Integrating Doxygen in comments

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diff --git a/SRC/spteqr.f b/SRC/spteqr.f
index 3407e44d..4f8fd565 100644
--- a/SRC/spteqr.f
+++ b/SRC/spteqr.f
@@ -1,9 +1,146 @@
+*> \brief \b SPTEQR
+*
+*  =========== DOCUMENTATION ===========
+*
+* Online html documentation available at 
+*            http://www.netlib.org/lapack/explore-html/ 
+*
+*  Definition
+*  ==========
+*
+*       SUBROUTINE SPTEQR( COMPZ, N, D, E, Z, LDZ, WORK, INFO )
+* 
+*       .. Scalar Arguments ..
+*       CHARACTER          COMPZ
+*       INTEGER            INFO, LDZ, N
+*       ..
+*       .. Array Arguments ..
+*       REAL               D( * ), E( * ), WORK( * ), Z( LDZ, * )
+*       ..
+*  
+*  Purpose
+*  =======
+*
+*>\details \b Purpose:
+*>\verbatim
+*>
+*> SPTEQR computes all eigenvalues and, optionally, eigenvectors of a
+*> symmetric positive definite tridiagonal matrix by first factoring the
+*> matrix using SPTTRF, and then calling SBDSQR to compute the singular
+*> values of the bidiagonal factor.
+*>
+*> This routine computes the eigenvalues of the positive definite
+*> tridiagonal matrix to high relative accuracy.  This means that if the
+*> eigenvalues range over many orders of magnitude in size, then the
+*> small eigenvalues and corresponding eigenvectors will be computed
+*> more accurately than, for example, with the standard QR method.
+*>
+*> The eigenvectors of a full or band symmetric positive definite matrix
+*> can also be found if SSYTRD, SSPTRD, or SSBTRD has been used to
+*> reduce this matrix to tridiagonal form. (The reduction to tridiagonal
+*> form, however, may preclude the possibility of obtaining high
+*> relative accuracy in the small eigenvalues of the original matrix, if
+*> these eigenvalues range over many orders of magnitude.)
+*>
+*>\endverbatim
+*
+*  Arguments
+*  =========
+*
+*> \param[in] COMPZ
+*> \verbatim
+*>          COMPZ is CHARACTER*1
+*>          = 'N':  Compute eigenvalues only.
+*>          = 'V':  Compute eigenvectors of original symmetric
+*>                  matrix also.  Array Z contains the orthogonal
+*>                  matrix used to reduce the original matrix to
+*>                  tridiagonal form.
+*>          = 'I':  Compute eigenvectors of tridiagonal matrix also.
+*> \endverbatim
+*>
+*> \param[in] N
+*> \verbatim
+*>          N is INTEGER
+*>          The order of the matrix.  N >= 0.
+*> \endverbatim
+*>
+*> \param[in,out] D
+*> \verbatim
+*>          D is REAL array, dimension (N)
+*>          On entry, the n diagonal elements of the tridiagonal
+*>          matrix.
+*>          On normal exit, D contains the eigenvalues, in descending
+*>          order.
+*> \endverbatim
+*>
+*> \param[in,out] E
+*> \verbatim
+*>          E is REAL array, dimension (N-1)
+*>          On entry, the (n-1) subdiagonal elements of the tridiagonal
+*>          matrix.
+*>          On exit, E has been destroyed.
+*> \endverbatim
+*>
+*> \param[in,out] Z
+*> \verbatim
+*>          Z is REAL array, dimension (LDZ, N)
+*>          On entry, if COMPZ = 'V', the orthogonal matrix used in the
+*>          reduction to tridiagonal form.
+*>          On exit, if COMPZ = 'V', the orthonormal eigenvectors of the
+*>          original symmetric matrix;
+*>          if COMPZ = 'I', the orthonormal eigenvectors of the
+*>          tridiagonal matrix.
+*>          If INFO > 0 on exit, Z contains the eigenvectors associated
+*>          with only the stored eigenvalues.
+*>          If  COMPZ = 'N', then Z is not referenced.
+*> \endverbatim
+*>
+*> \param[in] LDZ
+*> \verbatim
+*>          LDZ is INTEGER
+*>          The leading dimension of the array Z.  LDZ >= 1, and if
+*>          COMPZ = 'V' or 'I', LDZ >= max(1,N).
+*> \endverbatim
+*>
+*> \param[out] WORK
+*> \verbatim
+*>          WORK is REAL array, dimension (4*N)
+*> \endverbatim
+*>
+*> \param[out] INFO
+*> \verbatim
+*>          INFO is INTEGER
+*>          = 0:  successful exit.
+*>          < 0:  if INFO = -i, the i-th argument had an illegal value.
+*>          > 0:  if INFO = i, and i is:
+*>                <= N  the Cholesky factorization of the matrix could
+*>                      not be performed because the i-th principal minor
+*>                      was not positive definite.
+*>                > N   the SVD algorithm failed to converge;
+*>                      if INFO = N+i, i off-diagonal elements of the
+*>                      bidiagonal factor did not converge to zero.
+*> \endverbatim
+*>
+*
+*  Authors
+*  =======
+*
+*> \author Univ. of Tennessee 
+*> \author Univ. of California Berkeley 
+*> \author Univ. of Colorado Denver 
+*> \author NAG Ltd. 
+*
+*> \date November 2011
+*
+*> \ingroup realOTHERcomputational
+*
+*  =====================================================================
       SUBROUTINE SPTEQR( COMPZ, N, D, E, Z, LDZ, WORK, INFO )
 *
-*  -- LAPACK routine (version 3.2) --
+*  -- LAPACK computational routine (version 3.2) --
 *  -- LAPACK is a software package provided by Univ. of Tennessee,    --
 *  -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
-*     November 2006
+*     November 2011
 *
 *     .. Scalar Arguments ..
       CHARACTER          COMPZ
@@ -13,80 +150,6 @@
       REAL               D( * ), E( * ), WORK( * ), Z( LDZ, * )
 *     ..
 *
-*  Purpose
-*  =======
-*
-*  SPTEQR computes all eigenvalues and, optionally, eigenvectors of a
-*  symmetric positive definite tridiagonal matrix by first factoring the
-*  matrix using SPTTRF, and then calling SBDSQR to compute the singular
-*  values of the bidiagonal factor.
-*
-*  This routine computes the eigenvalues of the positive definite
-*  tridiagonal matrix to high relative accuracy.  This means that if the
-*  eigenvalues range over many orders of magnitude in size, then the
-*  small eigenvalues and corresponding eigenvectors will be computed
-*  more accurately than, for example, with the standard QR method.
-*
-*  The eigenvectors of a full or band symmetric positive definite matrix
-*  can also be found if SSYTRD, SSPTRD, or SSBTRD has been used to
-*  reduce this matrix to tridiagonal form. (The reduction to tridiagonal
-*  form, however, may preclude the possibility of obtaining high
-*  relative accuracy in the small eigenvalues of the original matrix, if
-*  these eigenvalues range over many orders of magnitude.)
-*
-*  Arguments
-*  =========
-*
-*  COMPZ   (input) CHARACTER*1
-*          = 'N':  Compute eigenvalues only.
-*          = 'V':  Compute eigenvectors of original symmetric
-*                  matrix also.  Array Z contains the orthogonal
-*                  matrix used to reduce the original matrix to
-*                  tridiagonal form.
-*          = 'I':  Compute eigenvectors of tridiagonal matrix also.
-*
-*  N       (input) INTEGER
-*          The order of the matrix.  N >= 0.
-*
-*  D       (input/output) REAL array, dimension (N)
-*          On entry, the n diagonal elements of the tridiagonal
-*          matrix.
-*          On normal exit, D contains the eigenvalues, in descending
-*          order.
-*
-*  E       (input/output) REAL array, dimension (N-1)
-*          On entry, the (n-1) subdiagonal elements of the tridiagonal
-*          matrix.
-*          On exit, E has been destroyed.
-*
-*  Z       (input/output) REAL array, dimension (LDZ, N)
-*          On entry, if COMPZ = 'V', the orthogonal matrix used in the
-*          reduction to tridiagonal form.
-*          On exit, if COMPZ = 'V', the orthonormal eigenvectors of the
-*          original symmetric matrix;
-*          if COMPZ = 'I', the orthonormal eigenvectors of the
-*          tridiagonal matrix.
-*          If INFO > 0 on exit, Z contains the eigenvectors associated
-*          with only the stored eigenvalues.
-*          If  COMPZ = 'N', then Z is not referenced.
-*
-*  LDZ     (input) INTEGER
-*          The leading dimension of the array Z.  LDZ >= 1, and if
-*          COMPZ = 'V' or 'I', LDZ >= max(1,N).
-*
-*  WORK    (workspace) REAL array, dimension (4*N)
-*
-*  INFO    (output) INTEGER
-*          = 0:  successful exit.
-*          < 0:  if INFO = -i, the i-th argument had an illegal value.
-*          > 0:  if INFO = i, and i is:
-*                <= N  the Cholesky factorization of the matrix could
-*                      not be performed because the i-th principal minor
-*                      was not positive definite.
-*                > N   the SVD algorithm failed to converge;
-*                      if INFO = N+i, i off-diagonal elements of the
-*                      bidiagonal factor did not converge to zero.
-*
 *  =====================================================================
 *
 *     .. Parameters ..