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- /*
- 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
- ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
- WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE
- DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR
- ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES
- (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
- LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON
- ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
- (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
- SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
- ********************************************************************************
- * 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
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