[] add metering mode to CLI

1 files changed, 918 insertions, 0 deletions

diff --git a/contrib/libs/clapack/dbdsqr.c b/contrib/libs/clapack/dbdsqr.c
new file mode 100644
index 0000000000..08b04fc9da
--- /dev/null
+++ b/contrib/libs/clapack/dbdsqr.c
@@ -0,0 +1,918 @@
+/* dbdsqr.f -- translated by f2c (version 20061008).
+   You must link the resulting object file with libf2c:
+	on Microsoft Windows system, link with libf2c.lib;
+	on Linux or Unix systems, link with .../path/to/libf2c.a -lm
+	or, if you install libf2c.a in a standard place, with -lf2c -lm
+	-- in that order, at the end of the command line, as in
+		cc *.o -lf2c -lm
+	Source for libf2c is in /netlib/f2c/libf2c.zip, e.g.,
+
+		http://www.netlib.org/f2c/libf2c.zip
+*/
+
+#include "f2c.h"
+#include "blaswrap.h"
+
+/* Table of constant values */
+
+static doublereal c_b15 = -.125;
+static integer c__1 = 1;
+static doublereal c_b49 = 1.;
+static doublereal c_b72 = -1.;
+
+/* Subroutine */ int dbdsqr_(char *uplo, integer *n, integer *ncvt, integer *
+	nru, integer *ncc, doublereal *d__, doublereal *e, doublereal *vt, 
+	integer *ldvt, doublereal *u, integer *ldu, doublereal *c__, integer *
+	ldc, doublereal *work, integer *info)
+{
+    /* System generated locals */
+    integer c_dim1, c_offset, u_dim1, u_offset, vt_dim1, vt_offset, i__1, 
+	    i__2;
+    doublereal d__1, d__2, d__3, d__4;
+
+    /* Builtin functions */
+    double pow_dd(doublereal *, doublereal *), sqrt(doublereal), d_sign(
+	    doublereal *, doublereal *);
+
+    /* Local variables */
+    doublereal f, g, h__;
+    integer i__, j, m;
+    doublereal r__, cs;
+    integer ll;
+    doublereal sn, mu;
+    integer nm1, nm12, nm13, lll;
+    doublereal eps, sll, tol, abse;
+    integer idir;
+    doublereal abss;
+    integer oldm;
+    doublereal cosl;
+    integer isub, iter;
+    doublereal unfl, sinl, cosr, smin, smax, sinr;
+    extern /* Subroutine */ int drot_(integer *, doublereal *, integer *, 
+	    doublereal *, integer *, doublereal *, doublereal *), dlas2_(
+	    doublereal *, doublereal *, doublereal *, doublereal *, 
+	    doublereal *), dscal_(integer *, doublereal *, doublereal *, 
+	    integer *);
+    extern logical lsame_(char *, char *);
+    doublereal oldcs;
+    extern /* Subroutine */ int dlasr_(char *, char *, char *, integer *, 
+	    integer *, doublereal *, doublereal *, doublereal *, integer *);
+    integer oldll;
+    doublereal shift, sigmn, oldsn;
+    extern /* Subroutine */ int dswap_(integer *, doublereal *, integer *, 
+	    doublereal *, integer *);
+    integer maxit;
+    doublereal sminl, sigmx;
+    logical lower;
+    extern /* Subroutine */ int dlasq1_(integer *, doublereal *, doublereal *, 
+	     doublereal *, integer *), dlasv2_(doublereal *, doublereal *, 
+	    doublereal *, doublereal *, doublereal *, doublereal *, 
+	    doublereal *, doublereal *, doublereal *);
+    extern doublereal dlamch_(char *);
+    extern /* Subroutine */ int dlartg_(doublereal *, doublereal *, 
+	    doublereal *, doublereal *, doublereal *), xerbla_(char *, 
+	    integer *);
+    doublereal sminoa, thresh;
+    logical rotate;
+    doublereal tolmul;
+
+
+/*  -- LAPACK routine (version 3.2) -- */
+/*     Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */
+/*     January 2007 */
+
+/*     .. Scalar Arguments .. */
+/*     .. */
+/*     .. Array Arguments .. */
+/*     .. */
+
+/*  Purpose */
+/*  ======= */
+
+/*  DBDSQR computes the singular values and, optionally, the right and/or */
+/*  left singular vectors from the singular value decomposition (SVD) of */
+/*  a real N-by-N (upper or lower) bidiagonal matrix B using the implicit */
+/*  zero-shift QR algorithm.  The SVD of B has the form */
+
+/*     B = Q * S * P**T */
+
+/*  where S is the diagonal matrix of singular values, Q is an orthogonal */
+/*  matrix of left singular vectors, and P is an orthogonal matrix of */
+/*  right singular vectors.  If left singular vectors are requested, this */
+/*  subroutine actually returns U*Q instead of Q, and, if right singular */
+/*  vectors are requested, this subroutine returns P**T*VT instead of */
+/*  P**T, for given real input matrices U and VT.  When U and VT are the */
+/*  orthogonal matrices that reduce a general matrix A to bidiagonal */
+/*  form:  A = U*B*VT, as computed by DGEBRD, then */
+
+/*     A = (U*Q) * S * (P**T*VT) */
+
+/*  is the SVD of A.  Optionally, the subroutine may also compute Q**T*C */
+/*  for a given real input matrix C. */
+
+/*  See "Computing  Small Singular Values of Bidiagonal Matrices With */
+/*  Guaranteed High Relative Accuracy," by J. Demmel and W. Kahan, */
+/*  LAPACK Working Note #3 (or SIAM J. Sci. Statist. Comput. vol. 11, */
+/*  no. 5, pp. 873-912, Sept 1990) and */
+/*  "Accurate singular values and differential qd algorithms," by */
+/*  B. Parlett and V. Fernando, Technical Report CPAM-554, Mathematics */
+/*  Department, University of California at Berkeley, July 1992 */
+/*  for a detailed description of the algorithm. */
+
+/*  Arguments */
+/*  ========= */
+
+/*  UPLO    (input) CHARACTER*1 */
+/*          = 'U':  B is upper bidiagonal; */
+/*          = 'L':  B is lower bidiagonal. */
+
+/*  N       (input) INTEGER */
+/*          The order of the matrix B.  N >= 0. */
+
+/*  NCVT    (input) INTEGER */
+/*          The number of columns of the matrix VT. NCVT >= 0. */
+
+/*  NRU     (input) INTEGER */
+/*          The number of rows of the matrix U. NRU >= 0. */
+
+/*  NCC     (input) INTEGER */
+/*          The number of columns of the matrix C. NCC >= 0. */
+
+/*  D       (input/output) DOUBLE PRECISION array, dimension (N) */
+/*          On entry, the n diagonal elements of the bidiagonal matrix B. */
+/*          On exit, if INFO=0, the singular values of B in decreasing */
+/*          order. */
+
+/*  E       (input/output) DOUBLE PRECISION array, dimension (N-1) */
+/*          On entry, the N-1 offdiagonal elements of the bidiagonal */
+/*          matrix B. */
+/*          On exit, if INFO = 0, E is destroyed; if INFO > 0, D and E */
+/*          will contain the diagonal and superdiagonal elements of a */
+/*          bidiagonal matrix orthogonally equivalent to the one given */
+/*          as input. */
+
+/*  VT      (input/output) DOUBLE PRECISION array, dimension (LDVT, NCVT) */
+/*          On entry, an N-by-NCVT matrix VT. */
+/*          On exit, VT is overwritten by P**T * VT. */
+/*          Not referenced if NCVT = 0. */
+
+/*  LDVT    (input) INTEGER */
+/*          The leading dimension of the array VT. */
+/*          LDVT >= max(1,N) if NCVT > 0; LDVT >= 1 if NCVT = 0. */
+
+/*  U       (input/output) DOUBLE PRECISION array, dimension (LDU, N) */
+/*          On entry, an NRU-by-N matrix U. */
+/*          On exit, U is overwritten by U * Q. */
+/*          Not referenced if NRU = 0. */
+
+/*  LDU     (input) INTEGER */
+/*          The leading dimension of the array U.  LDU >= max(1,NRU). */
+
+/*  C       (input/output) DOUBLE PRECISION array, dimension (LDC, NCC) */
+/*          On entry, an N-by-NCC matrix C. */
+/*          On exit, C is overwritten by Q**T * C. */
+/*          Not referenced if NCC = 0. */
+
+/*  LDC     (input) INTEGER */
+/*          The leading dimension of the array C. */
+/*          LDC >= max(1,N) if NCC > 0; LDC >=1 if NCC = 0. */
+
+/*  WORK    (workspace) DOUBLE PRECISION array, dimension (4*N) */
+
+/*  INFO    (output) INTEGER */
+/*          = 0:  successful exit */
+/*          < 0:  If INFO = -i, the i-th argument had an illegal value */
+/*          > 0: */
+/*             if NCVT = NRU = NCC = 0, */
+/*                = 1, a split was marked by a positive value in E */
+/*                = 2, current block of Z not diagonalized after 30*N */
+/*                     iterations (in inner while loop) */
+/*                = 3, termination criterion of outer while loop not met */
+/*                     (program created more than N unreduced blocks) */
+/*             else NCVT = NRU = NCC = 0, */
+/*                   the algorithm did not converge; D and E contain the */
+/*                   elements of a bidiagonal matrix which is orthogonally */
+/*                   similar to the input matrix B;  if INFO = i, i */
+/*                   elements of E have not converged to zero. */
+
+/*  Internal Parameters */
+/*  =================== */
+
+/*  TOLMUL  DOUBLE PRECISION, default = max(10,min(100,EPS**(-1/8))) */
+/*          TOLMUL controls the convergence criterion of the QR loop. */
+/*          If it is positive, TOLMUL*EPS is the desired relative */
+/*             precision in the computed singular values. */
+/*          If it is negative, abs(TOLMUL*EPS*sigma_max) is the */
+/*             desired absolute accuracy in the computed singular */
+/*             values (corresponds to relative accuracy */
+/*             abs(TOLMUL*EPS) in the largest singular value. */
+/*          abs(TOLMUL) should be between 1 and 1/EPS, and preferably */
+/*             between 10 (for fast convergence) and .1/EPS */
+/*             (for there to be some accuracy in the results). */
+/*          Default is to lose at either one eighth or 2 of the */
+/*             available decimal digits in each computed singular value */
+/*             (whichever is smaller). */
+
+/*  MAXITR  INTEGER, default = 6 */
+/*          MAXITR controls the maximum number of passes of the */
+/*          algorithm through its inner loop. The algorithms stops */
+/*          (and so fails to converge) if the number of passes */
+/*          through the inner loop exceeds MAXITR*N**2. */
+
+/*  ===================================================================== */
+
+/*     .. Parameters .. */
+/*     .. */
+/*     .. Local Scalars .. */
+/*     .. */
+/*     .. External Functions .. */
+/*     .. */
+/*     .. External Subroutines .. */
+/*     .. */
+/*     .. Intrinsic Functions .. */
+/*     .. */
+/*     .. Executable Statements .. */
+
+/*     Test the input parameters. */
+
+    /* Parameter adjustments */
+    --d__;
+    --e;
+    vt_dim1 = *ldvt;
+    vt_offset = 1 + vt_dim1;
+    vt -= vt_offset;
+    u_dim1 = *ldu;
+    u_offset = 1 + u_dim1;
+    u -= u_offset;
+    c_dim1 = *ldc;
+    c_offset = 1 + c_dim1;
+    c__ -= c_offset;
+    --work;
+
+    /* Function Body */
+    *info = 0;
+    lower = lsame_(uplo, "L");
+    if (! lsame_(uplo, "U") && ! lower) {
+	*info = -1;
+    } else if (*n < 0) {
+	*info = -2;
+    } else if (*ncvt < 0) {
+	*info = -3;
+    } else if (*nru < 0) {
+	*info = -4;
+    } else if (*ncc < 0) {
+	*info = -5;
+    } else if (*ncvt == 0 && *ldvt < 1 || *ncvt > 0 && *ldvt < max(1,*n)) {
+	*info = -9;
+    } else if (*ldu < max(1,*nru)) {
+	*info = -11;
+    } else if (*ncc == 0 && *ldc < 1 || *ncc > 0 && *ldc < max(1,*n)) {
+	*info = -13;
+    }
+    if (*info != 0) {
+	i__1 = -(*info);
+	xerbla_("DBDSQR", &i__1);
+	return 0;
+    }
+    if (*n == 0) {
+	return 0;
+    }
+    if (*n == 1) {
+	goto L160;
+    }
+
+/*     ROTATE is true if any singular vectors desired, false otherwise */
+
+    rotate = *ncvt > 0 || *nru > 0 || *ncc > 0;
+
+/*     If no singular vectors desired, use qd algorithm */
+
+    if (! rotate) {
+	dlasq1_(n, &d__[1], &e[1], &work[1], info);
+	return 0;
+    }
+
+    nm1 = *n - 1;
+    nm12 = nm1 + nm1;
+    nm13 = nm12 + nm1;
+    idir = 0;
+
+/*     Get machine constants */
+
+    eps = dlamch_("Epsilon");
+    unfl = dlamch_("Safe minimum");
+
+/*     If matrix lower bidiagonal, rotate to be upper bidiagonal */
+/*     by applying Givens rotations on the left */
+
+    if (lower) {
+	i__1 = *n - 1;
+	for (i__ = 1; i__ <= i__1; ++i__) {
+	    dlartg_(&d__[i__], &e[i__], &cs, &sn, &r__);
+	    d__[i__] = r__;
+	    e[i__] = sn * d__[i__ + 1];
+	    d__[i__ + 1] = cs * d__[i__ + 1];
+	    work[i__] = cs;
+	    work[nm1 + i__] = sn;
+/* L10: */
+	}
+
+/*        Update singular vectors if desired */
+
+	if (*nru > 0) {
+	    dlasr_("R", "V", "F", nru, n, &work[1], &work[*n], &u[u_offset], 
+		    ldu);
+	}
+	if (*ncc > 0) {
+	    dlasr_("L", "V", "F", n, ncc, &work[1], &work[*n], &c__[c_offset], 
+		     ldc);
+	}
+    }
+
+/*     Compute singular values to relative accuracy TOL */
+/*     (By setting TOL to be negative, algorithm will compute */
+/*     singular values to absolute accuracy ABS(TOL)*norm(input matrix)) */
+
+/* Computing MAX */
+/* Computing MIN */
+    d__3 = 100., d__4 = pow_dd(&eps, &c_b15);
+    d__1 = 10., d__2 = min(d__3,d__4);
+    tolmul = max(d__1,d__2);
+    tol = tolmul * eps;
+
+/*     Compute approximate maximum, minimum singular values */
+
+    smax = 0.;
+    i__1 = *n;
+    for (i__ = 1; i__ <= i__1; ++i__) {
+/* Computing MAX */
+	d__2 = smax, d__3 = (d__1 = d__[i__], abs(d__1));
+	smax = max(d__2,d__3);
+/* L20: */
+    }
+    i__1 = *n - 1;
+    for (i__ = 1; i__ <= i__1; ++i__) {
+/* Computing MAX */
+	d__2 = smax, d__3 = (d__1 = e[i__], abs(d__1));
+	smax = max(d__2,d__3);
+/* L30: */
+    }
+    sminl = 0.;
+    if (tol >= 0.) {
+
+/*        Relative accuracy desired */
+
+	sminoa = abs(d__[1]);
+	if (sminoa == 0.) {
+	    goto L50;
+	}
+	mu = sminoa;
+	i__1 = *n;
+	for (i__ = 2; i__ <= i__1; ++i__) {
+	    mu = (d__2 = d__[i__], abs(d__2)) * (mu / (mu + (d__1 = e[i__ - 1]
+		    , abs(d__1))));
+	    sminoa = min(sminoa,mu);
+	    if (sminoa == 0.) {
+		goto L50;
+	    }
+/* L40: */
+	}
+L50:
+	sminoa /= sqrt((doublereal) (*n));
+/* Computing MAX */
+	d__1 = tol * sminoa, d__2 = *n * 6 * *n * unfl;
+	thresh = max(d__1,d__2);
+    } else {
+
+/*        Absolute accuracy desired */
+
+/* Computing MAX */
+	d__1 = abs(tol) * smax, d__2 = *n * 6 * *n * unfl;
+	thresh = max(d__1,d__2);
+    }
+
+/*     Prepare for main iteration loop for the singular values */
+/*     (MAXIT is the maximum number of passes through the inner */
+/*     loop permitted before nonconvergence signalled.) */
+
+    maxit = *n * 6 * *n;
+    iter = 0;
+    oldll = -1;
+    oldm = -1;
+
+/*     M points to last element of unconverged part of matrix */
+
+    m = *n;
+
+/*     Begin main iteration loop */
+
+L60:
+
+/*     Check for convergence or exceeding iteration count */
+
+    if (m <= 1) {
+	goto L160;
+    }
+    if (iter > maxit) {
+	goto L200;
+    }
+
+/*     Find diagonal block of matrix to work on */
+
+    if (tol < 0. && (d__1 = d__[m], abs(d__1)) <= thresh) {
+	d__[m] = 0.;
+    }
+    smax = (d__1 = d__[m], abs(d__1));
+    smin = smax;
+    i__1 = m - 1;
+    for (lll = 1; lll <= i__1; ++lll) {
+	ll = m - lll;
+	abss = (d__1 = d__[ll], abs(d__1));
+	abse = (d__1 = e[ll], abs(d__1));
+	if (tol < 0. && abss <= thresh) {
+	    d__[ll] = 0.;
+	}
+	if (abse <= thresh) {
+	    goto L80;
+	}
+	smin = min(smin,abss);
+/* Computing MAX */
+	d__1 = max(smax,abss);
+	smax = max(d__1,abse);
+/* L70: */
+    }
+    ll = 0;
+    goto L90;
+L80:
+    e[ll] = 0.;
+
+/*     Matrix splits since E(LL) = 0 */
+
+    if (ll == m - 1) {
+
+/*        Convergence of bottom singular value, return to top of loop */
+
+	--m;
+	goto L60;
+    }
+L90:
+    ++ll;
+
+/*     E(LL) through E(M-1) are nonzero, E(LL-1) is zero */
+
+    if (ll == m - 1) {
+
+/*        2 by 2 block, handle separately */
+
+	dlasv2_(&d__[m - 1], &e[m - 1], &d__[m], &sigmn, &sigmx, &sinr, &cosr, 
+		 &sinl, &cosl);
+	d__[m - 1] = sigmx;
+	e[m - 1] = 0.;
+	d__[m] = sigmn;
+
+/*        Compute singular vectors, if desired */
+
+	if (*ncvt > 0) {
+	    drot_(ncvt, &vt[m - 1 + vt_dim1], ldvt, &vt[m + vt_dim1], ldvt, &
+		    cosr, &sinr);
+	}
+	if (*nru > 0) {
+	    drot_(nru, &u[(m - 1) * u_dim1 + 1], &c__1, &u[m * u_dim1 + 1], &
+		    c__1, &cosl, &sinl);
+	}
+	if (*ncc > 0) {
+	    drot_(ncc, &c__[m - 1 + c_dim1], ldc, &c__[m + c_dim1], ldc, &
+		    cosl, &sinl);
+	}
+	m += -2;
+	goto L60;
+    }
+
+/*     If working on new submatrix, choose shift direction */
+/*     (from larger end diagonal element towards smaller) */
+
+    if (ll > oldm || m < oldll) {
+	if ((d__1 = d__[ll], abs(d__1)) >= (d__2 = d__[m], abs(d__2))) {
+
+/*           Chase bulge from top (big end) to bottom (small end) */
+
+	    idir = 1;
+	} else {
+
+/*           Chase bulge from bottom (big end) to top (small end) */
+
+	    idir = 2;
+	}
+    }
+
+/*     Apply convergence tests */
+
+    if (idir == 1) {
+
+/*        Run convergence test in forward direction */
+/*        First apply standard test to bottom of matrix */
+
+	if ((d__2 = e[m - 1], abs(d__2)) <= abs(tol) * (d__1 = d__[m], abs(
+		d__1)) || tol < 0. && (d__3 = e[m - 1], abs(d__3)) <= thresh) 
+		{
+	    e[m - 1] = 0.;
+	    goto L60;
+	}
+
+	if (tol >= 0.) {
+
+/*           If relative accuracy desired, */
+/*           apply convergence criterion forward */
+
+	    mu = (d__1 = d__[ll], abs(d__1));
+	    sminl = mu;
+	    i__1 = m - 1;
+	    for (lll = ll; lll <= i__1; ++lll) {
+		if ((d__1 = e[lll], abs(d__1)) <= tol * mu) {
+		    e[lll] = 0.;
+		    goto L60;
+		}
+		mu = (d__2 = d__[lll + 1], abs(d__2)) * (mu / (mu + (d__1 = e[
+			lll], abs(d__1))));
+		sminl = min(sminl,mu);
+/* L100: */
+	    }
+	}
+
+    } else {
+
+/*        Run convergence test in backward direction */
+/*        First apply standard test to top of matrix */
+
+	if ((d__2 = e[ll], abs(d__2)) <= abs(tol) * (d__1 = d__[ll], abs(d__1)
+		) || tol < 0. && (d__3 = e[ll], abs(d__3)) <= thresh) {
+	    e[ll] = 0.;
+	    goto L60;
+	}
+
+	if (tol >= 0.) {
+
+/*           If relative accuracy desired, */
+/*           apply convergence criterion backward */
+
+	    mu = (d__1 = d__[m], abs(d__1));
+	    sminl = mu;
+	    i__1 = ll;
+	    for (lll = m - 1; lll >= i__1; --lll) {
+		if ((d__1 = e[lll], abs(d__1)) <= tol * mu) {
+		    e[lll] = 0.;
+		    goto L60;
+		}
+		mu = (d__2 = d__[lll], abs(d__2)) * (mu / (mu + (d__1 = e[lll]
+			, abs(d__1))));
+		sminl = min(sminl,mu);
+/* L110: */
+	    }
+	}
+    }
+    oldll = ll;
+    oldm = m;
+
+/*     Compute shift.  First, test if shifting would ruin relative */
+/*     accuracy, and if so set the shift to zero. */
+
+/* Computing MAX */
+    d__1 = eps, d__2 = tol * .01;
+    if (tol >= 0. && *n * tol * (sminl / smax) <= max(d__1,d__2)) {
+
+/*        Use a zero shift to avoid loss of relative accuracy */
+
+	shift = 0.;
+    } else {
+
+/*        Compute the shift from 2-by-2 block at end of matrix */
+
+	if (idir == 1) {
+	    sll = (d__1 = d__[ll], abs(d__1));
+	    dlas2_(&d__[m - 1], &e[m - 1], &d__[m], &shift, &r__);
+	} else {
+	    sll = (d__1 = d__[m], abs(d__1));
+	    dlas2_(&d__[ll], &e[ll], &d__[ll + 1], &shift, &r__);
+	}
+
+/*        Test if shift negligible, and if so set to zero */
+
+	if (sll > 0.) {
+/* Computing 2nd power */
+	    d__1 = shift / sll;
+	    if (d__1 * d__1 < eps) {
+		shift = 0.;
+	    }
+	}
+    }
+
+/*     Increment iteration count */
+
+    iter = iter + m - ll;
+
+/*     If SHIFT = 0, do simplified QR iteration */
+
+    if (shift == 0.) {
+	if (idir == 1) {
+
+/*           Chase bulge from top to bottom */
+/*           Save cosines and sines for later singular vector updates */
+
+	    cs = 1.;
+	    oldcs = 1.;
+	    i__1 = m - 1;
+	    for (i__ = ll; i__ <= i__1; ++i__) {
+		d__1 = d__[i__] * cs;
+		dlartg_(&d__1, &e[i__], &cs, &sn, &r__);
+		if (i__ > ll) {
+		    e[i__ - 1] = oldsn * r__;
+		}
+		d__1 = oldcs * r__;
+		d__2 = d__[i__ + 1] * sn;
+		dlartg_(&d__1, &d__2, &oldcs, &oldsn, &d__[i__]);
+		work[i__ - ll + 1] = cs;
+		work[i__ - ll + 1 + nm1] = sn;
+		work[i__ - ll + 1 + nm12] = oldcs;
+		work[i__ - ll + 1 + nm13] = oldsn;
+/* L120: */
+	    }
+	    h__ = d__[m] * cs;
+	    d__[m] = h__ * oldcs;
+	    e[m - 1] = h__ * oldsn;
+
+/*           Update singular vectors */
+
+	    if (*ncvt > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("L", "V", "F", &i__1, ncvt, &work[1], &work[*n], &vt[
+			ll + vt_dim1], ldvt);
+	    }
+	    if (*nru > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("R", "V", "F", nru, &i__1, &work[nm12 + 1], &work[nm13 
+			+ 1], &u[ll * u_dim1 + 1], ldu);
+	    }
+	    if (*ncc > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("L", "V", "F", &i__1, ncc, &work[nm12 + 1], &work[nm13 
+			+ 1], &c__[ll + c_dim1], ldc);
+	    }
+
+/*           Test convergence */
+
+	    if ((d__1 = e[m - 1], abs(d__1)) <= thresh) {
+		e[m - 1] = 0.;
+	    }
+
+	} else {
+
+/*           Chase bulge from bottom to top */
+/*           Save cosines and sines for later singular vector updates */
+
+	    cs = 1.;
+	    oldcs = 1.;
+	    i__1 = ll + 1;
+	    for (i__ = m; i__ >= i__1; --i__) {
+		d__1 = d__[i__] * cs;
+		dlartg_(&d__1, &e[i__ - 1], &cs, &sn, &r__);
+		if (i__ < m) {
+		    e[i__] = oldsn * r__;
+		}
+		d__1 = oldcs * r__;
+		d__2 = d__[i__ - 1] * sn;
+		dlartg_(&d__1, &d__2, &oldcs, &oldsn, &d__[i__]);
+		work[i__ - ll] = cs;
+		work[i__ - ll + nm1] = -sn;
+		work[i__ - ll + nm12] = oldcs;
+		work[i__ - ll + nm13] = -oldsn;
+/* L130: */
+	    }
+	    h__ = d__[ll] * cs;
+	    d__[ll] = h__ * oldcs;
+	    e[ll] = h__ * oldsn;
+
+/*           Update singular vectors */
+
+	    if (*ncvt > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("L", "V", "B", &i__1, ncvt, &work[nm12 + 1], &work[
+			nm13 + 1], &vt[ll + vt_dim1], ldvt);
+	    }
+	    if (*nru > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("R", "V", "B", nru, &i__1, &work[1], &work[*n], &u[ll *
+			 u_dim1 + 1], ldu);
+	    }
+	    if (*ncc > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("L", "V", "B", &i__1, ncc, &work[1], &work[*n], &c__[
+			ll + c_dim1], ldc);
+	    }
+
+/*           Test convergence */
+
+	    if ((d__1 = e[ll], abs(d__1)) <= thresh) {
+		e[ll] = 0.;
+	    }
+	}
+    } else {
+
+/*        Use nonzero shift */
+
+	if (idir == 1) {
+
+/*           Chase bulge from top to bottom */
+/*           Save cosines and sines for later singular vector updates */
+
+	    f = ((d__1 = d__[ll], abs(d__1)) - shift) * (d_sign(&c_b49, &d__[
+		    ll]) + shift / d__[ll]);
+	    g = e[ll];
+	    i__1 = m - 1;
+	    for (i__ = ll; i__ <= i__1; ++i__) {
+		dlartg_(&f, &g, &cosr, &sinr, &r__);
+		if (i__ > ll) {
+		    e[i__ - 1] = r__;
+		}
+		f = cosr * d__[i__] + sinr * e[i__];
+		e[i__] = cosr * e[i__] - sinr * d__[i__];
+		g = sinr * d__[i__ + 1];
+		d__[i__ + 1] = cosr * d__[i__ + 1];
+		dlartg_(&f, &g, &cosl, &sinl, &r__);
+		d__[i__] = r__;
+		f = cosl * e[i__] + sinl * d__[i__ + 1];
+		d__[i__ + 1] = cosl * d__[i__ + 1] - sinl * e[i__];
+		if (i__ < m - 1) {
+		    g = sinl * e[i__ + 1];
+		    e[i__ + 1] = cosl * e[i__ + 1];
+		}
+		work[i__ - ll + 1] = cosr;
+		work[i__ - ll + 1 + nm1] = sinr;
+		work[i__ - ll + 1 + nm12] = cosl;
+		work[i__ - ll + 1 + nm13] = sinl;
+/* L140: */
+	    }
+	    e[m - 1] = f;
+
+/*           Update singular vectors */
+
+	    if (*ncvt > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("L", "V", "F", &i__1, ncvt, &work[1], &work[*n], &vt[
+			ll + vt_dim1], ldvt);
+	    }
+	    if (*nru > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("R", "V", "F", nru, &i__1, &work[nm12 + 1], &work[nm13 
+			+ 1], &u[ll * u_dim1 + 1], ldu);
+	    }
+	    if (*ncc > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("L", "V", "F", &i__1, ncc, &work[nm12 + 1], &work[nm13 
+			+ 1], &c__[ll + c_dim1], ldc);
+	    }
+
+/*           Test convergence */
+
+	    if ((d__1 = e[m - 1], abs(d__1)) <= thresh) {
+		e[m - 1] = 0.;
+	    }
+
+	} else {
+
+/*           Chase bulge from bottom to top */
+/*           Save cosines and sines for later singular vector updates */
+
+	    f = ((d__1 = d__[m], abs(d__1)) - shift) * (d_sign(&c_b49, &d__[m]
+		    ) + shift / d__[m]);
+	    g = e[m - 1];
+	    i__1 = ll + 1;
+	    for (i__ = m; i__ >= i__1; --i__) {
+		dlartg_(&f, &g, &cosr, &sinr, &r__);
+		if (i__ < m) {
+		    e[i__] = r__;
+		}
+		f = cosr * d__[i__] + sinr * e[i__ - 1];
+		e[i__ - 1] = cosr * e[i__ - 1] - sinr * d__[i__];
+		g = sinr * d__[i__ - 1];
+		d__[i__ - 1] = cosr * d__[i__ - 1];
+		dlartg_(&f, &g, &cosl, &sinl, &r__);
+		d__[i__] = r__;
+		f = cosl * e[i__ - 1] + sinl * d__[i__ - 1];
+		d__[i__ - 1] = cosl * d__[i__ - 1] - sinl * e[i__ - 1];
+		if (i__ > ll + 1) {
+		    g = sinl * e[i__ - 2];
+		    e[i__ - 2] = cosl * e[i__ - 2];
+		}
+		work[i__ - ll] = cosr;
+		work[i__ - ll + nm1] = -sinr;
+		work[i__ - ll + nm12] = cosl;
+		work[i__ - ll + nm13] = -sinl;
+/* L150: */
+	    }
+	    e[ll] = f;
+
+/*           Test convergence */
+
+	    if ((d__1 = e[ll], abs(d__1)) <= thresh) {
+		e[ll] = 0.;
+	    }
+
+/*           Update singular vectors if desired */
+
+	    if (*ncvt > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("L", "V", "B", &i__1, ncvt, &work[nm12 + 1], &work[
+			nm13 + 1], &vt[ll + vt_dim1], ldvt);
+	    }
+	    if (*nru > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("R", "V", "B", nru, &i__1, &work[1], &work[*n], &u[ll *
+			 u_dim1 + 1], ldu);
+	    }
+	    if (*ncc > 0) {
+		i__1 = m - ll + 1;
+		dlasr_("L", "V", "B", &i__1, ncc, &work[1], &work[*n], &c__[
+			ll + c_dim1], ldc);
+	    }
+	}
+    }
+
+/*     QR iteration finished, go back and check convergence */
+
+    goto L60;
+
+/*     All singular values converged, so make them positive */
+
+L160:
+    i__1 = *n;
+    for (i__ = 1; i__ <= i__1; ++i__) {
+	if (d__[i__] < 0.) {
+	    d__[i__] = -d__[i__];
+
+/*           Change sign of singular vectors, if desired */
+
+	    if (*ncvt > 0) {
+		dscal_(ncvt, &c_b72, &vt[i__ + vt_dim1], ldvt);
+	    }
+	}
+/* L170: */
+    }
+
+/*     Sort the singular values into decreasing order (insertion sort on */
+/*     singular values, but only one transposition per singular vector) */
+
+    i__1 = *n - 1;
+    for (i__ = 1; i__ <= i__1; ++i__) {
+
+/*        Scan for smallest D(I) */
+
+	isub = 1;
+	smin = d__[1];
+	i__2 = *n + 1 - i__;
+	for (j = 2; j <= i__2; ++j) {
+	    if (d__[j] <= smin) {
+		isub = j;
+		smin = d__[j];
+	    }
+/* L180: */
+	}
+	if (isub != *n + 1 - i__) {
+
+/*           Swap singular values and vectors */
+
+	    d__[isub] = d__[*n + 1 - i__];
+	    d__[*n + 1 - i__] = smin;
+	    if (*ncvt > 0) {
+		dswap_(ncvt, &vt[isub + vt_dim1], ldvt, &vt[*n + 1 - i__ + 
+			vt_dim1], ldvt);
+	    }
+	    if (*nru > 0) {
+		dswap_(nru, &u[isub * u_dim1 + 1], &c__1, &u[(*n + 1 - i__) * 
+			u_dim1 + 1], &c__1);
+	    }
+	    if (*ncc > 0) {
+		dswap_(ncc, &c__[isub + c_dim1], ldc, &c__[*n + 1 - i__ + 
+			c_dim1], ldc);
+	    }
+	}
+/* L190: */
+    }
+    goto L220;
+
+/*     Maximum number of iterations exceeded, failure to converge */
+
+L200:
+    *info = 0;
+    i__1 = *n - 1;
+    for (i__ = 1; i__ <= i__1; ++i__) {
+	if (e[i__] != 0.) {
+	    ++(*info);
+	}
+/* L210: */
+    }
+L220:
+    return 0;
+
+/*     End of DBDSQR */
+
+} /* dbdsqr_ */