/home/abui.../zherfsx.f(3)
π
/home/abui.../zherfsx.f(3) β Library Functions Manual
Ok bestie, this is the manual page for /home/abui.../zherfsx.f(3) from the Library Functions Manual. The actual source file is /home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/zherfsx.f β yes, that whole absolute-path moment π
.
πΈ NAME πΈ
/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/zherfsx.f
β¨ SYNOPSIS β¨
π«Ά Functions/Subroutines π«Ά
subroutine ZHERFSX (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, rwork, info)
ZHERFSX
π Function/Subroutine Documentation π
subroutine ZHERFSX (character uplo, character equed, integer n, integer
nrhs, complex*16, dimension( lda, * ) a, integer lda, complex*16,
dimension( ldaf, * ) af, integer ldaf, integer, dimension( * ) ipiv,
double precision, dimension( * ) s, complex*16, dimension( ldb, * ) b,
integer ldb, complex*16, dimension( ldx, * ) x, integer ldx, double
precision rcond, double precision, dimension( * ) berr, integer
n_err_bnds, double precision, dimension( nrhs, * ) err_bnds_norm, double
precision, dimension( nrhs, * ) err_bnds_comp, integer nparams, double
precision, dimension( * ) params, complex*16, dimension( * ) work,
double precision, dimension( * ) rwork, integer info)
ZHERFSX
π― Purpose π―
Ok so ZHERFSX is here to improve the computed solution to a system of linear equations when the coefficient matrix is Hermitian indefinite, and it 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.
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. Low-key iconic shortcut, tbh π«Ά.
π§Έ Parameters π§Έ
UPLOβCHARACTER*1.= 'U': upper triangle ofAis stored;= 'L': lower triangle ofAis stored.
EQUEDβCHARACTER*1. Specifies the form of equilibration that was done toAbefore 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.,Ahas been replaced bydiag(S) * A * diag(S). The right hand sideBhas been changed accordingly.
NβINTEGER. The order of the matrixA.N >= 0.NRHSβINTEGER. The number of right hand sides, i.e., the number of columns of the matricesBandX.NRHS >= 0.AβCOMPLEX*16array, dimension(LDA,N). The Hermitian matrixA. IfUPLO = 'U', the leadingN-by-Nupper triangular part ofAcontains the upper triangular part of the matrixA, and the strictly lower triangular part ofAis not referenced. IfUPLO = 'L', the leadingN-by-Nlower triangular part ofAcontains the lower triangular part of the matrixA, and the strictly upper triangular part ofAis not referenced.LDAβINTEGER. The leading dimension of the arrayA.LDA >= max(1,N).AFβCOMPLEX*16array, dimension(LDAF,N). The factored form of the matrixA.AFcontains the block diagonal matrixDand the multipliers used to obtain the factorUorLfrom the factorizationA = U*D*U**HorA = L*D*L**Has computed byZHETRF.LDAFβINTEGER. The leading dimension of the arrayAF.LDAF >= max(1,N).IPIVβINTEGERarray, dimension(N). Details of the interchanges and the block structure ofDas determined byZHETRF.SβDOUBLE PRECISIONarray, dimension(N). The scale factors forA. IfEQUED = 'Y',Ais multiplied on the left and right bydiag(S).Sis an input argument ifFACT = 'F'; otherwise,Sis an output argument. IfFACT = 'F'andEQUED = 'Y', each element ofSmust be positive. IfSis output, each element ofSis a power of the radix. IfSis input, each element ofSshould 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.BβCOMPLEX*16array, dimension(LDB,NRHS). The right hand side matrixB.LDBβINTEGER. The leading dimension of the arrayB.LDB >= max(1,N).XβCOMPLEX*16array, dimension(LDX,NRHS). On entry, the solution matrixX, as computed byZHETRS. On exit, the improved solution matrixX.LDXβINTEGER. The leading dimension of the arrayX.LDX >= max(1,N).RCONDβDOUBLE PRECISION. Reciprocal scaled condition number. This is an estimate of the reciprocal Skeel condition number of the matrixAafter 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.BERRβDOUBLE PRECISIONarray, dimension(NRHS). Componentwise relative backward error. This is the componentwise relative backward error of each solution vectorX(j)(i.e., the smallest relative change in any element ofAorBthat makesX(j)an exact solution).N_ERR_BNDSβINTEGER. Number of error bounds to return for each right hand side and each type (normwise or componentwise). SeeERR_BNDS_NORMandERR_BNDS_COMPbelow.ERR_BNDS_NORMβDOUBLE PRECISIONarray, 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:
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 = 1β boolean. Trust the answer if the reciprocal condition number is less than the thresholdsqrt(n) * dlamch('Epsilon').err = 2β 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 thresholdsqrt(n) * dlamch('Epsilon'). This error bound should only be trusted if the previous boolean is true.err = 3β Reciprocal condition number: Estimated normwise reciprocal condition number. Compared with the thresholdsqrt(n) * dlamch('Epsilon')to determine if the error estimate is . These reciprocal condition numbers are1 / (norm(Z^{-1},inf) * norm(Z,inf))for some appropriately scaled matrixZ. LetZ = S*A, whereSscales each row by a power of the radix so all absolute row sums ofZare approximately 1.
See Lapack Working Note 165 for further details and extra cautions.
ERR_BNDS_COMPβ
Okay so picking up right where we left off: ERR_BNDS_COMP is a DOUBLE PRECISION 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:
abs(XTRUE(j,i) - X(j,i))
max_j ----------------------
abs(X(j,i))
Componentwise relative error in the ith solution vector: that's the formula above, bestie. 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 < 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 = 1β boolean. Trust the answer if the reciprocal condition number is less than the thresholdsqrt(n) * dlamch('Epsilon').err = 2β 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 thresholdsqrt(n) * dlamch('Epsilon'). This error bound should only be trusted if the previous boolean is true.err = 3β Reciprocal condition number: Estimated componentwise reciprocal condition number. Compared with the thresholdsqrt(n) * dlamch('Epsilon')to determine if the error estimate is . These reciprocal condition numbers are1 / (norm(Z^{-1},inf) * norm(Z,inf))for some appropriately scaled matrix Z. LetZ = S*(A*diag(x)), where x is the solution for the current right-hand side and S scales each row ofA*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. iykyk π¦
NPARAMS β NPARAMS is INTEGER. Specifies the number of parameters set in PARAMS. If <= 0, the PARAMS array is never referenced and default values are used.
PARAMS β PARAMS is DOUBLE PRECISION array, dimension NPARAMS. Specifies algorithm parameters. If an entry is < 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)β Whether to perform iterative refinement or not.- Default:
1.0D+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)
- Default:
PARAMS(LA_LINRX_ITHRESH_I = 2)β Maximum number of residual computations allowed for refinement.- Default:
10 - Aggressive: Set to
100to permit convergence using approximate factorizations or factorizations other than LU. If the factorization uses a technique other than Gaussian elimination, the guarantees inerr_bnds_normanderr_bnds_compmay no longer be trustworthy.
- Default:
PARAMS(LA_LINRX_CWISE_I = 3)β Flag determining if the code will attempt to find a solution with small componentwise relative error in the double-precision algorithm. Positive is true,0.0is false.- Default:
1.0(attempt componentwise convergence)
- Default:
WORK β WORK is COMPLEX*16 array, dimension (2*N).
RWORK β RWORK is DOUBLE PRECISION array, dimension (2*N).
INFO β INFO is INTEGER
= 0: Successful exit. The solution to every right-hand side is guaranteed.< 0: IfINFO = -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 = 0is 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 thatERR_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 eitherERR_BNDS_NORM(J,1) = 0.0orERR_BNDS_COMP(J,1) = 0.0). See the definition ofERR_BNDS_NORM(:,1)andERR_BNDS_COMP(:,1). To get information about all of the right-hand sides checkERR_BNDS_NORMorERR_BNDS_COMP.
π Author
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
Definition at line 397 of file zherfsx.f.
πΈ Author
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