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opencv/3rdparty/lapack/slarrv.c

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/* slarrv.f -- translated by f2c (version 20061008).
You must link the resulting object file with libf2c:
on Microsoft Windows system, link with libf2c.lib;
on Linux or Unix systems, link with .../path/to/libf2c.a -lm
or, if you install libf2c.a in a standard place, with -lf2c -lm
-- in that order, at the end of the command line, as in
cc *.o -lf2c -lm
Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
http://www.netlib.org/f2c/libf2c.zip
*/
#include "clapack.h"
/* Table of constant values */
static real c_b5 = 0.f;
static integer c__1 = 1;
static integer c__2 = 2;
/* Subroutine */ int slarrv_(integer *n, real *vl, real *vu, real *d__, real *
l, real *pivmin, integer *isplit, integer *m, integer *dol, integer *
dou, real *minrgp, real *rtol1, real *rtol2, real *w, real *werr,
real *wgap, integer *iblock, integer *indexw, real *gers, real *z__,
integer *ldz, integer *isuppz, real *work, integer *iwork, integer *
info)
{
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2, i__3, i__4, i__5;
real r__1, r__2;
logical L__1;
/* Builtin functions */
double log(doublereal);
/* Local variables */
integer minwsize, i__, j, k, p, q, miniwsize, ii;
real gl;
integer im, in;
real gu, gap, eps, tau, tol, tmp;
integer zto;
real ztz;
integer iend, jblk;
real lgap;
integer done;
real rgap, left;
integer wend, iter;
real bstw;
integer itmp1, indld;
real fudge;
integer idone;
real sigma;
integer iinfo, iindr;
real resid;
extern /* Subroutine */ int sscal_(integer *, real *, real *, integer *);
logical eskip;
real right;
integer nclus, zfrom;
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *);
real rqtol;
integer iindc1, iindc2;
extern /* Subroutine */ int slar1v_(integer *, integer *, integer *, real
*, real *, real *, real *, real *, real *, real *, real *,
logical *, integer *, real *, real *, integer *, integer *, real *
, real *, real *, real *);
logical stp2ii;
real lambda;
integer ibegin, indeig;
logical needbs;
integer indlld;
real sgndef, mingma;
extern doublereal slamch_(char *);
integer oldien, oldncl, wbegin;
real spdiam;
integer negcnt, oldcls;
real savgap;
integer ndepth;
real ssigma;
logical usedbs;
integer iindwk, offset;
real gaptol;
extern /* Subroutine */ int slarrb_(integer *, real *, real *, integer *,
integer *, real *, real *, integer *, real *, real *, real *,
real *, integer *, real *, real *, integer *, integer *), slarrf_(
integer *, real *, real *, real *, integer *, integer *, real *,
real *, real *, real *, real *, real *, real *, real *, real *,
real *, real *, integer *);
integer newcls, oldfst, indwrk, windex, oldlst;
logical usedrq;
integer newfst, newftt, parity, windmn, isupmn, newlst, windpl, zusedl,
newsiz, zusedu, zusedw;
real bstres, nrminv;
logical tryrqc;
integer isupmx;
real rqcorr;
extern /* Subroutine */ int slaset_(char *, integer *, integer *, real *,
real *, real *, integer *);
/* -- LAPACK auxiliary routine (version 3.2) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* 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. */
/* Arguments */
/* ========= */
/* N (input) INTEGER */
/* The order of the matrix. N >= 0. */
/* VL (input) REAL */
/* VU (input) REAL */
/* Lower and upper bounds 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. */
/* D (input/output) REAL array, dimension (N) */
/* On entry, the N diagonal elements of the diagonal matrix D. */
/* On exit, D may be overwritten. */
/* L (input/output) REAL array, dimension (N) */
/* On entry, the (N-1) subdiagonal elements of the unit */
/* bidiagonal matrix L are in elements 1 to N-1 of L */
/* (if the matrix is not splitted.) At the end of each block */
/* is stored the corresponding shift as given by SLARRE. */
/* On exit, L is overwritten. */
/* PIVMIN (in) DOUBLE PRECISION */
/* The minimum pivot allowed in the Sturm sequence. */
/* ISPLIT (input) INTEGER array, dimension (N) */
/* The splitting points, at which T breaks up into blocks. */
/* The first block consists of rows/columns 1 to */
/* ISPLIT( 1 ), the second of rows/columns ISPLIT( 1 )+1 */
/* through ISPLIT( 2 ), etc. */
/* M (input) INTEGER */
/* The total number of input eigenvalues. 0 <= M <= N. */
/* DOL (input) INTEGER */
/* DOU (input) INTEGER */
/* If the user wants to compute only selected eigenvectors from all */
/* the eigenvalues supplied, he can specify an index range DOL:DOU. */
/* Or else the setting DOL=1, DOU=M should be applied. */
/* Note that DOL and DOU refer to the order in which the eigenvalues */
/* are stored in W. */
/* If the user wants to compute only selected eigenpairs, then */
/* the columns DOL-1 to DOU+1 of the eigenvector space Z contain the */
/* computed eigenvectors. All other columns of Z are set to zero. */
/* MINRGP (input) REAL */
/* RTOL1 (input) REAL */
/* RTOL2 (input) REAL */
/* Parameters for bisection. */
/* An interval [LEFT,RIGHT] has converged if */
/* RIGHT-LEFT.LT.MAX( RTOL1*GAP, RTOL2*MAX(|LEFT|,|RIGHT|) ) */
/* W (input/output) REAL array, dimension (N) */
/* The first M elements of W contain 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 array */
/* W from SLARRE is expected here ). Furthermore, they are with */
/* respect to the shift of the corresponding root representation */
/* for their block. On exit, W holds the eigenvalues of the */
/* UNshifted matrix. */
/* WERR (input/output) REAL array, dimension (N) */
/* The first M elements contain the semiwidth of the uncertainty */
/* interval of the corresponding eigenvalue in W */
/* WGAP (input/output) REAL array, dimension (N) */
/* The separation from the right neighbor eigenvalue in W. */
/* IBLOCK (input) INTEGER array, dimension (N) */
/* The indices of the blocks (submatrices) associated with the */
/* corresponding eigenvalues in W; IBLOCK(i)=1 if eigenvalue */
/* W(i) belongs to the first block from the top, =2 if W(i) */
/* belongs to the second block, etc. */
/* INDEXW (input) INTEGER array, dimension (N) */
/* The indices of the eigenvalues within each block (submatrix); */
/* for example, INDEXW(i)= 10 and IBLOCK(i)=2 imply that the */
/* i-th eigenvalue W(i) is the 10-th eigenvalue in the second block. */
/* GERS (input) REAL array, dimension (2*N) */
/* The N Gerschgorin intervals (the i-th Gerschgorin interval */
/* is (GERS(2*i-1), GERS(2*i)). The Gerschgorin intervals should */
/* be computed from the original UNshifted matrix. */
/* Z (output) REAL array, dimension (LDZ, max(1,M) ) */
/* If INFO = 0, the first M columns of Z contain the */
/* orthonormal eigenvectors of the matrix T */
/* corresponding to the input eigenvalues, with the i-th */
/* column of Z holding the eigenvector associated with W(i). */
/* Note: the user must ensure that at least max(1,M) columns are */
/* supplied in the array Z. */
/* LDZ (input) INTEGER */
/* The leading dimension of the array Z. LDZ >= 1, and if */
/* JOBZ = 'V', LDZ >= max(1,N). */
/* ISUPPZ (output) INTEGER array, dimension ( 2*max(1,M) ) */
/* The support of the eigenvectors in Z, i.e., the indices */
/* indicating the nonzero elements in Z. The I-th eigenvector */
/* is nonzero only in elements ISUPPZ( 2*I-1 ) through */
/* ISUPPZ( 2*I ). */
/* WORK (workspace) REAL array, dimension (12*N) */
/* IWORK (workspace) INTEGER array, dimension (7*N) */
/* INFO (output) INTEGER */
/* = 0: successful exit */
/* > 0: A problem occured in SLARRV. */
/* < 0: One of the called subroutines signaled an internal problem. */
/* Needs inspection of the corresponding parameter IINFO */
/* for further information. */
/* =-1: Problem in SLARRB when refining a child's eigenvalues. */
/* =-2: Problem in SLARRF when 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 parameter MINRGP smaller and recompile. */
/* However, as the orthogonality of the computed vectors is */
/* proportional to 1/MINRGP, the user should be aware that */
/* he might be trading in precision when he decreases MINRGP. */
/* =-3: Problem in SLARRB when refining a single eigenvalue */
/* after the Rayleigh correction was rejected. */
/* = 5: The Rayleigh Quotient Iteration failed to converge to */
/* full accuracy in MAXITR steps. */
/* Further Details */
/* =============== */
/* Based on contributions by */
/* 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 */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* .. */
/* The first N entries of WORK are reserved for the eigenvalues */
/* Parameter adjustments */
--d__;
--l;
--isplit;
--w;
--werr;
--wgap;
--iblock;
--indexw;
--gers;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--isuppz;
--work;
--iwork;
/* Function Body */
indld = *n + 1;
indlld = (*n << 1) + 1;
indwrk = *n * 3 + 1;
minwsize = *n * 12;
i__1 = minwsize;
for (i__ = 1; i__ <= i__1; ++i__) {
work[i__] = 0.f;
/* L5: */
}
/* IWORK(IINDR+1:IINDR+N) hold the twist indices R for the */
/* factorization used to compute the FP vector */
iindr = 0;
/* IWORK(IINDC1+1:IINC2+N) are used to store the clusters of the current */
/* layer and the one above. */
iindc1 = *n;
iindc2 = *n << 1;
iindwk = *n * 3 + 1;
miniwsize = *n * 7;
i__1 = miniwsize;
for (i__ = 1; i__ <= i__1; ++i__) {
iwork[i__] = 0;
/* L10: */
}
zusedl = 1;
if (*dol > 1) {
/* Set lower bound for use of Z */
zusedl = *dol - 1;
}
zusedu = *m;
if (*dou < *m) {
/* Set lower bound for use of Z */
zusedu = *dou + 1;
}
/* The width of the part of Z that is used */
zusedw = zusedu - zusedl + 1;
slaset_("Full", n, &zusedw, &c_b5, &c_b5, &z__[zusedl * z_dim1 + 1], ldz);
eps = slamch_("Precision");
rqtol = eps * 2.f;
/* Set expert flags for standard code. */
tryrqc = TRUE_;
if (*dol == 1 && *dou == *m) {
} else {
/* Only selected eigenpairs are computed. Since the other evalues */
/* are not refined by RQ iteration, bisection has to compute to full */
/* accuracy. */
*rtol1 = eps * 4.f;
*rtol2 = eps * 4.f;
}
/* The entries WBEGIN:WEND in W, WERR, WGAP correspond to the */
/* desired eigenvalues. The support of the nonzero eigenvector */
/* entries is contained in the interval IBEGIN:IEND. */
/* Remark that if k eigenpairs are desired, then the eigenvectors */
/* are stored in k contiguous columns of Z. */
/* DONE is the number of eigenvectors already computed */
done = 0;
ibegin = 1;
wbegin = 1;
i__1 = iblock[*m];
for (jblk = 1; jblk <= i__1; ++jblk) {
iend = isplit[jblk];
sigma = l[iend];
/* Find the eigenvectors of the submatrix indexed IBEGIN */
/* through IEND. */
wend = wbegin - 1;
L15:
if (wend < *m) {
if (iblock[wend + 1] == jblk) {
++wend;
goto L15;
}
}
if (wend < wbegin) {
ibegin = iend + 1;
goto L170;
} else if (wend < *dol || wbegin > *dou) {
ibegin = iend + 1;
wbegin = wend + 1;
goto L170;
}
/* Find local spectral diameter of the block */
gl = gers[(ibegin << 1) - 1];
gu = gers[ibegin * 2];
i__2 = iend;
for (i__ = ibegin + 1; i__ <= i__2; ++i__) {
/* Computing MIN */
r__1 = gers[(i__ << 1) - 1];
gl = dmin(r__1,gl);
/* Computing MAX */
r__1 = gers[i__ * 2];
gu = dmax(r__1,gu);
/* L20: */
}
spdiam = gu - gl;
/* OLDIEN is the last index of the previous block */
oldien = ibegin - 1;
/* Calculate the size of the current block */
in = iend - ibegin + 1;
/* The number of eigenvalues in the current block */
im = wend - wbegin + 1;
/* This is for a 1x1 block */
if (ibegin == iend) {
++done;
z__[ibegin + wbegin * z_dim1] = 1.f;
isuppz[(wbegin << 1) - 1] = ibegin;
isuppz[wbegin * 2] = ibegin;
w[wbegin] += sigma;
work[wbegin] = w[wbegin];
ibegin = iend + 1;
++wbegin;
goto L170;
}
/* The desired (shifted) eigenvalues are stored in W(WBEGIN:WEND) */
/* Note that these can be approximations, in this case, the corresp. */
/* entries of WERR give the size of the uncertainty interval. */
/* The eigenvalue approximations will be refined when necessary as */
/* high relative accuracy is required for the computation of the */
/* corresponding eigenvectors. */
scopy_(&im, &w[wbegin], &c__1, &work[wbegin], &c__1);
/* We store in W the eigenvalue approximations w.r.t. the original */
/* matrix T. */
i__2 = im;
for (i__ = 1; i__ <= i__2; ++i__) {
w[wbegin + i__ - 1] += sigma;
/* L30: */
}
/* NDEPTH is the current depth of the representation tree */
ndepth = 0;
/* PARITY is either 1 or 0 */
parity = 1;
/* NCLUS is the number of clusters for the next level of the */
/* representation tree, we start with NCLUS = 1 for the root */
nclus = 1;
iwork[iindc1 + 1] = 1;
iwork[iindc1 + 2] = im;
/* IDONE is the number of eigenvectors already computed in the current */
/* block */
idone = 0;
/* loop while( IDONE.LT.IM ) */
/* generate the representation tree for the current block and */
/* compute the eigenvectors */
L40:
if (idone < im) {
/* This is a crude protection against infinitely deep trees */
if (ndepth > *m) {
*info = -2;
return 0;
}
/* breadth first processing of the current level of the representation */
/* tree: OLDNCL = number of clusters on current level */
oldncl = nclus;
/* reset NCLUS to count the number of child clusters */
nclus = 0;
parity = 1 - parity;
if (parity == 0) {
oldcls = iindc1;
newcls = iindc2;
} else {
oldcls = iindc2;
newcls = iindc1;
}
/* Process the clusters on the current level */
i__2 = oldncl;
for (i__ = 1; i__ <= i__2; ++i__) {
j = oldcls + (i__ << 1);
/* OLDFST, OLDLST = first, last index of current cluster. */
/* cluster indices start with 1 and are relative */
/* to WBEGIN when accessing W, WGAP, WERR, Z */
oldfst = iwork[j - 1];
oldlst = iwork[j];
if (ndepth > 0) {
/* Retrieve relatively robust representation (RRR) of cluster */
/* that has been computed at the previous level */
/* The RRR is stored in Z and overwritten once the eigenvectors */
/* have been computed or when the cluster is refined */
if (*dol == 1 && *dou == *m) {
/* Get representation from location of the leftmost evalue */
/* of the cluster */
j = wbegin + oldfst - 1;
} else {
if (wbegin + oldfst - 1 < *dol) {
/* Get representation from the left end of Z array */
j = *dol - 1;
} else if (wbegin + oldfst - 1 > *dou) {
/* Get representation from the right end of Z array */
j = *dou;
} else {
j = wbegin + oldfst - 1;
}
}
scopy_(&in, &z__[ibegin + j * z_dim1], &c__1, &d__[ibegin]
, &c__1);
i__3 = in - 1;
scopy_(&i__3, &z__[ibegin + (j + 1) * z_dim1], &c__1, &l[
ibegin], &c__1);
sigma = z__[iend + (j + 1) * z_dim1];
/* Set the corresponding entries in Z to zero */
slaset_("Full", &in, &c__2, &c_b5, &c_b5, &z__[ibegin + j
* z_dim1], ldz);
}
/* Compute DL and DLL of current RRR */
i__3 = iend - 1;
for (j = ibegin; j <= i__3; ++j) {
tmp = d__[j] * l[j];
work[indld - 1 + j] = tmp;
work[indlld - 1 + j] = tmp * l[j];
/* L50: */
}
if (ndepth > 0) {
/* P and Q are index of the first and last eigenvalue to compute */
/* within the current block */
p = indexw[wbegin - 1 + oldfst];
q = indexw[wbegin - 1 + oldlst];
/* Offset for the arrays WORK, WGAP and WERR, i.e., th P-OFFSET */
/* thru' Q-OFFSET elements of these arrays are to be used. */
/* OFFSET = P-OLDFST */
offset = indexw[wbegin] - 1;
/* perform limited bisection (if necessary) to get approximate */
/* eigenvalues to the precision needed. */
slarrb_(&in, &d__[ibegin], &work[indlld + ibegin - 1], &p,
&q, rtol1, rtol2, &offset, &work[wbegin], &wgap[
wbegin], &werr[wbegin], &work[indwrk], &iwork[
iindwk], pivmin, &spdiam, &in, &iinfo);
if (iinfo != 0) {
*info = -1;
return 0;
}
/* We also recompute the extremal gaps. W holds all eigenvalues */
/* of the unshifted matrix and must be used for computation */
/* of WGAP, the entries of WORK might stem from RRRs with */
/* different shifts. The gaps from WBEGIN-1+OLDFST to */
/* WBEGIN-1+OLDLST are correctly computed in SLARRB. */
/* However, we only allow the gaps to become greater since */
/* this is what should happen when we decrease WERR */
if (oldfst > 1) {
/* Computing MAX */
r__1 = wgap[wbegin + oldfst - 2], r__2 = w[wbegin +
oldfst - 1] - werr[wbegin + oldfst - 1] - w[
wbegin + oldfst - 2] - werr[wbegin + oldfst -
2];
wgap[wbegin + oldfst - 2] = dmax(r__1,r__2);
}
if (wbegin + oldlst - 1 < wend) {
/* Computing MAX */
r__1 = wgap[wbegin + oldlst - 1], r__2 = w[wbegin +
oldlst] - werr[wbegin + oldlst] - w[wbegin +
oldlst - 1] - werr[wbegin + oldlst - 1];
wgap[wbegin + oldlst - 1] = dmax(r__1,r__2);
}
/* Each time the eigenvalues in WORK get refined, we store */
/* the newly found approximation with all shifts applied in W */
i__3 = oldlst;
for (j = oldfst; j <= i__3; ++j) {
w[wbegin + j - 1] = work[wbegin + j - 1] + sigma;
/* L53: */
}
}
/* Process the current node. */
newfst = oldfst;
i__3 = oldlst;
for (j = oldfst; j <= i__3; ++j) {
if (j == oldlst) {
/* we are at the right end of the cluster, this is also the */
/* boundary of the child cluster */
newlst = j;
} else if (wgap[wbegin + j - 1] >= *minrgp * (r__1 = work[
wbegin + j - 1], dabs(r__1))) {
/* the right relative gap is big enough, the child cluster */
/* (NEWFST,..,NEWLST) is well separated from the following */
newlst = j;
} else {
/* inside a child cluster, the relative gap is not */
/* big enough. */
goto L140;
}
/* Compute size of child cluster found */
newsiz = newlst - newfst + 1;
/* NEWFTT is the place in Z where the new RRR or the computed */
/* eigenvector is to be stored */
if (*dol == 1 && *dou == *m) {
/* Store representation at location of the leftmost evalue */
/* of the cluster */
newftt = wbegin + newfst - 1;
} else {
if (wbegin + newfst - 1 < *dol) {
/* Store representation at the left end of Z array */
newftt = *dol - 1;
} else if (wbegin + newfst - 1 > *dou) {
/* Store representation at the right end of Z array */
newftt = *dou;
} else {
newftt = wbegin + newfst - 1;
}
}
if (newsiz > 1) {
/* Current child is not a singleton but a cluster. */
/* Compute and store new representation of child. */
/* Compute left and right cluster gap. */
/* LGAP and RGAP are not computed from WORK because */
/* the eigenvalue approximations may stem from RRRs */
/* different shifts. However, W hold all eigenvalues */
/* of the unshifted matrix. Still, the entries in WGAP */
/* have to be computed from WORK since the entries */
/* in W might be of the same order so that gaps are not */
/* exhibited correctly for very close eigenvalues. */
if (newfst == 1) {
/* Computing MAX */
r__1 = 0.f, r__2 = w[wbegin] - werr[wbegin] - *vl;
lgap = dmax(r__1,r__2);
} else {
lgap = wgap[wbegin + newfst - 2];
}
rgap = wgap[wbegin + newlst - 1];
/* Compute left- and rightmost eigenvalue of child */
/* to high precision in order to shift as close */
/* as possible and obtain as large relative gaps */
/* as possible */
for (k = 1; k <= 2; ++k) {
if (k == 1) {
p = indexw[wbegin - 1 + newfst];
} else {
p = indexw[wbegin - 1 + newlst];
}
offset = indexw[wbegin] - 1;
slarrb_(&in, &d__[ibegin], &work[indlld + ibegin
- 1], &p, &p, &rqtol, &rqtol, &offset, &
work[wbegin], &wgap[wbegin], &werr[wbegin]
, &work[indwrk], &iwork[iindwk], pivmin, &
spdiam, &in, &iinfo);
/* L55: */
}
if (wbegin + newlst - 1 < *dol || wbegin + newfst - 1
> *dou) {
/* if the cluster contains no desired eigenvalues */
/* skip the computation of that branch of the rep. tree */
/* We could skip before the refinement of the extremal */
/* eigenvalues of the child, but then the representation */
/* tree could be different from the one when nothing is */
/* skipped. For this reason we skip at this place. */
idone = idone + newlst - newfst + 1;
goto L139;
}
/* Compute RRR of child cluster. */
/* Note that the new RRR is stored in Z */
/* SLARRF needs LWORK = 2*N */
slarrf_(&in, &d__[ibegin], &l[ibegin], &work[indld +
ibegin - 1], &newfst, &newlst, &work[wbegin],
&wgap[wbegin], &werr[wbegin], &spdiam, &lgap,
&rgap, pivmin, &tau, &z__[ibegin + newftt *
z_dim1], &z__[ibegin + (newftt + 1) * z_dim1],
&work[indwrk], &iinfo);
if (iinfo == 0) {
/* a new RRR for the cluster was found by SLARRF */
/* update shift and store it */
ssigma = sigma + tau;
z__[iend + (newftt + 1) * z_dim1] = ssigma;
/* WORK() are the midpoints and WERR() the semi-width */
/* Note that the entries in W are unchanged. */
i__4 = newlst;
for (k = newfst; k <= i__4; ++k) {
fudge = eps * 3.f * (r__1 = work[wbegin + k -
1], dabs(r__1));
work[wbegin + k - 1] -= tau;
fudge += eps * 4.f * (r__1 = work[wbegin + k
- 1], dabs(r__1));
/* Fudge errors */
werr[wbegin + k - 1] += fudge;
/* Gaps are not fudged. Provided that WERR is small */
/* when eigenvalues are close, a zero gap indicates */
/* that a new representation is needed for resolving */
/* the cluster. A fudge could lead to a wrong decision */
/* of judging eigenvalues 'separated' which in */
/* reality are not. This could have a negative impact */
/* on the orthogonality of the computed eigenvectors. */
/* L116: */
}
++nclus;
k = newcls + (nclus << 1);
iwork[k - 1] = newfst;
iwork[k] = newlst;
} else {
*info = -2;
return 0;
}
} else {
/* Compute eigenvector of singleton */
iter = 0;
tol = log((real) in) * 4.f * eps;
k = newfst;
windex = wbegin + k - 1;
/* Computing MAX */
i__4 = windex - 1;
windmn = max(i__4,1);
/* Computing MIN */
i__4 = windex + 1;
windpl = min(i__4,*m);
lambda = work[windex];
++done;
/* Check if eigenvector computation is to be skipped */
if (windex < *dol || windex > *dou) {
eskip = TRUE_;
goto L125;
} else {
eskip = FALSE_;
}
left = work[windex] - werr[windex];
right = work[windex] + werr[windex];
indeig = indexw[windex];
/* Note that since we compute the eigenpairs for a child, */
/* all eigenvalue approximations are w.r.t the same shift. */
/* In this case, the entries in WORK should be used for */
/* computing the gaps since they exhibit even very small */
/* differences in the eigenvalues, as opposed to the */
/* entries in W which might "look" the same. */
if (k == 1) {
/* In the case RANGE='I' and with not much initial */
/* accuracy in LAMBDA and VL, the formula */
/* LGAP = MAX( ZERO, (SIGMA - VL) + LAMBDA ) */
/* can lead to an overestimation of the left gap and */
/* thus to inadequately early RQI 'convergence'. */
/* Prevent this by forcing a small left gap. */
/* Computing MAX */
r__1 = dabs(left), r__2 = dabs(right);
lgap = eps * dmax(r__1,r__2);
} else {
lgap = wgap[windmn];
}
if (k == im) {
/* In the case RANGE='I' and with not much initial */
/* accuracy in LAMBDA and VU, the formula */
/* can lead to an overestimation of the right gap and */
/* thus to inadequately early RQI 'convergence'. */
/* Prevent this by forcing a small right gap. */
/* Computing MAX */
r__1 = dabs(left), r__2 = dabs(right);
rgap = eps * dmax(r__1,r__2);
} else {
rgap = wgap[windex];
}
gap = dmin(lgap,rgap);
if (k == 1 || k == im) {
/* The eigenvector support can become wrong */
/* because significant entries could be cut off due to a */
/* large GAPTOL parameter in LAR1V. Prevent this. */
gaptol = 0.f;
} else {
gaptol = gap * eps;
}
isupmn = in;
isupmx = 1;
/* Update WGAP so that it holds the minimum gap */
/* to the left or the right. This is crucial in the */
/* case where bisection is used to ensure that the */
/* eigenvalue is refined up to the required precision. */
/* The correct value is restored afterwards. */
savgap = wgap[windex];
wgap[windex] = gap;
/* We want to use the Rayleigh Quotient Correction */
/* as often as possible since it converges quadratically */
/* when we are close enough to the desired eigenvalue. */
/* However, the Rayleigh Quotient can have the wrong sign */
/* and lead us away from the desired eigenvalue. In this */
/* case, the best we can do is to use bisection. */
usedbs = FALSE_;
usedrq = FALSE_;
/* Bisection is initially turned off unless it is forced */
needbs = ! tryrqc;
L120:
/* Check if bisection should be used to refine eigenvalue */
if (needbs) {
/* Take the bisection as new iterate */
usedbs = TRUE_;
itmp1 = iwork[iindr + windex];
offset = indexw[wbegin] - 1;
r__1 = eps * 2.f;
slarrb_(&in, &d__[ibegin], &work[indlld + ibegin
- 1], &indeig, &indeig, &c_b5, &r__1, &
offset, &work[wbegin], &wgap[wbegin], &
werr[wbegin], &work[indwrk], &iwork[
iindwk], pivmin, &spdiam, &itmp1, &iinfo);
if (iinfo != 0) {
*info = -3;
return 0;
}
lambda = work[windex];
/* Reset twist index from inaccurate LAMBDA to */
/* force computation of true MINGMA */
iwork[iindr + windex] = 0;
}
/* Given LAMBDA, compute the eigenvector. */
L__1 = ! usedbs;
slar1v_(&in, &c__1, &in, &lambda, &d__[ibegin], &l[
ibegin], &work[indld + ibegin - 1], &work[
indlld + ibegin - 1], pivmin, &gaptol, &z__[
ibegin + windex * z_dim1], &L__1, &negcnt, &
ztz, &mingma, &iwork[iindr + windex], &isuppz[
(windex << 1) - 1], &nrminv, &resid, &rqcorr,
&work[indwrk]);
if (iter == 0) {
bstres = resid;
bstw = lambda;
} else if (resid < bstres) {
bstres = resid;
bstw = lambda;
}
/* Computing MIN */
i__4 = isupmn, i__5 = isuppz[(windex << 1) - 1];
isupmn = min(i__4,i__5);
/* Computing MAX */
i__4 = isupmx, i__5 = isuppz[windex * 2];
isupmx = max(i__4,i__5);
++iter;
/* sin alpha <= |resid|/gap */
/* Note that both the residual and the gap are */
/* proportional to the matrix, so ||T|| doesn't play */
/* a role in the quotient */
/* Convergence test for Rayleigh-Quotient iteration */
/* (omitted when Bisection has been used) */
if (resid > tol * gap && dabs(rqcorr) > rqtol * dabs(
lambda) && ! usedbs) {
/* We need to check that the RQCORR update doesn't */
/* move the eigenvalue away from the desired one and */
/* towards a neighbor. -> protection with bisection */
if (indeig <= negcnt) {
/* The wanted eigenvalue lies to the left */
sgndef = -1.f;
} else {
/* The wanted eigenvalue lies to the right */
sgndef = 1.f;
}
/* We only use the RQCORR if it improves the */
/* the iterate reasonably. */
if (rqcorr * sgndef >= 0.f && lambda + rqcorr <=
right && lambda + rqcorr >= left) {
usedrq = TRUE_;
/* Store new midpoint of bisection interval in WORK */
if (sgndef == 1.f) {
/* The current LAMBDA is on the left of the true */
/* eigenvalue */
left = lambda;
/* We prefer to assume that the error estimate */
/* is correct. We could make the interval not */
/* as a bracket but to be modified if the RQCORR */
/* chooses to. In this case, the RIGHT side should */
/* be modified as follows: */
/* RIGHT = MAX(RIGHT, LAMBDA + RQCORR) */
} else {
/* The current LAMBDA is on the right of the true */
/* eigenvalue */
right = lambda;
/* See comment about assuming the error estimate is */
/* correct above. */
/* LEFT = MIN(LEFT, LAMBDA + RQCORR) */
}
work[windex] = (right + left) * .5f;
/* Take RQCORR since it has the correct sign and */
/* improves the iterate reasonably */
lambda += rqcorr;
/* Update width of error interval */
werr[windex] = (right - left) * .5f;
} else {
needbs = TRUE_;
}
if (right - left < rqtol * dabs(lambda)) {
/* The eigenvalue is computed to bisection accuracy */
/* compute eigenvector and stop */
usedbs = TRUE_;
goto L120;
} else if (iter < 10) {
goto L120;
} else if (iter == 10) {
needbs = TRUE_;
goto L120;
} else {
*info = 5;
return 0;
}
} else {
stp2ii = FALSE_;
if (usedrq && usedbs && bstres <= resid) {
lambda = bstw;
stp2ii = TRUE_;
}
if (stp2ii) {
/* improve error angle by second step */
L__1 = ! usedbs;
slar1v_(&in, &c__1, &in, &lambda, &d__[ibegin]
, &l[ibegin], &work[indld + ibegin -
1], &work[indlld + ibegin - 1],
pivmin, &gaptol, &z__[ibegin + windex
* z_dim1], &L__1, &negcnt, &ztz, &
mingma, &iwork[iindr + windex], &
isuppz[(windex << 1) - 1], &nrminv, &
resid, &rqcorr, &work[indwrk]);
}
work[windex] = lambda;
}
/* Compute FP-vector support w.r.t. whole matrix */
isuppz[(windex << 1) - 1] += oldien;
isuppz[windex * 2] += oldien;
zfrom = isuppz[(windex << 1) - 1];
zto = isuppz[windex * 2];
isupmn += oldien;
isupmx += oldien;
/* Ensure vector is ok if support in the RQI has changed */
if (isupmn < zfrom) {
i__4 = zfrom - 1;
for (ii = isupmn; ii <= i__4; ++ii) {
z__[ii + windex * z_dim1] = 0.f;
/* L122: */
}
}
if (isupmx > zto) {
i__4 = isupmx;
for (ii = zto + 1; ii <= i__4; ++ii) {
z__[ii + windex * z_dim1] = 0.f;
/* L123: */
}
}
i__4 = zto - zfrom + 1;
sscal_(&i__4, &nrminv, &z__[zfrom + windex * z_dim1],
&c__1);
L125:
/* Update W */
w[windex] = lambda + sigma;
/* Recompute the gaps on the left and right */
/* But only allow them to become larger and not */
/* smaller (which can only happen through "bad" */
/* cancellation and doesn't reflect the theory */
/* where the initial gaps are underestimated due */
/* to WERR being too crude.) */
if (! eskip) {
if (k > 1) {
/* Computing MAX */
r__1 = wgap[windmn], r__2 = w[windex] - werr[
windex] - w[windmn] - werr[windmn];
wgap[windmn] = dmax(r__1,r__2);
}
if (windex < wend) {
/* Computing MAX */
r__1 = savgap, r__2 = w[windpl] - werr[windpl]
- w[windex] - werr[windex];
wgap[windex] = dmax(r__1,r__2);
}
}
++idone;
}
/* here ends the code for the current child */
L139:
/* Proceed to any remaining child nodes */
newfst = j + 1;
L140:
;
}
/* L150: */
}
++ndepth;
goto L40;
}
ibegin = iend + 1;
wbegin = wend + 1;
L170:
;
}
return 0;
/* End of SLARRV */
} /* slarrv_ */
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