/* Subroutine */ int sstegr_(char *jobz, char *range, integer *n, real *d__,
real *e, real *vl, real *vu, integer *il, integer *iu, real *abstol,
integer *m, real *w, real *z__, integer *ldz, integer *isuppz, real *
work, integer *lwork, integer *iwork, integer *liwork, integer *info,
ftnlen jobz_len, ftnlen range_len)
{
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2;
real r__1, r__2;
/* Builtin functions */
double sqrt(doublereal);
/* Local variables */
static integer i__, j, jj;
static real eps, tol, tmp;
static integer iend;
static real rmin, rmax;
static integer itmp;
static real tnrm, scale;
extern logical lsame_(char *, char *, ftnlen, ftnlen);
static integer iinfo;
extern /* Subroutine */ int sscal_(integer *, real *, real *, integer *);
static integer lwmin;
extern /* Subroutine */ int sswap_(integer *, real *, integer *, real *,
integer *);
static logical wantz, alleig;
static integer ibegin;
static logical indeig;
static integer iindbl;
static logical valeig;
extern doublereal slamch_(char *, ftnlen);
static real safmin;
extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
static real bignum;
static integer iindwk, indgrs, indwof;
extern /* Subroutine */ int slarre_(integer *, real *, real *, real *,
integer *, integer *, integer *, real *, real *, real *, real *,
integer *), slaset_(char *, integer *, integer *, real *, real *,
real *, integer *, ftnlen);
static real thresh;
static integer iinspl, indwrk, liwmin;
extern doublereal slanst_(char *, integer *, real *, real *, ftnlen);
static integer nsplit;
extern /* Subroutine */ int slarrv_(integer *, real *, real *, integer *,
integer *, real *, integer *, real *, real *, real *, integer *,
integer *, real *, integer *, integer *);
static real smlnum;
static logical lquery;
/* -- LAPACK computational routine (version 3.0) -- */
/* Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., */
/* Courant Institute, Argonne National Lab, and Rice University */
/* June 30, 1999 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SSTEGR computes selected eigenvalues and, optionally, eigenvectors */
/* of a real symmetric tridiagonal matrix T. Eigenvalues and */
/* eigenvectors can be selected by specifying either a range of values */
/* or a range of indices for the desired eigenvalues. The eigenvalues */
/* are computed by the dqds algorithm, while orthogonal eigenvectors are */
/* computed from various ``good'' L D L^T representations (also known as */
/* Relatively Robust Representations). Gram-Schmidt orthogonalization is */
/* avoided as far as possible. More specifically, the various steps of */
/* the algorithm are as follows. For the i-th unreduced block of T, */
/* (a) Compute T - sigma_i = L_i D_i L_i^T, such that L_i D_i L_i^T */
/* is a relatively robust representation, */
/* (b) Compute the eigenvalues, lambda_j, of L_i D_i L_i^T to high */
/* relative accuracy by the dqds algorithm, */
/* (c) If there is a cluster of close eigenvalues, "choose" sigma_i */
/* close to the cluster, and go to step (a), */
/* (d) Given the approximate eigenvalue lambda_j of L_i D_i L_i^T, */
/* compute the corresponding eigenvector by forming a */
/* rank-revealing twisted factorization. */
/* The desired accuracy of the output can be specified by the input */
/* parameter ABSTOL. */
/* For more details, see "A new O(n^2) algorithm for the symmetric */
/* tridiagonal eigenvalue/eigenvector problem", by Inderjit Dhillon, */
/* Computer Science Division Technical Report No. UCB/CSD-97-971, */
/* UC Berkeley, May 1997. */
/* Note 1 : Currently SSTEGR is only set up to find ALL the n */
/* eigenvalues and eigenvectors of T in O(n^2) time */
/* Note 2 : Currently the routine SSTEIN is called when an appropriate */
/* sigma_i cannot be chosen in step (c) above. SSTEIN invokes modified */
/* Gram-Schmidt when eigenvalues are close. */
/* Note 3 : SSTEGR works only on machines which follow ieee-754 */
/* floating-point standard in their handling of infinities and NaNs. */
/* Normal execution of SSTEGR may create NaNs and infinities and hence */
/* may abort due to a floating point exception in environments which */
/* do not conform to the ieee standard. */
/* 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. */
/* ********* Only RANGE = 'A' is currently supported ********************* */
/* 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 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; IL = 1 and IU = 0 if N = 0. */
/* Not referenced if RANGE = 'A' or 'V'. */
/* ABSTOL (input) REAL */
/* The absolute error tolerance for the */
/* eigenvalues/eigenvectors. IF JOBZ = 'V', the eigenvalues and */
/* eigenvectors output have residual norms bounded by ABSTOL, */
/* and the dot products between different eigenvectors are */
/* bounded by ABSTOL. If ABSTOL is less than N*EPS*|T|, then */
/* N*EPS*|T| will be used in its place, where EPS is the */
/* machine precision and |T| is the 1-norm of the tridiagonal */
/* matrix. The eigenvalues are computed to an accuracy of */
/* EPS*|T| irrespective of ABSTOL. If high relative accuracy */
/* is important, set ABSTOL to DLAMCH( 'Safe minimum' ). */
/* See Barlow and Demmel "Computing Accurate Eigensystems of */
/* Scaled Diagonally Dominant Matrices", LAPACK Working Note #7 */
/* for a discussion of which matrices define their eigenvalues */
/* to high relative accuracy. */
/* 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', then if INFO = 0, 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 an upper bound must be used. */
/* 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/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 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 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 */
/* = 0: successful exit */
/* < 0: if INFO = -i, the i-th argument had an illegal value */
/* > 0: if INFO = 1, internal error in SLARRE, */
/* if INFO = 2, internal error in SLARRV. */
/* Further Details */
/* =============== */
/* Based on contributions by */
/* Inderjit Dhillon, IBM Almaden, USA */
/* Osni Marques, LBNL/NERSC, 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", (ftnlen)1, (ftnlen)1);
alleig = lsame_(range, "A", (ftnlen)1, (ftnlen)1);
valeig = lsame_(range, "V", (ftnlen)1, (ftnlen)1);
indeig = lsame_(range, "I", (ftnlen)1, (ftnlen)1);
lquery = *lwork == -1 || *liwork == -1;
lwmin = *n * 18;
liwmin = *n * 10;
*info = 0;
if (! (wantz || lsame_(jobz, "N", (ftnlen)1, (ftnlen)1))) {
*info = -1;
} else if (! (alleig || valeig || indeig)) {
*info = -2;
/* The following two lines need to be removed once the */
/* RANGE = 'V' and RANGE = 'I' options are provided. */
} else if (valeig || indeig) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (valeig && *n > 0 && *vu <= *vl) {
*info = -7;
} else if (indeig && *il < 1) {
*info = -8;
/* The following change should be made in DSTEVX also, otherwise */
/* IL can be specified as N+1 and IU as N. */
/* ELSE IF( INDEIG .AND. ( IU.LT.MIN( N, IL ) .OR. IU.GT.N ) ) THEN */
} else if (indeig && (*iu < *il || *iu > *n)) {
*info = -9;
} else if (*ldz < 1 || wantz && *ldz < *n) {
*info = -14;
} else if (*lwork < lwmin && ! lquery) {
*info = -17;
} else if (*liwork < liwmin && ! lquery) {
*info = -19;
}
if (*info == 0) {
work[1] = (real) lwmin;
iwork[1] = liwmin;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEGR", &i__1, (ftnlen)6);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
*m = 0;
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (alleig || indeig) {
*m = 1;
w[1] = d__[1];
} else {
if (*vl < d__[1] && *vu >= d__[1]) {
*m = 1;
w[1] = d__[1];
}
}
if (wantz) {
z__[z_dim1 + 1] = 1.f;
}
return 0;
}
/* Get machine constants. */
safmin = slamch_("Safe minimum", (ftnlen)12);
eps = slamch_("Precision", (ftnlen)9);
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);
/* Scale matrix to allowable range, if necessary. */
scale = 1.f;
tnrm = slanst_("M", n, &d__[1], &e[1], (ftnlen)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;
}
indgrs = 1;
indwof = (*n << 1) + 1;
indwrk = *n * 3 + 1;
iinspl = 1;
iindbl = *n + 1;
iindwk = (*n << 1) + 1;
slaset_("Full", n, n, &c_b14, &c_b14, &z__[z_offset], ldz, (ftnlen)4);
/* Compute the desired eigenvalues of the tridiagonal after splitting */
/* into smaller subblocks if the corresponding of-diagonal elements */
/* are small */
thresh = eps * tnrm;
slarre_(n, &d__[1], &e[1], &thresh, &nsplit, &iwork[iinspl], m, &w[1], &
work[indwof], &work[indgrs], &work[indwrk], &iinfo);
if (iinfo != 0) {
*info = 1;
return 0;
}
if (wantz) {
/* Compute the desired eigenvectors corresponding to the computed */
/* eigenvalues */
/* Computing MAX */
r__1 = *abstol, r__2 = (real) (*n) * thresh;
tol = dmax(r__1,r__2);
ibegin = 1;
i__1 = nsplit;
for (i__ = 1; i__ <= i__1; ++i__) {
iend = iwork[iinspl + i__ - 1];
i__2 = iend;
for (j = ibegin; j <= i__2; ++j) {
iwork[iindbl + j - 1] = i__;
/* L10: */
}
ibegin = iend + 1;
/* L20: */
}
slarrv_(n, &d__[1], &e[1], &iwork[iinspl], m, &w[1], &iwork[iindbl], &
work[indgrs], &tol, &z__[z_offset], ldz, &isuppz[1], &work[
indwrk], &iwork[iindwk], &iinfo);
if (iinfo != 0) {
*info = 2;
return 0;
}
}
ibegin = 1;
i__1 = nsplit;
for (i__ = 1; i__ <= i__1; ++i__) {
iend = iwork[iinspl + i__ - 1];
i__2 = iend;
for (j = ibegin; j <= i__2; ++j) {
w[j] += work[indwof + i__ - 1];
/* L30: */
}
ibegin = iend + 1;
/* L40: */
}
/* 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 order, then sort them, along with */
/* eigenvectors. */
if (nsplit > 1) {
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 SSTEGR */
} /* sstegr_ */
/* Subroutine */ int ssteqr_(char *compz, integer *n, real *d__, real *e,
real *z__, integer *ldz, real *work, integer *info)
{
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2;
real r__1, r__2;
/* Local variables */
real b, c__, f, g;
integer i__, j, k, l, m;
real p, r__, s;
integer l1, ii, mm, lm1, mm1, nm1;
real rt1, rt2, eps;
integer lsv;
real tst, eps2;
integer lend, jtot;
real anorm;
integer lendm1, lendp1;
integer iscale;
real safmin;
real safmax;
integer lendsv;
real ssfmin;
integer nmaxit, icompz;
real ssfmax;
/* -- LAPACK routine (version 3.2) -- */
/* November 2006 */
/* Purpose */
/* ======= */
/* SSTEQR computes all eigenvalues and, optionally, eigenvectors of a */
/* symmetric tridiagonal matrix using the implicit QL or QR method. */
/* The eigenvectors of a full or band symmetric matrix can also be found */
/* if SSYTRD or SSPTRD or SSBTRD has been used to reduce this matrix to */
/* tridiagonal form. */
/* Arguments */
/* ========= */
/* COMPZ (input) CHARACTER*1 */
/* = 'N': Compute eigenvalues only. */
/* = 'V': Compute eigenvalues and eigenvectors of the original */
/* symmetric matrix. On entry, Z must contain the */
/* orthogonal matrix used to reduce the original matrix */
/* to tridiagonal form. */
/* = 'I': Compute eigenvalues and eigenvectors of the */
/* tridiagonal matrix. Z is initialized to the identity */
/* matrix. */
/* N (input) INTEGER */
/* The order of the matrix. N >= 0. */
/* D (input/output) REAL array, dimension (N) */
/* On entry, the diagonal elements of the tridiagonal matrix. */
/* On exit, if INFO = 0, the eigenvalues in ascending order. */
/* E (input/output) REAL array, dimension (N-1) */
/* On entry, the (n-1) subdiagonal elements of the tridiagonal */
/* matrix. */
/* On exit, E has been destroyed. */
/* Z (input/output) REAL array, dimension (LDZ, N) */
/* On entry, if COMPZ = 'V', then Z contains the orthogonal */
/* matrix used in the reduction to tridiagonal form. */
/* On exit, if INFO = 0, then if COMPZ = 'V', Z contains the */
/* orthonormal eigenvectors of the original symmetric matrix, */
/* and if COMPZ = 'I', Z contains the orthonormal eigenvectors */
/* of the symmetric tridiagonal matrix. */
/* If COMPZ = 'N', then Z is not referenced. */
/* LDZ (input) INTEGER */
/* The leading dimension of the array Z. LDZ >= 1, and if */
/* eigenvectors are desired, then LDZ >= max(1,N). */
/* WORK (workspace) REAL array, dimension (max(1,2*N-2)) */
/* If COMPZ = 'N', then WORK is not referenced. */
/* INFO (output) INTEGER */
/* = 0: successful exit */
/* < 0: if INFO = -i, the i-th argument had an illegal value */
/* > 0: the algorithm has failed to find all the eigenvalues in */
/* a total of 30*N iterations; if INFO = i, then i */
/* elements of E have not converged to zero; on exit, D */
/* and E contain the elements of a symmetric tridiagonal */
/* matrix which is orthogonally similar to the original */
/* matrix. */
/* ===================================================================== */
/* Test the input parameters. */
/* Parameter adjustments */
--d__;
--e;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--work;
/* Function Body */
*info = 0;
if (lsame_(compz, "N")) {
icompz = 0;
} else if (lsame_(compz, "V")) {
icompz = 1;
} else if (lsame_(compz, "I")) {
icompz = 2;
} else {
icompz = -1;
}
if (icompz < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*ldz < 1 || icompz > 0 && *ldz < max(1,*n)) {
*info = -6;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEQR", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (icompz == 2) {
z__[z_dim1 + 1] = 1.f;
}
return 0;
}
/* Determine the unit roundoff and over/underflow thresholds. */
eps = slamch_("E");
/* Computing 2nd power */
r__1 = eps;
eps2 = r__1 * r__1;
safmin = slamch_("S");
safmax = 1.f / safmin;
ssfmax = sqrt(safmax) / 3.f;
ssfmin = sqrt(safmin) / eps2;
/* Compute the eigenvalues and eigenvectors of the tridiagonal */
/* matrix. */
if (icompz == 2) {
slaset_("Full", n, n, &c_b9, &c_b10, &z__[z_offset], ldz);
}
nmaxit = *n * 30;
jtot = 0;
/* Determine where the matrix splits and choose QL or QR iteration */
/* for each block, according to whether top or bottom diagonal */
/* element is smaller. */
l1 = 1;
nm1 = *n - 1;
L10:
if (l1 > *n) {
goto L160;
}
if (l1 > 1) {
e[l1 - 1] = 0.f;
}
if (l1 <= nm1) {
i__1 = nm1;
for (m = l1; m <= i__1; ++m) {
tst = (r__1 = e[m], dabs(r__1));
if (tst == 0.f) {
goto L30;
}
if (tst <= sqrt((r__1 = d__[m], dabs(r__1))) * sqrt((r__2 = d__[m
+ 1], dabs(r__2))) * eps) {
e[m] = 0.f;
goto L30;
}
}
}
m = *n;
L30:
l = l1;
lsv = l;
lend = m;
lendsv = lend;
l1 = m + 1;
if (lend == l) {
goto L10;
}
/* Scale submatrix in rows and columns L to LEND */
i__1 = lend - l + 1;
anorm = slanst_("I", &i__1, &d__[l], &e[l]);
iscale = 0;
if (anorm == 0.f) {
goto L10;
}
if (anorm > ssfmax) {
iscale = 1;
i__1 = lend - l + 1;
slascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &d__[l], n,
info);
i__1 = lend - l;
slascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &e[l], n,
info);
} else if (anorm < ssfmin) {
iscale = 2;
i__1 = lend - l + 1;
slascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &d__[l], n,
info);
i__1 = lend - l;
slascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &e[l], n,
info);
}
/* Choose between QL and QR iteration */
if ((r__1 = d__[lend], dabs(r__1)) < (r__2 = d__[l], dabs(r__2))) {
lend = lsv;
l = lendsv;
}
if (lend > l) {
/* QL Iteration */
/* Look for small subdiagonal element. */
L40:
if (l != lend) {
lendm1 = lend - 1;
i__1 = lendm1;
for (m = l; m <= i__1; ++m) {
/* Computing 2nd power */
r__2 = (r__1 = e[m], dabs(r__1));
tst = r__2 * r__2;
if (tst <= eps2 * (r__1 = d__[m], dabs(r__1)) * (r__2 = d__[m
+ 1], dabs(r__2)) + safmin) {
goto L60;
}
}
}
m = lend;
L60:
if (m < lend) {
e[m] = 0.f;
}
p = d__[l];
if (m == l) {
goto L80;
}
/* If remaining matrix is 2-by-2, use SLAE2 or SLAEV2 */
/* to compute its eigensystem. */
if (m == l + 1) {
if (icompz > 0) {
slaev2_(&d__[l], &e[l], &d__[l + 1], &rt1, &rt2, &c__, &s);
work[l] = c__;
work[*n - 1 + l] = s;
slasr_("R", "V", "B", n, &c__2, &work[l], &work[*n - 1 + l], &
z__[l * z_dim1 + 1], ldz);
} else {
slae2_(&d__[l], &e[l], &d__[l + 1], &rt1, &rt2);
}
d__[l] = rt1;
d__[l + 1] = rt2;
e[l] = 0.f;
l += 2;
if (l <= lend) {
goto L40;
}
goto L140;
}
if (jtot == nmaxit) {
goto L140;
}
++jtot;
/* Form shift. */
g = (d__[l + 1] - p) / (e[l] * 2.f);
r__ = slapy2_(&g, &c_b10);
g = d__[m] - p + e[l] / (g + r_sign(&r__, &g));
s = 1.f;
c__ = 1.f;
p = 0.f;
/* Inner loop */
mm1 = m - 1;
i__1 = l;
for (i__ = mm1; i__ >= i__1; --i__) {
f = s * e[i__];
b = c__ * e[i__];
slartg_(&g, &f, &c__, &s, &r__);
if (i__ != m - 1) {
e[i__ + 1] = r__;
}
g = d__[i__ + 1] - p;
r__ = (d__[i__] - g) * s + c__ * 2.f * b;
p = s * r__;
d__[i__ + 1] = g + p;
g = c__ * r__ - b;
/* If eigenvectors are desired, then save rotations. */
if (icompz > 0) {
work[i__] = c__;
work[*n - 1 + i__] = -s;
}
}
/* If eigenvectors are desired, then apply saved rotations. */
if (icompz > 0) {
mm = m - l + 1;
slasr_("R", "V", "B", n, &mm, &work[l], &work[*n - 1 + l], &z__[l
* z_dim1 + 1], ldz);
}
d__[l] -= p;
e[l] = g;
goto L40;
/* Eigenvalue found. */
L80:
d__[l] = p;
++l;
if (l <= lend) {
goto L40;
}
goto L140;
} else {
/* QR Iteration */
/* Look for small superdiagonal element. */
L90:
if (l != lend) {
lendp1 = lend + 1;
i__1 = lendp1;
for (m = l; m >= i__1; --m) {
/* Computing 2nd power */
r__2 = (r__1 = e[m - 1], dabs(r__1));
tst = r__2 * r__2;
if (tst <= eps2 * (r__1 = d__[m], dabs(r__1)) * (r__2 = d__[m
- 1], dabs(r__2)) + safmin) {
goto L110;
}
}
}
m = lend;
L110:
if (m > lend) {
e[m - 1] = 0.f;
}
p = d__[l];
if (m == l) {
goto L130;
}
/* If remaining matrix is 2-by-2, use SLAE2 or SLAEV2 */
/* to compute its eigensystem. */
if (m == l - 1) {
if (icompz > 0) {
slaev2_(&d__[l - 1], &e[l - 1], &d__[l], &rt1, &rt2, &c__, &s)
;
work[m] = c__;
work[*n - 1 + m] = s;
slasr_("R", "V", "F", n, &c__2, &work[m], &work[*n - 1 + m], &
z__[(l - 1) * z_dim1 + 1], ldz);
} else {
slae2_(&d__[l - 1], &e[l - 1], &d__[l], &rt1, &rt2);
}
d__[l - 1] = rt1;
d__[l] = rt2;
e[l - 1] = 0.f;
l += -2;
if (l >= lend) {
goto L90;
}
goto L140;
}
if (jtot == nmaxit) {
goto L140;
}
++jtot;
/* Form shift. */
g = (d__[l - 1] - p) / (e[l - 1] * 2.f);
r__ = slapy2_(&g, &c_b10);
g = d__[m] - p + e[l - 1] / (g + r_sign(&r__, &g));
s = 1.f;
c__ = 1.f;
p = 0.f;
/* Inner loop */
lm1 = l - 1;
i__1 = lm1;
for (i__ = m; i__ <= i__1; ++i__) {
f = s * e[i__];
b = c__ * e[i__];
slartg_(&g, &f, &c__, &s, &r__);
if (i__ != m) {
e[i__ - 1] = r__;
}
g = d__[i__] - p;
r__ = (d__[i__ + 1] - g) * s + c__ * 2.f * b;
p = s * r__;
d__[i__] = g + p;
g = c__ * r__ - b;
/* If eigenvectors are desired, then save rotations. */
if (icompz > 0) {
work[i__] = c__;
work[*n - 1 + i__] = s;
}
}
/* If eigenvectors are desired, then apply saved rotations. */
if (icompz > 0) {
mm = l - m + 1;
slasr_("R", "V", "F", n, &mm, &work[m], &work[*n - 1 + m], &z__[m
* z_dim1 + 1], ldz);
}
d__[l] -= p;
e[lm1] = g;
goto L90;
/* Eigenvalue found. */
L130:
d__[l] = p;
--l;
if (l >= lend) {
goto L90;
}
goto L140;
}
/* Undo scaling if necessary */
L140:
if (iscale == 1) {
i__1 = lendsv - lsv + 1;
slascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &d__[lsv],
n, info);
i__1 = lendsv - lsv;
slascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &e[lsv], n,
info);
} else if (iscale == 2) {
i__1 = lendsv - lsv + 1;
slascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &d__[lsv],
n, info);
i__1 = lendsv - lsv;
slascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &e[lsv], n,
info);
}
/* Check for no convergence to an eigenvalue after a total */
/* of N*MAXIT iterations. */
if (jtot < nmaxit) {
goto L10;
}
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
if (e[i__] != 0.f) {
++(*info);
}
}
goto L190;
/* Order eigenvalues and eigenvectors. */
L160:
if (icompz == 0) {
/* Use Quick Sort */
slasrt_("I", n, &d__[1], info);
} else {
/* Use Selection Sort to minimize swaps of eigenvectors */
i__1 = *n;
for (ii = 2; ii <= i__1; ++ii) {
i__ = ii - 1;
k = i__;
p = d__[i__];
i__2 = *n;
for (j = ii; j <= i__2; ++j) {
if (d__[j] < p) {
k = j;
p = d__[j];
}
}
if (k != i__) {
d__[k] = d__[i__];
d__[i__] = p;
sswap_(n, &z__[i__ * z_dim1 + 1], &c__1, &z__[k * z_dim1 + 1],
&c__1);
}
}
}
L190:
return 0;
/* End of SSTEQR */
} /* ssteqr_ */
/* 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 3.1) -- */
/* 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;
*tryrac = *info != 0;
/* 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_ */
/* Subroutine */ int slalsd_(char *uplo, integer *smlsiz, integer *n, integer
*nrhs, real *d__, real *e, real *b, integer *ldb, real *rcond,
integer *rank, real *work, integer *iwork, integer *info)
{
/* System generated locals */
integer b_dim1, b_offset, i__1, i__2;
real r__1;
/* Builtin functions */
double log(doublereal), r_sign(real *, real *);
/* Local variables */
static integer difl, difr, perm, nsub, nlvl, sqre, bxst;
extern /* Subroutine */ int srot_(integer *, real *, integer *, real *,
integer *, real *, real *);
static integer c__, i__, j, k;
static real r__;
static integer s, u, z__;
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
static integer poles, sizei, nsize;
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *);
static integer nwork, icmpq1, icmpq2;
extern doublereal sopbl3_(char *, integer *, integer *, integer *)
;
static real cs;
static integer bx;
static real sn;
static integer st;
extern /* Subroutine */ int slasda_(integer *, integer *, integer *,
integer *, real *, real *, real *, integer *, real *, integer *,
real *, real *, real *, real *, integer *, integer *, integer *,
integer *, real *, real *, real *, real *, integer *, integer *);
extern doublereal slamch_(char *);
static integer vt;
extern /* Subroutine */ int xerbla_(char *, integer *), slalsa_(
integer *, integer *, integer *, integer *, real *, integer *,
real *, integer *, real *, integer *, real *, integer *, real *,
real *, real *, real *, integer *, integer *, integer *, integer *
, real *, real *, real *, real *, integer *, integer *), slascl_(
char *, integer *, integer *, real *, real *, integer *, integer *
, real *, integer *, integer *);
static integer givcol;
extern integer isamax_(integer *, real *, integer *);
extern /* Subroutine */ int slasdq_(char *, integer *, integer *, integer
*, integer *, integer *, real *, real *, real *, integer *, real *
, integer *, real *, integer *, real *, integer *),
slacpy_(char *, integer *, integer *, real *, integer *, real *,
integer *), slartg_(real *, real *, real *, real *, real *
), slaset_(char *, integer *, integer *, real *, real *, real *,
integer *);
static real orgnrm;
static integer givnum;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int slasrt_(char *, integer *, real *, integer *);
static integer givptr, nm1, smlszp, st1;
static real eps;
static integer iwk;
static real tol;
#define b_ref(a_1,a_2) b[(a_2)*b_dim1 + a_1]
/* -- LAPACK routine (instrumented to count ops, version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
October 31, 1999
Purpose
=======
SLALSD uses the singular value decomposition of A to solve the least
squares problem of finding X to minimize the Euclidean norm of each
column of A*X-B, where A is N-by-N upper bidiagonal, and X and B
are N-by-NRHS. The solution X overwrites B.
The singular values of A smaller than RCOND times the largest
singular value are treated as zero in solving the least squares
problem; in this case a minimum norm solution is returned.
The actual singular values are returned in D in ascending order.
This code makes very mild assumptions about floating point
arithmetic. It will work on machines with a guard digit in
add/subtract, or on those binary machines without guard digits
which subtract like the Cray XMP, Cray YMP, Cray C 90, or Cray 2.
It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': D and E define an upper bidiagonal matrix.
= 'L': D and E define a lower bidiagonal matrix.
SMLSIZ (input) INTEGER
The maximum size of the subproblems at the bottom of the
computation tree.
N (input) INTEGER
The dimension of the bidiagonal matrix. N >= 0.
NRHS (input) INTEGER
The number of columns of B. NRHS must be at least 1.
D (input/output) REAL array, dimension (N)
On entry D contains the main diagonal of the bidiagonal
matrix. On exit, if INFO = 0, D contains its singular values.
E (input) REAL array, dimension (N-1)
Contains the super-diagonal entries of the bidiagonal matrix.
On exit, E has been destroyed.
B (input/output) REAL array, dimension (LDB,NRHS)
On input, B contains the right hand sides of the least
squares problem. On output, B contains the solution X.
LDB (input) INTEGER
The leading dimension of B in the calling subprogram.
LDB must be at least max(1,N).
RCOND (input) REAL
The singular values of A less than or equal to RCOND times
the largest singular value are treated as zero in solving
the least squares problem. If RCOND is negative,
machine precision is used instead.
For example, if diag(S)*X=B were the least squares problem,
where diag(S) is a diagonal matrix of singular values, the
solution would be X(i) = B(i) / S(i) if S(i) is greater than
RCOND*max(S), and X(i) = 0 if S(i) is less than or equal to
RCOND*max(S).
RANK (output) INTEGER
The number of singular values of A greater than RCOND times
the largest singular value.
WORK (workspace) REAL array, dimension at least
(9*N + 2*N*SMLSIZ + 8*N*NLVL + N*NRHS + (SMLSIZ+1)**2),
where NLVL = max(0, INT(log_2 (N/(SMLSIZ+1))) + 1).
IWORK (workspace) INTEGER array, dimension at least
(3 * N * NLVL + 11 * N)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: The algorithm failed to compute an singular value while
working on the submatrix lying in rows and columns
INFO/(N+1) through MOD(INFO,N+1).
=====================================================================
Test the input parameters.
Parameter adjustments */
--d__;
--e;
b_dim1 = *ldb;
b_offset = 1 + b_dim1 * 1;
b -= b_offset;
--work;
--iwork;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -3;
} else if (*nrhs < 1) {
*info = -4;
} else if (*ldb < 1 || *ldb < *n) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SLALSD", &i__1);
return 0;
}
eps = slamch_("Epsilon");
/* Set up the tolerance. */
if (*rcond <= 0.f || *rcond >= 1.f) {
*rcond = eps;
}
*rank = 0;
/* Quick return if possible. */
if (*n == 0) {
return 0;
} else if (*n == 1) {
if (d__[1] == 0.f) {
slaset_("A", &c__1, nrhs, &c_b6, &c_b6, &b[b_offset], ldb);
} else {
*rank = 1;
latime_1.ops += (real) (*nrhs << 1);
slascl_("G", &c__0, &c__0, &d__[1], &c_b11, &c__1, nrhs, &b[
b_offset], ldb, info);
d__[1] = dabs(d__[1]);
}
return 0;
}
/* Rotate the matrix if it is lower bidiagonal. */
if (*(unsigned char *)uplo == 'L') {
latime_1.ops += (real) ((*n - 1) * 6);
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
slartg_(&d__[i__], &e[i__], &cs, &sn, &r__);
d__[i__] = r__;
e[i__] = sn * d__[i__ + 1];
d__[i__ + 1] = cs * d__[i__ + 1];
if (*nrhs == 1) {
latime_1.ops += 6.f;
srot_(&c__1, &b_ref(i__, 1), &c__1, &b_ref(i__ + 1, 1), &c__1,
&cs, &sn);
} else {
work[(i__ << 1) - 1] = cs;
work[i__ * 2] = sn;
}
/* L10: */
}
if (*nrhs > 1) {
latime_1.ops += (real) ((*n - 1) * 6 * *nrhs);
i__1 = *nrhs;
for (i__ = 1; i__ <= i__1; ++i__) {
i__2 = *n - 1;
for (j = 1; j <= i__2; ++j) {
cs = work[(j << 1) - 1];
sn = work[j * 2];
srot_(&c__1, &b_ref(j, i__), &c__1, &b_ref(j + 1, i__), &
c__1, &cs, &sn);
/* L20: */
}
/* L30: */
}
}
}
/* Scale. */
nm1 = *n - 1;
orgnrm = slanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.f) {
slaset_("A", n, nrhs, &c_b6, &c_b6, &b[b_offset], ldb);
return 0;
}
latime_1.ops += (real) (*n + nm1);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b11, n, &c__1, &d__[1], n, info);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b11, &nm1, &c__1, &e[1], &nm1,
info);
/* If N is smaller than the minimum divide size SMLSIZ, then solve
the problem with another solver. */
if (*n <= *smlsiz) {
nwork = *n * *n + 1;
slaset_("A", n, n, &c_b6, &c_b11, &work[1], n);
slasdq_("U", &c__0, n, n, &c__0, nrhs, &d__[1], &e[1], &work[1], n, &
work[1], n, &b[b_offset], ldb, &work[nwork], info);
if (*info != 0) {
return 0;
}
latime_1.ops += 1.f;
tol = *rcond * (r__1 = d__[isamax_(n, &d__[1], &c__1)], dabs(r__1));
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if (d__[i__] <= tol) {
slaset_("A", &c__1, nrhs, &c_b6, &c_b6, &b_ref(i__, 1), ldb);
} else {
latime_1.ops += (real) (*nrhs);
slascl_("G", &c__0, &c__0, &d__[i__], &c_b11, &c__1, nrhs, &
b_ref(i__, 1), ldb, info);
++(*rank);
}
/* L40: */
}
latime_1.ops += sopbl3_("SGEMM ", n, nrhs, n);
sgemm_("T", "N", n, nrhs, n, &c_b11, &work[1], n, &b[b_offset], ldb, &
c_b6, &work[nwork], n);
slacpy_("A", n, nrhs, &work[nwork], n, &b[b_offset], ldb);
/* Unscale. */
latime_1.ops += (real) (*n + *n * *nrhs);
slascl_("G", &c__0, &c__0, &c_b11, &orgnrm, n, &c__1, &d__[1], n,
info);
slasrt_("D", n, &d__[1], info);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b11, n, nrhs, &b[b_offset],
ldb, info);
return 0;
}
/* Book-keeping and setting up some constants. */
nlvl = (integer) (log((real) (*n) / (real) (*smlsiz + 1)) / log(2.f)) + 1;
smlszp = *smlsiz + 1;
u = 1;
vt = *smlsiz * *n + 1;
difl = vt + smlszp * *n;
difr = difl + nlvl * *n;
z__ = difr + (nlvl * *n << 1);
c__ = z__ + nlvl * *n;
s = c__ + *n;
poles = s + *n;
givnum = poles + (nlvl << 1) * *n;
bx = givnum + (nlvl << 1) * *n;
nwork = bx + *n * *nrhs;
sizei = *n + 1;
k = sizei + *n;
givptr = k + *n;
perm = givptr + *n;
givcol = perm + nlvl * *n;
iwk = givcol + (nlvl * *n << 1);
st = 1;
sqre = 0;
icmpq1 = 1;
icmpq2 = 0;
nsub = 0;
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = d__[i__], dabs(r__1)) < eps) {
d__[i__] = r_sign(&eps, &d__[i__]);
}
/* L50: */
}
i__1 = nm1;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = e[i__], dabs(r__1)) < eps || i__ == nm1) {
++nsub;
iwork[nsub] = st;
/* Subproblem found. First determine its size and then
apply divide and conquer on it. */
if (i__ < nm1) {
/* A subproblem with E(I) small for I < NM1. */
nsize = i__ - st + 1;
iwork[sizei + nsub - 1] = nsize;
} else if ((r__1 = e[i__], dabs(r__1)) >= eps) {
/* A subproblem with E(NM1) not too small but I = NM1. */
nsize = *n - st + 1;
iwork[sizei + nsub - 1] = nsize;
} else {
/* A subproblem with E(NM1) small. This implies an
1-by-1 subproblem at D(N), which is not solved
explicitly. */
nsize = i__ - st + 1;
iwork[sizei + nsub - 1] = nsize;
++nsub;
iwork[nsub] = *n;
iwork[sizei + nsub - 1] = 1;
scopy_(nrhs, &b_ref(*n, 1), ldb, &work[bx + nm1], n);
}
st1 = st - 1;
if (nsize == 1) {
/* This is a 1-by-1 subproblem and is not solved
explicitly. */
scopy_(nrhs, &b_ref(st, 1), ldb, &work[bx + st1], n);
} else if (nsize <= *smlsiz) {
/* This is a small subproblem and is solved by SLASDQ. */
slaset_("A", &nsize, &nsize, &c_b6, &c_b11, &work[vt + st1],
n);
slasdq_("U", &c__0, &nsize, &nsize, &c__0, nrhs, &d__[st], &e[
st], &work[vt + st1], n, &work[nwork], n, &b_ref(st,
1), ldb, &work[nwork], info);
if (*info != 0) {
return 0;
}
slacpy_("A", &nsize, nrhs, &b_ref(st, 1), ldb, &work[bx + st1]
, n);
} else {
/* A large problem. Solve it using divide and conquer. */
slasda_(&icmpq1, smlsiz, &nsize, &sqre, &d__[st], &e[st], &
work[u + st1], n, &work[vt + st1], &iwork[k + st1], &
work[difl + st1], &work[difr + st1], &work[z__ + st1],
&work[poles + st1], &iwork[givptr + st1], &iwork[
givcol + st1], n, &iwork[perm + st1], &work[givnum +
st1], &work[c__ + st1], &work[s + st1], &work[nwork],
&iwork[iwk], info);
if (*info != 0) {
return 0;
}
bxst = bx + st1;
slalsa_(&icmpq2, smlsiz, &nsize, nrhs, &b_ref(st, 1), ldb, &
work[bxst], n, &work[u + st1], n, &work[vt + st1], &
iwork[k + st1], &work[difl + st1], &work[difr + st1],
&work[z__ + st1], &work[poles + st1], &iwork[givptr +
st1], &iwork[givcol + st1], n, &iwork[perm + st1], &
work[givnum + st1], &work[c__ + st1], &work[s + st1],
&work[nwork], &iwork[iwk], info);
if (*info != 0) {
return 0;
}
}
st = i__ + 1;
}
/* L60: */
}
/* Apply the singular values and treat the tiny ones as zero. */
tol = *rcond * (r__1 = d__[isamax_(n, &d__[1], &c__1)], dabs(r__1));
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Some of the elements in D can be negative because 1-by-1
subproblems were not solved explicitly. */
if ((r__1 = d__[i__], dabs(r__1)) <= tol) {
slaset_("A", &c__1, nrhs, &c_b6, &c_b6, &work[bx + i__ - 1], n);
} else {
++(*rank);
latime_1.ops += (real) (*nrhs);
slascl_("G", &c__0, &c__0, &d__[i__], &c_b11, &c__1, nrhs, &work[
bx + i__ - 1], n, info);
}
d__[i__] = (r__1 = d__[i__], dabs(r__1));
/* L70: */
}
/* Now apply back the right singular vectors. */
icmpq2 = 1;
i__1 = nsub;
for (i__ = 1; i__ <= i__1; ++i__) {
st = iwork[i__];
st1 = st - 1;
nsize = iwork[sizei + i__ - 1];
bxst = bx + st1;
if (nsize == 1) {
scopy_(nrhs, &work[bxst], n, &b_ref(st, 1), ldb);
} else if (nsize <= *smlsiz) {
latime_1.ops += sopbl3_("SGEMM ", &nsize, nrhs, &nsize)
;
sgemm_("T", "N", &nsize, nrhs, &nsize, &c_b11, &work[vt + st1], n,
&work[bxst], n, &c_b6, &b_ref(st, 1), ldb);
} else {
slalsa_(&icmpq2, smlsiz, &nsize, nrhs, &work[bxst], n, &b_ref(st,
1), ldb, &work[u + st1], n, &work[vt + st1], &iwork[k +
st1], &work[difl + st1], &work[difr + st1], &work[z__ +
st1], &work[poles + st1], &iwork[givptr + st1], &iwork[
givcol + st1], n, &iwork[perm + st1], &work[givnum + st1],
&work[c__ + st1], &work[s + st1], &work[nwork], &iwork[
iwk], info);
if (*info != 0) {
return 0;
}
}
/* L80: */
}
/* Unscale and sort the singular values. */
latime_1.ops += (real) (*n + *n * *nrhs);
slascl_("G", &c__0, &c__0, &c_b11, &orgnrm, n, &c__1, &d__[1], n, info);
slasrt_("D", n, &d__[1], info);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b11, n, nrhs, &b[b_offset], ldb,
info);
return 0;
/* End of SLALSD */
} /* slalsd_ */
int sstev_(char *jobz, int *n, float *d__, float *e, float *
z__, int *ldz, float *work, int *info)
{
/* System generated locals */
int z_dim1, z_offset, i__1;
float r__1;
/* Builtin functions */
double sqrt(double);
/* Local variables */
float eps;
int imax;
float rmin, rmax, tnrm, sigma;
extern int lsame_(char *, char *);
extern int sscal_(int *, float *, float *, int *);
int wantz;
int iscale;
extern double slamch_(char *);
float safmin;
extern int xerbla_(char *, int *);
float bignum;
extern double slanst_(char *, int *, float *, float *);
extern int ssterf_(int *, float *, float *, int *);
float smlnum;
extern int ssteqr_(char *, int *, float *, float *,
float *, int *, float *, int *);
/* -- LAPACK driver routine (version 3.2) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SSTEV computes all eigenvalues and, optionally, eigenvectors of a */
/* float symmetric tridiagonal matrix A. */
/* Arguments */
/* ========= */
/* JOBZ (input) CHARACTER*1 */
/* = 'N': Compute eigenvalues only; */
/* = 'V': Compute eigenvalues and eigenvectors. */
/* 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 */
/* A. */
/* On exit, if INFO = 0, the eigenvalues in ascending order. */
/* E (input/output) REAL array, dimension (N-1) */
/* On entry, the (n-1) subdiagonal elements of the tridiagonal */
/* matrix A, stored in elements 1 to N-1 of E. */
/* On exit, the contents of E are destroyed. */
/* Z (output) REAL array, dimension (LDZ, N) */
/* If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal */
/* eigenvectors of the matrix A, with the i-th column of Z */
/* holding the eigenvector associated with D(i). */
/* If JOBZ = 'N', then Z is not referenced. */
/* LDZ (input) INTEGER */
/* The leading dimension of the array Z. LDZ >= 1, and if */
/* JOBZ = 'V', LDZ >= MAX(1,N). */
/* WORK (workspace) REAL array, dimension (MAX(1,2*N-2)) */
/* If JOBZ = 'N', WORK is not referenced. */
/* INFO (output) INTEGER */
/* = 0: successful exit */
/* < 0: if INFO = -i, the i-th argument had an illegal value */
/* > 0: if INFO = i, the algorithm failed to converge; i */
/* off-diagonal elements of E did not converge to zero. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
--d__;
--e;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--work;
/* Function Body */
wantz = lsame_(jobz, "V");
*info = 0;
if (! (wantz || lsame_(jobz, "N"))) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*ldz < 1 || wantz && *ldz < *n) {
*info = -6;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEV ", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (wantz) {
z__[z_dim1 + 1] = 1.f;
}
return 0;
}
/* Get machine constants. */
safmin = slamch_("Safe minimum");
eps = slamch_("Precision");
smlnum = safmin / eps;
bignum = 1.f / smlnum;
rmin = sqrt(smlnum);
rmax = sqrt(bignum);
/* Scale matrix to allowable range, if necessary. */
iscale = 0;
tnrm = slanst_("M", n, &d__[1], &e[1]);
if (tnrm > 0.f && tnrm < rmin) {
iscale = 1;
sigma = rmin / tnrm;
} else if (tnrm > rmax) {
iscale = 1;
sigma = rmax / tnrm;
}
if (iscale == 1) {
sscal_(n, &sigma, &d__[1], &c__1);
i__1 = *n - 1;
sscal_(&i__1, &sigma, &e[1], &c__1);
}
/* For eigenvalues only, call SSTERF. For eigenvalues and */
/* eigenvectors, call SSTEQR. */
if (! wantz) {
ssterf_(n, &d__[1], &e[1], info);
} else {
ssteqr_("I", n, &d__[1], &e[1], &z__[z_offset], ldz, &work[1], info);
}
/* If matrix was scaled, then rescale eigenvalues appropriately. */
if (iscale == 1) {
if (*info == 0) {
imax = *n;
} else {
imax = *info - 1;
}
r__1 = 1.f / sigma;
sscal_(&imax, &r__1, &d__[1], &c__1);
}
return 0;
/* End of SSTEV */
} /* sstev_ */
/* Subroutine */ int sstevx_(char *jobz, char *range, integer *n, real *d,
real *e, real *vl, real *vu, integer *il, integer *iu, real *abstol,
integer *m, real *w, real *z, integer *ldz, real *work, integer *
iwork, integer *ifail, integer *info)
{
/* -- LAPACK driver routine (version 2.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
September 30, 1994
Purpose
=======
SSTEVX computes selected eigenvalues and, optionally, eigenvectors
of a real symmetric tridiagonal matrix A. Eigenvalues and
eigenvectors can be selected by specifying either a range of values
or a range of indices for the desired eigenvalues.
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
A.
On exit, D may be multiplied by a constant factor chosen
to avoid over/underflow in computing the eigenvalues.
E (input/output) REAL array, dimension (N)
On entry, the (n-1) subdiagonal elements of the tridiagonal
matrix A in elements 1 to N-1 of E; E(N) need not be set.
On exit, E may be multiplied by a constant factor chosen
to avoid over/underflow in computing the eigenvalues.
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; IL = 1 and IU = 0 if N = 0.
Not referenced if RANGE = 'A' or 'V'.
ABSTOL (input) REAL
The absolute error tolerance for the eigenvalues.
An approximate eigenvalue is accepted as converged
when it is determined to lie in an interval [a,b]
of width less than or equal to
ABSTOL + EPS * max( |a|,|b| ) ,
where EPS is the machine precision. If ABSTOL is less
than or equal to zero, then EPS*|T| will be used in
its place, where |T| is the 1-norm of the tridiagonal
matrix.
Eigenvalues will be computed most accurately when ABSTOL is
set to twice the underflow threshold 2*SLAMCH('S'), not zero.
If this routine returns with INFO>0, indicating that some
eigenvectors did not converge, try setting ABSTOL to
2*SLAMCH('S').
See "Computing Small Singular Values of Bidiagonal Matrices
with Guaranteed High Relative Accuracy," by Demmel and
Kahan, LAPACK Working Note #3.
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', then if INFO = 0, the first M columns of Z
contain the orthonormal eigenvectors of the matrix A
corresponding to the selected eigenvalues, with the i-th
column of Z holding the eigenvector associated with W(i).
If an eigenvector fails to converge (INFO > 0), then that
column of Z contains the latest approximation to the
eigenvector, and the index of the eigenvector is returned
in IFAIL. 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 an upper bound must be used.
LDZ (input) INTEGER
The leading dimension of the array Z. LDZ >= 1, and if
JOBZ = 'V', LDZ >= max(1,N).
WORK (workspace) REAL array, dimension (5*N)
IWORK (workspace) INTEGER array, dimension (5*N)
IFAIL (output) INTEGER array, dimension (N)
If JOBZ = 'V', then if INFO = 0, the first M elements of
IFAIL are zero. If INFO > 0, then IFAIL contains the
indices of the eigenvectors that failed to converge.
If JOBZ = 'N', then IFAIL is not referenced.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, then i eigenvectors failed to converge.
Their indices are stored in array IFAIL.
=====================================================================
Test the input parameters.
Parameter adjustments
Function Body */
/* Table of constant values */
static integer c__1 = 1;
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2;
real r__1, r__2;
/* Builtin functions */
double sqrt(doublereal);
/* Local variables */
static integer imax;
static real rmin, rmax, tnrm;
static integer itmp1, i, j;
static real sigma;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int sscal_(integer *, real *, real *, integer *);
static char order[1];
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *), sswap_(integer *, real *, integer *, real *, integer *
);
static logical wantz;
static integer jj;
static logical alleig, indeig;
static integer iscale, indibl;
static logical valeig;
extern doublereal slamch_(char *);
static real safmin;
extern /* Subroutine */ int xerbla_(char *, integer *);
static real bignum;
static integer indisp, indiwo, indwrk;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int sstein_(integer *, real *, real *, integer *,
real *, integer *, integer *, real *, integer *, real *, integer *
, integer *, integer *), ssterf_(integer *, real *, real *,
integer *);
static integer nsplit;
extern /* Subroutine */ int sstebz_(char *, char *, integer *, real *,
real *, integer *, integer *, real *, real *, real *, integer *,
integer *, real *, integer *, integer *, real *, integer *,
integer *);
static real smlnum;
extern /* Subroutine */ int ssteqr_(char *, integer *, real *, real *,
real *, integer *, real *, integer *);
static real eps, vll, vuu, tmp1;
#define D(I) d[(I)-1]
#define E(I) e[(I)-1]
#define W(I) w[(I)-1]
#define WORK(I) work[(I)-1]
#define IWORK(I) iwork[(I)-1]
#define IFAIL(I) ifail[(I)-1]
#define Z(I,J) z[(I)-1 + ((J)-1)* ( *ldz)]
wantz = lsame_(jobz, "V");
alleig = lsame_(range, "A");
valeig = lsame_(range, "V");
indeig = lsame_(range, "I");
*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 && *vu <= *vl) {
*info = -7;
} else if (indeig && *il < 1) {
*info = -8;
} else if (indeig && (*iu < min(*n,*il) || *iu > *n)) {
*info = -9;
} else if (*ldz < 1 || wantz && *ldz < *n) {
*info = -14;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEVX", &i__1);
return 0;
}
/* Quick return if possible */
*m = 0;
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (alleig || indeig) {
*m = 1;
W(1) = D(1);
} else {
if (*vl < D(1) && *vu >= D(1)) {
*m = 1;
W(1) = D(1);
}
}
if (wantz) {
Z(1,1) = 1.f;
}
return 0;
}
/* 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);
/* Scale matrix to allowable range, if necessary. */
iscale = 0;
if (valeig) {
vll = *vl;
vuu = *vu;
}
tnrm = slanst_("M", n, &D(1), &E(1));
if (tnrm > 0.f && tnrm < rmin) {
iscale = 1;
sigma = rmin / tnrm;
} else if (tnrm > rmax) {
iscale = 1;
sigma = rmax / tnrm;
}
if (iscale == 1) {
sscal_(n, &sigma, &D(1), &c__1);
i__1 = *n - 1;
sscal_(&i__1, &sigma, &E(1), &c__1);
if (valeig) {
vll = *vl * sigma;
vuu = *vu * sigma;
}
}
/* If all eigenvalues are desired and ABSTOL is less than zero, then
call SSTERF or SSTEQR. If this fails for some eigenvalue, then
try SSTEBZ. */
if ((alleig || indeig && *il == 1 && *iu == *n) && *abstol <= 0.f) {
scopy_(n, &D(1), &c__1, &W(1), &c__1);
i__1 = *n - 1;
scopy_(&i__1, &E(1), &c__1, &WORK(1), &c__1);
indwrk = *n + 1;
if (! wantz) {
ssterf_(n, &W(1), &WORK(1), info);
} else {
ssteqr_("I", n, &W(1), &WORK(1), &Z(1,1), ldz, &WORK(indwrk),
info);
if (*info == 0) {
i__1 = *n;
for (i = 1; i <= *n; ++i) {
IFAIL(i) = 0;
/* L10: */
}
}
}
if (*info == 0) {
*m = *n;
goto L20;
}
*info = 0;
}
/* Otherwise, call SSTEBZ and, if eigenvectors are desired, SSTEIN. */
if (wantz) {
*(unsigned char *)order = 'B';
} else {
*(unsigned char *)order = 'E';
}
indwrk = 1;
indibl = 1;
indisp = indibl + *n;
indiwo = indisp + *n;
sstebz_(range, order, n, &vll, &vuu, il, iu, abstol, &D(1), &E(1), m, &
nsplit, &W(1), &IWORK(indibl), &IWORK(indisp), &WORK(indwrk), &
IWORK(indiwo), info);
if (wantz) {
sstein_(n, &D(1), &E(1), m, &W(1), &IWORK(indibl), &IWORK(indisp), &Z(1,1), ldz, &WORK(indwrk), &IWORK(indiwo), &IFAIL(1),
info);
}
/* If matrix was scaled, then rescale eigenvalues appropriately. */
L20:
if (iscale == 1) {
if (*info == 0) {
imax = *m;
} else {
imax = *info - 1;
}
r__1 = 1.f / sigma;
sscal_(&imax, &r__1, &W(1), &c__1);
}
/* If eigenvalues are not in order, then sort them, along with
eigenvectors. */
if (wantz) {
i__1 = *m - 1;
for (j = 1; j <= *m-1; ++j) {
i = 0;
tmp1 = W(j);
i__2 = *m;
for (jj = j + 1; jj <= *m; ++jj) {
if (W(jj) < tmp1) {
i = jj;
tmp1 = W(jj);
}
/* L30: */
}
if (i != 0) {
itmp1 = IWORK(indibl + i - 1);
W(i) = W(j);
IWORK(indibl + i - 1) = IWORK(indibl + j - 1);
W(j) = tmp1;
IWORK(indibl + j - 1) = itmp1;
sswap_(n, &Z(1,i), &c__1, &Z(1,j), &
c__1);
if (*info != 0) {
itmp1 = IFAIL(i);
IFAIL(i) = IFAIL(j);
IFAIL(j) = itmp1;
}
}
/* L40: */
}
}
return 0;
/* End of SSTEVX */
} /* sstevx_ */
/* Subroutine */ int ssteqr_(char *compz, int *n, real *d, real *e, real *
z, int *ldz, real *work, int *info)
{
/* -- LAPACK routine (version 2.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
September 30, 1994
Purpose
=======
SSTEQR computes all eigenvalues and, optionally, eigenvectors of a
symmetric tridiagonal matrix using the implicit QL or QR method.
The eigenvectors of a full or band symmetric matrix can also be found
if SSYTRD or SSPTRD or SSBTRD has been used to reduce this matrix to
tridiagonal form.
Arguments
=========
COMPZ (input) CHARACTER*1
= 'N': Compute eigenvalues only.
= 'V': Compute eigenvalues and eigenvectors of the original
symmetric matrix. On entry, Z must contain the
orthogonal matrix used to reduce the original matrix
to tridiagonal form.
= 'I': Compute eigenvalues and eigenvectors of the
tridiagonal matrix. Z is initialized to the identity
matrix.
N (input) INTEGER
The order of the matrix. N >= 0.
D (input/output) REAL array, dimension (N)
On entry, the diagonal elements of the tridiagonal matrix.
On exit, if INFO = 0, the eigenvalues in ascending order.
E (input/output) REAL array, dimension (N-1)
On entry, the (n-1) subdiagonal elements of the tridiagonal
matrix.
On exit, E has been destroyed.
Z (input/output) REAL array, dimension (LDZ, N)
On entry, if COMPZ = 'V', then Z contains the orthogonal
matrix used in the reduction to tridiagonal form.
On exit, if INFO = 0, then if COMPZ = 'V', Z contains the
orthonormal eigenvectors of the original symmetric matrix,
and if COMPZ = 'I', Z contains the orthonormal eigenvectors
of the symmetric tridiagonal matrix.
If COMPZ = 'N', then Z is not referenced.
LDZ (input) INTEGER
The leading dimension of the array Z. LDZ >= 1, and if
eigenvectors are desired, then LDZ >= max(1,N).
WORK (workspace) REAL array, dimension (max(1,2*N-2))
If COMPZ = 'N', then WORK is not referenced.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: the algorithm has failed to find all the eigenvalues in
a total of 30*N iterations; if INFO = i, then i
elements of E have not converged to zero; on exit, D
and E contain the elements of a symmetric tridiagonal
matrix which is orthogonally similar to the original
matrix.
=====================================================================
Test the input parameters.
Parameter adjustments
Function Body */
/* Table of constant values */
static real c_b9 = 0.f;
static real c_b10 = 1.f;
static int c__0 = 0;
static int c__1 = 1;
static int c__2 = 2;
/* System generated locals */
/* Unused variables commented out by MDG on 03-09-05
int z_dim1, z_offset;
*/
int i__1, i__2;
real r__1, r__2;
/* Builtin functions */
double sqrt(doublereal), r_sign(real *, real *);
/* Local variables */
static int lend, jtot;
extern /* Subroutine */ int slae2_(real *, real *, real *, real *, real *)
;
static real b, c, f, g;
static int i, j, k, l, m;
static real p, r, s;
extern logical lsame_(char *, char *);
static real anorm;
extern /* Subroutine */ int slasr_(char *, char *, char *, int *,
int *, real *, real *, real *, int *);
static int l1;
extern /* Subroutine */ int sswap_(int *, real *, int *, real *,
int *);
static int lendm1, lendp1;
extern /* Subroutine */ int slaev2_(real *, real *, real *, real *, real *
, real *, real *);
extern doublereal slapy2_(real *, real *);
static int ii, mm, iscale;
extern doublereal slamch_(char *);
static real safmin;
extern /* Subroutine */ int xerbla_(char *, int *);
static real safmax;
extern /* Subroutine */ int slascl_(char *, int *, int *, real *,
real *, int *, int *, real *, int *, int *);
static int lendsv;
extern /* Subroutine */ int slartg_(real *, real *, real *, real *, real *
), slaset_(char *, int *, int *, real *, real *, real *,
int *);
static real ssfmin;
static int nmaxit, icompz;
static real ssfmax;
extern doublereal slanst_(char *, int *, real *, real *);
extern /* Subroutine */ int slasrt_(char *, int *, real *, int *);
static int lm1, mm1, nm1;
static real rt1, rt2, eps;
static int lsv;
static real tst, eps2;
#define D(I) d[(I)-1]
#define E(I) e[(I)-1]
#define WORK(I) work[(I)-1]
#define Z(I,J) z[(I)-1 + ((J)-1)* ( *ldz)]
*info = 0;
if (lsame_(compz, "N")) {
icompz = 0;
} else if (lsame_(compz, "V")) {
icompz = 1;
} else if (lsame_(compz, "I")) {
icompz = 2;
} else {
icompz = -1;
}
if (icompz < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
/*
} else if (*ldz < 1 || icompz > 0 && *ldz < max(1,*n)) {
*/
/* Paretheses added by MDG on 03-09-05 */
} else if ((*ldz < 1 || icompz > 0) && (*ldz < max(1,*n))) {
*info = -6;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEQR", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (icompz == 2) {
Z(1,1) = 1.f;
}
return 0;
}
/* Determine the unit roundoff and over/underflow thresholds. */
eps = slamch_("E");
/* Computing 2nd power */
r__1 = eps;
eps2 = r__1 * r__1;
safmin = slamch_("S");
safmax = 1.f / safmin;
ssfmax = sqrt(safmax) / 3.f;
ssfmin = sqrt(safmin) / eps2;
/* Compute the eigenvalues and eigenvectors of the tridiagonal
matrix. */
if (icompz == 2) {
slaset_("Full", n, n, &c_b9, &c_b10, &Z(1,1), ldz);
}
nmaxit = *n * 30;
jtot = 0;
/* Determine where the matrix splits and choose QL or QR iteration
for each block, according to whether top or bottom diagonal
element is smaller. */
l1 = 1;
nm1 = *n - 1;
L10:
if (l1 > *n) {
goto L160;
}
if (l1 > 1) {
E(l1 - 1) = 0.f;
}
if (l1 <= nm1) {
i__1 = nm1;
for (m = l1; m <= nm1; ++m) {
tst = (r__1 = E(m), dabs(r__1));
if (tst == 0.f) {
goto L30;
}
if (tst <= sqrt((r__1 = D(m), dabs(r__1))) * sqrt((r__2 = D(m + 1)
, dabs(r__2))) * eps) {
E(m) = 0.f;
goto L30;
}
/* L20: */
}
}
m = *n;
L30:
l = l1;
lsv = l;
lend = m;
lendsv = lend;
l1 = m + 1;
if (lend == l) {
goto L10;
}
/* Scale submatrix in rows and columns L to LEND */
i__1 = lend - l + 1;
anorm = slanst_("I", &i__1, &D(l), &E(l));
iscale = 0;
if (anorm == 0.f) {
goto L10;
}
if (anorm > ssfmax) {
iscale = 1;
i__1 = lend - l + 1;
slascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &D(l), n,
info);
i__1 = lend - l;
slascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &E(l), n,
info);
} else if (anorm < ssfmin) {
iscale = 2;
i__1 = lend - l + 1;
slascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &D(l), n,
info);
i__1 = lend - l;
slascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &E(l), n,
info);
}
/* Choose between QL and QR iteration */
if ((r__1 = D(lend), dabs(r__1)) < (r__2 = D(l), dabs(r__2))) {
lend = lsv;
l = lendsv;
}
if (lend > l) {
/* QL Iteration
Look for small subdiagonal element. */
L40:
if (l != lend) {
lendm1 = lend - 1;
i__1 = lendm1;
for (m = l; m <= lendm1; ++m) {
/* Computing 2nd power */
r__2 = (r__1 = E(m), dabs(r__1));
tst = r__2 * r__2;
if (tst <= eps2 * (r__1 = D(m), dabs(r__1)) * (r__2 = D(m + 1)
, dabs(r__2)) + safmin) {
goto L60;
}
/* L50: */
}
}
m = lend;
L60:
if (m < lend) {
E(m) = 0.f;
}
p = D(l);
if (m == l) {
goto L80;
}
/* If remaining matrix is 2-by-2, use SLAE2 or SLAEV2
to compute its eigensystem. */
if (m == l + 1) {
if (icompz > 0) {
slaev2_(&D(l), &E(l), &D(l + 1), &rt1, &rt2, &c, &s);
WORK(l) = c;
WORK(*n - 1 + l) = s;
slasr_("R", "V", "B", n, &c__2, &WORK(l), &WORK(*n - 1 + l), &
Z(1,l), ldz);
} else {
slae2_(&D(l), &E(l), &D(l + 1), &rt1, &rt2);
}
D(l) = rt1;
D(l + 1) = rt2;
E(l) = 0.f;
l += 2;
if (l <= lend) {
goto L40;
}
goto L140;
}
if (jtot == nmaxit) {
goto L140;
}
++jtot;
/* Form shift. */
g = (D(l + 1) - p) / (E(l) * 2.f);
r = slapy2_(&g, &c_b10);
g = D(m) - p + E(l) / (g + r_sign(&r, &g));
s = 1.f;
c = 1.f;
p = 0.f;
/* Inner loop */
mm1 = m - 1;
i__1 = l;
for (i = mm1; i >= l; --i) {
f = s * E(i);
b = c * E(i);
slartg_(&g, &f, &c, &s, &r);
if (i != m - 1) {
E(i + 1) = r;
}
g = D(i + 1) - p;
r = (D(i) - g) * s + c * 2.f * b;
p = s * r;
D(i + 1) = g + p;
g = c * r - b;
/* If eigenvectors are desired, then save rotations. */
if (icompz > 0) {
WORK(i) = c;
WORK(*n - 1 + i) = -(doublereal)s;
}
/* L70: */
}
/* If eigenvectors are desired, then apply saved rotations. */
if (icompz > 0) {
mm = m - l + 1;
slasr_("R", "V", "B", n, &mm, &WORK(l), &WORK(*n - 1 + l), &Z(1,l), ldz);
}
D(l) -= p;
E(l) = g;
goto L40;
/* Eigenvalue found. */
L80:
D(l) = p;
++l;
if (l <= lend) {
goto L40;
}
goto L140;
} else {
/* QR Iteration
Look for small superdiagonal element. */
L90:
if (l != lend) {
lendp1 = lend + 1;
i__1 = lendp1;
for (m = l; m >= lendp1; --m) {
/* Computing 2nd power */
r__2 = (r__1 = E(m - 1), dabs(r__1));
tst = r__2 * r__2;
if (tst <= eps2 * (r__1 = D(m), dabs(r__1)) * (r__2 = D(m - 1)
, dabs(r__2)) + safmin) {
goto L110;
}
/* L100: */
}
}
m = lend;
L110:
if (m > lend) {
E(m - 1) = 0.f;
}
p = D(l);
if (m == l) {
goto L130;
}
/* If remaining matrix is 2-by-2, use SLAE2 or SLAEV2
to compute its eigensystem. */
if (m == l - 1) {
if (icompz > 0) {
slaev2_(&D(l - 1), &E(l - 1), &D(l), &rt1, &rt2, &c, &s);
WORK(m) = c;
WORK(*n - 1 + m) = s;
slasr_("R", "V", "F", n, &c__2, &WORK(m), &WORK(*n - 1 + m), &
Z(1,l-1), ldz);
} else {
slae2_(&D(l - 1), &E(l - 1), &D(l), &rt1, &rt2);
}
D(l - 1) = rt1;
D(l) = rt2;
E(l - 1) = 0.f;
l += -2;
if (l >= lend) {
goto L90;
}
goto L140;
}
if (jtot == nmaxit) {
goto L140;
}
++jtot;
/* Form shift. */
g = (D(l - 1) - p) / (E(l - 1) * 2.f);
r = slapy2_(&g, &c_b10);
g = D(m) - p + E(l - 1) / (g + r_sign(&r, &g));
s = 1.f;
c = 1.f;
p = 0.f;
/* Inner loop */
lm1 = l - 1;
i__1 = lm1;
for (i = m; i <= lm1; ++i) {
f = s * E(i);
b = c * E(i);
slartg_(&g, &f, &c, &s, &r);
if (i != m) {
E(i - 1) = r;
}
g = D(i) - p;
r = (D(i + 1) - g) * s + c * 2.f * b;
p = s * r;
D(i) = g + p;
g = c * r - b;
/* If eigenvectors are desired, then save rotations. */
if (icompz > 0) {
WORK(i) = c;
WORK(*n - 1 + i) = s;
}
/* L120: */
}
/* If eigenvectors are desired, then apply saved rotations. */
if (icompz > 0) {
mm = l - m + 1;
slasr_("R", "V", "F", n, &mm, &WORK(m), &WORK(*n - 1 + m), &Z(1,m), ldz);
}
D(l) -= p;
E(lm1) = g;
goto L90;
/* Eigenvalue found. */
L130:
D(l) = p;
--l;
if (l >= lend) {
goto L90;
}
goto L140;
}
/* Undo scaling if necessary */
L140:
if (iscale == 1) {
i__1 = lendsv - lsv + 1;
slascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &D(lsv), n,
info);
i__1 = lendsv - lsv;
slascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &E(lsv), n,
info);
} else if (iscale == 2) {
i__1 = lendsv - lsv + 1;
slascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &D(lsv), n,
info);
i__1 = lendsv - lsv;
slascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &E(lsv), n,
info);
}
/* Check for no convergence to an eigenvalue after a total
of N*MAXIT iterations. */
if (jtot < nmaxit) {
goto L10;
}
i__1 = *n - 1;
for (i = 1; i <= *n-1; ++i) {
if (E(i) != 0.f) {
++(*info);
}
/* L150: */
}
goto L190;
/* Order eigenvalues and eigenvectors. */
L160:
if (icompz == 0) {
/* Use Quick Sort */
slasrt_("I", n, &D(1), info);
} else {
/* Use Selection Sort to minimize swaps of eigenvectors */
i__1 = *n;
for (ii = 2; ii <= *n; ++ii) {
i = ii - 1;
k = i;
p = D(i);
i__2 = *n;
for (j = ii; j <= *n; ++j) {
if (D(j) < p) {
k = j;
p = D(j);
}
/* L170: */
}
if (k != i) {
D(k) = D(i);
D(i) = p;
sswap_(n, &Z(1,i), &c__1, &Z(1,k), &
c__1);
}
/* L180: */
}
}
L190:
return 0;
/* End of SSTEQR */
} /* ssteqr_ */
/* Subroutine */ int sstedc_(char *compz, integer *n, real *d__, real *e,
real *z__, integer *ldz, 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 log(doublereal);
integer pow_ii(integer *, integer *);
double sqrt(doublereal);
/* Local variables */
integer i__, j, k, m;
real p;
integer ii, lgn;
real eps, tiny;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
integer lwmin, start;
extern /* Subroutine */ int sswap_(integer *, real *, integer *, real *,
integer *), slaed0_(integer *, integer *, integer *, real *, real
*, real *, integer *, real *, integer *, real *, integer *,
integer *);
extern doublereal slamch_(char *);
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *);
integer finish;
extern /* Subroutine */ int slascl_(char *, integer *, integer *, real *,
real *, integer *, integer *, real *, integer *, integer *), slacpy_(char *, integer *, integer *, real *, integer *,
real *, integer *), slaset_(char *, integer *, integer *,
real *, real *, real *, integer *);
integer liwmin, icompz;
real orgnrm;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int ssterf_(integer *, real *, real *, integer *),
slasrt_(char *, integer *, real *, integer *);
logical lquery;
integer smlsiz;
extern /* Subroutine */ int ssteqr_(char *, integer *, real *, real *,
real *, integer *, real *, integer *);
integer storez, strtrw;
/* -- LAPACK driver routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SSTEDC computes all eigenvalues and, optionally, eigenvectors of a */
/* symmetric tridiagonal matrix using the divide and conquer method. */
/* The eigenvectors of a full or band real symmetric matrix can also be */
/* found if SSYTRD or SSPTRD or SSBTRD has been used to reduce this */
/* matrix to tridiagonal form. */
/* This code makes very mild assumptions about floating point */
/* arithmetic. It will work on machines with a guard digit in */
/* add/subtract, or on those binary machines without guard digits */
/* which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2. */
/* It could conceivably fail on hexadecimal or decimal machines */
/* without guard digits, but we know of none. See SLAED3 for details. */
/* Arguments */
/* ========= */
/* COMPZ (input) CHARACTER*1 */
/* = 'N': Compute eigenvalues only. */
/* = 'I': Compute eigenvectors of tridiagonal matrix also. */
/* = 'V': Compute eigenvectors of original dense symmetric */
/* matrix also. On entry, Z contains the orthogonal */
/* matrix used to reduce the original matrix to */
/* tridiagonal form. */
/* N (input) INTEGER */
/* The dimension of the symmetric tridiagonal matrix. N >= 0. */
/* D (input/output) REAL array, dimension (N) */
/* On entry, the diagonal elements of the tridiagonal matrix. */
/* On exit, if INFO = 0, the eigenvalues in ascending order. */
/* E (input/output) REAL array, dimension (N-1) */
/* On entry, the subdiagonal elements of the tridiagonal matrix. */
/* On exit, E has been destroyed. */
/* Z (input/output) REAL array, dimension (LDZ,N) */
/* On entry, if COMPZ = 'V', then Z contains the orthogonal */
/* matrix used in the reduction to tridiagonal form. */
/* On exit, if INFO = 0, then if COMPZ = 'V', Z contains the */
/* orthonormal eigenvectors of the original symmetric matrix, */
/* and if COMPZ = 'I', Z contains the orthonormal eigenvectors */
/* of the symmetric tridiagonal matrix. */
/* If COMPZ = 'N', then Z is not referenced. */
/* LDZ (input) INTEGER */
/* The leading dimension of the array Z. LDZ >= 1. */
/* If eigenvectors are desired, then LDZ >= max(1,N). */
/* WORK (workspace/output) REAL array, dimension (MAX(1,LWORK)) */
/* On exit, if INFO = 0, WORK(1) returns the optimal LWORK. */
/* LWORK (input) INTEGER */
/* The dimension of the array WORK. */
/* If COMPZ = 'N' or N <= 1 then LWORK must be at least 1. */
/* If COMPZ = 'V' and N > 1 then LWORK must be at least */
/* ( 1 + 3*N + 2*N*lg N + 3*N**2 ), */
/* where lg( N ) = smallest integer k such */
/* that 2**k >= N. */
/* If COMPZ = 'I' and N > 1 then LWORK must be at least */
/* ( 1 + 4*N + N**2 ). */
/* Note that for COMPZ = 'I' or 'V', then if N is less than or */
/* equal to the minimum divide size, usually 25, then LWORK need */
/* only be max(1,2*(N-1)). */
/* 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 (MAX(1,LIWORK)) */
/* On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK. */
/* LIWORK (input) INTEGER */
/* The dimension of the array IWORK. */
/* If COMPZ = 'N' or N <= 1 then LIWORK must be at least 1. */
/* If COMPZ = 'V' and N > 1 then LIWORK must be at least */
/* ( 6 + 6*N + 5*N*lg N ). */
/* If COMPZ = 'I' and N > 1 then LIWORK must be at least */
/* ( 3 + 5*N ). */
/* Note that for COMPZ = 'I' or 'V', then if N is less than or */
/* equal to the minimum divide size, usually 25, then LIWORK */
/* need only be 1. */
/* 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 */
/* = 0: successful exit. */
/* < 0: if INFO = -i, the i-th argument had an illegal value. */
/* > 0: The algorithm failed to compute an eigenvalue while */
/* working on the submatrix lying in rows and columns */
/* INFO/(N+1) through mod(INFO,N+1). */
/* Further Details */
/* =============== */
/* Based on contributions by */
/* Jeff Rutter, Computer Science Division, University of California */
/* at Berkeley, USA */
/* Modified by Francoise Tisseur, University of Tennessee. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
--d__;
--e;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--work;
--iwork;
/* Function Body */
*info = 0;
lquery = *lwork == -1 || *liwork == -1;
if (lsame_(compz, "N")) {
icompz = 0;
} else if (lsame_(compz, "V")) {
icompz = 1;
} else if (lsame_(compz, "I")) {
icompz = 2;
} else {
icompz = -1;
}
if (icompz < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*ldz < 1 || icompz > 0 && *ldz < max(1,*n)) {
*info = -6;
}
if (*info == 0) {
/* Compute the workspace requirements */
smlsiz = ilaenv_(&c__9, "SSTEDC", " ", &c__0, &c__0, &c__0, &c__0);
if (*n <= 1 || icompz == 0) {
liwmin = 1;
lwmin = 1;
} else if (*n <= smlsiz) {
liwmin = 1;
lwmin = *n - 1 << 1;
} else {
lgn = (integer) (log((real) (*n)) / log(2.f));
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
if (icompz == 1) {
/* Computing 2nd power */
i__1 = *n;
lwmin = *n * 3 + 1 + (*n << 1) * lgn + i__1 * i__1 * 3;
liwmin = *n * 6 + 6 + *n * 5 * lgn;
} else if (icompz == 2) {
/* Computing 2nd power */
i__1 = *n;
lwmin = (*n << 2) + 1 + i__1 * i__1;
liwmin = *n * 5 + 3;
}
}
work[1] = (real) lwmin;
iwork[1] = liwmin;
if (*lwork < lwmin && ! lquery) {
*info = -8;
} else if (*liwork < liwmin && ! lquery) {
*info = -10;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEDC", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (icompz != 0) {
z__[z_dim1 + 1] = 1.f;
}
return 0;
}
/* If the following conditional clause is removed, then the routine */
/* will use the Divide and Conquer routine to compute only the */
/* eigenvalues, which requires (3N + 3N**2) real workspace and */
/* (2 + 5N + 2N lg(N)) integer workspace. */
/* Since on many architectures SSTERF is much faster than any other */
/* algorithm for finding eigenvalues only, it is used here */
/* as the default. If the conditional clause is removed, then */
/* information on the size of workspace needs to be changed. */
/* If COMPZ = 'N', use SSTERF to compute the eigenvalues. */
if (icompz == 0) {
ssterf_(n, &d__[1], &e[1], info);
goto L50;
}
/* If N is smaller than the minimum divide size (SMLSIZ+1), then */
/* solve the problem with another solver. */
if (*n <= smlsiz) {
ssteqr_(compz, n, &d__[1], &e[1], &z__[z_offset], ldz, &work[1], info);
} else {
/* If COMPZ = 'V', the Z matrix must be stored elsewhere for later */
/* use. */
if (icompz == 1) {
storez = *n * *n + 1;
} else {
storez = 1;
}
if (icompz == 2) {
slaset_("Full", n, n, &c_b17, &c_b18, &z__[z_offset], ldz);
}
/* Scale. */
orgnrm = slanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.f) {
goto L50;
}
eps = slamch_("Epsilon");
start = 1;
/* while ( START <= N ) */
L10:
if (start <= *n) {
/* Let FINISH be the position of the next subdiagonal entry */
/* such that E( FINISH ) <= TINY or FINISH = N if no such */
/* subdiagonal exists. The matrix identified by the elements */
/* between START and FINISH constitutes an independent */
/* sub-problem. */
finish = start;
L20:
if (finish < *n) {
tiny = eps * sqrt((r__1 = d__[finish], dabs(r__1))) * sqrt((
r__2 = d__[finish + 1], dabs(r__2)));
if ((r__1 = e[finish], dabs(r__1)) > tiny) {
++finish;
goto L20;
}
}
/* (Sub) Problem determined. Compute its size and solve it. */
m = finish - start + 1;
if (m == 1) {
start = finish + 1;
goto L10;
}
if (m > smlsiz) {
/* Scale. */
orgnrm = slanst_("M", &m, &d__[start], &e[start]);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b18, &m, &c__1, &d__[
start], &m, info);
i__1 = m - 1;
i__2 = m - 1;
slascl_("G", &c__0, &c__0, &orgnrm, &c_b18, &i__1, &c__1, &e[
start], &i__2, info);
if (icompz == 1) {
strtrw = 1;
} else {
strtrw = start;
}
slaed0_(&icompz, n, &m, &d__[start], &e[start], &z__[strtrw +
start * z_dim1], ldz, &work[1], n, &work[storez], &
iwork[1], info);
if (*info != 0) {
*info = (*info / (m + 1) + start - 1) * (*n + 1) + *info %
(m + 1) + start - 1;
goto L50;
}
/* Scale back. */
slascl_("G", &c__0, &c__0, &c_b18, &orgnrm, &m, &c__1, &d__[
start], &m, info);
} else {
if (icompz == 1) {
/* Since QR won't update a Z matrix which is larger than */
/* the length of D, we must solve the sub-problem in a */
/* workspace and then multiply back into Z. */
ssteqr_("I", &m, &d__[start], &e[start], &work[1], &m, &
work[m * m + 1], info);
slacpy_("A", n, &m, &z__[start * z_dim1 + 1], ldz, &work[
storez], n);
sgemm_("N", "N", n, &m, &m, &c_b18, &work[storez], n, &
work[1], &m, &c_b17, &z__[start * z_dim1 + 1],
ldz);
} else if (icompz == 2) {
ssteqr_("I", &m, &d__[start], &e[start], &z__[start +
start * z_dim1], ldz, &work[1], info);
} else {
ssterf_(&m, &d__[start], &e[start], info);
}
if (*info != 0) {
*info = start * (*n + 1) + finish;
goto L50;
}
}
start = finish + 1;
goto L10;
}
/* endwhile */
/* If the problem split any number of times, then the eigenvalues */
/* will not be properly ordered. Here we permute the eigenvalues */
/* (and the associated eigenvectors) into ascending order. */
if (m != *n) {
if (icompz == 0) {
/* Use Quick Sort */
slasrt_("I", n, &d__[1], info);
} else {
/* Use Selection Sort to minimize swaps of eigenvectors */
i__1 = *n;
for (ii = 2; ii <= i__1; ++ii) {
i__ = ii - 1;
k = i__;
p = d__[i__];
i__2 = *n;
for (j = ii; j <= i__2; ++j) {
if (d__[j] < p) {
k = j;
p = d__[j];
}
/* L30: */
}
if (k != i__) {
d__[k] = d__[i__];
d__[i__] = p;
sswap_(n, &z__[i__ * z_dim1 + 1], &c__1, &z__[k *
z_dim1 + 1], &c__1);
}
/* L40: */
}
}
}
}
L50:
work[1] = (real) lwmin;
iwork[1] = liwmin;
return 0;
/* End of SSTEDC */
} /* sstedc_ */
/* Subroutine */ int sptt02_(integer *n, integer *nrhs, real *d__, real *e,
real *x, integer *ldx, real *b, integer *ldb, real *resid)
{
/* System generated locals */
integer b_dim1, b_offset, x_dim1, x_offset, i__1;
real r__1, r__2;
/* Local variables */
integer j;
real eps, anorm, bnorm;
extern doublereal sasum_(integer *, real *, integer *);
real xnorm;
extern doublereal slamch_(char *);
extern /* Subroutine */ int slaptm_(integer *, integer *, real *, real *,
real *, real *, integer *, real *, real *, integer *);
extern doublereal slanst_(char *, integer *, real *, real *);
/* -- LAPACK test routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SPTT02 computes the residual for the solution to a symmetric */
/* tridiagonal system of equations: */
/* RESID = norm(B - A*X) / (norm(A) * norm(X) * EPS), */
/* where EPS is the machine epsilon. */
/* Arguments */
/* ========= */
/* N (input) INTEGTER */
/* The order of the matrix A. */
/* NRHS (input) INTEGER */
/* The number of right hand sides, i.e., the number of columns */
/* of the matrices B and X. NRHS >= 0. */
/* D (input) REAL array, dimension (N) */
/* The n diagonal elements of the tridiagonal matrix A. */
/* E (input) REAL array, dimension (N-1) */
/* The (n-1) subdiagonal elements of the tridiagonal matrix A. */
/* X (input) REAL array, dimension (LDX,NRHS) */
/* The n by nrhs matrix of solution vectors X. */
/* LDX (input) INTEGER */
/* The leading dimension of the array X. LDX >= max(1,N). */
/* B (input/output) REAL array, dimension (LDB,NRHS) */
/* On entry, the n by nrhs matrix of right hand side vectors B. */
/* On exit, B is overwritten with the difference B - A*X. */
/* LDB (input) INTEGER */
/* The leading dimension of the array B. LDB >= max(1,N). */
/* RESID (output) REAL */
/* norm(B - A*X) / (norm(A) * norm(X) * EPS) */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Executable Statements .. */
/* Quick return if possible */
/* Parameter adjustments */
--d__;
--e;
x_dim1 = *ldx;
x_offset = 1 + x_dim1;
x -= x_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
/* Function Body */
if (*n <= 0) {
*resid = 0.f;
return 0;
}
/* Compute the 1-norm of the tridiagonal matrix A. */
anorm = slanst_("1", n, &d__[1], &e[1]);
/* Exit with RESID = 1/EPS if ANORM = 0. */
eps = slamch_("Epsilon");
if (anorm <= 0.f) {
*resid = 1.f / eps;
return 0;
}
/* Compute B - A*X. */
slaptm_(n, nrhs, &c_b4, &d__[1], &e[1], &x[x_offset], ldx, &c_b5, &b[
b_offset], ldb);
/* Compute the maximum over the number of right hand sides of */
/* norm(B - A*X) / ( norm(A) * norm(X) * EPS ). */
*resid = 0.f;
i__1 = *nrhs;
for (j = 1; j <= i__1; ++j) {
bnorm = sasum_(n, &b[j * b_dim1 + 1], &c__1);
xnorm = sasum_(n, &x[j * x_dim1 + 1], &c__1);
if (xnorm <= 0.f) {
*resid = 1.f / eps;
} else {
/* Computing MAX */
r__1 = *resid, r__2 = bnorm / anorm / xnorm / eps;
*resid = dmax(r__1,r__2);
}
/* L10: */
}
return 0;
/* End of SPTT02 */
} /* sptt02_ */
/* Subroutine */ int sstevd_(char *jobz, integer *n, real *d__, real *e, real
*z__, integer *ldz, real *work, integer *lwork, integer *iwork,
integer *liwork, integer *info)
{
/* -- LAPACK driver routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
June 30, 1999
Purpose
=======
SSTEVD computes all eigenvalues and, optionally, eigenvectors of a
real symmetric tridiagonal matrix. If eigenvectors are desired, it
uses a divide and conquer algorithm.
The divide and conquer algorithm makes very mild assumptions about
floating point arithmetic. It will work on machines with a guard
digit in add/subtract, or on those binary machines without guard
digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
Cray-2. It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none.
Arguments
=========
JOBZ (input) CHARACTER*1
= 'N': Compute eigenvalues only;
= 'V': Compute eigenvalues and eigenvectors.
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
A.
On exit, if INFO = 0, the eigenvalues in ascending order.
E (input/output) REAL array, dimension (N)
On entry, the (n-1) subdiagonal elements of the tridiagonal
matrix A, stored in elements 1 to N-1 of E; E(N) need not
be set, but is used by the routine.
On exit, the contents of E are destroyed.
Z (output) REAL array, dimension (LDZ, N)
If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal
eigenvectors of the matrix A, with the i-th column of Z
holding the eigenvector associated with D(i).
If JOBZ = 'N', then Z is not referenced.
LDZ (input) INTEGER
The leading dimension of the array Z. LDZ >= 1, and if
JOBZ = 'V', LDZ >= max(1,N).
WORK (workspace/output) REAL array,
dimension (LWORK)
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If JOBZ = 'N' or N <= 1 then LWORK must be at least 1.
If JOBZ = 'V' and N > 1 then LWORK must be at least
( 1 + 4*N + N**2 ).
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.
If JOBZ = 'N' or N <= 1 then LIWORK must be at least 1.
If JOBZ = 'V' and N > 1 then LIWORK must be at least 3+5*N.
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
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, the algorithm failed to converge; i
off-diagonal elements of E did not converge to zero.
=====================================================================
Test the input parameters.
Parameter adjustments */
/* Table of constant values */
static integer c__1 = 1;
/* System generated locals */
integer z_dim1, z_offset, i__1;
real r__1;
/* Builtin functions */
double sqrt(doublereal);
/* Local variables */
static real rmin, rmax, tnrm, sigma;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int sscal_(integer *, real *, real *, integer *);
static integer lwmin;
static logical wantz;
static integer iscale;
extern doublereal slamch_(char *);
static real safmin;
extern /* Subroutine */ int xerbla_(char *, integer *);
static real bignum;
extern /* Subroutine */ int sstedc_(char *, integer *, real *, real *,
real *, integer *, real *, integer *, integer *, integer *,
integer *);
static integer liwmin;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int ssterf_(integer *, real *, real *, integer *);
static real smlnum;
static logical lquery;
static real eps;
#define z___ref(a_1,a_2) z__[(a_2)*z_dim1 + a_1]
--d__;
--e;
z_dim1 = *ldz;
z_offset = 1 + z_dim1 * 1;
z__ -= z_offset;
--work;
--iwork;
/* Function Body */
wantz = lsame_(jobz, "V");
lquery = *lwork == -1 || *liwork == -1;
*info = 0;
liwmin = 1;
lwmin = 1;
if (*n > 1 && wantz) {
/* Computing 2nd power */
i__1 = *n;
lwmin = (*n << 2) + 1 + i__1 * i__1;
liwmin = *n * 5 + 3;
}
if (! (wantz || lsame_(jobz, "N"))) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*ldz < 1 || wantz && *ldz < *n) {
*info = -6;
} else if (*lwork < lwmin && ! lquery) {
*info = -8;
} else if (*liwork < liwmin && ! lquery) {
*info = -10;
}
if (*info == 0) {
work[1] = (real) lwmin;
iwork[1] = liwmin;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEVD", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (wantz) {
z___ref(1, 1) = 1.f;
}
return 0;
}
/* Get machine constants. */
safmin = slamch_("Safe minimum");
eps = slamch_("Precision");
smlnum = safmin / eps;
bignum = 1.f / smlnum;
rmin = sqrt(smlnum);
rmax = sqrt(bignum);
/* Scale matrix to allowable range, if necessary. */
iscale = 0;
tnrm = slanst_("M", n, &d__[1], &e[1]);
if (tnrm > 0.f && tnrm < rmin) {
iscale = 1;
sigma = rmin / tnrm;
} else if (tnrm > rmax) {
iscale = 1;
sigma = rmax / tnrm;
}
if (iscale == 1) {
sscal_(n, &sigma, &d__[1], &c__1);
i__1 = *n - 1;
sscal_(&i__1, &sigma, &e[1], &c__1);
}
/* For eigenvalues only, call SSTERF. For eigenvalues and
eigenvectors, call SSTEDC. */
if (! wantz) {
ssterf_(n, &d__[1], &e[1], info);
} else {
sstedc_("I", n, &d__[1], &e[1], &z__[z_offset], ldz, &work[1], lwork,
&iwork[1], liwork, info);
}
/* If matrix was scaled, then rescale eigenvalues appropriately. */
if (iscale == 1) {
r__1 = 1.f / sigma;
sscal_(n, &r__1, &d__[1], &c__1);
}
work[1] = (real) lwmin;
iwork[1] = liwmin;
return 0;
/* End of SSTEVD */
} /* sstevd_ */
/* Subroutine */ int sptsvx_(char *fact, integer *n, integer *nrhs, real *d__,
real *e, real *df, real *ef, real *b, integer *ldb, real *x, integer
*ldx, real *rcond, real *ferr, real *berr, real *work, integer *info)
{
/* -- LAPACK routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
June 30, 1999
Purpose
=======
SPTSVX uses the factorization A = L*D*L**T to compute the solution
to a real system of linear equations A*X = B, where A is an N-by-N
symmetric positive definite tridiagonal matrix and X and B are
N-by-NRHS matrices.
Error bounds on the solution and a condition estimate are also
provided.
Description
===========
The following steps are performed:
1. If FACT = 'N', the matrix A is factored as A = L*D*L**T, where L
is a unit lower bidiagonal matrix and D is diagonal. The
factorization can also be regarded as having the form
A = U**T*D*U.
2. If the leading i-by-i principal minor is not positive definite,
then the routine returns with INFO = i. Otherwise, the factored
form of A is used to estimate the condition number of the matrix
A. If the reciprocal of the condition number is less than machine
precision, INFO = N+1 is returned as a warning, but the routine
still goes on to solve for X and compute error bounds as
described below.
3. The system of equations is solved for X using the factored form
of A.
4. Iterative refinement is applied to improve the computed solution
matrix and calculate error bounds and backward error estimates
for it.
Arguments
=========
FACT (input) CHARACTER*1
Specifies whether or not the factored form of A has been
supplied on entry.
= 'F': On entry, DF and EF contain the factored form of A.
D, E, DF, and EF will not be modified.
= 'N': The matrix A will be copied to DF and EF and
factored.
N (input) INTEGER
The order of the matrix A. N >= 0.
NRHS (input) INTEGER
The number of right hand sides, i.e., the number of columns
of the matrices B and X. NRHS >= 0.
D (input) REAL array, dimension (N)
The n diagonal elements of the tridiagonal matrix A.
E (input) REAL array, dimension (N-1)
The (n-1) subdiagonal elements of the tridiagonal matrix A.
DF (input or output) REAL array, dimension (N)
If FACT = 'F', then DF is an input argument and on entry
contains the n diagonal elements of the diagonal matrix D
from the L*D*L**T factorization of A.
If FACT = 'N', then DF is an output argument and on exit
contains the n diagonal elements of the diagonal matrix D
from the L*D*L**T factorization of A.
EF (input or output) REAL array, dimension (N-1)
If FACT = 'F', then EF is an input argument and on entry
contains the (n-1) subdiagonal elements of the unit
bidiagonal factor L from the L*D*L**T factorization of A.
If FACT = 'N', then EF is an output argument and on exit
contains the (n-1) subdiagonal elements of the unit
bidiagonal factor L from the L*D*L**T factorization of A.
B (input) REAL array, dimension (LDB,NRHS)
The N-by-NRHS right hand side matrix B.
LDB (input) INTEGER
The leading dimension of the array B. LDB >= max(1,N).
X (output) REAL array, dimension (LDX,NRHS)
If INFO = 0 of INFO = N+1, the N-by-NRHS solution matrix X.
LDX (input) INTEGER
The leading dimension of the array X. LDX >= max(1,N).
RCOND (output) REAL
The reciprocal condition number of the matrix A. If RCOND
is less than the machine precision (in particular, if
RCOND = 0), the matrix is singular to working precision.
This condition is indicated by a return code of INFO > 0.
FERR (output) REAL array, dimension (NRHS)
The forward error bound for each solution vector
X(j) (the j-th column of the solution matrix X).
If XTRUE is the true solution corresponding to X(j), FERR(j)
is an estimated upper bound for the magnitude of the largest
element in (X(j) - XTRUE) divided by the magnitude of the
largest element in X(j).
BERR (output) REAL array, dimension (NRHS)
The componentwise relative backward error of each solution
vector X(j) (i.e., the smallest relative change in any
element of A or B that makes X(j) an exact solution).
WORK (workspace) REAL array, dimension (2*N)
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, and i is
<= N: the leading minor of order i of A is
not positive definite, so the factorization
could not be completed, and the solution has not
been computed. RCOND = 0 is returned.
= N+1: U is nonsingular, but RCOND is less than machine
precision, meaning that the matrix is singular
to working precision. Nevertheless, the
solution and error bounds are computed because
there are a number of situations where the
computed solution can be more accurate than the
value of RCOND would suggest.
=====================================================================
Test the input parameters.
Parameter adjustments */
/* Table of constant values */
static integer c__1 = 1;
/* System generated locals */
integer b_dim1, b_offset, x_dim1, x_offset, i__1;
/* Local variables */
extern logical lsame_(char *, char *);
static real anorm;
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *);
extern doublereal slamch_(char *);
static logical nofact;
extern /* Subroutine */ int xerbla_(char *, integer *), slacpy_(
char *, integer *, integer *, real *, integer *, real *, integer *
);
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int sptcon_(integer *, real *, real *, real *,
real *, real *, integer *), sptrfs_(integer *, integer *, real *,
real *, real *, real *, real *, integer *, real *, integer *,
real *, real *, real *, integer *), spttrf_(integer *, real *,
real *, integer *), spttrs_(integer *, integer *, real *, real *,
real *, integer *, integer *);
--d__;
--e;
--df;
--ef;
b_dim1 = *ldb;
b_offset = 1 + b_dim1 * 1;
b -= b_offset;
x_dim1 = *ldx;
x_offset = 1 + x_dim1 * 1;
x -= x_offset;
--ferr;
--berr;
--work;
/* Function Body */
*info = 0;
nofact = lsame_(fact, "N");
if (! nofact && ! lsame_(fact, "F")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*nrhs < 0) {
*info = -3;
} else if (*ldb < max(1,*n)) {
*info = -9;
} else if (*ldx < max(1,*n)) {
*info = -11;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SPTSVX", &i__1);
return 0;
}
if (nofact) {
/* Compute the L*D*L' (or U'*D*U) factorization of A. */
scopy_(n, &d__[1], &c__1, &df[1], &c__1);
if (*n > 1) {
i__1 = *n - 1;
scopy_(&i__1, &e[1], &c__1, &ef[1], &c__1);
}
spttrf_(n, &df[1], &ef[1], info);
/* Return if INFO is non-zero. */
if (*info != 0) {
if (*info > 0) {
*rcond = 0.f;
}
return 0;
}
}
/* Compute the norm of the matrix A. */
anorm = slanst_("1", n, &d__[1], &e[1]);
/* Compute the reciprocal of the condition number of A. */
sptcon_(n, &df[1], &ef[1], &anorm, rcond, &work[1], info);
/* Set INFO = N+1 if the matrix is singular to working precision. */
if (*rcond < slamch_("Epsilon")) {
*info = *n + 1;
}
/* Compute the solution vectors X. */
slacpy_("Full", n, nrhs, &b[b_offset], ldb, &x[x_offset], ldx);
spttrs_(n, nrhs, &df[1], &ef[1], &x[x_offset], ldx, info);
/* Use iterative refinement to improve the computed solutions and
compute error bounds and backward error estimates for them. */
sptrfs_(n, nrhs, &d__[1], &e[1], &df[1], &ef[1], &b[b_offset], ldb, &x[
x_offset], ldx, &ferr[1], &berr[1], &work[1], info);
return 0;
/* End of SPTSVX */
} /* sptsvx_ */
/* Subroutine */
int sptsvx_(char *fact, integer *n, integer *nrhs, real *d__, real *e, real *df, real *ef, real *b, integer *ldb, real *x, integer *ldx, real *rcond, real *ferr, real *berr, real *work, integer *info)
{
/* System generated locals */
integer b_dim1, b_offset, x_dim1, x_offset, i__1;
/* Local variables */
extern logical lsame_(char *, char *);
real anorm;
extern /* Subroutine */
int scopy_(integer *, real *, integer *, real *, integer *);
extern real slamch_(char *);
logical nofact;
extern /* Subroutine */
int xerbla_(char *, integer *), slacpy_( char *, integer *, integer *, real *, integer *, real *, integer * );
extern real slanst_(char *, integer *, real *, real *);
extern /* Subroutine */
int sptcon_(integer *, real *, real *, real *, real *, real *, integer *), sptrfs_(integer *, integer *, real *, real *, real *, real *, real *, integer *, real *, integer *, real *, real *, real *, integer *), spttrf_(integer *, real *, real *, integer *), spttrs_(integer *, integer *, real *, real *, real *, integer *, integer *);
/* -- LAPACK driver routine (version 3.4.2) -- */
/* -- LAPACK is a software package provided by Univ. of Tennessee, -- */
/* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- */
/* September 2012 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
--d__;
--e;
--df;
--ef;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
x_dim1 = *ldx;
x_offset = 1 + x_dim1;
x -= x_offset;
--ferr;
--berr;
--work;
/* Function Body */
*info = 0;
nofact = lsame_(fact, "N");
if (! nofact && ! lsame_(fact, "F"))
{
*info = -1;
}
else if (*n < 0)
{
*info = -2;
}
else if (*nrhs < 0)
{
*info = -3;
}
else if (*ldb < max(1,*n))
{
*info = -9;
}
else if (*ldx < max(1,*n))
{
*info = -11;
}
if (*info != 0)
{
i__1 = -(*info);
xerbla_("SPTSVX", &i__1);
return 0;
}
if (nofact)
{
/* Compute the L*D*L**T (or U**T*D*U) factorization of A. */
scopy_(n, &d__[1], &c__1, &df[1], &c__1);
if (*n > 1)
{
i__1 = *n - 1;
scopy_(&i__1, &e[1], &c__1, &ef[1], &c__1);
}
spttrf_(n, &df[1], &ef[1], info);
/* Return if INFO is non-zero. */
if (*info > 0)
{
*rcond = 0.f;
return 0;
}
}
/* Compute the norm of the matrix A. */
anorm = slanst_("1", n, &d__[1], &e[1]);
/* Compute the reciprocal of the condition number of A. */
sptcon_(n, &df[1], &ef[1], &anorm, rcond, &work[1], info);
/* Compute the solution vectors X. */
slacpy_("Full", n, nrhs, &b[b_offset], ldb, &x[x_offset], ldx);
spttrs_(n, nrhs, &df[1], &ef[1], &x[x_offset], ldx, info);
/* Use iterative refinement to improve the computed solutions and */
/* compute error bounds and backward error estimates for them. */
sptrfs_(n, nrhs, &d__[1], &e[1], &df[1], &ef[1], &b[b_offset], ldb, &x[ x_offset], ldx, &ferr[1], &berr[1], &work[1], info);
/* Set INFO = N+1 if the matrix is singular to working precision. */
if (*rcond < slamch_("Epsilon"))
{
*info = *n + 1;
}
return 0;
/* End of SPTSVX */
}
/* Subroutine */ int clalsd_(char *uplo, integer *smlsiz, integer *n, integer
*nrhs, real *d__, real *e, complex *b, integer *ldb, real *rcond,
integer *rank, complex *work, real *rwork, integer *iwork, integer *
info)
{
/* System generated locals */
integer b_dim1, b_offset, i__1, i__2, i__3, i__4, i__5, i__6;
real r__1;
complex q__1;
/* Builtin functions */
double r_imag(complex *), log(doublereal), r_sign(real *, real *);
/* Local variables */
integer c__, i__, j, k;
real r__;
integer s, u, z__;
real cs;
integer bx;
real sn;
integer st, vt, nm1, st1;
real eps;
integer iwk;
real tol;
integer difl, difr;
real rcnd;
integer jcol, irwb, perm, nsub, nlvl, sqre, bxst, jrow, irwu, jimag,
jreal;
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
integer irwib;
extern /* Subroutine */ int ccopy_(integer *, complex *, integer *,
complex *, integer *);
integer poles, sizei, irwrb, nsize;
extern /* Subroutine */ int csrot_(integer *, complex *, integer *,
complex *, integer *, real *, real *);
integer irwvt, icmpq1, icmpq2;
extern /* Subroutine */ int clalsa_(integer *, integer *, integer *,
integer *, complex *, integer *, complex *, integer *, real *,
integer *, real *, integer *, real *, real *, real *, real *,
integer *, integer *, integer *, integer *, real *, real *, real *
, real *, integer *, integer *), clascl_(char *, integer *,
integer *, real *, real *, integer *, integer *, complex *,
integer *, integer *);
extern doublereal slamch_(char *);
extern /* Subroutine */ int slasda_(integer *, integer *, integer *,
integer *, real *, real *, real *, integer *, real *, integer *,
real *, real *, real *, real *, integer *, integer *, integer *,
integer *, real *, real *, real *, real *, integer *, integer *),
clacpy_(char *, integer *, integer *, complex *, integer *,
complex *, integer *), claset_(char *, integer *, integer
*, complex *, complex *, complex *, integer *), xerbla_(
char *, integer *), slascl_(char *, integer *, integer *,
real *, real *, integer *, integer *, real *, integer *, integer *
);
extern integer isamax_(integer *, real *, integer *);
integer givcol;
extern /* Subroutine */ int slasdq_(char *, integer *, integer *, integer
*, integer *, integer *, real *, real *, real *, integer *, real *
, integer *, real *, integer *, real *, integer *),
slaset_(char *, integer *, integer *, real *, real *, real *,
integer *), slartg_(real *, real *, real *, real *, real *
);
real orgnrm;
integer givnum;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int slasrt_(char *, integer *, real *, integer *);
integer givptr, nrwork, irwwrk, smlszp;
/* -- LAPACK routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* CLALSD uses the singular value decomposition of A to solve the least */
/* squares problem of finding X to minimize the Euclidean norm of each */
/* column of A*X-B, where A is N-by-N upper bidiagonal, and X and B */
/* are N-by-NRHS. The solution X overwrites B. */
/* The singular values of A smaller than RCOND times the largest */
/* singular value are treated as zero in solving the least squares */
/* problem; in this case a minimum norm solution is returned. */
/* The actual singular values are returned in D in ascending order. */
/* This code makes very mild assumptions about floating point */
/* arithmetic. It will work on machines with a guard digit in */
/* add/subtract, or on those binary machines without guard digits */
/* which subtract like the Cray XMP, Cray YMP, Cray C 90, or Cray 2. */
/* It could conceivably fail on hexadecimal or decimal machines */
/* without guard digits, but we know of none. */
/* Arguments */
/* ========= */
/* UPLO (input) CHARACTER*1 */
/* = 'U': D and E define an upper bidiagonal matrix. */
/* = 'L': D and E define a lower bidiagonal matrix. */
/* SMLSIZ (input) INTEGER */
/* The maximum size of the subproblems at the bottom of the */
/* computation tree. */
/* N (input) INTEGER */
/* The dimension of the bidiagonal matrix. N >= 0. */
/* NRHS (input) INTEGER */
/* The number of columns of B. NRHS must be at least 1. */
/* D (input/output) REAL array, dimension (N) */
/* On entry D contains the main diagonal of the bidiagonal */
/* matrix. On exit, if INFO = 0, D contains its singular values. */
/* E (input/output) REAL array, dimension (N-1) */
/* Contains the super-diagonal entries of the bidiagonal matrix. */
/* On exit, E has been destroyed. */
/* B (input/output) COMPLEX array, dimension (LDB,NRHS) */
/* On input, B contains the right hand sides of the least */
/* squares problem. On output, B contains the solution X. */
/* LDB (input) INTEGER */
/* The leading dimension of B in the calling subprogram. */
/* LDB must be at least max(1,N). */
/* RCOND (input) REAL */
/* The singular values of A less than or equal to RCOND times */
/* the largest singular value are treated as zero in solving */
/* the least squares problem. If RCOND is negative, */
/* machine precision is used instead. */
/* For example, if diag(S)*X=B were the least squares problem, */
/* where diag(S) is a diagonal matrix of singular values, the */
/* solution would be X(i) = B(i) / S(i) if S(i) is greater than */
/* RCOND*max(S), and X(i) = 0 if S(i) is less than or equal to */
/* RCOND*max(S). */
/* RANK (output) INTEGER */
/* The number of singular values of A greater than RCOND times */
/* the largest singular value. */
/* WORK (workspace) COMPLEX array, dimension (N * NRHS). */
/* RWORK (workspace) REAL array, dimension at least */
/* (9*N + 2*N*SMLSIZ + 8*N*NLVL + 3*SMLSIZ*NRHS + (SMLSIZ+1)**2), */
/* where */
/* NLVL = MAX( 0, INT( LOG_2( MIN( M,N )/(SMLSIZ+1) ) ) + 1 ) */
/* IWORK (workspace) INTEGER array, dimension (3*N*NLVL + 11*N). */
/* INFO (output) INTEGER */
/* = 0: successful exit. */
/* < 0: if INFO = -i, the i-th argument had an illegal value. */
/* > 0: The algorithm failed to compute an singular value while */
/* working on the submatrix lying in rows and columns */
/* INFO/(N+1) through MOD(INFO,N+1). */
/* Further Details */
/* =============== */
/* Based on contributions by */
/* Ming Gu and Ren-Cang Li, Computer Science Division, University of */
/* California at Berkeley, USA */
/* Osni Marques, LBNL/NERSC, USA */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
--d__;
--e;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
--work;
--rwork;
--iwork;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -3;
} else if (*nrhs < 1) {
*info = -4;
} else if (*ldb < 1 || *ldb < *n) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("CLALSD", &i__1);
return 0;
}
eps = slamch_("Epsilon");
/* Set up the tolerance. */
if (*rcond <= 0.f || *rcond >= 1.f) {
rcnd = eps;
} else {
rcnd = *rcond;
}
*rank = 0;
/* Quick return if possible. */
if (*n == 0) {
return 0;
} else if (*n == 1) {
if (d__[1] == 0.f) {
claset_("A", &c__1, nrhs, &c_b1, &c_b1, &b[b_offset], ldb);
} else {
*rank = 1;
clascl_("G", &c__0, &c__0, &d__[1], &c_b10, &c__1, nrhs, &b[
b_offset], ldb, info);
d__[1] = dabs(d__[1]);
}
return 0;
}
/* Rotate the matrix if it is lower bidiagonal. */
if (*(unsigned char *)uplo == 'L') {
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
slartg_(&d__[i__], &e[i__], &cs, &sn, &r__);
d__[i__] = r__;
e[i__] = sn * d__[i__ + 1];
d__[i__ + 1] = cs * d__[i__ + 1];
if (*nrhs == 1) {
csrot_(&c__1, &b[i__ + b_dim1], &c__1, &b[i__ + 1 + b_dim1], &
c__1, &cs, &sn);
} else {
rwork[(i__ << 1) - 1] = cs;
rwork[i__ * 2] = sn;
}
/* L10: */
}
if (*nrhs > 1) {
i__1 = *nrhs;
for (i__ = 1; i__ <= i__1; ++i__) {
i__2 = *n - 1;
for (j = 1; j <= i__2; ++j) {
cs = rwork[(j << 1) - 1];
sn = rwork[j * 2];
csrot_(&c__1, &b[j + i__ * b_dim1], &c__1, &b[j + 1 + i__
* b_dim1], &c__1, &cs, &sn);
/* L20: */
}
/* L30: */
}
}
}
/* Scale. */
nm1 = *n - 1;
orgnrm = slanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.f) {
claset_("A", n, nrhs, &c_b1, &c_b1, &b[b_offset], ldb);
return 0;
}
slascl_("G", &c__0, &c__0, &orgnrm, &c_b10, n, &c__1, &d__[1], n, info);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b10, &nm1, &c__1, &e[1], &nm1,
info);
/* If N is smaller than the minimum divide size SMLSIZ, then solve */
/* the problem with another solver. */
if (*n <= *smlsiz) {
irwu = 1;
irwvt = irwu + *n * *n;
irwwrk = irwvt + *n * *n;
irwrb = irwwrk;
irwib = irwrb + *n * *nrhs;
irwb = irwib + *n * *nrhs;
slaset_("A", n, n, &c_b35, &c_b10, &rwork[irwu], n);
slaset_("A", n, n, &c_b35, &c_b10, &rwork[irwvt], n);
slasdq_("U", &c__0, n, n, n, &c__0, &d__[1], &e[1], &rwork[irwvt], n,
&rwork[irwu], n, &rwork[irwwrk], &c__1, &rwork[irwwrk], info);
if (*info != 0) {
return 0;
}
/* In the real version, B is passed to SLASDQ and multiplied */
/* internally by Q'. Here B is complex and that product is */
/* computed below in two steps (real and imaginary parts). */
j = irwb - 1;
i__1 = *nrhs;
for (jcol = 1; jcol <= i__1; ++jcol) {
i__2 = *n;
for (jrow = 1; jrow <= i__2; ++jrow) {
++j;
i__3 = jrow + jcol * b_dim1;
rwork[j] = b[i__3].r;
/* L40: */
}
/* L50: */
}
sgemm_("T", "N", n, nrhs, n, &c_b10, &rwork[irwu], n, &rwork[irwb], n,
&c_b35, &rwork[irwrb], n);
j = irwb - 1;
i__1 = *nrhs;
for (jcol = 1; jcol <= i__1; ++jcol) {
i__2 = *n;
for (jrow = 1; jrow <= i__2; ++jrow) {
++j;
rwork[j] = r_imag(&b[jrow + jcol * b_dim1]);
/* L60: */
}
/* L70: */
}
sgemm_("T", "N", n, nrhs, n, &c_b10, &rwork[irwu], n, &rwork[irwb], n,
&c_b35, &rwork[irwib], n);
jreal = irwrb - 1;
jimag = irwib - 1;
i__1 = *nrhs;
for (jcol = 1; jcol <= i__1; ++jcol) {
i__2 = *n;
for (jrow = 1; jrow <= i__2; ++jrow) {
++jreal;
++jimag;
i__3 = jrow + jcol * b_dim1;
i__4 = jreal;
i__5 = jimag;
q__1.r = rwork[i__4], q__1.i = rwork[i__5];
b[i__3].r = q__1.r, b[i__3].i = q__1.i;
/* L80: */
}
/* L90: */
}
tol = rcnd * (r__1 = d__[isamax_(n, &d__[1], &c__1)], dabs(r__1));
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if (d__[i__] <= tol) {
claset_("A", &c__1, nrhs, &c_b1, &c_b1, &b[i__ + b_dim1], ldb);
} else {
clascl_("G", &c__0, &c__0, &d__[i__], &c_b10, &c__1, nrhs, &b[
i__ + b_dim1], ldb, info);
++(*rank);
}
/* L100: */
}
/* Since B is complex, the following call to SGEMM is performed */
/* in two steps (real and imaginary parts). That is for V * B */
/* (in the real version of the code V' is stored in WORK). */
/* CALL SGEMM( 'T', 'N', N, NRHS, N, ONE, WORK, N, B, LDB, ZERO, */
/* $ WORK( NWORK ), N ) */
j = irwb - 1;
i__1 = *nrhs;
for (jcol = 1; jcol <= i__1; ++jcol) {
i__2 = *n;
for (jrow = 1; jrow <= i__2; ++jrow) {
++j;
i__3 = jrow + jcol * b_dim1;
rwork[j] = b[i__3].r;
/* L110: */
}
/* L120: */
}
sgemm_("T", "N", n, nrhs, n, &c_b10, &rwork[irwvt], n, &rwork[irwb],
n, &c_b35, &rwork[irwrb], n);
j = irwb - 1;
i__1 = *nrhs;
for (jcol = 1; jcol <= i__1; ++jcol) {
i__2 = *n;
for (jrow = 1; jrow <= i__2; ++jrow) {
++j;
rwork[j] = r_imag(&b[jrow + jcol * b_dim1]);
/* L130: */
}
/* L140: */
}
sgemm_("T", "N", n, nrhs, n, &c_b10, &rwork[irwvt], n, &rwork[irwb],
n, &c_b35, &rwork[irwib], n);
jreal = irwrb - 1;
jimag = irwib - 1;
i__1 = *nrhs;
for (jcol = 1; jcol <= i__1; ++jcol) {
i__2 = *n;
for (jrow = 1; jrow <= i__2; ++jrow) {
++jreal;
++jimag;
i__3 = jrow + jcol * b_dim1;
i__4 = jreal;
i__5 = jimag;
q__1.r = rwork[i__4], q__1.i = rwork[i__5];
b[i__3].r = q__1.r, b[i__3].i = q__1.i;
/* L150: */
}
/* L160: */
}
/* Unscale. */
slascl_("G", &c__0, &c__0, &c_b10, &orgnrm, n, &c__1, &d__[1], n,
info);
slasrt_("D", n, &d__[1], info);
clascl_("G", &c__0, &c__0, &orgnrm, &c_b10, n, nrhs, &b[b_offset],
ldb, info);
return 0;
}
/* Book-keeping and setting up some constants. */
nlvl = (integer) (log((real) (*n) / (real) (*smlsiz + 1)) / log(2.f)) + 1;
smlszp = *smlsiz + 1;
u = 1;
vt = *smlsiz * *n + 1;
difl = vt + smlszp * *n;
difr = difl + nlvl * *n;
z__ = difr + (nlvl * *n << 1);
c__ = z__ + nlvl * *n;
s = c__ + *n;
poles = s + *n;
givnum = poles + (nlvl << 1) * *n;
nrwork = givnum + (nlvl << 1) * *n;
bx = 1;
irwrb = nrwork;
irwib = irwrb + *smlsiz * *nrhs;
irwb = irwib + *smlsiz * *nrhs;
sizei = *n + 1;
k = sizei + *n;
givptr = k + *n;
perm = givptr + *n;
givcol = perm + nlvl * *n;
iwk = givcol + (nlvl * *n << 1);
st = 1;
sqre = 0;
icmpq1 = 1;
icmpq2 = 0;
nsub = 0;
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = d__[i__], dabs(r__1)) < eps) {
d__[i__] = r_sign(&eps, &d__[i__]);
}
/* L170: */
}
i__1 = nm1;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = e[i__], dabs(r__1)) < eps || i__ == nm1) {
++nsub;
iwork[nsub] = st;
/* Subproblem found. First determine its size and then */
/* apply divide and conquer on it. */
if (i__ < nm1) {
/* A subproblem with E(I) small for I < NM1. */
nsize = i__ - st + 1;
iwork[sizei + nsub - 1] = nsize;
} else if ((r__1 = e[i__], dabs(r__1)) >= eps) {
/* A subproblem with E(NM1) not too small but I = NM1. */
nsize = *n - st + 1;
iwork[sizei + nsub - 1] = nsize;
} else {
/* A subproblem with E(NM1) small. This implies an */
/* 1-by-1 subproblem at D(N), which is not solved */
/* explicitly. */
nsize = i__ - st + 1;
iwork[sizei + nsub - 1] = nsize;
++nsub;
iwork[nsub] = *n;
iwork[sizei + nsub - 1] = 1;
ccopy_(nrhs, &b[*n + b_dim1], ldb, &work[bx + nm1], n);
}
st1 = st - 1;
if (nsize == 1) {
/* This is a 1-by-1 subproblem and is not solved */
/* explicitly. */
ccopy_(nrhs, &b[st + b_dim1], ldb, &work[bx + st1], n);
} else if (nsize <= *smlsiz) {
/* This is a small subproblem and is solved by SLASDQ. */
slaset_("A", &nsize, &nsize, &c_b35, &c_b10, &rwork[vt + st1],
n);
slaset_("A", &nsize, &nsize, &c_b35, &c_b10, &rwork[u + st1],
n);
slasdq_("U", &c__0, &nsize, &nsize, &nsize, &c__0, &d__[st], &
e[st], &rwork[vt + st1], n, &rwork[u + st1], n, &
rwork[nrwork], &c__1, &rwork[nrwork], info)
;
if (*info != 0) {
return 0;
}
/* In the real version, B is passed to SLASDQ and multiplied */
/* internally by Q'. Here B is complex and that product is */
/* computed below in two steps (real and imaginary parts). */
j = irwb - 1;
i__2 = *nrhs;
for (jcol = 1; jcol <= i__2; ++jcol) {
i__3 = st + nsize - 1;
for (jrow = st; jrow <= i__3; ++jrow) {
++j;
i__4 = jrow + jcol * b_dim1;
rwork[j] = b[i__4].r;
/* L180: */
}
/* L190: */
}
sgemm_("T", "N", &nsize, nrhs, &nsize, &c_b10, &rwork[u + st1]
, n, &rwork[irwb], &nsize, &c_b35, &rwork[irwrb], &
nsize);
j = irwb - 1;
i__2 = *nrhs;
for (jcol = 1; jcol <= i__2; ++jcol) {
i__3 = st + nsize - 1;
for (jrow = st; jrow <= i__3; ++jrow) {
++j;
rwork[j] = r_imag(&b[jrow + jcol * b_dim1]);
/* L200: */
}
/* L210: */
}
sgemm_("T", "N", &nsize, nrhs, &nsize, &c_b10, &rwork[u + st1]
, n, &rwork[irwb], &nsize, &c_b35, &rwork[irwib], &
nsize);
jreal = irwrb - 1;
jimag = irwib - 1;
i__2 = *nrhs;
for (jcol = 1; jcol <= i__2; ++jcol) {
i__3 = st + nsize - 1;
for (jrow = st; jrow <= i__3; ++jrow) {
++jreal;
++jimag;
i__4 = jrow + jcol * b_dim1;
i__5 = jreal;
i__6 = jimag;
q__1.r = rwork[i__5], q__1.i = rwork[i__6];
b[i__4].r = q__1.r, b[i__4].i = q__1.i;
/* L220: */
}
/* L230: */
}
clacpy_("A", &nsize, nrhs, &b[st + b_dim1], ldb, &work[bx +
st1], n);
} else {
/* A large problem. Solve it using divide and conquer. */
slasda_(&icmpq1, smlsiz, &nsize, &sqre, &d__[st], &e[st], &
rwork[u + st1], n, &rwork[vt + st1], &iwork[k + st1],
&rwork[difl + st1], &rwork[difr + st1], &rwork[z__ +
st1], &rwork[poles + st1], &iwork[givptr + st1], &
iwork[givcol + st1], n, &iwork[perm + st1], &rwork[
givnum + st1], &rwork[c__ + st1], &rwork[s + st1], &
rwork[nrwork], &iwork[iwk], info);
if (*info != 0) {
return 0;
}
bxst = bx + st1;
clalsa_(&icmpq2, smlsiz, &nsize, nrhs, &b[st + b_dim1], ldb, &
work[bxst], n, &rwork[u + st1], n, &rwork[vt + st1], &
iwork[k + st1], &rwork[difl + st1], &rwork[difr + st1]
, &rwork[z__ + st1], &rwork[poles + st1], &iwork[
givptr + st1], &iwork[givcol + st1], n, &iwork[perm +
st1], &rwork[givnum + st1], &rwork[c__ + st1], &rwork[
s + st1], &rwork[nrwork], &iwork[iwk], info);
if (*info != 0) {
return 0;
}
}
st = i__ + 1;
}
/* L240: */
}
/* Apply the singular values and treat the tiny ones as zero. */
tol = rcnd * (r__1 = d__[isamax_(n, &d__[1], &c__1)], dabs(r__1));
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Some of the elements in D can be negative because 1-by-1 */
/* subproblems were not solved explicitly. */
if ((r__1 = d__[i__], dabs(r__1)) <= tol) {
claset_("A", &c__1, nrhs, &c_b1, &c_b1, &work[bx + i__ - 1], n);
} else {
++(*rank);
clascl_("G", &c__0, &c__0, &d__[i__], &c_b10, &c__1, nrhs, &work[
bx + i__ - 1], n, info);
}
d__[i__] = (r__1 = d__[i__], dabs(r__1));
/* L250: */
}
/* Now apply back the right singular vectors. */
icmpq2 = 1;
i__1 = nsub;
for (i__ = 1; i__ <= i__1; ++i__) {
st = iwork[i__];
st1 = st - 1;
nsize = iwork[sizei + i__ - 1];
bxst = bx + st1;
if (nsize == 1) {
ccopy_(nrhs, &work[bxst], n, &b[st + b_dim1], ldb);
} else if (nsize <= *smlsiz) {
/* Since B and BX are complex, the following call to SGEMM */
/* is performed in two steps (real and imaginary parts). */
/* CALL SGEMM( 'T', 'N', NSIZE, NRHS, NSIZE, ONE, */
/* $ RWORK( VT+ST1 ), N, RWORK( BXST ), N, ZERO, */
/* $ B( ST, 1 ), LDB ) */
j = bxst - *n - 1;
jreal = irwb - 1;
i__2 = *nrhs;
for (jcol = 1; jcol <= i__2; ++jcol) {
j += *n;
i__3 = nsize;
for (jrow = 1; jrow <= i__3; ++jrow) {
++jreal;
i__4 = j + jrow;
rwork[jreal] = work[i__4].r;
/* L260: */
}
/* L270: */
}
sgemm_("T", "N", &nsize, nrhs, &nsize, &c_b10, &rwork[vt + st1],
n, &rwork[irwb], &nsize, &c_b35, &rwork[irwrb], &nsize);
j = bxst - *n - 1;
jimag = irwb - 1;
i__2 = *nrhs;
for (jcol = 1; jcol <= i__2; ++jcol) {
j += *n;
i__3 = nsize;
for (jrow = 1; jrow <= i__3; ++jrow) {
++jimag;
rwork[jimag] = r_imag(&work[j + jrow]);
/* L280: */
}
/* L290: */
}
sgemm_("T", "N", &nsize, nrhs, &nsize, &c_b10, &rwork[vt + st1],
n, &rwork[irwb], &nsize, &c_b35, &rwork[irwib], &nsize);
jreal = irwrb - 1;
jimag = irwib - 1;
i__2 = *nrhs;
for (jcol = 1; jcol <= i__2; ++jcol) {
i__3 = st + nsize - 1;
for (jrow = st; jrow <= i__3; ++jrow) {
++jreal;
++jimag;
i__4 = jrow + jcol * b_dim1;
i__5 = jreal;
i__6 = jimag;
q__1.r = rwork[i__5], q__1.i = rwork[i__6];
b[i__4].r = q__1.r, b[i__4].i = q__1.i;
/* L300: */
}
/* L310: */
}
} else {
clalsa_(&icmpq2, smlsiz, &nsize, nrhs, &work[bxst], n, &b[st +
b_dim1], ldb, &rwork[u + st1], n, &rwork[vt + st1], &
iwork[k + st1], &rwork[difl + st1], &rwork[difr + st1], &
rwork[z__ + st1], &rwork[poles + st1], &iwork[givptr +
st1], &iwork[givcol + st1], n, &iwork[perm + st1], &rwork[
givnum + st1], &rwork[c__ + st1], &rwork[s + st1], &rwork[
nrwork], &iwork[iwk], info);
if (*info != 0) {
return 0;
}
}
/* L320: */
}
/* Unscale and sort the singular values. */
slascl_("G", &c__0, &c__0, &c_b10, &orgnrm, n, &c__1, &d__[1], n, info);
slasrt_("D", n, &d__[1], info);
clascl_("G", &c__0, &c__0, &orgnrm, &c_b10, n, nrhs, &b[b_offset], ldb,
info);
return 0;
/* End of CLALSD */
} /* clalsd_ */
int sbdsdc_(char *uplo, char *compq, int *n, float *d__,
float *e, float *u, int *ldu, float *vt, int *ldvt, float *q,
int *iq, float *work, int *iwork, int *info)
{
/* System generated locals */
int u_dim1, u_offset, vt_dim1, vt_offset, i__1, i__2;
float r__1;
/* Builtin functions */
double r_sign(float *, float *), log(double);
/* Local variables */
int i__, j, k;
float p, r__;
int z__, ic, ii, kk;
float cs;
int is, iu;
float sn;
int nm1;
float eps;
int ivt, difl, difr, ierr, perm, mlvl, sqre;
extern int lsame_(char *, char *);
int poles;
extern int slasr_(char *, char *, char *, int *,
int *, float *, float *, float *, int *);
int iuplo, nsize, start;
extern int scopy_(int *, float *, int *, float *,
int *), sswap_(int *, float *, int *, float *, int *
), slasd0_(int *, int *, float *, float *, float *, int *
, float *, int *, int *, int *, float *, int *);
extern double slamch_(char *);
extern int slasda_(int *, int *, int *,
int *, float *, float *, float *, int *, float *, int *,
float *, float *, float *, float *, int *, int *, int *,
int *, float *, float *, float *, float *, int *, int *),
xerbla_(char *, int *);
extern int ilaenv_(int *, char *, char *, int *, int *,
int *, int *);
extern int slascl_(char *, int *, int *, float *,
float *, int *, int *, float *, int *, int *);
int givcol;
extern int slasdq_(char *, int *, int *, int
*, int *, int *, float *, float *, float *, int *, float *
, int *, float *, int *, float *, int *);
int icompq;
extern int slaset_(char *, int *, int *, float *,
float *, float *, int *), slartg_(float *, float *, float *
, float *, float *);
float orgnrm;
int givnum;
extern double slanst_(char *, int *, float *, float *);
int givptr, qstart, smlsiz, wstart, smlszp;
/* -- LAPACK routine (version 3.2) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SBDSDC computes the singular value decomposition (SVD) of a float */
/* N-by-N (upper or lower) bidiagonal matrix B: B = U * S * VT, */
/* using a divide and conquer method, where S is a diagonal matrix */
/* with non-negative diagonal elements (the singular values of B), and */
/* U and VT are orthogonal matrices of left and right singular vectors, */
/* respectively. SBDSDC can be used to compute all singular values, */
/* and optionally, singular vectors or singular vectors in compact form. */
/* This code makes very mild assumptions about floating point */
/* arithmetic. It will work on machines with a guard digit in */
/* add/subtract, or on those binary machines without guard digits */
/* which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2. */
/* It could conceivably fail on hexadecimal or decimal machines */
/* without guard digits, but we know of none. See SLASD3 for details. */
/* The code currently calls SLASDQ if singular values only are desired. */
/* However, it can be slightly modified to compute singular values */
/* using the divide and conquer method. */
/* Arguments */
/* ========= */
/* UPLO (input) CHARACTER*1 */
/* = 'U': B is upper bidiagonal. */
/* = 'L': B is lower bidiagonal. */
/* COMPQ (input) CHARACTER*1 */
/* Specifies whether singular vectors are to be computed */
/* as follows: */
/* = 'N': Compute singular values only; */
/* = 'P': Compute singular values and compute singular */
/* vectors in compact form; */
/* = 'I': Compute singular values and singular vectors. */
/* N (input) INTEGER */
/* The order of the matrix B. N >= 0. */
/* D (input/output) REAL array, dimension (N) */
/* On entry, the n diagonal elements of the bidiagonal matrix B. */
/* On exit, if INFO=0, the singular values of B. */
/* E (input/output) REAL array, dimension (N-1) */
/* On entry, the elements of E contain the offdiagonal */
/* elements of the bidiagonal matrix whose SVD is desired. */
/* On exit, E has been destroyed. */
/* U (output) REAL array, dimension (LDU,N) */
/* If COMPQ = 'I', then: */
/* On exit, if INFO = 0, U contains the left singular vectors */
/* of the bidiagonal matrix. */
/* For other values of COMPQ, U is not referenced. */
/* LDU (input) INTEGER */
/* The leading dimension of the array U. LDU >= 1. */
/* If singular vectors are desired, then LDU >= MAX( 1, N ). */
/* VT (output) REAL array, dimension (LDVT,N) */
/* If COMPQ = 'I', then: */
/* On exit, if INFO = 0, VT' contains the right singular */
/* vectors of the bidiagonal matrix. */
/* For other values of COMPQ, VT is not referenced. */
/* LDVT (input) INTEGER */
/* The leading dimension of the array VT. LDVT >= 1. */
/* If singular vectors are desired, then LDVT >= MAX( 1, N ). */
/* Q (output) REAL array, dimension (LDQ) */
/* If COMPQ = 'P', then: */
/* On exit, if INFO = 0, Q and IQ contain the left */
/* and right singular vectors in a compact form, */
/* requiring O(N log N) space instead of 2*N**2. */
/* In particular, Q contains all the REAL data in */
/* LDQ >= N*(11 + 2*SMLSIZ + 8*INT(LOG_2(N/(SMLSIZ+1)))) */
/* words of memory, where SMLSIZ is returned by ILAENV and */
/* is equal to the maximum size of the subproblems at the */
/* bottom of the computation tree (usually about 25). */
/* For other values of COMPQ, Q is not referenced. */
/* IQ (output) INTEGER array, dimension (LDIQ) */
/* If COMPQ = 'P', then: */
/* On exit, if INFO = 0, Q and IQ contain the left */
/* and right singular vectors in a compact form, */
/* requiring O(N log N) space instead of 2*N**2. */
/* In particular, IQ contains all INTEGER data in */
/* LDIQ >= N*(3 + 3*INT(LOG_2(N/(SMLSIZ+1)))) */
/* words of memory, where SMLSIZ is returned by ILAENV and */
/* is equal to the maximum size of the subproblems at the */
/* bottom of the computation tree (usually about 25). */
/* For other values of COMPQ, IQ is not referenced. */
/* WORK (workspace) REAL array, dimension (MAX(1,LWORK)) */
/* If COMPQ = 'N' then LWORK >= (4 * N). */
/* If COMPQ = 'P' then LWORK >= (6 * N). */
/* If COMPQ = 'I' then LWORK >= (3 * N**2 + 4 * N). */
/* IWORK (workspace) INTEGER array, dimension (8*N) */
/* INFO (output) INTEGER */
/* = 0: successful exit. */
/* < 0: if INFO = -i, the i-th argument had an illegal value. */
/* > 0: The algorithm failed to compute an singular value. */
/* The update process of divide and conquer failed. */
/* Further Details */
/* =============== */
/* Based on contributions by */
/* Ming Gu and Huan Ren, Computer Science Division, University of */
/* California at Berkeley, USA */
/* ===================================================================== */
/* Changed dimension statement in comment describing E from (N) to */
/* (N-1). Sven, 17 Feb 05. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
--d__;
--e;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
vt_dim1 = *ldvt;
vt_offset = 1 + vt_dim1;
vt -= vt_offset;
--q;
--iq;
--work;
--iwork;
/* Function Body */
*info = 0;
iuplo = 0;
if (lsame_(uplo, "U")) {
iuplo = 1;
}
if (lsame_(uplo, "L")) {
iuplo = 2;
}
if (lsame_(compq, "N")) {
icompq = 0;
} else if (lsame_(compq, "P")) {
icompq = 1;
} else if (lsame_(compq, "I")) {
icompq = 2;
} else {
icompq = -1;
}
if (iuplo == 0) {
*info = -1;
} else if (icompq < 0) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*ldu < 1 || icompq == 2 && *ldu < *n) {
*info = -7;
} else if (*ldvt < 1 || icompq == 2 && *ldvt < *n) {
*info = -9;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SBDSDC", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
smlsiz = ilaenv_(&c__9, "SBDSDC", " ", &c__0, &c__0, &c__0, &c__0);
if (*n == 1) {
if (icompq == 1) {
q[1] = r_sign(&c_b15, &d__[1]);
q[smlsiz * *n + 1] = 1.f;
} else if (icompq == 2) {
u[u_dim1 + 1] = r_sign(&c_b15, &d__[1]);
vt[vt_dim1 + 1] = 1.f;
}
d__[1] = ABS(d__[1]);
return 0;
}
nm1 = *n - 1;
/* If matrix lower bidiagonal, rotate to be upper bidiagonal */
/* by applying Givens rotations on the left */
wstart = 1;
qstart = 3;
if (icompq == 1) {
scopy_(n, &d__[1], &c__1, &q[1], &c__1);
i__1 = *n - 1;
scopy_(&i__1, &e[1], &c__1, &q[*n + 1], &c__1);
}
if (iuplo == 2) {
qstart = 5;
wstart = (*n << 1) - 1;
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
slartg_(&d__[i__], &e[i__], &cs, &sn, &r__);
d__[i__] = r__;
e[i__] = sn * d__[i__ + 1];
d__[i__ + 1] = cs * d__[i__ + 1];
if (icompq == 1) {
q[i__ + (*n << 1)] = cs;
q[i__ + *n * 3] = sn;
} else if (icompq == 2) {
work[i__] = cs;
work[nm1 + i__] = -sn;
}
/* L10: */
}
}
/* If ICOMPQ = 0, use SLASDQ to compute the singular values. */
if (icompq == 0) {
slasdq_("U", &c__0, n, &c__0, &c__0, &c__0, &d__[1], &e[1], &vt[
vt_offset], ldvt, &u[u_offset], ldu, &u[u_offset], ldu, &work[
wstart], info);
goto L40;
}
/* If N is smaller than the minimum divide size SMLSIZ, then solve */
/* the problem with another solver. */
if (*n <= smlsiz) {
if (icompq == 2) {
slaset_("A", n, n, &c_b29, &c_b15, &u[u_offset], ldu);
slaset_("A", n, n, &c_b29, &c_b15, &vt[vt_offset], ldvt);
slasdq_("U", &c__0, n, n, n, &c__0, &d__[1], &e[1], &vt[vt_offset]
, ldvt, &u[u_offset], ldu, &u[u_offset], ldu, &work[
wstart], info);
} else if (icompq == 1) {
iu = 1;
ivt = iu + *n;
slaset_("A", n, n, &c_b29, &c_b15, &q[iu + (qstart - 1) * *n], n);
slaset_("A", n, n, &c_b29, &c_b15, &q[ivt + (qstart - 1) * *n], n);
slasdq_("U", &c__0, n, n, n, &c__0, &d__[1], &e[1], &q[ivt + (
qstart - 1) * *n], n, &q[iu + (qstart - 1) * *n], n, &q[
iu + (qstart - 1) * *n], n, &work[wstart], info);
}
goto L40;
}
if (icompq == 2) {
slaset_("A", n, n, &c_b29, &c_b15, &u[u_offset], ldu);
slaset_("A", n, n, &c_b29, &c_b15, &vt[vt_offset], ldvt);
}
/* Scale. */
orgnrm = slanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.f) {
return 0;
}
slascl_("G", &c__0, &c__0, &orgnrm, &c_b15, n, &c__1, &d__[1], n, &ierr);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b15, &nm1, &c__1, &e[1], &nm1, &
ierr);
eps = slamch_("Epsilon");
mlvl = (int) (log((float) (*n) / (float) (smlsiz + 1)) / log(2.f)) + 1;
smlszp = smlsiz + 1;
if (icompq == 1) {
iu = 1;
ivt = smlsiz + 1;
difl = ivt + smlszp;
difr = difl + mlvl;
z__ = difr + (mlvl << 1);
ic = z__ + mlvl;
is = ic + 1;
poles = is + 1;
givnum = poles + (mlvl << 1);
k = 1;
givptr = 2;
perm = 3;
givcol = perm + mlvl;
}
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = d__[i__], ABS(r__1)) < eps) {
d__[i__] = r_sign(&eps, &d__[i__]);
}
/* L20: */
}
start = 1;
sqre = 0;
i__1 = nm1;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = e[i__], ABS(r__1)) < eps || i__ == nm1) {
/* Subproblem found. First determine its size and then */
/* apply divide and conquer on it. */
if (i__ < nm1) {
/* A subproblem with E(I) small for I < NM1. */
nsize = i__ - start + 1;
} else if ((r__1 = e[i__], ABS(r__1)) >= eps) {
/* A subproblem with E(NM1) not too small but I = NM1. */
nsize = *n - start + 1;
} else {
/* A subproblem with E(NM1) small. This implies an */
/* 1-by-1 subproblem at D(N). Solve this 1-by-1 problem */
/* first. */
nsize = i__ - start + 1;
if (icompq == 2) {
u[*n + *n * u_dim1] = r_sign(&c_b15, &d__[*n]);
vt[*n + *n * vt_dim1] = 1.f;
} else if (icompq == 1) {
q[*n + (qstart - 1) * *n] = r_sign(&c_b15, &d__[*n]);
q[*n + (smlsiz + qstart - 1) * *n] = 1.f;
}
d__[*n] = (r__1 = d__[*n], ABS(r__1));
}
if (icompq == 2) {
slasd0_(&nsize, &sqre, &d__[start], &e[start], &u[start +
start * u_dim1], ldu, &vt[start + start * vt_dim1],
ldvt, &smlsiz, &iwork[1], &work[wstart], info);
} else {
slasda_(&icompq, &smlsiz, &nsize, &sqre, &d__[start], &e[
start], &q[start + (iu + qstart - 2) * *n], n, &q[
start + (ivt + qstart - 2) * *n], &iq[start + k * *n],
&q[start + (difl + qstart - 2) * *n], &q[start + (
difr + qstart - 2) * *n], &q[start + (z__ + qstart -
2) * *n], &q[start + (poles + qstart - 2) * *n], &iq[
start + givptr * *n], &iq[start + givcol * *n], n, &
iq[start + perm * *n], &q[start + (givnum + qstart -
2) * *n], &q[start + (ic + qstart - 2) * *n], &q[
start + (is + qstart - 2) * *n], &work[wstart], &
iwork[1], info);
if (*info != 0) {
return 0;
}
}
start = i__ + 1;
}
/* L30: */
}
/* Unscale */
slascl_("G", &c__0, &c__0, &c_b15, &orgnrm, n, &c__1, &d__[1], n, &ierr);
L40:
/* Use Selection Sort to minimize swaps of singular vectors */
i__1 = *n;
for (ii = 2; ii <= i__1; ++ii) {
i__ = ii - 1;
kk = i__;
p = d__[i__];
i__2 = *n;
for (j = ii; j <= i__2; ++j) {
if (d__[j] > p) {
kk = j;
p = d__[j];
}
/* L50: */
}
if (kk != i__) {
d__[kk] = d__[i__];
d__[i__] = p;
if (icompq == 1) {
iq[i__] = kk;
} else if (icompq == 2) {
sswap_(n, &u[i__ * u_dim1 + 1], &c__1, &u[kk * u_dim1 + 1], &
c__1);
sswap_(n, &vt[i__ + vt_dim1], ldvt, &vt[kk + vt_dim1], ldvt);
}
} else if (icompq == 1) {
iq[i__] = i__;
}
/* L60: */
}
/* If ICOMPQ = 1, use IQ(N,1) as the indicator for UPLO */
if (icompq == 1) {
if (iuplo == 1) {
iq[*n] = 1;
} else {
iq[*n] = 0;
}
}
/* If B is lower bidiagonal, update U by those Givens rotations */
/* which rotated B to be upper bidiagonal */
if (iuplo == 2 && icompq == 2) {
slasr_("L", "V", "B", n, n, &work[1], &work[*n], &u[u_offset], ldu);
}
return 0;
/* End of SBDSDC */
} /* sbdsdc_ */
/* Subroutine */ int sstedc_(char *compz, integer *n, real *d__, real *e,
real *z__, integer *ldz, real *work, integer *lwork, integer *iwork,
integer *liwork, integer *info)
{
/* -- LAPACK driver routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
June 30, 1999
Purpose
=======
SSTEDC computes all eigenvalues and, optionally, eigenvectors of a
symmetric tridiagonal matrix using the divide and conquer method.
The eigenvectors of a full or band real symmetric matrix can also be
found if SSYTRD or SSPTRD or SSBTRD has been used to reduce this
matrix to tridiagonal form.
This code makes very mild assumptions about floating point
arithmetic. It will work on machines with a guard digit in
add/subtract, or on those binary machines without guard digits
which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2.
It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none. See SLAED3 for details.
Arguments
=========
COMPZ (input) CHARACTER*1
= 'N': Compute eigenvalues only.
= 'I': Compute eigenvectors of tridiagonal matrix also.
= 'V': Compute eigenvectors of original dense symmetric
matrix also. On entry, Z contains the orthogonal
matrix used to reduce the original matrix to
tridiagonal form.
N (input) INTEGER
The dimension of the symmetric tridiagonal matrix. N >= 0.
D (input/output) REAL array, dimension (N)
On entry, the diagonal elements of the tridiagonal matrix.
On exit, if INFO = 0, the eigenvalues in ascending order.
E (input/output) REAL array, dimension (N-1)
On entry, the subdiagonal elements of the tridiagonal matrix.
On exit, E has been destroyed.
Z (input/output) REAL array, dimension (LDZ,N)
On entry, if COMPZ = 'V', then Z contains the orthogonal
matrix used in the reduction to tridiagonal form.
On exit, if INFO = 0, then if COMPZ = 'V', Z contains the
orthonormal eigenvectors of the original symmetric matrix,
and if COMPZ = 'I', Z contains the orthonormal eigenvectors
of the symmetric tridiagonal matrix.
If COMPZ = 'N', then Z is not referenced.
LDZ (input) INTEGER
The leading dimension of the array Z. LDZ >= 1.
If eigenvectors are desired, then LDZ >= max(1,N).
WORK (workspace/output) REAL array,
dimension (LWORK)
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If COMPZ = 'N' or N <= 1 then LWORK must be at least 1.
If COMPZ = 'V' and N > 1 then LWORK must be at least
( 1 + 3*N + 2*N*lg N + 3*N**2 ),
where lg( N ) = smallest integer k such
that 2**k >= N.
If COMPZ = 'I' and N > 1 then LWORK must be at least
( 1 + 4*N + N**2 ).
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.
If COMPZ = 'N' or N <= 1 then LIWORK must be at least 1.
If COMPZ = 'V' and N > 1 then LIWORK must be at least
( 6 + 6*N + 5*N*lg N ).
If COMPZ = 'I' and N > 1 then LIWORK must be at least
( 3 + 5*N ).
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
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: The algorithm failed to compute an eigenvalue while
working on the submatrix lying in rows and columns
INFO/(N+1) through mod(INFO,N+1).
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
Modified by Francoise Tisseur, University of Tennessee.
=====================================================================
Test the input parameters.
Parameter adjustments */
/* Table of constant values */
static integer c__2 = 2;
static integer c__9 = 9;
static integer c__0 = 0;
static real c_b18 = 0.f;
static real c_b19 = 1.f;
static integer c__1 = 1;
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2;
real r__1, r__2;
/* Builtin functions */
double log(doublereal);
integer pow_ii(integer *, integer *);
double sqrt(doublereal);
/* Local variables */
static real tiny;
static integer i__, j, k, m;
static real p;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int sgemm_(char *, char *, integer *, integer *,
integer *, real *, real *, integer *, real *, integer *, real *,
real *, integer *);
static integer lwmin, start;
extern /* Subroutine */ int sswap_(integer *, real *, integer *, real *,
integer *), slaed0_(integer *, integer *, integer *, real *, real
*, real *, integer *, real *, integer *, real *, integer *,
integer *);
static integer ii;
extern doublereal slamch_(char *);
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int slascl_(char *, integer *, integer *, real *,
real *, integer *, integer *, real *, integer *, integer *), slacpy_(char *, integer *, integer *, real *, integer *,
real *, integer *), slaset_(char *, integer *, integer *,
real *, real *, real *, integer *);
static integer liwmin, icompz;
static real orgnrm;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int ssterf_(integer *, real *, real *, integer *),
slasrt_(char *, integer *, real *, integer *);
static logical lquery;
static integer smlsiz;
extern /* Subroutine */ int ssteqr_(char *, integer *, real *, real *,
real *, integer *, real *, integer *);
static integer storez, strtrw, end, lgn;
static real eps;
#define z___ref(a_1,a_2) z__[(a_2)*z_dim1 + a_1]
--d__;
--e;
z_dim1 = *ldz;
z_offset = 1 + z_dim1 * 1;
z__ -= z_offset;
--work;
--iwork;
/* Function Body */
*info = 0;
lquery = *lwork == -1 || *liwork == -1;
if (lsame_(compz, "N")) {
icompz = 0;
} else if (lsame_(compz, "V")) {
icompz = 1;
} else if (lsame_(compz, "I")) {
icompz = 2;
} else {
icompz = -1;
}
if (*n <= 1 || icompz <= 0) {
liwmin = 1;
lwmin = 1;
} else {
lgn = (integer) (log((real) (*n)) / log(2.f));
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
if (icompz == 1) {
/* Computing 2nd power */
i__1 = *n;
lwmin = *n * 3 + 1 + (*n << 1) * lgn + i__1 * i__1 * 3;
liwmin = *n * 6 + 6 + *n * 5 * lgn;
} else if (icompz == 2) {
/* Computing 2nd power */
i__1 = *n;
lwmin = (*n << 2) + 1 + i__1 * i__1;
liwmin = *n * 5 + 3;
}
}
if (icompz < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*ldz < 1 || icompz > 0 && *ldz < max(1,*n)) {
*info = -6;
} else if (*lwork < lwmin && ! lquery) {
*info = -8;
} else if (*liwork < liwmin && ! lquery) {
*info = -10;
}
if (*info == 0) {
work[1] = (real) lwmin;
iwork[1] = liwmin;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEDC", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (icompz != 0) {
z___ref(1, 1) = 1.f;
}
return 0;
}
smlsiz = ilaenv_(&c__9, "SSTEDC", " ", &c__0, &c__0, &c__0, &c__0, (
ftnlen)6, (ftnlen)1);
/* If the following conditional clause is removed, then the routine
will use the Divide and Conquer routine to compute only the
eigenvalues, which requires (3N + 3N**2) real workspace and
(2 + 5N + 2N lg(N)) integer workspace.
Since on many architectures SSTERF is much faster than any other
algorithm for finding eigenvalues only, it is used here
as the default.
If COMPZ = 'N', use SSTERF to compute the eigenvalues. */
if (icompz == 0) {
ssterf_(n, &d__[1], &e[1], info);
return 0;
}
/* If N is smaller than the minimum divide size (SMLSIZ+1), then
solve the problem with another solver. */
if (*n <= smlsiz) {
if (icompz == 0) {
ssterf_(n, &d__[1], &e[1], info);
return 0;
} else if (icompz == 2) {
ssteqr_("I", n, &d__[1], &e[1], &z__[z_offset], ldz, &work[1],
info);
return 0;
} else {
ssteqr_("V", n, &d__[1], &e[1], &z__[z_offset], ldz, &work[1],
info);
return 0;
}
}
/* If COMPZ = 'V', the Z matrix must be stored elsewhere for later
use. */
if (icompz == 1) {
storez = *n * *n + 1;
} else {
storez = 1;
}
if (icompz == 2) {
slaset_("Full", n, n, &c_b18, &c_b19, &z__[z_offset], ldz);
}
/* Scale. */
orgnrm = slanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.f) {
return 0;
}
eps = slamch_("Epsilon");
start = 1;
/* while ( START <= N ) */
L10:
if (start <= *n) {
/* Let END be the position of the next subdiagonal entry such that
E( END ) <= TINY or END = N if no such subdiagonal exists. The
matrix identified by the elements between START and END
constitutes an independent sub-problem. */
end = start;
L20:
if (end < *n) {
tiny = eps * sqrt((r__1 = d__[end], dabs(r__1))) * sqrt((r__2 =
d__[end + 1], dabs(r__2)));
if ((r__1 = e[end], dabs(r__1)) > tiny) {
++end;
goto L20;
}
}
/* (Sub) Problem determined. Compute its size and solve it. */
m = end - start + 1;
if (m == 1) {
start = end + 1;
goto L10;
}
if (m > smlsiz) {
*info = smlsiz;
/* Scale. */
orgnrm = slanst_("M", &m, &d__[start], &e[start]);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b19, &m, &c__1, &d__[start]
, &m, info);
i__1 = m - 1;
i__2 = m - 1;
slascl_("G", &c__0, &c__0, &orgnrm, &c_b19, &i__1, &c__1, &e[
start], &i__2, info);
if (icompz == 1) {
strtrw = 1;
} else {
strtrw = start;
}
slaed0_(&icompz, n, &m, &d__[start], &e[start], &z___ref(strtrw,
start), ldz, &work[1], n, &work[storez], &iwork[1], info);
if (*info != 0) {
*info = (*info / (m + 1) + start - 1) * (*n + 1) + *info % (m
+ 1) + start - 1;
return 0;
}
/* Scale back. */
slascl_("G", &c__0, &c__0, &c_b19, &orgnrm, &m, &c__1, &d__[start]
, &m, info);
} else {
if (icompz == 1) {
/* Since QR won't update a Z matrix which is larger than the
length of D, we must solve the sub-problem in a workspace and
then multiply back into Z. */
ssteqr_("I", &m, &d__[start], &e[start], &work[1], &m, &work[
m * m + 1], info);
slacpy_("A", n, &m, &z___ref(1, start), ldz, &work[storez], n);
sgemm_("N", "N", n, &m, &m, &c_b19, &work[storez], ldz, &work[
1], &m, &c_b18, &z___ref(1, start), ldz);
} else if (icompz == 2) {
ssteqr_("I", &m, &d__[start], &e[start], &z___ref(start,
start), ldz, &work[1], info);
} else {
ssterf_(&m, &d__[start], &e[start], info);
}
if (*info != 0) {
*info = start * (*n + 1) + end;
return 0;
}
}
start = end + 1;
goto L10;
}
/* endwhile
If the problem split any number of times, then the eigenvalues
will not be properly ordered. Here we permute the eigenvalues
(and the associated eigenvectors) into ascending order. */
if (m != *n) {
if (icompz == 0) {
/* Use Quick Sort */
slasrt_("I", n, &d__[1], info);
} else {
/* Use Selection Sort to minimize swaps of eigenvectors */
i__1 = *n;
for (ii = 2; ii <= i__1; ++ii) {
i__ = ii - 1;
k = i__;
p = d__[i__];
i__2 = *n;
for (j = ii; j <= i__2; ++j) {
if (d__[j] < p) {
k = j;
p = d__[j];
}
/* L30: */
}
if (k != i__) {
d__[k] = d__[i__];
d__[i__] = p;
sswap_(n, &z___ref(1, i__), &c__1, &z___ref(1, k), &c__1);
}
/* L40: */
}
}
}
work[1] = (real) lwmin;
iwork[1] = liwmin;
return 0;
/* End of SSTEDC */
} /* sstedc_ */
/* Subroutine */ int sstevr_(char *jobz, char *range, integer *n, real *d__,
real *e, real *vl, real *vu, integer *il, integer *iu, real *abstol,
integer *m, real *w, real *z__, integer *ldz, integer *isuppz, real *
work, integer *lwork, integer *iwork, integer *liwork, integer *info,
ftnlen jobz_len, ftnlen range_len)
{
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2;
real r__1, r__2;
/* Builtin functions */
double sqrt(doublereal);
/* Local variables */
static integer i__, j, jj;
static real eps, vll, vuu, tmp1;
static integer imax;
static real rmin, rmax, tnrm;
static integer itmp1;
static real sigma;
extern logical lsame_(char *, char *, ftnlen, ftnlen);
extern /* Subroutine */ int sscal_(integer *, real *, real *, integer *);
static char order[1];
static integer lwmin;
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *), sswap_(integer *, real *, integer *, real *, integer *
);
static logical wantz, alleig, indeig;
static integer iscale, ieeeok, indibl, indifl;
static logical valeig;
extern doublereal slamch_(char *, ftnlen);
static real safmin;
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int xerbla_(char *, integer *, ftnlen);
static real bignum;
static integer indisp, indiwo, liwmin;
extern doublereal slanst_(char *, integer *, real *, real *, ftnlen);
extern /* Subroutine */ int sstein_(integer *, real *, real *, integer *,
real *, integer *, integer *, real *, integer *, real *, integer *
, integer *, integer *), ssterf_(integer *, real *, real *,
integer *), sstegr_(char *, char *, integer *, real *, real *,
real *, real *, integer *, integer *, real *, integer *, real *,
real *, integer *, integer *, real *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static integer nsplit;
extern /* Subroutine */ int sstebz_(char *, char *, integer *, real *,
real *, integer *, integer *, real *, real *, real *, integer *,
integer *, real *, integer *, integer *, real *, integer *,
integer *, ftnlen, ftnlen);
static real smlnum;
static logical lquery;
/* -- LAPACK driver routine (version 3.0) -- */
/* Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., */
/* Courant Institute, Argonne National Lab, and Rice University */
/* March 20, 2000 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SSTEVR computes selected eigenvalues and, optionally, eigenvectors */
/* of a real symmetric tridiagonal matrix T. Eigenvalues and */
/* eigenvectors can be selected by specifying either a range of values */
/* or a range of indices for the desired eigenvalues. */
/* Whenever possible, SSTEVR calls SSTEGR to compute the */
/* eigenspectrum using Relatively Robust Representations. SSTEGR */
/* computes eigenvalues by the dqds algorithm, while orthogonal */
/* eigenvectors are computed from various "good" L D L^T representations */
/* (also known as Relatively Robust Representations). Gram-Schmidt */
/* orthogonalization is avoided as far as possible. More specifically, */
/* the various steps of the algorithm are as follows. For the i-th */
/* unreduced block of T, */
/* (a) Compute T - sigma_i = L_i D_i L_i^T, such that L_i D_i L_i^T */
/* is a relatively robust representation, */
/* (b) Compute the eigenvalues, lambda_j, of L_i D_i L_i^T to high */
/* relative accuracy by the dqds algorithm, */
/* (c) If there is a cluster of close eigenvalues, "choose" sigma_i */
/* close to the cluster, and go to step (a), */
/* (d) Given the approximate eigenvalue lambda_j of L_i D_i L_i^T, */
/* compute the corresponding eigenvector by forming a */
/* rank-revealing twisted factorization. */
/* The desired accuracy of the output can be specified by the input */
/* parameter ABSTOL. */
/* For more details, see "A new O(n^2) algorithm for the symmetric */
/* tridiagonal eigenvalue/eigenvector problem", by Inderjit Dhillon, */
/* Computer Science Division Technical Report No. UCB//CSD-97-971, */
/* UC Berkeley, May 1997. */
/* Note 1 : SSTEVR calls SSTEGR when the full spectrum is requested */
/* on machines which conform to the ieee-754 floating point standard. */
/* SSTEVR calls SSTEBZ and SSTEIN on non-ieee machines and */
/* when partial spectrum requests are made. */
/* Normal execution of SSTEGR may create NaNs and infinities and */
/* hence may abort due to a floating point exception in environments */
/* which do not handle NaNs and infinities in the ieee standard default */
/* manner. */
/* 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. */
/* ********* For RANGE = 'V' or 'I' and IU - IL < N - 1, SSTEBZ and */
/* ********* SSTEIN are called */
/* 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 */
/* A. */
/* On exit, D may be multiplied by a constant factor chosen */
/* to avoid over/underflow in computing the eigenvalues. */
/* E (input/output) REAL array, dimension (N) */
/* On entry, the (n-1) subdiagonal elements of the tridiagonal */
/* matrix A in elements 1 to N-1 of E; E(N) need not be set. */
/* On exit, E may be multiplied by a constant factor chosen */
/* to avoid over/underflow in computing the eigenvalues. */
/* 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; IL = 1 and IU = 0 if N = 0. */
/* Not referenced if RANGE = 'A' or 'V'. */
/* ABSTOL (input) REAL */
/* The absolute error tolerance for the eigenvalues. */
/* An approximate eigenvalue is accepted as converged */
/* when it is determined to lie in an interval [a,b] */
/* of width less than or equal to */
/* ABSTOL + EPS * max( |a|,|b| ) , */
/* where EPS is the machine precision. If ABSTOL is less than */
/* or equal to zero, then EPS*|T| will be used in its place, */
/* where |T| is the 1-norm of the tridiagonal matrix obtained */
/* by reducing A to tridiagonal form. */
/* See "Computing Small Singular Values of Bidiagonal Matrices */
/* with Guaranteed High Relative Accuracy," by Demmel and */
/* Kahan, LAPACK Working Note #3. */
/* If high relative accuracy is important, set ABSTOL to */
/* SLAMCH( 'Safe minimum' ). Doing so will guarantee that */
/* eigenvalues are computed to high relative accuracy when */
/* possible in future releases. The current code does not */
/* make any guarantees about high relative accuracy, but */
/* future releases will. See J. Barlow and J. Demmel, */
/* "Computing Accurate Eigensystems of Scaled Diagonally */
/* Dominant Matrices", LAPACK Working Note #7, for a discussion */
/* of which matrices define their eigenvalues to high relative */
/* accuracy. */
/* 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', then if INFO = 0, the first M columns of Z */
/* contain the orthonormal eigenvectors of the matrix A */
/* corresponding to the selected 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; if RANGE = 'V', the exact value of M */
/* is not known in advance and an upper bound must be used. */
/* 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 ). */
/* ********* Implemented only for RANGE = 'A' or 'I' and IU - IL = N - 1 */
/* 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 >= 20*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 (and */
/* minimal) LIWORK. */
/* LIWORK (input) INTEGER */
/* The dimension of the array IWORK. LIWORK >= 10*N. */
/* 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 */
/* = 0: successful exit */
/* < 0: if INFO = -i, the i-th argument had an illegal value */
/* > 0: Internal error */
/* Further Details */
/* =============== */
/* Based on contributions by */
/* Inderjit Dhillon, IBM Almaden, USA */
/* Osni Marques, LBNL/NERSC, USA */
/* Ken Stanley, Computer Science Division, University of */
/* California at 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 */
ieeeok = ilaenv_(&c__10, "SSTEVR", "N", &c__1, &c__2, &c__3, &c__4, (
ftnlen)6, (ftnlen)1);
wantz = lsame_(jobz, "V", (ftnlen)1, (ftnlen)1);
alleig = lsame_(range, "A", (ftnlen)1, (ftnlen)1);
valeig = lsame_(range, "V", (ftnlen)1, (ftnlen)1);
indeig = lsame_(range, "I", (ftnlen)1, (ftnlen)1);
lquery = *lwork == -1 || *liwork == -1;
lwmin = *n * 20;
liwmin = *n * 10;
*info = 0;
if (! (wantz || lsame_(jobz, "N", (ftnlen)1, (ftnlen)1))) {
*info = -1;
} else if (! (alleig || valeig || indeig)) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else {
if (valeig) {
if (*n > 0 && *vu <= *vl) {
*info = -7;
}
} else if (indeig) {
if (*il < 1 || *il > max(1,*n)) {
*info = -8;
} else if (*iu < min(*n,*il) || *iu > *n) {
*info = -9;
}
}
}
if (*info == 0) {
if (*ldz < 1 || wantz && *ldz < *n) {
*info = -14;
} else if (*lwork < lwmin && ! lquery) {
*info = -17;
} else if (*liwork < liwmin && ! lquery) {
*info = -19;
}
}
if (*info == 0) {
work[1] = (real) lwmin;
iwork[1] = liwmin;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEVR", &i__1, (ftnlen)6);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
*m = 0;
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (alleig || indeig) {
*m = 1;
w[1] = d__[1];
} else {
if (*vl < d__[1] && *vu >= d__[1]) {
*m = 1;
w[1] = d__[1];
}
}
if (wantz) {
z__[z_dim1 + 1] = 1.f;
}
return 0;
}
/* Get machine constants. */
safmin = slamch_("Safe minimum", (ftnlen)12);
eps = slamch_("Precision", (ftnlen)9);
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);
/* Scale matrix to allowable range, if necessary. */
iscale = 0;
vll = *vl;
vuu = *vu;
tnrm = slanst_("M", n, &d__[1], &e[1], (ftnlen)1);
if (tnrm > 0.f && tnrm < rmin) {
iscale = 1;
sigma = rmin / tnrm;
} else if (tnrm > rmax) {
iscale = 1;
sigma = rmax / tnrm;
}
if (iscale == 1) {
sscal_(n, &sigma, &d__[1], &c__1);
i__1 = *n - 1;
sscal_(&i__1, &sigma, &e[1], &c__1);
if (valeig) {
vll = *vl * sigma;
vuu = *vu * sigma;
}
}
/* If all eigenvalues are desired, then */
/* call SSTERF or SSTEGR. If this fails for some eigenvalue, then */
/* try SSTEBZ. */
if ((alleig || indeig && *il == 1 && *iu == *n) && ieeeok == 1) {
i__1 = *n - 1;
scopy_(&i__1, &e[1], &c__1, &work[1], &c__1);
if (! wantz) {
scopy_(n, &d__[1], &c__1, &w[1], &c__1);
ssterf_(n, &w[1], &work[1], info);
} else {
scopy_(n, &d__[1], &c__1, &work[*n + 1], &c__1);
i__1 = *lwork - (*n << 1);
sstegr_(jobz, "A", n, &work[*n + 1], &work[1], vl, vu, il, iu,
abstol, m, &w[1], &z__[z_offset], ldz, &isuppz[1], &work[(
*n << 1) + 1], &i__1, &iwork[1], liwork, info, (ftnlen)1,
(ftnlen)1);
}
if (*info == 0) {
*m = *n;
goto L10;
}
*info = 0;
}
/* Otherwise, call SSTEBZ and, if eigenvectors are desired, SSTEIN. */
if (wantz) {
*(unsigned char *)order = 'B';
} else {
*(unsigned char *)order = 'E';
}
indibl = 1;
indisp = indibl + *n;
indifl = indisp + *n;
indiwo = indifl + *n;
sstebz_(range, order, n, &vll, &vuu, il, iu, abstol, &d__[1], &e[1], m, &
nsplit, &w[1], &iwork[indibl], &iwork[indisp], &work[1], &iwork[
indiwo], info, (ftnlen)1, (ftnlen)1);
if (wantz) {
sstein_(n, &d__[1], &e[1], m, &w[1], &iwork[indibl], &iwork[indisp], &
z__[z_offset], ldz, &work[1], &iwork[indiwo], &iwork[indifl],
info);
}
/* If matrix was scaled, then rescale eigenvalues appropriately. */
L10:
if (iscale == 1) {
if (*info == 0) {
imax = *m;
} else {
imax = *info - 1;
}
r__1 = 1.f / sigma;
sscal_(&imax, &r__1, &w[1], &c__1);
}
/* If eigenvalues are not in order, then sort them, along with */
/* eigenvectors. */
if (wantz) {
i__1 = *m - 1;
for (j = 1; j <= i__1; ++j) {
i__ = 0;
tmp1 = w[j];
i__2 = *m;
for (jj = j + 1; jj <= i__2; ++jj) {
if (w[jj] < tmp1) {
i__ = jj;
tmp1 = w[jj];
}
/* L20: */
}
if (i__ != 0) {
itmp1 = iwork[i__];
w[i__] = w[j];
iwork[i__] = iwork[j];
w[j] = tmp1;
iwork[j] = itmp1;
sswap_(n, &z__[i__ * z_dim1 + 1], &c__1, &z__[j * z_dim1 + 1],
&c__1);
}
/* L30: */
}
}
/* Causes problems with tests 19 & 20: */
/* IF (wantz .and. INDEIG ) Z( 1,1) = Z(1,1) / 1.002 + .002 */
work[1] = (real) lwmin;
iwork[1] = liwmin;
return 0;
/* End of SSTEVR */
} /* sstevr_ */
/* Subroutine */ int ssterf_(integer *n, real *d, real *e, integer *info)
{
/* -- LAPACK routine (version 2.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
September 30, 1994
Purpose
=======
SSTERF computes all eigenvalues of a symmetric tridiagonal matrix
using the Pal-Walker-Kahan variant of the QL or QR algorithm.
Arguments
=========
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.
On exit, if INFO = 0, the eigenvalues in ascending order.
E (input/output) REAL array, dimension (N-1)
On entry, the (n-1) subdiagonal elements of the tridiagonal
matrix.
On exit, E has been destroyed.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: the algorithm failed to find all of the eigenvalues in
a total of 30*N iterations; if INFO = i, then i
elements of E have not converged to zero.
=====================================================================
Test the input parameters.
Parameter adjustments
Function Body */
/* Table of constant values */
static integer c__0 = 0;
static integer c__1 = 1;
static real c_b32 = 1.f;
/* System generated locals */
integer i__1;
real r__1, r__2;
/* Builtin functions */
double sqrt(doublereal), r_sign(real *, real *);
/* Local variables */
static real oldc;
static integer lend, jtot;
extern /* Subroutine */ int slae2_(real *, real *, real *, real *, real *)
;
static real c;
static integer i, l, m;
static real p, gamma, r, s, alpha, sigma, anorm;
static integer l1, lendm1, lendp1;
static real bb;
extern doublereal slapy2_(real *, real *);
static integer iscale;
static real oldgam;
extern doublereal slamch_(char *);
static real safmin;
extern /* Subroutine */ int xerbla_(char *, integer *);
static real safmax;
extern /* Subroutine */ int slascl_(char *, integer *, integer *, real *,
real *, integer *, integer *, real *, integer *, integer *);
static integer lendsv;
static real ssfmin;
static integer nmaxit;
static real ssfmax;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int slasrt_(char *, integer *, real *, integer *);
static integer lm1, mm1, nm1;
static real rt1, rt2, eps, rte;
static integer lsv;
static real tst, eps2;
#define E(I) e[(I)-1]
#define D(I) d[(I)-1]
*info = 0;
/* Quick return if possible */
if (*n < 0) {
*info = -1;
i__1 = -(*info);
xerbla_("SSTERF", &i__1);
return 0;
}
if (*n <= 1) {
return 0;
}
/* Determine the unit roundoff for this environment. */
eps = slamch_("E");
/* Computing 2nd power */
r__1 = eps;
eps2 = r__1 * r__1;
safmin = slamch_("S");
safmax = 1.f / safmin;
ssfmax = sqrt(safmax) / 3.f;
ssfmin = sqrt(safmin) / eps2;
/* Compute the eigenvalues of the tridiagonal matrix. */
nmaxit = *n * 30;
sigma = 0.f;
jtot = 0;
/* Determine where the matrix splits and choose QL or QR iteration
for each block, according to whether top or bottom diagonal
element is smaller. */
l1 = 1;
nm1 = *n - 1;
L10:
if (l1 > *n) {
goto L170;
}
if (l1 > 1) {
E(l1 - 1) = 0.f;
}
if (l1 <= nm1) {
i__1 = nm1;
for (m = l1; m <= nm1; ++m) {
tst = (r__1 = E(m), dabs(r__1));
if (tst == 0.f) {
goto L30;
}
if (tst <= sqrt((r__1 = D(m), dabs(r__1))) * sqrt((r__2 = D(m + 1)
, dabs(r__2))) * eps) {
E(m) = 0.f;
goto L30;
}
/* L20: */
}
}
m = *n;
L30:
l = l1;
lsv = l;
lend = m;
lendsv = lend;
l1 = m + 1;
if (lend == l) {
goto L10;
}
/* Scale submatrix in rows and columns L to LEND */
i__1 = lend - l + 1;
anorm = slanst_("I", &i__1, &D(l), &E(l));
iscale = 0;
if (anorm > ssfmax) {
iscale = 1;
i__1 = lend - l + 1;
slascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &D(l), n,
info);
i__1 = lend - l;
slascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &E(l), n,
info);
} else if (anorm < ssfmin) {
iscale = 2;
i__1 = lend - l + 1;
slascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &D(l), n,
info);
i__1 = lend - l;
slascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &E(l), n,
info);
}
i__1 = lend - 1;
for (i = l; i <= lend-1; ++i) {
/* Computing 2nd power */
r__1 = E(i);
E(i) = r__1 * r__1;
/* L40: */
}
/* Choose between QL and QR iteration */
if ((r__1 = D(lend), dabs(r__1)) < (r__2 = D(l), dabs(r__2))) {
lend = lsv;
l = lendsv;
}
if (lend >= l) {
/* QL Iteration
Look for small subdiagonal element. */
L50:
if (l != lend) {
lendm1 = lend - 1;
i__1 = lendm1;
for (m = l; m <= lendm1; ++m) {
tst = (r__1 = E(m), dabs(r__1));
if (tst <= eps2 * (r__1 = D(m) * D(m + 1), dabs(r__1))) {
goto L70;
}
/* L60: */
}
}
m = lend;
L70:
if (m < lend) {
E(m) = 0.f;
}
p = D(l);
if (m == l) {
goto L90;
}
/* If remaining matrix is 2 by 2, use SLAE2 to compute its
eigenvalues. */
if (m == l + 1) {
rte = sqrt(E(l));
slae2_(&D(l), &rte, &D(l + 1), &rt1, &rt2);
D(l) = rt1;
D(l + 1) = rt2;
E(l) = 0.f;
l += 2;
if (l <= lend) {
goto L50;
}
goto L150;
}
if (jtot == nmaxit) {
goto L150;
}
++jtot;
/* Form shift. */
rte = sqrt(E(l));
sigma = (D(l + 1) - p) / (rte * 2.f);
r = slapy2_(&sigma, &c_b32);
sigma = p - rte / (sigma + r_sign(&r, &sigma));
c = 1.f;
s = 0.f;
gamma = D(m) - sigma;
p = gamma * gamma;
/* Inner loop */
mm1 = m - 1;
i__1 = l;
for (i = mm1; i >= l; --i) {
bb = E(i);
r = p + bb;
if (i != m - 1) {
E(i + 1) = s * r;
}
oldc = c;
c = p / r;
s = bb / r;
oldgam = gamma;
alpha = D(i);
gamma = c * (alpha - sigma) - s * oldgam;
D(i + 1) = oldgam + (alpha - gamma);
if (c != 0.f) {
p = gamma * gamma / c;
} else {
p = oldc * bb;
}
/* L80: */
}
E(l) = s * p;
D(l) = sigma + gamma;
goto L50;
/* Eigenvalue found. */
L90:
D(l) = p;
++l;
if (l <= lend) {
goto L50;
}
goto L150;
} else {
/* QR Iteration
Look for small superdiagonal element. */
L100:
if (l != lend) {
lendp1 = lend + 1;
i__1 = lendp1;
for (m = l; m >= lendp1; --m) {
tst = (r__1 = E(m - 1), dabs(r__1));
if (tst <= eps2 * (r__1 = D(m) * D(m - 1), dabs(r__1))) {
goto L120;
}
/* L110: */
}
}
m = lend;
L120:
if (m > lend) {
E(m - 1) = 0.f;
}
p = D(l);
if (m == l) {
goto L140;
}
/* If remaining matrix is 2 by 2, use SLAE2 to compute its
eigenvalues. */
if (m == l - 1) {
rte = sqrt(E(l - 1));
slae2_(&D(l), &rte, &D(l - 1), &rt1, &rt2);
D(l) = rt1;
D(l - 1) = rt2;
E(l - 1) = 0.f;
l += -2;
if (l >= lend) {
goto L100;
}
goto L150;
}
if (jtot == nmaxit) {
goto L150;
}
++jtot;
/* Form shift. */
rte = sqrt(E(l - 1));
sigma = (D(l - 1) - p) / (rte * 2.f);
r = slapy2_(&sigma, &c_b32);
sigma = p - rte / (sigma + r_sign(&r, &sigma));
c = 1.f;
s = 0.f;
gamma = D(m) - sigma;
p = gamma * gamma;
/* Inner loop */
lm1 = l - 1;
i__1 = lm1;
for (i = m; i <= lm1; ++i) {
bb = E(i);
r = p + bb;
if (i != m) {
E(i - 1) = s * r;
}
oldc = c;
c = p / r;
s = bb / r;
oldgam = gamma;
alpha = D(i + 1);
gamma = c * (alpha - sigma) - s * oldgam;
D(i) = oldgam + (alpha - gamma);
if (c != 0.f) {
p = gamma * gamma / c;
} else {
p = oldc * bb;
}
/* L130: */
}
E(lm1) = s * p;
D(l) = sigma + gamma;
goto L100;
/* Eigenvalue found. */
L140:
D(l) = p;
--l;
if (l >= lend) {
goto L100;
}
goto L150;
}
/* Undo scaling if necessary */
L150:
if (iscale == 1) {
i__1 = lendsv - lsv + 1;
slascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &D(lsv), n,
info);
}
if (iscale == 2) {
i__1 = lendsv - lsv + 1;
slascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &D(lsv), n,
info);
}
/* Check for no convergence to an eigenvalue after a total
of N*MAXIT iterations. */
if (jtot == nmaxit) {
i__1 = *n - 1;
for (i = 1; i <= *n-1; ++i) {
if (E(i) != 0.f) {
++(*info);
}
/* L160: */
}
return 0;
}
goto L10;
/* Sort eigenvalues in increasing order. */
L170:
slasrt_("I", n, &D(1), info);
return 0;
/* End of SSTERF */
} /* ssterf_ */
/* Subroutine */ int ssterf_(integer *n, real *d__, real *e, integer *info)
{
/* System generated locals */
integer i__1;
real r__1, r__2, r__3;
/* Builtin functions */
double sqrt(doublereal), r_sign(real *, real *);
/* Local variables */
real c__;
integer i__, l, m;
real p, r__, s;
integer l1;
real bb, rt1, rt2, eps, rte;
integer lsv;
real eps2, oldc;
integer lend, jtot;
extern /* Subroutine */ int slae2_(real *, real *, real *, real *, real *)
;
real gamma, alpha, sigma, anorm;
extern doublereal slapy2_(real *, real *);
integer iscale;
real oldgam;
extern doublereal slamch_(char *);
real safmin;
extern /* Subroutine */ int xerbla_(char *, integer *);
real safmax;
extern /* Subroutine */ int slascl_(char *, integer *, integer *, real *,
real *, integer *, integer *, real *, integer *, integer *);
integer lendsv;
real ssfmin;
integer nmaxit;
real ssfmax;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int slasrt_(char *, integer *, real *, integer *);
/* -- LAPACK routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SSTERF computes all eigenvalues of a symmetric tridiagonal matrix */
/* using the Pal-Walker-Kahan variant of the QL or QR algorithm. */
/* Arguments */
/* ========= */
/* 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. */
/* On exit, if INFO = 0, the eigenvalues in ascending order. */
/* E (input/output) REAL array, dimension (N-1) */
/* On entry, the (n-1) subdiagonal elements of the tridiagonal */
/* matrix. */
/* On exit, E has been destroyed. */
/* INFO (output) INTEGER */
/* = 0: successful exit */
/* < 0: if INFO = -i, the i-th argument had an illegal value */
/* > 0: the algorithm failed to find all of the eigenvalues in */
/* a total of 30*N iterations; if INFO = i, then i */
/* elements of E have not converged to zero. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Test the input parameters. */
/* Parameter adjustments */
--e;
--d__;
/* Function Body */
*info = 0;
/* Quick return if possible */
if (*n < 0) {
*info = -1;
i__1 = -(*info);
xerbla_("SSTERF", &i__1);
return 0;
}
if (*n <= 1) {
return 0;
}
/* Determine the unit roundoff for this environment. */
eps = slamch_("E");
/* Computing 2nd power */
r__1 = eps;
eps2 = r__1 * r__1;
safmin = slamch_("S");
safmax = 1.f / safmin;
ssfmax = sqrt(safmax) / 3.f;
ssfmin = sqrt(safmin) / eps2;
/* Compute the eigenvalues of the tridiagonal matrix. */
nmaxit = *n * 30;
sigma = 0.f;
jtot = 0;
/* Determine where the matrix splits and choose QL or QR iteration */
/* for each block, according to whether top or bottom diagonal */
/* element is smaller. */
l1 = 1;
L10:
if (l1 > *n) {
goto L170;
}
if (l1 > 1) {
e[l1 - 1] = 0.f;
}
i__1 = *n - 1;
for (m = l1; m <= i__1; ++m) {
if ((r__3 = e[m], dabs(r__3)) <= sqrt((r__1 = d__[m], dabs(r__1))) *
sqrt((r__2 = d__[m + 1], dabs(r__2))) * eps) {
e[m] = 0.f;
goto L30;
}
/* L20: */
}
m = *n;
L30:
l = l1;
lsv = l;
lend = m;
lendsv = lend;
l1 = m + 1;
if (lend == l) {
goto L10;
}
/* Scale submatrix in rows and columns L to LEND */
i__1 = lend - l + 1;
anorm = slanst_("I", &i__1, &d__[l], &e[l]);
iscale = 0;
if (anorm > ssfmax) {
iscale = 1;
i__1 = lend - l + 1;
slascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &d__[l], n,
info);
i__1 = lend - l;
slascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &e[l], n,
info);
} else if (anorm < ssfmin) {
iscale = 2;
i__1 = lend - l + 1;
slascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &d__[l], n,
info);
i__1 = lend - l;
slascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &e[l], n,
info);
}
i__1 = lend - 1;
for (i__ = l; i__ <= i__1; ++i__) {
/* Computing 2nd power */
r__1 = e[i__];
e[i__] = r__1 * r__1;
/* L40: */
}
/* Choose between QL and QR iteration */
if ((r__1 = d__[lend], dabs(r__1)) < (r__2 = d__[l], dabs(r__2))) {
lend = lsv;
l = lendsv;
}
if (lend >= l) {
/* QL Iteration */
/* Look for small subdiagonal element. */
L50:
if (l != lend) {
i__1 = lend - 1;
for (m = l; m <= i__1; ++m) {
if ((r__2 = e[m], dabs(r__2)) <= eps2 * (r__1 = d__[m] * d__[
m + 1], dabs(r__1))) {
goto L70;
}
/* L60: */
}
}
m = lend;
L70:
if (m < lend) {
e[m] = 0.f;
}
p = d__[l];
if (m == l) {
goto L90;
}
/* If remaining matrix is 2 by 2, use SLAE2 to compute its */
/* eigenvalues. */
if (m == l + 1) {
rte = sqrt(e[l]);
slae2_(&d__[l], &rte, &d__[l + 1], &rt1, &rt2);
d__[l] = rt1;
d__[l + 1] = rt2;
e[l] = 0.f;
l += 2;
if (l <= lend) {
goto L50;
}
goto L150;
}
if (jtot == nmaxit) {
goto L150;
}
++jtot;
/* Form shift. */
rte = sqrt(e[l]);
sigma = (d__[l + 1] - p) / (rte * 2.f);
r__ = slapy2_(&sigma, &c_b32);
sigma = p - rte / (sigma + r_sign(&r__, &sigma));
c__ = 1.f;
s = 0.f;
gamma = d__[m] - sigma;
p = gamma * gamma;
/* Inner loop */
i__1 = l;
for (i__ = m - 1; i__ >= i__1; --i__) {
bb = e[i__];
r__ = p + bb;
if (i__ != m - 1) {
e[i__ + 1] = s * r__;
}
oldc = c__;
c__ = p / r__;
s = bb / r__;
oldgam = gamma;
alpha = d__[i__];
gamma = c__ * (alpha - sigma) - s * oldgam;
d__[i__ + 1] = oldgam + (alpha - gamma);
if (c__ != 0.f) {
p = gamma * gamma / c__;
} else {
p = oldc * bb;
}
/* L80: */
}
e[l] = s * p;
d__[l] = sigma + gamma;
goto L50;
/* Eigenvalue found. */
L90:
d__[l] = p;
++l;
if (l <= lend) {
goto L50;
}
goto L150;
} else {
/* QR Iteration */
/* Look for small superdiagonal element. */
L100:
i__1 = lend + 1;
for (m = l; m >= i__1; --m) {
if ((r__2 = e[m - 1], dabs(r__2)) <= eps2 * (r__1 = d__[m] * d__[
m - 1], dabs(r__1))) {
goto L120;
}
/* L110: */
}
m = lend;
L120:
if (m > lend) {
e[m - 1] = 0.f;
}
p = d__[l];
if (m == l) {
goto L140;
}
/* If remaining matrix is 2 by 2, use SLAE2 to compute its */
/* eigenvalues. */
if (m == l - 1) {
rte = sqrt(e[l - 1]);
slae2_(&d__[l], &rte, &d__[l - 1], &rt1, &rt2);
d__[l] = rt1;
d__[l - 1] = rt2;
e[l - 1] = 0.f;
l += -2;
if (l >= lend) {
goto L100;
}
goto L150;
}
if (jtot == nmaxit) {
goto L150;
}
++jtot;
/* Form shift. */
rte = sqrt(e[l - 1]);
sigma = (d__[l - 1] - p) / (rte * 2.f);
r__ = slapy2_(&sigma, &c_b32);
sigma = p - rte / (sigma + r_sign(&r__, &sigma));
c__ = 1.f;
s = 0.f;
gamma = d__[m] - sigma;
p = gamma * gamma;
/* Inner loop */
i__1 = l - 1;
for (i__ = m; i__ <= i__1; ++i__) {
bb = e[i__];
r__ = p + bb;
if (i__ != m) {
e[i__ - 1] = s * r__;
}
oldc = c__;
c__ = p / r__;
s = bb / r__;
oldgam = gamma;
alpha = d__[i__ + 1];
gamma = c__ * (alpha - sigma) - s * oldgam;
d__[i__] = oldgam + (alpha - gamma);
if (c__ != 0.f) {
p = gamma * gamma / c__;
} else {
p = oldc * bb;
}
/* L130: */
}
e[l - 1] = s * p;
d__[l] = sigma + gamma;
goto L100;
/* Eigenvalue found. */
L140:
d__[l] = p;
--l;
if (l >= lend) {
goto L100;
}
goto L150;
}
/* Undo scaling if necessary */
L150:
if (iscale == 1) {
i__1 = lendsv - lsv + 1;
slascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &d__[lsv],
n, info);
}
if (iscale == 2) {
i__1 = lendsv - lsv + 1;
slascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &d__[lsv],
n, info);
}
/* Check for no convergence to an eigenvalue after a total */
/* of N*MAXIT iterations. */
if (jtot < nmaxit) {
goto L10;
}
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
if (e[i__] != 0.f) {
++(*info);
}
/* L160: */
}
goto L180;
/* Sort eigenvalues in increasing order. */
L170:
slasrt_("I", n, &d__[1], info);
L180:
return 0;
/* End of SSTERF */
} /* ssterf_ */
/* Subroutine */ int sstevd_(char *jobz, integer *n, real *d, real *e, real *
z, integer *ldz, real *work, integer *lwork, integer *iwork, integer *
liwork, integer *info)
{
/* -- LAPACK driver routine (version 2.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
September 30, 1994
Purpose
=======
SSTEVD computes all eigenvalues and, optionally, eigenvectors of a
real symmetric tridiagonal matrix. If eigenvectors are desired, it
uses a divide and conquer algorithm.
The divide and conquer algorithm makes very mild assumptions about
floating point arithmetic. It will work on machines with a guard
digit in add/subtract, or on those binary machines without guard
digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
Cray-2. It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none.
Arguments
=========
JOBZ (input) CHARACTER*1
= 'N': Compute eigenvalues only;
= 'V': Compute eigenvalues and eigenvectors.
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
A.
On exit, if INFO = 0, the eigenvalues in ascending order.
E (input/output) REAL array, dimension (N)
On entry, the (n-1) subdiagonal elements of the tridiagonal
matrix A, stored in elements 1 to N-1 of E; E(N) need not
be set, but is used by the routine.
On exit, the contents of E are destroyed.
Z (output) REAL array, dimension (LDZ, N)
If JOBZ = 'V', then if INFO = 0, Z contains the orthonormal
eigenvectors of the matrix A, with the i-th column of Z
holding the eigenvector associated with D(i).
If JOBZ = 'N', then Z is not referenced.
LDZ (input) INTEGER
The leading dimension of the array Z. LDZ >= 1, and if
JOBZ = 'V', LDZ >= max(1,N).
WORK (workspace/output) REAL array,
dimension (LWORK)
On exit, if LWORK > 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If JOBZ = 'N' or N <= 1 then LWORK must be at least 1.
If JOBZ = 'V' and N > 1 then LWORK must be at least
( 1 + 3*N + 2*N*lg N + 2*N**2 ),
where lg( N ) = smallest integer k such
that 2**k >= N.
IWORK (workspace/output) INTEGER array, dimension (LIWORK)
On exit, if LIWORK > 0, IWORK(1) returns the optimal LIWORK.
LIWORK (input) INTEGER
The dimension of the array IWORK.
If JOBZ = 'N' or N <= 1 then LIWORK must be at least 1.
If JOBZ = 'V' and N > 1 then LIWORK must be at least 2+5*N.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, the algorithm failed to converge; i
off-diagonal elements of E did not converge to zero.
=====================================================================
Test the input parameters.
Parameter adjustments
Function Body */
/* Table of constant values */
static integer c__2 = 2;
static integer c__1 = 1;
/* System generated locals */
integer z_dim1, z_offset, i__1;
real r__1;
/* Builtin functions */
double log(doublereal);
integer pow_ii(integer *, integer *);
double sqrt(doublereal);
/* Local variables */
static real rmin, rmax, tnrm, sigma;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int sscal_(integer *, real *, real *, integer *);
static integer lwmin;
static logical wantz;
static integer iscale;
extern doublereal slamch_(char *);
static real safmin;
extern /* Subroutine */ int xerbla_(char *, integer *);
static real bignum;
extern /* Subroutine */ int sstedc_(char *, integer *, real *, real *,
real *, integer *, real *, integer *, integer *, integer *,
integer *);
static integer liwmin;
extern doublereal slanst_(char *, integer *, real *, real *);
extern /* Subroutine */ int ssterf_(integer *, real *, real *, integer *);
static real smlnum;
static integer lgn;
static real eps;
#define D(I) d[(I)-1]
#define E(I) e[(I)-1]
#define WORK(I) work[(I)-1]
#define IWORK(I) iwork[(I)-1]
#define Z(I,J) z[(I)-1 + ((J)-1)* ( *ldz)]
wantz = lsame_(jobz, "V");
*info = 0;
liwmin = 1;
lwmin = 1;
if (! (wantz || lsame_(jobz, "N"))) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*ldz < 1 || wantz && *ldz < *n) {
*info = -6;
} else if (*n > 1 && wantz) {
lgn = (integer) (log((real) (*n)) / log(2.f));
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
/* Computing 2nd power */
i__1 = *n;
lwmin = *n * 3 + 1 + (*n << 1) * lgn + (i__1 * i__1 << 1);
liwmin = *n * 5 + 2;
if (*lwork < lwmin) {
*info = -8;
} else if (*liwork < liwmin) {
*info = -10;
}
} else if (*lwork < 1) {
*info = -8;
} else if (*liwork < 1) {
*info = -10;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SSTEVD", &i__1);
goto L10;
}
/* Quick return if possible */
if (*n == 0) {
goto L10;
}
if (*n == 1) {
if (wantz) {
Z(1,1) = 1.f;
}
goto L10;
}
/* Get machine constants. */
safmin = slamch_("Safe minimum");
eps = slamch_("Precision");
smlnum = safmin / eps;
bignum = 1.f / smlnum;
rmin = sqrt(smlnum);
rmax = sqrt(bignum);
/* Scale matrix to allowable range, if necessary. */
iscale = 0;
tnrm = slanst_("M", n, &D(1), &E(1));
if (tnrm > 0.f && tnrm < rmin) {
iscale = 1;
sigma = rmin / tnrm;
} else if (tnrm > rmax) {
iscale = 1;
sigma = rmax / tnrm;
}
if (iscale == 1) {
sscal_(n, &sigma, &D(1), &c__1);
i__1 = *n - 1;
sscal_(&i__1, &sigma, &E(1), &c__1);
}
/* For eigenvalues only, call SSTERF. For eigenvalues and
eigenvectors, call SSTEDC. */
if (! wantz) {
ssterf_(n, &D(1), &E(1), info);
} else {
sstedc_("I", n, &D(1), &E(1), &Z(1,1), ldz, &WORK(1), lwork, &
IWORK(1), liwork, info);
}
/* If matrix was scaled, then rescale eigenvalues appropriately. */
if (iscale == 1) {
r__1 = 1.f / sigma;
sscal_(n, &r__1, &D(1), &c__1);
}
L10:
if (*lwork > 0) {
WORK(1) = (real) lwmin;
}
if (*liwork > 0) {
IWORK(1) = liwmin;
}
return 0;
/* End of SSTEVD */
} /* sstevd_ */
/* Subroutine */ int sdrvpt_(logical *dotype, integer *nn, integer *nval,
integer *nrhs, real *thresh, logical *tsterr, real *a, real *d__,
real *e, real *b, real *x, real *xact, real *work, real *rwork,
integer *nout)
{
/* Initialized data */
static integer iseedy[4] = { 0,0,0,1 };
/* Format strings */
static char fmt_9999[] = "(1x,a,\002, N =\002,i5,\002, type \002,i2,\002"
", test \002,i2,\002, ratio = \002,g12.5)";
static char fmt_9998[] = "(1x,a,\002, FACT='\002,a1,\002', N =\002,i5"
",\002, type \002,i2,\002, test \002,i2,\002, ratio = \002,g12.5)";
/* System generated locals */
integer i__1, i__2, i__3, i__4;
real r__1, r__2, r__3;
/* Local variables */
integer i__, j, k, n;
real z__[3];
integer k1, ia, in, kl, ku, ix, nt, lda;
char fact[1];
real cond;
integer mode;
real dmax__;
integer imat, info;
char path[3], dist[1], type__[1];
integer nrun, ifact, nfail, iseed[4];
real rcond;
integer nimat;
real anorm;
integer izero, nerrs;
logical zerot;
real rcondc;
real ainvnm;
real result[6];
/* Fortran I/O blocks */
static cilist io___35 = { 0, 0, 0, fmt_9999, 0 };
static cilist io___38 = { 0, 0, 0, fmt_9998, 0 };
/* -- LAPACK test routine (version 3.1) -- */
/* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
/* November 2006 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* Purpose */
/* ======= */
/* SDRVPT tests SPTSV and -SVX. */
/* Arguments */
/* ========= */
/* DOTYPE (input) LOGICAL array, dimension (NTYPES) */
/* The matrix types to be used for testing. Matrices of type j */
/* (for 1 <= j <= NTYPES) are used for testing if DOTYPE(j) = */
/* .TRUE.; if DOTYPE(j) = .FALSE., then type j is not used. */
/* NN (input) INTEGER */
/* The number of values of N contained in the vector NVAL. */
/* NVAL (input) INTEGER array, dimension (NN) */
/* The values of the matrix dimension N. */
/* NRHS (input) INTEGER */
/* The number of right hand side vectors to be generated for */
/* each linear system. */
/* THRESH (input) REAL */
/* The threshold value for the test ratios. A result is */
/* included in the output file if RESULT >= THRESH. To have */
/* every test ratio printed, use THRESH = 0. */
/* TSTERR (input) LOGICAL */
/* Flag that indicates whether error exits are to be tested. */
/* A (workspace) REAL array, dimension (NMAX*2) */
/* D (workspace) REAL array, dimension (NMAX*2) */
/* E (workspace) REAL array, dimension (NMAX*2) */
/* B (workspace) REAL array, dimension (NMAX*NRHS) */
/* X (workspace) REAL array, dimension (NMAX*NRHS) */
/* XACT (workspace) REAL array, dimension (NMAX*NRHS) */
/* WORK (workspace) REAL array, dimension */
/* (NMAX*max(3,NRHS)) */
/* RWORK (workspace) REAL array, dimension */
/* (max(NMAX,2*NRHS)) */
/* NOUT (input) INTEGER */
/* The unit number for output. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. Local Arrays .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Scalars in Common .. */
/* .. */
/* .. Common blocks .. */
/* .. */
/* .. Data statements .. */
/* Parameter adjustments */
--rwork;
--work;
--xact;
--x;
--b;
--e;
--d__;
--a;
--nval;
--dotype;
/* Function Body */
/* .. */
/* .. Executable Statements .. */
s_copy(path, "Single precision", (ftnlen)1, (ftnlen)16);
s_copy(path + 1, "PT", (ftnlen)2, (ftnlen)2);
nrun = 0;
nfail = 0;
nerrs = 0;
for (i__ = 1; i__ <= 4; ++i__) {
iseed[i__ - 1] = iseedy[i__ - 1];
/* L10: */
}
/* Test the error exits */
if (*tsterr) {
serrvx_(path, nout);
}
infoc_1.infot = 0;
i__1 = *nn;
for (in = 1; in <= i__1; ++in) {
/* Do for each value of N in NVAL. */
n = nval[in];
lda = max(1,n);
nimat = 12;
if (n <= 0) {
nimat = 1;
}
i__2 = nimat;
for (imat = 1; imat <= i__2; ++imat) {
/* Do the tests only if DOTYPE( IMAT ) is true. */
if (n > 0 && ! dotype[imat]) {
goto L110;
}
/* Set up parameters with SLATB4. */
slatb4_(path, &imat, &n, &n, type__, &kl, &ku, &anorm, &mode, &
cond, dist);
zerot = imat >= 8 && imat <= 10;
if (imat <= 6) {
/* Type 1-6: generate a symmetric tridiagonal matrix of */
/* known condition number in lower triangular band storage. */
s_copy(srnamc_1.srnamt, "SLATMS", (ftnlen)32, (ftnlen)6);
slatms_(&n, &n, dist, iseed, type__, &rwork[1], &mode, &cond,
&anorm, &kl, &ku, "B", &a[1], &c__2, &work[1], &info);
/* Check the error code from SLATMS. */
if (info != 0) {
alaerh_(path, "SLATMS", &info, &c__0, " ", &n, &n, &kl, &
ku, &c_n1, &imat, &nfail, &nerrs, nout);
goto L110;
}
izero = 0;
/* Copy the matrix to D and E. */
ia = 1;
i__3 = n - 1;
for (i__ = 1; i__ <= i__3; ++i__) {
d__[i__] = a[ia];
e[i__] = a[ia + 1];
ia += 2;
/* L20: */
}
if (n > 0) {
d__[n] = a[ia];
}
} else {
/* Type 7-12: generate a diagonally dominant matrix with */
/* unknown condition number in the vectors D and E. */
if (! zerot || ! dotype[7]) {
/* Let D and E have values from [-1,1]. */
slarnv_(&c__2, iseed, &n, &d__[1]);
i__3 = n - 1;
slarnv_(&c__2, iseed, &i__3, &e[1]);
/* Make the tridiagonal matrix diagonally dominant. */
if (n == 1) {
d__[1] = dabs(d__[1]);
} else {
d__[1] = dabs(d__[1]) + dabs(e[1]);
d__[n] = (r__1 = d__[n], dabs(r__1)) + (r__2 = e[n -
1], dabs(r__2));
i__3 = n - 1;
for (i__ = 2; i__ <= i__3; ++i__) {
d__[i__] = (r__1 = d__[i__], dabs(r__1)) + (r__2 =
e[i__], dabs(r__2)) + (r__3 = e[i__ - 1],
dabs(r__3));
/* L30: */
}
}
/* Scale D and E so the maximum element is ANORM. */
ix = isamax_(&n, &d__[1], &c__1);
dmax__ = d__[ix];
r__1 = anorm / dmax__;
sscal_(&n, &r__1, &d__[1], &c__1);
if (n > 1) {
i__3 = n - 1;
r__1 = anorm / dmax__;
sscal_(&i__3, &r__1, &e[1], &c__1);
}
} else if (izero > 0) {
/* Reuse the last matrix by copying back the zeroed out */
/* elements. */
if (izero == 1) {
d__[1] = z__[1];
if (n > 1) {
e[1] = z__[2];
}
} else if (izero == n) {
e[n - 1] = z__[0];
d__[n] = z__[1];
} else {
e[izero - 1] = z__[0];
d__[izero] = z__[1];
e[izero] = z__[2];
}
}
/* For types 8-10, set one row and column of the matrix to */
/* zero. */
izero = 0;
if (imat == 8) {
izero = 1;
z__[1] = d__[1];
d__[1] = 0.f;
if (n > 1) {
z__[2] = e[1];
e[1] = 0.f;
}
} else if (imat == 9) {
izero = n;
if (n > 1) {
z__[0] = e[n - 1];
e[n - 1] = 0.f;
}
z__[1] = d__[n];
d__[n] = 0.f;
} else if (imat == 10) {
izero = (n + 1) / 2;
if (izero > 1) {
z__[0] = e[izero - 1];
z__[2] = e[izero];
e[izero - 1] = 0.f;
e[izero] = 0.f;
}
z__[1] = d__[izero];
d__[izero] = 0.f;
}
}
/* Generate NRHS random solution vectors. */
ix = 1;
i__3 = *nrhs;
for (j = 1; j <= i__3; ++j) {
slarnv_(&c__2, iseed, &n, &xact[ix]);
ix += lda;
/* L40: */
}
/* Set the right hand side. */
slaptm_(&n, nrhs, &c_b23, &d__[1], &e[1], &xact[1], &lda, &c_b24,
&b[1], &lda);
for (ifact = 1; ifact <= 2; ++ifact) {
if (ifact == 1) {
*(unsigned char *)fact = 'F';
} else {
*(unsigned char *)fact = 'N';
}
/* Compute the condition number for comparison with */
/* the value returned by SPTSVX. */
if (zerot) {
if (ifact == 1) {
goto L100;
}
rcondc = 0.f;
} else if (ifact == 1) {
/* Compute the 1-norm of A. */
anorm = slanst_("1", &n, &d__[1], &e[1]);
scopy_(&n, &d__[1], &c__1, &d__[n + 1], &c__1);
if (n > 1) {
i__3 = n - 1;
scopy_(&i__3, &e[1], &c__1, &e[n + 1], &c__1);
}
/* Factor the matrix A. */
spttrf_(&n, &d__[n + 1], &e[n + 1], &info);
/* Use SPTTRS to solve for one column at a time of */
/* inv(A), computing the maximum column sum as we go. */
ainvnm = 0.f;
i__3 = n;
for (i__ = 1; i__ <= i__3; ++i__) {
i__4 = n;
for (j = 1; j <= i__4; ++j) {
x[j] = 0.f;
/* L50: */
}
x[i__] = 1.f;
spttrs_(&n, &c__1, &d__[n + 1], &e[n + 1], &x[1], &
lda, &info);
/* Computing MAX */
r__1 = ainvnm, r__2 = sasum_(&n, &x[1], &c__1);
ainvnm = dmax(r__1,r__2);
/* L60: */
}
/* Compute the 1-norm condition number of A. */
if (anorm <= 0.f || ainvnm <= 0.f) {
rcondc = 1.f;
} else {
rcondc = 1.f / anorm / ainvnm;
}
}
if (ifact == 2) {
/* --- Test SPTSV -- */
scopy_(&n, &d__[1], &c__1, &d__[n + 1], &c__1);
if (n > 1) {
i__3 = n - 1;
scopy_(&i__3, &e[1], &c__1, &e[n + 1], &c__1);
}
slacpy_("Full", &n, nrhs, &b[1], &lda, &x[1], &lda);
/* Factor A as L*D*L' and solve the system A*X = B. */
s_copy(srnamc_1.srnamt, "SPTSV ", (ftnlen)32, (ftnlen)6);
sptsv_(&n, nrhs, &d__[n + 1], &e[n + 1], &x[1], &lda, &
info);
/* Check error code from SPTSV . */
if (info != izero) {
alaerh_(path, "SPTSV ", &info, &izero, " ", &n, &n, &
c__1, &c__1, nrhs, &imat, &nfail, &nerrs,
nout);
}
nt = 0;
if (izero == 0) {
/* Check the factorization by computing the ratio */
/* norm(L*D*L' - A) / (n * norm(A) * EPS ) */
sptt01_(&n, &d__[1], &e[1], &d__[n + 1], &e[n + 1], &
work[1], result);
/* Compute the residual in the solution. */
slacpy_("Full", &n, nrhs, &b[1], &lda, &work[1], &lda);
sptt02_(&n, nrhs, &d__[1], &e[1], &x[1], &lda, &work[
1], &lda, &result[1]);
/* Check solution from generated exact solution. */
sget04_(&n, nrhs, &x[1], &lda, &xact[1], &lda, &
rcondc, &result[2]);
nt = 3;
}
/* Print information about the tests that did not pass */
/* the threshold. */
i__3 = nt;
for (k = 1; k <= i__3; ++k) {
if (result[k - 1] >= *thresh) {
if (nfail == 0 && nerrs == 0) {
aladhd_(nout, path);
}
io___35.ciunit = *nout;
s_wsfe(&io___35);
do_fio(&c__1, "SPTSV ", (ftnlen)6);
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer))
;
do_fio(&c__1, (char *)&imat, (ftnlen)sizeof(
integer));
do_fio(&c__1, (char *)&k, (ftnlen)sizeof(integer))
;
do_fio(&c__1, (char *)&result[k - 1], (ftnlen)
sizeof(real));
e_wsfe();
++nfail;
}
/* L70: */
}
nrun += nt;
}
/* --- Test SPTSVX --- */
if (ifact > 1) {
/* Initialize D( N+1:2*N ) and E( N+1:2*N ) to zero. */
i__3 = n - 1;
for (i__ = 1; i__ <= i__3; ++i__) {
d__[n + i__] = 0.f;
e[n + i__] = 0.f;
/* L80: */
}
if (n > 0) {
d__[n + n] = 0.f;
}
}
slaset_("Full", &n, nrhs, &c_b24, &c_b24, &x[1], &lda);
/* Solve the system and compute the condition number and */
/* error bounds using SPTSVX. */
s_copy(srnamc_1.srnamt, "SPTSVX", (ftnlen)32, (ftnlen)6);
sptsvx_(fact, &n, nrhs, &d__[1], &e[1], &d__[n + 1], &e[n + 1]
, &b[1], &lda, &x[1], &lda, &rcond, &rwork[1], &rwork[
*nrhs + 1], &work[1], &info);
/* Check the error code from SPTSVX. */
if (info != izero) {
alaerh_(path, "SPTSVX", &info, &izero, fact, &n, &n, &
c__1, &c__1, nrhs, &imat, &nfail, &nerrs, nout);
}
if (izero == 0) {
if (ifact == 2) {
/* Check the factorization by computing the ratio */
/* norm(L*D*L' - A) / (n * norm(A) * EPS ) */
k1 = 1;
sptt01_(&n, &d__[1], &e[1], &d__[n + 1], &e[n + 1], &
work[1], result);
} else {
k1 = 2;
}
/* Compute the residual in the solution. */
slacpy_("Full", &n, nrhs, &b[1], &lda, &work[1], &lda);
sptt02_(&n, nrhs, &d__[1], &e[1], &x[1], &lda, &work[1], &
lda, &result[1]);
/* Check solution from generated exact solution. */
sget04_(&n, nrhs, &x[1], &lda, &xact[1], &lda, &rcondc, &
result[2]);
/* Check error bounds from iterative refinement. */
sptt05_(&n, nrhs, &d__[1], &e[1], &b[1], &lda, &x[1], &
lda, &xact[1], &lda, &rwork[1], &rwork[*nrhs + 1],
&result[3]);
} else {
k1 = 6;
}
/* Check the reciprocal of the condition number. */
result[5] = sget06_(&rcond, &rcondc);
/* Print information about the tests that did not pass */
/* the threshold. */
for (k = k1; k <= 6; ++k) {
if (result[k - 1] >= *thresh) {
if (nfail == 0 && nerrs == 0) {
aladhd_(nout, path);
}
io___38.ciunit = *nout;
s_wsfe(&io___38);
do_fio(&c__1, "SPTSVX", (ftnlen)6);
do_fio(&c__1, fact, (ftnlen)1);
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&imat, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&k, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&result[k - 1], (ftnlen)sizeof(
real));
e_wsfe();
++nfail;
}
/* L90: */
}
nrun = nrun + 7 - k1;
L100:
;
}
L110:
;
}
/* L120: */
}
/* Print a summary of the results. */
alasvm_(path, nout, &nfail, &nrun, &nerrs);
return 0;
/* End of SDRVPT */
} /* sdrvpt_ */
/* Subroutine */ int sbdsdc_(char *uplo, char *compq, integer *n, real *d__,
real *e, real *u, integer *ldu, real *vt, integer *ldvt, real *q,
integer *iq, real *work, integer *iwork, integer *info)
{
/* System generated locals */
integer u_dim1, u_offset, vt_dim1, vt_offset, i__1, i__2;
real r__1;
/* Builtin functions */
double r_sign(real *, real *), log(doublereal);
/* Local variables */
static integer difl, difr, ierr, perm, mlvl, sqre, i__, j, k;
static real p, r__;
static integer z__;
extern logical lsame_(char *, char *);
static integer poles;
extern /* Subroutine */ int slasr_(char *, char *, char *, integer *,
integer *, real *, real *, real *, integer *);
static integer iuplo, nsize, start;
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *), sswap_(integer *, real *, integer *, real *, integer *
), slasd0_(integer *, integer *, real *, real *, real *, integer *
, real *, integer *, integer *, integer *, real *, integer *);
static integer ic, ii, kk;
static real cs;
static integer is, iu;
static real sn;
extern doublereal slamch_(char *);
extern /* Subroutine */ int slasda_(integer *, integer *, integer *,
integer *, real *, real *, real *, integer *, real *, integer *,
real *, real *, real *, real *, integer *, integer *, integer *,
integer *, real *, real *, real *, real *, integer *, integer *),
xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int slascl_(char *, integer *, integer *, real *,
real *, integer *, integer *, real *, integer *, integer *);
static integer givcol;
extern /* Subroutine */ int slasdq_(char *, integer *, integer *, integer
*, integer *, integer *, real *, real *, real *, integer *, real *
, integer *, real *, integer *, real *, integer *);
static integer icompq;
extern /* Subroutine */ int slaset_(char *, integer *, integer *, real *,
real *, real *, integer *), slartg_(real *, real *, real *
, real *, real *);
static real orgnrm;
static integer givnum;
extern doublereal slanst_(char *, integer *, real *, real *);
static integer givptr, nm1, qstart, smlsiz, wstart, smlszp;
static real eps;
static integer ivt;
#define u_ref(a_1,a_2) u[(a_2)*u_dim1 + a_1]
#define vt_ref(a_1,a_2) vt[(a_2)*vt_dim1 + a_1]
/* -- LAPACK routine (instrumented to count ops, version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
October 31, 1999
Purpose
=======
SBDSDC computes the singular value decomposition (SVD) of a real
N-by-N (upper or lower) bidiagonal matrix B: B = U * S * VT,
using a divide and conquer method, where S is a diagonal matrix
with non-negative diagonal elements (the singular values of B), and
U and VT are orthogonal matrices of left and right singular vectors,
respectively. SBDSDC can be used to compute all singular values,
and optionally, singular vectors or singular vectors in compact form.
This code makes very mild assumptions about floating point
arithmetic. It will work on machines with a guard digit in
add/subtract, or on those binary machines without guard digits
which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2.
It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none. See SLASD3 for details.
The code currently call SLASDQ if singular values only are desired.
However, it can be slightly modified to compute singular values
using the divide and conquer method.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': B is upper bidiagonal.
= 'L': B is lower bidiagonal.
COMPQ (input) CHARACTER*1
Specifies whether singular vectors are to be computed
as follows:
= 'N': Compute singular values only;
= 'P': Compute singular values and compute singular
vectors in compact form;
= 'I': Compute singular values and singular vectors.
N (input) INTEGER
The order of the matrix B. N >= 0.
D (input/output) REAL array, dimension (N)
On entry, the n diagonal elements of the bidiagonal matrix B.
On exit, if INFO=0, the singular values of B.
E (input/output) REAL array, dimension (N)
On entry, the elements of E contain the offdiagonal
elements of the bidiagonal matrix whose SVD is desired.
On exit, E has been destroyed.
U (output) REAL array, dimension (LDU,N)
If COMPQ = 'I', then:
On exit, if INFO = 0, U contains the left singular vectors
of the bidiagonal matrix.
For other values of COMPQ, U is not referenced.
LDU (input) INTEGER
The leading dimension of the array U. LDU >= 1.
If singular vectors are desired, then LDU >= max( 1, N ).
VT (output) REAL array, dimension (LDVT,N)
If COMPQ = 'I', then:
On exit, if INFO = 0, VT' contains the right singular
vectors of the bidiagonal matrix.
For other values of COMPQ, VT is not referenced.
LDVT (input) INTEGER
The leading dimension of the array VT. LDVT >= 1.
If singular vectors are desired, then LDVT >= max( 1, N ).
Q (output) REAL array, dimension (LDQ)
If COMPQ = 'P', then:
On exit, if INFO = 0, Q and IQ contain the left
and right singular vectors in a compact form,
requiring O(N log N) space instead of 2*N**2.
In particular, Q contains all the REAL data in
LDQ >= N*(11 + 2*SMLSIZ + 8*INT(LOG_2(N/(SMLSIZ+1))))
words of memory, where SMLSIZ is returned by ILAENV and
is equal to the maximum size of the subproblems at the
bottom of the computation tree (usually about 25).
For other values of COMPQ, Q is not referenced.
IQ (output) INTEGER array, dimension (LDIQ)
If COMPQ = 'P', then:
On exit, if INFO = 0, Q and IQ contain the left
and right singular vectors in a compact form,
requiring O(N log N) space instead of 2*N**2.
In particular, IQ contains all INTEGER data in
LDIQ >= N*(3 + 3*INT(LOG_2(N/(SMLSIZ+1))))
words of memory, where SMLSIZ is returned by ILAENV and
is equal to the maximum size of the subproblems at the
bottom of the computation tree (usually about 25).
For other values of COMPQ, IQ is not referenced.
WORK (workspace) REAL array, dimension (LWORK)
If COMPQ = 'N' then LWORK >= (4 * N).
If COMPQ = 'P' then LWORK >= (6 * N).
If COMPQ = 'I' then LWORK >= (3 * N**2 + 4 * N).
IWORK (workspace) INTEGER array, dimension (7*N)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: The algorithm failed to compute an singular value.
The update process of divide and conquer failed.
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters.
Parameter adjustments */
--d__;
--e;
u_dim1 = *ldu;
u_offset = 1 + u_dim1 * 1;
u -= u_offset;
vt_dim1 = *ldvt;
vt_offset = 1 + vt_dim1 * 1;
vt -= vt_offset;
--q;
--iq;
--work;
--iwork;
/* Function Body */
*info = 0;
iuplo = 0;
if (lsame_(uplo, "U")) {
iuplo = 1;
}
if (lsame_(uplo, "L")) {
iuplo = 2;
}
if (lsame_(compq, "N")) {
icompq = 0;
} else if (lsame_(compq, "P")) {
icompq = 1;
} else if (lsame_(compq, "I")) {
icompq = 2;
} else {
icompq = -1;
}
if (iuplo == 0) {
*info = -1;
} else if (icompq < 0) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*ldu < 1 || icompq == 2 && *ldu < *n) {
*info = -7;
} else if (*ldvt < 1 || icompq == 2 && *ldvt < *n) {
*info = -9;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("SBDSDC", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
smlsiz = ilaenv_(&c__9, "SBDSDC", " ", &c__0, &c__0, &c__0, &c__0, (
ftnlen)6, (ftnlen)1);
if (*n == 1) {
if (icompq == 1) {
q[1] = r_sign(&c_b15, &d__[1]);
q[smlsiz * *n + 1] = 1.f;
} else if (icompq == 2) {
u_ref(1, 1) = r_sign(&c_b15, &d__[1]);
vt_ref(1, 1) = 1.f;
}
d__[1] = dabs(d__[1]);
return 0;
}
nm1 = *n - 1;
/* If matrix lower bidiagonal, rotate to be upper bidiagonal
by applying Givens rotations on the left */
wstart = 1;
qstart = 3;
if (icompq == 1) {
scopy_(n, &d__[1], &c__1, &q[1], &c__1);
i__1 = *n - 1;
scopy_(&i__1, &e[1], &c__1, &q[*n + 1], &c__1);
}
if (iuplo == 2) {
qstart = 5;
wstart = (*n << 1) - 1;
latime_1.ops += (real) (*n - 1 << 3);
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
slartg_(&d__[i__], &e[i__], &cs, &sn, &r__);
d__[i__] = r__;
e[i__] = sn * d__[i__ + 1];
d__[i__ + 1] = cs * d__[i__ + 1];
if (icompq == 1) {
q[i__ + (*n << 1)] = cs;
q[i__ + *n * 3] = sn;
} else if (icompq == 2) {
work[i__] = cs;
work[nm1 + i__] = -sn;
}
/* L10: */
}
}
/* If ICOMPQ = 0, use SLASDQ to compute the singular values. */
if (icompq == 0) {
slasdq_("U", &c__0, n, &c__0, &c__0, &c__0, &d__[1], &e[1], &vt[
vt_offset], ldvt, &u[u_offset], ldu, &u[u_offset], ldu, &work[
wstart], info);
goto L40;
}
/* If N is smaller than the minimum divide size SMLSIZ, then solve
the problem with another solver. */
if (*n <= smlsiz) {
if (icompq == 2) {
slaset_("A", n, n, &c_b29, &c_b15, &u[u_offset], ldu);
slaset_("A", n, n, &c_b29, &c_b15, &vt[vt_offset], ldvt);
slasdq_("U", &c__0, n, n, n, &c__0, &d__[1], &e[1], &vt[vt_offset]
, ldvt, &u[u_offset], ldu, &u[u_offset], ldu, &work[
wstart], info);
} else if (icompq == 1) {
iu = 1;
ivt = iu + *n;
slaset_("A", n, n, &c_b29, &c_b15, &q[iu + (qstart - 1) * *n], n);
slaset_("A", n, n, &c_b29, &c_b15, &q[ivt + (qstart - 1) * *n], n);
slasdq_("U", &c__0, n, n, n, &c__0, &d__[1], &e[1], &q[ivt + (
qstart - 1) * *n], n, &q[iu + (qstart - 1) * *n], n, &q[
iu + (qstart - 1) * *n], n, &work[wstart], info);
}
goto L40;
}
if (icompq == 2) {
slaset_("A", n, n, &c_b29, &c_b15, &u[u_offset], ldu);
slaset_("A", n, n, &c_b29, &c_b15, &vt[vt_offset], ldvt);
}
/* Scale. */
orgnrm = slanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.f) {
return 0;
}
latime_1.ops += (real) (*n + nm1);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b15, n, &c__1, &d__[1], n, &ierr);
slascl_("G", &c__0, &c__0, &orgnrm, &c_b15, &nm1, &c__1, &e[1], &nm1, &
ierr);
eps = slamch_("Epsilon");
mlvl = (integer) (log((real) (*n) / (real) (smlsiz + 1)) / log(2.f)) + 1;
smlszp = smlsiz + 1;
if (icompq == 1) {
iu = 1;
ivt = smlsiz + 1;
difl = ivt + smlszp;
difr = difl + mlvl;
z__ = difr + (mlvl << 1);
ic = z__ + mlvl;
is = ic + 1;
poles = is + 1;
givnum = poles + (mlvl << 1);
k = 1;
givptr = 2;
perm = 3;
givcol = perm + mlvl;
}
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = d__[i__], dabs(r__1)) < eps) {
d__[i__] = r_sign(&eps, &d__[i__]);
}
/* L20: */
}
start = 1;
sqre = 0;
i__1 = nm1;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((r__1 = e[i__], dabs(r__1)) < eps || i__ == nm1) {
/* Subproblem found. First determine its size and then
apply divide and conquer on it. */
if (i__ < nm1) {
/* A subproblem with E(I) small for I < NM1. */
nsize = i__ - start + 1;
} else if ((r__1 = e[i__], dabs(r__1)) >= eps) {
/* A subproblem with E(NM1) not too small but I = NM1. */
nsize = *n - start + 1;
} else {
/* A subproblem with E(NM1) small. This implies an
1-by-1 subproblem at D(N). Solve this 1-by-1 problem
first. */
nsize = i__ - start + 1;
if (icompq == 2) {
u_ref(*n, *n) = r_sign(&c_b15, &d__[*n]);
vt_ref(*n, *n) = 1.f;
} else if (icompq == 1) {
q[*n + (qstart - 1) * *n] = r_sign(&c_b15, &d__[*n]);
q[*n + (smlsiz + qstart - 1) * *n] = 1.f;
}
d__[*n] = (r__1 = d__[*n], dabs(r__1));
}
if (icompq == 2) {
slasd0_(&nsize, &sqre, &d__[start], &e[start], &u_ref(start,
start), ldu, &vt_ref(start, start), ldvt, &smlsiz, &
iwork[1], &work[wstart], info);
} else {
slasda_(&icompq, &smlsiz, &nsize, &sqre, &d__[start], &e[
start], &q[start + (iu + qstart - 2) * *n], n, &q[
start + (ivt + qstart - 2) * *n], &iq[start + k * *n],
&q[start + (difl + qstart - 2) * *n], &q[start + (
difr + qstart - 2) * *n], &q[start + (z__ + qstart -
2) * *n], &q[start + (poles + qstart - 2) * *n], &iq[
start + givptr * *n], &iq[start + givcol * *n], n, &
iq[start + perm * *n], &q[start + (givnum + qstart -
2) * *n], &q[start + (ic + qstart - 2) * *n], &q[
start + (is + qstart - 2) * *n], &work[wstart], &
iwork[1], info);
if (*info != 0) {
return 0;
}
}
start = i__ + 1;
}
/* L30: */
}
/* Unscale */
latime_1.ops += (real) (*n);
slascl_("G", &c__0, &c__0, &c_b15, &orgnrm, n, &c__1, &d__[1], n, &ierr);
L40:
/* Use Selection Sort to minimize swaps of singular vectors */
i__1 = *n;
for (ii = 2; ii <= i__1; ++ii) {
i__ = ii - 1;
kk = i__;
p = d__[i__];
i__2 = *n;
for (j = ii; j <= i__2; ++j) {
if (d__[j] > p) {
kk = j;
p = d__[j];
}
/* L50: */
}
if (kk != i__) {
d__[kk] = d__[i__];
d__[i__] = p;
if (icompq == 1) {
iq[i__] = kk;
} else if (icompq == 2) {
sswap_(n, &u_ref(1, i__), &c__1, &u_ref(1, kk), &c__1);
sswap_(n, &vt_ref(i__, 1), ldvt, &vt_ref(kk, 1), ldvt);
}
} else if (icompq == 1) {
iq[i__] = i__;
}
/* L60: */
}
/* If ICOMPQ = 1, use IQ(N,1) as the indicator for UPLO */
if (icompq == 1) {
if (iuplo == 1) {
iq[*n] = 1;
} else {
iq[*n] = 0;
}
}
/* If B is lower bidiagonal, update U by those Givens rotations
which rotated B to be upper bidiagonal */
if (iuplo == 2 && icompq == 2) {
latime_1.ops += (real) ((*n - 1) * 6 * *n);
slasr_("L", "V", "B", n, n, &work[1], &work[*n], &u[u_offset], ldu);
}
return 0;
/* End of SBDSDC */
} /* sbdsdc_ */
