33 #ifndef EIGEN_SAEIGENSOLVER_LAPACKE_H 34 #define EIGEN_SAEIGENSOLVER_LAPACKE_H 40 #define EIGEN_LAPACKE_EIG_SELFADJ(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, EIGCOLROW, LAPACKE_COLROW ) \ 41 template<> template<typename InputType> inline \ 42 SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \ 43 SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const EigenBase<InputType>& matrix, int options) \ 45 eigen_assert(matrix.cols() == matrix.rows()); \ 46 eigen_assert((options&~(EigVecMask|GenEigMask))==0 \ 47 && (options&EigVecMask)!=EigVecMask \ 48 && "invalid option parameter"); \ 49 bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; \ 50 lapack_int n = internal::convert_index<lapack_int>(matrix.cols()), lda, matrix_order, info; \ 51 m_eivalues.resize(n,1); \ 52 m_subdiag.resize(n-1); \ 57 m_eivalues.coeffRef(0,0) = numext::real(m_eivec.coeff(0,0)); \ 58 if(computeEigenvectors) m_eivec.setOnes(n,n); \ 60 m_isInitialized = true; \ 61 m_eigenvectorsOk = computeEigenvectors; \ 65 lda = internal::convert_index<lapack_int>(m_eivec.outerStride()); \ 66 matrix_order=LAPACKE_COLROW; \ 67 char jobz, uplo='L'; \ 68 jobz = computeEigenvectors ? 'V' : 'N'; \ 70 info = LAPACKE_##LAPACKE_NAME( matrix_order, jobz, uplo, n, (LAPACKE_TYPE*)m_eivec.data(), lda, (LAPACKE_RTYPE*)m_eivalues.data() ); \ 71 m_info = (info==0) ? Success : NoConvergence; \ 72 m_isInitialized = true; \ 73 m_eigenvectorsOk = computeEigenvectors; \ 90 #endif // EIGEN_SAEIGENSOLVER_H #define lapack_complex_float
std::complex< float > scomplex
std::complex< double > dcomplex
#define EIGEN_LAPACKE_EIG_SELFADJ(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, EIGCOLROW, LAPACKE_COLROW)
#define lapack_complex_double