ZLARRV(3)
okay bestie, we're in the Library Functions Manual and the page is ZLARRV(3) β yes, that ZLARRV, the LAPACK one. The header's manual-name vibe is folded in right here, and we are so ready. π
πΈ NAME πΈ
/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/zlarrv.f
β¨ SYNOPSIS β¨
π§ Functions/Subroutines π§
subroutine ZLARRV (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)
ZLARRV computes the eigenvectors of the tridiagonal matrix T = L D LT given L, D and the eigenvalues of L D LT. π«Ά
π Function/Subroutine Documentation π
subroutine ZLARRV (integer n, double precision vl, double precision vu,
double precision, dimension( * ) d, double precision, dimension( * ) l,
double precision pivmin, integer, dimension( * ) isplit, integer m,
integer dol, integer dou, double precision minrgp, double precision
rtol1, double precision rtol2, double precision, dimension( * ) w,
double precision, dimension( * ) werr, double precision, dimension( * )
wgap, integer, dimension( * ) iblock, integer, dimension( * ) indexw,
double precision, dimension( * ) gers, complex*16, dimension( ldz, * )
z, integer ldz, integer, dimension( * ) isuppz, double precision,
dimension( * ) work, integer, dimension( * ) iwork, integer info)
ZLARRV computes the eigenvectors of the tridiagonal matrix T = L D LT given L, D and the eigenvalues of L D LT. no cap, that's the whole assignment. β¨
π Purpose: π
ZLARRV 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 DLARRE. π
πΈ Parameters πΈ
NβN is INTEGER, the order of the matrix.N >= 0. πVLβVL is DOUBLE PRECISION, 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. π¦VUβVU is DOUBLE PRECISION, upper 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. π¦DβD is DOUBLE PRECISION array, dimension (N). On entry, theNdiagonal elements of the diagonal matrixD. On exit,Dmay be overwritten. πLβL is DOUBLE PRECISION array, dimension (N). On entry, the(N-1)subdiagonal elements of the unit bidiagonal matrixLare in elements1toN-1ofL(if the matrix is not split.) At the end of each block is stored the corresponding shift as given byDLARRE. On exit,Lis overwritten. π«PIVMINβPIVMIN is DOUBLE PRECISION. The minimum pivot allowed in the Sturm sequence. πISPLITβISPLIT is INTEGER array, dimension (N). The splitting points, at whichTbreaks up into blocks. The first block consists of rows/columns1toISPLIT( 1 ), the second of rows/columnsISPLIT( 1 )+1throughISPLIT( 2 ), etc. π§MβM is INTEGER. The total number of input eigenvalues.0 <= M <= N. πDOLβDOL is INTEGER. πDOUβDOU 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. πMINRGPβMINRGP is DOUBLE PRECISION. πRTOL1βRTOL1 is DOUBLE PRECISION. πRTOL2βRTOL2 is DOUBLE PRECISION. Parameters for bisection. An interval[LEFT,RIGHT]has converged ifRIGHT-LEFT < MAX( RTOL1*GAP, RTOL2*MAX(|LEFT|,|RIGHT|) ). π₯WβW is DOUBLE PRECISION 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 arrayWfromDLARREis 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. β¨WERRβWERR is DOUBLE PRECISION array, dimension (N). The firstMelements contain the semiwidth of the uncertainty interval of the corresponding eigenvalue inW. πWGAPβWGAP is DOUBLE PRECISION array, dimension (N). The separation from the right neighbor eigenvalue inW. π¦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. πΈINDEXWβINDEXW 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 the10-th eigenvalue in the second block. π§GERSβGERS is DOUBLE PRECISION 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. πZβZ is COMPLEX*16 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. πLDZβLDZ is INTEGER. The leading dimension of the arrayZ.LDZ >= 1, and ifJOBZ = 'V',LDZ >= max(1,N). πISUPPZβISUPPZ 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 ). π¦WORKβWORK is DOUBLE PRECISION array, dimension (12*N). π₯IWORKβIWORK is INTEGER array, dimension (7*N). π₯INFOβINFO is INTEGER:= 0: successful exit> 0: A problem occurred inZLARRV.< 0: One of the called subroutines signaled an internal problem. Needs inspection of the corresponding parameterIINFOfor further information.=-1: Problem inDLARRBwhen refining a child's eigenvalues.=-2: Problem inDLARRFwhen 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 inDLARRBwhen 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
Definition at line 281 of file zlarrv.f.
β¨ Author β¨
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