REAL routines for symmetric matrix

ssycon

USAGE:
  rcond, info = NumRu::Lapack.ssycon( uplo, a, ipiv, anorm, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYCON( UPLO, N, A, LDA, IPIV, ANORM, RCOND, WORK, IWORK, INFO )

*  Purpose
*  =======
*
*  SSYCON estimates the reciprocal of the condition number (in the
*  1-norm) of a real symmetric matrix A using the factorization
*  A = U*D*U**T or A = L*D*L**T computed by SSYTRF.
*
*  An estimate is obtained for norm(inv(A)), and the reciprocal of the
*  condition number is computed as RCOND = 1 / (ANORM * norm(inv(A))).
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the details of the factorization are stored
*          as an upper or lower triangular matrix.
*          = 'U':  Upper triangular, form is A = U*D*U**T;
*          = 'L':  Lower triangular, form is A = L*D*L**T.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input) REAL array, dimension (LDA,N)
*          The block diagonal matrix D and the multipliers used to
*          obtain the factor U or L as computed by SSYTRF.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (input) INTEGER array, dimension (N)
*          Details of the interchanges and the block structure of D
*          as determined by SSYTRF.
*
*  ANORM   (input) REAL
*          The 1-norm of the original matrix A.
*
*  RCOND   (output) REAL
*          The reciprocal of the condition number of the matrix A,
*          computed as RCOND = 1/(ANORM * AINVNM), where AINVNM is an
*          estimate of the 1-norm of inv(A) computed in this routine.
*
*  WORK    (workspace) REAL array, dimension (2*N)
*
*  IWORK    (workspace) INTEGER array, dimension (N)
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*

*  =====================================================================
*


    
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ssyconv

USAGE:
  info = NumRu::Lapack.ssyconv( uplo, way, a, ipiv, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYCONV( UPLO, WAY, N, A, LDA, IPIV, WORK, INFO )

*  Purpose
*  =======
*
*  SSYCONV convert A given by TRF into L and D and vice-versa.
*  Get Non-diag elements of D (returned in workspace) and 
*  apply or reverse permutation done in TRF.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the details of the factorization are stored
*          as an upper or lower triangular matrix.
*          = 'U':  Upper triangular, form is A = U*D*U**T;
*          = 'L':  Lower triangular, form is A = L*D*L**T.
* 
*  WAY     (input) CHARACTER*1
*          = 'C': Convert 
*          = 'R': Revert
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input) REAL array, dimension (LDA,N)
*          The block diagonal matrix D and the multipliers used to
*          obtain the factor U or L as computed by SSYTRF.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (input) INTEGER array, dimension (N)
*          Details of the interchanges and the block structure of D
*          as determined by SSYTRF.
*
* WORK     (workspace) REAL array, dimension (N)
*
* LWORK    (input) INTEGER
*          The length of WORK.  LWORK >=1. 
*          LWORK = N
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array, and no error
*          message related to LWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*

*  =====================================================================
*


    
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ssyequb

USAGE:
  s, scond, amax, info = NumRu::Lapack.ssyequb( uplo, a, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYEQUB( UPLO, N, A, LDA, S, SCOND, AMAX, WORK, INFO )

*  Purpose
*  =======
*
*  SSYEQUB computes row and column scalings intended to equilibrate a
*  symmetric matrix A and reduce its condition number
*  (with respect to the two-norm).  S contains the scale factors,
*  S(i) = 1/sqrt(A(i,i)), chosen so that the scaled matrix B with
*  elements B(i,j) = S(i)*A(i,j)*S(j) has ones on the diagonal.  This
*  choice of S puts the condition number of B within a factor N of the
*  smallest possible condition number over all possible diagonal
*  scalings.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the details of the factorization are stored
*          as an upper or lower triangular matrix.
*          = 'U':  Upper triangular, form is A = U*D*U**T;
*          = 'L':  Lower triangular, form is A = L*D*L**T.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input) REAL array, dimension (LDA,N)
*          The N-by-N symmetric matrix whose scaling
*          factors are to be computed.  Only the diagonal elements of A
*          are referenced.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  S       (output) REAL array, dimension (N)
*          If INFO = 0, S contains the scale factors for A.
*
*  SCOND   (output) REAL
*          If INFO = 0, S contains the ratio of the smallest S(i) to
*          the largest S(i).  If SCOND >= 0.1 and AMAX is neither too
*          large nor too small, it is not worth scaling by S.
*
*  AMAX    (output) REAL
*          Absolute value of largest matrix element.  If AMAX is very
*          close to overflow or very close to underflow, the matrix
*          should be scaled.
*
*  WORK    (workspace) REAL array, dimension (3*N)
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*          > 0:  if INFO = i, the i-th diagonal element is nonpositive.
*

*  Further Details
*  ======= =======
*
*  Reference: Livne, O.E. and Golub, G.H., "Scaling by Binormalization",
*  Numerical Algorithms, vol. 35, no. 1, pp. 97-120, January 2004.
*  DOI 10.1023/B:NUMA.0000016606.32820.69
*  Tech report version: http://ruready.utah.edu/archive/papers/bin.pdf
*
*  =====================================================================
*


    
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ssyev

USAGE:
  w, work, info, a = NumRu::Lapack.ssyev( jobz, uplo, a, [:lwork => lwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYEV( JOBZ, UPLO, N, A, LDA, W, WORK, LWORK, INFO )

*  Purpose
*  =======
*
*  SSYEV computes all eigenvalues and, optionally, eigenvectors of a
*  real symmetric matrix A.
*

*  Arguments
*  =========
*
*  JOBZ    (input) CHARACTER*1
*          = 'N':  Compute eigenvalues only;
*          = 'V':  Compute eigenvalues and eigenvectors.
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored;
*          = 'L':  Lower triangle of A is stored.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA, N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the
*          leading N-by-N upper triangular part of A contains the
*          upper triangular part of the matrix A.  If UPLO = 'L',
*          the leading N-by-N lower triangular part of A contains
*          the lower triangular part of the matrix A.
*          On exit, if JOBZ = 'V', then if INFO = 0, A contains the
*          orthonormal eigenvectors of the matrix A.
*          If JOBZ = 'N', then on exit the lower triangle (if UPLO='L')
*          or the upper triangle (if UPLO='U') of A, including the
*          diagonal, is destroyed.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  W       (output) REAL array, dimension (N)
*          If INFO = 0, the eigenvalues in ascending order.
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The length of the array WORK.  LWORK >= max(1,3*N-1).
*          For optimal efficiency, LWORK >= (NB+2)*N,
*          where NB is the blocksize for SSYTRD returned by ILAENV.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array, and no error
*          message related to LWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*          > 0:  if INFO = i, the algorithm failed to converge; i
*                off-diagonal elements of an intermediate tridiagonal
*                form did not converge to zero.
*

*  =====================================================================
*


    
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ssyevd

USAGE:
  w, work, iwork, info, a = NumRu::Lapack.ssyevd( jobz, uplo, a, [:lwork => lwork, :liwork => liwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYEVD( JOBZ, UPLO, N, A, LDA, W, WORK, LWORK, IWORK, LIWORK, INFO )

*  Purpose
*  =======
*
*  SSYEVD computes all eigenvalues and, optionally, eigenvectors of a
*  real symmetric matrix A. If eigenvectors are desired, it uses a
*  divide and conquer algorithm.
*
*  The divide and conquer algorithm makes very mild assumptions about
*  floating point arithmetic. It will work on machines with a guard
*  digit in add/subtract, or on those binary machines without guard
*  digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
*  Cray-2. It could conceivably fail on hexadecimal or decimal machines
*  without guard digits, but we know of none.
*
*  Because of large use of BLAS of level 3, SSYEVD needs N**2 more
*  workspace than SSYEVX.
*

*  Arguments
*  =========
*
*  JOBZ    (input) CHARACTER*1
*          = 'N':  Compute eigenvalues only;
*          = 'V':  Compute eigenvalues and eigenvectors.
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored;
*          = 'L':  Lower triangle of A is stored.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA, N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the
*          leading N-by-N upper triangular part of A contains the
*          upper triangular part of the matrix A.  If UPLO = 'L',
*          the leading N-by-N lower triangular part of A contains
*          the lower triangular part of the matrix A.
*          On exit, if JOBZ = 'V', then if INFO = 0, A contains the
*          orthonormal eigenvectors of the matrix A.
*          If JOBZ = 'N', then on exit the lower triangle (if UPLO='L')
*          or the upper triangle (if UPLO='U') of A, including the
*          diagonal, is destroyed.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  W       (output) REAL array, dimension (N)
*          If INFO = 0, the eigenvalues in ascending order.
*
*  WORK    (workspace/output) REAL array,
*                                         dimension (LWORK)
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The dimension of the array WORK.
*          If N <= 1,               LWORK must be at least 1.
*          If JOBZ = 'N' and N > 1, LWORK must be at least 2*N+1.
*          If JOBZ = 'V' and N > 1, LWORK must be at least 
*                                                1 + 6*N + 2*N**2.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal sizes of the WORK and IWORK
*          arrays, returns these values as the first entries of the WORK
*          and IWORK arrays, and no error message related to LWORK or
*          LIWORK is issued by XERBLA.
*
*  IWORK   (workspace/output) INTEGER array, dimension (MAX(1,LIWORK))
*          On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.
*
*  LIWORK  (input) INTEGER
*          The dimension of the array IWORK.
*          If N <= 1,                LIWORK must be at least 1.
*          If JOBZ  = 'N' and N > 1, LIWORK must be at least 1.
*          If JOBZ  = 'V' and N > 1, LIWORK must be at least 3 + 5*N.
*
*          If LIWORK = -1, then a workspace query is assumed; the
*          routine only calculates the optimal sizes of the WORK and
*          IWORK arrays, returns these values as the first entries of
*          the WORK and IWORK arrays, and no error message related to
*          LWORK or LIWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*          > 0:  if INFO = i and JOBZ = 'N', then the algorithm failed
*                to converge; i off-diagonal elements of an intermediate
*                tridiagonal form did not converge to zero;
*                if INFO = i and JOBZ = 'V', then the algorithm failed
*                to compute an eigenvalue while working on the submatrix
*                lying in rows and columns INFO/(N+1) through
*                mod(INFO,N+1).
*

*  Further Details
*  ===============
*
*  Based on contributions by
*     Jeff Rutter, Computer Science Division, University of California
*     at Berkeley, USA
*  Modified by Francoise Tisseur, University of Tennessee.
*
*  Modified description of INFO. Sven, 16 Feb 05.
*  =====================================================================
*


    
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ssyevr

USAGE:
  m, w, z, isuppz, work, iwork, info, a = NumRu::Lapack.ssyevr( jobz, range, uplo, a, vl, vu, il, iu, abstol, [:lwork => lwork, :liwork => liwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYEVR( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, ISUPPZ, WORK, LWORK, IWORK, LIWORK, INFO )

*  Purpose
*  =======
*
*  SSYEVR computes selected eigenvalues and, optionally, eigenvectors
*  of a real symmetric matrix A.  Eigenvalues and eigenvectors can be
*  selected by specifying either a range of values or a range of
*  indices for the desired eigenvalues.
*
*  SSYEVR first reduces the matrix A to tridiagonal form T with a call
*  to SSYTRD.  Then, whenever possible, SSYEVR calls SSTEMR to compute
*  the eigenspectrum using Relatively Robust Representations.  SSTEMR
*  computes eigenvalues by the dqds algorithm, while orthogonal
*  eigenvectors are computed from various "good" L D L^T representations
*  (also known as Relatively Robust Representations). Gram-Schmidt
*  orthogonalization is avoided as far as possible. More specifically,
*  the various steps of the algorithm are as follows.
*
*  For each unreduced block (submatrix) of T,
*     (a) Compute T - sigma I  = L D L^T, so that L and D
*         define all the wanted eigenvalues to high relative accuracy.
*         This means that small relative changes in the entries of D and L
*         cause only small relative changes in the eigenvalues and
*         eigenvectors. The standard (unfactored) representation of the
*         tridiagonal matrix T does not have this property in general.
*     (b) Compute the eigenvalues to suitable accuracy.
*         If the eigenvectors are desired, the algorithm attains full
*         accuracy of the computed eigenvalues only right before
*         the corresponding vectors have to be computed, see steps c) and d).
*     (c) For each cluster of close eigenvalues, select a new
*         shift close to the cluster, find a new factorization, and refine
*         the shifted eigenvalues to suitable accuracy.
*     (d) For each eigenvalue with a large enough relative separation compute
*         the corresponding eigenvector by forming a rank revealing twisted
*         factorization. Go back to (c) for any clusters that remain.
*
*  The desired accuracy of the output can be specified by the input
*  parameter ABSTOL.
*
*  For more details, see SSTEMR's documentation and:
*  - Inderjit S. Dhillon and Beresford N. Parlett: "Multiple representations
*    to compute orthogonal eigenvectors of symmetric tridiagonal matrices,"
*    Linear Algebra and its Applications, 387(1), pp. 1-28, August 2004.
*  - Inderjit Dhillon and Beresford Parlett: "Orthogonal Eigenvectors and
*    Relative Gaps," SIAM Journal on Matrix Analysis and Applications, Vol. 25,
*    2004.  Also LAPACK Working Note 154.
*  - Inderjit Dhillon: "A new O(n^2) algorithm for the symmetric
*    tridiagonal eigenvalue/eigenvector problem",
*    Computer Science Division Technical Report No. UCB/CSD-97-971,
*    UC Berkeley, May 1997.
*
*
*  Note 1 : SSYEVR calls SSTEMR when the full spectrum is requested
*  on machines which conform to the ieee-754 floating point standard.
*  SSYEVR calls SSTEBZ and SSTEIN on non-ieee machines and
*  when partial spectrum requests are made.
*
*  Normal execution of SSTEMR may create NaNs and infinities and
*  hence may abort due to a floating point exception in environments
*  which do not handle NaNs and infinities in the ieee standard default
*  manner.
*

*  Arguments
*  =========
*
*  JOBZ    (input) CHARACTER*1
*          = 'N':  Compute eigenvalues only;
*          = 'V':  Compute eigenvalues and eigenvectors.
*
*  RANGE   (input) CHARACTER*1
*          = 'A': all eigenvalues will be found.
*          = 'V': all eigenvalues in the half-open interval (VL,VU]
*                 will be found.
*          = 'I': the IL-th through IU-th eigenvalues will be found.
********** For RANGE = 'V' or 'I' and IU - IL < N - 1, SSTEBZ and
********** SSTEIN are called
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored;
*          = 'L':  Lower triangle of A is stored.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA, N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the
*          leading N-by-N upper triangular part of A contains the
*          upper triangular part of the matrix A.  If UPLO = 'L',
*          the leading N-by-N lower triangular part of A contains
*          the lower triangular part of the matrix A.
*          On exit, the lower triangle (if UPLO='L') or the upper
*          triangle (if UPLO='U') of A, including the diagonal, is
*          destroyed.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  VL      (input) REAL
*  VU      (input) REAL
*          If RANGE='V', the lower and upper bounds of the interval to
*          be searched for eigenvalues. VL < VU.
*          Not referenced if RANGE = 'A' or 'I'.
*
*  IL      (input) INTEGER
*  IU      (input) INTEGER
*          If RANGE='I', the indices (in ascending order) of the
*          smallest and largest eigenvalues to be returned.
*          1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0.
*          Not referenced if RANGE = 'A' or 'V'.
*
*  ABSTOL  (input) REAL
*          The absolute error tolerance for the eigenvalues.
*          An approximate eigenvalue is accepted as converged
*          when it is determined to lie in an interval [a,b]
*          of width less than or equal to
*
*                  ABSTOL + EPS *   max( |a|,|b| ) ,
*
*          where EPS is the machine precision.  If ABSTOL is less than
*          or equal to zero, then  EPS*|T|  will be used in its place,
*          where |T| is the 1-norm of the tridiagonal matrix obtained
*          by reducing A to tridiagonal form.
*
*          See "Computing Small Singular Values of Bidiagonal Matrices
*          with Guaranteed High Relative Accuracy," by Demmel and
*          Kahan, LAPACK Working Note #3.
*
*          If high relative accuracy is important, set ABSTOL to
*          SLAMCH( 'Safe minimum' ).  Doing so will guarantee that
*          eigenvalues are computed to high relative accuracy when
*          possible in future releases.  The current code does not
*          make any guarantees about high relative accuracy, but
*          future releases will. See J. Barlow and J. Demmel,
*          "Computing Accurate Eigensystems of Scaled Diagonally
*          Dominant Matrices", LAPACK Working Note #7, for a discussion
*          of which matrices define their eigenvalues to high relative
*          accuracy.
*
*  M       (output) INTEGER
*          The total number of eigenvalues found.  0 <= M <= N.
*          If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1.
*
*  W       (output) REAL array, dimension (N)
*          The first M elements contain the selected eigenvalues in
*          ascending order.
*
*  Z       (output) REAL array, dimension (LDZ, max(1,M))
*          If JOBZ = 'V', then if INFO = 0, the first M columns of Z
*          contain the orthonormal eigenvectors of the matrix A
*          corresponding to the selected eigenvalues, with the i-th
*          column of Z holding the eigenvector associated with W(i).
*          If JOBZ = 'N', then Z is not referenced.
*          Note: the user must ensure that at least max(1,M) columns are
*          supplied in the array Z; if RANGE = 'V', the exact value of M
*          is not known in advance and an upper bound must be used.
*          Supplying N columns is always safe.
*
*  LDZ     (input) INTEGER
*          The leading dimension of the array Z.  LDZ >= 1, and if
*          JOBZ = 'V', LDZ >= max(1,N).
*
*  ISUPPZ  (output) INTEGER array, dimension ( 2*max(1,M) )
*          The support of the eigenvectors in Z, i.e., the indices
*          indicating the nonzero elements in Z. The i-th eigenvector
*          is nonzero only in elements ISUPPZ( 2*i-1 ) through
*          ISUPPZ( 2*i ).
********** Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The dimension of the array WORK.  LWORK >= max(1,26*N).
*          For optimal efficiency, LWORK >= (NB+6)*N,
*          where NB is the max of the blocksize for SSYTRD and SORMTR
*          returned by ILAENV.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal sizes of the WORK and IWORK
*          arrays, returns these values as the first entries of the WORK
*          and IWORK arrays, and no error message related to LWORK or
*          LIWORK is issued by XERBLA.
*
*  IWORK   (workspace/output) INTEGER array, dimension (MAX(1,LIWORK))
*          On exit, if INFO = 0, IWORK(1) returns the optimal LWORK.
*
*  LIWORK  (input) INTEGER
*          The dimension of the array IWORK.  LIWORK >= max(1,10*N).
*
*          If LIWORK = -1, then a workspace query is assumed; the
*          routine only calculates the optimal sizes of the WORK and
*          IWORK arrays, returns these values as the first entries of
*          the WORK and IWORK arrays, and no error message related to
*          LWORK or LIWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*          > 0:  Internal error
*

*  Further Details
*  ===============
*
*  Based on contributions by
*     Inderjit Dhillon, IBM Almaden, USA
*     Osni Marques, LBNL/NERSC, USA
*     Ken Stanley, Computer Science Division, University of
*       California at Berkeley, USA
*     Jason Riedy, Computer Science Division, University of
*       California at Berkeley, USA
*
* =====================================================================
*


    
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ssyevx

USAGE:
  m, w, z, work, ifail, info, a = NumRu::Lapack.ssyevx( jobz, range, uplo, a, vl, vu, il, iu, abstol, [:lwork => lwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYEVX( JOBZ, RANGE, UPLO, N, A, LDA, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, WORK, LWORK, IWORK, IFAIL, INFO )

*  Purpose
*  =======
*
*  SSYEVX computes selected eigenvalues and, optionally, eigenvectors
*  of a real symmetric matrix A.  Eigenvalues and eigenvectors can be
*  selected by specifying either a range of values or a range of indices
*  for the desired eigenvalues.
*

*  Arguments
*  =========
*
*  JOBZ    (input) CHARACTER*1
*          = 'N':  Compute eigenvalues only;
*          = 'V':  Compute eigenvalues and eigenvectors.
*
*  RANGE   (input) CHARACTER*1
*          = 'A': all eigenvalues will be found.
*          = 'V': all eigenvalues in the half-open interval (VL,VU]
*                 will be found.
*          = 'I': the IL-th through IU-th eigenvalues will be found.
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored;
*          = 'L':  Lower triangle of A is stored.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA, N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the
*          leading N-by-N upper triangular part of A contains the
*          upper triangular part of the matrix A.  If UPLO = 'L',
*          the leading N-by-N lower triangular part of A contains
*          the lower triangular part of the matrix A.
*          On exit, the lower triangle (if UPLO='L') or the upper
*          triangle (if UPLO='U') of A, including the diagonal, is
*          destroyed.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  VL      (input) REAL
*  VU      (input) REAL
*          If RANGE='V', the lower and upper bounds of the interval to
*          be searched for eigenvalues. VL < VU.
*          Not referenced if RANGE = 'A' or 'I'.
*
*  IL      (input) INTEGER
*  IU      (input) INTEGER
*          If RANGE='I', the indices (in ascending order) of the
*          smallest and largest eigenvalues to be returned.
*          1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0.
*          Not referenced if RANGE = 'A' or 'V'.
*
*  ABSTOL  (input) REAL
*          The absolute error tolerance for the eigenvalues.
*          An approximate eigenvalue is accepted as converged
*          when it is determined to lie in an interval [a,b]
*          of width less than or equal to
*
*                  ABSTOL + EPS *   max( |a|,|b| ) ,
*
*          where EPS is the machine precision.  If ABSTOL is less than
*          or equal to zero, then  EPS*|T|  will be used in its place,
*          where |T| is the 1-norm of the tridiagonal matrix obtained
*          by reducing A to tridiagonal form.
*
*          Eigenvalues will be computed most accurately when ABSTOL is
*          set to twice the underflow threshold 2*SLAMCH('S'), not zero.
*          If this routine returns with INFO>0, indicating that some
*          eigenvectors did not converge, try setting ABSTOL to
*          2*SLAMCH('S').
*
*          See "Computing Small Singular Values of Bidiagonal Matrices
*          with Guaranteed High Relative Accuracy," by Demmel and
*          Kahan, LAPACK Working Note #3.
*
*  M       (output) INTEGER
*          The total number of eigenvalues found.  0 <= M <= N.
*          If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1.
*
*  W       (output) REAL array, dimension (N)
*          On normal exit, the first M elements contain the selected
*          eigenvalues in ascending order.
*
*  Z       (output) REAL array, dimension (LDZ, max(1,M))
*          If JOBZ = 'V', then if INFO = 0, the first M columns of Z
*          contain the orthonormal eigenvectors of the matrix A
*          corresponding to the selected eigenvalues, with the i-th
*          column of Z holding the eigenvector associated with W(i).
*          If an eigenvector fails to converge, then that column of Z
*          contains the latest approximation to the eigenvector, and the
*          index of the eigenvector is returned in IFAIL.
*          If JOBZ = 'N', then Z is not referenced.
*          Note: the user must ensure that at least max(1,M) columns are
*          supplied in the array Z; if RANGE = 'V', the exact value of M
*          is not known in advance and an upper bound must be used.
*
*  LDZ     (input) INTEGER
*          The leading dimension of the array Z.  LDZ >= 1, and if
*          JOBZ = 'V', LDZ >= max(1,N).
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The length of the array WORK.  LWORK >= 1, when N <= 1;
*          otherwise 8*N.
*          For optimal efficiency, LWORK >= (NB+3)*N,
*          where NB is the max of the blocksize for SSYTRD and SORMTR
*          returned by ILAENV.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array, and no error
*          message related to LWORK is issued by XERBLA.
*
*  IWORK   (workspace) INTEGER array, dimension (5*N)
*
*  IFAIL   (output) INTEGER array, dimension (N)
*          If JOBZ = 'V', then if INFO = 0, the first M elements of
*          IFAIL are zero.  If INFO > 0, then IFAIL contains the
*          indices of the eigenvectors that failed to converge.
*          If JOBZ = 'N', then IFAIL is not referenced.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*          > 0:  if INFO = i, then i eigenvectors failed to converge.
*                Their indices are stored in array IFAIL.
*

* =====================================================================
*


    
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ssygs2

USAGE:
  info, a = NumRu::Lapack.ssygs2( itype, uplo, a, b, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYGS2( ITYPE, UPLO, N, A, LDA, B, LDB, INFO )

*  Purpose
*  =======
*
*  SSYGS2 reduces a real symmetric-definite generalized eigenproblem
*  to standard form.
*
*  If ITYPE = 1, the problem is A*x = lambda*B*x,
*  and A is overwritten by inv(U')*A*inv(U) or inv(L)*A*inv(L')
*
*  If ITYPE = 2 or 3, the problem is A*B*x = lambda*x or
*  B*A*x = lambda*x, and A is overwritten by U*A*U` or L'*A*L.
*
*  B must have been previously factorized as U'*U or L*L' by SPOTRF.
*

*  Arguments
*  =========
*
*  ITYPE   (input) INTEGER
*          = 1: compute inv(U')*A*inv(U) or inv(L)*A*inv(L');
*          = 2 or 3: compute U*A*U' or L'*A*L.
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the upper or lower triangular part of the
*          symmetric matrix A is stored, and how B has been factorized.
*          = 'U':  Upper triangular
*          = 'L':  Lower triangular
*
*  N       (input) INTEGER
*          The order of the matrices A and B.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the leading
*          n by n upper triangular part of A contains the upper
*          triangular part of the matrix A, and the strictly lower
*          triangular part of A is not referenced.  If UPLO = 'L', the
*          leading n by n lower triangular part of A contains the lower
*          triangular part of the matrix A, and the strictly upper
*          triangular part of A is not referenced.
*
*          On exit, if INFO = 0, the transformed matrix, stored in the
*          same format as A.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  B       (input) REAL array, dimension (LDB,N)
*          The triangular factor from the Cholesky factorization of B,
*          as returned by SPOTRF.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  INFO    (output) INTEGER
*          = 0:  successful exit.
*          < 0:  if INFO = -i, the i-th argument had an illegal value.
*

*  =====================================================================
*


    
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ssygst

USAGE:
  info, a = NumRu::Lapack.ssygst( itype, uplo, a, b, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYGST( ITYPE, UPLO, N, A, LDA, B, LDB, INFO )

*  Purpose
*  =======
*
*  SSYGST reduces a real symmetric-definite generalized eigenproblem
*  to standard form.
*
*  If ITYPE = 1, the problem is A*x = lambda*B*x,
*  and A is overwritten by inv(U**T)*A*inv(U) or inv(L)*A*inv(L**T)
*
*  If ITYPE = 2 or 3, the problem is A*B*x = lambda*x or
*  B*A*x = lambda*x, and A is overwritten by U*A*U**T or L**T*A*L.
*
*  B must have been previously factorized as U**T*U or L*L**T by SPOTRF.
*

*  Arguments
*  =========
*
*  ITYPE   (input) INTEGER
*          = 1: compute inv(U**T)*A*inv(U) or inv(L)*A*inv(L**T);
*          = 2 or 3: compute U*A*U**T or L**T*A*L.
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored and B is factored as
*                  U**T*U;
*          = 'L':  Lower triangle of A is stored and B is factored as
*                  L*L**T.
*
*  N       (input) INTEGER
*          The order of the matrices A and B.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the leading
*          N-by-N upper triangular part of A contains the upper
*          triangular part of the matrix A, and the strictly lower
*          triangular part of A is not referenced.  If UPLO = 'L', the
*          leading N-by-N lower triangular part of A contains the lower
*          triangular part of the matrix A, and the strictly upper
*          triangular part of A is not referenced.
*
*          On exit, if INFO = 0, the transformed matrix, stored in the
*          same format as A.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  B       (input) REAL array, dimension (LDB,N)
*          The triangular factor from the Cholesky factorization of B,
*          as returned by SPOTRF.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*

*  =====================================================================
*


    
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ssygv

USAGE:
  w, work, info, a, b = NumRu::Lapack.ssygv( itype, jobz, uplo, a, b, [:lwork => lwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYGV( ITYPE, JOBZ, UPLO, N, A, LDA, B, LDB, W, WORK, LWORK, INFO )

*  Purpose
*  =======
*
*  SSYGV computes all the eigenvalues, and optionally, the eigenvectors
*  of a real generalized symmetric-definite eigenproblem, of the form
*  A*x=(lambda)*B*x,  A*Bx=(lambda)*x,  or B*A*x=(lambda)*x.
*  Here A and B are assumed to be symmetric and B is also
*  positive definite.
*

*  Arguments
*  =========
*
*  ITYPE   (input) INTEGER
*          Specifies the problem type to be solved:
*          = 1:  A*x = (lambda)*B*x
*          = 2:  A*B*x = (lambda)*x
*          = 3:  B*A*x = (lambda)*x
*
*  JOBZ    (input) CHARACTER*1
*          = 'N':  Compute eigenvalues only;
*          = 'V':  Compute eigenvalues and eigenvectors.
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangles of A and B are stored;
*          = 'L':  Lower triangles of A and B are stored.
*
*  N       (input) INTEGER
*          The order of the matrices A and B.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA, N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the
*          leading N-by-N upper triangular part of A contains the
*          upper triangular part of the matrix A.  If UPLO = 'L',
*          the leading N-by-N lower triangular part of A contains
*          the lower triangular part of the matrix A.
*
*          On exit, if JOBZ = 'V', then if INFO = 0, A contains the
*          matrix Z of eigenvectors.  The eigenvectors are normalized
*          as follows:
*          if ITYPE = 1 or 2, Z**T*B*Z = I;
*          if ITYPE = 3, Z**T*inv(B)*Z = I.
*          If JOBZ = 'N', then on exit the upper triangle (if UPLO='U')
*          or the lower triangle (if UPLO='L') of A, including the
*          diagonal, is destroyed.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  B       (input/output) REAL array, dimension (LDB, N)
*          On entry, the symmetric positive definite matrix B.
*          If UPLO = 'U', the leading N-by-N upper triangular part of B
*          contains the upper triangular part of the matrix B.
*          If UPLO = 'L', the leading N-by-N lower triangular part of B
*          contains the lower triangular part of the matrix B.
*
*          On exit, if INFO <= N, the part of B containing the matrix is
*          overwritten by the triangular factor U or L from the Cholesky
*          factorization B = U**T*U or B = L*L**T.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  W       (output) REAL array, dimension (N)
*          If INFO = 0, the eigenvalues in ascending order.
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The length of the array WORK.  LWORK >= max(1,3*N-1).
*          For optimal efficiency, LWORK >= (NB+2)*N,
*          where NB is the blocksize for SSYTRD returned by ILAENV.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array, and no error
*          message related to LWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*          > 0:  SPOTRF or SSYEV returned an error code:
*             <= N:  if INFO = i, SSYEV failed to converge;
*                    i off-diagonal elements of an intermediate
*                    tridiagonal form did not converge to zero;
*             > N:   if INFO = N + i, for 1 <= i <= N, then the leading
*                    minor of order i of B is not positive definite.
*                    The factorization of B could not be completed and
*                    no eigenvalues or eigenvectors were computed.
*

*  =====================================================================
*


    
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ssygvd

USAGE:
  w, work, iwork, info, a, b = NumRu::Lapack.ssygvd( itype, jobz, uplo, a, b, [:lwork => lwork, :liwork => liwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYGVD( ITYPE, JOBZ, UPLO, N, A, LDA, B, LDB, W, WORK, LWORK, IWORK, LIWORK, INFO )

*  Purpose
*  =======
*
*  SSYGVD computes all the eigenvalues, and optionally, the eigenvectors
*  of a real generalized symmetric-definite eigenproblem, of the form
*  A*x=(lambda)*B*x,  A*Bx=(lambda)*x,  or B*A*x=(lambda)*x.  Here A and
*  B are assumed to be symmetric and B is also positive definite.
*  If eigenvectors are desired, it uses a divide and conquer algorithm.
*
*  The divide and conquer algorithm makes very mild assumptions about
*  floating point arithmetic. It will work on machines with a guard
*  digit in add/subtract, or on those binary machines without guard
*  digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
*  Cray-2. It could conceivably fail on hexadecimal or decimal machines
*  without guard digits, but we know of none.
*

*  Arguments
*  =========
*
*  ITYPE   (input) INTEGER
*          Specifies the problem type to be solved:
*          = 1:  A*x = (lambda)*B*x
*          = 2:  A*B*x = (lambda)*x
*          = 3:  B*A*x = (lambda)*x
*
*  JOBZ    (input) CHARACTER*1
*          = 'N':  Compute eigenvalues only;
*          = 'V':  Compute eigenvalues and eigenvectors.
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangles of A and B are stored;
*          = 'L':  Lower triangles of A and B are stored.
*
*  N       (input) INTEGER
*          The order of the matrices A and B.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA, N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the
*          leading N-by-N upper triangular part of A contains the
*          upper triangular part of the matrix A.  If UPLO = 'L',
*          the leading N-by-N lower triangular part of A contains
*          the lower triangular part of the matrix A.
*
*          On exit, if JOBZ = 'V', then if INFO = 0, A contains the
*          matrix Z of eigenvectors.  The eigenvectors are normalized
*          as follows:
*          if ITYPE = 1 or 2, Z**T*B*Z = I;
*          if ITYPE = 3, Z**T*inv(B)*Z = I.
*          If JOBZ = 'N', then on exit the upper triangle (if UPLO='U')
*          or the lower triangle (if UPLO='L') of A, including the
*          diagonal, is destroyed.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  B       (input/output) REAL array, dimension (LDB, N)
*          On entry, the symmetric matrix B.  If UPLO = 'U', the
*          leading N-by-N upper triangular part of B contains the
*          upper triangular part of the matrix B.  If UPLO = 'L',
*          the leading N-by-N lower triangular part of B contains
*          the lower triangular part of the matrix B.
*
*          On exit, if INFO <= N, the part of B containing the matrix is
*          overwritten by the triangular factor U or L from the Cholesky
*          factorization B = U**T*U or B = L*L**T.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  W       (output) REAL array, dimension (N)
*          If INFO = 0, the eigenvalues in ascending order.
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The dimension of the array WORK.
*          If N <= 1,               LWORK >= 1.
*          If JOBZ = 'N' and N > 1, LWORK >= 2*N+1.
*          If JOBZ = 'V' and N > 1, LWORK >= 1 + 6*N + 2*N**2.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal sizes of the WORK and IWORK
*          arrays, returns these values as the first entries of the WORK
*          and IWORK arrays, and no error message related to LWORK or
*          LIWORK is issued by XERBLA.
*
*  IWORK   (workspace/output) INTEGER array, dimension (MAX(1,LIWORK))
*          On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.
*
*  LIWORK  (input) INTEGER
*          The dimension of the array IWORK.
*          If N <= 1,                LIWORK >= 1.
*          If JOBZ  = 'N' and N > 1, LIWORK >= 1.
*          If JOBZ  = 'V' and N > 1, LIWORK >= 3 + 5*N.
*
*          If LIWORK = -1, then a workspace query is assumed; the
*          routine only calculates the optimal sizes of the WORK and
*          IWORK arrays, returns these values as the first entries of
*          the WORK and IWORK arrays, and no error message related to
*          LWORK or LIWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*          > 0:  SPOTRF or SSYEVD returned an error code:
*             <= N:  if INFO = i and JOBZ = 'N', then the algorithm
*                    failed to converge; i off-diagonal elements of an
*                    intermediate tridiagonal form did not converge to
*                    zero;
*                    if INFO = i and JOBZ = 'V', then the algorithm
*                    failed to compute an eigenvalue while working on
*                    the submatrix lying in rows and columns INFO/(N+1)
*                    through mod(INFO,N+1);
*             > N:   if INFO = N + i, for 1 <= i <= N, then the leading
*                    minor of order i of B is not positive definite.
*                    The factorization of B could not be completed and
*                    no eigenvalues or eigenvectors were computed.
*

*  Further Details
*  ===============
*
*  Based on contributions by
*     Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA
*
*  Modified so that no backsubstitution is performed if SSYEVD fails to
*  converge (NEIG in old code could be greater than N causing out of
*  bounds reference to A - reported by Ralf Meyer).  Also corrected the
*  description of INFO and the test on ITYPE. Sven, 16 Feb 05.
*  =====================================================================
*


    
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ssygvx

USAGE:
  m, w, z, work, ifail, info, a, b = NumRu::Lapack.ssygvx( itype, jobz, range, uplo, a, b, ldb, vl, vu, il, iu, abstol, [:lwork => lwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYGVX( ITYPE, JOBZ, RANGE, UPLO, N, A, LDA, B, LDB, VL, VU, IL, IU, ABSTOL, M, W, Z, LDZ, WORK, LWORK, IWORK, IFAIL, INFO )

*  Purpose
*  =======
*
*  SSYGVX computes selected eigenvalues, and optionally, eigenvectors
*  of a real generalized symmetric-definite eigenproblem, of the form
*  A*x=(lambda)*B*x,  A*Bx=(lambda)*x,  or B*A*x=(lambda)*x.  Here A
*  and B are assumed to be symmetric and B is also positive definite.
*  Eigenvalues and eigenvectors can be selected by specifying either a
*  range of values or a range of indices for the desired eigenvalues.
*

*  Arguments
*  =========
*
*  ITYPE   (input) INTEGER
*          Specifies the problem type to be solved:
*          = 1:  A*x = (lambda)*B*x
*          = 2:  A*B*x = (lambda)*x
*          = 3:  B*A*x = (lambda)*x
*
*  JOBZ    (input) CHARACTER*1
*          = 'N':  Compute eigenvalues only;
*          = 'V':  Compute eigenvalues and eigenvectors.
*
*  RANGE   (input) CHARACTER*1
*          = 'A': all eigenvalues will be found.
*          = 'V': all eigenvalues in the half-open interval (VL,VU]
*                 will be found.
*          = 'I': the IL-th through IU-th eigenvalues will be found.
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A and B are stored;
*          = 'L':  Lower triangle of A and B are stored.
*
*  N       (input) INTEGER
*          The order of the matrix pencil (A,B).  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA, N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the
*          leading N-by-N upper triangular part of A contains the
*          upper triangular part of the matrix A.  If UPLO = 'L',
*          the leading N-by-N lower triangular part of A contains
*          the lower triangular part of the matrix A.
*
*          On exit, the lower triangle (if UPLO='L') or the upper
*          triangle (if UPLO='U') of A, including the diagonal, is
*          destroyed.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  B       (input/output) REAL array, dimension (LDA, N)
*          On entry, the symmetric matrix B.  If UPLO = 'U', the
*          leading N-by-N upper triangular part of B contains the
*          upper triangular part of the matrix B.  If UPLO = 'L',
*          the leading N-by-N lower triangular part of B contains
*          the lower triangular part of the matrix B.
*
*          On exit, if INFO <= N, the part of B containing the matrix is
*          overwritten by the triangular factor U or L from the Cholesky
*          factorization B = U**T*U or B = L*L**T.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  VL      (input) REAL
*  VU      (input) REAL
*          If RANGE='V', the lower and upper bounds of the interval to
*          be searched for eigenvalues. VL < VU.
*          Not referenced if RANGE = 'A' or 'I'.
*
*  IL      (input) INTEGER
*  IU      (input) INTEGER
*          If RANGE='I', the indices (in ascending order) of the
*          smallest and largest eigenvalues to be returned.
*          1 <= IL <= IU <= N, if N > 0; IL = 1 and IU = 0 if N = 0.
*          Not referenced if RANGE = 'A' or 'V'.
*
*  ABSTOL  (input) REAL
*          The absolute error tolerance for the eigenvalues.
*          An approximate eigenvalue is accepted as converged
*          when it is determined to lie in an interval [a,b]
*          of width less than or equal to
*
*                  ABSTOL + EPS *   max( |a|,|b| ) ,
*
*          where EPS is the machine precision.  If ABSTOL is less than
*          or equal to zero, then  EPS*|T|  will be used in its place,
*          where |T| is the 1-norm of the tridiagonal matrix obtained
*          by reducing A to tridiagonal form.
*
*          Eigenvalues will be computed most accurately when ABSTOL is
*          set to twice the underflow threshold 2*DLAMCH('S'), not zero.
*          If this routine returns with INFO>0, indicating that some
*          eigenvectors did not converge, try setting ABSTOL to
*          2*SLAMCH('S').
*
*  M       (output) INTEGER
*          The total number of eigenvalues found.  0 <= M <= N.
*          If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1.
*
*  W       (output) REAL array, dimension (N)
*          On normal exit, the first M elements contain the selected
*          eigenvalues in ascending order.
*
*  Z       (output) REAL array, dimension (LDZ, max(1,M))
*          If JOBZ = 'N', then Z is not referenced.
*          If JOBZ = 'V', then if INFO = 0, the first M columns of Z
*          contain the orthonormal eigenvectors of the matrix A
*          corresponding to the selected eigenvalues, with the i-th
*          column of Z holding the eigenvector associated with W(i).
*          The eigenvectors are normalized as follows:
*          if ITYPE = 1 or 2, Z**T*B*Z = I;
*          if ITYPE = 3, Z**T*inv(B)*Z = I.
*
*          If an eigenvector fails to converge, then that column of Z
*          contains the latest approximation to the eigenvector, and the
*          index of the eigenvector is returned in IFAIL.
*          Note: the user must ensure that at least max(1,M) columns are
*          supplied in the array Z; if RANGE = 'V', the exact value of M
*          is not known in advance and an upper bound must be used.
*
*  LDZ     (input) INTEGER
*          The leading dimension of the array Z.  LDZ >= 1, and if
*          JOBZ = 'V', LDZ >= max(1,N).
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The length of the array WORK.  LWORK >= max(1,8*N).
*          For optimal efficiency, LWORK >= (NB+3)*N,
*          where NB is the blocksize for SSYTRD returned by ILAENV.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array, and no error
*          message related to LWORK is issued by XERBLA.
*
*  IWORK   (workspace) INTEGER array, dimension (5*N)
*
*  IFAIL   (output) INTEGER array, dimension (N)
*          If JOBZ = 'V', then if INFO = 0, the first M elements of
*          IFAIL are zero.  If INFO > 0, then IFAIL contains the
*          indices of the eigenvectors that failed to converge.
*          If JOBZ = 'N', then IFAIL is not referenced.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*          > 0:  SPOTRF or SSYEVX returned an error code:
*             <= N:  if INFO = i, SSYEVX failed to converge;
*                    i eigenvectors failed to converge.  Their indices
*                    are stored in array IFAIL.
*             > N:   if INFO = N + i, for 1 <= i <= N, then the leading
*                    minor of order i of B is not positive definite.
*                    The factorization of B could not be completed and
*                    no eigenvalues or eigenvectors were computed.
*

*  Further Details
*  ===============
*
*  Based on contributions by
*     Mark Fahey, Department of Mathematics, Univ. of Kentucky, USA
*
* =====================================================================
*


    
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ssyrfs

USAGE:
  ferr, berr, info, x = NumRu::Lapack.ssyrfs( uplo, a, af, ipiv, b, x, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYRFS( UPLO, N, NRHS, A, LDA, AF, LDAF, IPIV, B, LDB, X, LDX, FERR, BERR, WORK, IWORK, INFO )

*  Purpose
*  =======
*
*  SSYRFS improves the computed solution to a system of linear
*  equations when the coefficient matrix is symmetric indefinite, and
*  provides error bounds and backward error estimates for the solution.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored;
*          = 'L':  Lower triangle of A is stored.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  NRHS    (input) INTEGER
*          The number of right hand sides, i.e., the number of columns
*          of the matrices B and X.  NRHS >= 0.
*
*  A       (input) REAL array, dimension (LDA,N)
*          The symmetric matrix A.  If UPLO = 'U', the leading N-by-N
*          upper triangular part of A contains the upper triangular part
*          of the matrix A, and the strictly lower triangular part of A
*          is not referenced.  If UPLO = 'L', the leading N-by-N lower
*          triangular part of A contains the lower triangular part of
*          the matrix A, and the strictly upper triangular part of A is
*          not referenced.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  AF      (input) REAL array, dimension (LDAF,N)
*          The factored form of the matrix A.  AF contains the block
*          diagonal matrix D and the multipliers used to obtain the
*          factor U or L from the factorization A = U*D*U**T or
*          A = L*D*L**T as computed by SSYTRF.
*
*  LDAF    (input) INTEGER
*          The leading dimension of the array AF.  LDAF >= max(1,N).
*
*  IPIV    (input) INTEGER array, dimension (N)
*          Details of the interchanges and the block structure of D
*          as determined by SSYTRF.
*
*  B       (input) REAL array, dimension (LDB,NRHS)
*          The right hand side matrix B.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  X       (input/output) REAL array, dimension (LDX,NRHS)
*          On entry, the solution matrix X, as computed by SSYTRS.
*          On exit, the improved solution matrix X.
*
*  LDX     (input) INTEGER
*          The leading dimension of the array X.  LDX >= max(1,N).
*
*  FERR    (output) REAL array, dimension (NRHS)
*          The estimated forward error bound for each solution vector
*          X(j) (the j-th column of the solution matrix X).
*          If XTRUE is the true solution corresponding to X(j), FERR(j)
*          is an estimated upper bound for the magnitude of the largest
*          element in (X(j) - XTRUE) divided by the magnitude of the
*          largest element in X(j).  The estimate is as reliable as
*          the estimate for RCOND, and is almost always a slight
*          overestimate of the true error.
*
*  BERR    (output) REAL array, dimension (NRHS)
*          The componentwise relative backward error of each solution
*          vector X(j) (i.e., the smallest relative change in
*          any element of A or B that makes X(j) an exact solution).
*
*  WORK    (workspace) REAL array, dimension (3*N)
*
*  IWORK   (workspace) INTEGER array, dimension (N)
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*
*  Internal Parameters
*  ===================
*
*  ITMAX is the maximum number of steps of iterative refinement.
*

*  =====================================================================
*


    
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ssyrfsx

USAGE:
  rcond, berr, err_bnds_norm, err_bnds_comp, info, s, x, params = NumRu::Lapack.ssyrfsx( uplo, equed, a, af, ipiv, s, b, x, params, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYRFSX( UPLO, EQUED, N, NRHS, A, LDA, AF, LDAF, IPIV, S, B, LDB, X, LDX, RCOND, BERR, N_ERR_BNDS, ERR_BNDS_NORM, ERR_BNDS_COMP, NPARAMS, PARAMS, WORK, IWORK, INFO )

*     Purpose
*     =======
*
*     SSYRFSX improves the computed solution to a system of linear
*     equations when the coefficient matrix is symmetric indefinite, and
*     provides error bounds and backward error estimates for the
*     solution.  In addition to normwise error bound, the code provides
*     maximum componentwise error bound if possible.  See comments for
*     ERR_BNDS_NORM and ERR_BNDS_COMP for details of the error bounds.
*
*     The original system of linear equations may have been equilibrated
*     before calling this routine, as described by arguments EQUED and S
*     below. In this case, the solution and error bounds returned are
*     for the original unequilibrated system.
*

*     Arguments
*     =========
*
*     Some optional parameters are bundled in the PARAMS array.  These
*     settings determine how refinement is performed, but often the
*     defaults are acceptable.  If the defaults are acceptable, users
*     can pass NPARAMS = 0 which prevents the source code from accessing
*     the PARAMS argument.
*
*     UPLO    (input) CHARACTER*1
*       = 'U':  Upper triangle of A is stored;
*       = 'L':  Lower triangle of A is stored.
*
*     EQUED   (input) CHARACTER*1
*     Specifies the form of equilibration that was done to A
*     before calling this routine. This is needed to compute
*     the solution and error bounds correctly.
*       = 'N':  No equilibration
*       = 'Y':  Both row and column equilibration, i.e., A has been
*               replaced by diag(S) * A * diag(S).
*               The right hand side B has been changed accordingly.
*
*     N       (input) INTEGER
*     The order of the matrix A.  N >= 0.
*
*     NRHS    (input) INTEGER
*     The number of right hand sides, i.e., the number of columns
*     of the matrices B and X.  NRHS >= 0.
*
*     A       (input) REAL array, dimension (LDA,N)
*     The symmetric matrix A.  If UPLO = 'U', the leading N-by-N
*     upper triangular part of A contains the upper triangular
*     part of the matrix A, and the strictly lower triangular
*     part of A is not referenced.  If UPLO = 'L', the leading
*     N-by-N lower triangular part of A contains the lower
*     triangular part of the matrix A, and the strictly upper
*     triangular part of A is not referenced.
*
*     LDA     (input) INTEGER
*     The leading dimension of the array A.  LDA >= max(1,N).
*
*     AF      (input) REAL array, dimension (LDAF,N)
*     The factored form of the matrix A.  AF contains the block
*     diagonal matrix D and the multipliers used to obtain the
*     factor U or L from the factorization A = U*D*U**T or A =
*     L*D*L**T as computed by SSYTRF.
*
*     LDAF    (input) INTEGER
*     The leading dimension of the array AF.  LDAF >= max(1,N).
*
*     IPIV    (input) INTEGER array, dimension (N)
*     Details of the interchanges and the block structure of D
*     as determined by SSYTRF.
*
*     S       (input or output) REAL array, dimension (N)
*     The scale factors for A.  If EQUED = 'Y', A is multiplied on
*     the left and right by diag(S).  S is an input argument if FACT =
*     'F'; otherwise, S is an output argument.  If FACT = 'F' and EQUED
*     = 'Y', each element of S must be positive.  If S is output, each
*     element of S is a power of the radix. If S is input, each element
*     of S should be a power of the radix to ensure a reliable solution
*     and error estimates. Scaling by powers of the radix does not cause
*     rounding errors unless the result underflows or overflows.
*     Rounding errors during scaling lead to refining with a matrix that
*     is not equivalent to the input matrix, producing error estimates
*     that may not be reliable.
*
*     B       (input) REAL array, dimension (LDB,NRHS)
*     The right hand side matrix B.
*
*     LDB     (input) INTEGER
*     The leading dimension of the array B.  LDB >= max(1,N).
*
*     X       (input/output) REAL array, dimension (LDX,NRHS)
*     On entry, the solution matrix X, as computed by SGETRS.
*     On exit, the improved solution matrix X.
*
*     LDX     (input) INTEGER
*     The leading dimension of the array X.  LDX >= max(1,N).
*
*     RCOND   (output) REAL
*     Reciprocal scaled condition number.  This is an estimate of the
*     reciprocal Skeel condition number of the matrix A after
*     equilibration (if done).  If this is less than the machine
*     precision (in particular, if it is zero), the matrix is singular
*     to working precision.  Note that the error may still be small even
*     if this number is very small and the matrix appears ill-
*     conditioned.
*
*     BERR    (output) REAL array, dimension (NRHS)
*     Componentwise relative backward error.  This is the
*     componentwise relative backward error of each solution vector X(j)
*     (i.e., the smallest relative change in any element of A or B that
*     makes X(j) an exact solution).
*
*     N_ERR_BNDS (input) INTEGER
*     Number of error bounds to return for each right hand side
*     and each type (normwise or componentwise).  See ERR_BNDS_NORM and
*     ERR_BNDS_COMP below.
*
*     ERR_BNDS_NORM  (output) REAL array, dimension (NRHS, N_ERR_BNDS)
*     For each right-hand side, this array contains information about
*     various error bounds and condition numbers corresponding to the
*     normwise relative error, which is defined as follows:
*
*     Normwise relative error in the ith solution vector:
*             max_j (abs(XTRUE(j,i) - X(j,i)))
*            ------------------------------
*                  max_j abs(X(j,i))
*
*     The array is indexed by the type of error information as described
*     below. There currently are up to three pieces of information
*     returned.
*
*     The first index in ERR_BNDS_NORM(i,:) corresponds to the ith
*     right-hand side.
*
*     The second index in ERR_BNDS_NORM(:,err) contains the following
*     three fields:
*     err = 1 "Trust/don't trust" boolean. Trust the answer if the
*              reciprocal condition number is less than the threshold
*              sqrt(n) * slamch('Epsilon').
*
*     err = 2 "Guaranteed" error bound: The estimated forward error,
*              almost certainly within a factor of 10 of the true error
*              so long as the next entry is greater than the threshold
*              sqrt(n) * slamch('Epsilon'). This error bound should only
*              be trusted if the previous boolean is true.
*
*     err = 3  Reciprocal condition number: Estimated normwise
*              reciprocal condition number.  Compared with the threshold
*              sqrt(n) * slamch('Epsilon') to determine if the error
*              estimate is "guaranteed". These reciprocal condition
*              numbers are 1 / (norm(Z^{-1},inf) * norm(Z,inf)) for some
*              appropriately scaled matrix Z.
*              Let Z = S*A, where S scales each row by a power of the
*              radix so all absolute row sums of Z are approximately 1.
*
*     See Lapack Working Note 165 for further details and extra
*     cautions.
*
*     ERR_BNDS_COMP  (output) REAL array, dimension (NRHS, N_ERR_BNDS)
*     For each right-hand side, this array contains information about
*     various error bounds and condition numbers corresponding to the
*     componentwise relative error, which is defined as follows:
*
*     Componentwise relative error in the ith solution vector:
*                    abs(XTRUE(j,i) - X(j,i))
*             max_j ----------------------
*                         abs(X(j,i))
*
*     The array is indexed by the right-hand side i (on which the
*     componentwise relative error depends), and the type of error
*     information as described below. There currently are up to three
*     pieces of information returned for each right-hand side. If
*     componentwise accuracy is not requested (PARAMS(3) = 0.0), then
*     ERR_BNDS_COMP is not accessed.  If N_ERR_BNDS .LT. 3, then at most
*     the first (:,N_ERR_BNDS) entries are returned.
*
*     The first index in ERR_BNDS_COMP(i,:) corresponds to the ith
*     right-hand side.
*
*     The second index in ERR_BNDS_COMP(:,err) contains the following
*     three fields:
*     err = 1 "Trust/don't trust" boolean. Trust the answer if the
*              reciprocal condition number is less than the threshold
*              sqrt(n) * slamch('Epsilon').
*
*     err = 2 "Guaranteed" error bound: The estimated forward error,
*              almost certainly within a factor of 10 of the true error
*              so long as the next entry is greater than the threshold
*              sqrt(n) * slamch('Epsilon'). This error bound should only
*              be trusted if the previous boolean is true.
*
*     err = 3  Reciprocal condition number: Estimated componentwise
*              reciprocal condition number.  Compared with the threshold
*              sqrt(n) * slamch('Epsilon') to determine if the error
*              estimate is "guaranteed". These reciprocal condition
*              numbers are 1 / (norm(Z^{-1},inf) * norm(Z,inf)) for some
*              appropriately scaled matrix Z.
*              Let Z = S*(A*diag(x)), where x is the solution for the
*              current right-hand side and S scales each row of
*              A*diag(x) by a power of the radix so all absolute row
*              sums of Z are approximately 1.
*
*     See Lapack Working Note 165 for further details and extra
*     cautions.
*
*     NPARAMS (input) INTEGER
*     Specifies the number of parameters set in PARAMS.  If .LE. 0, the
*     PARAMS array is never referenced and default values are used.
*
*     PARAMS  (input / output) REAL array, dimension NPARAMS
*     Specifies algorithm parameters.  If an entry is .LT. 0.0, then
*     that entry will be filled with default value used for that
*     parameter.  Only positions up to NPARAMS are accessed; defaults
*     are used for higher-numbered parameters.
*
*       PARAMS(LA_LINRX_ITREF_I = 1) : Whether to perform iterative
*            refinement or not.
*         Default: 1.0
*            = 0.0 : No refinement is performed, and no error bounds are
*                    computed.
*            = 1.0 : Use the double-precision refinement algorithm,
*                    possibly with doubled-single computations if the
*                    compilation environment does not support DOUBLE
*                    PRECISION.
*              (other values are reserved for future use)
*
*       PARAMS(LA_LINRX_ITHRESH_I = 2) : Maximum number of residual
*            computations allowed for refinement.
*         Default: 10
*         Aggressive: Set to 100 to permit convergence using approximate
*                     factorizations or factorizations other than LU. If
*                     the factorization uses a technique other than
*                     Gaussian elimination, the guarantees in
*                     err_bnds_norm and err_bnds_comp may no longer be
*                     trustworthy.
*
*       PARAMS(LA_LINRX_CWISE_I = 3) : Flag determining if the code
*            will attempt to find a solution with small componentwise
*            relative error in the double-precision algorithm.  Positive
*            is true, 0.0 is false.
*         Default: 1.0 (attempt componentwise convergence)
*
*     WORK    (workspace) REAL array, dimension (4*N)
*
*     IWORK   (workspace) INTEGER array, dimension (N)
*
*     INFO    (output) INTEGER
*       = 0:  Successful exit. The solution to every right-hand side is
*         guaranteed.
*       < 0:  If INFO = -i, the i-th argument had an illegal value
*       > 0 and <= N:  U(INFO,INFO) is exactly zero.  The factorization
*         has been completed, but the factor U is exactly singular, so
*         the solution and error bounds could not be computed. RCOND = 0
*         is returned.
*       = N+J: The solution corresponding to the Jth right-hand side is
*         not guaranteed. The solutions corresponding to other right-
*         hand sides K with K > J may not be guaranteed as well, but
*         only the first such right-hand side is reported. If a small
*         componentwise error is not requested (PARAMS(3) = 0.0) then
*         the Jth right-hand side is the first with a normwise error
*         bound that is not guaranteed (the smallest J such
*         that ERR_BNDS_NORM(J,1) = 0.0). By default (PARAMS(3) = 1.0)
*         the Jth right-hand side is the first with either a normwise or
*         componentwise error bound that is not guaranteed (the smallest
*         J such that either ERR_BNDS_NORM(J,1) = 0.0 or
*         ERR_BNDS_COMP(J,1) = 0.0). See the definition of
*         ERR_BNDS_NORM(:,1) and ERR_BNDS_COMP(:,1). To get information
*         about all of the right-hand sides check ERR_BNDS_NORM or
*         ERR_BNDS_COMP.
*

*     ==================================================================
*


    
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ssysv

USAGE:
  ipiv, work, info, a, b = NumRu::Lapack.ssysv( uplo, a, b, [:lwork => lwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYSV( UPLO, N, NRHS, A, LDA, IPIV, B, LDB, WORK, LWORK, INFO )

*  Purpose
*  =======
*
*  SSYSV computes the solution to a real system of linear equations
*     A * X = B,
*  where A is an N-by-N symmetric matrix and X and B are N-by-NRHS
*  matrices.
*
*  The diagonal pivoting method is used to factor A as
*     A = U * D * U**T,  if UPLO = 'U', or
*     A = L * D * L**T,  if UPLO = 'L',
*  where U (or L) is a product of permutation and unit upper (lower)
*  triangular matrices, and D is symmetric and block diagonal with 
*  1-by-1 and 2-by-2 diagonal blocks.  The factored form of A is then
*  used to solve the system of equations A * X = B.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored;
*          = 'L':  Lower triangle of A is stored.
*
*  N       (input) INTEGER
*          The number of linear equations, i.e., the order of the
*          matrix A.  N >= 0.
*
*  NRHS    (input) INTEGER
*          The number of right hand sides, i.e., the number of columns
*          of the matrix B.  NRHS >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the leading
*          N-by-N upper triangular part of A contains the upper
*          triangular part of the matrix A, and the strictly lower
*          triangular part of A is not referenced.  If UPLO = 'L', the
*          leading N-by-N lower triangular part of A contains the lower
*          triangular part of the matrix A, and the strictly upper
*          triangular part of A is not referenced.
*
*          On exit, if INFO = 0, the block diagonal matrix D and the
*          multipliers used to obtain the factor U or L from the
*          factorization A = U*D*U**T or A = L*D*L**T as computed by
*          SSYTRF.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (output) INTEGER array, dimension (N)
*          Details of the interchanges and the block structure of D, as
*          determined by SSYTRF.  If IPIV(k) > 0, then rows and columns
*          k and IPIV(k) were interchanged, and D(k,k) is a 1-by-1
*          diagonal block.  If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0,
*          then rows and columns k-1 and -IPIV(k) were interchanged and
*          D(k-1:k,k-1:k) is a 2-by-2 diagonal block.  If UPLO = 'L' and
*          IPIV(k) = IPIV(k+1) < 0, then rows and columns k+1 and
*          -IPIV(k) were interchanged and D(k:k+1,k:k+1) is a 2-by-2
*          diagonal block.
*
*  B       (input/output) REAL array, dimension (LDB,NRHS)
*          On entry, the N-by-NRHS right hand side matrix B.
*          On exit, if INFO = 0, the N-by-NRHS solution matrix X.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The length of WORK.  LWORK >= 1, and for best performance
*          LWORK >= max(1,N*NB), where NB is the optimal blocksize for
*          SSYTRF.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array, and no error
*          message related to LWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0: successful exit
*          < 0: if INFO = -i, the i-th argument had an illegal value
*          > 0: if INFO = i, D(i,i) is exactly zero.  The factorization
*               has been completed, but the block diagonal matrix D is
*               exactly singular, so the solution could not be computed.
*

*  =====================================================================
*
*     .. Local Scalars ..
      LOGICAL            LQUERY
      INTEGER            LWKOPT, NB
*     ..
*     .. External Functions ..
      LOGICAL            LSAME
      INTEGER            ILAENV
      EXTERNAL           ILAENV, LSAME
*     ..
*     .. External Subroutines ..
      EXTERNAL           SSYTRF, SSYTRS2, XERBLA
*     ..
*     .. Intrinsic Functions ..
      INTRINSIC          MAX
*     ..


    
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ssysvx

USAGE:
  x, rcond, ferr, berr, work, info, af, ipiv = NumRu::Lapack.ssysvx( fact, uplo, a, af, ipiv, b, [:lwork => lwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYSVX( FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, IPIV, B, LDB, X, LDX, RCOND, FERR, BERR, WORK, LWORK, IWORK, INFO )

*  Purpose
*  =======
*
*  SSYSVX uses the diagonal pivoting factorization to compute the
*  solution to a real system of linear equations A * X = B,
*  where A is an N-by-N symmetric matrix and X and B are N-by-NRHS
*  matrices.
*
*  Error bounds on the solution and a condition estimate are also
*  provided.
*
*  Description
*  ===========
*
*  The following steps are performed:
*
*  1. If FACT = 'N', the diagonal pivoting method is used to factor A.
*     The form of the factorization is
*        A = U * D * U**T,  if UPLO = 'U', or
*        A = L * D * L**T,  if UPLO = 'L',
*     where U (or L) is a product of permutation and unit upper (lower)
*     triangular matrices, and D is symmetric and block diagonal with
*     1-by-1 and 2-by-2 diagonal blocks.
*
*  2. If some D(i,i)=0, so that D is exactly singular, then the routine
*     returns with INFO = i. Otherwise, the factored form of A is used
*     to estimate the condition number of the matrix A.  If the
*     reciprocal of the condition number is less than machine precision,
*     INFO = N+1 is returned as a warning, but the routine still goes on
*     to solve for X and compute error bounds as described below.
*
*  3. The system of equations is solved for X using the factored form
*     of A.
*
*  4. Iterative refinement is applied to improve the computed solution
*     matrix and calculate error bounds and backward error estimates
*     for it.
*

*  Arguments
*  =========
*
*  FACT    (input) CHARACTER*1
*          Specifies whether or not the factored form of A has been
*          supplied on entry.
*          = 'F':  On entry, AF and IPIV contain the factored form of
*                  A.  AF and IPIV will not be modified.
*          = 'N':  The matrix A will be copied to AF and factored.
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored;
*          = 'L':  Lower triangle of A is stored.
*
*  N       (input) INTEGER
*          The number of linear equations, i.e., the order of the
*          matrix A.  N >= 0.
*
*  NRHS    (input) INTEGER
*          The number of right hand sides, i.e., the number of columns
*          of the matrices B and X.  NRHS >= 0.
*
*  A       (input) REAL array, dimension (LDA,N)
*          The symmetric matrix A.  If UPLO = 'U', the leading N-by-N
*          upper triangular part of A contains the upper triangular part
*          of the matrix A, and the strictly lower triangular part of A
*          is not referenced.  If UPLO = 'L', the leading N-by-N lower
*          triangular part of A contains the lower triangular part of
*          the matrix A, and the strictly upper triangular part of A is
*          not referenced.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  AF      (input or output) REAL array, dimension (LDAF,N)
*          If FACT = 'F', then AF is an input argument and on entry
*          contains the block diagonal matrix D and the multipliers used
*          to obtain the factor U or L from the factorization
*          A = U*D*U**T or A = L*D*L**T as computed by SSYTRF.
*
*          If FACT = 'N', then AF is an output argument and on exit
*          returns the block diagonal matrix D and the multipliers used
*          to obtain the factor U or L from the factorization
*          A = U*D*U**T or A = L*D*L**T.
*
*  LDAF    (input) INTEGER
*          The leading dimension of the array AF.  LDAF >= max(1,N).
*
*  IPIV    (input or output) INTEGER array, dimension (N)
*          If FACT = 'F', then IPIV is an input argument and on entry
*          contains details of the interchanges and the block structure
*          of D, as determined by SSYTRF.
*          If IPIV(k) > 0, then rows and columns k and IPIV(k) were
*          interchanged and D(k,k) is a 1-by-1 diagonal block.
*          If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0, then rows and
*          columns k-1 and -IPIV(k) were interchanged and D(k-1:k,k-1:k)
*          is a 2-by-2 diagonal block.  If UPLO = 'L' and IPIV(k) =
*          IPIV(k+1) < 0, then rows and columns k+1 and -IPIV(k) were
*          interchanged and D(k:k+1,k:k+1) is a 2-by-2 diagonal block.
*
*          If FACT = 'N', then IPIV is an output argument and on exit
*          contains details of the interchanges and the block structure
*          of D, as determined by SSYTRF.
*
*  B       (input) REAL array, dimension (LDB,NRHS)
*          The N-by-NRHS right hand side matrix B.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  X       (output) REAL array, dimension (LDX,NRHS)
*          If INFO = 0 or INFO = N+1, the N-by-NRHS solution matrix X.
*
*  LDX     (input) INTEGER
*          The leading dimension of the array X.  LDX >= max(1,N).
*
*  RCOND   (output) REAL
*          The estimate of the reciprocal condition number of the matrix
*          A.  If RCOND is less than the machine precision (in
*          particular, if RCOND = 0), the matrix is singular to working
*          precision.  This condition is indicated by a return code of
*          INFO > 0.
*
*  FERR    (output) REAL array, dimension (NRHS)
*          The estimated forward error bound for each solution vector
*          X(j) (the j-th column of the solution matrix X).
*          If XTRUE is the true solution corresponding to X(j), FERR(j)
*          is an estimated upper bound for the magnitude of the largest
*          element in (X(j) - XTRUE) divided by the magnitude of the
*          largest element in X(j).  The estimate is as reliable as
*          the estimate for RCOND, and is almost always a slight
*          overestimate of the true error.
*
*  BERR    (output) REAL array, dimension (NRHS)
*          The componentwise relative backward error of each solution
*          vector X(j) (i.e., the smallest relative change in
*          any element of A or B that makes X(j) an exact solution).
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The length of WORK.  LWORK >= max(1,3*N), and for best
*          performance, when FACT = 'N', LWORK >= max(1,3*N,N*NB), where
*          NB is the optimal blocksize for SSYTRF.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array, and no error
*          message related to LWORK is issued by XERBLA.
*
*  IWORK   (workspace) INTEGER array, dimension (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:  D(i,i) is exactly zero.  The factorization
*                       has been completed but the factor D is exactly
*                       singular, so the solution and error bounds could
*                       not be computed. RCOND = 0 is returned.
*                = N+1: D is nonsingular, but RCOND is less than machine
*                       precision, meaning that the matrix is singular
*                       to working precision.  Nevertheless, the
*                       solution and error bounds are computed because
*                       there are a number of situations where the
*                       computed solution can be more accurate than the
*                       value of RCOND would suggest.
*

*  =====================================================================
*


    
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ssysvxx

USAGE:
  x, rcond, rpvgrw, berr, err_bnds_norm, err_bnds_comp, info, a, af, ipiv, equed, s, b, params = NumRu::Lapack.ssysvxx( fact, uplo, a, af, ipiv, equed, s, b, params, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYSVXX( FACT, UPLO, N, NRHS, A, LDA, AF, LDAF, IPIV, EQUED, S, B, LDB, X, LDX, RCOND, RPVGRW, BERR, N_ERR_BNDS, ERR_BNDS_NORM, ERR_BNDS_COMP, NPARAMS, PARAMS, WORK, IWORK, INFO )

*     Purpose
*     =======
*
*     SSYSVXX uses the diagonal pivoting factorization to compute the
*     solution to a real system of linear equations A * X = B, where A
*     is an N-by-N symmetric matrix and X and B are N-by-NRHS matrices.
*
*     If requested, both normwise and maximum componentwise error bounds
*     are returned. SSYSVXX will return a solution with a tiny
*     guaranteed error (O(eps) where eps is the working machine
*     precision) unless the matrix is very ill-conditioned, in which
*     case a warning is returned. Relevant condition numbers also are
*     calculated and returned.
*
*     SSYSVXX accepts user-provided factorizations and equilibration
*     factors; see the definitions of the FACT and EQUED options.
*     Solving with refinement and using a factorization from a previous
*     SSYSVXX call will also produce a solution with either O(eps)
*     errors or warnings, but we cannot make that claim for general
*     user-provided factorizations and equilibration factors if they
*     differ from what SSYSVXX would itself produce.
*
*     Description
*     ===========
*
*     The following steps are performed:
*
*     1. If FACT = 'E', real scaling factors are computed to equilibrate
*     the system:
*
*       diag(S)*A*diag(S)     *inv(diag(S))*X = diag(S)*B
*
*     Whether or not the system will be equilibrated depends on the
*     scaling of the matrix A, but if equilibration is used, A is
*     overwritten by diag(S)*A*diag(S) and B by diag(S)*B.
*
*     2. If FACT = 'N' or 'E', the LU decomposition is used to factor
*     the matrix A (after equilibration if FACT = 'E') as
*
*        A = U * D * U**T,  if UPLO = 'U', or
*        A = L * D * L**T,  if UPLO = 'L',
*
*     where U (or L) is a product of permutation and unit upper (lower)
*     triangular matrices, and D is symmetric and block diagonal with
*     1-by-1 and 2-by-2 diagonal blocks.
*
*     3. If some D(i,i)=0, so that D is exactly singular, then the
*     routine returns with INFO = i. Otherwise, the factored form of A
*     is used to estimate the condition number of the matrix A (see
*     argument RCOND).  If the reciprocal of the condition number is
*     less than machine precision, the routine still goes on to solve
*     for X and compute error bounds as described below.
*
*     4. The system of equations is solved for X using the factored form
*     of A.
*
*     5. By default (unless PARAMS(LA_LINRX_ITREF_I) is set to zero),
*     the routine will use iterative refinement to try to get a small
*     error and error bounds.  Refinement calculates the residual to at
*     least twice the working precision.
*
*     6. If equilibration was used, the matrix X is premultiplied by
*     diag(R) so that it solves the original system before
*     equilibration.
*

*     Arguments
*     =========
*
*     Some optional parameters are bundled in the PARAMS array.  These
*     settings determine how refinement is performed, but often the
*     defaults are acceptable.  If the defaults are acceptable, users
*     can pass NPARAMS = 0 which prevents the source code from accessing
*     the PARAMS argument.
*
*     FACT    (input) CHARACTER*1
*     Specifies whether or not the factored form of the matrix A is
*     supplied on entry, and if not, whether the matrix A should be
*     equilibrated before it is factored.
*       = 'F':  On entry, AF and IPIV contain the factored form of A.
*               If EQUED is not 'N', the matrix A has been
*               equilibrated with scaling factors given by S.
*               A, AF, and IPIV are not modified.
*       = 'N':  The matrix A will be copied to AF and factored.
*       = 'E':  The matrix A will be equilibrated if necessary, then
*               copied to AF and factored.
*
*     UPLO    (input) CHARACTER*1
*       = 'U':  Upper triangle of A is stored;
*       = 'L':  Lower triangle of A is stored.
*
*     N       (input) INTEGER
*     The number of linear equations, i.e., the order of the
*     matrix A.  N >= 0.
*
*     NRHS    (input) INTEGER
*     The number of right hand sides, i.e., the number of columns
*     of the matrices B and X.  NRHS >= 0.
*
*     A       (input/output) REAL array, dimension (LDA,N)
*     The symmetric matrix A.  If UPLO = 'U', the leading N-by-N
*     upper triangular part of A contains the upper triangular
*     part of the matrix A, and the strictly lower triangular
*     part of A is not referenced.  If UPLO = 'L', the leading
*     N-by-N lower triangular part of A contains the lower
*     triangular part of the matrix A, and the strictly upper
*     triangular part of A is not referenced.
*
*     On exit, if FACT = 'E' and EQUED = 'Y', A is overwritten by
*     diag(S)*A*diag(S).
*
*     LDA     (input) INTEGER
*     The leading dimension of the array A.  LDA >= max(1,N).
*
*     AF      (input or output) REAL array, dimension (LDAF,N)
*     If FACT = 'F', then AF is an input argument and on entry
*     contains the block diagonal matrix D and the multipliers
*     used to obtain the factor U or L from the factorization A =
*     U*D*U**T or A = L*D*L**T as computed by SSYTRF.
*
*     If FACT = 'N', then AF is an output argument and on exit
*     returns the block diagonal matrix D and the multipliers
*     used to obtain the factor U or L from the factorization A =
*     U*D*U**T or A = L*D*L**T.
*
*     LDAF    (input) INTEGER
*     The leading dimension of the array AF.  LDAF >= max(1,N).
*
*     IPIV    (input or output) INTEGER array, dimension (N)
*     If FACT = 'F', then IPIV is an input argument and on entry
*     contains details of the interchanges and the block
*     structure of D, as determined by SSYTRF.  If IPIV(k) > 0,
*     then rows and columns k and IPIV(k) were interchanged and
*     D(k,k) is a 1-by-1 diagonal block.  If UPLO = 'U' and
*     IPIV(k) = IPIV(k-1) < 0, then rows and columns k-1 and
*     -IPIV(k) were interchanged and D(k-1:k,k-1:k) is a 2-by-2
*     diagonal block.  If UPLO = 'L' and IPIV(k) = IPIV(k+1) < 0,
*     then rows and columns k+1 and -IPIV(k) were interchanged
*     and D(k:k+1,k:k+1) is a 2-by-2 diagonal block.
*
*     If FACT = 'N', then IPIV is an output argument and on exit
*     contains details of the interchanges and the block
*     structure of D, as determined by SSYTRF.
*
*     EQUED   (input or output) CHARACTER*1
*     Specifies the form of equilibration that was done.
*       = 'N':  No equilibration (always true if FACT = 'N').
*       = 'Y':  Both row and column equilibration, i.e., A has been
*               replaced by diag(S) * A * diag(S).
*     EQUED is an input argument if FACT = 'F'; otherwise, it is an
*     output argument.
*
*     S       (input or output) REAL array, dimension (N)
*     The scale factors for A.  If EQUED = 'Y', A is multiplied on
*     the left and right by diag(S).  S is an input argument if FACT =
*     'F'; otherwise, S is an output argument.  If FACT = 'F' and EQUED
*     = 'Y', each element of S must be positive.  If S is output, each
*     element of S is a power of the radix. If S is input, each element
*     of S should be a power of the radix to ensure a reliable solution
*     and error estimates. Scaling by powers of the radix does not cause
*     rounding errors unless the result underflows or overflows.
*     Rounding errors during scaling lead to refining with a matrix that
*     is not equivalent to the input matrix, producing error estimates
*     that may not be reliable.
*
*     B       (input/output) REAL array, dimension (LDB,NRHS)
*     On entry, the N-by-NRHS right hand side matrix B.
*     On exit,
*     if EQUED = 'N', B is not modified;
*     if EQUED = 'Y', B is overwritten by diag(S)*B;
*
*     LDB     (input) INTEGER
*     The leading dimension of the array B.  LDB >= max(1,N).
*
*     X       (output) REAL array, dimension (LDX,NRHS)
*     If INFO = 0, the N-by-NRHS solution matrix X to the original
*     system of equations.  Note that A and B are modified on exit if
*     EQUED .ne. 'N', and the solution to the equilibrated system is
*     inv(diag(S))*X.
*
*     LDX     (input) INTEGER
*     The leading dimension of the array X.  LDX >= max(1,N).
*
*     RCOND   (output) REAL
*     Reciprocal scaled condition number.  This is an estimate of the
*     reciprocal Skeel condition number of the matrix A after
*     equilibration (if done).  If this is less than the machine
*     precision (in particular, if it is zero), the matrix is singular
*     to working precision.  Note that the error may still be small even
*     if this number is very small and the matrix appears ill-
*     conditioned.
*
*     RPVGRW  (output) REAL
*     Reciprocal pivot growth.  On exit, this contains the reciprocal
*     pivot growth factor norm(A)/norm(U). The "max absolute element"
*     norm is used.  If this is much less than 1, then the stability of
*     the LU factorization of the (equilibrated) matrix A could be poor.
*     This also means that the solution X, estimated condition numbers,
*     and error bounds could be unreliable. If factorization fails with
*     0 0 and <= N:  U(INFO,INFO) is exactly zero.  The factorization
*         has been completed, but the factor U is exactly singular, so
*         the solution and error bounds could not be computed. RCOND = 0
*         is returned.
*       = N+J: The solution corresponding to the Jth right-hand side is
*         not guaranteed. The solutions corresponding to other right-
*         hand sides K with K > J may not be guaranteed as well, but
*         only the first such right-hand side is reported. If a small
*         componentwise error is not requested (PARAMS(3) = 0.0) then
*         the Jth right-hand side is the first with a normwise error
*         bound that is not guaranteed (the smallest J such
*         that ERR_BNDS_NORM(J,1) = 0.0). By default (PARAMS(3) = 1.0)
*         the Jth right-hand side is the first with either a normwise or
*         componentwise error bound that is not guaranteed (the smallest
*         J such that either ERR_BNDS_NORM(J,1) = 0.0 or
*         ERR_BNDS_COMP(J,1) = 0.0). See the definition of
*         ERR_BNDS_NORM(:,1) and ERR_BNDS_COMP(:,1). To get information
*         about all of the right-hand sides check ERR_BNDS_NORM or
*         ERR_BNDS_COMP.
*

*     ==================================================================
*


    
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ssyswapr

USAGE:
  a = NumRu::Lapack.ssyswapr( uplo, a, i1, i2, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYSWAPR( UPLO, N, A, I1, I2)

*  Purpose
*  =======
*
*  SSYSWAPR applies an elementary permutation on the rows and the columns of
*  a symmetric matrix.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the details of the factorization are stored
*          as an upper or lower triangular matrix.
*          = 'U':  Upper triangular, form is A = U*D*U**T;
*          = 'L':  Lower triangular, form is A = L*D*L**T.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the NB diagonal matrix D and the multipliers
*          used to obtain the factor U or L as computed by SSYTRF.
*
*          On exit, if INFO = 0, the (symmetric) inverse of the original
*          matrix.  If UPLO = 'U', the upper triangular part of the
*          inverse is formed and the part of A below the diagonal is not
*          referenced; if UPLO = 'L' the lower triangular part of the
*          inverse is formed and the part of A above the diagonal is
*          not referenced.
*
*  I1      (input) INTEGER
*          Index of the first row to swap
*
*  I2      (input) INTEGER
*          Index of the second row to swap
*

*  =====================================================================
*
*     ..
*     .. Local Scalars ..
      LOGICAL            UPPER
      INTEGER            I
      REAL               TMP
*
*     .. External Functions ..
      LOGICAL            LSAME
      EXTERNAL           LSAME
*     ..
*     .. External Subroutines ..
      EXTERNAL           SSWAP
*     ..


    
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ssytd2

USAGE:
  d, e, tau, info, a = NumRu::Lapack.ssytd2( uplo, a, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYTD2( UPLO, N, A, LDA, D, E, TAU, INFO )

*  Purpose
*  =======
*
*  SSYTD2 reduces a real symmetric matrix A to symmetric tridiagonal
*  form T by an orthogonal similarity transformation: Q' * A * Q = T.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the upper or lower triangular part of the
*          symmetric matrix A is stored:
*          = 'U':  Upper triangular
*          = 'L':  Lower triangular
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the leading
*          n-by-n upper triangular part of A contains the upper
*          triangular part of the matrix A, and the strictly lower
*          triangular part of A is not referenced.  If UPLO = 'L', the
*          leading n-by-n lower triangular part of A contains the lower
*          triangular part of the matrix A, and the strictly upper
*          triangular part of A is not referenced.
*          On exit, if UPLO = 'U', the diagonal and first superdiagonal
*          of A are overwritten by the corresponding elements of the
*          tridiagonal matrix T, and the elements above the first
*          superdiagonal, with the array TAU, represent the orthogonal
*          matrix Q as a product of elementary reflectors; if UPLO
*          = 'L', the diagonal and first subdiagonal of A are over-
*          written by the corresponding elements of the tridiagonal
*          matrix T, and the elements below the first subdiagonal, with
*          the array TAU, represent the orthogonal matrix Q as a product
*          of elementary reflectors. See Further Details.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  D       (output) REAL array, dimension (N)
*          The diagonal elements of the tridiagonal matrix T:
*          D(i) = A(i,i).
*
*  E       (output) REAL array, dimension (N-1)
*          The off-diagonal elements of the tridiagonal matrix T:
*          E(i) = A(i,i+1) if UPLO = 'U', E(i) = A(i+1,i) if UPLO = 'L'.
*
*  TAU     (output) REAL array, dimension (N-1)
*          The scalar factors of the elementary reflectors (see Further
*          Details).
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value.
*

*  Further Details
*  ===============
*
*  If UPLO = 'U', the matrix Q is represented as a product of elementary
*  reflectors
*
*     Q = H(n-1) . . . H(2) H(1).
*
*  Each H(i) has the form
*
*     H(i) = I - tau * v * v'
*
*  where tau is a real scalar, and v is a real vector with
*  v(i+1:n) = 0 and v(i) = 1; v(1:i-1) is stored on exit in
*  A(1:i-1,i+1), and tau in TAU(i).
*
*  If UPLO = 'L', the matrix Q is represented as a product of elementary
*  reflectors
*
*     Q = H(1) H(2) . . . H(n-1).
*
*  Each H(i) has the form
*
*     H(i) = I - tau * v * v'
*
*  where tau is a real scalar, and v is a real vector with
*  v(1:i) = 0 and v(i+1) = 1; v(i+2:n) is stored on exit in A(i+2:n,i),
*  and tau in TAU(i).
*
*  The contents of A on exit are illustrated by the following examples
*  with n = 5:
*
*  if UPLO = 'U':                       if UPLO = 'L':
*
*    (  d   e   v2  v3  v4 )              (  d                  )
*    (      d   e   v3  v4 )              (  e   d              )
*    (          d   e   v4 )              (  v1  e   d          )
*    (              d   e  )              (  v1  v2  e   d      )
*    (                  d  )              (  v1  v2  v3  e   d  )
*
*  where d and e denote diagonal and off-diagonal elements of T, and vi
*  denotes an element of the vector defining H(i).
*
*  =====================================================================
*


    
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ssytf2

USAGE:
  ipiv, info, a = NumRu::Lapack.ssytf2( uplo, a, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYTF2( UPLO, N, A, LDA, IPIV, INFO )

*  Purpose
*  =======
*
*  SSYTF2 computes the factorization of a real symmetric matrix A using
*  the Bunch-Kaufman diagonal pivoting method:
*
*     A = U*D*U'  or  A = L*D*L'
*
*  where U (or L) is a product of permutation and unit upper (lower)
*  triangular matrices, U' is the transpose of U, and D is symmetric and
*  block diagonal with 1-by-1 and 2-by-2 diagonal blocks.
*
*  This is the unblocked version of the algorithm, calling Level 2 BLAS.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the upper or lower triangular part of the
*          symmetric matrix A is stored:
*          = 'U':  Upper triangular
*          = 'L':  Lower triangular
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the leading
*          n-by-n upper triangular part of A contains the upper
*          triangular part of the matrix A, and the strictly lower
*          triangular part of A is not referenced.  If UPLO = 'L', the
*          leading n-by-n lower triangular part of A contains the lower
*          triangular part of the matrix A, and the strictly upper
*          triangular part of A is not referenced.
*
*          On exit, the block diagonal matrix D and the multipliers used
*          to obtain the factor U or L (see below for further details).
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (output) INTEGER array, dimension (N)
*          Details of the interchanges and the block structure of D.
*          If IPIV(k) > 0, then rows and columns k and IPIV(k) were
*          interchanged and D(k,k) is a 1-by-1 diagonal block.
*          If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0, then rows and
*          columns k-1 and -IPIV(k) were interchanged and D(k-1:k,k-1:k)
*          is a 2-by-2 diagonal block.  If UPLO = 'L' and IPIV(k) =
*          IPIV(k+1) < 0, then rows and columns k+1 and -IPIV(k) were
*          interchanged and D(k:k+1,k:k+1) is a 2-by-2 diagonal block.
*
*  INFO    (output) INTEGER
*          = 0: successful exit
*          < 0: if INFO = -k, the k-th argument had an illegal value
*          > 0: if INFO = k, D(k,k) is exactly zero.  The factorization
*               has been completed, but the block diagonal matrix D is
*               exactly singular, and division by zero will occur if it
*               is used to solve a system of equations.
*

*  Further Details
*  ===============
*
*  09-29-06 - patch from
*    Bobby Cheng, MathWorks
*
*    Replace l.204 and l.372
*         IF( MAX( ABSAKK, COLMAX ).EQ.ZERO ) THEN
*    by
*         IF( (MAX( ABSAKK, COLMAX ).EQ.ZERO) .OR. SISNAN(ABSAKK) ) THEN
*
*  01-01-96 - Based on modifications by
*    J. Lewis, Boeing Computer Services Company
*    A. Petitet, Computer Science Dept., Univ. of Tenn., Knoxville, USA
*  1-96 - Based on modifications by J. Lewis, Boeing Computer Services
*         Company
*
*  If UPLO = 'U', then A = U*D*U', where
*     U = P(n)*U(n)* ... *P(k)U(k)* ...,
*  i.e., U is a product of terms P(k)*U(k), where k decreases from n to
*  1 in steps of 1 or 2, and D is a block diagonal matrix with 1-by-1
*  and 2-by-2 diagonal blocks D(k).  P(k) is a permutation matrix as
*  defined by IPIV(k), and U(k) is a unit upper triangular matrix, such
*  that if the diagonal block D(k) is of order s (s = 1 or 2), then
*
*             (   I    v    0   )   k-s
*     U(k) =  (   0    I    0   )   s
*             (   0    0    I   )   n-k
*                k-s   s   n-k
*
*  If s = 1, D(k) overwrites A(k,k), and v overwrites A(1:k-1,k).
*  If s = 2, the upper triangle of D(k) overwrites A(k-1,k-1), A(k-1,k),
*  and A(k,k), and v overwrites A(1:k-2,k-1:k).
*
*  If UPLO = 'L', then A = L*D*L', where
*     L = P(1)*L(1)* ... *P(k)*L(k)* ...,
*  i.e., L is a product of terms P(k)*L(k), where k increases from 1 to
*  n in steps of 1 or 2, and D is a block diagonal matrix with 1-by-1
*  and 2-by-2 diagonal blocks D(k).  P(k) is a permutation matrix as
*  defined by IPIV(k), and L(k) is a unit lower triangular matrix, such
*  that if the diagonal block D(k) is of order s (s = 1 or 2), then
*
*             (   I    0     0   )  k-1
*     L(k) =  (   0    I     0   )  s
*             (   0    v     I   )  n-k-s+1
*                k-1   s  n-k-s+1
*
*  If s = 1, D(k) overwrites A(k,k), and v overwrites A(k+1:n,k).
*  If s = 2, the lower triangle of D(k) overwrites A(k,k), A(k+1,k),
*  and A(k+1,k+1), and v overwrites A(k+2:n,k:k+1).
*
*  =====================================================================
*


    
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ssytrd

USAGE:
  d, e, tau, work, info, a = NumRu::Lapack.ssytrd( uplo, a, lwork, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYTRD( UPLO, N, A, LDA, D, E, TAU, WORK, LWORK, INFO )

*  Purpose
*  =======
*
*  SSYTRD reduces a real symmetric matrix A to real symmetric
*  tridiagonal form T by an orthogonal similarity transformation:
*  Q**T * A * Q = T.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored;
*          = 'L':  Lower triangle of A is stored.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the leading
*          N-by-N upper triangular part of A contains the upper
*          triangular part of the matrix A, and the strictly lower
*          triangular part of A is not referenced.  If UPLO = 'L', the
*          leading N-by-N lower triangular part of A contains the lower
*          triangular part of the matrix A, and the strictly upper
*          triangular part of A is not referenced.
*          On exit, if UPLO = 'U', the diagonal and first superdiagonal
*          of A are overwritten by the corresponding elements of the
*          tridiagonal matrix T, and the elements above the first
*          superdiagonal, with the array TAU, represent the orthogonal
*          matrix Q as a product of elementary reflectors; if UPLO
*          = 'L', the diagonal and first subdiagonal of A are over-
*          written by the corresponding elements of the tridiagonal
*          matrix T, and the elements below the first subdiagonal, with
*          the array TAU, represent the orthogonal matrix Q as a product
*          of elementary reflectors. See Further Details.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  D       (output) REAL array, dimension (N)
*          The diagonal elements of the tridiagonal matrix T:
*          D(i) = A(i,i).
*
*  E       (output) REAL array, dimension (N-1)
*          The off-diagonal elements of the tridiagonal matrix T:
*          E(i) = A(i,i+1) if UPLO = 'U', E(i) = A(i+1,i) if UPLO = 'L'.
*
*  TAU     (output) REAL array, dimension (N-1)
*          The scalar factors of the elementary reflectors (see Further
*          Details).
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The dimension of the array WORK.  LWORK >= 1.
*          For optimum performance LWORK >= N*NB, where NB is the
*          optimal blocksize.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array, and no error
*          message related to LWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*

*  Further Details
*  ===============
*
*  If UPLO = 'U', the matrix Q is represented as a product of elementary
*  reflectors
*
*     Q = H(n-1) . . . H(2) H(1).
*
*  Each H(i) has the form
*
*     H(i) = I - tau * v * v'
*
*  where tau is a real scalar, and v is a real vector with
*  v(i+1:n) = 0 and v(i) = 1; v(1:i-1) is stored on exit in
*  A(1:i-1,i+1), and tau in TAU(i).
*
*  If UPLO = 'L', the matrix Q is represented as a product of elementary
*  reflectors
*
*     Q = H(1) H(2) . . . H(n-1).
*
*  Each H(i) has the form
*
*     H(i) = I - tau * v * v'
*
*  where tau is a real scalar, and v is a real vector with
*  v(1:i) = 0 and v(i+1) = 1; v(i+2:n) is stored on exit in A(i+2:n,i),
*  and tau in TAU(i).
*
*  The contents of A on exit are illustrated by the following examples
*  with n = 5:
*
*  if UPLO = 'U':                       if UPLO = 'L':
*
*    (  d   e   v2  v3  v4 )              (  d                  )
*    (      d   e   v3  v4 )              (  e   d              )
*    (          d   e   v4 )              (  v1  e   d          )
*    (              d   e  )              (  v1  v2  e   d      )
*    (                  d  )              (  v1  v2  v3  e   d  )
*
*  where d and e denote diagonal and off-diagonal elements of T, and vi
*  denotes an element of the vector defining H(i).
*
*  =====================================================================
*


    
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ssytrf

USAGE:
  ipiv, work, info, a = NumRu::Lapack.ssytrf( uplo, a, lwork, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYTRF( UPLO, N, A, LDA, IPIV, WORK, LWORK, INFO )

*  Purpose
*  =======
*
*  SSYTRF computes the factorization of a real symmetric matrix A using
*  the Bunch-Kaufman diagonal pivoting method.  The form of the
*  factorization is
*
*     A = U*D*U**T  or  A = L*D*L**T
*
*  where U (or L) is a product of permutation and unit upper (lower)
*  triangular matrices, and D is symmetric and block diagonal with 
*  1-by-1 and 2-by-2 diagonal blocks.
*
*  This is the blocked version of the algorithm, calling Level 3 BLAS.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          = 'U':  Upper triangle of A is stored;
*          = 'L':  Lower triangle of A is stored.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the symmetric matrix A.  If UPLO = 'U', the leading
*          N-by-N upper triangular part of A contains the upper
*          triangular part of the matrix A, and the strictly lower
*          triangular part of A is not referenced.  If UPLO = 'L', the
*          leading N-by-N lower triangular part of A contains the lower
*          triangular part of the matrix A, and the strictly upper
*          triangular part of A is not referenced.
*
*          On exit, the block diagonal matrix D and the multipliers used
*          to obtain the factor U or L (see below for further details).
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (output) INTEGER array, dimension (N)
*          Details of the interchanges and the block structure of D.
*          If IPIV(k) > 0, then rows and columns k and IPIV(k) were
*          interchanged and D(k,k) is a 1-by-1 diagonal block.
*          If UPLO = 'U' and IPIV(k) = IPIV(k-1) < 0, then rows and
*          columns k-1 and -IPIV(k) were interchanged and D(k-1:k,k-1:k)
*          is a 2-by-2 diagonal block.  If UPLO = 'L' and IPIV(k) =
*          IPIV(k+1) < 0, then rows and columns k+1 and -IPIV(k) were
*          interchanged and D(k:k+1,k:k+1) is a 2-by-2 diagonal block.
*
*  WORK    (workspace/output) REAL array, dimension (MAX(1,LWORK))
*          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
*
*  LWORK   (input) INTEGER
*          The length of WORK.  LWORK >=1.  For best performance
*          LWORK >= N*NB, where NB is the block size returned by ILAENV.
*
*          If LWORK = -1, then a workspace query is assumed; the routine
*          only calculates the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array, and no error
*          message related to LWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*          > 0:  if INFO = i, D(i,i) is exactly zero.  The factorization
*                has been completed, but the block diagonal matrix D is
*                exactly singular, and division by zero will occur if it
*                is used to solve a system of equations.
*

*  Further Details
*  ===============
*
*  If UPLO = 'U', then A = U*D*U', where
*     U = P(n)*U(n)* ... *P(k)U(k)* ...,
*  i.e., U is a product of terms P(k)*U(k), where k decreases from n to
*  1 in steps of 1 or 2, and D is a block diagonal matrix with 1-by-1
*  and 2-by-2 diagonal blocks D(k).  P(k) is a permutation matrix as
*  defined by IPIV(k), and U(k) is a unit upper triangular matrix, such
*  that if the diagonal block D(k) is of order s (s = 1 or 2), then
*
*             (   I    v    0   )   k-s
*     U(k) =  (   0    I    0   )   s
*             (   0    0    I   )   n-k
*                k-s   s   n-k
*
*  If s = 1, D(k) overwrites A(k,k), and v overwrites A(1:k-1,k).
*  If s = 2, the upper triangle of D(k) overwrites A(k-1,k-1), A(k-1,k),
*  and A(k,k), and v overwrites A(1:k-2,k-1:k).
*
*  If UPLO = 'L', then A = L*D*L', where
*     L = P(1)*L(1)* ... *P(k)*L(k)* ...,
*  i.e., L is a product of terms P(k)*L(k), where k increases from 1 to
*  n in steps of 1 or 2, and D is a block diagonal matrix with 1-by-1
*  and 2-by-2 diagonal blocks D(k).  P(k) is a permutation matrix as
*  defined by IPIV(k), and L(k) is a unit lower triangular matrix, such
*  that if the diagonal block D(k) is of order s (s = 1 or 2), then
*
*             (   I    0     0   )  k-1
*     L(k) =  (   0    I     0   )  s
*             (   0    v     I   )  n-k-s+1
*                k-1   s  n-k-s+1
*
*  If s = 1, D(k) overwrites A(k,k), and v overwrites A(k+1:n,k).
*  If s = 2, the lower triangle of D(k) overwrites A(k,k), A(k+1,k),
*  and A(k+1,k+1), and v overwrites A(k+2:n,k:k+1).
*
*  =====================================================================
*
*     .. Local Scalars ..
      LOGICAL            LQUERY, UPPER
      INTEGER            IINFO, IWS, J, K, KB, LDWORK, LWKOPT, NB, NBMIN
*     ..
*     .. External Functions ..
      LOGICAL            LSAME
      INTEGER            ILAENV
      EXTERNAL           LSAME, ILAENV
*     ..
*     .. External Subroutines ..
      EXTERNAL           SLASYF, SSYTF2, XERBLA
*     ..
*     .. Intrinsic Functions ..
      INTRINSIC          MAX
*     ..


    
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ssytri

USAGE:
  info, a = NumRu::Lapack.ssytri( uplo, a, ipiv, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYTRI( UPLO, N, A, LDA, IPIV, WORK, INFO )

*  Purpose
*  =======
*
*  SSYTRI computes the inverse of a real symmetric indefinite matrix
*  A using the factorization A = U*D*U**T or A = L*D*L**T computed by
*  SSYTRF.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the details of the factorization are stored
*          as an upper or lower triangular matrix.
*          = 'U':  Upper triangular, form is A = U*D*U**T;
*          = 'L':  Lower triangular, form is A = L*D*L**T.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the block diagonal matrix D and the multipliers
*          used to obtain the factor U or L as computed by SSYTRF.
*
*          On exit, if INFO = 0, the (symmetric) inverse of the original
*          matrix.  If UPLO = 'U', the upper triangular part of the
*          inverse is formed and the part of A below the diagonal is not
*          referenced; if UPLO = 'L' the lower triangular part of the
*          inverse is formed and the part of A above the diagonal is
*          not referenced.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (input) INTEGER array, dimension (N)
*          Details of the interchanges and the block structure of D
*          as determined by SSYTRF.
*
*  WORK    (workspace) REAL array, dimension (N)
*
*  INFO    (output) INTEGER
*          = 0: successful exit
*          < 0: if INFO = -i, the i-th argument had an illegal value
*          > 0: if INFO = i, D(i,i) = 0; the matrix is singular and its
*               inverse could not be computed.
*

*  =====================================================================
*


    
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ssytri2

USAGE:
  info, a, work = NumRu::Lapack.ssytri2( uplo, a, ipiv, work, [:lwork => lwork, :usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYTRI2( UPLO, N, A, LDA, IPIV, WORK, LWORK, INFO )

*  Purpose
*  =======
*
*  SSYTRI2 computes the inverse of a real symmetric indefinite matrix
*  A using the factorization A = U*D*U**T or A = L*D*L**T computed by
*  SSYTRF. SSYTRI2 sets the LEADING DIMENSION of the workspace
*  before calling SSYTRI2X that actually computes the inverse.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the details of the factorization are stored
*          as an upper or lower triangular matrix.
*          = 'U':  Upper triangular, form is A = U*D*U**T;
*          = 'L':  Lower triangular, form is A = L*D*L**T.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the NB diagonal matrix D and the multipliers
*          used to obtain the factor U or L as computed by SSYTRF.
*
*          On exit, if INFO = 0, the (symmetric) inverse of the original
*          matrix.  If UPLO = 'U', the upper triangular part of the
*          inverse is formed and the part of A below the diagonal is not
*          referenced; if UPLO = 'L' the lower triangular part of the
*          inverse is formed and the part of A above the diagonal is
*          not referenced.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (input) INTEGER array, dimension (N)
*          Details of the interchanges and the NB structure of D
*          as determined by SSYTRF.
*
*  WORK    (workspace) REAL array, dimension (N+NB+1)*(NB+3)
*
*  LWORK   (input) INTEGER
*          The dimension of the array WORK.
*          WORK is size >= (N+NB+1)*(NB+3)
*          If LDWORK = -1, then a workspace query is assumed; the routine
*           calculates:
*              - the optimal size of the WORK array, returns
*          this value as the first entry of the WORK array,
*              - and no error message related to LDWORK is issued by XERBLA.
*
*  INFO    (output) INTEGER
*          = 0: successful exit
*          < 0: if INFO = -i, the i-th argument had an illegal value
*          > 0: if INFO = i, D(i,i) = 0; the matrix is singular and its
*               inverse could not be computed.
*

*  =====================================================================
*
*     .. Local Scalars ..
      LOGICAL            UPPER, LQUERY
      INTEGER            MINSIZE, NBMAX
*     ..
*     .. External Functions ..
      LOGICAL            LSAME
      INTEGER            ILAENV
      EXTERNAL           LSAME, ILAENV
*     ..
*     .. External Subroutines ..
      EXTERNAL           SSYTRI2X
*     ..


    
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ssytri2x

USAGE:
  info, a = NumRu::Lapack.ssytri2x( uplo, a, ipiv, nb, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYTRI2X( UPLO, N, A, LDA, IPIV, WORK, NB, INFO )

*  Purpose
*  =======
*
*  SSYTRI2X computes the inverse of a real symmetric indefinite matrix
*  A using the factorization A = U*D*U**T or A = L*D*L**T computed by
*  SSYTRF.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the details of the factorization are stored
*          as an upper or lower triangular matrix.
*          = 'U':  Upper triangular, form is A = U*D*U**T;
*          = 'L':  Lower triangular, form is A = L*D*L**T.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  A       (input/output) REAL array, dimension (LDA,N)
*          On entry, the NNB diagonal matrix D and the multipliers
*          used to obtain the factor U or L as computed by SSYTRF.
*
*          On exit, if INFO = 0, the (symmetric) inverse of the original
*          matrix.  If UPLO = 'U', the upper triangular part of the
*          inverse is formed and the part of A below the diagonal is not
*          referenced; if UPLO = 'L' the lower triangular part of the
*          inverse is formed and the part of A above the diagonal is
*          not referenced.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (input) INTEGER array, dimension (N)
*          Details of the interchanges and the NNB structure of D
*          as determined by SSYTRF.
*
*  WORK    (workspace) REAL array, dimension (N+NNB+1,NNB+3)
*
*  NB      (input) INTEGER
*          Block size
*
*  INFO    (output) INTEGER
*          = 0: successful exit
*          < 0: if INFO = -i, the i-th argument had an illegal value
*          > 0: if INFO = i, D(i,i) = 0; the matrix is singular and its
*               inverse could not be computed.
*

*  =====================================================================
*


    
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ssytrs

USAGE:
  info, b = NumRu::Lapack.ssytrs( uplo, a, ipiv, b, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYTRS( UPLO, N, NRHS, A, LDA, IPIV, B, LDB, INFO )

*  Purpose
*  =======
*
*  SSYTRS solves a system of linear equations A*X = B with a real
*  symmetric matrix A using the factorization A = U*D*U**T or
*  A = L*D*L**T computed by SSYTRF.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the details of the factorization are stored
*          as an upper or lower triangular matrix.
*          = 'U':  Upper triangular, form is A = U*D*U**T;
*          = 'L':  Lower triangular, form is A = L*D*L**T.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  NRHS    (input) INTEGER
*          The number of right hand sides, i.e., the number of columns
*          of the matrix B.  NRHS >= 0.
*
*  A       (input) REAL array, dimension (LDA,N)
*          The block diagonal matrix D and the multipliers used to
*          obtain the factor U or L as computed by SSYTRF.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (input) INTEGER array, dimension (N)
*          Details of the interchanges and the block structure of D
*          as determined by SSYTRF.
*
*  B       (input/output) REAL array, dimension (LDB,NRHS)
*          On entry, the right hand side matrix B.
*          On exit, the solution matrix X.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*

*  =====================================================================
*


    
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ssytrs2

USAGE:
  info, b = NumRu::Lapack.ssytrs2( uplo, a, ipiv, b, [:usage => usage, :help => help])


FORTRAN MANUAL
      SUBROUTINE SSYTRS2( UPLO, N, NRHS, A, LDA, IPIV, B, LDB,  WORK, INFO )

*  Purpose
*  =======
*
*  SSYTRS2 solves a system of linear equations A*X = B with a real
*  symmetric matrix A using the factorization A = U*D*U**T or
*  A = L*D*L**T computed by SSYTRF and converted by SSYCONV.
*

*  Arguments
*  =========
*
*  UPLO    (input) CHARACTER*1
*          Specifies whether the details of the factorization are stored
*          as an upper or lower triangular matrix.
*          = 'U':  Upper triangular, form is A = U*D*U**T;
*          = 'L':  Lower triangular, form is A = L*D*L**T.
*
*  N       (input) INTEGER
*          The order of the matrix A.  N >= 0.
*
*  NRHS    (input) INTEGER
*          The number of right hand sides, i.e., the number of columns
*          of the matrix B.  NRHS >= 0.
*
*  A       (input) REAL array, dimension (LDA,N)
*          The block diagonal matrix D and the multipliers used to
*          obtain the factor U or L as computed by SSYTRF.
*
*  LDA     (input) INTEGER
*          The leading dimension of the array A.  LDA >= max(1,N).
*
*  IPIV    (input) INTEGER array, dimension (N)
*          Details of the interchanges and the block structure of D
*          as determined by SSYTRF.
*
*  B       (input/output) REAL array, dimension (LDB,NRHS)
*          On entry, the right hand side matrix B.
*          On exit, the solution matrix X.
*
*  LDB     (input) INTEGER
*          The leading dimension of the array B.  LDB >= max(1,N).
*
*  WORK    (workspace) REAL array, dimension (N)
*
*  INFO    (output) INTEGER
*          = 0:  successful exit
*          < 0:  if INFO = -i, the i-th argument had an illegal value
*

*  =====================================================================
*


    
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