la_herpvgrw(3)
π la_herpvgrw
okay so bestie, welcome to la_herpvgrw(3) β straight out of the Library Functions Manual β and it's giving "niche LAPACK function that's actually carrying the whole numerical-stability friend group." This is a family page: six functions, all doing reciprocal pivot growth, each in its own precision and matrix flavor. Grab a snack π, we're going through every single one.
β¨ NAME β¨
la_herpvgrw β la_herpvgrw: reciprocal pivot growth. that's it, that's the name π
πΈ SYNOPSIS πΈ
Functions
Six besties, one mission. Here's the whole lineup so you know who's who:
real function cla_herpvgrw (uplo, n, info, a, lda, af, ldaf, ipiv, work)βCLA_HERPVGRWreal function cla_syrpvgrw (uplo, n, info, a, lda, af, ldaf, ipiv, work)βCLA_SYRPVGRWcomputes the reciprocal pivot growth factornorm(A)/norm(U)for a symmetric indefinite matrix.double precision function dla_syrpvgrw (uplo, n, info, a, lda, af, ldaf, ipiv, work)βDLA_SYRPVGRWcomputes the reciprocal pivot growth factornorm(A)/norm(U)for a symmetric indefinite matrix.real function sla_syrpvgrw (uplo, n, info, a, lda, af, ldaf, ipiv, work)βSLA_SYRPVGRWcomputes the reciprocal pivot growth factornorm(A)/norm(U)for a symmetric indefinite matrix.double precision function zla_herpvgrw (uplo, n, info, a, lda, af, ldaf, ipiv, work)βZLA_HERPVGRWdouble precision function zla_syrpvgrw (uplo, n, info, a, lda, af, ldaf, ipiv, work)βZLA_SYRPVGRWcomputes the reciprocal pivot growth factornorm(A)/norm(U)for a symmetric indefinite matrix.
fr fr, that's the whole cast π
π Detailed Description π
okay this section is literally empty on the original page β no description text, no lore, nothing. It just exists and then we move on. Respect the minimalist queen for that, honestly π. Everything juicy lives under Function Documentation below.
π₯ Function Documentation π₯
π real function cla_herpvgrw
real function cla_herpvgrw (character*1 uplo, integer n, integer info,
complex, dimension( lda, * ) a, integer lda, complex, dimension( ldaf, * )
af, integer ldaf, integer, dimension( * ) ipiv, real, dimension( * )
work)
CLA_HERPVGRW β¨
Purpose
CLA_HERPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U). The norm is used. (yes, that double space is exactly how it's printed β the symbol did not survive the typesetting, we mourn π). If this is much less than 1, the stability of the LU factorization of the (equilibrated) matrix A could be poor. This also means that the solution X, estimated condition numbers, and error bounds could be unreliable.
β οΈ heads up bestie: if that factor is much less than1, the LU factorization of the (equilibrated)Acould be poor in stability β and then the solutionX, the estimated condition numbers, and the error bounds could all be unreliable. three strikes, no cap π
Parameters
UPLOβUPLOisCHARACTER*1.= 'U': Upper triangle ofAis stored;= 'L': Lower triangle ofAis stored.
NβNisINTEGER. The number of linear equations, i.e., the order of the matrixA.N >= 0.INFOβINFOisINTEGER. The value ofINFOreturned fromSSYTRF,.i.e., the pivot in columnINFOis exactly0.AβAisCOMPLEXarray, dimension(LDA,N). On entry, theN-by-NmatrixA.LDAβLDAisINTEGER. The leading dimension of the arrayA.LDA >= max(1,N).AFβAFisCOMPLEXarray, dimension(LDAF,N). The block diagonal matrixDand the multipliers used to obtain the factorUorLas computed byCHETRF.LDAFβLDAFisINTEGER. The leading dimension of the arrayAF.LDAF >= max(1,N).IPIVβIPIVisINTEGERarray, dimension(N). Details of the interchanges and the block structure ofDas determined byCHETRF.WORKβWORKisREALarray, dimension(2*N).
Author
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
Definition
Definition at line 121 of file cla_herpvgrw.f.
π¦ real function cla_syrpvgrw
real function cla_syrpvgrw (character*1 uplo, integer n, integer info,
complex, dimension( lda, * ) a, integer lda, complex, dimension( ldaf, * )
af, integer ldaf, integer, dimension( * ) ipiv, real, dimension( * )
work)
CLA_SYRPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric indefinite matrix. iykyk π«Ά
Purpose
CLA_SYRPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U). The norm is used. If this is much less than 1, the stability of the LU factorization of the (equilibrated) matrix A could be poor. This also means that the solution X, estimated condition numbers, and error bounds could be unreliable.
β οΈ same warning, different function: factor much less than1β stability of the LU factorization of the (equilibrated)Acould be poor, and the solutionX, estimated condition numbers, and error bounds could be unreliable. don't ignore her π«Ά
Parameters
UPLOβUPLOisCHARACTER*1.= 'U': Upper triangle ofAis stored;= 'L': Lower triangle ofAis stored.
NβNisINTEGER. The number of linear equations, i.e., the order of the matrixA.N >= 0.INFOβINFOisINTEGER. The value ofINFOreturned fromCSYTRF,.i.e., the pivot in columnINFOis exactly0.AβAisCOMPLEXarray, dimension(LDA,N). On entry, theN-by-NmatrixA.LDAβLDAisINTEGER. The leading dimension of the arrayA.LDA >= max(1,N).AFβAFisCOMPLEXarray, dimension(LDAF,N). The block diagonal matrixDand the multipliers used to obtain the factorUorLas computed byCSYTRF.LDAFβLDAFisINTEGER. The leading dimension of the arrayAF.LDAF >= max(1,N).IPIVβIPIVisINTEGERarray, dimension(N). Details of the interchanges and the block structure ofDas determined byCSYTRF.WORKβWORKisREALarray, dimension(2*N).
Author
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
Definition
Definition at line 121 of file cla_syrpvgrw.f.
π double precision function dla_syrpvgrw
double precision function dla_syrpvgrw (character*1 uplo, integer n, integer
info, double precision, dimension( lda, * ) a, integer lda, double
precision, dimension( ldaf, * ) af, integer ldaf, integer, dimension( * )
ipiv, double precision, dimension( * ) work)
DLA_SYRPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric indefinite matrix. double precision era, we love to see it π
Purpose
DLA_SYRPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U). The norm is used. If this is much less than 1, the stability of the LU factorization of the (equilibrated) matrix A could be poor. This also means that the solution X, estimated condition numbers, and error bounds could be unreliable.
β οΈ the caveat travels with the family: much less than1= the LU factorization of the (equilibrated)Acould be poor in stability, andX, the estimated condition numbers, and error bounds could be unreliable. periodt π
Parameters
UPLOβUPLOisCHARACTER*1.= 'U': Upper triangle ofAis stored;= 'L': Lower triangle ofAis stored.
NβNisINTEGER. The number of linear equations, i.e., the order of the matrixA.N >= 0.INFOβINFOisINTEGER. The value ofINFOreturned fromDSYTRF,.i.e., the pivot in columnINFOis exactly0.AβAisDOUBLE PRECISIONarray, dimension(LDA,N). On entry, theN-by-NmatrixA.LDAβLDAisINTEGER. The leading dimension of the arrayA.LDA >= max(1,N).AFβAFisDOUBLE PRECISIONarray, dimension(LDAF,N). The block diagonal matrixDand the multipliers used to obtain the factorUorLas computed byDSYTRF.LDAFβLDAFisINTEGER. The leading dimension of the arrayAF.LDAF >= max(1,N).IPIVβIPIVisINTEGERarray, dimension(N). Details of the interchanges and the block structure ofDas determined byDSYTRF.WORKβWORKisDOUBLE PRECISIONarray, dimension(2*N).
Author
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
Definition
Definition at line 120 of file dla_syrpvgrw.f.
π§ real function sla_syrpvgrw
real function sla_syrpvgrw (character*1 uplo, integer n, integer info, real,
dimension( lda, * ) a, integer lda, real, dimension( ldaf, * ) af,
integer ldaf, integer, dimension( * ) ipiv, real, dimension( * ) work)
SLA_SYRPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric indefinite matrix. single precision real, she's the accessible queen πΈ
Purpose
SLA_SYRPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U). The norm is used. If this is much less than 1, the stability of the LU factorization of the (equilibrated) matrix A could be poor. This also means that the solution X, estimated condition numbers, and error bounds could be unreliable.
β οΈ say it with me: much less than1β LU factorization of the (equilibrated)Acould be poor in stability, and the solutionX, estimated condition numbers, and error bounds could be unreliable. don't let it slide π
Parameters
UPLOβUPLOisCHARACTER*1.= 'U': Upper triangle ofAis stored;= 'L': Lower triangle ofAis stored.
NβNisINTEGER. The number of linear equations, i.e., the order of the matrixA.N >= 0.INFOβINFOisINTEGER. The value ofINFOreturned fromSSYTRF,.i.e., the pivot in columnINFOis exactly0.AβAisREALarray, dimension(LDA,N). On entry, theN-by-NmatrixA.LDAβLDAisINTEGER. The leading dimension of the arrayA.LDA >= max(1,N).AFβAFisREALarray, dimension(LDAF,N). The block diagonal matrixDand the multipliers used to obtain the factorUorLas computed bySSYTRF.LDAFβLDAFisINTEGER. The leading dimension of the arrayAF.LDAF >= max(1,N).IPIVβIPIVisINTEGERarray, dimension(N). Details of the interchanges and the block structure ofDas determined bySSYTRF.WORKβWORKisREALarray, dimension(2*N).
Author
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
Definition
Definition at line 120 of file sla_syrpvgrw.f.
π double precision function zla_herpvgrw
double precision function zla_herpvgrw (character*1 uplo, integer n, integer
info, complex*16, dimension( lda, * ) a, integer lda, complex*16,
dimension( ldaf, * ) af, integer ldaf, integer, dimension( * ) ipiv,
double precision, dimension( * ) work)
ZLA_HERPVGRW β the double precision complex*16 icon herself π
Purpose
β¦and that's exactly where this part of the page cuts off, bestie π the purpose text for ZLA_HERPVGRW keeps going in part 2 β same page, more lore, don't go anywhere π«Ά
π and now the sequel: zla_syrpvgrw π
okay bestie, same energy, different function β this one's the symmetric-indefinite twin and she's giving sisterhood. here's the whole signature, verbatim, no cap:
double precision function zla_syrpvgrw (character*1 uplo, integer n, integer
info, complex*16, dimension( lda, * ) a, integer lda, complex*16,
dimension( ldaf, * ) af, integer ldaf, integer, dimension( * ) ipiv,
double precision, dimension( * ) work)
ZLA_SYRPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U) for a symmetric indefinite matrix. that's her whole personality, and honestly? iconic.
β¨ Purpose β the vibe check β¨
so here's the tea: ZLA_SYRPVGRW computes the reciprocal pivot growth factor norm(A)/norm(U). the norm is used β yes it says it just like that, we don't ask questions, we accept. π«Ά
if that number comes out much less than 1, then bestieβ¦ the stability of the LU factorization of the (equilibrated) matrix A could be poor. π and because the universe is like that, it also means the solution X, the estimated condition numbers and the error bounds could be unreliable. so likeβ¦ don't trust them?? do not let them borrow your charger, that kind of untrustworthy. π
π Parameters β meet the cast π
UPLOβ isCHARACTER*1, and it's literally just "which triangle, bestie?" π¦= 'U': the Upper triangle ofAis stored= 'L': the Lower triangle ofAis stored
Nβ isINTEGER. the number of linear equations, i.e. the order of the matrixA. must satisfyN >= 0. zero is valid, she's flexible πINFOβ isINTEGER. this is the value ofINFOreturned fromZSYTRF,.i.e., the pivot in columnINFOis exactly0. β¨ (yes the doc really typed.i.e.,like that, we stan a quirky queen)Aβ is aCOMPLEX*16array, dimension(LDA,N). on entry, it's theN-by-NmatrixA. the main character, obviously πLDAβ isINTEGER. the leading dimension of the arrayA. requirement:LDA >= max(1,N). no shortcuts, she checks IDs at the door πAFβ is aCOMPLEX*16array, dimension(LDAF,N). this holds the block diagonal matrixDand the multipliers used to obtain the factorUorL, as computed byZSYTRF. so it's like, the receipts from factorization π§ΎLDAFβ isINTEGER. the leading dimension of the arrayAF. requirement:LDAF >= max(1,N). same energy, same bouncer π«ΆIPIVβ is anINTEGERarray, dimension(N). the details of the interchanges and the block structure ofD, as determined byZSYTRF. the lore. the backstory. πWORKβ is aDOUBLE PRECISIONarray, dimension(2*N). that's it. that's the whole description. she's low-maintenance, we love her for that πΈ
π Author π
these absolute legends:
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
β Definition at line 121 of file zla_syrpvgrw.f
yes bestie, line 121, file zla_syrpvgrw.f β if you need to know exactly where the sauce lives, it's right there. π₯
π Author (the meta one) π
Generated automatically by Doxygen for LAPACK from the source code. so nobody hand-wrote this section, it's a robot doing its little robot thing π€π
friendly reminder before you go: both of these routines had that same warning in their Purpose text β if the reciprocal pivot growth factor is much less than 1, the factorization stability could be poor and the solutionX, estimated condition numbers and error bounds could be unreliable. that goes for bothzla_herpvgrwandzla_syrpvgrw, no cap. take the warning seriously even though we're giggling π
and that's a wrap on LAPACK Version 3.12.0, page la_herpvgrw(3), served fresh from the source code by that little Doxygen gremlin. slay, go forth, and may all your pivot growth factors be close to 1 πβ¨π¦π
π¦ where this page comes from
- arch rolling: lapack-doc 3.12.1-2 Β· custom
- π girlified by deepseek-ai/DeepSeek-V4.1-Flash-1017 on : a language model's rewrite of the original, under its terms