#include "blaswrap.h" /* -- translated by f2c (version 19990503). You must link the resulting object file with the libraries: -lf2c -lm (in that order) */ #include "f2c.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 */ static doublereal abse; static integer idir; static doublereal abss; static integer oldm; static doublereal cosl; static integer isub, iter; static doublereal unfl, sinl, cosr, smin, smax, sinr; extern /* Subroutine */ int drot_(integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, doublereal *), dlas2_( doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); static doublereal f, g, h__; static integer i__, j, m; static doublereal r__; extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *, integer *); extern logical lsame_(char *, char *); static doublereal oldcs; extern /* Subroutine */ int dlasr_(char *, char *, char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *); static integer oldll; static doublereal shift, sigmn, oldsn; extern /* Subroutine */ int dswap_(integer *, doublereal *, integer *, doublereal *, integer *); static integer maxit; static doublereal sminl, sigmx; static logical lower; extern /* Subroutine */ int dlasq1_(integer *, doublereal *, doublereal *, doublereal *, integer *), dlasv2_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *, doublereal *); static doublereal cs; static integer ll; extern doublereal dlamch_(char *); static doublereal sn, mu; extern /* Subroutine */ int dlartg_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), xerbla_(char *, integer *); static doublereal sminoa, thresh; static logical rotate; static doublereal sminlo; static integer nm1; static doublereal tolmul; static integer nm12, nm13, lll; static doublereal eps, sll, tol; #define c___ref(a_1,a_2) c__[(a_2)*c_dim1 + a_1] #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 (version 3.0) -- Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd., Courant Institute, Argonne National Lab, and Rice University October 31, 1999 Purpose ======= DBDSQR computes the singular value decomposition (SVD) of a real N-by-N (upper or lower) bidiagonal matrix B: B = Q * S * P' (P' denotes the transpose of P), where S is a diagonal matrix with non-negative diagonal elements (the singular values of B), and Q and P are orthogonal matrices. The routine computes S, and optionally computes U * Q, P' * VT, or Q' * C, for given real input matrices U, VT, and 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) On entry, the elements of E contain the offdiagonal elements of the bidiagonal matrix whose SVD is desired. On normal exit (INFO = 0), E is destroyed. If the algorithm does not converge (INFO > 0), D and E will contain the diagonal and superdiagonal elements of a bidiagonal matrix orthogonally equivalent to the one given as input. E(N) is used for workspace. VT (input/output) DOUBLE PRECISION array, dimension (LDVT, NCVT) On entry, an N-by-NCVT matrix VT. On exit, VT is overwritten by P' * VT. VT is 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. U is 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' * C. C is 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: 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. ===================================================================== Test the input parameters. Parameter adjustments */ --d__; --e; vt_dim1 = *ldvt; vt_offset = 1 + vt_dim1 * 1; vt -= vt_offset; u_dim1 = *ldu; u_offset = 1 + u_dim1 * 1; u -= u_offset; c_dim1 = *ldc; c_offset = 1 + c_dim1 * 1; 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_ref(m - 1, 1), ldvt, &vt_ref(m, 1), ldvt, &cosr, & sinr); } if (*nru > 0) { drot_(nru, &u_ref(1, m - 1), &c__1, &u_ref(1, m), &c__1, &cosl, & sinl); } if (*ncc > 0) { drot_(ncc, &c___ref(m - 1, 1), ldc, &c___ref(m, 1), 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; } sminlo = sminl; 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; } sminlo = sminl; 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_ref(ll, 1), ldvt); } if (*nru > 0) { i__1 = m - ll + 1; dlasr_("R", "V", "F", nru, &i__1, &work[nm12 + 1], &work[nm13 + 1], &u_ref(1, ll), ldu); } if (*ncc > 0) { i__1 = m - ll + 1; dlasr_("L", "V", "F", &i__1, ncc, &work[nm12 + 1], &work[nm13 + 1], &c___ref(ll, 1), 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_ref(ll, 1), ldvt); } if (*nru > 0) { i__1 = m - ll + 1; dlasr_("R", "V", "B", nru, &i__1, &work[1], &work[*n], &u_ref( 1, ll), ldu); } if (*ncc > 0) { i__1 = m - ll + 1; dlasr_("L", "V", "B", &i__1, ncc, &work[1], &work[*n], & c___ref(ll, 1), 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_ref(ll, 1), ldvt); } if (*nru > 0) { i__1 = m - ll + 1; dlasr_("R", "V", "F", nru, &i__1, &work[nm12 + 1], &work[nm13 + 1], &u_ref(1, ll), ldu); } if (*ncc > 0) { i__1 = m - ll + 1; dlasr_("L", "V", "F", &i__1, ncc, &work[nm12 + 1], &work[nm13 + 1], &c___ref(ll, 1), 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_ref(ll, 1), ldvt); } if (*nru > 0) { i__1 = m - ll + 1; dlasr_("R", "V", "B", nru, &i__1, &work[1], &work[*n], &u_ref( 1, ll), ldu); } if (*ncc > 0) { i__1 = m - ll + 1; dlasr_("L", "V", "B", &i__1, ncc, &work[1], &work[*n], & c___ref(ll, 1), 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_ref(i__, 1), 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_ref(isub, 1), ldvt, &vt_ref(*n + 1 - i__, 1), ldvt); } if (*nru > 0) { dswap_(nru, &u_ref(1, isub), &c__1, &u_ref(1, *n + 1 - i__), & c__1); } if (*ncc > 0) { dswap_(ncc, &c___ref(isub, 1), ldc, &c___ref(*n + 1 - i__, 1), 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_ */ #undef vt_ref #undef u_ref #undef c___ref