SLAQR2(3)
π
slaqr2.f(3) β Library Functions Manual π
πΈ NAME πΈ
/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/slaqr2.f
β¨ SYNOPSIS β¨
π Functions/Subroutines π
subroutine SLAQR2 (wantt, wantz, n, ktop, kbot, nw, h, ldh, iloz, ihiz,
z, ldz, ns, nd, sr, si, v, ldv, nh, t, ldt, nv, wv, ldwv, work,
lwork)
SLAQR2 performs the orthogonal similarity transformation of a Hessenberg matrix to detect and deflate fully converged eigenvalues from a trailing principal submatrix (aggressive early deflation).
π« Function/Subroutine Documentation π«
subroutine SLAQR2 (logical wantt, logical wantz, integer n, integer ktop,
integer kbot, integer nw, real, dimension( ldh, * ) h, integer ldh,
integer iloz, integer ihiz, real, dimension( ldz, * ) z, integer ldz,
integer ns, integer nd, real, dimension( * ) sr, real, dimension( * )
si, real, dimension( ldv, * ) v, integer ldv, integer nh, real,
dimension( ldt, * ) t, integer ldt, integer nv, real, dimension( ldwv, *
) wv, integer ldwv, real, dimension( * ) work, integer lwork)
SLAQR2 performs the orthogonal similarity transformation of a Hessenberg matrix to detect and deflate fully converged eigenvalues from a trailing principal submatrix (aggressive early deflation).
π― Purpose π―
SLAQR2 is identical to SLAQR3 except that it avoids recursion by calling SLAHQR instead of SLAQR4.
Aggressive early deflation:
This subroutine accepts as input an upper Hessenberg matrix H and performs an orthogonal similarity transformation designed to detect and deflate fully converged eigenvalues from a trailing principal submatrix. On output H has been over-written by a new Hessenberg matrix that is a perturbation of an orthogonal similarity transformation of H. It is to be hoped that the final version of H has many zero subdiagonal entries.
π§Έ Parameters π§Έ
WANTTβWANTTisLOGICAL. If.TRUE., then the Hessenberg matrix H is fully updated so that the quasi-triangular Schur factor may be computed (in cooperation with the calling subroutine). If.FALSE., then only enough of H is updated to preserve the eigenvalues.WANTZβWANTZisLOGICAL. If.TRUE., then the orthogonal matrix Z is updated so that the orthogonal Schur factor may be computed (in cooperation with the calling subroutine). If.FALSE., then Z is not referenced.NβNisINTEGER. The order of the matrix H and (ifWANTZis.TRUE.) the order of the orthogonal matrix Z.KTOPβKTOPisINTEGER. It is assumed that eitherKTOP = 1orH(KTOP,KTOP-1)=0.KBOTandKTOPtogether determine an isolated block along the diagonal of the Hessenberg matrix.KBOTβKBOTisINTEGER. It is assumed without a check that eitherKBOT = NorH(KBOT+1,KBOT)=0.KBOTandKTOPtogether determine an isolated block along the diagonal of the Hessenberg matrix.NWβNWisINTEGER. Deflation window size.1 <= NW <= (KBOT-KTOP+1).HβHisREALarray, dimension(LDH,N). On input the initial N-by-N section of H stores the Hessenberg matrix undergoing aggressive early deflation. On output H has been transformed by an orthogonal similarity transformation, perturbed, and the returned to Hessenberg form that (it is to be hoped) has some zero subdiagonal entries.LDHβLDHisINTEGER. Leading dimension of H just as declared in the calling subroutine.N <= LDH.ILOZβILOZisINTEGER.IHIZβIHIZisINTEGER. Specify the rows of Z to which transformations must be applied ifWANTZis.TRUE..1 <= ILOZ <= IHIZ <= N.ZβZisREALarray, dimension(LDZ,N). IFWANTZis.TRUE., then on output, the orthogonal similarity transformation mentioned above has been accumulated intoZ(ILOZ:IHIZ,ILOZ:IHIZ)from the right. IfWANTZis.FALSE., then Z is unreferenced.LDZβLDZisINTEGER. The leading dimension of Z just as declared in the calling subroutine.1 <= LDZ.NSβNSisINTEGER. The number of unconverged (ie approximate) eigenvalues returned in SR and SI that may be used as shifts by the calling subroutine.NDβNDisINTEGER. The number of converged eigenvalues uncovered by this subroutine.SRβSRisREALarray, dimension(KBOT).SIβSIisREALarray, dimension(KBOT). On output, the real and imaginary parts of approximate eigenvalues that may be used for shifts are stored inSR(KBOT-ND-NS+1)throughSR(KBOT-ND)andSI(KBOT-ND-NS+1)throughSI(KBOT-ND), respectively. The real and imaginary parts of converged eigenvalues are stored inSR(KBOT-ND+1)throughSR(KBOT)andSI(KBOT-ND+1)throughSI(KBOT), respectively.VβVisREALarray, dimension(LDV,NW). An NW-by-NW work array.LDVβLDVisINTEGER. The leading dimension of V just as declared in the calling subroutine.NW <= LDV.NHβNHisINTEGER. The number of columns of T.NH >= NW.TβTisREALarray, dimension(LDT,NW).LDTβLDTisINTEGER. The leading dimension of T just as declared in the calling subroutine.NW <= LDT.NVβNVisINTEGER. The number of rows of work array WV available for workspace.NV >= NW.WVβWVisREALarray, dimension(LDWV,NW).LDWVβLDWVisINTEGER. The leading dimension of W just as declared in the calling subroutine.NW <= LDV.WORKβWORKisREALarray, dimension(LWORK). On exit,WORK(1)is set to an estimate of the optimal value ofLWORKfor the given values ofN,NW,KTOPandKBOT.LWORKβLWORKisINTEGER. The dimension of the work array WORK.LWORK = 2*NWsuffices, but greater efficiency may result from larger values ofLWORK.
IfLWORK = -1, then a workspace query is assumed; SLAQR2 only estimates the optimal workspace size for the given values ofN,NW,KTOPandKBOT. The estimate is returned inWORK(1). No error message related toLWORKis issued by XERBLA. Neither H nor Z are accessed.
π Author π
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
π Contributors: π
Karen Braman and Ralph Byers, Department of Mathematics, University of Kansas, USA
Definition at line 275 of file slaqr2.f.
π Author π
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