| Brian Silverman | 72890c2 | 2015-09-19 14:37:37 -0400 | [diff] [blame] | 1 | // This file is part of Eigen, a lightweight C++ template library |
| 2 | // for linear algebra. |
| 3 | // |
| 4 | // Copyright (C) 2011 Gael Guennebaud <gael.guennebaud@inria.fr> |
| 5 | // |
| 6 | // This Source Code Form is subject to the terms of the Mozilla |
| 7 | // Public License v. 2.0. If a copy of the MPL was not distributed |
| 8 | // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. |
| 9 | |
| 10 | #include "common.h" |
| 11 | #include <Eigen/Eigenvalues> |
| 12 | |
| 13 | // computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges |
| 14 | EIGEN_LAPACK_FUNC(syev,(char *jobz, char *uplo, int* n, Scalar* a, int *lda, Scalar* w, Scalar* /*work*/, int* lwork, int *info)) |
| 15 | { |
| 16 | // TODO exploit the work buffer |
| 17 | bool query_size = *lwork==-1; |
| 18 | |
| 19 | *info = 0; |
| 20 | if(*jobz!='N' && *jobz!='V') *info = -1; |
| 21 | else if(UPLO(*uplo)==INVALID) *info = -2; |
| 22 | else if(*n<0) *info = -3; |
| 23 | else if(*lda<std::max(1,*n)) *info = -5; |
| 24 | else if((!query_size) && *lwork<std::max(1,3**n-1)) *info = -8; |
| 25 | |
| 26 | // if(*info==0) |
| 27 | // { |
| 28 | // int nb = ILAENV( 1, 'SSYTRD', UPLO, N, -1, -1, -1 ) |
| 29 | // LWKOPT = MAX( 1, ( NB+2 )*N ) |
| 30 | // WORK( 1 ) = LWKOPT |
| 31 | // * |
| 32 | // IF( LWORK.LT.MAX( 1, 3*N-1 ) .AND. .NOT.LQUERY ) |
| 33 | // $ INFO = -8 |
| 34 | // END IF |
| 35 | // * |
| 36 | // IF( INFO.NE.0 ) THEN |
| 37 | // CALL XERBLA( 'SSYEV ', -INFO ) |
| 38 | // RETURN |
| 39 | // ELSE IF( LQUERY ) THEN |
| 40 | // RETURN |
| 41 | // END IF |
| 42 | |
| 43 | if(*info!=0) |
| 44 | { |
| 45 | int e = -*info; |
| 46 | return xerbla_(SCALAR_SUFFIX_UP"SYEV ", &e, 6); |
| 47 | } |
| 48 | |
| 49 | if(query_size) |
| 50 | { |
| 51 | *lwork = 0; |
| 52 | return 0; |
| 53 | } |
| 54 | |
| 55 | if(*n==0) |
| 56 | return 0; |
| 57 | |
| 58 | PlainMatrixType mat(*n,*n); |
| 59 | if(UPLO(*uplo)==UP) mat = matrix(a,*n,*n,*lda).adjoint(); |
| 60 | else mat = matrix(a,*n,*n,*lda); |
| 61 | |
| 62 | bool computeVectors = *jobz=='V' || *jobz=='v'; |
| 63 | SelfAdjointEigenSolver<PlainMatrixType> eig(mat,computeVectors?ComputeEigenvectors:EigenvaluesOnly); |
| 64 | |
| 65 | if(eig.info()==NoConvergence) |
| 66 | { |
| 67 | vector(w,*n).setZero(); |
| 68 | if(computeVectors) |
| 69 | matrix(a,*n,*n,*lda).setIdentity(); |
| 70 | //*info = 1; |
| 71 | return 0; |
| 72 | } |
| 73 | |
| 74 | vector(w,*n) = eig.eigenvalues(); |
| 75 | if(computeVectors) |
| 76 | matrix(a,*n,*n,*lda) = eig.eigenvectors(); |
| 77 | |
| 78 | return 0; |
| 79 | } |