numeric-linalg
Educational material on the SciPy implementation of numerical linear algebra algorithms
| Name | Size | Mode | |
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| lapack/TESTING/EIG/slsets.f | 5412B | -rw-r--r-- |
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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. * *> \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 -- * -- LAPACK is a software package provided by Univ. of Tennessee, -- * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- * * .. 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