#include "clapack.h" /* Table of constant values */ static integer c__1 = 1; /* Subroutine */ int dlasdq_(char *uplo, integer *sqre, 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; /* Local variables */ integer i__, j; doublereal r__, cs, sn; integer np1, isub; doublereal smin; integer sqre1; extern logical lsame_(char *, char *); extern /* Subroutine */ int dlasr_(char *, char *, char *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *), dswap_(integer *, doublereal *, integer * , doublereal *, integer *); integer iuplo; extern /* Subroutine */ int dlartg_(doublereal *, doublereal *, doublereal *, doublereal *, doublereal *), xerbla_(char *, integer *), dbdsqr_(char *, integer *, integer *, integer *, integer *, doublereal *, doublereal *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *, doublereal *, integer *); logical rotate; /* -- LAPACK auxiliary routine (version 3.1) -- */ /* Univ. of Tennessee, Univ. of California Berkeley and NAG Ltd.. */ /* November 2006 */ /* .. Scalar Arguments .. */ /* .. */ /* .. Array Arguments .. */ /* .. */ /* Purpose */ /* ======= */ /* DLASDQ computes the singular value decomposition (SVD) of a real */ /* (upper or lower) bidiagonal matrix with diagonal D and offdiagonal */ /* E, accumulating the transformations if desired. Letting B denote */ /* the input bidiagonal matrix, the algorithm computes orthogonal */ /* matrices Q and P such that B = Q * S * P' (P' denotes the transpose */ /* of P). The singular values S are overwritten on D. */ /* The input matrix U is changed to U * Q if desired. */ /* The input matrix VT is changed to P' * VT if desired. */ /* The input matrix C is changed to Q' * C if desired. */ /* See "Computing Small Singular Values of Bidiagonal Matrices With */ /* Guaranteed High Relative Accuracy," by J. Demmel and W. Kahan, */ /* LAPACK Working Note #3, for a detailed description of the algorithm. */ /* Arguments */ /* ========= */ /* UPLO (input) CHARACTER*1 */ /* On entry, UPLO specifies whether the input bidiagonal matrix */ /* is upper or lower bidiagonal, and wether it is square are */ /* not. */ /* UPLO = 'U' or 'u' B is upper bidiagonal. */ /* UPLO = 'L' or 'l' B is lower bidiagonal. */ /* SQRE (input) INTEGER */ /* = 0: then the input matrix is N-by-N. */ /* = 1: then the input matrix is N-by-(N+1) if UPLU = 'U' and */ /* (N+1)-by-N if UPLU = 'L'. */ /* The bidiagonal matrix has */ /* N = NL + NR + 1 rows and */ /* M = N + SQRE >= N columns. */ /* N (input) INTEGER */ /* On entry, N specifies the number of rows and columns */ /* in the matrix. N must be at least 0. */ /* NCVT (input) INTEGER */ /* On entry, NCVT specifies the number of columns of */ /* the matrix VT. NCVT must be at least 0. */ /* NRU (input) INTEGER */ /* On entry, NRU specifies the number of rows of */ /* the matrix U. NRU must be at least 0. */ /* NCC (input) INTEGER */ /* On entry, NCC specifies the number of columns of */ /* the matrix C. NCC must be at least 0. */ /* D (input/output) DOUBLE PRECISION array, dimension (N) */ /* On entry, D contains the diagonal entries of the */ /* bidiagonal matrix whose SVD is desired. On normal exit, */ /* D contains the singular values in ascending order. */ /* E (input/output) DOUBLE PRECISION array. */ /* dimension is (N-1) if SQRE = 0 and N if SQRE = 1. */ /* On entry, the entries of E contain the offdiagonal entries */ /* of the bidiagonal matrix whose SVD is desired. On normal */ /* exit, E will contain 0. If the algorithm does not converge, */ /* D and E will contain the diagonal and superdiagonal entries */ /* of a bidiagonal matrix orthogonally equivalent to the one */ /* given as input. */ /* VT (input/output) DOUBLE PRECISION array, dimension (LDVT, NCVT) */ /* On entry, contains a matrix which on exit has been */ /* premultiplied by P', dimension N-by-NCVT if SQRE = 0 */ /* and (N+1)-by-NCVT if SQRE = 1 (not referenced if NCVT=0). */ /* LDVT (input) INTEGER */ /* On entry, LDVT specifies the leading dimension of VT as */ /* declared in the calling (sub) program. LDVT must be at */ /* least 1. If NCVT is nonzero LDVT must also be at least N. */ /* U (input/output) DOUBLE PRECISION array, dimension (LDU, N) */ /* On entry, contains a matrix which on exit has been */ /* postmultiplied by Q, dimension NRU-by-N if SQRE = 0 */ /* and NRU-by-(N+1) if SQRE = 1 (not referenced if NRU=0). */ /* LDU (input) INTEGER */ /* On entry, LDU specifies the leading dimension of U as */ /* declared in the calling (sub) program. LDU must be at */ /* least max( 1, NRU ) . */ /* C (input/output) DOUBLE PRECISION array, dimension (LDC, NCC) */ /* On entry, contains an N-by-NCC matrix which on exit */ /* has been premultiplied by Q' dimension N-by-NCC if SQRE = 0 */ /* and (N+1)-by-NCC if SQRE = 1 (not referenced if NCC=0). */ /* LDC (input) INTEGER */ /* On entry, LDC specifies the leading dimension of C as */ /* declared in the calling (sub) program. LDC must be at */ /* least 1. If NCC is nonzero, LDC must also be at least N. */ /* WORK (workspace) DOUBLE PRECISION array, dimension (4*N) */ /* Workspace. Only referenced if one of NCVT, NRU, or NCC is */ /* nonzero, and if N is at least 2. */ /* INFO (output) INTEGER */ /* On exit, a value of 0 indicates a successful exit. */ /* If INFO < 0, argument number -INFO is illegal. */ /* If INFO > 0, the algorithm did not converge, and INFO */ /* specifies how many superdiagonals did not converge. */ /* Further Details */ /* =============== */ /* Based on contributions by */ /* Ming Gu and Huan Ren, Computer Science Division, University of */ /* California at Berkeley, USA */ /* ===================================================================== */ /* .. Parameters .. */ /* .. */ /* .. Local Scalars .. */ /* .. */ /* .. External Subroutines .. */ /* .. */ /* .. External Functions .. */ /* .. */ /* .. 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; iuplo = 0; if (lsame_(uplo, "U")) { iuplo = 1; } if (lsame_(uplo, "L")) { iuplo = 2; } if (iuplo == 0) { *info = -1; } else if (*sqre < 0 || *sqre > 1) { *info = -2; } else if (*n < 0) { *info = -3; } else if (*ncvt < 0) { *info = -4; } else if (*nru < 0) { *info = -5; } else if (*ncc < 0) { *info = -6; } else if (*ncvt == 0 && *ldvt < 1 || *ncvt > 0 && *ldvt < max(1,*n)) { *info = -10; } else if (*ldu < max(1,*nru)) { *info = -12; } else if (*ncc == 0 && *ldc < 1 || *ncc > 0 && *ldc < max(1,*n)) { *info = -14; } if (*info != 0) { i__1 = -(*info); xerbla_("DLASDQ", &i__1); return 0; } if (*n == 0) { return 0; } /* ROTATE is true if any singular vectors desired, false otherwise */ rotate = *ncvt > 0 || *nru > 0 || *ncc > 0; np1 = *n + 1; sqre1 = *sqre; /* If matrix non-square upper bidiagonal, rotate to be lower */ /* bidiagonal. The rotations are on the right. */ if (iuplo == 1 && sqre1 == 1) { 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]; if (rotate) { work[i__] = cs; work[*n + i__] = sn; } /* L10: */ } dlartg_(&d__[*n], &e[*n], &cs, &sn, &r__); d__[*n] = r__; e[*n] = 0.; if (rotate) { work[*n] = cs; work[*n + *n] = sn; } iuplo = 2; sqre1 = 0; /* Update singular vectors if desired. */ if (*ncvt > 0) { dlasr_("L", "V", "F", &np1, ncvt, &work[1], &work[np1], &vt[ vt_offset], ldvt); } } /* If matrix lower bidiagonal, rotate to be upper bidiagonal */ /* by applying Givens rotations on the left. */ if (iuplo == 2) { 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]; if (rotate) { work[i__] = cs; work[*n + i__] = sn; } /* L20: */ } /* If matrix (N+1)-by-N lower bidiagonal, one additional */ /* rotation is needed. */ if (sqre1 == 1) { dlartg_(&d__[*n], &e[*n], &cs, &sn, &r__); d__[*n] = r__; if (rotate) { work[*n] = cs; work[*n + *n] = sn; } } /* Update singular vectors if desired. */ if (*nru > 0) { if (sqre1 == 0) { dlasr_("R", "V", "F", nru, n, &work[1], &work[np1], &u[ u_offset], ldu); } else { dlasr_("R", "V", "F", nru, &np1, &work[1], &work[np1], &u[ u_offset], ldu); } } if (*ncc > 0) { if (sqre1 == 0) { dlasr_("L", "V", "F", n, ncc, &work[1], &work[np1], &c__[ c_offset], ldc); } else { dlasr_("L", "V", "F", &np1, ncc, &work[1], &work[np1], &c__[ c_offset], ldc); } } } /* Call DBDSQR to compute the SVD of the reduced real */ /* N-by-N upper bidiagonal matrix. */ dbdsqr_("U", n, ncvt, nru, ncc, &d__[1], &e[1], &vt[vt_offset], ldvt, &u[ u_offset], ldu, &c__[c_offset], ldc, &work[1], info); /* Sort the singular values into ascending order (insertion sort on */ /* singular values, but only one transposition per singular vector) */ i__1 = *n; for (i__ = 1; i__ <= i__1; ++i__) { /* Scan for smallest D(I). */ isub = i__; smin = d__[i__]; i__2 = *n; for (j = i__ + 1; j <= i__2; ++j) { if (d__[j] < smin) { isub = j; smin = d__[j]; } /* L30: */ } if (isub != i__) { /* Swap singular values and vectors. */ d__[isub] = d__[i__]; d__[i__] = smin; if (*ncvt > 0) { dswap_(ncvt, &vt[isub + vt_dim1], ldvt, &vt[i__ + vt_dim1], ldvt); } if (*nru > 0) { dswap_(nru, &u[isub * u_dim1 + 1], &c__1, &u[i__ * u_dim1 + 1] , &c__1); } if (*ncc > 0) { dswap_(ncc, &c__[isub + c_dim1], ldc, &c__[i__ + c_dim1], ldc) ; } } /* L40: */ } return 0; /* End of DLASDQ */ } /* dlasdq_ */