#include "clapack.h" /* Table of constant values */ static doublereal c_b5 = 0.; static integer c__1 = 1; static integer c__2 = 2; /* Subroutine */ int dlarrv_(integer *n, doublereal *vl, doublereal *vu, doublereal *d__, doublereal *l, doublereal *pivmin, integer *isplit, integer *m, integer *dol, integer *dou, doublereal *minrgp, doublereal *rtol1, doublereal *rtol2, doublereal *w, doublereal *werr, doublereal *wgap, integer *iblock, integer *indexw, doublereal *gers, doublereal *z__, integer *ldz, integer *isuppz, doublereal *work, integer *iwork, integer *info) { /* System generated locals */ integer z_dim1, z_offset, i__1, i__2, i__3, i__4, i__5; doublereal d__1, d__2; logical L__1; /* Builtin functions */ double log(doublereal); /* Local variables */ integer minwsize, i__, j, k, p, q, miniwsize, ii; doublereal gl; integer im, in; doublereal gu, gap, eps, tau, tol, tmp; integer zto; doublereal ztz; integer iend, jblk; doublereal lgap; integer done; doublereal rgap, left; integer wend, iter; doublereal bstw; integer itmp1; extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *, integer *); integer indld; doublereal fudge; integer idone; doublereal sigma; integer iinfo, iindr; doublereal resid; logical eskip; doublereal right; extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *, doublereal *, integer *); integer nclus, zfrom; doublereal rqtol; integer iindc1, iindc2; extern /* Subroutine */ int dlar1v_(integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, logical *, integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *); logical stp2ii; doublereal lambda; extern doublereal dlamch_(char *); integer ibegin, indeig; logical needbs; integer indlld; doublereal sgndef, mingma; extern /* Subroutine */ int dlarrb_(integer *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, doublereal *, integer *, integer *); integer oldien, oldncl, wbegin; doublereal spdiam; integer negcnt; extern /* Subroutine */ int dlarrf_(integer *, doublereal *, doublereal *, doublereal *, integer *, integer *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, integer *); integer oldcls; doublereal savgap; integer ndepth; doublereal ssigma; extern /* Subroutine */ int dlaset_(char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); logical usedbs; integer iindwk, offset; doublereal gaptol; integer newcls, oldfst, indwrk, windex, oldlst; logical usedrq; integer newfst, newftt, parity, windmn, windpl, isupmn, newlst, zusedl; doublereal bstres; integer newsiz, zusedu, zusedw; doublereal nrminv, rqcorr; logical tryrqc; integer isupmx; /* -- LAPACK auxiliary routine (version 3.1.1) -- */ /* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */ /* November 2006 */ /* .. Scalar Arguments .. */ /* .. */ /* .. Array Arguments .. */ /* .. */ /* Purpose */ /* ======= */ /* DLARRV 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. */ /* Arguments */ /* ========= */ /* N (input) INTEGER */ /* The order of the matrix. N >= 0. */ /* VL (input) DOUBLE PRECISION */ /* VU (input) DOUBLE PRECISION */ /* 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) DOUBLE PRECISION array, dimension (N) */ /* On entry, the N diagonal elements of the diagonal matrix D. */ /* On exit, D may be overwritten. */ /* L (input/output) DOUBLE PRECISION 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 DLARRE. */ /* 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) DOUBLE PRECISION */ /* RTOL1 (input) DOUBLE PRECISION */ /* RTOL2 (input) DOUBLE PRECISION */ /* Parameters for bisection. */ /* An interval [LEFT,RIGHT] has converged if */ /* RIGHT-LEFT.LT.MAX( RTOL1*GAP, RTOL2*MAX(|LEFT|,|RIGHT|) ) */ /* W (input/output) DOUBLE PRECISION 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 DLARRE 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) DOUBLE PRECISION array, dimension (N) */ /* The first M elements contain the semiwidth of the uncertainty */ /* interval of the corresponding eigenvalue in W */ /* WGAP (input/output) DOUBLE PRECISION 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) DOUBLE PRECISION 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) DOUBLE PRECISION 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) DOUBLE PRECISION array, dimension (12*N) */ /* IWORK (workspace) INTEGER array, dimension (7*N) */ /* INFO (output) INTEGER */ /* = 0: successful exit */ /* > 0: A problem occured in DLARRV. */ /* < 0: One of the called subroutines signaled an internal problem. */ /* Needs inspection of the corresponding parameter IINFO */ /* for further information. */ /* =-1: Problem in DLARRB when refining a child's eigenvalues. */ /* =-2: Problem in DLARRF 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 DLARRB 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.; /* 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; dlaset_("Full", n, &zusedw, &c_b5, &c_b5, &z__[zusedl * z_dim1 + 1], ldz); eps = dlamch_("Precision"); rqtol = eps * 2.; /* 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.; *rtol2 = eps * 4.; } /* 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 */ d__1 = gers[(i__ << 1) - 1]; gl = min(d__1,gl); /* Computing MAX */ d__1 = gers[i__ * 2]; gu = max(d__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.; 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. */ dcopy_(&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; } } dcopy_(&in, &z__[ibegin + j * z_dim1], &c__1, &d__[ibegin] , &c__1); i__3 = in - 1; dcopy_(&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 */ dlaset_("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. */ dlarrb_(&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 DLARRB. */ /* However, we only allow the gaps to become greater since */ /* this is what should happen when we decrease WERR */ if (oldfst > 1) { /* Computing MAX */ d__1 = wgap[wbegin + oldfst - 2], d__2 = w[wbegin + oldfst - 1] - werr[wbegin + oldfst - 1] - w[ wbegin + oldfst - 2] - werr[wbegin + oldfst - 2]; wgap[wbegin + oldfst - 2] = max(d__1,d__2); } if (wbegin + oldlst - 1 < wend) { /* Computing MAX */ d__1 = wgap[wbegin + oldlst - 1], d__2 = w[wbegin + oldlst] - werr[wbegin + oldlst] - w[wbegin + oldlst - 1] - werr[wbegin + oldlst - 1]; wgap[wbegin + oldlst - 1] = max(d__1,d__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 * (d__1 = work[ wbegin + j - 1], abs(d__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 */ d__1 = 0., d__2 = w[wbegin] - werr[wbegin] - *vl; lgap = max(d__1,d__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; dlarrb_(&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 */ /* DLARRF needs LWORK = 2*N */ dlarrf_(&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 DLARRF */ /* 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. * (d__1 = work[wbegin + k - 1], abs(d__1)); work[wbegin + k - 1] -= tau; fudge += eps * 4. * (d__1 = work[wbegin + k - 1], abs(d__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((doublereal) in) * 4. * 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 */ d__1 = abs(left), d__2 = abs(right); lgap = eps * max(d__1,d__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 */ d__1 = abs(left), d__2 = abs(right); rgap = eps * max(d__1,d__2); } else { rgap = wgap[windex]; } gap = min(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.; } 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; d__1 = eps * 2.; dlarrb_(&in, &d__[ibegin], &work[indlld + ibegin - 1], &indeig, &indeig, &c_b5, &d__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; dlar1v_(&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 && abs(rqcorr) > rqtol * abs( 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.; } else { /* The wanted eigenvalue lies to the right */ sgndef = 1.; } /* We only use the RQCORR if it improves the */ /* the iterate reasonably. */ if (rqcorr * sgndef >= 0. && lambda + rqcorr <= right && lambda + rqcorr >= left) { usedrq = TRUE_; /* Store new midpoint of bisection interval in WORK */ if (sgndef == 1.) { /* 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) * .5; /* Take RQCORR since it has the correct sign and */ /* improves the iterate reasonably */ lambda += rqcorr; /* Update width of error interval */ werr[windex] = (right - left) * .5; } else { needbs = TRUE_; } if (right - left < rqtol * abs(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; dlar1v_(&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.; /* L122: */ } } if (isupmx > zto) { i__4 = isupmx; for (ii = zto + 1; ii <= i__4; ++ii) { z__[ii + windex * z_dim1] = 0.; /* L123: */ } } i__4 = zto - zfrom + 1; dscal_(&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 */ d__1 = wgap[windmn], d__2 = w[windex] - werr[ windex] - w[windmn] - werr[windmn]; wgap[windmn] = max(d__1,d__2); } if (windex < wend) { /* Computing MAX */ d__1 = savgap, d__2 = w[windpl] - werr[windpl] - w[windex] - werr[windex]; wgap[windex] = max(d__1,d__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 DLARRV */ } /* dlarrv_ */