1 files changed, 79 insertions, 0 deletions
diff --git a/lapack/eigenvalues.cpp b/lapack/eigenvalues.cpp
new file mode 100644
index 000000000..a1526ebcd
--- /dev/null
+++ b/lapack/eigenvalues.cpp
@@ -0,0 +1,79 @@
+// 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 "common.h"
+#include <Eigen/Eigenvalues>
+
+// computes an LU factorization of a general M-by-N matrix A using partial pivoting with row interchanges
+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 nb = ILAENV( 1, 'SSYTRD', UPLO, N, -1, -1, -1 )
+//          LWKOPT = MAX( 1, ( NB+2 )*N )
+//          WORK( 1 ) = LWKOPT
+// *
+//          IF( LWORK.LT.MAX( 1, 3*N-1 ) .AND. .NOT.LQUERY )
+//      $      INFO = -8
+//       END IF
+// *
+//       IF( INFO.NE.0 ) THEN
+//          CALL XERBLA( 'SSYEV ', -INFO )
+//          RETURN
+//       ELSE IF( LQUERY ) THEN
+//          RETURN
+//       END IF
+  
+  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)
+  {
+    vector(w,*n).setZero();
+    if(computeVectors)
+      matrix(a,*n,*n,*lda).setIdentity();
+    //*info = 1;
+    return 0;
+  }
+  
+  vector(w,*n) = eig.eigenvalues();
+  if(computeVectors)
+    matrix(a,*n,*n,*lda) = eig.eigenvectors();
+  
+  return 0;
+}