906 lines
24 KiB
C
906 lines
24 KiB
C
#include "blaswrap.h"
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/* -- translated by f2c (version 19990503).
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You must link the resulting object file with the libraries:
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-lf2c -lm (in that order)
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*/
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#ifdef _cpluscplus
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extern "C" {
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#endif
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#include "f2c.h"
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/* Table of constant values */
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static doublereal c_b15 = -.125;
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static integer c__1 = 1;
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static doublereal c_b49 = 1.;
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static doublereal c_b72 = -1.;
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/* Subroutine */ int dbdsqr_(char *uplo, integer *n, integer *ncvt, integer *
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nru, integer *ncc, doublereal *d__, doublereal *e, doublereal *vt,
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integer *ldvt, doublereal *u, integer *ldu, doublereal *c__, integer *
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ldc, doublereal *work, integer *info)
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{
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/* System generated locals */
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integer c_dim1, c_offset, u_dim1, u_offset, vt_dim1, vt_offset, i__1,
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i__2;
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doublereal d__1, d__2, d__3, d__4;
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/* Builtin functions */
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double pow_dd(doublereal *, doublereal *), sqrt(doublereal), d_sign(
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doublereal *, doublereal *);
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/* Local variables */
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static doublereal abse;
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static integer idir;
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static doublereal abss;
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static integer oldm;
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static doublereal cosl;
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static integer isub, iter;
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static doublereal unfl, sinl, cosr, smin, smax, sinr;
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extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
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doublereal *, integer *, doublereal *, doublereal *), dlas2_(
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doublereal *, doublereal *, doublereal *, doublereal *,
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doublereal *);
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static doublereal f, g, h__;
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static integer i__, j, m;
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static doublereal r__;
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extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
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integer *);
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extern logical lsame_(char *, char *);
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static doublereal oldcs;
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extern /* Subroutine */ int dlasr_(char *, char *, char *, integer *,
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integer *, doublereal *, doublereal *, doublereal *, integer *);
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static integer oldll;
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static doublereal shift, sigmn, oldsn;
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extern /* Subroutine */ int dswap_(integer *, doublereal *, integer *,
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doublereal *, integer *);
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static integer maxit;
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static doublereal sminl, sigmx;
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static logical lower;
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extern /* Subroutine */ int dlasq1_(integer *, doublereal *, doublereal *,
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doublereal *, integer *), dlasv2_(doublereal *, doublereal *,
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doublereal *, doublereal *, doublereal *, doublereal *,
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doublereal *, doublereal *, doublereal *);
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static doublereal cs;
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static integer ll;
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extern doublereal dlamch_(char *);
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static doublereal sn, mu;
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extern /* Subroutine */ int dlartg_(doublereal *, doublereal *,
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doublereal *, doublereal *, doublereal *), xerbla_(char *,
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integer *);
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static doublereal sminoa, thresh;
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static logical rotate;
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static doublereal sminlo;
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static integer nm1;
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static doublereal tolmul;
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static integer nm12, nm13, lll;
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static doublereal eps, sll, tol;
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#define c___ref(a_1,a_2) c__[(a_2)*c_dim1 + a_1]
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#define u_ref(a_1,a_2) u[(a_2)*u_dim1 + a_1]
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#define vt_ref(a_1,a_2) vt[(a_2)*vt_dim1 + a_1]
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/* -- LAPACK routine (version 3.0) --
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Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
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Courant Institute, Argonne National Lab, and Rice University
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October 31, 1999
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Purpose
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=======
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DBDSQR computes the singular value decomposition (SVD) of a real
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N-by-N (upper or lower) bidiagonal matrix B: B = Q * S * P' (P'
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denotes the transpose of P), where S is a diagonal matrix with
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non-negative diagonal elements (the singular values of B), and Q
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and P are orthogonal matrices.
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The routine computes S, and optionally computes U * Q, P' * VT,
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or Q' * C, for given real input matrices U, VT, and C.
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See "Computing Small Singular Values of Bidiagonal Matrices With
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Guaranteed High Relative Accuracy," by J. Demmel and W. Kahan,
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LAPACK Working Note #3 (or SIAM J. Sci. Statist. Comput. vol. 11,
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no. 5, pp. 873-912, Sept 1990) and
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"Accurate singular values and differential qd algorithms," by
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B. Parlett and V. Fernando, Technical Report CPAM-554, Mathematics
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Department, University of California at Berkeley, July 1992
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for a detailed description of the algorithm.
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Arguments
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=========
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UPLO (input) CHARACTER*1
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= 'U': B is upper bidiagonal;
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= 'L': B is lower bidiagonal.
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N (input) INTEGER
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The order of the matrix B. N >= 0.
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NCVT (input) INTEGER
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The number of columns of the matrix VT. NCVT >= 0.
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NRU (input) INTEGER
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The number of rows of the matrix U. NRU >= 0.
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NCC (input) INTEGER
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The number of columns of the matrix C. NCC >= 0.
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D (input/output) DOUBLE PRECISION array, dimension (N)
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On entry, the n diagonal elements of the bidiagonal matrix B.
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On exit, if INFO=0, the singular values of B in decreasing
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order.
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E (input/output) DOUBLE PRECISION array, dimension (N)
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On entry, the elements of E contain the
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offdiagonal elements of the bidiagonal matrix whose SVD
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is desired. On normal exit (INFO = 0), E is destroyed.
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If the algorithm does not converge (INFO > 0), D and E
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will contain the diagonal and superdiagonal elements of a
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bidiagonal matrix orthogonally equivalent to the one given
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as input. E(N) is used for workspace.
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VT (input/output) DOUBLE PRECISION array, dimension (LDVT, NCVT)
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On entry, an N-by-NCVT matrix VT.
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On exit, VT is overwritten by P' * VT.
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VT is not referenced if NCVT = 0.
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LDVT (input) INTEGER
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The leading dimension of the array VT.
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LDVT >= max(1,N) if NCVT > 0; LDVT >= 1 if NCVT = 0.
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U (input/output) DOUBLE PRECISION array, dimension (LDU, N)
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On entry, an NRU-by-N matrix U.
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On exit, U is overwritten by U * Q.
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U is not referenced if NRU = 0.
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LDU (input) INTEGER
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The leading dimension of the array U. LDU >= max(1,NRU).
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C (input/output) DOUBLE PRECISION array, dimension (LDC, NCC)
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On entry, an N-by-NCC matrix C.
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On exit, C is overwritten by Q' * C.
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C is not referenced if NCC = 0.
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LDC (input) INTEGER
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The leading dimension of the array C.
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LDC >= max(1,N) if NCC > 0; LDC >=1 if NCC = 0.
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WORK (workspace) DOUBLE PRECISION array, dimension (4*N)
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INFO (output) INTEGER
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= 0: successful exit
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< 0: If INFO = -i, the i-th argument had an illegal value
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> 0: the algorithm did not converge; D and E contain the
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elements of a bidiagonal matrix which is orthogonally
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similar to the input matrix B; if INFO = i, i
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elements of E have not converged to zero.
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Internal Parameters
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===================
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TOLMUL DOUBLE PRECISION, default = max(10,min(100,EPS**(-1/8)))
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TOLMUL controls the convergence criterion of the QR loop.
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If it is positive, TOLMUL*EPS is the desired relative
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precision in the computed singular values.
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If it is negative, abs(TOLMUL*EPS*sigma_max) is the
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desired absolute accuracy in the computed singular
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values (corresponds to relative accuracy
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abs(TOLMUL*EPS) in the largest singular value.
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abs(TOLMUL) should be between 1 and 1/EPS, and preferably
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between 10 (for fast convergence) and .1/EPS
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(for there to be some accuracy in the results).
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Default is to lose at either one eighth or 2 of the
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available decimal digits in each computed singular value
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(whichever is smaller).
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MAXITR INTEGER, default = 6
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MAXITR controls the maximum number of passes of the
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algorithm through its inner loop. The algorithms stops
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(and so fails to converge) if the number of passes
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through the inner loop exceeds MAXITR*N**2.
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=====================================================================
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Test the input parameters.
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Parameter adjustments */
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--d__;
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--e;
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vt_dim1 = *ldvt;
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vt_offset = 1 + vt_dim1 * 1;
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vt -= vt_offset;
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u_dim1 = *ldu;
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u_offset = 1 + u_dim1 * 1;
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u -= u_offset;
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c_dim1 = *ldc;
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c_offset = 1 + c_dim1 * 1;
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c__ -= c_offset;
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--work;
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/* Function Body */
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*info = 0;
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lower = lsame_(uplo, "L");
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if (! lsame_(uplo, "U") && ! lower) {
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*info = -1;
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} else if (*n < 0) {
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*info = -2;
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} else if (*ncvt < 0) {
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*info = -3;
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} else if (*nru < 0) {
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*info = -4;
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} else if (*ncc < 0) {
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*info = -5;
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} else if ((*ncvt == 0 && *ldvt < 1) ||
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(*ncvt > 0 && *ldvt < max(1,*n))) {
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*info = -9;
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} else if (*ldu < max(1,*nru)) {
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*info = -11;
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} else if ((*ncc == 0 && *ldc < 1) ||
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(*ncc > 0 && *ldc < max(1,*n))) {
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*info = -13;
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}
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if (*info != 0) {
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i__1 = -(*info);
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xerbla_("DBDSQR", &i__1);
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return 0;
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}
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if (*n == 0) {
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return 0;
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}
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if (*n == 1) {
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goto L160;
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}
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/* ROTATE is true if any singular vectors desired, false otherwise */
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rotate = *ncvt > 0 || *nru > 0 || *ncc > 0;
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/* If no singular vectors desired, use qd algorithm */
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if (! rotate) {
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dlasq1_(n, &d__[1], &e[1], &work[1], info);
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return 0;
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}
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nm1 = *n - 1;
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nm12 = nm1 + nm1;
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nm13 = nm12 + nm1;
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idir = 0;
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/* Get machine constants */
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eps = dlamch_("Epsilon");
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unfl = dlamch_("Safe minimum");
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/* If matrix lower bidiagonal, rotate to be upper bidiagonal
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by applying Givens rotations on the left */
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if (lower) {
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i__1 = *n - 1;
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for (i__ = 1; i__ <= i__1; ++i__) {
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dlartg_(&d__[i__], &e[i__], &cs, &sn, &r__);
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d__[i__] = r__;
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e[i__] = sn * d__[i__ + 1];
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d__[i__ + 1] = cs * d__[i__ + 1];
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work[i__] = cs;
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work[nm1 + i__] = sn;
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/* L10: */
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}
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/* Update singular vectors if desired */
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if (*nru > 0) {
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dlasr_("R", "V", "F", nru, n, &work[1], &work[*n], &u[u_offset],
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ldu);
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}
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if (*ncc > 0) {
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dlasr_("L", "V", "F", n, ncc, &work[1], &work[*n], &c__[c_offset],
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ldc);
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}
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}
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/* Compute singular values to relative accuracy TOL
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(By setting TOL to be negative, algorithm will compute
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singular values to absolute accuracy ABS(TOL)*norm(input matrix))
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Computing MAX
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Computing MIN */
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d__3 = 100., d__4 = pow_dd(&eps, &c_b15);
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d__1 = 10., d__2 = min(d__3,d__4);
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tolmul = max(d__1,d__2);
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tol = tolmul * eps;
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/* Compute approximate maximum, minimum singular values */
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smax = 0.;
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i__1 = *n;
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for (i__ = 1; i__ <= i__1; ++i__) {
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/* Computing MAX */
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d__2 = smax, d__3 = (d__1 = d__[i__], abs(d__1));
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smax = max(d__2,d__3);
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/* L20: */
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}
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i__1 = *n - 1;
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for (i__ = 1; i__ <= i__1; ++i__) {
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/* Computing MAX */
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d__2 = smax, d__3 = (d__1 = e[i__], abs(d__1));
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smax = max(d__2,d__3);
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/* L30: */
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}
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sminl = 0.;
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if (tol >= 0.) {
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/* Relative accuracy desired */
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sminoa = abs(d__[1]);
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if (sminoa == 0.) {
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goto L50;
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}
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mu = sminoa;
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i__1 = *n;
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for (i__ = 2; i__ <= i__1; ++i__) {
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mu = (d__2 = d__[i__], abs(d__2)) * (mu / (mu + (d__1 = e[i__ - 1]
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, abs(d__1))));
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sminoa = min(sminoa,mu);
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if (sminoa == 0.) {
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goto L50;
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}
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/* L40: */
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}
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L50:
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sminoa /= sqrt((doublereal) (*n));
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/* Computing MAX */
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d__1 = tol * sminoa, d__2 = *n * 6 * *n * unfl;
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thresh = max(d__1,d__2);
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} else {
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/* Absolute accuracy desired
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Computing MAX */
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d__1 = abs(tol) * smax, d__2 = *n * 6 * *n * unfl;
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thresh = max(d__1,d__2);
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}
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/* Prepare for main iteration loop for the singular values
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(MAXIT is the maximum number of passes through the inner
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loop permitted before nonconvergence signalled.) */
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maxit = *n * 6 * *n;
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iter = 0;
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oldll = -1;
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oldm = -1;
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/* M points to last element of unconverged part of matrix */
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m = *n;
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/* Begin main iteration loop */
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L60:
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/* Check for convergence or exceeding iteration count */
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if (m <= 1) {
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goto L160;
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}
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if (iter > maxit) {
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goto L200;
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}
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/* Find diagonal block of matrix to work on */
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if (tol < 0. && (d__1 = d__[m], abs(d__1)) <= thresh) {
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d__[m] = 0.;
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}
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smax = (d__1 = d__[m], abs(d__1));
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smin = smax;
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i__1 = m - 1;
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for (lll = 1; lll <= i__1; ++lll) {
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ll = m - lll;
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abss = (d__1 = d__[ll], abs(d__1));
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abse = (d__1 = e[ll], abs(d__1));
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if (tol < 0. && abss <= thresh) {
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d__[ll] = 0.;
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}
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if (abse <= thresh) {
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goto L80;
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}
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smin = min(smin,abss);
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/* Computing MAX */
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d__1 = max(smax,abss);
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smax = max(d__1,abse);
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/* L70: */
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}
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ll = 0;
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goto L90;
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L80:
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e[ll] = 0.;
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/* Matrix splits since E(LL) = 0 */
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if (ll == m - 1) {
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/* Convergence of bottom singular value, return to top of loop */
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--m;
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goto L60;
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}
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L90:
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++ll;
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/* E(LL) through E(M-1) are nonzero, E(LL-1) is zero */
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if (ll == m - 1) {
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/* 2 by 2 block, handle separately */
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dlasv2_(&d__[m - 1], &e[m - 1], &d__[m], &sigmn, &sigmx, &sinr, &cosr,
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&sinl, &cosl);
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d__[m - 1] = sigmx;
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e[m - 1] = 0.;
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d__[m] = sigmn;
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/* Compute singular vectors, if desired */
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if (*ncvt > 0) {
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drot_(ncvt, &vt_ref(m - 1, 1), ldvt, &vt_ref(m, 1), ldvt, &cosr, &
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sinr);
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}
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if (*nru > 0) {
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drot_(nru, &u_ref(1, m - 1), &c__1, &u_ref(1, m), &c__1, &cosl, &
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sinl);
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}
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if (*ncc > 0) {
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drot_(ncc, &c___ref(m - 1, 1), ldc, &c___ref(m, 1), ldc, &cosl, &
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sinl);
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}
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m += -2;
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goto L60;
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}
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/* If working on new submatrix, choose shift direction
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(from larger end diagonal element towards smaller) */
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if (ll > oldm || m < oldll) {
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if ((d__1 = d__[ll], abs(d__1)) >= (d__2 = d__[m], abs(d__2))) {
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/* Chase bulge from top (big end) to bottom (small end) */
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idir = 1;
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} else {
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/* Chase bulge from bottom (big end) to top (small end) */
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idir = 2;
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}
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}
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/* Apply convergence tests */
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if (idir == 1) {
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/* Run convergence test in forward direction
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First apply standard test to bottom of matrix */
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if (((d__2 = e[m - 1], abs(d__2)) <=
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abs(tol) * (d__1 = d__[m], abs(d__1))) ||
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(tol < 0. && (d__3 = e[m - 1], abs(d__3)) <= thresh))
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{
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e[m - 1] = 0.;
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goto L60;
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}
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if (tol >= 0.) {
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/* If relative accuracy desired,
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apply convergence criterion forward */
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mu = (d__1 = d__[ll], abs(d__1));
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sminl = mu;
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i__1 = m - 1;
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for (lll = ll; lll <= i__1; ++lll) {
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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
|
|
|
|
|
|
#ifdef _cpluscplus
|
|
}
|
|
#endif
|