/home/abui...extended.f(3)
πΈ NAME πΈ
Okay so this page is for zla_porfsx_extended.f(3) from the Library Functions Manual, and the NAME line is literally the full build path:
/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/zla_porfsx_extended.f
No cap, that's the whole NAME. It's giving βmy identity is my filesystem locationβ energy π .
β¨ SYNOPSIS β¨
π Functions/Subroutines π
Bestie, there's exactly one subroutine here, and she's a long one with main character energy:
ZLA_PORFSX_EXTENDEDβ the one and only. Signature:
subroutine ZLA_PORFSX_EXTENDED (prec_type, uplo, n, nrhs, a, lda, af,
ldaf, colequ, c, b, ldb, y, ldy, berr_out, n_norms, err_bnds_norm,
err_bnds_comp, res, ayb, dy, y_tail, rcond, ithresh, rthresh, dz_ub,
ignore_cwise, info)
ZLA_PORFSX_EXTENDED improves the computed solution to a system of linear equations for symmetric or Hermitian positive-definite matrices by performing extra-precise iterative refinement and provides error bounds and backward error estimates for the solution.
π¦ Function/Subroutine Documentation π¦
Full signature time β every type, every dimension, every * stays put. π«Ά
subroutine ZLA_PORFSX_EXTENDED (integer prec_type, character uplo, integer
n, integer nrhs, complex*16, dimension( lda, * ) a, integer lda,
complex*16, dimension( ldaf, * ) af, integer ldaf, logical colequ,
double precision, dimension( * ) c, complex*16, dimension( ldb, * ) b,
integer ldb, complex*16, dimension( ldy, * ) y, integer ldy, double
precision, dimension( * ) berr_out, integer n_norms, double precision,
dimension( nrhs, * ) err_bnds_norm, double precision, dimension( nrhs, *
) err_bnds_comp, complex*16, dimension( * ) res, double precision,
dimension( * ) ayb, complex*16, dimension( * ) dy, complex*16,
dimension( * ) y_tail, double precision rcond, integer ithresh, double
precision rthresh, double precision dz_ub, logical ignore_cwise, integer
info)
ZLA_PORFSX_EXTENDED improves the computed solution to a system of linear equations for symmetric or Hermitian positive-definite matrices by performing extra-precise iterative refinement and provides error bounds and backward error estimates for the solution.
π Purpose π
Okay so here's the purpose, and it's honestly iconic:
ZLA_PORFSX_EXTENDED improves the computed solution to a system of linear equations by performing extra-precise iterative refinement and provides error bounds and backward error estimates for the solution. This subroutine is called by ZPORFSX to perform iterative refinement. 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. Note that this subroutine is only responsible for setting the second fields of ERR_BNDS_NORM and ERR_BNDS_COMP. Periodt.
π Parameters π
Vibe check: every parameter, every value, every >= β all here, bestie. No skipping, no summarizing, no βyou get the idea.β π
PREC_TYPE β PREC_TYPE is INTEGER. Specifies the intermediate precision to be used in refinement. The value is defined by ILAPREC(P) where P is a CHARACTER and P:
= 'S': Single
= 'D': Double
= 'I': Indigenous
= 'X' or 'E': Extra
UPLO β UPLO is CHARACTER*1.
= 'U': Upper triangle of A is stored;
= 'L': Lower triangle of A is stored.
N β N is INTEGER. The number of linear equations, i.e., the order of the matrix A. N >= 0.
NRHS β NRHS is INTEGER. The number of right-hand-sides, i.e., the number of columns of the matrix B.
A β A is COMPLEX*16 array, dimension (LDA,N). On entry, the N-by-N matrix A.
LDA β LDA is INTEGER. The leading dimension of the array A. LDA >= max(1,N).
AF β AF is COMPLEX*16 array, dimension (LDAF,N). The triangular factor U or L from the Cholesky factorization A = U**T*U or A = L*L**T, as computed by ZPOTRF.
LDAF β LDAF is INTEGER. The leading dimension of the array AF. LDAF >= max(1,N).
COLEQU β COLEQU is LOGICAL. If .TRUE. then column equilibration was done to A before calling this routine. This is needed to compute the solution and error bounds correctly.
C β C is DOUBLE PRECISION array, dimension (N). The column scale factors for A. If COLEQU = .FALSE., C is not accessed. If C is input, each element of C 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. This is highkey a warning, fr fr.
B β B is COMPLEX*16 array, dimension (LDB,NRHS). The right-hand-side matrix B.
LDB β LDB is INTEGER. The leading dimension of the array B. LDB >= max(1,N).
Y β Y is COMPLEX*16 array, dimension (LDY,NRHS). On entry, the solution matrix X, as computed by ZPOTRS. On exit, the improved solution matrix Y.
LDY β LDY is INTEGER. The leading dimension of the array Y. LDY >= max(1,N).
BERR_OUT β BERR_OUT is DOUBLE PRECISION array, dimension (NRHS). On exit, BERR_OUT(j) contains the componentwise relative backward error for right-hand-side j from the formula
max(i) ( abs(RES(i)) / ( abs(op(A_s))*abs(Y) + abs(B_s) )(i) )
where abs(Z) is the componentwise absolute value of the matrix or vector Z. This is computed by ZLA_LIN_BERR. Ngl, this formula is doing the most.
N_NORMS β N_NORMS is INTEGER. Determines which error bounds to return (see ERR_BNDS_NORM and ERR_BNDS_COMP). If N_NORMS >= 1 return normwise error bounds. If N_NORMS >= 2 return componentwise error bounds. Lowkey the switch for how much error lore you get.
ERR_BNDS_NORM β ERR_BNDS_NORM is 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 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 = 1boolean. Trust the answer if the reciprocal condition number is less than the thresholdsqrt(n) * slamch('Epsilon').err = 2error 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) * slamch('Epsilon'). This error bound should only be trusted if the previous boolean is true.err = 3Reciprocal condition number: Estimated normwise reciprocal condition number. Compared with the thresholdsqrt(n) * slamch('Epsilon')to determine if the error estimate is . (Yes, the source sentence really stops there β we're preserving the blank exactly, bestie π) These reciprocal condition numbers are1 / (norm(Z^{-1},inf) * norm(Z,inf))for some appropriately scaled matrix Z. LetZ = S*A, where S scales each row by a power of the radix so all absolute row sums of Z are approximately 1.
This subroutine is only responsible for setting the second field above. See Lapack Working Note 165 for further details and extra cautions.
ERR_BNDS_COMP β description continues in part 2 β¨
okay bestie, picking up right where we left off β here's the rest of the parameter squad, plus the author credits and that little definition line. no cap, we're keeping every single detail. let's go π β¨
ERR_BNDS_COMPβ okay so this one is aDOUBLE PRECISION array, dimension (NRHS, N_ERR_BNDS). For each right-hand side, it's packed with info about various error bounds and condition numbers that correspond to the componentwise relative error, which is defined as:
abs(XTRUE(j,i) - X(j,i))
max_j ----------------------
abs(X(j,i))
The array is indexed by the right-hand side i (the componentwise relative error depends on it) and the type of error info. There are currently up to three pieces of info 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 these three fields:
err = 1β a boolean. Trust the answer if the reciprocal condition number is less than the thresholdsqrt(n) * slamch('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) * slamch('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) * slamch('Epsilon')to determine if the error estimate is . (yep, that's literally what it says, we're not fixing it π) These reciprocal condition numbers are1 / (norm(Z^{-1},inf) * norm(Z,inf))for some appropriately scaled matrix Z. LetZ = S*(A*diag(x)), wherexis the solution for the current right-hand side andSscales each row ofA*diag(x)by a power of the radix so all absolute row sums of Z are approximately 1.
This subroutine is only responsible for setting the second field above. See Lapack Working Note 165 for further details and extra cautions.
RESβ aCOMPLEX*16 array, dimension (N). It's workspace to hold the intermediate residual. lowkey just a scratchpad, no biggie π«ΆAYBβ aDOUBLE PRECISION array, dimension (N). Workspace. that's it, that's the whole vibe β¨DYβ aCOMPLEX*16 PRECISION array, dimension (N). Workspace to hold the intermediate solution. yes bestie, it literally saysCOMPLEX*16 PRECISIONβ we keep the typo, we don't touch it πY_TAILβ aCOMPLEX*16 array, dimension (N). Workspace to hold the trailing bits of the intermediate solution. fancy β¨RCONDβ aDOUBLE PRECISION. 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. so don't panic immediately, okay? πITHRESHβ anINTEGER. The maximum number of residual computations allowed for refinement. The default is 10. For '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 inERR_BNDS_NORMandERR_BNDS_COMPmay no longer be trustworthy. so like, aggressive mode is a whole commitment, bestie π₯RTHRESHβ aDOUBLE PRECISION. Determines when to stop refinement if the error estimate stops decreasing. Refinement will stop when the next solution no longer satisfiesnorm(dx_{i+1}) < RTHRESH * norm(dx_i)wherenorm(Z)is the infinity norm of Z.RTHRESHsatisfies0 < RTHRESH <= 1. The default value is 0.5. For 'aggressive' set to 0.9 to permit convergence on extremely ill-conditioned matrices. See LAWN 165 for more details. it's giving tuning knob energy ποΈDZ_UBβ aDOUBLE PRECISION. Determines when to start considering componentwise convergence. Componentwise convergence is only considered after each component of the solution Y is stable, which we define as the relative change in each component being less thanDZ_UB. The default value is 0.25, requiring the first bit to be stable. See LAWN 165 for more details. first bit stable = main character energy πIGNORE_CWISEβ aLOGICAL. If.TRUE.then ignore componentwise convergence. Default value is.FALSE.. simple as that πINFOβ anINTEGER. Here's the tea:= 0: Successful exit. slay π< 0: ifINFO = -i, the ith argument toZPOTRShad an illegal value. oop, something went wrong π¬
Author π«Ά
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
Definition at line 380 of file zla_porfsx_extended.f.
Author (the sequel) β¨
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