numeric-linalg
Educational material on the SciPy implementation of numerical linear algebra algorithms
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lapack/TESTING/MATGEN/clahilb.f | 8066B | -rw-r--r-- |
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*> \brief \b CLAHILB * * =========== DOCUMENTATION =========== * * Online html documentation available at * http://www.netlib.org/lapack/explore-html/ * * Definition: * =========== * * SUBROUTINE CLAHILB( N, NRHS, A, LDA, X, LDX, B, LDB, WORK, * INFO, PATH) * * .. Scalar Arguments .. * INTEGER N, NRHS, LDA, LDX, LDB, INFO * .. Array Arguments .. * REAL WORK(N) * COMPLEX A(LDA,N), X(LDX, NRHS), B(LDB, NRHS) * CHARACTER*3 PATH * .. * * *> \par Purpose: * ============= *> *> \verbatim *> *> CLAHILB generates an N by N scaled Hilbert matrix in A along with *> NRHS right-hand sides in B and solutions in X such that A*X=B. *> *> The Hilbert matrix is scaled by M = LCM(1, 2, ..., 2*N-1) so that all *> entries are integers. The right-hand sides are the first NRHS *> columns of M * the identity matrix, and the solutions are the *> first NRHS columns of the inverse Hilbert matrix. *> *> The condition number of the Hilbert matrix grows exponentially with *> its size, roughly as O(e ** (3.5*N)). Additionally, the inverse *> Hilbert matrices beyond a relatively small dimension cannot be *> generated exactly without extra precision. Precision is exhausted *> when the largest entry in the inverse Hilbert matrix is greater than *> 2 to the power of the number of bits in the fraction of the data type *> used plus one, which is 24 for single precision. *> *> In single, the generated solution is exact for N <= 6 and has *> small componentwise error for 7 <= N <= 11. *> \endverbatim * * Arguments: * ========== * *> \param[in] N *> \verbatim *> N is INTEGER *> The dimension of the matrix A. *> \endverbatim *> *> \param[in] NRHS *> \verbatim *> NRHS is INTEGER *> The requested number of right-hand sides. *> \endverbatim *> *> \param[out] A *> \verbatim *> A is COMPLEX array, dimension (LDA, N) *> The generated scaled Hilbert matrix. *> \endverbatim *> *> \param[in] LDA *> \verbatim *> LDA is INTEGER *> The leading dimension of the array A. LDA >= N. *> \endverbatim *> *> \param[out] X *> \verbatim *> X is COMPLEX array, dimension (LDX, NRHS) *> The generated exact solutions. Currently, the first NRHS *> columns of the inverse Hilbert matrix. *> \endverbatim *> *> \param[in] LDX *> \verbatim *> LDX is INTEGER *> The leading dimension of the array X. LDX >= N. *> \endverbatim *> *> \param[out] B *> \verbatim *> B is REAL array, dimension (LDB, NRHS) *> The generated right-hand sides. Currently, the first NRHS *> columns of LCM(1, 2, ..., 2*N-1) * the identity matrix. *> \endverbatim *> *> \param[in] LDB *> \verbatim *> LDB is INTEGER *> The leading dimension of the array B. LDB >= N. *> \endverbatim *> *> \param[out] WORK *> \verbatim *> WORK is REAL array, dimension (N) *> \endverbatim *> *> \param[out] INFO *> \verbatim *> INFO is INTEGER *> = 0: successful exit *> = 1: N is too large; the data is still generated but may not *> be not exact. *> < 0: if INFO = -i, the i-th argument had an illegal value *> \endverbatim *> *> \param[in] PATH *> \verbatim *> PATH is CHARACTER*3 *> The LAPACK path name. *> \endverbatim * * Authors: * ======== * *> \author Univ. of Tennessee *> \author Univ. of California Berkeley *> \author Univ. of Colorado Denver *> \author NAG Ltd. * *> \ingroup complex_matgen * * ===================================================================== SUBROUTINE CLAHILB( N, NRHS, A, LDA, X, LDX, B, LDB, WORK, $ INFO, PATH) * * -- 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 N, NRHS, LDA, LDX, LDB, INFO * .. Array Arguments .. REAL WORK(N) COMPLEX A(LDA,N), X(LDX, NRHS), B(LDB, NRHS) CHARACTER*3 PATH * .. * * ===================================================================== * .. Local Scalars .. INTEGER TM, TI, R INTEGER M INTEGER I, J COMPLEX TMP CHARACTER*2 C2 * .. * .. Parameters .. * NMAX_EXACT the largest dimension where the generated data is * exact. * NMAX_APPROX the largest dimension where the generated data has * a small componentwise relative error. * ??? complex uses how many bits ??? INTEGER NMAX_EXACT, NMAX_APPROX, SIZE_D PARAMETER (NMAX_EXACT = 6, NMAX_APPROX = 11, SIZE_D = 8) * * d's are generated from random permutation of those eight elements. COMPLEX D1(8), D2(8), INVD1(8), INVD2(8) DATA D1 /(-1,0),(0,1),(-1,-1),(0,-1),(1,0),(-1,1),(1,1),(1,-1)/ DATA D2 /(-1,0),(0,-1),(-1,1),(0,1),(1,0),(-1,-1),(1,-1),(1,1)/ DATA INVD1 /(-1,0),(0,-1),(-.5,.5),(0,1),(1,0), $ (-.5,-.5),(.5,-.5),(.5,.5)/ DATA INVD2 /(-1,0),(0,1),(-.5,-.5),(0,-1),(1,0), $ (-.5,.5),(.5,.5),(.5,-.5)/ * .. * .. External Subroutines .. EXTERNAL XERBLA * .. * .. External Functions EXTERNAL CLASET, LSAMEN INTRINSIC REAL LOGICAL LSAMEN * .. * .. Executable Statements .. C2 = PATH( 2: 3 ) * * Test the input arguments * INFO = 0 IF (N .LT. 0 .OR. N .GT. NMAX_APPROX) THEN INFO = -1 ELSE IF (NRHS .LT. 0) THEN INFO = -2 ELSE IF (LDA .LT. N) THEN INFO = -4 ELSE IF (LDX .LT. N) THEN INFO = -6 ELSE IF (LDB .LT. N) THEN INFO = -8 END IF IF (INFO .LT. 0) THEN CALL XERBLA('CLAHILB', -INFO) RETURN END IF IF (N .GT. NMAX_EXACT) THEN INFO = 1 END IF * * Compute M = the LCM of the integers [1, 2*N-1]. The largest * reasonable N is small enough that integers suffice (up to N = 11). M = 1 DO I = 2, (2*N-1) TM = M TI = I R = MOD(TM, TI) DO WHILE (R .NE. 0) TM = TI TI = R R = MOD(TM, TI) END DO M = (M / TI) * I END DO * * Generate the scaled Hilbert matrix in A * If we are testing SY routines, take * D1_i = D2_i, else, D1_i = D2_i* IF ( LSAMEN( 2, C2, 'SY' ) ) THEN DO J = 1, N DO I = 1, N A(I, J) = D1(MOD(J,SIZE_D)+1) * (REAL(M) $ / REAL(I + J - 1)) * D1(MOD(I,SIZE_D)+1) END DO END DO ELSE DO J = 1, N DO I = 1, N A(I, J) = D1(MOD(J,SIZE_D)+1) * (REAL(M) $ / REAL(I + J - 1)) * D2(MOD(I,SIZE_D)+1) END DO END DO END IF * * Generate matrix B as simply the first NRHS columns of M * the * identity. TMP = REAL(M) CALL CLASET('Full', N, NRHS, (0.0,0.0), TMP, B, LDB) * * Generate the true solutions in X. Because B = the first NRHS * columns of M*I, the true solutions are just the first NRHS columns * of the inverse Hilbert matrix. WORK(1) = REAL(N) DO J = 2, N WORK(J) = ( ( (WORK(J-1)/REAL(J-1)) * REAL(J-1 - N) ) $ / REAL(J-1) ) * REAL(N +J -1) END DO * If we are testing SY routines, * take D1_i = D2_i, else, D1_i = D2_i* IF ( LSAMEN( 2, C2, 'SY' ) ) THEN DO J = 1, NRHS DO I = 1, N X(I, J) = $ INVD1(MOD(J,SIZE_D)+1) * $ ((WORK(I)*WORK(J)) / REAL(I + J - 1)) $ * INVD1(MOD(I,SIZE_D)+1) END DO END DO ELSE DO J = 1, NRHS DO I = 1, N X(I, J) = $ INVD2(MOD(J,SIZE_D)+1) * $ ((WORK(I)*WORK(J)) / REAL(I + J - 1)) $ * INVD1(MOD(I,SIZE_D)+1) END DO END DO END IF END