|  | // 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); | 
|  | } | 
|  |  | 
|  | if (query_size) { | 
|  | *lwork = 0; | 
|  | return; | 
|  | } | 
|  |  | 
|  | if (*n == 0) return; | 
|  |  | 
|  | 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'; | 
|  | Eigen::SelfAdjointEigenSolver<PlainMatrixType> eig( | 
|  | mat, computeVectors ? Eigen::ComputeEigenvectors : Eigen::EigenvaluesOnly); | 
|  |  | 
|  | if (eig.info() == Eigen::NoConvergence) { | 
|  | make_vector(w, *n).setZero(); | 
|  | if (computeVectors) matrix(a, *n, *n, *lda).setIdentity(); | 
|  | //*info = 1; | 
|  | return; | 
|  | } | 
|  |  | 
|  | make_vector(w, *n) = eig.eigenvalues(); | 
|  | if (computeVectors) matrix(a, *n, *n, *lda) = eig.eigenvectors(); | 
|  | } |