| // 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; | 
 | } |