| /* | |
| Copyright (c) 2011, Intel Corporation. All rights reserved. | |
| Redistribution and use in source and binary forms, with or without modification, | |
| are permitted provided that the following conditions are met: | |
| * Redistributions of source code must retain the above copyright notice, this | |
| list of conditions and the following disclaimer. | |
| * Redistributions in binary form must reproduce the above copyright notice, | |
| this list of conditions and the following disclaimer in the documentation | |
| and/or other materials provided with the distribution. | |
| * Neither the name of Intel Corporation nor the names of its contributors may | |
| be used to endorse or promote products derived from this software without | |
| specific prior written permission. | |
| THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND | |
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| DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR | |
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| ******************************************************************************** | |
| * Content : Eigen bindings to LAPACKe | |
| * Self-adjoint eigenvalues/eigenvectors. | |
| ******************************************************************************** | |
| */ | |
| #ifndef EIGEN_SAEIGENSOLVER_LAPACKE_H | |
| #define EIGEN_SAEIGENSOLVER_LAPACKE_H | |
| namespace Eigen { | |
| /** \internal Specialization for the data types supported by LAPACKe */ | |
| #define EIGEN_LAPACKE_EIG_SELFADJ_2(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, EIGCOLROW ) \ | |
| template<> template<typename InputType> inline \ | |
| SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >& \ | |
| SelfAdjointEigenSolver<Matrix<EIGTYPE, Dynamic, Dynamic, EIGCOLROW> >::compute(const EigenBase<InputType>& matrix, int options) \ | |
| { \ | |
| eigen_assert(matrix.cols() == matrix.rows()); \ | |
| eigen_assert((options&~(EigVecMask|GenEigMask))==0 \ | |
| && (options&EigVecMask)!=EigVecMask \ | |
| && "invalid option parameter"); \ | |
| bool computeEigenvectors = (options&ComputeEigenvectors)==ComputeEigenvectors; \ | |
| lapack_int n = internal::convert_index<lapack_int>(matrix.cols()), lda, info; \ | |
| m_eivalues.resize(n,1); \ | |
| m_subdiag.resize(n-1); \ | |
| m_eivec = matrix; \ | |
| \ | |
| if(n==1) \ | |
| { \ | |
| m_eivalues.coeffRef(0,0) = numext::real(m_eivec.coeff(0,0)); \ | |
| if(computeEigenvectors) m_eivec.setOnes(n,n); \ | |
| m_info = Success; \ | |
| m_isInitialized = true; \ | |
| m_eigenvectorsOk = computeEigenvectors; \ | |
| return *this; \ | |
| } \ | |
| \ | |
| lda = internal::convert_index<lapack_int>(m_eivec.outerStride()); \ | |
| char jobz, uplo='L'/*, range='A'*/; \ | |
| jobz = computeEigenvectors ? 'V' : 'N'; \ | |
| \ | |
| info = LAPACKE_##LAPACKE_NAME( LAPACK_COL_MAJOR, jobz, uplo, n, (LAPACKE_TYPE*)m_eivec.data(), lda, (LAPACKE_RTYPE*)m_eivalues.data() ); \ | |
| m_info = (info==0) ? Success : NoConvergence; \ | |
| m_isInitialized = true; \ | |
| m_eigenvectorsOk = computeEigenvectors; \ | |
| return *this; \ | |
| } | |
| #define EIGEN_LAPACKE_EIG_SELFADJ(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME ) \ | |
| EIGEN_LAPACKE_EIG_SELFADJ_2(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, ColMajor ) \ | |
| EIGEN_LAPACKE_EIG_SELFADJ_2(EIGTYPE, LAPACKE_TYPE, LAPACKE_RTYPE, LAPACKE_NAME, RowMajor ) | |
| EIGEN_LAPACKE_EIG_SELFADJ(double, double, double, dsyev) | |
| EIGEN_LAPACKE_EIG_SELFADJ(float, float, float, ssyev) | |
| EIGEN_LAPACKE_EIG_SELFADJ(dcomplex, lapack_complex_double, double, zheev) | |
| EIGEN_LAPACKE_EIG_SELFADJ(scomplex, lapack_complex_float, float, cheev) | |
| } // end namespace Eigen | |
| #endif // EIGEN_SAEIGENSOLVER_H |