); } @@ -339,7 +339,7 @@ typename EigenSolver<MatrixType>::EigenvectorsType EigenSolver<MatrixType>::eige EigenvectorsType matV(n,n); for (Index j=0; j<n; ++j) { - if (internal::isMuchSmallerThan(internal::imag(m_eivalues.coeff(j)), internal::real(m_eivalues.coeff(j)))) + if (internal::isMuchSmallerThan(internal::imag(m_eivalues.coeff(j)), internal::real(m_eivalues.coeff(j))) || j+1==n) { // we have a real eigen value matV.col(j) = m_eivec.col(j).template cast<ComplexScalar>(); @@ -570,10 +570,13 @@ void EigenSolver<MatrixType>::doComputeEigenvectors() } } + + // We handled a pair of complex conjugate eigenvalues, so need to skip them both + n--; } else { - eigen_assert("Internal bug in EigenSolver"); // this should not happen + eigen_assert(0 && "Internal bug in EigenSolver"); // this should not happen } } diff --git a/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h b/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h index 965dda88bda..ad107c63282 100644 --- a/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h +++ b/extern/Eigen3/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h @@ -307,7 +307,8 @@ template<typename _MatrixType> class SelfAdjointEigenSolver /** \brief Maximum number of iterations. * - * Maximum number of iterations allowed for an eigenvalue to converge. + * The algorithm terminates if it does not converge within m_maxIterations * n iterations, where n + * denotes the size of the matrix. This value is currently set to 30 (copied from LAPACK). */ static const int m_maxIterations = 30; @@ -407,7 +408,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType> Index end = n-1; Index start = 0; - Index iter = 0; // number of iterations we are working on one element + Index iter = 0; // total number of iterations while (end>0) { @@ -418,15 +419,14 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType> // find the largest unreduced block while (end>0 && m_subdiag[end-1]==0) { - iter = 0; end--; } if (end<=0) break; - // if we spent too many iterations on the current element, we give up + // if we spent too many iterations, we give up iter++; - if(iter > m_maxIterations) break; + if(iter > m_maxIterations * n) break; start = end - 1; while (start>0 && m_subdiag[start-1]!=0) @@ -435,7 +435,7 @@ SelfAdjointEigenSolver<MatrixType>& SelfAdjointEigenSolver<MatrixType> internal::tridiagonal_qr_step<MatrixType::Flags&RowMajorBit ? RowMajor : ColMajor>(diag.data(), m_subdiag.data(), start, end, computeEigenvectors ? m_eivec.data() : (Scalar*)0, n); } - if (iter <= m_maxIterations) + if (iter <= m_maxIterations * n) m_info = Success; else m_info = NoConvergence; |