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*> \brief \b SLSETS
*
* =========== DOCUMENTATION ===========
*
* Online html documentation available at
* http://www.netlib.org/lapack/explore-html/
*
* Definition:
* ===========
*
* SUBROUTINE SLSETS( M, P, N, A, AF, LDA, B, BF, LDB, C, CF,
* D, DF, X, WORK, LWORK, RWORK, RESULT )
*
* .. Scalar Arguments ..
* INTEGER LDA, LDB, LWORK, M, P, N
* ..
* .. Array Arguments ..
* REAL A( LDA, * ), AF( LDA, * ), B( LDB, * ),
* $ BF( LDB, * ), RESULT( 2 ), RWORK( * ),
* $ C( * ), D( * ), CF( * ), DF( * ),
* $ WORK( LWORK ), X( * )
*
*
*> \par Purpose:
* =============
*>
*> \verbatim
*>
*> SLSETS tests SGGLSE - a subroutine for solving linear equality
*> constrained least square problem (LSE).
*> \endverbatim
*
* Arguments:
* ==========
*
*> \param[in] M
*> \verbatim
*> M is INTEGER
*> The number of rows of the matrix A. M >= 0.
*> \endverbatim
*>
*> \param[in] P
*> \verbatim
*> P is INTEGER
*> The number of rows of the matrix B. P >= 0.
*> \endverbatim
*>
*> \param[in] N
*> \verbatim
*> N is INTEGER
*> The number of columns of the matrices A and B. N >= 0.
*> \endverbatim
*>
*> \param[in] A
*> \verbatim
*> A is REAL array, dimension (LDA,N)
*> The M-by-N matrix A.
*> \endverbatim
*>
*> \param[out] AF
*> \verbatim
*> AF is REAL array, dimension (LDA,N)
*> \endverbatim
*>
*> \param[in] LDA
*> \verbatim
*> LDA is INTEGER
*> The leading dimension of the arrays A, AF, Q and R.
*> LDA >= max(M,N).
*> \endverbatim
*>
*> \param[in] B
*> \verbatim
*> B is REAL array, dimension (LDB,N)
*> The P-by-N matrix A.
*> \endverbatim
*>
*> \param[out] BF
*> \verbatim
*> BF is REAL array, dimension (LDB,N)
*> \endverbatim
*>
*> \param[in] LDB
*> \verbatim
*> LDB is INTEGER
*> The leading dimension of the arrays B, BF, V and S.
*> LDB >= max(P,N).
*> \endverbatim
*>
*> \param[in] C
*> \verbatim
*> C is REAL array, dimension( M )
*> the vector C in the LSE problem.
*> \endverbatim
*>
*> \param[out] CF
*> \verbatim
*> CF is REAL array, dimension( M )
*> \endverbatim
*>
*> \param[in] D
*> \verbatim
*> D is REAL array, dimension( P )
*> the vector D in the LSE problem.
*> \endverbatim
*>
*> \param[out] DF
*> \verbatim
*> DF is REAL array, dimension( P )
*> \endverbatim
*>
*> \param[out] X
*> \verbatim
*> X is REAL array, dimension( N )
*> solution vector X in the LSE problem.
*> \endverbatim
*>
*> \param[out] WORK
*> \verbatim
*> WORK is REAL array, dimension (LWORK)
*> \endverbatim
*>
*> \param[in] LWORK
*> \verbatim
*> LWORK is INTEGER
*> The dimension of the array WORK.
*> \endverbatim
*>
*> \param[out] RWORK
*> \verbatim
*> RWORK is REAL array, dimension (M)
*> \endverbatim
*>
*> \param[out] RESULT
*> \verbatim
*> RESULT is REAL array, dimension (2)
*> The test ratios:
*> RESULT(1) = norm( A*x - c )/ norm(A)*norm(X)*EPS
*> RESULT(2) = norm( B*x - d )/ norm(B)*norm(X)*EPS
*> \endverbatim
*
* Authors:
* ========
*
*> \author Univ. of Tennessee
*> \author Univ. of California Berkeley
*> \author Univ. of Colorado Denver
*> \author NAG Ltd.
*
*> \date November 2011
*
*> \ingroup single_eig
*
* =====================================================================
SUBROUTINE SLSETS( M, P, N, A, AF, LDA, B, BF, LDB, C, CF,
$ D, DF, X, WORK, LWORK, RWORK, RESULT )
*
* -- LAPACK test routine (version 3.4.0) --
* -- LAPACK is a software package provided by Univ. of Tennessee, --
* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
* November 2011
*
* .. Scalar Arguments ..
INTEGER LDA, LDB, LWORK, M, P, N
* ..
* .. Array Arguments ..
REAL A( LDA, * ), AF( LDA, * ), B( LDB, * ),
$ BF( LDB, * ), RESULT( 2 ), RWORK( * ),
$ C( * ), D( * ), CF( * ), DF( * ),
$ WORK( LWORK ), X( * )
*
* ====================================================================
*
* ..
* .. Local Scalars ..
INTEGER INFO
* ..
* .. External Subroutines ..
EXTERNAL SGGLSE, SLACPY, SGET02
* ..
* .. Executable Statements ..
*
* Copy the matrices A and B to the arrays AF and BF,
* and the vectors C and D to the arrays CF and DF,
*
CALL SLACPY( 'Full', M, N, A, LDA, AF, LDA )
CALL SLACPY( 'Full', P, N, B, LDB, BF, LDB )
CALL SCOPY( M, C, 1, CF, 1 )
CALL SCOPY( P, D, 1, DF, 1 )
*
* Solve LSE problem
*
CALL SGGLSE( M, N, P, AF, LDA, BF, LDB, CF, DF, X,
$ WORK, LWORK, INFO )
*
* Test the residual for the solution of LSE
*
* Compute RESULT(1) = norm( A*x - c ) / norm(A)*norm(X)*EPS
*
CALL SCOPY( M, C, 1, CF, 1 )
CALL SCOPY( P, D, 1, DF, 1 )
CALL SGET02( 'No transpose', M, N, 1, A, LDA, X, N, CF, M,
$ RWORK, RESULT( 1 ) )
*
* Compute result(2) = norm( B*x - d ) / norm(B)*norm(X)*EPS
*
CALL SGET02( 'No transpose', P, N, 1, B, LDB, X, N, DF, P,
$ RWORK, RESULT( 2 ) )
*
RETURN
*
* End of SLSETS
*
END
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