|  | // This file is part of Eigen, a lightweight C++ template library | 
|  | // for linear algebra. | 
|  | // | 
|  | // Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr> | 
|  | // | 
|  | // This Source Code Form is subject to the terms of the Mozilla | 
|  | // Public License v. 2.0. If a copy of the MPL was not distributed | 
|  | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. | 
|  |  | 
|  | #include "lapack_common.h" | 
|  | #include <Eigen/Eigenvalues> | 
|  |  | 
|  | // computes eigen values and vectors of a general N-by-N matrix A | 
|  | EIGEN_LAPACK_FUNC(syev,(char *jobz, char *uplo, int* n, Scalar* a, int *lda, Scalar* w, Scalar* /*work*/, int* lwork, int *info)) | 
|  | { | 
|  | // TODO exploit the work buffer | 
|  | bool query_size = *lwork==-1; | 
|  |  | 
|  | *info = 0; | 
|  | if(*jobz!='N' && *jobz!='V')                    *info = -1; | 
|  | else  if(UPLO(*uplo)==INVALID)                        *info = -2; | 
|  | else  if(*n<0)                                        *info = -3; | 
|  | else  if(*lda<std::max(1,*n))                         *info = -5; | 
|  | else  if((!query_size) && *lwork<std::max(1,3**n-1))  *info = -8; | 
|  |  | 
|  | if(*info!=0) | 
|  | { | 
|  | int e = -*info; | 
|  | return xerbla_(SCALAR_SUFFIX_UP"SYEV ", &e, 6); | 
|  | } | 
|  |  | 
|  | if(query_size) | 
|  | { | 
|  | *lwork = 0; | 
|  | return 0; | 
|  | } | 
|  |  | 
|  | if(*n==0) | 
|  | return 0; | 
|  |  | 
|  | PlainMatrixType mat(*n,*n); | 
|  | if(UPLO(*uplo)==UP) mat = matrix(a,*n,*n,*lda).adjoint(); | 
|  | else                mat = matrix(a,*n,*n,*lda); | 
|  |  | 
|  | bool computeVectors = *jobz=='V' || *jobz=='v'; | 
|  | SelfAdjointEigenSolver<PlainMatrixType> eig(mat,computeVectors?ComputeEigenvectors:EigenvaluesOnly); | 
|  |  | 
|  | if(eig.info()==NoConvergence) | 
|  | { | 
|  | make_vector(w,*n).setZero(); | 
|  | if(computeVectors) | 
|  | matrix(a,*n,*n,*lda).setIdentity(); | 
|  | //*info = 1; | 
|  | return 0; | 
|  | } | 
|  |  | 
|  | make_vector(w,*n) = eig.eigenvalues(); | 
|  | if(computeVectors) | 
|  | matrix(a,*n,*n,*lda) = eig.eigenvectors(); | 
|  |  | 
|  | return 0; | 
|  | } |