SRC/slarrv.f(3)
π¦ SRC/slarrv.f β Library Functions Manual π¦
okay bestie, this page is from the Library Functions Manual and it's all about SRC/slarrv.f. It's giving LAPACK subroutine documentation, and the way it lists every parameter? obsessed. Let's go. π
πΈ NAME πΈ
SRC/slarrv.f
β¨ SYNOPSIS β¨
π«Ά Functions/Subroutines π«Ά
subroutine slarrv (n, vl, vu, d, l, pivmin, isplit, m, dol, dou, minrgp, rtol1, rtol2, w, werr, wgap, iblock, indexw, gers, z, ldz, isuppz, work, iwork, info)
SLARRV computes the eigenvectors of the tridiagonal matrix T = L D LT given L, D and the eigenvalues of L D LT.
π Function/Subroutine Documentation π
π« subroutine slarrv π«
subroutine slarrv (integer n, real vl, real vu, real, dimension( * ) d,
real, dimension( * ) l, real pivmin, integer, dimension( * ) isplit,
integer m, integer dol, integer dou, real minrgp, real rtol1, real
rtol2, real, dimension( * ) w, real, dimension( * ) werr, real,
dimension( * ) wgap, integer, dimension( * ) iblock, integer, dimension(
* ) indexw, real, dimension( * ) gers, real, dimension( ldz, * ) z,
integer ldz, integer, dimension( * ) isuppz, real, dimension( * ) work,
integer, dimension( * ) iwork, integer info)
SLARRV computes the eigenvectors of the tridiagonal matrix T = L D LT given L, D and the eigenvalues of L D LT.
π― Purpose π―
SLARRV computes the eigenvectors of the tridiagonal matrix T = L D L**T given L, D and APPROXIMATIONS to the eigenvalues of L D L**T. The input eigenvalues should have been computed by SLARRE.
π Parameters π
okay bestie, here is every single parameter, no skips, fr fr:
NβN is INTEGER; the order of the matrix.N >= 0.VLβVL is REAL; lower bound of the interval that contains the desired eigenvalues.VL < VU. Needed to compute gaps on the left or right end of the extremal eigenvalues in the desired RANGE.VUβVU is REAL; upper bound of the interval that contains the desired eigenvalues.VL < VU. Note:VUis currently not used by this implementation ofSLARRV;VUis passed toSLARRVbecause it could be used to compute gaps on the right end of the extremal eigenvalues. However, with not much initial accuracy inLAMBDAandVU, the formula can lead to an overestimation of the right gap and thus to inadequately early RQI 'convergence'. This is currently prevented by forcing a small right gap. And so it turns out thatVUis currently not used by this implementation ofSLARRV.DβD is REAL array, dimension (N). On entry, theNdiagonal elements of the diagonal matrixD. On exit,Dmay be overwritten.LβL is REAL array, dimension (N). On entry, the(N-1)subdiagonal elements of the unit bidiagonal matrixLare in elements 1 toN-1ofL(if the matrix is not split.) At the end of each block is stored the corresponding shift as given bySLARRE. On exit,Lis overwritten.PIVMINβPIVMIN is REAL; the minimum pivot allowed in the Sturm sequence.ISPLITβISPLIT is INTEGER array, dimension (N). The splitting points, at whichTbreaks up into blocks. The first block consists of rows/columns 1 toISPLIT( 1 ), the second of rows/columnsISPLIT( 1 )+1throughISPLIT( 2 ), etc.MβM is INTEGER; the total number of input eigenvalues.0 <= M <= N.DOLβDOL is INTEGER.DOUβDOU is INTEGER. If the user wants to compute only selected eigenvectors from all the eigenvalues supplied, he can specify an index rangeDOL:DOU. Or else the settingDOL=1, DOU=Mshould be applied. Note thatDOLandDOUrefer to the order in which the eigenvalues are stored inW. If the user wants to compute only selected eigenpairs, then the columnsDOL-1toDOU+1of the eigenvector spaceZcontain the computed eigenvectors. All other columns ofZare set to zero.MINRGPβMINRGP is REAL.RTOL1βRTOL1 is REAL.RTOL2βRTOL2 is REAL. Parameters for bisection. An interval[LEFT,RIGHT]has converged ifRIGHT-LEFT < MAX( RTOL1*GAP, RTOL2*MAX(|LEFT|,|RIGHT|) ).WβW is REAL array, dimension (N). The firstMelements ofWcontain the APPROXIMATE eigenvalues for which eigenvectors are to be computed. The eigenvalues should be grouped by split-off block and ordered from smallest to largest within the block ( The output arrayWfromSLARREis expected here ). Furthermore, they are with respect to the shift of the corresponding root representation for their block. On exit,Wholds the eigenvalues of the UNshifted matrix.WERRβWERR is REAL array, dimension (N). The firstMelements contain the semiwidth of the uncertainty interval of the corresponding eigenvalue inW.WGAPβWGAP is REAL array, dimension (N). The separation from the right neighbor eigenvalue inW.IBLOCKβIBLOCK is INTEGER array, dimension (N). The indices of the blocks (submatrices) associated with the corresponding eigenvalues inW;IBLOCK(i)=1if eigenvalueW(i)belongs to the first block from the top,=2ifW(i)belongs to the second block, etc.INDEXWβINDEXW is INTEGER array, dimension (N). The indices of the eigenvalues within each block (submatrix); for example,INDEXW(i)= 10andIBLOCK(i)=2imply that thei-th eigenvalueW(i)is the 10-th eigenvalue in the second block.GERSβGERS is REAL array, dimension (2*N). TheNGerschgorin intervals (thei-th Gerschgorin interval is(GERS(2*i-1), GERS(2*i))). The Gerschgorin intervals should be computed from the original UNshifted matrix.ZβZ is REAL array, dimension (LDZ, max(1,M) ). IfINFO = 0, the firstMcolumns ofZcontain the orthonormal eigenvectors of the matrixTcorresponding to the input eigenvalues, with thei-th column ofZholding the eigenvector associated withW(i). Note: the user must ensure that at leastmax(1,M)columns are supplied in the arrayZ.LDZβLDZ is INTEGER; the leading dimension of the arrayZ.LDZ >= 1, and ifJOBZ = 'V',LDZ >= max(1,N).ISUPPZβISUPPZ is INTEGER array, dimension ( 2*max(1,M) ). The support of the eigenvectors inZ, i.e., the indices indicating the nonzero elements inZ. TheI-th eigenvector is nonzero only in elementsISUPPZ( 2*I-1 )throughISUPPZ( 2*I ).WORKβWORK is REAL array, dimension (12*N).IWORKβIWORK is INTEGER array, dimension (7*N).INFOβINFO is INTEGER.= 0: successful exit.> 0: A problem occurred inSLARRV.< 0: One of the called subroutines signaled an internal problem. Needs inspection of the corresponding parameterIINFOfor further information.=-1: Problem inSLARRBwhen refining a child's eigenvalues.=-2: Problem inSLARRFwhen computing the RRR of a child. When a child is inside a tight cluster, it can be difficult to find an RRR. A partial remedy from the user's point of view is to make the parameterMINRGPsmaller and recompile. However, as the orthogonality of the computed vectors is proportional to1/MINRGP, the user should be aware that he might be trading in precision when he decreasesMINRGP.=-3: Problem inSLARRBwhen refining a single eigenvalue after the Rayleigh correction was rejected.= 5: The Rayleigh Quotient Iteration failed to converge to full accuracy inMAXITRsteps.
π Author π
- Univ. of Tennessee
- Univ. of California Berkeley
- Univ. of Colorado Denver
- NAG Ltd.
π Contributors: π
- Beresford Parlett, University of California, Berkeley, USA
- Jim Demmel, University of California, Berkeley, USA
- Inderjit Dhillon, University of Texas, Austin, USA
- Osni Marques, LBNL/NERSC, USA
- Christof Voemel, University of California, Berkeley, USA
π§Ύ Definition π§Ύ
Definition at line 287 of file slarrv.f.
π Author π
Generated automatically by Doxygen for LAPACK from the source code.
π footer sign-off: LAPACK Version 3.12.0, SRC/slarrv.f(3) β that's the source/version energy, and no separate date appears in the footer. mwah, bestie. π«Ά
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