/* sstemr.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 integer c__1 = 1; static real c_b18 = .003f; /* Subroutine */ int sstemr_(char *jobz, char *range, integer *n, real *d__, real *e, real *vl, real *vu, integer *il, integer *iu, integer *m, real *w, real *z__, integer *ldz, integer *nzc, integer *isuppz, logical *tryrac, real *work, integer *lwork, integer *iwork, integer * liwork, integer *info) { /* System generated locals */ integer z_dim1, z_offset, i__1, i__2; real r__1, r__2; /* Builtin functions */ double sqrt(doublereal); /* Local variables */ integer i__, j; real r1, r2; integer jj; real cs; integer in; real sn, wl, wu; integer iil, iiu; real eps, tmp; integer indd, iend, jblk, wend; real rmin, rmax; integer itmp; real tnrm; integer inde2; extern /* Subroutine */ int slae2_(real *, real *, real *, real *, real *) ; integer itmp2; real rtol1, rtol2, scale; integer indgp; extern logical lsame_(char *, char *); integer iinfo; extern /* Subroutine */ int sscal_(integer *, real *, real *, integer *); integer iindw, ilast, lwmin; extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *, integer *), sswap_(integer *, real *, integer *, real *, integer * ); logical wantz; extern /* Subroutine */ int slaev2_(real *, real *, real *, real *, real * , real *, real *); logical alleig; integer ibegin; logical indeig; integer iindbl; logical valeig; extern doublereal slamch_(char *); integer wbegin; real safmin; extern /* Subroutine */ int xerbla_(char *, integer *); real bignum; integer inderr, iindwk, indgrs, offset; extern /* Subroutine */ int slarrc_(char *, integer *, real *, real *, real *, real *, real *, integer *, integer *, integer *, integer * ), slarre_(char *, integer *, real *, real *, integer *, integer *, real *, real *, real *, real *, real *, real *, integer *, integer *, integer *, real *, real *, real *, integer * , integer *, real *, real *, real *, integer *, integer *) ; real thresh; integer iinspl, indwrk, ifirst, liwmin, nzcmin; real pivmin; extern doublereal slanst_(char *, integer *, real *, real *); extern /* Subroutine */ int slarrj_(integer *, real *, real *, integer *, integer *, real *, integer *, real *, real *, real *, integer *, real *, real *, integer *), slarrr_(integer *, real *, real *, integer *); integer nsplit; extern /* Subroutine */ int slarrv_(integer *, real *, real *, real *, real *, real *, integer *, integer *, integer *, integer *, real * , real *, real *, real *, real *, real *, integer *, integer *, real *, real *, integer *, integer *, real *, integer *, integer * ); real smlnum; extern /* Subroutine */ int slasrt_(char *, integer *, real *, integer *); logical lquery, zquery; /* -- LAPACK computational routine (version 3.2) -- */ /* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */ /* November 2006 */ /* .. Scalar Arguments .. */ /* .. */ /* .. Array Arguments .. */ /* .. */ /* Purpose */ /* ======= */ /* SSTEMR computes selected eigenvalues and, optionally, eigenvectors */ /* of a real symmetric tridiagonal matrix T. Any such unreduced matrix has */ /* a well defined set of pairwise different real eigenvalues, the corresponding */ /* real eigenvectors are pairwise orthogonal. */ /* The spectrum may be computed either completely or partially by specifying */ /* either an interval (VL,VU] or a range of indices IL:IU for the desired */ /* eigenvalues. */ /* Depending on the number of desired eigenvalues, these are computed either */ /* by bisection or the dqds algorithm. Numerically orthogonal eigenvectors are */ /* computed by the use of various suitable L D L^T factorizations near clusters */ /* of close eigenvalues (referred to as RRRs, Relatively Robust */ /* Representations). An informal sketch of the algorithm follows. */ /* For each unreduced block (submatrix) of T, */ /* (a) Compute T - sigma I = L D L^T, so that L and D */ /* define all the wanted eigenvalues to high relative accuracy. */ /* This means that small relative changes in the entries of D and L */ /* cause only small relative changes in the eigenvalues and */ /* eigenvectors. The standard (unfactored) representation of the */ /* tridiagonal matrix T does not have this property in general. */ /* (b) Compute the eigenvalues to suitable accuracy. */ /* If the eigenvectors are desired, the algorithm attains full */ /* accuracy of the computed eigenvalues only right before */ /* the corresponding vectors have to be computed, see steps c) and d). */ /* (c) For each cluster of close eigenvalues, select a new */ /* shift close to the cluster, find a new factorization, and refine */ /* the shifted eigenvalues to suitable accuracy. */ /* (d) For each eigenvalue with a large enough relative separation compute */ /* the corresponding eigenvector by forming a rank revealing twisted */ /* factorization. Go back to (c) for any clusters that remain. */ /* For more details, see: */ /* - Inderjit S. Dhillon and Beresford N. Parlett: "Multiple representations */ /* to compute orthogonal eigenvectors of symmetric tridiagonal matrices," */ /* Linear Algebra and its Applications, 387(1), pp. 1-28, August 2004. */ /* - Inderjit Dhillon and Beresford Parlett: "Orthogonal Eigenvectors and */ /* Relative Gaps," SIAM Journal on Matrix Analysis and Applications, Vol. 25, */ /* 2004. Also LAPACK Working Note 154. */ /* - Inderjit Dhillon: "A new O(n^2) algorithm for the symmetric */ /* tridiagonal eigenvalue/eigenvector problem", */ /* Computer Science Division Technical Report No. UCB/CSD-97-971, */ /* UC Berkeley, May 1997. */ /* Notes: */ /* 1.SSTEMR works only on machines which follow IEEE-754 */ /* floating-point standard in their handling of infinities and NaNs. */ /* This permits the use of efficient inner loops avoiding a check for */ /* zero divisors. */ /* Arguments */ /* ========= */ /* JOBZ (input) CHARACTER*1 */ /* = 'N': Compute eigenvalues only; */ /* = 'V': Compute eigenvalues and eigenvectors. */ /* RANGE (input) CHARACTER*1 */ /* = 'A': all eigenvalues will be found. */ /* = 'V': all eigenvalues in the half-open interval (VL,VU] */ /* will be found. */ /* = 'I': the IL-th through IU-th eigenvalues will be found. */ /* N (input) INTEGER */ /* The order of the matrix. N >= 0. */ /* D (input/output) REAL array, dimension (N) */ /* On entry, the N diagonal elements of the tridiagonal matrix */ /* T. On exit, D is overwritten. */ /* E (input/output) REAL array, dimension (N) */ /* On entry, the (N-1) subdiagonal elements of the tridiagonal */ /* matrix T in elements 1 to N-1 of E. E(N) need not be set on */ /* input, but is used internally as workspace. */ /* On exit, E is overwritten. */ /* VL (input) REAL */ /* VU (input) REAL */ /* If RANGE='V', the lower and upper bounds of the interval to */ /* be searched for eigenvalues. VL < VU. */ /* Not referenced if RANGE = 'A' or 'I'. */ /* IL (input) INTEGER */ /* IU (input) INTEGER */ /* If RANGE='I', the indices (in ascending order) of the */ /* smallest and largest eigenvalues to be returned. */ /* 1 <= IL <= IU <= N, if N > 0. */ /* Not referenced if RANGE = 'A' or 'V'. */ /* M (output) INTEGER */ /* The total number of eigenvalues found. 0 <= M <= N. */ /* If RANGE = 'A', M = N, and if RANGE = 'I', M = IU-IL+1. */ /* W (output) REAL array, dimension (N) */ /* The first M elements contain the selected eigenvalues in */ /* ascending order. */ /* Z (output) REAL array, dimension (LDZ, max(1,M) ) */ /* If JOBZ = 'V', and if INFO = 0, then the first M columns of Z */ /* contain the orthonormal eigenvectors of the matrix T */ /* corresponding to the selected eigenvalues, with the i-th */ /* column of Z holding the eigenvector associated with W(i). */ /* If JOBZ = 'N', then Z is not referenced. */ /* Note: the user must ensure that at least max(1,M) columns are */ /* supplied in the array Z; if RANGE = 'V', the exact value of M */ /* is not known in advance and can be computed with a workspace */ /* query by setting NZC = -1, see below. */ /* LDZ (input) INTEGER */ /* The leading dimension of the array Z. LDZ >= 1, and if */ /* JOBZ = 'V', then LDZ >= max(1,N). */ /* NZC (input) INTEGER */ /* The number of eigenvectors to be held in the array Z. */ /* If RANGE = 'A', then NZC >= max(1,N). */ /* If RANGE = 'V', then NZC >= the number of eigenvalues in (VL,VU]. */ /* If RANGE = 'I', then NZC >= IU-IL+1. */ /* If NZC = -1, then a workspace query is assumed; the */ /* routine calculates the number of columns of the array Z that */ /* are needed to hold the eigenvectors. */ /* This value is returned as the first entry of the Z array, and */ /* no error message related to NZC is issued by XERBLA. */ /* 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 computed eigenvector */ /* is nonzero only in elements ISUPPZ( 2*i-1 ) through */ /* ISUPPZ( 2*i ). This is relevant in the case when the matrix */ /* is split. ISUPPZ is only accessed when JOBZ is 'V' and N > 0. */ /* TRYRAC (input/output) LOGICAL */ /* If TRYRAC.EQ..TRUE., indicates that the code should check whether */ /* the tridiagonal matrix defines its eigenvalues to high relative */ /* accuracy. If so, the code uses relative-accuracy preserving */ /* algorithms that might be (a bit) slower depending on the matrix. */ /* If the matrix does not define its eigenvalues to high relative */ /* accuracy, the code can uses possibly faster algorithms. */ /* If TRYRAC.EQ..FALSE., the code is not required to guarantee */ /* relatively accurate eigenvalues and can use the fastest possible */ /* techniques. */ /* On exit, a .TRUE. TRYRAC will be set to .FALSE. if the matrix */ /* does not define its eigenvalues to high relative accuracy. */ /* WORK (workspace/output) REAL array, dimension (LWORK) */ /* On exit, if INFO = 0, WORK(1) returns the optimal */ /* (and minimal) LWORK. */ /* LWORK (input) INTEGER */ /* The dimension of the array WORK. LWORK >= max(1,18*N) */ /* if JOBZ = 'V', and LWORK >= max(1,12*N) if JOBZ = 'N'. */ /* If LWORK = -1, then a workspace query is assumed; the routine */ /* only calculates the optimal size of the WORK array, returns */ /* this value as the first entry of the WORK array, and no error */ /* message related to LWORK is issued by XERBLA. */ /* IWORK (workspace/output) INTEGER array, dimension (LIWORK) */ /* On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. */ /* LIWORK (input) INTEGER */ /* The dimension of the array IWORK. LIWORK >= max(1,10*N) */ /* if the eigenvectors are desired, and LIWORK >= max(1,8*N) */ /* if only the eigenvalues are to be computed. */ /* If LIWORK = -1, then a workspace query is assumed; the */ /* routine only calculates the optimal size of the IWORK array, */ /* returns this value as the first entry of the IWORK array, and */ /* no error message related to LIWORK is issued by XERBLA. */ /* INFO (output) INTEGER */ /* On exit, INFO */ /* = 0: successful exit */ /* < 0: if INFO = -i, the i-th argument had an illegal value */ /* > 0: if INFO = 1X, internal error in SLARRE, */ /* if INFO = 2X, internal error in SLARRV. */ /* Here, the digit X = ABS( IINFO ) < 10, where IINFO is */ /* the nonzero error code returned by SLARRE or */ /* SLARRV, respectively. */ /* 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 .. */ /* Test the input parameters. */ /* Parameter adjustments */ --d__; --e; --w; z_dim1 = *ldz; z_offset = 1 + z_dim1; z__ -= z_offset; --isuppz; --work; --iwork; /* Function Body */ wantz = lsame_(jobz, "V"); alleig = lsame_(range, "A"); valeig = lsame_(range, "V"); indeig = lsame_(range, "I"); lquery = *lwork == -1 || *liwork == -1; zquery = *nzc == -1; /* SSTEMR needs WORK of size 6*N, IWORK of size 3*N. */ /* In addition, SLARRE needs WORK of size 6*N, IWORK of size 5*N. */ /* Furthermore, SLARRV needs WORK of size 12*N, IWORK of size 7*N. */ if (wantz) { lwmin = *n * 18; liwmin = *n * 10; } else { /* need less workspace if only the eigenvalues are wanted */ lwmin = *n * 12; liwmin = *n << 3; } wl = 0.f; wu = 0.f; iil = 0; iiu = 0; if (valeig) { /* We do not reference VL, VU in the cases RANGE = 'I','A' */ /* The interval (WL, WU] contains all the wanted eigenvalues. */ /* It is either given by the user or computed in SLARRE. */ wl = *vl; wu = *vu; } else if (indeig) { /* We do not reference IL, IU in the cases RANGE = 'V','A' */ iil = *il; iiu = *iu; } *info = 0; if (! (wantz || lsame_(jobz, "N"))) { *info = -1; } else if (! (alleig || valeig || indeig)) { *info = -2; } else if (*n < 0) { *info = -3; } else if (valeig && *n > 0 && wu <= wl) { *info = -7; } else if (indeig && (iil < 1 || iil > *n)) { *info = -8; } else if (indeig && (iiu < iil || iiu > *n)) { *info = -9; } else if (*ldz < 1 || wantz && *ldz < *n) { *info = -13; } else if (*lwork < lwmin && ! lquery) { *info = -17; } else if (*liwork < liwmin && ! lquery) { *info = -19; } /* Get machine constants. */ safmin = slamch_("Safe minimum"); eps = slamch_("Precision"); smlnum = safmin / eps; bignum = 1.f / smlnum; rmin = sqrt(smlnum); /* Computing MIN */ r__1 = sqrt(bignum), r__2 = 1.f / sqrt(sqrt(safmin)); rmax = dmin(r__1,r__2); if (*info == 0) { work[1] = (real) lwmin; iwork[1] = liwmin; if (wantz && alleig) { nzcmin = *n; } else if (wantz && valeig) { slarrc_("T", n, vl, vu, &d__[1], &e[1], &safmin, &nzcmin, &itmp, & itmp2, info); } else if (wantz && indeig) { nzcmin = iiu - iil + 1; } else { /* WANTZ .EQ. FALSE. */ nzcmin = 0; } if (zquery && *info == 0) { z__[z_dim1 + 1] = (real) nzcmin; } else if (*nzc < nzcmin && ! zquery) { *info = -14; } } if (*info != 0) { i__1 = -(*info); xerbla_("SSTEMR", &i__1); return 0; } else if (lquery || zquery) { return 0; } /* Handle N = 0, 1, and 2 cases immediately */ *m = 0; if (*n == 0) { return 0; } if (*n == 1) { if (alleig || indeig) { *m = 1; w[1] = d__[1]; } else { if (wl < d__[1] && wu >= d__[1]) { *m = 1; w[1] = d__[1]; } } if (wantz && ! zquery) { z__[z_dim1 + 1] = 1.f; isuppz[1] = 1; isuppz[2] = 1; } return 0; } if (*n == 2) { if (! wantz) { slae2_(&d__[1], &e[1], &d__[2], &r1, &r2); } else if (wantz && ! zquery) { slaev2_(&d__[1], &e[1], &d__[2], &r1, &r2, &cs, &sn); } if (alleig || valeig && r2 > wl && r2 <= wu || indeig && iil == 1) { ++(*m); w[*m] = r2; if (wantz && ! zquery) { z__[*m * z_dim1 + 1] = -sn; z__[*m * z_dim1 + 2] = cs; /* Note: At most one of SN and CS can be zero. */ if (sn != 0.f) { if (cs != 0.f) { isuppz[(*m << 1) - 1] = 1; isuppz[(*m << 1) - 1] = 2; } else { isuppz[(*m << 1) - 1] = 1; isuppz[(*m << 1) - 1] = 1; } } else { isuppz[(*m << 1) - 1] = 2; isuppz[*m * 2] = 2; } } } if (alleig || valeig && r1 > wl && r1 <= wu || indeig && iiu == 2) { ++(*m); w[*m] = r1; if (wantz && ! zquery) { z__[*m * z_dim1 + 1] = cs; z__[*m * z_dim1 + 2] = sn; /* Note: At most one of SN and CS can be zero. */ if (sn != 0.f) { if (cs != 0.f) { isuppz[(*m << 1) - 1] = 1; isuppz[(*m << 1) - 1] = 2; } else { isuppz[(*m << 1) - 1] = 1; isuppz[(*m << 1) - 1] = 1; } } else { isuppz[(*m << 1) - 1] = 2; isuppz[*m * 2] = 2; } } } return 0; } /* Continue with general N */ indgrs = 1; inderr = (*n << 1) + 1; indgp = *n * 3 + 1; indd = (*n << 2) + 1; inde2 = *n * 5 + 1; indwrk = *n * 6 + 1; iinspl = 1; iindbl = *n + 1; iindw = (*n << 1) + 1; iindwk = *n * 3 + 1; /* Scale matrix to allowable range, if necessary. */ /* The allowable range is related to the PIVMIN parameter; see the */ /* comments in SLARRD. The preference for scaling small values */ /* up is heuristic; we expect users' matrices not to be close to the */ /* RMAX threshold. */ scale = 1.f; tnrm = slanst_("M", n, &d__[1], &e[1]); if (tnrm > 0.f && tnrm < rmin) { scale = rmin / tnrm; } else if (tnrm > rmax) { scale = rmax / tnrm; } if (scale != 1.f) { sscal_(n, &scale, &d__[1], &c__1); i__1 = *n - 1; sscal_(&i__1, &scale, &e[1], &c__1); tnrm *= scale; if (valeig) { /* If eigenvalues in interval have to be found, */ /* scale (WL, WU] accordingly */ wl *= scale; wu *= scale; } } /* Compute the desired eigenvalues of the tridiagonal after splitting */ /* into smaller subblocks if the corresponding off-diagonal elements */ /* are small */ /* THRESH is the splitting parameter for SLARRE */ /* A negative THRESH forces the old splitting criterion based on the */ /* size of the off-diagonal. A positive THRESH switches to splitting */ /* which preserves relative accuracy. */ if (*tryrac) { /* Test whether the matrix warrants the more expensive relative approach. */ slarrr_(n, &d__[1], &e[1], &iinfo); } else { /* The user does not care about relative accurately eigenvalues */ iinfo = -1; } /* Set the splitting criterion */ if (iinfo == 0) { thresh = eps; } else { thresh = -eps; /* relative accuracy is desired but T does not guarantee it */ *tryrac = FALSE_; } if (*tryrac) { /* Copy original diagonal, needed to guarantee relative accuracy */ scopy_(n, &d__[1], &c__1, &work[indd], &c__1); } /* Store the squares of the offdiagonal values of T */ i__1 = *n - 1; for (j = 1; j <= i__1; ++j) { /* Computing 2nd power */ r__1 = e[j]; work[inde2 + j - 1] = r__1 * r__1; /* L5: */ } /* Set the tolerance parameters for bisection */ if (! wantz) { /* SLARRE computes the eigenvalues to full precision. */ rtol1 = eps * 4.f; rtol2 = eps * 4.f; } else { /* SLARRE computes the eigenvalues to less than full precision. */ /* SLARRV will refine the eigenvalue approximations, and we can */ /* need less accurate initial bisection in SLARRE. */ /* Note: these settings do only affect the subset case and SLARRE */ /* Computing MAX */ r__1 = sqrt(eps) * .05f, r__2 = eps * 4.f; rtol1 = dmax(r__1,r__2); /* Computing MAX */ r__1 = sqrt(eps) * .005f, r__2 = eps * 4.f; rtol2 = dmax(r__1,r__2); } slarre_(range, n, &wl, &wu, &iil, &iiu, &d__[1], &e[1], &work[inde2], & rtol1, &rtol2, &thresh, &nsplit, &iwork[iinspl], m, &w[1], &work[ inderr], &work[indgp], &iwork[iindbl], &iwork[iindw], &work[ indgrs], &pivmin, &work[indwrk], &iwork[iindwk], &iinfo); if (iinfo != 0) { *info = abs(iinfo) + 10; return 0; } /* Note that if RANGE .NE. 'V', SLARRE computes bounds on the desired */ /* part of the spectrum. All desired eigenvalues are contained in */ /* (WL,WU] */ if (wantz) { /* Compute the desired eigenvectors corresponding to the computed */ /* eigenvalues */ slarrv_(n, &wl, &wu, &d__[1], &e[1], &pivmin, &iwork[iinspl], m, & c__1, m, &c_b18, &rtol1, &rtol2, &w[1], &work[inderr], &work[ indgp], &iwork[iindbl], &iwork[iindw], &work[indgrs], &z__[ z_offset], ldz, &isuppz[1], &work[indwrk], &iwork[iindwk], & iinfo); if (iinfo != 0) { *info = abs(iinfo) + 20; return 0; } } else { /* SLARRE computes eigenvalues of the (shifted) root representation */ /* SLARRV returns the eigenvalues of the unshifted matrix. */ /* However, if the eigenvectors are not desired by the user, we need */ /* to apply the corresponding shifts from SLARRE to obtain the */ /* eigenvalues of the original matrix. */ i__1 = *m; for (j = 1; j <= i__1; ++j) { itmp = iwork[iindbl + j - 1]; w[j] += e[iwork[iinspl + itmp - 1]]; /* L20: */ } } if (*tryrac) { /* Refine computed eigenvalues so that they are relatively accurate */ /* with respect to the original matrix T. */ ibegin = 1; wbegin = 1; i__1 = iwork[iindbl + *m - 1]; for (jblk = 1; jblk <= i__1; ++jblk) { iend = iwork[iinspl + jblk - 1]; in = iend - ibegin + 1; wend = wbegin - 1; /* check if any eigenvalues have to be refined in this block */ L36: if (wend < *m) { if (iwork[iindbl + wend] == jblk) { ++wend; goto L36; } } if (wend < wbegin) { ibegin = iend + 1; goto L39; } offset = iwork[iindw + wbegin - 1] - 1; ifirst = iwork[iindw + wbegin - 1]; ilast = iwork[iindw + wend - 1]; rtol2 = eps * 4.f; slarrj_(&in, &work[indd + ibegin - 1], &work[inde2 + ibegin - 1], &ifirst, &ilast, &rtol2, &offset, &w[wbegin], &work[ inderr + wbegin - 1], &work[indwrk], &iwork[iindwk], & pivmin, &tnrm, &iinfo); ibegin = iend + 1; wbegin = wend + 1; L39: ; } } /* If matrix was scaled, then rescale eigenvalues appropriately. */ if (scale != 1.f) { r__1 = 1.f / scale; sscal_(m, &r__1, &w[1], &c__1); } /* If eigenvalues are not in increasing order, then sort them, */ /* possibly along with eigenvectors. */ if (nsplit > 1) { if (! wantz) { slasrt_("I", m, &w[1], &iinfo); if (iinfo != 0) { *info = 3; return 0; } } else { i__1 = *m - 1; for (j = 1; j <= i__1; ++j) { i__ = 0; tmp = w[j]; i__2 = *m; for (jj = j + 1; jj <= i__2; ++jj) { if (w[jj] < tmp) { i__ = jj; tmp = w[jj]; } /* L50: */ } if (i__ != 0) { w[i__] = w[j]; w[j] = tmp; if (wantz) { sswap_(n, &z__[i__ * z_dim1 + 1], &c__1, &z__[j * z_dim1 + 1], &c__1); itmp = isuppz[(i__ << 1) - 1]; isuppz[(i__ << 1) - 1] = isuppz[(j << 1) - 1]; isuppz[(j << 1) - 1] = itmp; itmp = isuppz[i__ * 2]; isuppz[i__ * 2] = isuppz[j * 2]; isuppz[j * 2] = itmp; } } /* L60: */ } } } work[1] = (real) lwmin; iwork[1] = liwmin; return 0; /* End of SSTEMR */ } /* sstemr_ */