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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