/*
NOTE: This is generated code. Look in Misc/lapack_lite for information on
remaking this file.
*/
#include "f2c.h"
#ifdef HAVE_CONFIG
#include "config.h"
#else
extern doublereal dlamch_(char *);
#define EPSILON dlamch_("Epsilon")
#define SAFEMINIMUM dlamch_("Safe minimum")
#define PRECISION dlamch_("Precision")
#define BASE dlamch_("Base")
#endif
extern doublereal dlapy2_(doublereal *x, doublereal *y);
/*
f2c knows the exact rules for precedence, and so omits parentheses where not
strictly necessary. Since this is generated code, we don't really care if
it's readable, and we know what is written is correct. So don't warn about
them.
*/
#if defined(__GNUC__)
#pragma GCC diagnostic ignored "-Wparentheses"
#endif
/* Table of constant values */
static integer c__9 = 9;
static integer c__0 = 0;
static doublereal c_b15 = 1.;
static integer c__1 = 1;
static doublereal c_b29 = 0.;
static doublereal c_b94 = -.125;
static doublereal c_b151 = -1.;
static integer c_n1 = -1;
static integer c__3 = 3;
static integer c__2 = 2;
static integer c__65 = 65;
static integer c__6 = 6;
static integer c__12 = 12;
static integer c__49 = 49;
static integer c__4 = 4;
static logical c_false = FALSE_;
static integer c__13 = 13;
static integer c__15 = 15;
static integer c__14 = 14;
static integer c__16 = 16;
static logical c_true = TRUE_;
static integer c__10 = 10;
static integer c__11 = 11;
static doublereal c_b3192 = 2.;
/* Subroutine */ int dbdsdc_(char *uplo, char *compq, integer *n, doublereal *
d__, doublereal *e, doublereal *u, integer *ldu, doublereal *vt,
integer *ldvt, doublereal *q, integer *iq, doublereal *work, integer *
iwork, integer *info)
{
/* System generated locals */
integer u_dim1, u_offset, vt_dim1, vt_offset, i__1, i__2;
doublereal d__1;
/* Local variables */
static integer i__, j, k;
static doublereal p, r__;
static integer z__, ic, ii, kk;
static doublereal cs;
static integer is, iu;
static doublereal sn;
static integer nm1;
static doublereal eps;
static integer ivt, difl, difr, ierr, perm, mlvl, sqre;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dlasr_(char *, char *, char *, integer *,
integer *, doublereal *, doublereal *, doublereal *, integer *), dcopy_(integer *, doublereal *, integer *
, doublereal *, integer *), dswap_(integer *, doublereal *,
integer *, doublereal *, integer *);
static integer poles, iuplo, nsize, start;
extern /* Subroutine */ int dlasd0_(integer *, integer *, doublereal *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
integer *, integer *, doublereal *, integer *);
extern /* Subroutine */ int dlasda_(integer *, integer *, integer *,
integer *, doublereal *, doublereal *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *, integer *, integer *, integer *,
doublereal *, doublereal *, doublereal *, doublereal *, integer *,
integer *), dlascl_(char *, integer *, integer *, doublereal *,
doublereal *, integer *, integer *, doublereal *, integer *,
integer *), dlasdq_(char *, integer *, integer *, integer
*, integer *, integer *, doublereal *, doublereal *, doublereal *,
integer *, doublereal *, integer *, doublereal *, integer *,
doublereal *, integer *), dlaset_(char *, integer *,
integer *, doublereal *, doublereal *, doublereal *, integer *), dlartg_(doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int xerbla_(char *, integer *);
static integer givcol;
extern doublereal dlanst_(char *, integer *, doublereal *, doublereal *);
static integer icompq;
static doublereal orgnrm;
static integer givnum, givptr, qstart, smlsiz, wstart, smlszp;
/*
-- LAPACK routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DBDSDC computes the singular value decomposition (SVD) of a real
N-by-N (upper or lower) bidiagonal matrix B: B = U * S * VT,
using a divide and conquer method, where S is a diagonal matrix
with non-negative diagonal elements (the singular values of B), and
U and VT are orthogonal matrices of left and right singular vectors,
respectively. DBDSDC can be used to compute all singular values,
and optionally, singular vectors or singular vectors in compact form.
This code makes very mild assumptions about floating point
arithmetic. It will work on machines with a guard digit in
add/subtract, or on those binary machines without guard digits
which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2.
It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none. See DLASD3 for details.
The code currently calls DLASDQ if singular values only are desired.
However, it can be slightly modified to compute singular values
using the divide and conquer method.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': B is upper bidiagonal.
= 'L': B is lower bidiagonal.
COMPQ (input) CHARACTER*1
Specifies whether singular vectors are to be computed
as follows:
= 'N': Compute singular values only;
= 'P': Compute singular values and compute singular
vectors in compact form;
= 'I': Compute singular values and singular vectors.
N (input) INTEGER
The order of the matrix B. N >= 0.
D (input/output) 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.
E (input/output) DOUBLE PRECISION array, dimension (N-1)
On entry, the elements of E contain the offdiagonal
elements of the bidiagonal matrix whose SVD is desired.
On exit, E has been destroyed.
U (output) DOUBLE PRECISION array, dimension (LDU,N)
If COMPQ = 'I', then:
On exit, if INFO = 0, U contains the left singular vectors
of the bidiagonal matrix.
For other values of COMPQ, U is not referenced.
LDU (input) INTEGER
The leading dimension of the array U. LDU >= 1.
If singular vectors are desired, then LDU >= max( 1, N ).
VT (output) DOUBLE PRECISION array, dimension (LDVT,N)
If COMPQ = 'I', then:
On exit, if INFO = 0, VT' contains the right singular
vectors of the bidiagonal matrix.
For other values of COMPQ, VT is not referenced.
LDVT (input) INTEGER
The leading dimension of the array VT. LDVT >= 1.
If singular vectors are desired, then LDVT >= max( 1, N ).
Q (output) DOUBLE PRECISION array, dimension (LDQ)
If COMPQ = 'P', then:
On exit, if INFO = 0, Q and IQ contain the left
and right singular vectors in a compact form,
requiring O(N log N) space instead of 2*N**2.
In particular, Q contains all the DOUBLE PRECISION data in
LDQ >= N*(11 + 2*SMLSIZ + 8*INT(LOG_2(N/(SMLSIZ+1))))
words of memory, where SMLSIZ is returned by ILAENV and
is equal to the maximum size of the subproblems at the
bottom of the computation tree (usually about 25).
For other values of COMPQ, Q is not referenced.
IQ (output) INTEGER array, dimension (LDIQ)
If COMPQ = 'P', then:
On exit, if INFO = 0, Q and IQ contain the left
and right singular vectors in a compact form,
requiring O(N log N) space instead of 2*N**2.
In particular, IQ contains all INTEGER data in
LDIQ >= N*(3 + 3*INT(LOG_2(N/(SMLSIZ+1))))
words of memory, where SMLSIZ is returned by ILAENV and
is equal to the maximum size of the subproblems at the
bottom of the computation tree (usually about 25).
For other values of COMPQ, IQ is not referenced.
WORK (workspace) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
If COMPQ = 'N' then LWORK >= (4 * N).
If COMPQ = 'P' then LWORK >= (6 * N).
If COMPQ = 'I' then LWORK >= (3 * N**2 + 4 * N).
IWORK (workspace) INTEGER array, dimension (8*N)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: The algorithm failed to compute a singular value.
The update process of divide and conquer failed.
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Changed dimension statement in comment describing E from (N) to
(N-1). Sven, 17 Feb 05.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--e;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
vt_dim1 = *ldvt;
vt_offset = 1 + vt_dim1;
vt -= vt_offset;
--q;
--iq;
--work;
--iwork;
/* Function Body */
*info = 0;
iuplo = 0;
if (lsame_(uplo, "U")) {
iuplo = 1;
}
if (lsame_(uplo, "L")) {
iuplo = 2;
}
if (lsame_(compq, "N")) {
icompq = 0;
} else if (lsame_(compq, "P")) {
icompq = 1;
} else if (lsame_(compq, "I")) {
icompq = 2;
} else {
icompq = -1;
}
if (iuplo == 0) {
*info = -1;
} else if (icompq < 0) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*ldu < 1 || icompq == 2 && *ldu < *n) {
*info = -7;
} else if (*ldvt < 1 || icompq == 2 && *ldvt < *n) {
*info = -9;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DBDSDC", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
smlsiz = ilaenv_(&c__9, "DBDSDC", " ", &c__0, &c__0, &c__0, &c__0, (
ftnlen)6, (ftnlen)1);
if (*n == 1) {
if (icompq == 1) {
q[1] = d_sign(&c_b15, &d__[1]);
q[smlsiz * *n + 1] = 1.;
} else if (icompq == 2) {
u[u_dim1 + 1] = d_sign(&c_b15, &d__[1]);
vt[vt_dim1 + 1] = 1.;
}
d__[1] = abs(d__[1]);
return 0;
}
nm1 = *n - 1;
/*
If matrix lower bidiagonal, rotate to be upper bidiagonal
by applying Givens rotations on the left
*/
wstart = 1;
qstart = 3;
if (icompq == 1) {
dcopy_(n, &d__[1], &c__1, &q[1], &c__1);
i__1 = *n - 1;
dcopy_(&i__1, &e[1], &c__1, &q[*n + 1], &c__1);
}
if (iuplo == 2) {
qstart = 5;
wstart = (*n << 1) - 1;
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
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 (icompq == 1) {
q[i__ + (*n << 1)] = cs;
q[i__ + *n * 3] = sn;
} else if (icompq == 2) {
work[i__] = cs;
work[nm1 + i__] = -sn;
}
/* L10: */
}
}
/* If ICOMPQ = 0, use DLASDQ to compute the singular values. */
if (icompq == 0) {
dlasdq_("U", &c__0, n, &c__0, &c__0, &c__0, &d__[1], &e[1], &vt[
vt_offset], ldvt, &u[u_offset], ldu, &u[u_offset], ldu, &work[
wstart], info);
goto L40;
}
/*
If N is smaller than the minimum divide size SMLSIZ, then solve
the problem with another solver.
*/
if (*n <= smlsiz) {
if (icompq == 2) {
dlaset_("A", n, n, &c_b29, &c_b15, &u[u_offset], ldu);
dlaset_("A", n, n, &c_b29, &c_b15, &vt[vt_offset], ldvt);
dlasdq_("U", &c__0, n, n, n, &c__0, &d__[1], &e[1], &vt[vt_offset]
, ldvt, &u[u_offset], ldu, &u[u_offset], ldu, &work[
wstart], info);
} else if (icompq == 1) {
iu = 1;
ivt = iu + *n;
dlaset_("A", n, n, &c_b29, &c_b15, &q[iu + (qstart - 1) * *n], n);
dlaset_("A", n, n, &c_b29, &c_b15, &q[ivt + (qstart - 1) * *n], n);
dlasdq_("U", &c__0, n, n, n, &c__0, &d__[1], &e[1], &q[ivt + (
qstart - 1) * *n], n, &q[iu + (qstart - 1) * *n], n, &q[
iu + (qstart - 1) * *n], n, &work[wstart], info);
}
goto L40;
}
if (icompq == 2) {
dlaset_("A", n, n, &c_b29, &c_b15, &u[u_offset], ldu);
dlaset_("A", n, n, &c_b29, &c_b15, &vt[vt_offset], ldvt);
}
/* Scale. */
orgnrm = dlanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.) {
return 0;
}
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, n, &c__1, &d__[1], n, &ierr);
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, &nm1, &c__1, &e[1], &nm1, &
ierr);
eps = EPSILON;
mlvl = (integer) (log((doublereal) (*n) / (doublereal) (smlsiz + 1)) /
log(2.)) + 1;
smlszp = smlsiz + 1;
if (icompq == 1) {
iu = 1;
ivt = smlsiz + 1;
difl = ivt + smlszp;
difr = difl + mlvl;
z__ = difr + (mlvl << 1);
ic = z__ + mlvl;
is = ic + 1;
poles = is + 1;
givnum = poles + (mlvl << 1);
k = 1;
givptr = 2;
perm = 3;
givcol = perm + mlvl;
}
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((d__1 = d__[i__], abs(d__1)) < eps) {
d__[i__] = d_sign(&eps, &d__[i__]);
}
/* L20: */
}
start = 1;
sqre = 0;
i__1 = nm1;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((d__1 = e[i__], abs(d__1)) < eps || i__ == nm1) {
/*
Subproblem found. First determine its size and then
apply divide and conquer on it.
*/
if (i__ < nm1) {
/* A subproblem with E(I) small for I < NM1. */
nsize = i__ - start + 1;
} else if ((d__1 = e[i__], abs(d__1)) >= eps) {
/* A subproblem with E(NM1) not too small but I = NM1. */
nsize = *n - start + 1;
} else {
/*
A subproblem with E(NM1) small. This implies an
1-by-1 subproblem at D(N). Solve this 1-by-1 problem
first.
*/
nsize = i__ - start + 1;
if (icompq == 2) {
u[*n + *n * u_dim1] = d_sign(&c_b15, &d__[*n]);
vt[*n + *n * vt_dim1] = 1.;
} else if (icompq == 1) {
q[*n + (qstart - 1) * *n] = d_sign(&c_b15, &d__[*n]);
q[*n + (smlsiz + qstart - 1) * *n] = 1.;
}
d__[*n] = (d__1 = d__[*n], abs(d__1));
}
if (icompq == 2) {
dlasd0_(&nsize, &sqre, &d__[start], &e[start], &u[start +
start * u_dim1], ldu, &vt[start + start * vt_dim1],
ldvt, &smlsiz, &iwork[1], &work[wstart], info);
} else {
dlasda_(&icompq, &smlsiz, &nsize, &sqre, &d__[start], &e[
start], &q[start + (iu + qstart - 2) * *n], n, &q[
start + (ivt + qstart - 2) * *n], &iq[start + k * *n],
&q[start + (difl + qstart - 2) * *n], &q[start + (
difr + qstart - 2) * *n], &q[start + (z__ + qstart -
2) * *n], &q[start + (poles + qstart - 2) * *n], &iq[
start + givptr * *n], &iq[start + givcol * *n], n, &
iq[start + perm * *n], &q[start + (givnum + qstart -
2) * *n], &q[start + (ic + qstart - 2) * *n], &q[
start + (is + qstart - 2) * *n], &work[wstart], &
iwork[1], info);
}
if (*info != 0) {
return 0;
}
start = i__ + 1;
}
/* L30: */
}
/* Unscale */
dlascl_("G", &c__0, &c__0, &c_b15, &orgnrm, n, &c__1, &d__[1], n, &ierr);
L40:
/* Use Selection Sort to minimize swaps of singular vectors */
i__1 = *n;
for (ii = 2; ii <= i__1; ++ii) {
i__ = ii - 1;
kk = i__;
p = d__[i__];
i__2 = *n;
for (j = ii; j <= i__2; ++j) {
if (d__[j] > p) {
kk = j;
p = d__[j];
}
/* L50: */
}
if (kk != i__) {
d__[kk] = d__[i__];
d__[i__] = p;
if (icompq == 1) {
iq[i__] = kk;
} else if (icompq == 2) {
dswap_(n, &u[i__ * u_dim1 + 1], &c__1, &u[kk * u_dim1 + 1], &
c__1);
dswap_(n, &vt[i__ + vt_dim1], ldvt, &vt[kk + vt_dim1], ldvt);
}
} else if (icompq == 1) {
iq[i__] = i__;
}
/* L60: */
}
/* If ICOMPQ = 1, use IQ(N,1) as the indicator for UPLO */
if (icompq == 1) {
if (iuplo == 1) {
iq[*n] = 1;
} else {
iq[*n] = 0;
}
}
/*
If B is lower bidiagonal, update U by those Givens rotations
which rotated B to be upper bidiagonal
*/
if (iuplo == 2 && icompq == 2) {
dlasr_("L", "V", "B", n, n, &work[1], &work[*n], &u[u_offset], ldu);
}
return 0;
/* End of DBDSDC */
} /* dbdsdc_ */
/* 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;
/* Local variables */
static doublereal f, g, h__;
static integer i__, j, m;
static doublereal r__, cs;
static integer ll;
static doublereal sn, mu;
static integer nm1, nm12, nm13, lll;
static doublereal eps, sll, tol, 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 *), 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 *);
extern /* Subroutine */ int dlartg_(doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *), xerbla_(char *,
integer *);
static doublereal sminoa, thresh;
static logical rotate;
static doublereal tolmul;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
January 2007
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.
=====================================================================
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 = EPSILON;
unfl = SAFEMINIMUM;
/*
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_b94);
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_b15, &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_b15, &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_b151, &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_ */
/* Subroutine */ int dgebak_(char *job, char *side, integer *n, integer *ilo,
integer *ihi, doublereal *scale, integer *m, doublereal *v, integer *
ldv, integer *info)
{
/* System generated locals */
integer v_dim1, v_offset, i__1;
/* Local variables */
static integer i__, k;
static doublereal s;
static integer ii;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dswap_(integer *, doublereal *, integer *,
doublereal *, integer *);
static logical leftv;
extern /* Subroutine */ int xerbla_(char *, integer *);
static logical rightv;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGEBAK forms the right or left eigenvectors of a real general matrix
by backward transformation on the computed eigenvectors of the
balanced matrix output by DGEBAL.
Arguments
=========
JOB (input) CHARACTER*1
Specifies the type of backward transformation required:
= 'N', do nothing, return immediately;
= 'P', do backward transformation for permutation only;
= 'S', do backward transformation for scaling only;
= 'B', do backward transformations for both permutation and
scaling.
JOB must be the same as the argument JOB supplied to DGEBAL.
SIDE (input) CHARACTER*1
= 'R': V contains right eigenvectors;
= 'L': V contains left eigenvectors.
N (input) INTEGER
The number of rows of the matrix V. N >= 0.
ILO (input) INTEGER
IHI (input) INTEGER
The integers ILO and IHI determined by DGEBAL.
1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0.
SCALE (input) DOUBLE PRECISION array, dimension (N)
Details of the permutation and scaling factors, as returned
by DGEBAL.
M (input) INTEGER
The number of columns of the matrix V. M >= 0.
V (input/output) DOUBLE PRECISION array, dimension (LDV,M)
On entry, the matrix of right or left eigenvectors to be
transformed, as returned by DHSEIN or DTREVC.
On exit, V is overwritten by the transformed eigenvectors.
LDV (input) INTEGER
The leading dimension of the array V. LDV >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
=====================================================================
Decode and Test the input parameters
*/
/* Parameter adjustments */
--scale;
v_dim1 = *ldv;
v_offset = 1 + v_dim1;
v -= v_offset;
/* Function Body */
rightv = lsame_(side, "R");
leftv = lsame_(side, "L");
*info = 0;
if (! lsame_(job, "N") && ! lsame_(job, "P") && ! lsame_(job, "S")
&& ! lsame_(job, "B")) {
*info = -1;
} else if (! rightv && ! leftv) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*ilo < 1 || *ilo > max(1,*n)) {
*info = -4;
} else if (*ihi < min(*ilo,*n) || *ihi > *n) {
*info = -5;
} else if (*m < 0) {
*info = -7;
} else if (*ldv < max(1,*n)) {
*info = -9;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGEBAK", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*m == 0) {
return 0;
}
if (lsame_(job, "N")) {
return 0;
}
if (*ilo == *ihi) {
goto L30;
}
/* Backward balance */
if (lsame_(job, "S") || lsame_(job, "B")) {
if (rightv) {
i__1 = *ihi;
for (i__ = *ilo; i__ <= i__1; ++i__) {
s = scale[i__];
dscal_(m, &s, &v[i__ + v_dim1], ldv);
/* L10: */
}
}
if (leftv) {
i__1 = *ihi;
for (i__ = *ilo; i__ <= i__1; ++i__) {
s = 1. / scale[i__];
dscal_(m, &s, &v[i__ + v_dim1], ldv);
/* L20: */
}
}
}
/*
Backward permutation
For I = ILO-1 step -1 until 1,
IHI+1 step 1 until N do --
*/
L30:
if (lsame_(job, "P") || lsame_(job, "B")) {
if (rightv) {
i__1 = *n;
for (ii = 1; ii <= i__1; ++ii) {
i__ = ii;
if (i__ >= *ilo && i__ <= *ihi) {
goto L40;
}
if (i__ < *ilo) {
i__ = *ilo - ii;
}
k = (integer) scale[i__];
if (k == i__) {
goto L40;
}
dswap_(m, &v[i__ + v_dim1], ldv, &v[k + v_dim1], ldv);
L40:
;
}
}
if (leftv) {
i__1 = *n;
for (ii = 1; ii <= i__1; ++ii) {
i__ = ii;
if (i__ >= *ilo && i__ <= *ihi) {
goto L50;
}
if (i__ < *ilo) {
i__ = *ilo - ii;
}
k = (integer) scale[i__];
if (k == i__) {
goto L50;
}
dswap_(m, &v[i__ + v_dim1], ldv, &v[k + v_dim1], ldv);
L50:
;
}
}
}
return 0;
/* End of DGEBAK */
} /* dgebak_ */
/* Subroutine */ int dgebal_(char *job, integer *n, doublereal *a, integer *
lda, integer *ilo, integer *ihi, doublereal *scale, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2;
doublereal d__1, d__2;
/* Local variables */
static doublereal c__, f, g;
static integer i__, j, k, l, m;
static doublereal r__, s, ca, ra;
static integer ica, ira, iexc;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dswap_(integer *, doublereal *, integer *,
doublereal *, integer *);
static doublereal sfmin1, sfmin2, sfmax1, sfmax2;
extern integer idamax_(integer *, doublereal *, integer *);
extern logical disnan_(doublereal *);
extern /* Subroutine */ int xerbla_(char *, integer *);
static logical noconv;
/*
-- LAPACK routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DGEBAL balances a general real matrix A. This involves, first,
permuting A by a similarity transformation to isolate eigenvalues
in the first 1 to ILO-1 and last IHI+1 to N elements on the
diagonal; and second, applying a diagonal similarity transformation
to rows and columns ILO to IHI to make the rows and columns as
close in norm as possible. Both steps are optional.
Balancing may reduce the 1-norm of the matrix, and improve the
accuracy of the computed eigenvalues and/or eigenvectors.
Arguments
=========
JOB (input) CHARACTER*1
Specifies the operations to be performed on A:
= 'N': none: simply set ILO = 1, IHI = N, SCALE(I) = 1.0
for i = 1,...,N;
= 'P': permute only;
= 'S': scale only;
= 'B': both permute and scale.
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the input matrix A.
On exit, A is overwritten by the balanced matrix.
If JOB = 'N', A is not referenced.
See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
ILO (output) INTEGER
IHI (output) INTEGER
ILO and IHI are set to integers such that on exit
A(i,j) = 0 if i > j and j = 1,...,ILO-1 or I = IHI+1,...,N.
If JOB = 'N' or 'S', ILO = 1 and IHI = N.
SCALE (output) DOUBLE PRECISION array, dimension (N)
Details of the permutations and scaling factors applied to
A. If P(j) is the index of the row and column interchanged
with row and column j and D(j) is the scaling factor
applied to row and column j, then
SCALE(j) = P(j) for j = 1,...,ILO-1
= D(j) for j = ILO,...,IHI
= P(j) for j = IHI+1,...,N.
The order in which the interchanges are made is N to IHI+1,
then 1 to ILO-1.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
The permutations consist of row and column interchanges which put
the matrix in the form
( T1 X Y )
P A P = ( 0 B Z )
( 0 0 T2 )
where T1 and T2 are upper triangular matrices whose eigenvalues lie
along the diagonal. The column indices ILO and IHI mark the starting
and ending columns of the submatrix B. Balancing consists of applying
a diagonal similarity transformation inv(D) * B * D to make the
1-norms of each row of B and its corresponding column nearly equal.
The output matrix is
( T1 X*D Y )
( 0 inv(D)*B*D inv(D)*Z ).
( 0 0 T2 )
Information about the permutations P and the diagonal matrix D is
returned in the vector SCALE.
This subroutine is based on the EISPACK routine BALANC.
Modified by Tzu-Yi Chen, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--scale;
/* Function Body */
*info = 0;
if (! lsame_(job, "N") && ! lsame_(job, "P") && ! lsame_(job, "S")
&& ! lsame_(job, "B")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGEBAL", &i__1);
return 0;
}
k = 1;
l = *n;
if (*n == 0) {
goto L210;
}
if (lsame_(job, "N")) {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
scale[i__] = 1.;
/* L10: */
}
goto L210;
}
if (lsame_(job, "S")) {
goto L120;
}
/* Permutation to isolate eigenvalues if possible */
goto L50;
/* Row and column exchange. */
L20:
scale[m] = (doublereal) j;
if (j == m) {
goto L30;
}
dswap_(&l, &a[j * a_dim1 + 1], &c__1, &a[m * a_dim1 + 1], &c__1);
i__1 = *n - k + 1;
dswap_(&i__1, &a[j + k * a_dim1], lda, &a[m + k * a_dim1], lda);
L30:
switch (iexc) {
case 1: goto L40;
case 2: goto L80;
}
/* Search for rows isolating an eigenvalue and push them down. */
L40:
if (l == 1) {
goto L210;
}
--l;
L50:
for (j = l; j >= 1; --j) {
i__1 = l;
for (i__ = 1; i__ <= i__1; ++i__) {
if (i__ == j) {
goto L60;
}
if (a[j + i__ * a_dim1] != 0.) {
goto L70;
}
L60:
;
}
m = l;
iexc = 1;
goto L20;
L70:
;
}
goto L90;
/* Search for columns isolating an eigenvalue and push them left. */
L80:
++k;
L90:
i__1 = l;
for (j = k; j <= i__1; ++j) {
i__2 = l;
for (i__ = k; i__ <= i__2; ++i__) {
if (i__ == j) {
goto L100;
}
if (a[i__ + j * a_dim1] != 0.) {
goto L110;
}
L100:
;
}
m = k;
iexc = 2;
goto L20;
L110:
;
}
L120:
i__1 = l;
for (i__ = k; i__ <= i__1; ++i__) {
scale[i__] = 1.;
/* L130: */
}
if (lsame_(job, "P")) {
goto L210;
}
/*
Balance the submatrix in rows K to L.
Iterative loop for norm reduction
*/
sfmin1 = SAFEMINIMUM / PRECISION;
sfmax1 = 1. / sfmin1;
sfmin2 = sfmin1 * 2.;
sfmax2 = 1. / sfmin2;
L140:
noconv = FALSE_;
i__1 = l;
for (i__ = k; i__ <= i__1; ++i__) {
c__ = 0.;
r__ = 0.;
i__2 = l;
for (j = k; j <= i__2; ++j) {
if (j == i__) {
goto L150;
}
c__ += (d__1 = a[j + i__ * a_dim1], abs(d__1));
r__ += (d__1 = a[i__ + j * a_dim1], abs(d__1));
L150:
;
}
ica = idamax_(&l, &a[i__ * a_dim1 + 1], &c__1);
ca = (d__1 = a[ica + i__ * a_dim1], abs(d__1));
i__2 = *n - k + 1;
ira = idamax_(&i__2, &a[i__ + k * a_dim1], lda);
ra = (d__1 = a[i__ + (ira + k - 1) * a_dim1], abs(d__1));
/* Guard against zero C or R due to underflow. */
if (c__ == 0. || r__ == 0.) {
goto L200;
}
g = r__ / 2.;
f = 1.;
s = c__ + r__;
L160:
/* Computing MAX */
d__1 = max(f,c__);
/* Computing MIN */
d__2 = min(r__,g);
if (c__ >= g || max(d__1,ca) >= sfmax2 || min(d__2,ra) <= sfmin2) {
goto L170;
}
d__1 = c__ + f + ca + r__ + g + ra;
if (disnan_(&d__1)) {
/* Exit if NaN to avoid infinite loop */
*info = -3;
i__2 = -(*info);
xerbla_("DGEBAL", &i__2);
return 0;
}
f *= 2.;
c__ *= 2.;
ca *= 2.;
r__ /= 2.;
g /= 2.;
ra /= 2.;
goto L160;
L170:
g = c__ / 2.;
L180:
/* Computing MIN */
d__1 = min(f,c__), d__1 = min(d__1,g);
if (g < r__ || max(r__,ra) >= sfmax2 || min(d__1,ca) <= sfmin2) {
goto L190;
}
f /= 2.;
c__ /= 2.;
g /= 2.;
ca /= 2.;
r__ *= 2.;
ra *= 2.;
goto L180;
/* Now balance. */
L190:
if (c__ + r__ >= s * .95) {
goto L200;
}
if (f < 1. && scale[i__] < 1.) {
if (f * scale[i__] <= sfmin1) {
goto L200;
}
}
if (f > 1. && scale[i__] > 1.) {
if (scale[i__] >= sfmax1 / f) {
goto L200;
}
}
g = 1. / f;
scale[i__] *= f;
noconv = TRUE_;
i__2 = *n - k + 1;
dscal_(&i__2, &g, &a[i__ + k * a_dim1], lda);
dscal_(&l, &f, &a[i__ * a_dim1 + 1], &c__1);
L200:
;
}
if (noconv) {
goto L140;
}
L210:
*ilo = k;
*ihi = l;
return 0;
/* End of DGEBAL */
} /* dgebal_ */
/* Subroutine */ int dgebd2_(integer *m, integer *n, doublereal *a, integer *
lda, doublereal *d__, doublereal *e, doublereal *tauq, doublereal *
taup, doublereal *work, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *), dlarfg_(integer *, doublereal *,
doublereal *, integer *, doublereal *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGEBD2 reduces a real general m by n matrix A to upper or lower
bidiagonal form B by an orthogonal transformation: Q' * A * P = B.
If m >= n, B is upper bidiagonal; if m < n, B is lower bidiagonal.
Arguments
=========
M (input) INTEGER
The number of rows in the matrix A. M >= 0.
N (input) INTEGER
The number of columns in the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the m by n general matrix to be reduced.
On exit,
if m >= n, the diagonal and the first superdiagonal are
overwritten with the upper bidiagonal matrix B; the
elements below the diagonal, with the array TAUQ, represent
the orthogonal matrix Q as a product of elementary
reflectors, and the elements above the first superdiagonal,
with the array TAUP, represent the orthogonal matrix P as
a product of elementary reflectors;
if m < n, the diagonal and the first subdiagonal are
overwritten with the lower bidiagonal matrix B; the
elements below the first subdiagonal, with the array TAUQ,
represent the orthogonal matrix Q as a product of
elementary reflectors, and the elements above the diagonal,
with the array TAUP, represent the orthogonal matrix P as
a product of elementary reflectors.
See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
D (output) DOUBLE PRECISION array, dimension (min(M,N))
The diagonal elements of the bidiagonal matrix B:
D(i) = A(i,i).
E (output) DOUBLE PRECISION array, dimension (min(M,N)-1)
The off-diagonal elements of the bidiagonal matrix B:
if m >= n, E(i) = A(i,i+1) for i = 1,2,...,n-1;
if m < n, E(i) = A(i+1,i) for i = 1,2,...,m-1.
TAUQ (output) DOUBLE PRECISION array dimension (min(M,N))
The scalar factors of the elementary reflectors which
represent the orthogonal matrix Q. See Further Details.
TAUP (output) DOUBLE PRECISION array, dimension (min(M,N))
The scalar factors of the elementary reflectors which
represent the orthogonal matrix P. See Further Details.
WORK (workspace) DOUBLE PRECISION array, dimension (max(M,N))
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
The matrices Q and P are represented as products of elementary
reflectors:
If m >= n,
Q = H(1) H(2) . . . H(n) and P = G(1) G(2) . . . G(n-1)
Each H(i) and G(i) has the form:
H(i) = I - tauq * v * v' and G(i) = I - taup * u * u'
where tauq and taup are real scalars, and v and u are real vectors;
v(1:i-1) = 0, v(i) = 1, and v(i+1:m) is stored on exit in A(i+1:m,i);
u(1:i) = 0, u(i+1) = 1, and u(i+2:n) is stored on exit in A(i,i+2:n);
tauq is stored in TAUQ(i) and taup in TAUP(i).
If m < n,
Q = H(1) H(2) . . . H(m-1) and P = G(1) G(2) . . . G(m)
Each H(i) and G(i) has the form:
H(i) = I - tauq * v * v' and G(i) = I - taup * u * u'
where tauq and taup are real scalars, and v and u are real vectors;
v(1:i) = 0, v(i+1) = 1, and v(i+2:m) is stored on exit in A(i+2:m,i);
u(1:i-1) = 0, u(i) = 1, and u(i+1:n) is stored on exit in A(i,i+1:n);
tauq is stored in TAUQ(i) and taup in TAUP(i).
The contents of A on exit are illustrated by the following examples:
m = 6 and n = 5 (m > n): m = 5 and n = 6 (m < n):
( d e u1 u1 u1 ) ( d u1 u1 u1 u1 u1 )
( v1 d e u2 u2 ) ( e d u2 u2 u2 u2 )
( v1 v2 d e u3 ) ( v1 e d u3 u3 u3 )
( v1 v2 v3 d e ) ( v1 v2 e d u4 u4 )
( v1 v2 v3 v4 d ) ( v1 v2 v3 e d u5 )
( v1 v2 v3 v4 v5 )
where d and e denote diagonal and off-diagonal elements of B, vi
denotes an element of the vector defining H(i), and ui an element of
the vector defining G(i).
=====================================================================
Test the input parameters
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--d__;
--e;
--tauq;
--taup;
--work;
/* Function Body */
*info = 0;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*m)) {
*info = -4;
}
if (*info < 0) {
i__1 = -(*info);
xerbla_("DGEBD2", &i__1);
return 0;
}
if (*m >= *n) {
/* Reduce to upper bidiagonal form */
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Generate elementary reflector H(i) to annihilate A(i+1:m,i) */
i__2 = *m - i__ + 1;
/* Computing MIN */
i__3 = i__ + 1;
dlarfg_(&i__2, &a[i__ + i__ * a_dim1], &a[min(i__3,*m) + i__ *
a_dim1], &c__1, &tauq[i__]);
d__[i__] = a[i__ + i__ * a_dim1];
a[i__ + i__ * a_dim1] = 1.;
/* Apply H(i) to A(i:m,i+1:n) from the left */
if (i__ < *n) {
i__2 = *m - i__ + 1;
i__3 = *n - i__;
dlarf_("Left", &i__2, &i__3, &a[i__ + i__ * a_dim1], &c__1, &
tauq[i__], &a[i__ + (i__ + 1) * a_dim1], lda, &work[1]
);
}
a[i__ + i__ * a_dim1] = d__[i__];
if (i__ < *n) {
/*
Generate elementary reflector G(i) to annihilate
A(i,i+2:n)
*/
i__2 = *n - i__;
/* Computing MIN */
i__3 = i__ + 2;
dlarfg_(&i__2, &a[i__ + (i__ + 1) * a_dim1], &a[i__ + min(
i__3,*n) * a_dim1], lda, &taup[i__]);
e[i__] = a[i__ + (i__ + 1) * a_dim1];
a[i__ + (i__ + 1) * a_dim1] = 1.;
/* Apply G(i) to A(i+1:m,i+1:n) from the right */
i__2 = *m - i__;
i__3 = *n - i__;
dlarf_("Right", &i__2, &i__3, &a[i__ + (i__ + 1) * a_dim1],
lda, &taup[i__], &a[i__ + 1 + (i__ + 1) * a_dim1],
lda, &work[1]);
a[i__ + (i__ + 1) * a_dim1] = e[i__];
} else {
taup[i__] = 0.;
}
/* L10: */
}
} else {
/* Reduce to lower bidiagonal form */
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Generate elementary reflector G(i) to annihilate A(i,i+1:n) */
i__2 = *n - i__ + 1;
/* Computing MIN */
i__3 = i__ + 1;
dlarfg_(&i__2, &a[i__ + i__ * a_dim1], &a[i__ + min(i__3,*n) *
a_dim1], lda, &taup[i__]);
d__[i__] = a[i__ + i__ * a_dim1];
a[i__ + i__ * a_dim1] = 1.;
/* Apply G(i) to A(i+1:m,i:n) from the right */
if (i__ < *m) {
i__2 = *m - i__;
i__3 = *n - i__ + 1;
dlarf_("Right", &i__2, &i__3, &a[i__ + i__ * a_dim1], lda, &
taup[i__], &a[i__ + 1 + i__ * a_dim1], lda, &work[1]);
}
a[i__ + i__ * a_dim1] = d__[i__];
if (i__ < *m) {
/*
Generate elementary reflector H(i) to annihilate
A(i+2:m,i)
*/
i__2 = *m - i__;
/* Computing MIN */
i__3 = i__ + 2;
dlarfg_(&i__2, &a[i__ + 1 + i__ * a_dim1], &a[min(i__3,*m) +
i__ * a_dim1], &c__1, &tauq[i__]);
e[i__] = a[i__ + 1 + i__ * a_dim1];
a[i__ + 1 + i__ * a_dim1] = 1.;
/* Apply H(i) to A(i+1:m,i+1:n) from the left */
i__2 = *m - i__;
i__3 = *n - i__;
dlarf_("Left", &i__2, &i__3, &a[i__ + 1 + i__ * a_dim1], &
c__1, &tauq[i__], &a[i__ + 1 + (i__ + 1) * a_dim1],
lda, &work[1]);
a[i__ + 1 + i__ * a_dim1] = e[i__];
} else {
tauq[i__] = 0.;
}
/* L20: */
}
}
return 0;
/* End of DGEBD2 */
} /* dgebd2_ */
/* Subroutine */ int dgebrd_(integer *m, integer *n, doublereal *a, integer *
lda, doublereal *d__, doublereal *e, doublereal *tauq, doublereal *
taup, doublereal *work, integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer i__, j, nb, nx;
static doublereal ws;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static integer nbmin, iinfo, minmn;
extern /* Subroutine */ int dgebd2_(integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *), dlabrd_(integer *, integer *, integer *
, doublereal *, integer *, doublereal *, doublereal *, doublereal
*, doublereal *, doublereal *, integer *, doublereal *, integer *)
, xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static integer ldwrkx, ldwrky, lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGEBRD reduces a general real M-by-N matrix A to upper or lower
bidiagonal form B by an orthogonal transformation: Q**T * A * P = B.
If m >= n, B is upper bidiagonal; if m < n, B is lower bidiagonal.
Arguments
=========
M (input) INTEGER
The number of rows in the matrix A. M >= 0.
N (input) INTEGER
The number of columns in the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the M-by-N general matrix to be reduced.
On exit,
if m >= n, the diagonal and the first superdiagonal are
overwritten with the upper bidiagonal matrix B; the
elements below the diagonal, with the array TAUQ, represent
the orthogonal matrix Q as a product of elementary
reflectors, and the elements above the first superdiagonal,
with the array TAUP, represent the orthogonal matrix P as
a product of elementary reflectors;
if m < n, the diagonal and the first subdiagonal are
overwritten with the lower bidiagonal matrix B; the
elements below the first subdiagonal, with the array TAUQ,
represent the orthogonal matrix Q as a product of
elementary reflectors, and the elements above the diagonal,
with the array TAUP, represent the orthogonal matrix P as
a product of elementary reflectors.
See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
D (output) DOUBLE PRECISION array, dimension (min(M,N))
The diagonal elements of the bidiagonal matrix B:
D(i) = A(i,i).
E (output) DOUBLE PRECISION array, dimension (min(M,N)-1)
The off-diagonal elements of the bidiagonal matrix B:
if m >= n, E(i) = A(i,i+1) for i = 1,2,...,n-1;
if m < n, E(i) = A(i+1,i) for i = 1,2,...,m-1.
TAUQ (output) DOUBLE PRECISION array dimension (min(M,N))
The scalar factors of the elementary reflectors which
represent the orthogonal matrix Q. See Further Details.
TAUP (output) DOUBLE PRECISION array, dimension (min(M,N))
The scalar factors of the elementary reflectors which
represent the orthogonal matrix P. See Further Details.
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The length of the array WORK. LWORK >= max(1,M,N).
For optimum performance LWORK >= (M+N)*NB, where NB
is the optimal blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
The matrices Q and P are represented as products of elementary
reflectors:
If m >= n,
Q = H(1) H(2) . . . H(n) and P = G(1) G(2) . . . G(n-1)
Each H(i) and G(i) has the form:
H(i) = I - tauq * v * v' and G(i) = I - taup * u * u'
where tauq and taup are real scalars, and v and u are real vectors;
v(1:i-1) = 0, v(i) = 1, and v(i+1:m) is stored on exit in A(i+1:m,i);
u(1:i) = 0, u(i+1) = 1, and u(i+2:n) is stored on exit in A(i,i+2:n);
tauq is stored in TAUQ(i) and taup in TAUP(i).
If m < n,
Q = H(1) H(2) . . . H(m-1) and P = G(1) G(2) . . . G(m)
Each H(i) and G(i) has the form:
H(i) = I - tauq * v * v' and G(i) = I - taup * u * u'
where tauq and taup are real scalars, and v and u are real vectors;
v(1:i) = 0, v(i+1) = 1, and v(i+2:m) is stored on exit in A(i+2:m,i);
u(1:i-1) = 0, u(i) = 1, and u(i+1:n) is stored on exit in A(i,i+1:n);
tauq is stored in TAUQ(i) and taup in TAUP(i).
The contents of A on exit are illustrated by the following examples:
m = 6 and n = 5 (m > n): m = 5 and n = 6 (m < n):
( d e u1 u1 u1 ) ( d u1 u1 u1 u1 u1 )
( v1 d e u2 u2 ) ( e d u2 u2 u2 u2 )
( v1 v2 d e u3 ) ( v1 e d u3 u3 u3 )
( v1 v2 v3 d e ) ( v1 v2 e d u4 u4 )
( v1 v2 v3 v4 d ) ( v1 v2 v3 e d u5 )
( v1 v2 v3 v4 v5 )
where d and e denote diagonal and off-diagonal elements of B, vi
denotes an element of the vector defining H(i), and ui an element of
the vector defining G(i).
=====================================================================
Test the input parameters
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--d__;
--e;
--tauq;
--taup;
--work;
/* Function Body */
*info = 0;
/* Computing MAX */
i__1 = 1, i__2 = ilaenv_(&c__1, "DGEBRD", " ", m, n, &c_n1, &c_n1, (
ftnlen)6, (ftnlen)1);
nb = max(i__1,i__2);
lwkopt = (*m + *n) * nb;
work[1] = (doublereal) lwkopt;
lquery = *lwork == -1;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*m)) {
*info = -4;
} else /* if(complicated condition) */ {
/* Computing MAX */
i__1 = max(1,*m);
if (*lwork < max(i__1,*n) && ! lquery) {
*info = -10;
}
}
if (*info < 0) {
i__1 = -(*info);
xerbla_("DGEBRD", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
minmn = min(*m,*n);
if (minmn == 0) {
work[1] = 1.;
return 0;
}
ws = (doublereal) max(*m,*n);
ldwrkx = *m;
ldwrky = *n;
if (nb > 1 && nb < minmn) {
/*
Set the crossover point NX.
Computing MAX
*/
i__1 = nb, i__2 = ilaenv_(&c__3, "DGEBRD", " ", m, n, &c_n1, &c_n1, (
ftnlen)6, (ftnlen)1);
nx = max(i__1,i__2);
/* Determine when to switch from blocked to unblocked code. */
if (nx < minmn) {
ws = (doublereal) ((*m + *n) * nb);
if ((doublereal) (*lwork) < ws) {
/*
Not enough work space for the optimal NB, consider using
a smaller block size.
*/
nbmin = ilaenv_(&c__2, "DGEBRD", " ", m, n, &c_n1, &c_n1, (
ftnlen)6, (ftnlen)1);
if (*lwork >= (*m + *n) * nbmin) {
nb = *lwork / (*m + *n);
} else {
nb = 1;
nx = minmn;
}
}
}
} else {
nx = minmn;
}
i__1 = minmn - nx;
i__2 = nb;
for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/*
Reduce rows and columns i:i+nb-1 to bidiagonal form and return
the matrices X and Y which are needed to update the unreduced
part of the matrix
*/
i__3 = *m - i__ + 1;
i__4 = *n - i__ + 1;
dlabrd_(&i__3, &i__4, &nb, &a[i__ + i__ * a_dim1], lda, &d__[i__], &e[
i__], &tauq[i__], &taup[i__], &work[1], &ldwrkx, &work[ldwrkx
* nb + 1], &ldwrky);
/*
Update the trailing submatrix A(i+nb:m,i+nb:n), using an update
of the form A := A - V*Y' - X*U'
*/
i__3 = *m - i__ - nb + 1;
i__4 = *n - i__ - nb + 1;
dgemm_("No transpose", "Transpose", &i__3, &i__4, &nb, &c_b151, &a[
i__ + nb + i__ * a_dim1], lda, &work[ldwrkx * nb + nb + 1], &
ldwrky, &c_b15, &a[i__ + nb + (i__ + nb) * a_dim1], lda);
i__3 = *m - i__ - nb + 1;
i__4 = *n - i__ - nb + 1;
dgemm_("No transpose", "No transpose", &i__3, &i__4, &nb, &c_b151, &
work[nb + 1], &ldwrkx, &a[i__ + (i__ + nb) * a_dim1], lda, &
c_b15, &a[i__ + nb + (i__ + nb) * a_dim1], lda);
/* Copy diagonal and off-diagonal elements of B back into A */
if (*m >= *n) {
i__3 = i__ + nb - 1;
for (j = i__; j <= i__3; ++j) {
a[j + j * a_dim1] = d__[j];
a[j + (j + 1) * a_dim1] = e[j];
/* L10: */
}
} else {
i__3 = i__ + nb - 1;
for (j = i__; j <= i__3; ++j) {
a[j + j * a_dim1] = d__[j];
a[j + 1 + j * a_dim1] = e[j];
/* L20: */
}
}
/* L30: */
}
/* Use unblocked code to reduce the remainder of the matrix */
i__2 = *m - i__ + 1;
i__1 = *n - i__ + 1;
dgebd2_(&i__2, &i__1, &a[i__ + i__ * a_dim1], lda, &d__[i__], &e[i__], &
tauq[i__], &taup[i__], &work[1], &iinfo);
work[1] = ws;
return 0;
/* End of DGEBRD */
} /* dgebrd_ */
/* Subroutine */ int dgeev_(char *jobvl, char *jobvr, integer *n, doublereal *
a, integer *lda, doublereal *wr, doublereal *wi, doublereal *vl,
integer *ldvl, doublereal *vr, integer *ldvr, doublereal *work,
integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, vl_dim1, vl_offset, vr_dim1, vr_offset, i__1,
i__2, i__3;
doublereal d__1, d__2;
/* Local variables */
static integer i__, k;
static doublereal r__, cs, sn;
static integer ihi;
static doublereal scl;
static integer ilo;
static doublereal dum[1], eps;
static integer ibal;
static char side[1];
static doublereal anrm;
static integer ierr, itau;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *);
static integer iwrk, nout;
extern doublereal dnrm2_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
extern logical lsame_(char *, char *);
extern doublereal dlapy2_(doublereal *, doublereal *);
extern /* Subroutine */ int dlabad_(doublereal *, doublereal *), dgebak_(
char *, char *, integer *, integer *, integer *, doublereal *,
integer *, doublereal *, integer *, integer *),
dgebal_(char *, integer *, doublereal *, integer *, integer *,
integer *, doublereal *, integer *);
static logical scalea;
static doublereal cscale;
extern doublereal dlange_(char *, integer *, integer *, doublereal *,
integer *, doublereal *);
extern /* Subroutine */ int dgehrd_(integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
integer *), dlascl_(char *, integer *, integer *, doublereal *,
doublereal *, integer *, integer *, doublereal *, integer *,
integer *);
extern integer idamax_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dlacpy_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *),
dlartg_(doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *), xerbla_(char *, integer *);
static logical select[1];
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static doublereal bignum;
extern /* Subroutine */ int dorghr_(integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
integer *), dhseqr_(char *, char *, integer *, integer *, integer
*, doublereal *, integer *, doublereal *, doublereal *,
doublereal *, integer *, doublereal *, integer *, integer *), dtrevc_(char *, char *, logical *, integer *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *, integer *, integer *, doublereal *, integer *);
static integer minwrk, maxwrk;
static logical wantvl;
static doublereal smlnum;
static integer hswork;
static logical lquery, wantvr;
/*
-- LAPACK driver routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGEEV computes for an N-by-N real nonsymmetric matrix A, the
eigenvalues and, optionally, the left and/or right eigenvectors.
The right eigenvector v(j) of A satisfies
A * v(j) = lambda(j) * v(j)
where lambda(j) is its eigenvalue.
The left eigenvector u(j) of A satisfies
u(j)**H * A = lambda(j) * u(j)**H
where u(j)**H denotes the conjugate transpose of u(j).
The computed eigenvectors are normalized to have Euclidean norm
equal to 1 and largest component real.
Arguments
=========
JOBVL (input) CHARACTER*1
= 'N': left eigenvectors of A are not computed;
= 'V': left eigenvectors of A are computed.
JOBVR (input) CHARACTER*1
= 'N': right eigenvectors of A are not computed;
= 'V': right eigenvectors of A are computed.
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the N-by-N matrix A.
On exit, A has been overwritten.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
WR (output) DOUBLE PRECISION array, dimension (N)
WI (output) DOUBLE PRECISION array, dimension (N)
WR and WI contain the real and imaginary parts,
respectively, of the computed eigenvalues. Complex
conjugate pairs of eigenvalues appear consecutively
with the eigenvalue having the positive imaginary part
first.
VL (output) DOUBLE PRECISION array, dimension (LDVL,N)
If JOBVL = 'V', the left eigenvectors u(j) are stored one
after another in the columns of VL, in the same order
as their eigenvalues.
If JOBVL = 'N', VL is not referenced.
If the j-th eigenvalue is real, then u(j) = VL(:,j),
the j-th column of VL.
If the j-th and (j+1)-st eigenvalues form a complex
conjugate pair, then u(j) = VL(:,j) + i*VL(:,j+1) and
u(j+1) = VL(:,j) - i*VL(:,j+1).
LDVL (input) INTEGER
The leading dimension of the array VL. LDVL >= 1; if
JOBVL = 'V', LDVL >= N.
VR (output) DOUBLE PRECISION array, dimension (LDVR,N)
If JOBVR = 'V', the right eigenvectors v(j) are stored one
after another in the columns of VR, in the same order
as their eigenvalues.
If JOBVR = 'N', VR is not referenced.
If the j-th eigenvalue is real, then v(j) = VR(:,j),
the j-th column of VR.
If the j-th and (j+1)-st eigenvalues form a complex
conjugate pair, then v(j) = VR(:,j) + i*VR(:,j+1) and
v(j+1) = VR(:,j) - i*VR(:,j+1).
LDVR (input) INTEGER
The leading dimension of the array VR. LDVR >= 1; if
JOBVR = 'V', LDVR >= N.
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= max(1,3*N), and
if JOBVL = 'V' or JOBVR = 'V', LWORK >= 4*N. For good
performance, LWORK must generally be larger.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = i, the QR algorithm failed to compute all the
eigenvalues, and no eigenvectors have been computed;
elements i+1:N of WR and WI contain eigenvalues which
have converged.
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--wr;
--wi;
vl_dim1 = *ldvl;
vl_offset = 1 + vl_dim1;
vl -= vl_offset;
vr_dim1 = *ldvr;
vr_offset = 1 + vr_dim1;
vr -= vr_offset;
--work;
/* Function Body */
*info = 0;
lquery = *lwork == -1;
wantvl = lsame_(jobvl, "V");
wantvr = lsame_(jobvr, "V");
if (! wantvl && ! lsame_(jobvl, "N")) {
*info = -1;
} else if (! wantvr && ! lsame_(jobvr, "N")) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
} else if (*ldvl < 1 || wantvl && *ldvl < *n) {
*info = -9;
} else if (*ldvr < 1 || wantvr && *ldvr < *n) {
*info = -11;
}
/*
Compute workspace
(Note: Comments in the code beginning "Workspace:" describe the
minimal amount of workspace needed at that point in the code,
as well as the preferred amount for good performance.
NB refers to the optimal block size for the immediately
following subroutine, as returned by ILAENV.
HSWORK refers to the workspace preferred by DHSEQR, as
calculated below. HSWORK is computed assuming ILO=1 and IHI=N,
the worst case.)
*/
if (*info == 0) {
if (*n == 0) {
minwrk = 1;
maxwrk = 1;
} else {
maxwrk = (*n << 1) + *n * ilaenv_(&c__1, "DGEHRD", " ", n, &c__1,
n, &c__0, (ftnlen)6, (ftnlen)1);
if (wantvl) {
minwrk = *n << 2;
/* Computing MAX */
i__1 = maxwrk, i__2 = (*n << 1) + (*n - 1) * ilaenv_(&c__1,
"DORGHR", " ", n, &c__1, n, &c_n1, (ftnlen)6, (ftnlen)
1);
maxwrk = max(i__1,i__2);
dhseqr_("S", "V", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[
1], &vl[vl_offset], ldvl, &work[1], &c_n1, info);
hswork = (integer) work[1];
/* Computing MAX */
i__1 = maxwrk, i__2 = *n + 1, i__1 = max(i__1,i__2), i__2 = *
n + hswork;
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n << 2;
maxwrk = max(i__1,i__2);
} else if (wantvr) {
minwrk = *n << 2;
/* Computing MAX */
i__1 = maxwrk, i__2 = (*n << 1) + (*n - 1) * ilaenv_(&c__1,
"DORGHR", " ", n, &c__1, n, &c_n1, (ftnlen)6, (ftnlen)
1);
maxwrk = max(i__1,i__2);
dhseqr_("S", "V", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[
1], &vr[vr_offset], ldvr, &work[1], &c_n1, info);
hswork = (integer) work[1];
/* Computing MAX */
i__1 = maxwrk, i__2 = *n + 1, i__1 = max(i__1,i__2), i__2 = *
n + hswork;
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n << 2;
maxwrk = max(i__1,i__2);
} else {
minwrk = *n * 3;
dhseqr_("E", "N", n, &c__1, n, &a[a_offset], lda, &wr[1], &wi[
1], &vr[vr_offset], ldvr, &work[1], &c_n1, info);
hswork = (integer) work[1];
/* Computing MAX */
i__1 = maxwrk, i__2 = *n + 1, i__1 = max(i__1,i__2), i__2 = *
n + hswork;
maxwrk = max(i__1,i__2);
}
maxwrk = max(maxwrk,minwrk);
}
work[1] = (doublereal) maxwrk;
if (*lwork < minwrk && ! lquery) {
*info = -13;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGEEV ", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/* Get machine constants */
eps = PRECISION;
smlnum = SAFEMINIMUM;
bignum = 1. / smlnum;
dlabad_(&smlnum, &bignum);
smlnum = sqrt(smlnum) / eps;
bignum = 1. / smlnum;
/* Scale A if max element outside range [SMLNUM,BIGNUM] */
anrm = dlange_("M", n, n, &a[a_offset], lda, dum);
scalea = FALSE_;
if (anrm > 0. && anrm < smlnum) {
scalea = TRUE_;
cscale = smlnum;
} else if (anrm > bignum) {
scalea = TRUE_;
cscale = bignum;
}
if (scalea) {
dlascl_("G", &c__0, &c__0, &anrm, &cscale, n, n, &a[a_offset], lda, &
ierr);
}
/*
Balance the matrix
(Workspace: need N)
*/
ibal = 1;
dgebal_("B", n, &a[a_offset], lda, &ilo, &ihi, &work[ibal], &ierr);
/*
Reduce to upper Hessenberg form
(Workspace: need 3*N, prefer 2*N+N*NB)
*/
itau = ibal + *n;
iwrk = itau + *n;
i__1 = *lwork - iwrk + 1;
dgehrd_(n, &ilo, &ihi, &a[a_offset], lda, &work[itau], &work[iwrk], &i__1,
&ierr);
if (wantvl) {
/*
Want left eigenvectors
Copy Householder vectors to VL
*/
*(unsigned char *)side = 'L';
dlacpy_("L", n, n, &a[a_offset], lda, &vl[vl_offset], ldvl)
;
/*
Generate orthogonal matrix in VL
(Workspace: need 3*N-1, prefer 2*N+(N-1)*NB)
*/
i__1 = *lwork - iwrk + 1;
dorghr_(n, &ilo, &ihi, &vl[vl_offset], ldvl, &work[itau], &work[iwrk],
&i__1, &ierr);
/*
Perform QR iteration, accumulating Schur vectors in VL
(Workspace: need N+1, prefer N+HSWORK (see comments) )
*/
iwrk = itau;
i__1 = *lwork - iwrk + 1;
dhseqr_("S", "V", n, &ilo, &ihi, &a[a_offset], lda, &wr[1], &wi[1], &
vl[vl_offset], ldvl, &work[iwrk], &i__1, info);
if (wantvr) {
/*
Want left and right eigenvectors
Copy Schur vectors to VR
*/
*(unsigned char *)side = 'B';
dlacpy_("F", n, n, &vl[vl_offset], ldvl, &vr[vr_offset], ldvr);
}
} else if (wantvr) {
/*
Want right eigenvectors
Copy Householder vectors to VR
*/
*(unsigned char *)side = 'R';
dlacpy_("L", n, n, &a[a_offset], lda, &vr[vr_offset], ldvr)
;
/*
Generate orthogonal matrix in VR
(Workspace: need 3*N-1, prefer 2*N+(N-1)*NB)
*/
i__1 = *lwork - iwrk + 1;
dorghr_(n, &ilo, &ihi, &vr[vr_offset], ldvr, &work[itau], &work[iwrk],
&i__1, &ierr);
/*
Perform QR iteration, accumulating Schur vectors in VR
(Workspace: need N+1, prefer N+HSWORK (see comments) )
*/
iwrk = itau;
i__1 = *lwork - iwrk + 1;
dhseqr_("S", "V", n, &ilo, &ihi, &a[a_offset], lda, &wr[1], &wi[1], &
vr[vr_offset], ldvr, &work[iwrk], &i__1, info);
} else {
/*
Compute eigenvalues only
(Workspace: need N+1, prefer N+HSWORK (see comments) )
*/
iwrk = itau;
i__1 = *lwork - iwrk + 1;
dhseqr_("E", "N", n, &ilo, &ihi, &a[a_offset], lda, &wr[1], &wi[1], &
vr[vr_offset], ldvr, &work[iwrk], &i__1, info);
}
/* If INFO > 0 from DHSEQR, then quit */
if (*info > 0) {
goto L50;
}
if (wantvl || wantvr) {
/*
Compute left and/or right eigenvectors
(Workspace: need 4*N)
*/
dtrevc_(side, "B", select, n, &a[a_offset], lda, &vl[vl_offset], ldvl,
&vr[vr_offset], ldvr, n, &nout, &work[iwrk], &ierr);
}
if (wantvl) {
/*
Undo balancing of left eigenvectors
(Workspace: need N)
*/
dgebak_("B", "L", n, &ilo, &ihi, &work[ibal], n, &vl[vl_offset], ldvl,
&ierr);
/* Normalize left eigenvectors and make largest component real */
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if (wi[i__] == 0.) {
scl = 1. / dnrm2_(n, &vl[i__ * vl_dim1 + 1], &c__1);
dscal_(n, &scl, &vl[i__ * vl_dim1 + 1], &c__1);
} else if (wi[i__] > 0.) {
d__1 = dnrm2_(n, &vl[i__ * vl_dim1 + 1], &c__1);
d__2 = dnrm2_(n, &vl[(i__ + 1) * vl_dim1 + 1], &c__1);
scl = 1. / dlapy2_(&d__1, &d__2);
dscal_(n, &scl, &vl[i__ * vl_dim1 + 1], &c__1);
dscal_(n, &scl, &vl[(i__ + 1) * vl_dim1 + 1], &c__1);
i__2 = *n;
for (k = 1; k <= i__2; ++k) {
/* Computing 2nd power */
d__1 = vl[k + i__ * vl_dim1];
/* Computing 2nd power */
d__2 = vl[k + (i__ + 1) * vl_dim1];
work[iwrk + k - 1] = d__1 * d__1 + d__2 * d__2;
/* L10: */
}
k = idamax_(n, &work[iwrk], &c__1);
dlartg_(&vl[k + i__ * vl_dim1], &vl[k + (i__ + 1) * vl_dim1],
&cs, &sn, &r__);
drot_(n, &vl[i__ * vl_dim1 + 1], &c__1, &vl[(i__ + 1) *
vl_dim1 + 1], &c__1, &cs, &sn);
vl[k + (i__ + 1) * vl_dim1] = 0.;
}
/* L20: */
}
}
if (wantvr) {
/*
Undo balancing of right eigenvectors
(Workspace: need N)
*/
dgebak_("B", "R", n, &ilo, &ihi, &work[ibal], n, &vr[vr_offset], ldvr,
&ierr);
/* Normalize right eigenvectors and make largest component real */
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if (wi[i__] == 0.) {
scl = 1. / dnrm2_(n, &vr[i__ * vr_dim1 + 1], &c__1);
dscal_(n, &scl, &vr[i__ * vr_dim1 + 1], &c__1);
} else if (wi[i__] > 0.) {
d__1 = dnrm2_(n, &vr[i__ * vr_dim1 + 1], &c__1);
d__2 = dnrm2_(n, &vr[(i__ + 1) * vr_dim1 + 1], &c__1);
scl = 1. / dlapy2_(&d__1, &d__2);
dscal_(n, &scl, &vr[i__ * vr_dim1 + 1], &c__1);
dscal_(n, &scl, &vr[(i__ + 1) * vr_dim1 + 1], &c__1);
i__2 = *n;
for (k = 1; k <= i__2; ++k) {
/* Computing 2nd power */
d__1 = vr[k + i__ * vr_dim1];
/* Computing 2nd power */
d__2 = vr[k + (i__ + 1) * vr_dim1];
work[iwrk + k - 1] = d__1 * d__1 + d__2 * d__2;
/* L30: */
}
k = idamax_(n, &work[iwrk], &c__1);
dlartg_(&vr[k + i__ * vr_dim1], &vr[k + (i__ + 1) * vr_dim1],
&cs, &sn, &r__);
drot_(n, &vr[i__ * vr_dim1 + 1], &c__1, &vr[(i__ + 1) *
vr_dim1 + 1], &c__1, &cs, &sn);
vr[k + (i__ + 1) * vr_dim1] = 0.;
}
/* L40: */
}
}
/* Undo scaling if necessary */
L50:
if (scalea) {
i__1 = *n - *info;
/* Computing MAX */
i__3 = *n - *info;
i__2 = max(i__3,1);
dlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wr[*info +
1], &i__2, &ierr);
i__1 = *n - *info;
/* Computing MAX */
i__3 = *n - *info;
i__2 = max(i__3,1);
dlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wi[*info +
1], &i__2, &ierr);
if (*info > 0) {
i__1 = ilo - 1;
dlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wr[1],
n, &ierr);
i__1 = ilo - 1;
dlascl_("G", &c__0, &c__0, &cscale, &anrm, &i__1, &c__1, &wi[1],
n, &ierr);
}
}
work[1] = (doublereal) maxwrk;
return 0;
/* End of DGEEV */
} /* dgeev_ */
/* Subroutine */ int dgehd2_(integer *n, integer *ilo, integer *ihi,
doublereal *a, integer *lda, doublereal *tau, doublereal *work,
integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__;
static doublereal aii;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *), dlarfg_(integer *, doublereal *,
doublereal *, integer *, doublereal *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGEHD2 reduces a real general matrix A to upper Hessenberg form H by
an orthogonal similarity transformation: Q' * A * Q = H .
Arguments
=========
N (input) INTEGER
The order of the matrix A. N >= 0.
ILO (input) INTEGER
IHI (input) INTEGER
It is assumed that A is already upper triangular in rows
and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally
set by a previous call to DGEBAL; otherwise they should be
set to 1 and N respectively. See Further Details.
1 <= ILO <= IHI <= max(1,N).
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the n by n general matrix to be reduced.
On exit, the upper triangle and the first subdiagonal of A
are overwritten with the upper Hessenberg matrix H, and the
elements below the first subdiagonal, with the array TAU,
represent the orthogonal matrix Q as a product of elementary
reflectors. See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
TAU (output) DOUBLE PRECISION array, dimension (N-1)
The scalar factors of the elementary reflectors (see Further
Details).
WORK (workspace) DOUBLE PRECISION array, dimension (N)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
The matrix Q is represented as a product of (ihi-ilo) elementary
reflectors
Q = H(ilo) H(ilo+1) . . . H(ihi-1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i) = 0, v(i+1) = 1 and v(ihi+1:n) = 0; v(i+2:ihi) is stored on
exit in A(i+2:ihi,i), and tau in TAU(i).
The contents of A are illustrated by the following example, with
n = 7, ilo = 2 and ihi = 6:
on entry, on exit,
( a a a a a a a ) ( a a h h h h a )
( a a a a a a ) ( a h h h h a )
( a a a a a a ) ( h h h h h h )
( a a a a a a ) ( v2 h h h h h )
( a a a a a a ) ( v2 v3 h h h h )
( a a a a a a ) ( v2 v3 v4 h h h )
( a ) ( a )
where a denotes an element of the original matrix A, h denotes a
modified element of the upper Hessenberg matrix H, and vi denotes an
element of the vector defining H(i).
=====================================================================
Test the input parameters
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -1;
} else if (*ilo < 1 || *ilo > max(1,*n)) {
*info = -2;
} else if (*ihi < min(*ilo,*n) || *ihi > *n) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGEHD2", &i__1);
return 0;
}
i__1 = *ihi - 1;
for (i__ = *ilo; i__ <= i__1; ++i__) {
/* Compute elementary reflector H(i) to annihilate A(i+2:ihi,i) */
i__2 = *ihi - i__;
/* Computing MIN */
i__3 = i__ + 2;
dlarfg_(&i__2, &a[i__ + 1 + i__ * a_dim1], &a[min(i__3,*n) + i__ *
a_dim1], &c__1, &tau[i__]);
aii = a[i__ + 1 + i__ * a_dim1];
a[i__ + 1 + i__ * a_dim1] = 1.;
/* Apply H(i) to A(1:ihi,i+1:ihi) from the right */
i__2 = *ihi - i__;
dlarf_("Right", ihi, &i__2, &a[i__ + 1 + i__ * a_dim1], &c__1, &tau[
i__], &a[(i__ + 1) * a_dim1 + 1], lda, &work[1]);
/* Apply H(i) to A(i+1:ihi,i+1:n) from the left */
i__2 = *ihi - i__;
i__3 = *n - i__;
dlarf_("Left", &i__2, &i__3, &a[i__ + 1 + i__ * a_dim1], &c__1, &tau[
i__], &a[i__ + 1 + (i__ + 1) * a_dim1], lda, &work[1]);
a[i__ + 1 + i__ * a_dim1] = aii;
/* L10: */
}
return 0;
/* End of DGEHD2 */
} /* dgehd2_ */
/* Subroutine */ int dgehrd_(integer *n, integer *ilo, integer *ihi,
doublereal *a, integer *lda, doublereal *tau, doublereal *work,
integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer i__, j;
static doublereal t[4160] /* was [65][64] */;
static integer ib;
static doublereal ei;
static integer nb, nh, nx, iws;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static integer nbmin, iinfo;
extern /* Subroutine */ int dtrmm_(char *, char *, char *, char *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *), daxpy_(
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *), dgehd2_(integer *, integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *), dlahr2_(
integer *, integer *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *),
dlarfb_(char *, char *, char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, integer *), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static integer ldwork, lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2.1) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
-- April 2009 --
Purpose
=======
DGEHRD reduces a real general matrix A to upper Hessenberg form H by
an orthogonal similarity transformation: Q' * A * Q = H .
Arguments
=========
N (input) INTEGER
The order of the matrix A. N >= 0.
ILO (input) INTEGER
IHI (input) INTEGER
It is assumed that A is already upper triangular in rows
and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally
set by a previous call to DGEBAL; otherwise they should be
set to 1 and N respectively. See Further Details.
1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the N-by-N general matrix to be reduced.
On exit, the upper triangle and the first subdiagonal of A
are overwritten with the upper Hessenberg matrix H, and the
elements below the first subdiagonal, with the array TAU,
represent the orthogonal matrix Q as a product of elementary
reflectors. See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
TAU (output) DOUBLE PRECISION array, dimension (N-1)
The scalar factors of the elementary reflectors (see Further
Details). Elements 1:ILO-1 and IHI:N-1 of TAU are set to
zero.
WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK)
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The length of the array WORK. LWORK >= max(1,N).
For optimum performance LWORK >= N*NB, where NB is the
optimal blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
The matrix Q is represented as a product of (ihi-ilo) elementary
reflectors
Q = H(ilo) H(ilo+1) . . . H(ihi-1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i) = 0, v(i+1) = 1 and v(ihi+1:n) = 0; v(i+2:ihi) is stored on
exit in A(i+2:ihi,i), and tau in TAU(i).
The contents of A are illustrated by the following example, with
n = 7, ilo = 2 and ihi = 6:
on entry, on exit,
( a a a a a a a ) ( a a h h h h a )
( a a a a a a ) ( a h h h h a )
( a a a a a a ) ( h h h h h h )
( a a a a a a ) ( v2 h h h h h )
( a a a a a a ) ( v2 v3 h h h h )
( a a a a a a ) ( v2 v3 v4 h h h )
( a ) ( a )
where a denotes an element of the original matrix A, h denotes a
modified element of the upper Hessenberg matrix H, and vi denotes an
element of the vector defining H(i).
This file is a slight modification of LAPACK-3.0's DGEHRD
subroutine incorporating improvements proposed by Quintana-Orti and
Van de Geijn (2006). (See DLAHR2.)
=====================================================================
Test the input parameters
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
/* Computing MIN */
i__1 = 64, i__2 = ilaenv_(&c__1, "DGEHRD", " ", n, ilo, ihi, &c_n1, (
ftnlen)6, (ftnlen)1);
nb = min(i__1,i__2);
lwkopt = *n * nb;
work[1] = (doublereal) lwkopt;
lquery = *lwork == -1;
if (*n < 0) {
*info = -1;
} else if (*ilo < 1 || *ilo > max(1,*n)) {
*info = -2;
} else if (*ihi < min(*ilo,*n) || *ihi > *n) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
} else if (*lwork < max(1,*n) && ! lquery) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGEHRD", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Set elements 1:ILO-1 and IHI:N-1 of TAU to zero */
i__1 = *ilo - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
tau[i__] = 0.;
/* L10: */
}
i__1 = *n - 1;
for (i__ = max(1,*ihi); i__ <= i__1; ++i__) {
tau[i__] = 0.;
/* L20: */
}
/* Quick return if possible */
nh = *ihi - *ilo + 1;
if (nh <= 1) {
work[1] = 1.;
return 0;
}
/*
Determine the block size
Computing MIN
*/
i__1 = 64, i__2 = ilaenv_(&c__1, "DGEHRD", " ", n, ilo, ihi, &c_n1, (
ftnlen)6, (ftnlen)1);
nb = min(i__1,i__2);
nbmin = 2;
iws = 1;
if (nb > 1 && nb < nh) {
/*
Determine when to cross over from blocked to unblocked code
(last block is always handled by unblocked code)
Computing MAX
*/
i__1 = nb, i__2 = ilaenv_(&c__3, "DGEHRD", " ", n, ilo, ihi, &c_n1, (
ftnlen)6, (ftnlen)1);
nx = max(i__1,i__2);
if (nx < nh) {
/* Determine if workspace is large enough for blocked code */
iws = *n * nb;
if (*lwork < iws) {
/*
Not enough workspace to use optimal NB: determine the
minimum value of NB, and reduce NB or force use of
unblocked code
Computing MAX
*/
i__1 = 2, i__2 = ilaenv_(&c__2, "DGEHRD", " ", n, ilo, ihi, &
c_n1, (ftnlen)6, (ftnlen)1);
nbmin = max(i__1,i__2);
if (*lwork >= *n * nbmin) {
nb = *lwork / *n;
} else {
nb = 1;
}
}
}
}
ldwork = *n;
if (nb < nbmin || nb >= nh) {
/* Use unblocked code below */
i__ = *ilo;
} else {
/* Use blocked code */
i__1 = *ihi - 1 - nx;
i__2 = nb;
for (i__ = *ilo; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/* Computing MIN */
i__3 = nb, i__4 = *ihi - i__;
ib = min(i__3,i__4);
/*
Reduce columns i:i+ib-1 to Hessenberg form, returning the
matrices V and T of the block reflector H = I - V*T*V'
which performs the reduction, and also the matrix Y = A*V*T
*/
dlahr2_(ihi, &i__, &ib, &a[i__ * a_dim1 + 1], lda, &tau[i__], t, &
c__65, &work[1], &ldwork);
/*
Apply the block reflector H to A(1:ihi,i+ib:ihi) from the
right, computing A := A - Y * V'. V(i+ib,ib-1) must be set
to 1
*/
ei = a[i__ + ib + (i__ + ib - 1) * a_dim1];
a[i__ + ib + (i__ + ib - 1) * a_dim1] = 1.;
i__3 = *ihi - i__ - ib + 1;
dgemm_("No transpose", "Transpose", ihi, &i__3, &ib, &c_b151, &
work[1], &ldwork, &a[i__ + ib + i__ * a_dim1], lda, &
c_b15, &a[(i__ + ib) * a_dim1 + 1], lda);
a[i__ + ib + (i__ + ib - 1) * a_dim1] = ei;
/*
Apply the block reflector H to A(1:i,i+1:i+ib-1) from the
right
*/
i__3 = ib - 1;
dtrmm_("Right", "Lower", "Transpose", "Unit", &i__, &i__3, &c_b15,
&a[i__ + 1 + i__ * a_dim1], lda, &work[1], &ldwork);
i__3 = ib - 2;
for (j = 0; j <= i__3; ++j) {
daxpy_(&i__, &c_b151, &work[ldwork * j + 1], &c__1, &a[(i__ +
j + 1) * a_dim1 + 1], &c__1);
/* L30: */
}
/*
Apply the block reflector H to A(i+1:ihi,i+ib:n) from the
left
*/
i__3 = *ihi - i__;
i__4 = *n - i__ - ib + 1;
dlarfb_("Left", "Transpose", "Forward", "Columnwise", &i__3, &
i__4, &ib, &a[i__ + 1 + i__ * a_dim1], lda, t, &c__65, &a[
i__ + 1 + (i__ + ib) * a_dim1], lda, &work[1], &ldwork);
/* L40: */
}
}
/* Use unblocked code to reduce the rest of the matrix */
dgehd2_(n, &i__, ihi, &a[a_offset], lda, &tau[1], &work[1], &iinfo);
work[1] = (doublereal) iws;
return 0;
/* End of DGEHRD */
} /* dgehrd_ */
/* Subroutine */ int dgelq2_(integer *m, integer *n, doublereal *a, integer *
lda, doublereal *tau, doublereal *work, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__, k;
static doublereal aii;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *), dlarfg_(integer *, doublereal *,
doublereal *, integer *, doublereal *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DGELQ2 computes an LQ factorization of a real m by n matrix A:
A = L * Q.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the m by n matrix A.
On exit, the elements on and below the diagonal of the array
contain the m by min(m,n) lower trapezoidal matrix L (L is
lower triangular if m <= n); the elements above the diagonal,
with the array TAU, represent the orthogonal matrix Q as a
product of elementary reflectors (see Further Details).
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
TAU (output) DOUBLE PRECISION array, dimension (min(M,N))
The scalar factors of the elementary reflectors (see Further
Details).
WORK (workspace) DOUBLE PRECISION array, dimension (M)
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
Further Details
===============
The matrix Q is represented as a product of elementary reflectors
Q = H(k) . . . H(2) H(1), where k = min(m,n).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i-1) = 0 and v(i) = 1; v(i+1:n) is stored on exit in A(i,i+1:n),
and tau in TAU(i).
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*m)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGELQ2", &i__1);
return 0;
}
k = min(*m,*n);
i__1 = k;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Generate elementary reflector H(i) to annihilate A(i,i+1:n) */
i__2 = *n - i__ + 1;
/* Computing MIN */
i__3 = i__ + 1;
dlarfg_(&i__2, &a[i__ + i__ * a_dim1], &a[i__ + min(i__3,*n) * a_dim1]
, lda, &tau[i__]);
if (i__ < *m) {
/* Apply H(i) to A(i+1:m,i:n) from the right */
aii = a[i__ + i__ * a_dim1];
a[i__ + i__ * a_dim1] = 1.;
i__2 = *m - i__;
i__3 = *n - i__ + 1;
dlarf_("Right", &i__2, &i__3, &a[i__ + i__ * a_dim1], lda, &tau[
i__], &a[i__ + 1 + i__ * a_dim1], lda, &work[1]);
a[i__ + i__ * a_dim1] = aii;
}
/* L10: */
}
return 0;
/* End of DGELQ2 */
} /* dgelq2_ */
/* Subroutine */ int dgelqf_(integer *m, integer *n, doublereal *a, integer *
lda, doublereal *tau, doublereal *work, integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer i__, k, ib, nb, nx, iws, nbmin, iinfo;
extern /* Subroutine */ int dgelq2_(integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *), dlarfb_(char *,
char *, char *, char *, integer *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *, doublereal *, integer *), dlarft_(char *, char *, integer *, integer *, doublereal
*, integer *, doublereal *, doublereal *, integer *), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static integer ldwork, lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGELQF computes an LQ factorization of a real M-by-N matrix A:
A = L * Q.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the M-by-N matrix A.
On exit, the elements on and below the diagonal of the array
contain the m-by-min(m,n) lower trapezoidal matrix L (L is
lower triangular if m <= n); the elements above the diagonal,
with the array TAU, represent the orthogonal matrix Q as a
product of elementary reflectors (see Further Details).
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
TAU (output) DOUBLE PRECISION array, dimension (min(M,N))
The scalar factors of the elementary reflectors (see Further
Details).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= max(1,M).
For optimum performance LWORK >= M*NB, where NB is the
optimal blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
Further Details
===============
The matrix Q is represented as a product of elementary reflectors
Q = H(k) . . . H(2) H(1), where k = min(m,n).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i-1) = 0 and v(i) = 1; v(i+1:n) is stored on exit in A(i,i+1:n),
and tau in TAU(i).
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
nb = ilaenv_(&c__1, "DGELQF", " ", m, n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)
1);
lwkopt = *m * nb;
work[1] = (doublereal) lwkopt;
lquery = *lwork == -1;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*m)) {
*info = -4;
} else if (*lwork < max(1,*m) && ! lquery) {
*info = -7;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGELQF", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
k = min(*m,*n);
if (k == 0) {
work[1] = 1.;
return 0;
}
nbmin = 2;
nx = 0;
iws = *m;
if (nb > 1 && nb < k) {
/*
Determine when to cross over from blocked to unblocked code.
Computing MAX
*/
i__1 = 0, i__2 = ilaenv_(&c__3, "DGELQF", " ", m, n, &c_n1, &c_n1, (
ftnlen)6, (ftnlen)1);
nx = max(i__1,i__2);
if (nx < k) {
/* Determine if workspace is large enough for blocked code. */
ldwork = *m;
iws = ldwork * nb;
if (*lwork < iws) {
/*
Not enough workspace to use optimal NB: reduce NB and
determine the minimum value of NB.
*/
nb = *lwork / ldwork;
/* Computing MAX */
i__1 = 2, i__2 = ilaenv_(&c__2, "DGELQF", " ", m, n, &c_n1, &
c_n1, (ftnlen)6, (ftnlen)1);
nbmin = max(i__1,i__2);
}
}
}
if (nb >= nbmin && nb < k && nx < k) {
/* Use blocked code initially */
i__1 = k - nx;
i__2 = nb;
for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/* Computing MIN */
i__3 = k - i__ + 1;
ib = min(i__3,nb);
/*
Compute the LQ factorization of the current block
A(i:i+ib-1,i:n)
*/
i__3 = *n - i__ + 1;
dgelq2_(&ib, &i__3, &a[i__ + i__ * a_dim1], lda, &tau[i__], &work[
1], &iinfo);
if (i__ + ib <= *m) {
/*
Form the triangular factor of the block reflector
H = H(i) H(i+1) . . . H(i+ib-1)
*/
i__3 = *n - i__ + 1;
dlarft_("Forward", "Rowwise", &i__3, &ib, &a[i__ + i__ *
a_dim1], lda, &tau[i__], &work[1], &ldwork);
/* Apply H to A(i+ib:m,i:n) from the right */
i__3 = *m - i__ - ib + 1;
i__4 = *n - i__ + 1;
dlarfb_("Right", "No transpose", "Forward", "Rowwise", &i__3,
&i__4, &ib, &a[i__ + i__ * a_dim1], lda, &work[1], &
ldwork, &a[i__ + ib + i__ * a_dim1], lda, &work[ib +
1], &ldwork);
}
/* L10: */
}
} else {
i__ = 1;
}
/* Use unblocked code to factor the last or only block. */
if (i__ <= k) {
i__2 = *m - i__ + 1;
i__1 = *n - i__ + 1;
dgelq2_(&i__2, &i__1, &a[i__ + i__ * a_dim1], lda, &tau[i__], &work[1]
, &iinfo);
}
work[1] = (doublereal) iws;
return 0;
/* End of DGELQF */
} /* dgelqf_ */
/* Subroutine */ int dgelsd_(integer *m, integer *n, integer *nrhs,
doublereal *a, integer *lda, doublereal *b, integer *ldb, doublereal *
s, doublereal *rcond, integer *rank, doublereal *work, integer *lwork,
integer *iwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, b_dim1, b_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer ie, il, mm;
static doublereal eps, anrm, bnrm;
static integer itau, nlvl, iascl, ibscl;
static doublereal sfmin;
static integer minmn, maxmn, itaup, itauq, mnthr, nwork;
extern /* Subroutine */ int dlabad_(doublereal *, doublereal *), dgebrd_(
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *, integer *,
integer *);
extern doublereal dlamch_(char *), dlange_(char *, integer *,
integer *, doublereal *, integer *, doublereal *);
extern /* Subroutine */ int dgelqf_(integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *, integer *),
dlalsd_(char *, integer *, integer *, integer *, doublereal *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, integer *, integer *), dlascl_(char *,
integer *, integer *, doublereal *, doublereal *, integer *,
integer *, doublereal *, integer *, integer *), dgeqrf_(
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, integer *), dlacpy_(char *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *), dlaset_(char *, integer *, integer *, doublereal *,
doublereal *, doublereal *, integer *), xerbla_(char *,
integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static doublereal bignum;
extern /* Subroutine */ int dormbr_(char *, char *, char *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, doublereal *, integer *, integer *);
static integer wlalsd;
extern /* Subroutine */ int dormlq_(char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *, integer *);
static integer ldwork;
extern /* Subroutine */ int dormqr_(char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *, integer *);
static integer liwork, minwrk, maxwrk;
static doublereal smlnum;
static logical lquery;
static integer smlsiz;
/*
-- LAPACK driver routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DGELSD computes the minimum-norm solution to a real linear least
squares problem:
minimize 2-norm(| b - A*x |)
using the singular value decomposition (SVD) of A. A is an M-by-N
matrix which may be rank-deficient.
Several right hand side vectors b and solution vectors x can be
handled in a single call; they are stored as the columns of the
M-by-NRHS right hand side matrix B and the N-by-NRHS solution
matrix X.
The problem is solved in three steps:
(1) Reduce the coefficient matrix A to bidiagonal form with
Householder transformations, reducing the original problem
into a "bidiagonal least squares problem" (BLS)
(2) Solve the BLS using a divide and conquer approach.
(3) Apply back all the Householder tranformations to solve
the original least squares problem.
The effective rank of A is determined by treating as zero those
singular values which are less than RCOND times the largest singular
value.
The divide and conquer algorithm makes very mild assumptions about
floating point arithmetic. It will work on machines with a guard
digit in add/subtract, or on those binary machines without guard
digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
Cray-2. It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none.
Arguments
=========
M (input) INTEGER
The number of rows of A. M >= 0.
N (input) INTEGER
The number of columns of A. N >= 0.
NRHS (input) INTEGER
The number of right hand sides, i.e., the number of columns
of the matrices B and X. NRHS >= 0.
A (input) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the M-by-N matrix A.
On exit, A has been destroyed.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS)
On entry, the M-by-NRHS right hand side matrix B.
On exit, B is overwritten by the N-by-NRHS solution
matrix X. If m >= n and RANK = n, the residual
sum-of-squares for the solution in the i-th column is given
by the sum of squares of elements n+1:m in that column.
LDB (input) INTEGER
The leading dimension of the array B. LDB >= max(1,max(M,N)).
S (output) DOUBLE PRECISION array, dimension (min(M,N))
The singular values of A in decreasing order.
The condition number of A in the 2-norm = S(1)/S(min(m,n)).
RCOND (input) DOUBLE PRECISION
RCOND is used to determine the effective rank of A.
Singular values S(i) <= RCOND*S(1) are treated as zero.
If RCOND < 0, machine precision is used instead.
RANK (output) INTEGER
The effective rank of A, i.e., the number of singular values
which are greater than RCOND*S(1).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK must be at least 1.
The exact minimum amount of workspace needed depends on M,
N and NRHS. As long as LWORK is at least
12*N + 2*N*SMLSIZ + 8*N*NLVL + N*NRHS + (SMLSIZ+1)**2,
if M is greater than or equal to N or
12*M + 2*M*SMLSIZ + 8*M*NLVL + M*NRHS + (SMLSIZ+1)**2,
if M is less than N, the code will execute correctly.
SMLSIZ is returned by ILAENV and is equal to the maximum
size of the subproblems at the bottom of the computation
tree (usually about 25), and
NLVL = MAX( 0, INT( LOG_2( MIN( M,N )/(SMLSIZ+1) ) ) + 1 )
For good performance, LWORK should generally be larger.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
IWORK (workspace) INTEGER array, dimension (MAX(1,LIWORK))
LIWORK >= max(1, 3 * MINMN * NLVL + 11 * MINMN),
where MINMN = MIN( M,N ).
On exit, if INFO = 0, IWORK(1) returns the minimum LIWORK.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: the algorithm for computing the SVD failed to converge;
if INFO = i, i off-diagonal elements of an intermediate
bidiagonal form did not converge to zero.
Further Details
===============
Based on contributions by
Ming Gu and Ren-Cang Li, Computer Science Division, University of
California at Berkeley, USA
Osni Marques, LBNL/NERSC, USA
=====================================================================
Test the input arguments.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
--s;
--work;
--iwork;
/* Function Body */
*info = 0;
minmn = min(*m,*n);
maxmn = max(*m,*n);
mnthr = ilaenv_(&c__6, "DGELSD", " ", m, n, nrhs, &c_n1, (ftnlen)6, (
ftnlen)1);
lquery = *lwork == -1;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*nrhs < 0) {
*info = -3;
} else if (*lda < max(1,*m)) {
*info = -5;
} else if (*ldb < max(1,maxmn)) {
*info = -7;
}
smlsiz = ilaenv_(&c__9, "DGELSD", " ", &c__0, &c__0, &c__0, &c__0, (
ftnlen)6, (ftnlen)1);
/*
Compute workspace.
(Note: Comments in the code beginning "Workspace:" describe the
minimal amount of workspace needed at that point in the code,
as well as the preferred amount for good performance.
NB refers to the optimal block size for the immediately
following subroutine, as returned by ILAENV.)
*/
minwrk = 1;
liwork = 1;
minmn = max(1,minmn);
/* Computing MAX */
i__1 = (integer) (log((doublereal) minmn / (doublereal) (smlsiz + 1)) /
log(2.)) + 1;
nlvl = max(i__1,0);
if (*info == 0) {
maxwrk = 0;
liwork = minmn * 3 * nlvl + minmn * 11;
mm = *m;
if (*m >= *n && *m >= mnthr) {
/* Path 1a - overdetermined, with many more rows than columns. */
mm = *n;
/* Computing MAX */
i__1 = maxwrk, i__2 = *n + *n * ilaenv_(&c__1, "DGEQRF", " ", m,
n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n + *nrhs * ilaenv_(&c__1, "DORMQR", "LT",
m, nrhs, n, &c_n1, (ftnlen)6, (ftnlen)2);
maxwrk = max(i__1,i__2);
}
if (*m >= *n) {
/*
Path 1 - overdetermined or exactly determined.
Computing MAX
*/
i__1 = maxwrk, i__2 = *n * 3 + (mm + *n) * ilaenv_(&c__1, "DGEBRD"
, " ", &mm, n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n * 3 + *nrhs * ilaenv_(&c__1, "DORMBR",
"QLT", &mm, nrhs, n, &c_n1, (ftnlen)6, (ftnlen)3);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *n * 3 + (*n - 1) * ilaenv_(&c__1, "DORMBR",
"PLN", n, nrhs, n, &c_n1, (ftnlen)6, (ftnlen)3);
maxwrk = max(i__1,i__2);
/* Computing 2nd power */
i__1 = smlsiz + 1;
wlalsd = *n * 9 + (*n << 1) * smlsiz + (*n << 3) * nlvl + *n * *
nrhs + i__1 * i__1;
/* Computing MAX */
i__1 = maxwrk, i__2 = *n * 3 + wlalsd;
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = *n * 3 + mm, i__2 = *n * 3 + *nrhs, i__1 = max(i__1,i__2),
i__2 = *n * 3 + wlalsd;
minwrk = max(i__1,i__2);
}
if (*n > *m) {
/* Computing 2nd power */
i__1 = smlsiz + 1;
wlalsd = *m * 9 + (*m << 1) * smlsiz + (*m << 3) * nlvl + *m * *
nrhs + i__1 * i__1;
if (*n >= mnthr) {
/*
Path 2a - underdetermined, with many more columns
than rows.
*/
maxwrk = *m + *m * ilaenv_(&c__1, "DGELQF", " ", m, n, &c_n1,
&c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + (*m << 2) + (*m << 1) *
ilaenv_(&c__1, "DGEBRD", " ", m, m, &c_n1, &c_n1, (
ftnlen)6, (ftnlen)1);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + (*m << 2) + *nrhs * ilaenv_(&
c__1, "DORMBR", "QLT", m, nrhs, m, &c_n1, (ftnlen)6, (
ftnlen)3);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + (*m << 2) + (*m - 1) *
ilaenv_(&c__1, "DORMBR", "PLN", m, nrhs, m, &c_n1, (
ftnlen)6, (ftnlen)3);
maxwrk = max(i__1,i__2);
if (*nrhs > 1) {
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + *m + *m * *nrhs;
maxwrk = max(i__1,i__2);
} else {
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + (*m << 1);
maxwrk = max(i__1,i__2);
}
/* Computing MAX */
i__1 = maxwrk, i__2 = *m + *nrhs * ilaenv_(&c__1, "DORMLQ",
"LT", n, nrhs, m, &c_n1, (ftnlen)6, (ftnlen)2);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * *m + (*m << 2) + wlalsd;
maxwrk = max(i__1,i__2);
/*
XXX: Ensure the Path 2a case below is triggered. The workspace
calculation should use queries for all routines eventually.
Computing MAX
Computing MAX
*/
i__3 = *m, i__4 = (*m << 1) - 4, i__3 = max(i__3,i__4), i__3 =
max(i__3,*nrhs), i__4 = *n - *m * 3;
i__1 = maxwrk, i__2 = (*m << 2) + *m * *m + max(i__3,i__4);
maxwrk = max(i__1,i__2);
} else {
/* Path 2 - remaining underdetermined cases. */
maxwrk = *m * 3 + (*n + *m) * ilaenv_(&c__1, "DGEBRD", " ", m,
n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * 3 + *nrhs * ilaenv_(&c__1, "DORMBR"
, "QLT", m, nrhs, n, &c_n1, (ftnlen)6, (ftnlen)3);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR",
"PLN", n, nrhs, m, &c_n1, (ftnlen)6, (ftnlen)3);
maxwrk = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = *m * 3 + wlalsd;
maxwrk = max(i__1,i__2);
}
/* Computing MAX */
i__1 = *m * 3 + *nrhs, i__2 = *m * 3 + *m, i__1 = max(i__1,i__2),
i__2 = *m * 3 + wlalsd;
minwrk = max(i__1,i__2);
}
minwrk = min(minwrk,maxwrk);
work[1] = (doublereal) maxwrk;
iwork[1] = liwork;
if (*lwork < minwrk && ! lquery) {
*info = -12;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGELSD", &i__1);
return 0;
} else if (lquery) {
goto L10;
}
/* Quick return if possible. */
if (*m == 0 || *n == 0) {
*rank = 0;
return 0;
}
/* Get machine parameters. */
eps = PRECISION;
sfmin = SAFEMINIMUM;
smlnum = sfmin / eps;
bignum = 1. / smlnum;
dlabad_(&smlnum, &bignum);
/* Scale A if max entry outside range [SMLNUM,BIGNUM]. */
anrm = dlange_("M", m, n, &a[a_offset], lda, &work[1]);
iascl = 0;
if (anrm > 0. && anrm < smlnum) {
/* Scale matrix norm up to SMLNUM. */
dlascl_("G", &c__0, &c__0, &anrm, &smlnum, m, n, &a[a_offset], lda,
info);
iascl = 1;
} else if (anrm > bignum) {
/* Scale matrix norm down to BIGNUM. */
dlascl_("G", &c__0, &c__0, &anrm, &bignum, m, n, &a[a_offset], lda,
info);
iascl = 2;
} else if (anrm == 0.) {
/* Matrix all zero. Return zero solution. */
i__1 = max(*m,*n);
dlaset_("F", &i__1, nrhs, &c_b29, &c_b29, &b[b_offset], ldb);
dlaset_("F", &minmn, &c__1, &c_b29, &c_b29, &s[1], &c__1);
*rank = 0;
goto L10;
}
/* Scale B if max entry outside range [SMLNUM,BIGNUM]. */
bnrm = dlange_("M", m, nrhs, &b[b_offset], ldb, &work[1]);
ibscl = 0;
if (bnrm > 0. && bnrm < smlnum) {
/* Scale matrix norm up to SMLNUM. */
dlascl_("G", &c__0, &c__0, &bnrm, &smlnum, m, nrhs, &b[b_offset], ldb,
info);
ibscl = 1;
} else if (bnrm > bignum) {
/* Scale matrix norm down to BIGNUM. */
dlascl_("G", &c__0, &c__0, &bnrm, &bignum, m, nrhs, &b[b_offset], ldb,
info);
ibscl = 2;
}
/* If M < N make sure certain entries of B are zero. */
if (*m < *n) {
i__1 = *n - *m;
dlaset_("F", &i__1, nrhs, &c_b29, &c_b29, &b[*m + 1 + b_dim1], ldb);
}
/* Overdetermined case. */
if (*m >= *n) {
/* Path 1 - overdetermined or exactly determined. */
mm = *m;
if (*m >= mnthr) {
/* Path 1a - overdetermined, with many more rows than columns. */
mm = *n;
itau = 1;
nwork = itau + *n;
/*
Compute A=Q*R.
(Workspace: need 2*N, prefer N+N*NB)
*/
i__1 = *lwork - nwork + 1;
dgeqrf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &i__1,
info);
/*
Multiply B by transpose(Q).
(Workspace: need N+NRHS, prefer N+NRHS*NB)
*/
i__1 = *lwork - nwork + 1;
dormqr_("L", "T", m, nrhs, n, &a[a_offset], lda, &work[itau], &b[
b_offset], ldb, &work[nwork], &i__1, info);
/* Zero out below R. */
if (*n > 1) {
i__1 = *n - 1;
i__2 = *n - 1;
dlaset_("L", &i__1, &i__2, &c_b29, &c_b29, &a[a_dim1 + 2],
lda);
}
}
ie = 1;
itauq = ie + *n;
itaup = itauq + *n;
nwork = itaup + *n;
/*
Bidiagonalize R in A.
(Workspace: need 3*N+MM, prefer 3*N+(MM+N)*NB)
*/
i__1 = *lwork - nwork + 1;
dgebrd_(&mm, n, &a[a_offset], lda, &s[1], &work[ie], &work[itauq], &
work[itaup], &work[nwork], &i__1, info);
/*
Multiply B by transpose of left bidiagonalizing vectors of R.
(Workspace: need 3*N+NRHS, prefer 3*N+NRHS*NB)
*/
i__1 = *lwork - nwork + 1;
dormbr_("Q", "L", "T", &mm, nrhs, n, &a[a_offset], lda, &work[itauq],
&b[b_offset], ldb, &work[nwork], &i__1, info);
/* Solve the bidiagonal least squares problem. */
dlalsd_("U", &smlsiz, n, nrhs, &s[1], &work[ie], &b[b_offset], ldb,
rcond, rank, &work[nwork], &iwork[1], info);
if (*info != 0) {
goto L10;
}
/* Multiply B by right bidiagonalizing vectors of R. */
i__1 = *lwork - nwork + 1;
dormbr_("P", "L", "N", n, nrhs, n, &a[a_offset], lda, &work[itaup], &
b[b_offset], ldb, &work[nwork], &i__1, info);
} else /* if(complicated condition) */ {
/* Computing MAX */
i__1 = *m, i__2 = (*m << 1) - 4, i__1 = max(i__1,i__2), i__1 = max(
i__1,*nrhs), i__2 = *n - *m * 3, i__1 = max(i__1,i__2);
if (*n >= mnthr && *lwork >= (*m << 2) + *m * *m + max(i__1,wlalsd)) {
/*
Path 2a - underdetermined, with many more columns than rows
and sufficient workspace for an efficient algorithm.
*/
ldwork = *m;
/*
Computing MAX
Computing MAX
*/
i__3 = *m, i__4 = (*m << 1) - 4, i__3 = max(i__3,i__4), i__3 =
max(i__3,*nrhs), i__4 = *n - *m * 3;
i__1 = (*m << 2) + *m * *lda + max(i__3,i__4), i__2 = *m * *lda +
*m + *m * *nrhs, i__1 = max(i__1,i__2), i__2 = (*m << 2)
+ *m * *lda + wlalsd;
if (*lwork >= max(i__1,i__2)) {
ldwork = *lda;
}
itau = 1;
nwork = *m + 1;
/*
Compute A=L*Q.
(Workspace: need 2*M, prefer M+M*NB)
*/
i__1 = *lwork - nwork + 1;
dgelqf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &i__1,
info);
il = nwork;
/* Copy L to WORK(IL), zeroing out above its diagonal. */
dlacpy_("L", m, m, &a[a_offset], lda, &work[il], &ldwork);
i__1 = *m - 1;
i__2 = *m - 1;
dlaset_("U", &i__1, &i__2, &c_b29, &c_b29, &work[il + ldwork], &
ldwork);
ie = il + ldwork * *m;
itauq = ie + *m;
itaup = itauq + *m;
nwork = itaup + *m;
/*
Bidiagonalize L in WORK(IL).
(Workspace: need M*M+5*M, prefer M*M+4*M+2*M*NB)
*/
i__1 = *lwork - nwork + 1;
dgebrd_(m, m, &work[il], &ldwork, &s[1], &work[ie], &work[itauq],
&work[itaup], &work[nwork], &i__1, info);
/*
Multiply B by transpose of left bidiagonalizing vectors of L.
(Workspace: need M*M+4*M+NRHS, prefer M*M+4*M+NRHS*NB)
*/
i__1 = *lwork - nwork + 1;
dormbr_("Q", "L", "T", m, nrhs, m, &work[il], &ldwork, &work[
itauq], &b[b_offset], ldb, &work[nwork], &i__1, info);
/* Solve the bidiagonal least squares problem. */
dlalsd_("U", &smlsiz, m, nrhs, &s[1], &work[ie], &b[b_offset],
ldb, rcond, rank, &work[nwork], &iwork[1], info);
if (*info != 0) {
goto L10;
}
/* Multiply B by right bidiagonalizing vectors of L. */
i__1 = *lwork - nwork + 1;
dormbr_("P", "L", "N", m, nrhs, m, &work[il], &ldwork, &work[
itaup], &b[b_offset], ldb, &work[nwork], &i__1, info);
/* Zero out below first M rows of B. */
i__1 = *n - *m;
dlaset_("F", &i__1, nrhs, &c_b29, &c_b29, &b[*m + 1 + b_dim1],
ldb);
nwork = itau + *m;
/*
Multiply transpose(Q) by B.
(Workspace: need M+NRHS, prefer M+NRHS*NB)
*/
i__1 = *lwork - nwork + 1;
dormlq_("L", "T", n, nrhs, m, &a[a_offset], lda, &work[itau], &b[
b_offset], ldb, &work[nwork], &i__1, info);
} else {
/* Path 2 - remaining underdetermined cases. */
ie = 1;
itauq = ie + *m;
itaup = itauq + *m;
nwork = itaup + *m;
/*
Bidiagonalize A.
(Workspace: need 3*M+N, prefer 3*M+(M+N)*NB)
*/
i__1 = *lwork - nwork + 1;
dgebrd_(m, n, &a[a_offset], lda, &s[1], &work[ie], &work[itauq], &
work[itaup], &work[nwork], &i__1, info);
/*
Multiply B by transpose of left bidiagonalizing vectors.
(Workspace: need 3*M+NRHS, prefer 3*M+NRHS*NB)
*/
i__1 = *lwork - nwork + 1;
dormbr_("Q", "L", "T", m, nrhs, n, &a[a_offset], lda, &work[itauq]
, &b[b_offset], ldb, &work[nwork], &i__1, info);
/* Solve the bidiagonal least squares problem. */
dlalsd_("L", &smlsiz, m, nrhs, &s[1], &work[ie], &b[b_offset],
ldb, rcond, rank, &work[nwork], &iwork[1], info);
if (*info != 0) {
goto L10;
}
/* Multiply B by right bidiagonalizing vectors of A. */
i__1 = *lwork - nwork + 1;
dormbr_("P", "L", "N", n, nrhs, m, &a[a_offset], lda, &work[itaup]
, &b[b_offset], ldb, &work[nwork], &i__1, info);
}
}
/* Undo scaling. */
if (iascl == 1) {
dlascl_("G", &c__0, &c__0, &anrm, &smlnum, n, nrhs, &b[b_offset], ldb,
info);
dlascl_("G", &c__0, &c__0, &smlnum, &anrm, &minmn, &c__1, &s[1], &
minmn, info);
} else if (iascl == 2) {
dlascl_("G", &c__0, &c__0, &anrm, &bignum, n, nrhs, &b[b_offset], ldb,
info);
dlascl_("G", &c__0, &c__0, &bignum, &anrm, &minmn, &c__1, &s[1], &
minmn, info);
}
if (ibscl == 1) {
dlascl_("G", &c__0, &c__0, &smlnum, &bnrm, n, nrhs, &b[b_offset], ldb,
info);
} else if (ibscl == 2) {
dlascl_("G", &c__0, &c__0, &bignum, &bnrm, n, nrhs, &b[b_offset], ldb,
info);
}
L10:
work[1] = (doublereal) maxwrk;
iwork[1] = liwork;
return 0;
/* End of DGELSD */
} /* dgelsd_ */
/* Subroutine */ int dgeqr2_(integer *m, integer *n, doublereal *a, integer *
lda, doublereal *tau, doublereal *work, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__, k;
static doublereal aii;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *), dlarfg_(integer *, doublereal *,
doublereal *, integer *, doublereal *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DGEQR2 computes a QR factorization of a real m by n matrix A:
A = Q * R.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the m by n matrix A.
On exit, the elements on and above the diagonal of the array
contain the min(m,n) by n upper trapezoidal matrix R (R is
upper triangular if m >= n); the elements below the diagonal,
with the array TAU, represent the orthogonal matrix Q as a
product of elementary reflectors (see Further Details).
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
TAU (output) DOUBLE PRECISION array, dimension (min(M,N))
The scalar factors of the elementary reflectors (see Further
Details).
WORK (workspace) DOUBLE PRECISION array, dimension (N)
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
Further Details
===============
The matrix Q is represented as a product of elementary reflectors
Q = H(1) H(2) . . . H(k), where k = min(m,n).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i),
and tau in TAU(i).
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*m)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGEQR2", &i__1);
return 0;
}
k = min(*m,*n);
i__1 = k;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Generate elementary reflector H(i) to annihilate A(i+1:m,i) */
i__2 = *m - i__ + 1;
/* Computing MIN */
i__3 = i__ + 1;
dlarfg_(&i__2, &a[i__ + i__ * a_dim1], &a[min(i__3,*m) + i__ * a_dim1]
, &c__1, &tau[i__]);
if (i__ < *n) {
/* Apply H(i) to A(i:m,i+1:n) from the left */
aii = a[i__ + i__ * a_dim1];
a[i__ + i__ * a_dim1] = 1.;
i__2 = *m - i__ + 1;
i__3 = *n - i__;
dlarf_("Left", &i__2, &i__3, &a[i__ + i__ * a_dim1], &c__1, &tau[
i__], &a[i__ + (i__ + 1) * a_dim1], lda, &work[1]);
a[i__ + i__ * a_dim1] = aii;
}
/* L10: */
}
return 0;
/* End of DGEQR2 */
} /* dgeqr2_ */
/* Subroutine */ int dgeqrf_(integer *m, integer *n, doublereal *a, integer *
lda, doublereal *tau, doublereal *work, integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer i__, k, ib, nb, nx, iws, nbmin, iinfo;
extern /* Subroutine */ int dgeqr2_(integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *), dlarfb_(char *,
char *, char *, char *, integer *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *, doublereal *, integer *), dlarft_(char *, char *, integer *, integer *, doublereal
*, integer *, doublereal *, doublereal *, integer *), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static integer ldwork, lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGEQRF computes a QR factorization of a real M-by-N matrix A:
A = Q * R.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the M-by-N matrix A.
On exit, the elements on and above the diagonal of the array
contain the min(M,N)-by-N upper trapezoidal matrix R (R is
upper triangular if m >= n); the elements below the diagonal,
with the array TAU, represent the orthogonal matrix Q as a
product of min(m,n) elementary reflectors (see Further
Details).
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
TAU (output) DOUBLE PRECISION array, dimension (min(M,N))
The scalar factors of the elementary reflectors (see Further
Details).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= max(1,N).
For optimum performance LWORK >= N*NB, where NB is
the optimal blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
Further Details
===============
The matrix Q is represented as a product of elementary reflectors
Q = H(1) H(2) . . . H(k), where k = min(m,n).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i-1) = 0 and v(i) = 1; v(i+1:m) is stored on exit in A(i+1:m,i),
and tau in TAU(i).
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
nb = ilaenv_(&c__1, "DGEQRF", " ", m, n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)
1);
lwkopt = *n * nb;
work[1] = (doublereal) lwkopt;
lquery = *lwork == -1;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*m)) {
*info = -4;
} else if (*lwork < max(1,*n) && ! lquery) {
*info = -7;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGEQRF", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
k = min(*m,*n);
if (k == 0) {
work[1] = 1.;
return 0;
}
nbmin = 2;
nx = 0;
iws = *n;
if (nb > 1 && nb < k) {
/*
Determine when to cross over from blocked to unblocked code.
Computing MAX
*/
i__1 = 0, i__2 = ilaenv_(&c__3, "DGEQRF", " ", m, n, &c_n1, &c_n1, (
ftnlen)6, (ftnlen)1);
nx = max(i__1,i__2);
if (nx < k) {
/* Determine if workspace is large enough for blocked code. */
ldwork = *n;
iws = ldwork * nb;
if (*lwork < iws) {
/*
Not enough workspace to use optimal NB: reduce NB and
determine the minimum value of NB.
*/
nb = *lwork / ldwork;
/* Computing MAX */
i__1 = 2, i__2 = ilaenv_(&c__2, "DGEQRF", " ", m, n, &c_n1, &
c_n1, (ftnlen)6, (ftnlen)1);
nbmin = max(i__1,i__2);
}
}
}
if (nb >= nbmin && nb < k && nx < k) {
/* Use blocked code initially */
i__1 = k - nx;
i__2 = nb;
for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/* Computing MIN */
i__3 = k - i__ + 1;
ib = min(i__3,nb);
/*
Compute the QR factorization of the current block
A(i:m,i:i+ib-1)
*/
i__3 = *m - i__ + 1;
dgeqr2_(&i__3, &ib, &a[i__ + i__ * a_dim1], lda, &tau[i__], &work[
1], &iinfo);
if (i__ + ib <= *n) {
/*
Form the triangular factor of the block reflector
H = H(i) H(i+1) . . . H(i+ib-1)
*/
i__3 = *m - i__ + 1;
dlarft_("Forward", "Columnwise", &i__3, &ib, &a[i__ + i__ *
a_dim1], lda, &tau[i__], &work[1], &ldwork);
/* Apply H' to A(i:m,i+ib:n) from the left */
i__3 = *m - i__ + 1;
i__4 = *n - i__ - ib + 1;
dlarfb_("Left", "Transpose", "Forward", "Columnwise", &i__3, &
i__4, &ib, &a[i__ + i__ * a_dim1], lda, &work[1], &
ldwork, &a[i__ + (i__ + ib) * a_dim1], lda, &work[ib
+ 1], &ldwork);
}
/* L10: */
}
} else {
i__ = 1;
}
/* Use unblocked code to factor the last or only block. */
if (i__ <= k) {
i__2 = *m - i__ + 1;
i__1 = *n - i__ + 1;
dgeqr2_(&i__2, &i__1, &a[i__ + i__ * a_dim1], lda, &tau[i__], &work[1]
, &iinfo);
}
work[1] = (doublereal) iws;
return 0;
/* End of DGEQRF */
} /* dgeqrf_ */
/* Subroutine */ int dgesdd_(char *jobz, integer *m, integer *n, doublereal *
a, integer *lda, doublereal *s, doublereal *u, integer *ldu,
doublereal *vt, integer *ldvt, doublereal *work, integer *lwork,
integer *iwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, u_dim1, u_offset, vt_dim1, vt_offset, i__1,
i__2, i__3;
/* Local variables */
static integer i__, ie, il, ir, iu, blk;
static doublereal dum[1], eps;
static integer ivt, iscl;
static doublereal anrm;
static integer idum[1], ierr, itau;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
extern logical lsame_(char *, char *);
static integer chunk, minmn, wrkbl, itaup, itauq, mnthr;
static logical wntqa;
static integer nwork;
static logical wntqn, wntqo, wntqs;
extern /* Subroutine */ int dbdsdc_(char *, char *, integer *, doublereal
*, doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, integer *, integer *), dgebrd_(integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *, integer *);
extern doublereal dlamch_(char *), dlange_(char *, integer *,
integer *, doublereal *, integer *, doublereal *);
static integer bdspac;
extern /* Subroutine */ int dgelqf_(integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *, integer *),
dlascl_(char *, integer *, integer *, doublereal *, doublereal *,
integer *, integer *, doublereal *, integer *, integer *),
dgeqrf_(integer *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *, integer *), dlacpy_(char *,
integer *, integer *, doublereal *, integer *, doublereal *,
integer *), dlaset_(char *, integer *, integer *,
doublereal *, doublereal *, doublereal *, integer *),
xerbla_(char *, integer *), dorgbr_(char *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static doublereal bignum;
extern /* Subroutine */ int dormbr_(char *, char *, char *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, doublereal *, integer *, integer *), dorglq_(integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
integer *), dorgqr_(integer *, integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *, integer *);
static integer ldwrkl, ldwrkr, minwrk, ldwrku, maxwrk, ldwkvt;
static doublereal smlnum;
static logical wntqas, lquery;
/*
-- LAPACK driver routine (version 3.2.1) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
March 2009
Purpose
=======
DGESDD computes the singular value decomposition (SVD) of a real
M-by-N matrix A, optionally computing the left and right singular
vectors. If singular vectors are desired, it uses a
divide-and-conquer algorithm.
The SVD is written
A = U * SIGMA * transpose(V)
where SIGMA is an M-by-N matrix which is zero except for its
min(m,n) diagonal elements, U is an M-by-M orthogonal matrix, and
V is an N-by-N orthogonal matrix. The diagonal elements of SIGMA
are the singular values of A; they are real and non-negative, and
are returned in descending order. The first min(m,n) columns of
U and V are the left and right singular vectors of A.
Note that the routine returns VT = V**T, not V.
The divide and conquer algorithm makes very mild assumptions about
floating point arithmetic. It will work on machines with a guard
digit in add/subtract, or on those binary machines without guard
digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
Cray-2. It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none.
Arguments
=========
JOBZ (input) CHARACTER*1
Specifies options for computing all or part of the matrix U:
= 'A': all M columns of U and all N rows of V**T are
returned in the arrays U and VT;
= 'S': the first min(M,N) columns of U and the first
min(M,N) rows of V**T are returned in the arrays U
and VT;
= 'O': If M >= N, the first N columns of U are overwritten
on the array A and all rows of V**T are returned in
the array VT;
otherwise, all columns of U are returned in the
array U and the first M rows of V**T are overwritten
in the array A;
= 'N': no columns of U or rows of V**T are computed.
M (input) INTEGER
The number of rows of the input matrix A. M >= 0.
N (input) INTEGER
The number of columns of the input matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the M-by-N matrix A.
On exit,
if JOBZ = 'O', A is overwritten with the first N columns
of U (the left singular vectors, stored
columnwise) if M >= N;
A is overwritten with the first M rows
of V**T (the right singular vectors, stored
rowwise) otherwise.
if JOBZ .ne. 'O', the contents of A are destroyed.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
S (output) DOUBLE PRECISION array, dimension (min(M,N))
The singular values of A, sorted so that S(i) >= S(i+1).
U (output) DOUBLE PRECISION array, dimension (LDU,UCOL)
UCOL = M if JOBZ = 'A' or JOBZ = 'O' and M < N;
UCOL = min(M,N) if JOBZ = 'S'.
If JOBZ = 'A' or JOBZ = 'O' and M < N, U contains the M-by-M
orthogonal matrix U;
if JOBZ = 'S', U contains the first min(M,N) columns of U
(the left singular vectors, stored columnwise);
if JOBZ = 'O' and M >= N, or JOBZ = 'N', U is not referenced.
LDU (input) INTEGER
The leading dimension of the array U. LDU >= 1; if
JOBZ = 'S' or 'A' or JOBZ = 'O' and M < N, LDU >= M.
VT (output) DOUBLE PRECISION array, dimension (LDVT,N)
If JOBZ = 'A' or JOBZ = 'O' and M >= N, VT contains the
N-by-N orthogonal matrix V**T;
if JOBZ = 'S', VT contains the first min(M,N) rows of
V**T (the right singular vectors, stored rowwise);
if JOBZ = 'O' and M < N, or JOBZ = 'N', VT is not referenced.
LDVT (input) INTEGER
The leading dimension of the array VT. LDVT >= 1; if
JOBZ = 'A' or JOBZ = 'O' and M >= N, LDVT >= N;
if JOBZ = 'S', LDVT >= min(M,N).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK;
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= 1.
If JOBZ = 'N',
LWORK >= 3*min(M,N) + max(max(M,N),7*min(M,N)).
If JOBZ = 'O',
LWORK >= 3*min(M,N) +
max(max(M,N),5*min(M,N)*min(M,N)+4*min(M,N)).
If JOBZ = 'S' or 'A'
LWORK >= 3*min(M,N) +
max(max(M,N),4*min(M,N)*min(M,N)+4*min(M,N)).
For good performance, LWORK should generally be larger.
If LWORK = -1 but other input arguments are legal, WORK(1)
returns the optimal LWORK.
IWORK (workspace) INTEGER array, dimension (8*min(M,N))
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: DBDSDC did not converge, updating process failed.
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--s;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
vt_dim1 = *ldvt;
vt_offset = 1 + vt_dim1;
vt -= vt_offset;
--work;
--iwork;
/* Function Body */
*info = 0;
minmn = min(*m,*n);
wntqa = lsame_(jobz, "A");
wntqs = lsame_(jobz, "S");
wntqas = wntqa || wntqs;
wntqo = lsame_(jobz, "O");
wntqn = lsame_(jobz, "N");
lquery = *lwork == -1;
if (! (wntqa || wntqs || wntqo || wntqn)) {
*info = -1;
} else if (*m < 0) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*lda < max(1,*m)) {
*info = -5;
} else if (*ldu < 1 || wntqas && *ldu < *m || wntqo && *m < *n && *ldu < *
m) {
*info = -8;
} else if (*ldvt < 1 || wntqa && *ldvt < *n || wntqs && *ldvt < minmn ||
wntqo && *m >= *n && *ldvt < *n) {
*info = -10;
}
/*
Compute workspace
(Note: Comments in the code beginning "Workspace:" describe the
minimal amount of workspace needed at that point in the code,
as well as the preferred amount for good performance.
NB refers to the optimal block size for the immediately
following subroutine, as returned by ILAENV.)
*/
if (*info == 0) {
minwrk = 1;
maxwrk = 1;
if (*m >= *n && minmn > 0) {
/* Compute space needed for DBDSDC */
mnthr = (integer) (minmn * 11. / 6.);
if (wntqn) {
bdspac = *n * 7;
} else {
bdspac = *n * 3 * *n + (*n << 2);
}
if (*m >= mnthr) {
if (wntqn) {
/* Path 1 (M much larger than N, JOBZ='N') */
wrkbl = *n + *n * ilaenv_(&c__1, "DGEQRF", " ", m, n, &
c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + (*n << 1) * ilaenv_(&c__1,
"DGEBRD", " ", n, n, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *n;
maxwrk = max(i__1,i__2);
minwrk = bdspac + *n;
} else if (wntqo) {
/* Path 2 (M much larger than N, JOBZ='O') */
wrkbl = *n + *n * ilaenv_(&c__1, "DGEQRF", " ", m, n, &
c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n + *n * ilaenv_(&c__1, "DORGQR",
" ", m, n, n, &c_n1, (ftnlen)6, (ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + (*n << 1) * ilaenv_(&c__1,
"DGEBRD", " ", n, n, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "QLN", n, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "PRT", n, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *n * 3;
wrkbl = max(i__1,i__2);
maxwrk = wrkbl + (*n << 1) * *n;
minwrk = bdspac + (*n << 1) * *n + *n * 3;
} else if (wntqs) {
/* Path 3 (M much larger than N, JOBZ='S') */
wrkbl = *n + *n * ilaenv_(&c__1, "DGEQRF", " ", m, n, &
c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n + *n * ilaenv_(&c__1, "DORGQR",
" ", m, n, n, &c_n1, (ftnlen)6, (ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + (*n << 1) * ilaenv_(&c__1,
"DGEBRD", " ", n, n, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "QLN", n, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "PRT", n, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *n * 3;
wrkbl = max(i__1,i__2);
maxwrk = wrkbl + *n * *n;
minwrk = bdspac + *n * *n + *n * 3;
} else if (wntqa) {
/* Path 4 (M much larger than N, JOBZ='A') */
wrkbl = *n + *n * ilaenv_(&c__1, "DGEQRF", " ", m, n, &
c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n + *m * ilaenv_(&c__1, "DORGQR",
" ", m, m, n, &c_n1, (ftnlen)6, (ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + (*n << 1) * ilaenv_(&c__1,
"DGEBRD", " ", n, n, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "QLN", n, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "PRT", n, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *n * 3;
wrkbl = max(i__1,i__2);
maxwrk = wrkbl + *n * *n;
minwrk = bdspac + *n * *n + *n * 3;
}
} else {
/* Path 5 (M at least N, but not much larger) */
wrkbl = *n * 3 + (*m + *n) * ilaenv_(&c__1, "DGEBRD", " ", m,
n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
if (wntqn) {
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *n * 3;
maxwrk = max(i__1,i__2);
minwrk = *n * 3 + max(*m,bdspac);
} else if (wntqo) {
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "QLN", m, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "PRT", n, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *n * 3;
wrkbl = max(i__1,i__2);
maxwrk = wrkbl + *m * *n;
/* Computing MAX */
i__1 = *m, i__2 = *n * *n + bdspac;
minwrk = *n * 3 + max(i__1,i__2);
} else if (wntqs) {
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "QLN", m, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "PRT", n, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *n * 3;
maxwrk = max(i__1,i__2);
minwrk = *n * 3 + max(*m,bdspac);
} else if (wntqa) {
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "QLN", m, m, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *n * 3 + *n * ilaenv_(&c__1, "DORMBR"
, "PRT", n, n, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = maxwrk, i__2 = bdspac + *n * 3;
maxwrk = max(i__1,i__2);
minwrk = *n * 3 + max(*m,bdspac);
}
}
} else if (minmn > 0) {
/* Compute space needed for DBDSDC */
mnthr = (integer) (minmn * 11. / 6.);
if (wntqn) {
bdspac = *m * 7;
} else {
bdspac = *m * 3 * *m + (*m << 2);
}
if (*n >= mnthr) {
if (wntqn) {
/* Path 1t (N much larger than M, JOBZ='N') */
wrkbl = *m + *m * ilaenv_(&c__1, "DGELQF", " ", m, n, &
c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + (*m << 1) * ilaenv_(&c__1,
"DGEBRD", " ", m, m, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *m;
maxwrk = max(i__1,i__2);
minwrk = bdspac + *m;
} else if (wntqo) {
/* Path 2t (N much larger than M, JOBZ='O') */
wrkbl = *m + *m * ilaenv_(&c__1, "DGELQF", " ", m, n, &
c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m + *m * ilaenv_(&c__1, "DORGLQ",
" ", m, n, m, &c_n1, (ftnlen)6, (ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + (*m << 1) * ilaenv_(&c__1,
"DGEBRD", " ", m, m, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "QLN", m, m, m, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "PRT", m, m, m, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *m * 3;
wrkbl = max(i__1,i__2);
maxwrk = wrkbl + (*m << 1) * *m;
minwrk = bdspac + (*m << 1) * *m + *m * 3;
} else if (wntqs) {
/* Path 3t (N much larger than M, JOBZ='S') */
wrkbl = *m + *m * ilaenv_(&c__1, "DGELQF", " ", m, n, &
c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m + *m * ilaenv_(&c__1, "DORGLQ",
" ", m, n, m, &c_n1, (ftnlen)6, (ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + (*m << 1) * ilaenv_(&c__1,
"DGEBRD", " ", m, m, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "QLN", m, m, m, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "PRT", m, m, m, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *m * 3;
wrkbl = max(i__1,i__2);
maxwrk = wrkbl + *m * *m;
minwrk = bdspac + *m * *m + *m * 3;
} else if (wntqa) {
/* Path 4t (N much larger than M, JOBZ='A') */
wrkbl = *m + *m * ilaenv_(&c__1, "DGELQF", " ", m, n, &
c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m + *n * ilaenv_(&c__1, "DORGLQ",
" ", n, n, m, &c_n1, (ftnlen)6, (ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + (*m << 1) * ilaenv_(&c__1,
"DGEBRD", " ", m, m, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "QLN", m, m, m, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "PRT", m, m, m, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *m * 3;
wrkbl = max(i__1,i__2);
maxwrk = wrkbl + *m * *m;
minwrk = bdspac + *m * *m + *m * 3;
}
} else {
/* Path 5t (N greater than M, but not much larger) */
wrkbl = *m * 3 + (*m + *n) * ilaenv_(&c__1, "DGEBRD", " ", m,
n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
if (wntqn) {
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *m * 3;
maxwrk = max(i__1,i__2);
minwrk = *m * 3 + max(*n,bdspac);
} else if (wntqo) {
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "QLN", m, m, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "PRT", m, n, m, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *m * 3;
wrkbl = max(i__1,i__2);
maxwrk = wrkbl + *m * *n;
/* Computing MAX */
i__1 = *n, i__2 = *m * *m + bdspac;
minwrk = *m * 3 + max(i__1,i__2);
} else if (wntqs) {
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "QLN", m, m, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "PRT", m, n, m, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *m * 3;
maxwrk = max(i__1,i__2);
minwrk = *m * 3 + max(*n,bdspac);
} else if (wntqa) {
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "QLN", m, m, n, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = *m * 3 + *m * ilaenv_(&c__1, "DORMBR"
, "PRT", n, n, m, &c_n1, (ftnlen)6, (ftnlen)3);
wrkbl = max(i__1,i__2);
/* Computing MAX */
i__1 = wrkbl, i__2 = bdspac + *m * 3;
maxwrk = max(i__1,i__2);
minwrk = *m * 3 + max(*n,bdspac);
}
}
}
maxwrk = max(maxwrk,minwrk);
work[1] = (doublereal) maxwrk;
if (*lwork < minwrk && ! lquery) {
*info = -12;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGESDD", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0) {
return 0;
}
/* Get machine constants */
eps = PRECISION;
smlnum = sqrt(SAFEMINIMUM) / eps;
bignum = 1. / smlnum;
/* Scale A if max element outside range [SMLNUM,BIGNUM] */
anrm = dlange_("M", m, n, &a[a_offset], lda, dum);
iscl = 0;
if (anrm > 0. && anrm < smlnum) {
iscl = 1;
dlascl_("G", &c__0, &c__0, &anrm, &smlnum, m, n, &a[a_offset], lda, &
ierr);
} else if (anrm > bignum) {
iscl = 1;
dlascl_("G", &c__0, &c__0, &anrm, &bignum, m, n, &a[a_offset], lda, &
ierr);
}
if (*m >= *n) {
/*
A has at least as many rows as columns. If A has sufficiently
more rows than columns, first reduce using the QR
decomposition (if sufficient workspace available)
*/
if (*m >= mnthr) {
if (wntqn) {
/*
Path 1 (M much larger than N, JOBZ='N')
No singular vectors to be computed
*/
itau = 1;
nwork = itau + *n;
/*
Compute A=Q*R
(Workspace: need 2*N, prefer N+N*NB)
*/
i__1 = *lwork - nwork + 1;
dgeqrf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &
i__1, &ierr);
/* Zero out below R */
i__1 = *n - 1;
i__2 = *n - 1;
dlaset_("L", &i__1, &i__2, &c_b29, &c_b29, &a[a_dim1 + 2],
lda);
ie = 1;
itauq = ie + *n;
itaup = itauq + *n;
nwork = itaup + *n;
/*
Bidiagonalize R in A
(Workspace: need 4*N, prefer 3*N+2*N*NB)
*/
i__1 = *lwork - nwork + 1;
dgebrd_(n, n, &a[a_offset], lda, &s[1], &work[ie], &work[
itauq], &work[itaup], &work[nwork], &i__1, &ierr);
nwork = ie + *n;
/*
Perform bidiagonal SVD, computing singular values only
(Workspace: need N+BDSPAC)
*/
dbdsdc_("U", "N", n, &s[1], &work[ie], dum, &c__1, dum, &c__1,
dum, idum, &work[nwork], &iwork[1], info);
} else if (wntqo) {
/*
Path 2 (M much larger than N, JOBZ = 'O')
N left singular vectors to be overwritten on A and
N right singular vectors to be computed in VT
*/
ir = 1;
/* WORK(IR) is LDWRKR by N */
if (*lwork >= *lda * *n + *n * *n + *n * 3 + bdspac) {
ldwrkr = *lda;
} else {
ldwrkr = (*lwork - *n * *n - *n * 3 - bdspac) / *n;
}
itau = ir + ldwrkr * *n;
nwork = itau + *n;
/*
Compute A=Q*R
(Workspace: need N*N+2*N, prefer N*N+N+N*NB)
*/
i__1 = *lwork - nwork + 1;
dgeqrf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &
i__1, &ierr);
/* Copy R to WORK(IR), zeroing out below it */
dlacpy_("U", n, n, &a[a_offset], lda, &work[ir], &ldwrkr);
i__1 = *n - 1;
i__2 = *n - 1;
dlaset_("L", &i__1, &i__2, &c_b29, &c_b29, &work[ir + 1], &
ldwrkr);
/*
Generate Q in A
(Workspace: need N*N+2*N, prefer N*N+N+N*NB)
*/
i__1 = *lwork - nwork + 1;
dorgqr_(m, n, n, &a[a_offset], lda, &work[itau], &work[nwork],
&i__1, &ierr);
ie = itau;
itauq = ie + *n;
itaup = itauq + *n;
nwork = itaup + *n;
/*
Bidiagonalize R in VT, copying result to WORK(IR)
(Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB)
*/
i__1 = *lwork - nwork + 1;
dgebrd_(n, n, &work[ir], &ldwrkr, &s[1], &work[ie], &work[
itauq], &work[itaup], &work[nwork], &i__1, &ierr);
/* WORK(IU) is N by N */
iu = nwork;
nwork = iu + *n * *n;
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in WORK(IU) and computing right
singular vectors of bidiagonal matrix in VT
(Workspace: need N+N*N+BDSPAC)
*/
dbdsdc_("U", "I", n, &s[1], &work[ie], &work[iu], n, &vt[
vt_offset], ldvt, dum, idum, &work[nwork], &iwork[1],
info);
/*
Overwrite WORK(IU) by left singular vectors of R
and VT by right singular vectors of R
(Workspace: need 2*N*N+3*N, prefer 2*N*N+2*N+N*NB)
*/
i__1 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", n, n, n, &work[ir], &ldwrkr, &work[
itauq], &work[iu], n, &work[nwork], &i__1, &ierr);
i__1 = *lwork - nwork + 1;
dormbr_("P", "R", "T", n, n, n, &work[ir], &ldwrkr, &work[
itaup], &vt[vt_offset], ldvt, &work[nwork], &i__1, &
ierr);
/*
Multiply Q in A by left singular vectors of R in
WORK(IU), storing result in WORK(IR) and copying to A
(Workspace: need 2*N*N, prefer N*N+M*N)
*/
i__1 = *m;
i__2 = ldwrkr;
for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ +=
i__2) {
/* Computing MIN */
i__3 = *m - i__ + 1;
chunk = min(i__3,ldwrkr);
dgemm_("N", "N", &chunk, n, n, &c_b15, &a[i__ + a_dim1],
lda, &work[iu], n, &c_b29, &work[ir], &ldwrkr);
dlacpy_("F", &chunk, n, &work[ir], &ldwrkr, &a[i__ +
a_dim1], lda);
/* L10: */
}
} else if (wntqs) {
/*
Path 3 (M much larger than N, JOBZ='S')
N left singular vectors to be computed in U and
N right singular vectors to be computed in VT
*/
ir = 1;
/* WORK(IR) is N by N */
ldwrkr = *n;
itau = ir + ldwrkr * *n;
nwork = itau + *n;
/*
Compute A=Q*R
(Workspace: need N*N+2*N, prefer N*N+N+N*NB)
*/
i__2 = *lwork - nwork + 1;
dgeqrf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &
i__2, &ierr);
/* Copy R to WORK(IR), zeroing out below it */
dlacpy_("U", n, n, &a[a_offset], lda, &work[ir], &ldwrkr);
i__2 = *n - 1;
i__1 = *n - 1;
dlaset_("L", &i__2, &i__1, &c_b29, &c_b29, &work[ir + 1], &
ldwrkr);
/*
Generate Q in A
(Workspace: need N*N+2*N, prefer N*N+N+N*NB)
*/
i__2 = *lwork - nwork + 1;
dorgqr_(m, n, n, &a[a_offset], lda, &work[itau], &work[nwork],
&i__2, &ierr);
ie = itau;
itauq = ie + *n;
itaup = itauq + *n;
nwork = itaup + *n;
/*
Bidiagonalize R in WORK(IR)
(Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB)
*/
i__2 = *lwork - nwork + 1;
dgebrd_(n, n, &work[ir], &ldwrkr, &s[1], &work[ie], &work[
itauq], &work[itaup], &work[nwork], &i__2, &ierr);
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagoal matrix in U and computing right singular
vectors of bidiagonal matrix in VT
(Workspace: need N+BDSPAC)
*/
dbdsdc_("U", "I", n, &s[1], &work[ie], &u[u_offset], ldu, &vt[
vt_offset], ldvt, dum, idum, &work[nwork], &iwork[1],
info);
/*
Overwrite U by left singular vectors of R and VT
by right singular vectors of R
(Workspace: need N*N+3*N, prefer N*N+2*N+N*NB)
*/
i__2 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", n, n, n, &work[ir], &ldwrkr, &work[
itauq], &u[u_offset], ldu, &work[nwork], &i__2, &ierr);
i__2 = *lwork - nwork + 1;
dormbr_("P", "R", "T", n, n, n, &work[ir], &ldwrkr, &work[
itaup], &vt[vt_offset], ldvt, &work[nwork], &i__2, &
ierr);
/*
Multiply Q in A by left singular vectors of R in
WORK(IR), storing result in U
(Workspace: need N*N)
*/
dlacpy_("F", n, n, &u[u_offset], ldu, &work[ir], &ldwrkr);
dgemm_("N", "N", m, n, n, &c_b15, &a[a_offset], lda, &work[ir]
, &ldwrkr, &c_b29, &u[u_offset], ldu);
} else if (wntqa) {
/*
Path 4 (M much larger than N, JOBZ='A')
M left singular vectors to be computed in U and
N right singular vectors to be computed in VT
*/
iu = 1;
/* WORK(IU) is N by N */
ldwrku = *n;
itau = iu + ldwrku * *n;
nwork = itau + *n;
/*
Compute A=Q*R, copying result to U
(Workspace: need N*N+2*N, prefer N*N+N+N*NB)
*/
i__2 = *lwork - nwork + 1;
dgeqrf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &
i__2, &ierr);
dlacpy_("L", m, n, &a[a_offset], lda, &u[u_offset], ldu);
/*
Generate Q in U
(Workspace: need N*N+2*N, prefer N*N+N+N*NB)
*/
i__2 = *lwork - nwork + 1;
dorgqr_(m, m, n, &u[u_offset], ldu, &work[itau], &work[nwork],
&i__2, &ierr);
/* Produce R in A, zeroing out other entries */
i__2 = *n - 1;
i__1 = *n - 1;
dlaset_("L", &i__2, &i__1, &c_b29, &c_b29, &a[a_dim1 + 2],
lda);
ie = itau;
itauq = ie + *n;
itaup = itauq + *n;
nwork = itaup + *n;
/*
Bidiagonalize R in A
(Workspace: need N*N+4*N, prefer N*N+3*N+2*N*NB)
*/
i__2 = *lwork - nwork + 1;
dgebrd_(n, n, &a[a_offset], lda, &s[1], &work[ie], &work[
itauq], &work[itaup], &work[nwork], &i__2, &ierr);
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in WORK(IU) and computing right
singular vectors of bidiagonal matrix in VT
(Workspace: need N+N*N+BDSPAC)
*/
dbdsdc_("U", "I", n, &s[1], &work[ie], &work[iu], n, &vt[
vt_offset], ldvt, dum, idum, &work[nwork], &iwork[1],
info);
/*
Overwrite WORK(IU) by left singular vectors of R and VT
by right singular vectors of R
(Workspace: need N*N+3*N, prefer N*N+2*N+N*NB)
*/
i__2 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", n, n, n, &a[a_offset], lda, &work[
itauq], &work[iu], &ldwrku, &work[nwork], &i__2, &
ierr);
i__2 = *lwork - nwork + 1;
dormbr_("P", "R", "T", n, n, n, &a[a_offset], lda, &work[
itaup], &vt[vt_offset], ldvt, &work[nwork], &i__2, &
ierr);
/*
Multiply Q in U by left singular vectors of R in
WORK(IU), storing result in A
(Workspace: need N*N)
*/
dgemm_("N", "N", m, n, n, &c_b15, &u[u_offset], ldu, &work[iu]
, &ldwrku, &c_b29, &a[a_offset], lda);
/* Copy left singular vectors of A from A to U */
dlacpy_("F", m, n, &a[a_offset], lda, &u[u_offset], ldu);
}
} else {
/*
M .LT. MNTHR
Path 5 (M at least N, but not much larger)
Reduce to bidiagonal form without QR decomposition
*/
ie = 1;
itauq = ie + *n;
itaup = itauq + *n;
nwork = itaup + *n;
/*
Bidiagonalize A
(Workspace: need 3*N+M, prefer 3*N+(M+N)*NB)
*/
i__2 = *lwork - nwork + 1;
dgebrd_(m, n, &a[a_offset], lda, &s[1], &work[ie], &work[itauq], &
work[itaup], &work[nwork], &i__2, &ierr);
if (wntqn) {
/*
Perform bidiagonal SVD, only computing singular values
(Workspace: need N+BDSPAC)
*/
dbdsdc_("U", "N", n, &s[1], &work[ie], dum, &c__1, dum, &c__1,
dum, idum, &work[nwork], &iwork[1], info);
} else if (wntqo) {
iu = nwork;
if (*lwork >= *m * *n + *n * 3 + bdspac) {
/* WORK( IU ) is M by N */
ldwrku = *m;
nwork = iu + ldwrku * *n;
dlaset_("F", m, n, &c_b29, &c_b29, &work[iu], &ldwrku);
} else {
/* WORK( IU ) is N by N */
ldwrku = *n;
nwork = iu + ldwrku * *n;
/* WORK(IR) is LDWRKR by N */
ir = nwork;
ldwrkr = (*lwork - *n * *n - *n * 3) / *n;
}
nwork = iu + ldwrku * *n;
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in WORK(IU) and computing right
singular vectors of bidiagonal matrix in VT
(Workspace: need N+N*N+BDSPAC)
*/
dbdsdc_("U", "I", n, &s[1], &work[ie], &work[iu], &ldwrku, &
vt[vt_offset], ldvt, dum, idum, &work[nwork], &iwork[
1], info);
/*
Overwrite VT by right singular vectors of A
(Workspace: need N*N+2*N, prefer N*N+N+N*NB)
*/
i__2 = *lwork - nwork + 1;
dormbr_("P", "R", "T", n, n, n, &a[a_offset], lda, &work[
itaup], &vt[vt_offset], ldvt, &work[nwork], &i__2, &
ierr);
if (*lwork >= *m * *n + *n * 3 + bdspac) {
/*
Overwrite WORK(IU) by left singular vectors of A
(Workspace: need N*N+2*N, prefer N*N+N+N*NB)
*/
i__2 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", m, n, n, &a[a_offset], lda, &work[
itauq], &work[iu], &ldwrku, &work[nwork], &i__2, &
ierr);
/* Copy left singular vectors of A from WORK(IU) to A */
dlacpy_("F", m, n, &work[iu], &ldwrku, &a[a_offset], lda);
} else {
/*
Generate Q in A
(Workspace: need N*N+2*N, prefer N*N+N+N*NB)
*/
i__2 = *lwork - nwork + 1;
dorgbr_("Q", m, n, n, &a[a_offset], lda, &work[itauq], &
work[nwork], &i__2, &ierr);
/*
Multiply Q in A by left singular vectors of
bidiagonal matrix in WORK(IU), storing result in
WORK(IR) and copying to A
(Workspace: need 2*N*N, prefer N*N+M*N)
*/
i__2 = *m;
i__1 = ldwrkr;
for (i__ = 1; i__1 < 0 ? i__ >= i__2 : i__ <= i__2; i__ +=
i__1) {
/* Computing MIN */
i__3 = *m - i__ + 1;
chunk = min(i__3,ldwrkr);
dgemm_("N", "N", &chunk, n, n, &c_b15, &a[i__ +
a_dim1], lda, &work[iu], &ldwrku, &c_b29, &
work[ir], &ldwrkr);
dlacpy_("F", &chunk, n, &work[ir], &ldwrkr, &a[i__ +
a_dim1], lda);
/* L20: */
}
}
} else if (wntqs) {
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in U and computing right singular
vectors of bidiagonal matrix in VT
(Workspace: need N+BDSPAC)
*/
dlaset_("F", m, n, &c_b29, &c_b29, &u[u_offset], ldu);
dbdsdc_("U", "I", n, &s[1], &work[ie], &u[u_offset], ldu, &vt[
vt_offset], ldvt, dum, idum, &work[nwork], &iwork[1],
info);
/*
Overwrite U by left singular vectors of A and VT
by right singular vectors of A
(Workspace: need 3*N, prefer 2*N+N*NB)
*/
i__1 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", m, n, n, &a[a_offset], lda, &work[
itauq], &u[u_offset], ldu, &work[nwork], &i__1, &ierr);
i__1 = *lwork - nwork + 1;
dormbr_("P", "R", "T", n, n, n, &a[a_offset], lda, &work[
itaup], &vt[vt_offset], ldvt, &work[nwork], &i__1, &
ierr);
} else if (wntqa) {
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in U and computing right singular
vectors of bidiagonal matrix in VT
(Workspace: need N+BDSPAC)
*/
dlaset_("F", m, m, &c_b29, &c_b29, &u[u_offset], ldu);
dbdsdc_("U", "I", n, &s[1], &work[ie], &u[u_offset], ldu, &vt[
vt_offset], ldvt, dum, idum, &work[nwork], &iwork[1],
info);
/* Set the right corner of U to identity matrix */
if (*m > *n) {
i__1 = *m - *n;
i__2 = *m - *n;
dlaset_("F", &i__1, &i__2, &c_b29, &c_b15, &u[*n + 1 + (*
n + 1) * u_dim1], ldu);
}
/*
Overwrite U by left singular vectors of A and VT
by right singular vectors of A
(Workspace: need N*N+2*N+M, prefer N*N+2*N+M*NB)
*/
i__1 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", m, m, n, &a[a_offset], lda, &work[
itauq], &u[u_offset], ldu, &work[nwork], &i__1, &ierr);
i__1 = *lwork - nwork + 1;
dormbr_("P", "R", "T", n, n, m, &a[a_offset], lda, &work[
itaup], &vt[vt_offset], ldvt, &work[nwork], &i__1, &
ierr);
}
}
} else {
/*
A has more columns than rows. If A has sufficiently more
columns than rows, first reduce using the LQ decomposition (if
sufficient workspace available)
*/
if (*n >= mnthr) {
if (wntqn) {
/*
Path 1t (N much larger than M, JOBZ='N')
No singular vectors to be computed
*/
itau = 1;
nwork = itau + *m;
/*
Compute A=L*Q
(Workspace: need 2*M, prefer M+M*NB)
*/
i__1 = *lwork - nwork + 1;
dgelqf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &
i__1, &ierr);
/* Zero out above L */
i__1 = *m - 1;
i__2 = *m - 1;
dlaset_("U", &i__1, &i__2, &c_b29, &c_b29, &a[(a_dim1 << 1) +
1], lda);
ie = 1;
itauq = ie + *m;
itaup = itauq + *m;
nwork = itaup + *m;
/*
Bidiagonalize L in A
(Workspace: need 4*M, prefer 3*M+2*M*NB)
*/
i__1 = *lwork - nwork + 1;
dgebrd_(m, m, &a[a_offset], lda, &s[1], &work[ie], &work[
itauq], &work[itaup], &work[nwork], &i__1, &ierr);
nwork = ie + *m;
/*
Perform bidiagonal SVD, computing singular values only
(Workspace: need M+BDSPAC)
*/
dbdsdc_("U", "N", m, &s[1], &work[ie], dum, &c__1, dum, &c__1,
dum, idum, &work[nwork], &iwork[1], info);
} else if (wntqo) {
/*
Path 2t (N much larger than M, JOBZ='O')
M right singular vectors to be overwritten on A and
M left singular vectors to be computed in U
*/
ivt = 1;
/* IVT is M by M */
il = ivt + *m * *m;
if (*lwork >= *m * *n + *m * *m + *m * 3 + bdspac) {
/* WORK(IL) is M by N */
ldwrkl = *m;
chunk = *n;
} else {
ldwrkl = *m;
chunk = (*lwork - *m * *m) / *m;
}
itau = il + ldwrkl * *m;
nwork = itau + *m;
/*
Compute A=L*Q
(Workspace: need M*M+2*M, prefer M*M+M+M*NB)
*/
i__1 = *lwork - nwork + 1;
dgelqf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &
i__1, &ierr);
/* Copy L to WORK(IL), zeroing about above it */
dlacpy_("L", m, m, &a[a_offset], lda, &work[il], &ldwrkl);
i__1 = *m - 1;
i__2 = *m - 1;
dlaset_("U", &i__1, &i__2, &c_b29, &c_b29, &work[il + ldwrkl],
&ldwrkl);
/*
Generate Q in A
(Workspace: need M*M+2*M, prefer M*M+M+M*NB)
*/
i__1 = *lwork - nwork + 1;
dorglq_(m, n, m, &a[a_offset], lda, &work[itau], &work[nwork],
&i__1, &ierr);
ie = itau;
itauq = ie + *m;
itaup = itauq + *m;
nwork = itaup + *m;
/*
Bidiagonalize L in WORK(IL)
(Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB)
*/
i__1 = *lwork - nwork + 1;
dgebrd_(m, m, &work[il], &ldwrkl, &s[1], &work[ie], &work[
itauq], &work[itaup], &work[nwork], &i__1, &ierr);
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in U, and computing right singular
vectors of bidiagonal matrix in WORK(IVT)
(Workspace: need M+M*M+BDSPAC)
*/
dbdsdc_("U", "I", m, &s[1], &work[ie], &u[u_offset], ldu, &
work[ivt], m, dum, idum, &work[nwork], &iwork[1],
info);
/*
Overwrite U by left singular vectors of L and WORK(IVT)
by right singular vectors of L
(Workspace: need 2*M*M+3*M, prefer 2*M*M+2*M+M*NB)
*/
i__1 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", m, m, m, &work[il], &ldwrkl, &work[
itauq], &u[u_offset], ldu, &work[nwork], &i__1, &ierr);
i__1 = *lwork - nwork + 1;
dormbr_("P", "R", "T", m, m, m, &work[il], &ldwrkl, &work[
itaup], &work[ivt], m, &work[nwork], &i__1, &ierr);
/*
Multiply right singular vectors of L in WORK(IVT) by Q
in A, storing result in WORK(IL) and copying to A
(Workspace: need 2*M*M, prefer M*M+M*N)
*/
i__1 = *n;
i__2 = chunk;
for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ +=
i__2) {
/* Computing MIN */
i__3 = *n - i__ + 1;
blk = min(i__3,chunk);
dgemm_("N", "N", m, &blk, m, &c_b15, &work[ivt], m, &a[
i__ * a_dim1 + 1], lda, &c_b29, &work[il], &
ldwrkl);
dlacpy_("F", m, &blk, &work[il], &ldwrkl, &a[i__ * a_dim1
+ 1], lda);
/* L30: */
}
} else if (wntqs) {
/*
Path 3t (N much larger than M, JOBZ='S')
M right singular vectors to be computed in VT and
M left singular vectors to be computed in U
*/
il = 1;
/* WORK(IL) is M by M */
ldwrkl = *m;
itau = il + ldwrkl * *m;
nwork = itau + *m;
/*
Compute A=L*Q
(Workspace: need M*M+2*M, prefer M*M+M+M*NB)
*/
i__2 = *lwork - nwork + 1;
dgelqf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &
i__2, &ierr);
/* Copy L to WORK(IL), zeroing out above it */
dlacpy_("L", m, m, &a[a_offset], lda, &work[il], &ldwrkl);
i__2 = *m - 1;
i__1 = *m - 1;
dlaset_("U", &i__2, &i__1, &c_b29, &c_b29, &work[il + ldwrkl],
&ldwrkl);
/*
Generate Q in A
(Workspace: need M*M+2*M, prefer M*M+M+M*NB)
*/
i__2 = *lwork - nwork + 1;
dorglq_(m, n, m, &a[a_offset], lda, &work[itau], &work[nwork],
&i__2, &ierr);
ie = itau;
itauq = ie + *m;
itaup = itauq + *m;
nwork = itaup + *m;
/*
Bidiagonalize L in WORK(IU), copying result to U
(Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB)
*/
i__2 = *lwork - nwork + 1;
dgebrd_(m, m, &work[il], &ldwrkl, &s[1], &work[ie], &work[
itauq], &work[itaup], &work[nwork], &i__2, &ierr);
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in U and computing right singular
vectors of bidiagonal matrix in VT
(Workspace: need M+BDSPAC)
*/
dbdsdc_("U", "I", m, &s[1], &work[ie], &u[u_offset], ldu, &vt[
vt_offset], ldvt, dum, idum, &work[nwork], &iwork[1],
info);
/*
Overwrite U by left singular vectors of L and VT
by right singular vectors of L
(Workspace: need M*M+3*M, prefer M*M+2*M+M*NB)
*/
i__2 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", m, m, m, &work[il], &ldwrkl, &work[
itauq], &u[u_offset], ldu, &work[nwork], &i__2, &ierr);
i__2 = *lwork - nwork + 1;
dormbr_("P", "R", "T", m, m, m, &work[il], &ldwrkl, &work[
itaup], &vt[vt_offset], ldvt, &work[nwork], &i__2, &
ierr);
/*
Multiply right singular vectors of L in WORK(IL) by
Q in A, storing result in VT
(Workspace: need M*M)
*/
dlacpy_("F", m, m, &vt[vt_offset], ldvt, &work[il], &ldwrkl);
dgemm_("N", "N", m, n, m, &c_b15, &work[il], &ldwrkl, &a[
a_offset], lda, &c_b29, &vt[vt_offset], ldvt);
} else if (wntqa) {
/*
Path 4t (N much larger than M, JOBZ='A')
N right singular vectors to be computed in VT and
M left singular vectors to be computed in U
*/
ivt = 1;
/* WORK(IVT) is M by M */
ldwkvt = *m;
itau = ivt + ldwkvt * *m;
nwork = itau + *m;
/*
Compute A=L*Q, copying result to VT
(Workspace: need M*M+2*M, prefer M*M+M+M*NB)
*/
i__2 = *lwork - nwork + 1;
dgelqf_(m, n, &a[a_offset], lda, &work[itau], &work[nwork], &
i__2, &ierr);
dlacpy_("U", m, n, &a[a_offset], lda, &vt[vt_offset], ldvt);
/*
Generate Q in VT
(Workspace: need M*M+2*M, prefer M*M+M+M*NB)
*/
i__2 = *lwork - nwork + 1;
dorglq_(n, n, m, &vt[vt_offset], ldvt, &work[itau], &work[
nwork], &i__2, &ierr);
/* Produce L in A, zeroing out other entries */
i__2 = *m - 1;
i__1 = *m - 1;
dlaset_("U", &i__2, &i__1, &c_b29, &c_b29, &a[(a_dim1 << 1) +
1], lda);
ie = itau;
itauq = ie + *m;
itaup = itauq + *m;
nwork = itaup + *m;
/*
Bidiagonalize L in A
(Workspace: need M*M+4*M, prefer M*M+3*M+2*M*NB)
*/
i__2 = *lwork - nwork + 1;
dgebrd_(m, m, &a[a_offset], lda, &s[1], &work[ie], &work[
itauq], &work[itaup], &work[nwork], &i__2, &ierr);
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in U and computing right singular
vectors of bidiagonal matrix in WORK(IVT)
(Workspace: need M+M*M+BDSPAC)
*/
dbdsdc_("U", "I", m, &s[1], &work[ie], &u[u_offset], ldu, &
work[ivt], &ldwkvt, dum, idum, &work[nwork], &iwork[1]
, info);
/*
Overwrite U by left singular vectors of L and WORK(IVT)
by right singular vectors of L
(Workspace: need M*M+3*M, prefer M*M+2*M+M*NB)
*/
i__2 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", m, m, m, &a[a_offset], lda, &work[
itauq], &u[u_offset], ldu, &work[nwork], &i__2, &ierr);
i__2 = *lwork - nwork + 1;
dormbr_("P", "R", "T", m, m, m, &a[a_offset], lda, &work[
itaup], &work[ivt], &ldwkvt, &work[nwork], &i__2, &
ierr);
/*
Multiply right singular vectors of L in WORK(IVT) by
Q in VT, storing result in A
(Workspace: need M*M)
*/
dgemm_("N", "N", m, n, m, &c_b15, &work[ivt], &ldwkvt, &vt[
vt_offset], ldvt, &c_b29, &a[a_offset], lda);
/* Copy right singular vectors of A from A to VT */
dlacpy_("F", m, n, &a[a_offset], lda, &vt[vt_offset], ldvt);
}
} else {
/*
N .LT. MNTHR
Path 5t (N greater than M, but not much larger)
Reduce to bidiagonal form without LQ decomposition
*/
ie = 1;
itauq = ie + *m;
itaup = itauq + *m;
nwork = itaup + *m;
/*
Bidiagonalize A
(Workspace: need 3*M+N, prefer 3*M+(M+N)*NB)
*/
i__2 = *lwork - nwork + 1;
dgebrd_(m, n, &a[a_offset], lda, &s[1], &work[ie], &work[itauq], &
work[itaup], &work[nwork], &i__2, &ierr);
if (wntqn) {
/*
Perform bidiagonal SVD, only computing singular values
(Workspace: need M+BDSPAC)
*/
dbdsdc_("L", "N", m, &s[1], &work[ie], dum, &c__1, dum, &c__1,
dum, idum, &work[nwork], &iwork[1], info);
} else if (wntqo) {
ldwkvt = *m;
ivt = nwork;
if (*lwork >= *m * *n + *m * 3 + bdspac) {
/* WORK( IVT ) is M by N */
dlaset_("F", m, n, &c_b29, &c_b29, &work[ivt], &ldwkvt);
nwork = ivt + ldwkvt * *n;
} else {
/* WORK( IVT ) is M by M */
nwork = ivt + ldwkvt * *m;
il = nwork;
/* WORK(IL) is M by CHUNK */
chunk = (*lwork - *m * *m - *m * 3) / *m;
}
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in U and computing right singular
vectors of bidiagonal matrix in WORK(IVT)
(Workspace: need M*M+BDSPAC)
*/
dbdsdc_("L", "I", m, &s[1], &work[ie], &u[u_offset], ldu, &
work[ivt], &ldwkvt, dum, idum, &work[nwork], &iwork[1]
, info);
/*
Overwrite U by left singular vectors of A
(Workspace: need M*M+2*M, prefer M*M+M+M*NB)
*/
i__2 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", m, m, n, &a[a_offset], lda, &work[
itauq], &u[u_offset], ldu, &work[nwork], &i__2, &ierr);
if (*lwork >= *m * *n + *m * 3 + bdspac) {
/*
Overwrite WORK(IVT) by left singular vectors of A
(Workspace: need M*M+2*M, prefer M*M+M+M*NB)
*/
i__2 = *lwork - nwork + 1;
dormbr_("P", "R", "T", m, n, m, &a[a_offset], lda, &work[
itaup], &work[ivt], &ldwkvt, &work[nwork], &i__2,
&ierr);
/* Copy right singular vectors of A from WORK(IVT) to A */
dlacpy_("F", m, n, &work[ivt], &ldwkvt, &a[a_offset], lda);
} else {
/*
Generate P**T in A
(Workspace: need M*M+2*M, prefer M*M+M+M*NB)
*/
i__2 = *lwork - nwork + 1;
dorgbr_("P", m, n, m, &a[a_offset], lda, &work[itaup], &
work[nwork], &i__2, &ierr);
/*
Multiply Q in A by right singular vectors of
bidiagonal matrix in WORK(IVT), storing result in
WORK(IL) and copying to A
(Workspace: need 2*M*M, prefer M*M+M*N)
*/
i__2 = *n;
i__1 = chunk;
for (i__ = 1; i__1 < 0 ? i__ >= i__2 : i__ <= i__2; i__ +=
i__1) {
/* Computing MIN */
i__3 = *n - i__ + 1;
blk = min(i__3,chunk);
dgemm_("N", "N", m, &blk, m, &c_b15, &work[ivt], &
ldwkvt, &a[i__ * a_dim1 + 1], lda, &c_b29, &
work[il], m);
dlacpy_("F", m, &blk, &work[il], m, &a[i__ * a_dim1 +
1], lda);
/* L40: */
}
}
} else if (wntqs) {
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in U and computing right singular
vectors of bidiagonal matrix in VT
(Workspace: need M+BDSPAC)
*/
dlaset_("F", m, n, &c_b29, &c_b29, &vt[vt_offset], ldvt);
dbdsdc_("L", "I", m, &s[1], &work[ie], &u[u_offset], ldu, &vt[
vt_offset], ldvt, dum, idum, &work[nwork], &iwork[1],
info);
/*
Overwrite U by left singular vectors of A and VT
by right singular vectors of A
(Workspace: need 3*M, prefer 2*M+M*NB)
*/
i__1 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", m, m, n, &a[a_offset], lda, &work[
itauq], &u[u_offset], ldu, &work[nwork], &i__1, &ierr);
i__1 = *lwork - nwork + 1;
dormbr_("P", "R", "T", m, n, m, &a[a_offset], lda, &work[
itaup], &vt[vt_offset], ldvt, &work[nwork], &i__1, &
ierr);
} else if (wntqa) {
/*
Perform bidiagonal SVD, computing left singular vectors
of bidiagonal matrix in U and computing right singular
vectors of bidiagonal matrix in VT
(Workspace: need M+BDSPAC)
*/
dlaset_("F", n, n, &c_b29, &c_b29, &vt[vt_offset], ldvt);
dbdsdc_("L", "I", m, &s[1], &work[ie], &u[u_offset], ldu, &vt[
vt_offset], ldvt, dum, idum, &work[nwork], &iwork[1],
info);
/* Set the right corner of VT to identity matrix */
if (*n > *m) {
i__1 = *n - *m;
i__2 = *n - *m;
dlaset_("F", &i__1, &i__2, &c_b29, &c_b15, &vt[*m + 1 + (*
m + 1) * vt_dim1], ldvt);
}
/*
Overwrite U by left singular vectors of A and VT
by right singular vectors of A
(Workspace: need 2*M+N, prefer 2*M+N*NB)
*/
i__1 = *lwork - nwork + 1;
dormbr_("Q", "L", "N", m, m, n, &a[a_offset], lda, &work[
itauq], &u[u_offset], ldu, &work[nwork], &i__1, &ierr);
i__1 = *lwork - nwork + 1;
dormbr_("P", "R", "T", n, n, m, &a[a_offset], lda, &work[
itaup], &vt[vt_offset], ldvt, &work[nwork], &i__1, &
ierr);
}
}
}
/* Undo scaling if necessary */
if (iscl == 1) {
if (anrm > bignum) {
dlascl_("G", &c__0, &c__0, &bignum, &anrm, &minmn, &c__1, &s[1], &
minmn, &ierr);
}
if (anrm < smlnum) {
dlascl_("G", &c__0, &c__0, &smlnum, &anrm, &minmn, &c__1, &s[1], &
minmn, &ierr);
}
}
/* Return optimal workspace in WORK(1) */
work[1] = (doublereal) maxwrk;
return 0;
/* End of DGESDD */
} /* dgesdd_ */
/* Subroutine */ int dgesv_(integer *n, integer *nrhs, doublereal *a, integer
*lda, integer *ipiv, doublereal *b, integer *ldb, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, b_dim1, b_offset, i__1;
/* Local variables */
extern /* Subroutine */ int dgetrf_(integer *, integer *, doublereal *,
integer *, integer *, integer *), xerbla_(char *, integer *), dgetrs_(char *, integer *, integer *, doublereal *,
integer *, integer *, doublereal *, integer *, integer *);
/*
-- LAPACK driver routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGESV computes the solution to a real system of linear equations
A * X = B,
where A is an N-by-N matrix and X and B are N-by-NRHS matrices.
The LU decomposition with partial pivoting and row interchanges is
used to factor A as
A = P * L * U,
where P is a permutation matrix, L is unit lower triangular, and U is
upper triangular. The factored form of A is then used to solve the
system of equations A * X = B.
Arguments
=========
N (input) INTEGER
The number of linear equations, i.e., the order of the
matrix A. N >= 0.
NRHS (input) INTEGER
The number of right hand sides, i.e., the number of columns
of the matrix B. NRHS >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the N-by-N coefficient matrix A.
On exit, the factors L and U from the factorization
A = P*L*U; the unit diagonal elements of L are not stored.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
IPIV (output) INTEGER array, dimension (N)
The pivot indices that define the permutation matrix P;
row i of the matrix was interchanged with row IPIV(i).
B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS)
On entry, the N-by-NRHS matrix of right hand side matrix B.
On exit, if INFO = 0, the N-by-NRHS solution matrix X.
LDB (input) INTEGER
The leading dimension of the array B. LDB >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, U(i,i) is exactly zero. The factorization
has been completed, but the factor U is exactly
singular, so the solution could not be computed.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--ipiv;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -1;
} else if (*nrhs < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
} else if (*ldb < max(1,*n)) {
*info = -7;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGESV ", &i__1);
return 0;
}
/* Compute the LU factorization of A. */
dgetrf_(n, n, &a[a_offset], lda, &ipiv[1], info);
if (*info == 0) {
/* Solve the system A*X = B, overwriting B with X. */
dgetrs_("No transpose", n, nrhs, &a[a_offset], lda, &ipiv[1], &b[
b_offset], ldb, info);
}
return 0;
/* End of DGESV */
} /* dgesv_ */
/* Subroutine */ int dgetf2_(integer *m, integer *n, doublereal *a, integer *
lda, integer *ipiv, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
doublereal d__1;
/* Local variables */
static integer i__, j, jp;
extern /* Subroutine */ int dger_(integer *, integer *, doublereal *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *), dscal_(integer *, doublereal *, doublereal *, integer
*);
static doublereal sfmin;
extern /* Subroutine */ int dswap_(integer *, doublereal *, integer *,
doublereal *, integer *);
extern integer idamax_(integer *, doublereal *, integer *);
extern /* Subroutine */ int xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGETF2 computes an LU factorization of a general m-by-n matrix A
using partial pivoting with row interchanges.
The factorization has the form
A = P * L * U
where P is a permutation matrix, L is lower triangular with unit
diagonal elements (lower trapezoidal if m > n), and U is upper
triangular (upper trapezoidal if m < n).
This is the right-looking Level 2 BLAS version of the algorithm.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the m by n matrix to be factored.
On exit, the factors L and U from the factorization
A = P*L*U; the unit diagonal elements of L are not stored.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
IPIV (output) INTEGER array, dimension (min(M,N))
The pivot indices; for 1 <= i <= min(M,N), row i of the
matrix was interchanged with row IPIV(i).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -k, the k-th argument had an illegal value
> 0: if INFO = k, U(k,k) is exactly zero. The factorization
has been completed, but the factor U is exactly
singular, and division by zero will occur if it is used
to solve a system of equations.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--ipiv;
/* Function Body */
*info = 0;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*m)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGETF2", &i__1);
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0) {
return 0;
}
/* Compute machine safe minimum */
sfmin = SAFEMINIMUM;
i__1 = min(*m,*n);
for (j = 1; j <= i__1; ++j) {
/* Find pivot and test for singularity. */
i__2 = *m - j + 1;
jp = j - 1 + idamax_(&i__2, &a[j + j * a_dim1], &c__1);
ipiv[j] = jp;
if (a[jp + j * a_dim1] != 0.) {
/* Apply the interchange to columns 1:N. */
if (jp != j) {
dswap_(n, &a[j + a_dim1], lda, &a[jp + a_dim1], lda);
}
/* Compute elements J+1:M of J-th column. */
if (j < *m) {
if ((d__1 = a[j + j * a_dim1], abs(d__1)) >= sfmin) {
i__2 = *m - j;
d__1 = 1. / a[j + j * a_dim1];
dscal_(&i__2, &d__1, &a[j + 1 + j * a_dim1], &c__1);
} else {
i__2 = *m - j;
for (i__ = 1; i__ <= i__2; ++i__) {
a[j + i__ + j * a_dim1] /= a[j + j * a_dim1];
/* L20: */
}
}
}
} else if (*info == 0) {
*info = j;
}
if (j < min(*m,*n)) {
/* Update trailing submatrix. */
i__2 = *m - j;
i__3 = *n - j;
dger_(&i__2, &i__3, &c_b151, &a[j + 1 + j * a_dim1], &c__1, &a[j
+ (j + 1) * a_dim1], lda, &a[j + 1 + (j + 1) * a_dim1],
lda);
}
/* L10: */
}
return 0;
/* End of DGETF2 */
} /* dgetf2_ */
/* Subroutine */ int dgetrf_(integer *m, integer *n, doublereal *a, integer *
lda, integer *ipiv, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4, i__5;
/* Local variables */
static integer i__, j, jb, nb;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static integer iinfo;
extern /* Subroutine */ int dtrsm_(char *, char *, char *, char *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *), dgetf2_(
integer *, integer *, doublereal *, integer *, integer *, integer
*), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int dlaswp_(integer *, doublereal *, integer *,
integer *, integer *, integer *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGETRF computes an LU factorization of a general M-by-N matrix A
using partial pivoting with row interchanges.
The factorization has the form
A = P * L * U
where P is a permutation matrix, L is lower triangular with unit
diagonal elements (lower trapezoidal if m > n), and U is upper
triangular (upper trapezoidal if m < n).
This is the right-looking Level 3 BLAS version of the algorithm.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the M-by-N matrix to be factored.
On exit, the factors L and U from the factorization
A = P*L*U; the unit diagonal elements of L are not stored.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
IPIV (output) INTEGER array, dimension (min(M,N))
The pivot indices; for 1 <= i <= min(M,N), row i of the
matrix was interchanged with row IPIV(i).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, U(i,i) is exactly zero. The factorization
has been completed, but the factor U is exactly
singular, and division by zero will occur if it is used
to solve a system of equations.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--ipiv;
/* Function Body */
*info = 0;
if (*m < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*m)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGETRF", &i__1);
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0) {
return 0;
}
/* Determine the block size for this environment. */
nb = ilaenv_(&c__1, "DGETRF", " ", m, n, &c_n1, &c_n1, (ftnlen)6, (ftnlen)
1);
if (nb <= 1 || nb >= min(*m,*n)) {
/* Use unblocked code. */
dgetf2_(m, n, &a[a_offset], lda, &ipiv[1], info);
} else {
/* Use blocked code. */
i__1 = min(*m,*n);
i__2 = nb;
for (j = 1; i__2 < 0 ? j >= i__1 : j <= i__1; j += i__2) {
/* Computing MIN */
i__3 = min(*m,*n) - j + 1;
jb = min(i__3,nb);
/*
Factor diagonal and subdiagonal blocks and test for exact
singularity.
*/
i__3 = *m - j + 1;
dgetf2_(&i__3, &jb, &a[j + j * a_dim1], lda, &ipiv[j], &iinfo);
/* Adjust INFO and the pivot indices. */
if (*info == 0 && iinfo > 0) {
*info = iinfo + j - 1;
}
/* Computing MIN */
i__4 = *m, i__5 = j + jb - 1;
i__3 = min(i__4,i__5);
for (i__ = j; i__ <= i__3; ++i__) {
ipiv[i__] = j - 1 + ipiv[i__];
/* L10: */
}
/* Apply interchanges to columns 1:J-1. */
i__3 = j - 1;
i__4 = j + jb - 1;
dlaswp_(&i__3, &a[a_offset], lda, &j, &i__4, &ipiv[1], &c__1);
if (j + jb <= *n) {
/* Apply interchanges to columns J+JB:N. */
i__3 = *n - j - jb + 1;
i__4 = j + jb - 1;
dlaswp_(&i__3, &a[(j + jb) * a_dim1 + 1], lda, &j, &i__4, &
ipiv[1], &c__1);
/* Compute block row of U. */
i__3 = *n - j - jb + 1;
dtrsm_("Left", "Lower", "No transpose", "Unit", &jb, &i__3, &
c_b15, &a[j + j * a_dim1], lda, &a[j + (j + jb) *
a_dim1], lda);
if (j + jb <= *m) {
/* Update trailing submatrix. */
i__3 = *m - j - jb + 1;
i__4 = *n - j - jb + 1;
dgemm_("No transpose", "No transpose", &i__3, &i__4, &jb,
&c_b151, &a[j + jb + j * a_dim1], lda, &a[j + (j
+ jb) * a_dim1], lda, &c_b15, &a[j + jb + (j + jb)
* a_dim1], lda);
}
}
/* L20: */
}
}
return 0;
/* End of DGETRF */
} /* dgetrf_ */
/* Subroutine */ int dgetrs_(char *trans, integer *n, integer *nrhs,
doublereal *a, integer *lda, integer *ipiv, doublereal *b, integer *
ldb, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, b_dim1, b_offset, i__1;
/* Local variables */
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dtrsm_(char *, char *, char *, char *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *), xerbla_(
char *, integer *), dlaswp_(integer *, doublereal *,
integer *, integer *, integer *, integer *, integer *);
static logical notran;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DGETRS solves a system of linear equations
A * X = B or A' * X = B
with a general N-by-N matrix A using the LU factorization computed
by DGETRF.
Arguments
=========
TRANS (input) CHARACTER*1
Specifies the form of the system of equations:
= 'N': A * X = B (No transpose)
= 'T': A'* X = B (Transpose)
= 'C': A'* X = B (Conjugate transpose = Transpose)
N (input) INTEGER
The order of the matrix A. N >= 0.
NRHS (input) INTEGER
The number of right hand sides, i.e., the number of columns
of the matrix B. NRHS >= 0.
A (input) DOUBLE PRECISION array, dimension (LDA,N)
The factors L and U from the factorization A = P*L*U
as computed by DGETRF.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
IPIV (input) INTEGER array, dimension (N)
The pivot indices from DGETRF; for 1<=i<=N, row i of the
matrix was interchanged with row IPIV(i).
B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS)
On entry, the right hand side matrix B.
On exit, the solution matrix X.
LDB (input) INTEGER
The leading dimension of the array B. LDB >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--ipiv;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
/* Function Body */
*info = 0;
notran = lsame_(trans, "N");
if (! notran && ! lsame_(trans, "T") && ! lsame_(
trans, "C")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*nrhs < 0) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
} else if (*ldb < max(1,*n)) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DGETRS", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0 || *nrhs == 0) {
return 0;
}
if (notran) {
/*
Solve A * X = B.
Apply row interchanges to the right hand sides.
*/
dlaswp_(nrhs, &b[b_offset], ldb, &c__1, n, &ipiv[1], &c__1);
/* Solve L*X = B, overwriting B with X. */
dtrsm_("Left", "Lower", "No transpose", "Unit", n, nrhs, &c_b15, &a[
a_offset], lda, &b[b_offset], ldb);
/* Solve U*X = B, overwriting B with X. */
dtrsm_("Left", "Upper", "No transpose", "Non-unit", n, nrhs, &c_b15, &
a[a_offset], lda, &b[b_offset], ldb);
} else {
/*
Solve A' * X = B.
Solve U'*X = B, overwriting B with X.
*/
dtrsm_("Left", "Upper", "Transpose", "Non-unit", n, nrhs, &c_b15, &a[
a_offset], lda, &b[b_offset], ldb);
/* Solve L'*X = B, overwriting B with X. */
dtrsm_("Left", "Lower", "Transpose", "Unit", n, nrhs, &c_b15, &a[
a_offset], lda, &b[b_offset], ldb);
/* Apply row interchanges to the solution vectors. */
dlaswp_(nrhs, &b[b_offset], ldb, &c__1, n, &ipiv[1], &c_n1);
}
return 0;
/* End of DGETRS */
} /* dgetrs_ */
/* Subroutine */ int dhseqr_(char *job, char *compz, integer *n, integer *ilo,
integer *ihi, doublereal *h__, integer *ldh, doublereal *wr,
doublereal *wi, doublereal *z__, integer *ldz, doublereal *work,
integer *lwork, integer *info)
{
/* System generated locals */
address a__1[2];
integer h_dim1, h_offset, z_dim1, z_offset, i__1, i__2[2], i__3;
doublereal d__1;
char ch__1[2];
/* Local variables */
static integer i__;
static doublereal hl[2401] /* was [49][49] */;
static integer kbot, nmin;
extern logical lsame_(char *, char *);
static logical initz;
static doublereal workl[49];
static logical wantt, wantz;
extern /* Subroutine */ int dlaqr0_(logical *, logical *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, integer *, doublereal *, integer *,
doublereal *, integer *, integer *), dlahqr_(logical *, logical *,
integer *, integer *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *), dlacpy_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *),
dlaset_(char *, integer *, integer *, doublereal *, doublereal *,
doublereal *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int xerbla_(char *, integer *);
static logical lquery;
/*
-- LAPACK computational routine (version 3.2.2) --
Univ. of Tennessee, Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..
June 2010
Purpose
=======
DHSEQR computes the eigenvalues of a Hessenberg matrix H
and, optionally, the matrices T and Z from the Schur decomposition
H = Z T Z**T, where T is an upper quasi-triangular matrix (the
Schur form), and Z is the orthogonal matrix of Schur vectors.
Optionally Z may be postmultiplied into an input orthogonal
matrix Q so that this routine can give the Schur factorization
of a matrix A which has been reduced to the Hessenberg form H
by the orthogonal matrix Q: A = Q*H*Q**T = (QZ)*T*(QZ)**T.
Arguments
=========
JOB (input) CHARACTER*1
= 'E': compute eigenvalues only;
= 'S': compute eigenvalues and the Schur form T.
COMPZ (input) CHARACTER*1
= 'N': no Schur vectors are computed;
= 'I': Z is initialized to the unit matrix and the matrix Z
of Schur vectors of H is returned;
= 'V': Z must contain an orthogonal matrix Q on entry, and
the product Q*Z is returned.
N (input) INTEGER
The order of the matrix H. N .GE. 0.
ILO (input) INTEGER
IHI (input) INTEGER
It is assumed that H is already upper triangular in rows
and columns 1:ILO-1 and IHI+1:N. ILO and IHI are normally
set by a previous call to DGEBAL, and then passed to DGEHRD
when the matrix output by DGEBAL is reduced to Hessenberg
form. Otherwise ILO and IHI should be set to 1 and N
respectively. If N.GT.0, then 1.LE.ILO.LE.IHI.LE.N.
If N = 0, then ILO = 1 and IHI = 0.
H (input/output) DOUBLE PRECISION array, dimension (LDH,N)
On entry, the upper Hessenberg matrix H.
On exit, if INFO = 0 and JOB = 'S', then H contains the
upper quasi-triangular matrix T from the Schur decomposition
(the Schur form); 2-by-2 diagonal blocks (corresponding to
complex conjugate pairs of eigenvalues) are returned in
standard form, with H(i,i) = H(i+1,i+1) and
H(i+1,i)*H(i,i+1).LT.0. If INFO = 0 and JOB = 'E', the
contents of H are unspecified on exit. (The output value of
H when INFO.GT.0 is given under the description of INFO
below.)
Unlike earlier versions of DHSEQR, this subroutine may
explicitly H(i,j) = 0 for i.GT.j and j = 1, 2, ... ILO-1
or j = IHI+1, IHI+2, ... N.
LDH (input) INTEGER
The leading dimension of the array H. LDH .GE. max(1,N).
WR (output) DOUBLE PRECISION array, dimension (N)
WI (output) DOUBLE PRECISION array, dimension (N)
The real and imaginary parts, respectively, of the computed
eigenvalues. If two eigenvalues are computed as a complex
conjugate pair, they are stored in consecutive elements of
WR and WI, say the i-th and (i+1)th, with WI(i) .GT. 0 and
WI(i+1) .LT. 0. If JOB = 'S', the eigenvalues are stored in
the same order as on the diagonal of the Schur form returned
in H, with WR(i) = H(i,i) and, if H(i:i+1,i:i+1) is a 2-by-2
diagonal block, WI(i) = sqrt(-H(i+1,i)*H(i,i+1)) and
WI(i+1) = -WI(i).
Z (input/output) DOUBLE PRECISION array, dimension (LDZ,N)
If COMPZ = 'N', Z is not referenced.
If COMPZ = 'I', on entry Z need not be set and on exit,
if INFO = 0, Z contains the orthogonal matrix Z of the Schur
vectors of H. If COMPZ = 'V', on entry Z must contain an
N-by-N matrix Q, which is assumed to be equal to the unit
matrix except for the submatrix Z(ILO:IHI,ILO:IHI). On exit,
if INFO = 0, Z contains Q*Z.
Normally Q is the orthogonal matrix generated by DORGHR
after the call to DGEHRD which formed the Hessenberg matrix
H. (The output value of Z when INFO.GT.0 is given under
the description of INFO below.)
LDZ (input) INTEGER
The leading dimension of the array Z. if COMPZ = 'I' or
COMPZ = 'V', then LDZ.GE.MAX(1,N). Otherwize, LDZ.GE.1.
WORK (workspace/output) DOUBLE PRECISION array, dimension (LWORK)
On exit, if INFO = 0, WORK(1) returns an estimate of
the optimal value for LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK .GE. max(1,N)
is sufficient and delivers very good and sometimes
optimal performance. However, LWORK as large as 11*N
may be required for optimal performance. A workspace
query is recommended to determine the optimal workspace
size.
If LWORK = -1, then DHSEQR does a workspace query.
In this case, DHSEQR checks the input parameters and
estimates the optimal workspace size for the given
values of N, ILO and IHI. The estimate is returned
in WORK(1). No error message related to LWORK is
issued by XERBLA. Neither H nor Z are accessed.
INFO (output) INTEGER
= 0: successful exit
.LT. 0: if INFO = -i, the i-th argument had an illegal
value
.GT. 0: if INFO = i, DHSEQR failed to compute all of
the eigenvalues. Elements 1:ilo-1 and i+1:n of WR
and WI contain those eigenvalues which have been
successfully computed. (Failures are rare.)
If INFO .GT. 0 and JOB = 'E', then on exit, the
remaining unconverged eigenvalues are the eigen-
values of the upper Hessenberg matrix rows and
columns ILO through INFO of the final, output
value of H.
If INFO .GT. 0 and JOB = 'S', then on exit
(*) (initial value of H)*U = U*(final value of H)
where U is an orthogonal matrix. The final
value of H is upper Hessenberg and quasi-triangular
in rows and columns INFO+1 through IHI.
If INFO .GT. 0 and COMPZ = 'V', then on exit
(final value of Z) = (initial value of Z)*U
where U is the orthogonal matrix in (*) (regard-
less of the value of JOB.)
If INFO .GT. 0 and COMPZ = 'I', then on exit
(final value of Z) = U
where U is the orthogonal matrix in (*) (regard-
less of the value of JOB.)
If INFO .GT. 0 and COMPZ = 'N', then Z is not
accessed.
================================================================
Default values supplied by
ILAENV(ISPEC,'DHSEQR',JOB(:1)//COMPZ(:1),N,ILO,IHI,LWORK).
It is suggested that these defaults be adjusted in order
to attain best performance in each particular
computational environment.
ISPEC=12: The DLAHQR vs DLAQR0 crossover point.
Default: 75. (Must be at least 11.)
ISPEC=13: Recommended deflation window size.
This depends on ILO, IHI and NS. NS is the
number of simultaneous shifts returned
by ILAENV(ISPEC=15). (See ISPEC=15 below.)
The default for (IHI-ILO+1).LE.500 is NS.
The default for (IHI-ILO+1).GT.500 is 3*NS/2.
ISPEC=14: Nibble crossover point. (See IPARMQ for
details.) Default: 14% of deflation window
size.
ISPEC=15: Number of simultaneous shifts in a multishift
QR iteration.
If IHI-ILO+1 is ...
greater than ...but less ... the
or equal to ... than default is
1 30 NS = 2(+)
30 60 NS = 4(+)
60 150 NS = 10(+)
150 590 NS = **
590 3000 NS = 64
3000 6000 NS = 128
6000 infinity NS = 256
(+) By default some or all matrices of this order
are passed to the implicit double shift routine
DLAHQR and this parameter is ignored. See
ISPEC=12 above and comments in IPARMQ for
details.
(**) The asterisks (**) indicate an ad-hoc
function of N increasing from 10 to 64.
ISPEC=16: Select structured matrix multiply.
If the number of simultaneous shifts (specified
by ISPEC=15) is less than 14, then the default
for ISPEC=16 is 0. Otherwise the default for
ISPEC=16 is 2.
================================================================
Based on contributions by
Karen Braman and Ralph Byers, Department of Mathematics,
University of Kansas, USA
================================================================
References:
K. Braman, R. Byers and R. Mathias, The Multi-Shift QR
Algorithm Part I: Maintaining Well Focused Shifts, and Level 3
Performance, SIAM Journal of Matrix Analysis, volume 23, pages
929--947, 2002.
K. Braman, R. Byers and R. Mathias, The Multi-Shift QR
Algorithm Part II: Aggressive Early Deflation, SIAM Journal
of Matrix Analysis, volume 23, pages 948--973, 2002.
================================================================
==== Matrices of order NTINY or smaller must be processed by
. DLAHQR because of insufficient subdiagonal scratch space.
. (This is a hard limit.) ====
==== NL allocates some local workspace to help small matrices
. through a rare DLAHQR failure. NL .GT. NTINY = 11 is
. required and NL .LE. NMIN = ILAENV(ISPEC=12,...) is recom-
. mended. (The default value of NMIN is 75.) Using NL = 49
. allows up to six simultaneous shifts and a 16-by-16
. deflation window. ====
==== Decode and check the input parameters. ====
*/
/* Parameter adjustments */
h_dim1 = *ldh;
h_offset = 1 + h_dim1;
h__ -= h_offset;
--wr;
--wi;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--work;
/* Function Body */
wantt = lsame_(job, "S");
initz = lsame_(compz, "I");
wantz = initz || lsame_(compz, "V");
work[1] = (doublereal) max(1,*n);
lquery = *lwork == -1;
*info = 0;
if (! lsame_(job, "E") && ! wantt) {
*info = -1;
} else if (! lsame_(compz, "N") && ! wantz) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*ilo < 1 || *ilo > max(1,*n)) {
*info = -4;
} else if (*ihi < min(*ilo,*n) || *ihi > *n) {
*info = -5;
} else if (*ldh < max(1,*n)) {
*info = -7;
} else if (*ldz < 1 || wantz && *ldz < max(1,*n)) {
*info = -11;
} else if (*lwork < max(1,*n) && ! lquery) {
*info = -13;
}
if (*info != 0) {
/* ==== Quick return in case of invalid argument. ==== */
i__1 = -(*info);
xerbla_("DHSEQR", &i__1);
return 0;
} else if (*n == 0) {
/* ==== Quick return in case N = 0; nothing to do. ==== */
return 0;
} else if (lquery) {
/* ==== Quick return in case of a workspace query ==== */
dlaqr0_(&wantt, &wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1], &wi[
1], ilo, ihi, &z__[z_offset], ldz, &work[1], lwork, info);
/*
==== Ensure reported workspace size is backward-compatible with
. previous LAPACK versions. ====
Computing MAX
*/
d__1 = (doublereal) max(1,*n);
work[1] = max(d__1,work[1]);
return 0;
} else {
/* ==== copy eigenvalues isolated by DGEBAL ==== */
i__1 = *ilo - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
wr[i__] = h__[i__ + i__ * h_dim1];
wi[i__] = 0.;
/* L10: */
}
i__1 = *n;
for (i__ = *ihi + 1; i__ <= i__1; ++i__) {
wr[i__] = h__[i__ + i__ * h_dim1];
wi[i__] = 0.;
/* L20: */
}
/* ==== Initialize Z, if requested ==== */
if (initz) {
dlaset_("A", n, n, &c_b29, &c_b15, &z__[z_offset], ldz)
;
}
/* ==== Quick return if possible ==== */
if (*ilo == *ihi) {
wr[*ilo] = h__[*ilo + *ilo * h_dim1];
wi[*ilo] = 0.;
return 0;
}
/*
==== DLAHQR/DLAQR0 crossover point ====
Writing concatenation
*/
i__2[0] = 1, a__1[0] = job;
i__2[1] = 1, a__1[1] = compz;
s_cat(ch__1, a__1, i__2, &c__2, (ftnlen)2);
nmin = ilaenv_(&c__12, "DHSEQR", ch__1, n, ilo, ihi, lwork, (ftnlen)6,
(ftnlen)2);
nmin = max(11,nmin);
/* ==== DLAQR0 for big matrices; DLAHQR for small ones ==== */
if (*n > nmin) {
dlaqr0_(&wantt, &wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1],
&wi[1], ilo, ihi, &z__[z_offset], ldz, &work[1], lwork,
info);
} else {
/* ==== Small matrix ==== */
dlahqr_(&wantt, &wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1],
&wi[1], ilo, ihi, &z__[z_offset], ldz, info);
if (*info > 0) {
/*
==== A rare DLAHQR failure! DLAQR0 sometimes succeeds
. when DLAHQR fails. ====
*/
kbot = *info;
if (*n >= 49) {
/*
==== Larger matrices have enough subdiagonal scratch
. space to call DLAQR0 directly. ====
*/
dlaqr0_(&wantt, &wantz, n, ilo, &kbot, &h__[h_offset],
ldh, &wr[1], &wi[1], ilo, ihi, &z__[z_offset],
ldz, &work[1], lwork, info);
} else {
/*
==== Tiny matrices don't have enough subdiagonal
. scratch space to benefit from DLAQR0. Hence,
. tiny matrices must be copied into a larger
. array before calling DLAQR0. ====
*/
dlacpy_("A", n, n, &h__[h_offset], ldh, hl, &c__49);
hl[*n + 1 + *n * 49 - 50] = 0.;
i__1 = 49 - *n;
dlaset_("A", &c__49, &i__1, &c_b29, &c_b29, &hl[(*n + 1) *
49 - 49], &c__49);
dlaqr0_(&wantt, &wantz, &c__49, ilo, &kbot, hl, &c__49, &
wr[1], &wi[1], ilo, ihi, &z__[z_offset], ldz,
workl, &c__49, info);
if (wantt || *info != 0) {
dlacpy_("A", n, n, hl, &c__49, &h__[h_offset], ldh);
}
}
}
}
/* ==== Clear out the trash, if necessary. ==== */
if ((wantt || *info != 0) && *n > 2) {
i__1 = *n - 2;
i__3 = *n - 2;
dlaset_("L", &i__1, &i__3, &c_b29, &c_b29, &h__[h_dim1 + 3], ldh);
}
/*
==== Ensure reported workspace size is backward-compatible with
. previous LAPACK versions. ====
Computing MAX
*/
d__1 = (doublereal) max(1,*n);
work[1] = max(d__1,work[1]);
}
/* ==== End of DHSEQR ==== */
return 0;
} /* dhseqr_ */
logical disnan_(doublereal *din)
{
/* System generated locals */
logical ret_val;
/* Local variables */
extern logical dlaisnan_(doublereal *, doublereal *);
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DISNAN returns .TRUE. if its argument is NaN, and .FALSE.
otherwise. To be replaced by the Fortran 2003 intrinsic in the
future.
Arguments
=========
DIN (input) DOUBLE PRECISION
Input to test for NaN.
=====================================================================
*/
ret_val = dlaisnan_(din, din);
return ret_val;
} /* disnan_ */
/* Subroutine */ int dlabad_(doublereal *small, doublereal *large)
{
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLABAD takes as input the values computed by DLAMCH for underflow and
overflow, and returns the square root of each of these values if the
log of LARGE is sufficiently large. This subroutine is intended to
identify machines with a large exponent range, such as the Crays, and
redefine the underflow and overflow limits to be the square roots of
the values computed by DLAMCH. This subroutine is needed because
DLAMCH does not compensate for poor arithmetic in the upper half of
the exponent range, as is found on a Cray.
Arguments
=========
SMALL (input/output) DOUBLE PRECISION
On entry, the underflow threshold as computed by DLAMCH.
On exit, if LOG10(LARGE) is sufficiently large, the square
root of SMALL, otherwise unchanged.
LARGE (input/output) DOUBLE PRECISION
On entry, the overflow threshold as computed by DLAMCH.
On exit, if LOG10(LARGE) is sufficiently large, the square
root of LARGE, otherwise unchanged.
=====================================================================
If it looks like we're on a Cray, take the square root of
SMALL and LARGE to avoid overflow and underflow problems.
*/
if (d_lg10(large) > 2e3) {
*small = sqrt(*small);
*large = sqrt(*large);
}
return 0;
/* End of DLABAD */
} /* dlabad_ */
/* Subroutine */ int dlabrd_(integer *m, integer *n, integer *nb, doublereal *
a, integer *lda, doublereal *d__, doublereal *e, doublereal *tauq,
doublereal *taup, doublereal *x, integer *ldx, doublereal *y, integer
*ldy)
{
/* System generated locals */
integer a_dim1, a_offset, x_dim1, x_offset, y_dim1, y_offset, i__1, i__2,
i__3;
/* Local variables */
static integer i__;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *), dgemv_(char *, integer *, integer *, doublereal *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *), dlarfg_(integer *, doublereal *,
doublereal *, integer *, doublereal *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLABRD reduces the first NB rows and columns of a real general
m by n matrix A to upper or lower bidiagonal form by an orthogonal
transformation Q' * A * P, and returns the matrices X and Y which
are needed to apply the transformation to the unreduced part of A.
If m >= n, A is reduced to upper bidiagonal form; if m < n, to lower
bidiagonal form.
This is an auxiliary routine called by DGEBRD
Arguments
=========
M (input) INTEGER
The number of rows in the matrix A.
N (input) INTEGER
The number of columns in the matrix A.
NB (input) INTEGER
The number of leading rows and columns of A to be reduced.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the m by n general matrix to be reduced.
On exit, the first NB rows and columns of the matrix are
overwritten; the rest of the array is unchanged.
If m >= n, elements on and below the diagonal in the first NB
columns, with the array TAUQ, represent the orthogonal
matrix Q as a product of elementary reflectors; and
elements above the diagonal in the first NB rows, with the
array TAUP, represent the orthogonal matrix P as a product
of elementary reflectors.
If m < n, elements below the diagonal in the first NB
columns, with the array TAUQ, represent the orthogonal
matrix Q as a product of elementary reflectors, and
elements on and above the diagonal in the first NB rows,
with the array TAUP, represent the orthogonal matrix P as
a product of elementary reflectors.
See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
D (output) DOUBLE PRECISION array, dimension (NB)
The diagonal elements of the first NB rows and columns of
the reduced matrix. D(i) = A(i,i).
E (output) DOUBLE PRECISION array, dimension (NB)
The off-diagonal elements of the first NB rows and columns of
the reduced matrix.
TAUQ (output) DOUBLE PRECISION array dimension (NB)
The scalar factors of the elementary reflectors which
represent the orthogonal matrix Q. See Further Details.
TAUP (output) DOUBLE PRECISION array, dimension (NB)
The scalar factors of the elementary reflectors which
represent the orthogonal matrix P. See Further Details.
X (output) DOUBLE PRECISION array, dimension (LDX,NB)
The m-by-nb matrix X required to update the unreduced part
of A.
LDX (input) INTEGER
The leading dimension of the array X. LDX >= M.
Y (output) DOUBLE PRECISION array, dimension (LDY,NB)
The n-by-nb matrix Y required to update the unreduced part
of A.
LDY (input) INTEGER
The leading dimension of the array Y. LDY >= N.
Further Details
===============
The matrices Q and P are represented as products of elementary
reflectors:
Q = H(1) H(2) . . . H(nb) and P = G(1) G(2) . . . G(nb)
Each H(i) and G(i) has the form:
H(i) = I - tauq * v * v' and G(i) = I - taup * u * u'
where tauq and taup are real scalars, and v and u are real vectors.
If m >= n, v(1:i-1) = 0, v(i) = 1, and v(i:m) is stored on exit in
A(i:m,i); u(1:i) = 0, u(i+1) = 1, and u(i+1:n) is stored on exit in
A(i,i+1:n); tauq is stored in TAUQ(i) and taup in TAUP(i).
If m < n, v(1:i) = 0, v(i+1) = 1, and v(i+1:m) is stored on exit in
A(i+2:m,i); u(1:i-1) = 0, u(i) = 1, and u(i:n) is stored on exit in
A(i,i+1:n); tauq is stored in TAUQ(i) and taup in TAUP(i).
The elements of the vectors v and u together form the m-by-nb matrix
V and the nb-by-n matrix U' which are needed, with X and Y, to apply
the transformation to the unreduced part of the matrix, using a block
update of the form: A := A - V*Y' - X*U'.
The contents of A on exit are illustrated by the following examples
with nb = 2:
m = 6 and n = 5 (m > n): m = 5 and n = 6 (m < n):
( 1 1 u1 u1 u1 ) ( 1 u1 u1 u1 u1 u1 )
( v1 1 1 u2 u2 ) ( 1 1 u2 u2 u2 u2 )
( v1 v2 a a a ) ( v1 1 a a a a )
( v1 v2 a a a ) ( v1 v2 a a a a )
( v1 v2 a a a ) ( v1 v2 a a a a )
( v1 v2 a a a )
where a denotes an element of the original matrix which is unchanged,
vi denotes an element of the vector defining H(i), and ui an element
of the vector defining G(i).
=====================================================================
Quick return if possible
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--d__;
--e;
--tauq;
--taup;
x_dim1 = *ldx;
x_offset = 1 + x_dim1;
x -= x_offset;
y_dim1 = *ldy;
y_offset = 1 + y_dim1;
y -= y_offset;
/* Function Body */
if (*m <= 0 || *n <= 0) {
return 0;
}
if (*m >= *n) {
/* Reduce to upper bidiagonal form */
i__1 = *nb;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Update A(i:m,i) */
i__2 = *m - i__ + 1;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &a[i__ + a_dim1],
lda, &y[i__ + y_dim1], ldy, &c_b15, &a[i__ + i__ * a_dim1]
, &c__1);
i__2 = *m - i__ + 1;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &x[i__ + x_dim1],
ldx, &a[i__ * a_dim1 + 1], &c__1, &c_b15, &a[i__ + i__ *
a_dim1], &c__1);
/* Generate reflection Q(i) to annihilate A(i+1:m,i) */
i__2 = *m - i__ + 1;
/* Computing MIN */
i__3 = i__ + 1;
dlarfg_(&i__2, &a[i__ + i__ * a_dim1], &a[min(i__3,*m) + i__ *
a_dim1], &c__1, &tauq[i__]);
d__[i__] = a[i__ + i__ * a_dim1];
if (i__ < *n) {
a[i__ + i__ * a_dim1] = 1.;
/* Compute Y(i+1:n,i) */
i__2 = *m - i__ + 1;
i__3 = *n - i__;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &a[i__ + (i__ + 1) *
a_dim1], lda, &a[i__ + i__ * a_dim1], &c__1, &c_b29,
&y[i__ + 1 + i__ * y_dim1], &c__1);
i__2 = *m - i__ + 1;
i__3 = i__ - 1;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &a[i__ + a_dim1],
lda, &a[i__ + i__ * a_dim1], &c__1, &c_b29, &y[i__ *
y_dim1 + 1], &c__1);
i__2 = *n - i__;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &y[i__ + 1 +
y_dim1], ldy, &y[i__ * y_dim1 + 1], &c__1, &c_b15, &y[
i__ + 1 + i__ * y_dim1], &c__1);
i__2 = *m - i__ + 1;
i__3 = i__ - 1;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &x[i__ + x_dim1],
ldx, &a[i__ + i__ * a_dim1], &c__1, &c_b29, &y[i__ *
y_dim1 + 1], &c__1);
i__2 = i__ - 1;
i__3 = *n - i__;
dgemv_("Transpose", &i__2, &i__3, &c_b151, &a[(i__ + 1) *
a_dim1 + 1], lda, &y[i__ * y_dim1 + 1], &c__1, &c_b15,
&y[i__ + 1 + i__ * y_dim1], &c__1);
i__2 = *n - i__;
dscal_(&i__2, &tauq[i__], &y[i__ + 1 + i__ * y_dim1], &c__1);
/* Update A(i,i+1:n) */
i__2 = *n - i__;
dgemv_("No transpose", &i__2, &i__, &c_b151, &y[i__ + 1 +
y_dim1], ldy, &a[i__ + a_dim1], lda, &c_b15, &a[i__ +
(i__ + 1) * a_dim1], lda);
i__2 = i__ - 1;
i__3 = *n - i__;
dgemv_("Transpose", &i__2, &i__3, &c_b151, &a[(i__ + 1) *
a_dim1 + 1], lda, &x[i__ + x_dim1], ldx, &c_b15, &a[
i__ + (i__ + 1) * a_dim1], lda);
/* Generate reflection P(i) to annihilate A(i,i+2:n) */
i__2 = *n - i__;
/* Computing MIN */
i__3 = i__ + 2;
dlarfg_(&i__2, &a[i__ + (i__ + 1) * a_dim1], &a[i__ + min(
i__3,*n) * a_dim1], lda, &taup[i__]);
e[i__] = a[i__ + (i__ + 1) * a_dim1];
a[i__ + (i__ + 1) * a_dim1] = 1.;
/* Compute X(i+1:m,i) */
i__2 = *m - i__;
i__3 = *n - i__;
dgemv_("No transpose", &i__2, &i__3, &c_b15, &a[i__ + 1 + (
i__ + 1) * a_dim1], lda, &a[i__ + (i__ + 1) * a_dim1],
lda, &c_b29, &x[i__ + 1 + i__ * x_dim1], &c__1);
i__2 = *n - i__;
dgemv_("Transpose", &i__2, &i__, &c_b15, &y[i__ + 1 + y_dim1],
ldy, &a[i__ + (i__ + 1) * a_dim1], lda, &c_b29, &x[
i__ * x_dim1 + 1], &c__1);
i__2 = *m - i__;
dgemv_("No transpose", &i__2, &i__, &c_b151, &a[i__ + 1 +
a_dim1], lda, &x[i__ * x_dim1 + 1], &c__1, &c_b15, &x[
i__ + 1 + i__ * x_dim1], &c__1);
i__2 = i__ - 1;
i__3 = *n - i__;
dgemv_("No transpose", &i__2, &i__3, &c_b15, &a[(i__ + 1) *
a_dim1 + 1], lda, &a[i__ + (i__ + 1) * a_dim1], lda, &
c_b29, &x[i__ * x_dim1 + 1], &c__1);
i__2 = *m - i__;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &x[i__ + 1 +
x_dim1], ldx, &x[i__ * x_dim1 + 1], &c__1, &c_b15, &x[
i__ + 1 + i__ * x_dim1], &c__1);
i__2 = *m - i__;
dscal_(&i__2, &taup[i__], &x[i__ + 1 + i__ * x_dim1], &c__1);
}
/* L10: */
}
} else {
/* Reduce to lower bidiagonal form */
i__1 = *nb;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Update A(i,i:n) */
i__2 = *n - i__ + 1;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &y[i__ + y_dim1],
ldy, &a[i__ + a_dim1], lda, &c_b15, &a[i__ + i__ * a_dim1]
, lda);
i__2 = i__ - 1;
i__3 = *n - i__ + 1;
dgemv_("Transpose", &i__2, &i__3, &c_b151, &a[i__ * a_dim1 + 1],
lda, &x[i__ + x_dim1], ldx, &c_b15, &a[i__ + i__ * a_dim1]
, lda);
/* Generate reflection P(i) to annihilate A(i,i+1:n) */
i__2 = *n - i__ + 1;
/* Computing MIN */
i__3 = i__ + 1;
dlarfg_(&i__2, &a[i__ + i__ * a_dim1], &a[i__ + min(i__3,*n) *
a_dim1], lda, &taup[i__]);
d__[i__] = a[i__ + i__ * a_dim1];
if (i__ < *m) {
a[i__ + i__ * a_dim1] = 1.;
/* Compute X(i+1:m,i) */
i__2 = *m - i__;
i__3 = *n - i__ + 1;
dgemv_("No transpose", &i__2, &i__3, &c_b15, &a[i__ + 1 + i__
* a_dim1], lda, &a[i__ + i__ * a_dim1], lda, &c_b29, &
x[i__ + 1 + i__ * x_dim1], &c__1);
i__2 = *n - i__ + 1;
i__3 = i__ - 1;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &y[i__ + y_dim1],
ldy, &a[i__ + i__ * a_dim1], lda, &c_b29, &x[i__ *
x_dim1 + 1], &c__1);
i__2 = *m - i__;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &a[i__ + 1 +
a_dim1], lda, &x[i__ * x_dim1 + 1], &c__1, &c_b15, &x[
i__ + 1 + i__ * x_dim1], &c__1);
i__2 = i__ - 1;
i__3 = *n - i__ + 1;
dgemv_("No transpose", &i__2, &i__3, &c_b15, &a[i__ * a_dim1
+ 1], lda, &a[i__ + i__ * a_dim1], lda, &c_b29, &x[
i__ * x_dim1 + 1], &c__1);
i__2 = *m - i__;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &x[i__ + 1 +
x_dim1], ldx, &x[i__ * x_dim1 + 1], &c__1, &c_b15, &x[
i__ + 1 + i__ * x_dim1], &c__1);
i__2 = *m - i__;
dscal_(&i__2, &taup[i__], &x[i__ + 1 + i__ * x_dim1], &c__1);
/* Update A(i+1:m,i) */
i__2 = *m - i__;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &a[i__ + 1 +
a_dim1], lda, &y[i__ + y_dim1], ldy, &c_b15, &a[i__ +
1 + i__ * a_dim1], &c__1);
i__2 = *m - i__;
dgemv_("No transpose", &i__2, &i__, &c_b151, &x[i__ + 1 +
x_dim1], ldx, &a[i__ * a_dim1 + 1], &c__1, &c_b15, &a[
i__ + 1 + i__ * a_dim1], &c__1);
/* Generate reflection Q(i) to annihilate A(i+2:m,i) */
i__2 = *m - i__;
/* Computing MIN */
i__3 = i__ + 2;
dlarfg_(&i__2, &a[i__ + 1 + i__ * a_dim1], &a[min(i__3,*m) +
i__ * a_dim1], &c__1, &tauq[i__]);
e[i__] = a[i__ + 1 + i__ * a_dim1];
a[i__ + 1 + i__ * a_dim1] = 1.;
/* Compute Y(i+1:n,i) */
i__2 = *m - i__;
i__3 = *n - i__;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &a[i__ + 1 + (i__ +
1) * a_dim1], lda, &a[i__ + 1 + i__ * a_dim1], &c__1,
&c_b29, &y[i__ + 1 + i__ * y_dim1], &c__1);
i__2 = *m - i__;
i__3 = i__ - 1;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &a[i__ + 1 + a_dim1]
, lda, &a[i__ + 1 + i__ * a_dim1], &c__1, &c_b29, &y[
i__ * y_dim1 + 1], &c__1);
i__2 = *n - i__;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &y[i__ + 1 +
y_dim1], ldy, &y[i__ * y_dim1 + 1], &c__1, &c_b15, &y[
i__ + 1 + i__ * y_dim1], &c__1);
i__2 = *m - i__;
dgemv_("Transpose", &i__2, &i__, &c_b15, &x[i__ + 1 + x_dim1],
ldx, &a[i__ + 1 + i__ * a_dim1], &c__1, &c_b29, &y[
i__ * y_dim1 + 1], &c__1);
i__2 = *n - i__;
dgemv_("Transpose", &i__, &i__2, &c_b151, &a[(i__ + 1) *
a_dim1 + 1], lda, &y[i__ * y_dim1 + 1], &c__1, &c_b15,
&y[i__ + 1 + i__ * y_dim1], &c__1);
i__2 = *n - i__;
dscal_(&i__2, &tauq[i__], &y[i__ + 1 + i__ * y_dim1], &c__1);
}
/* L20: */
}
}
return 0;
/* End of DLABRD */
} /* dlabrd_ */
/* Subroutine */ int dlacpy_(char *uplo, integer *m, integer *n, doublereal *
a, integer *lda, doublereal *b, integer *ldb)
{
/* System generated locals */
integer a_dim1, a_offset, b_dim1, b_offset, i__1, i__2;
/* Local variables */
static integer i__, j;
extern logical lsame_(char *, char *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLACPY copies all or part of a two-dimensional matrix A to another
matrix B.
Arguments
=========
UPLO (input) CHARACTER*1
Specifies the part of the matrix A to be copied to B.
= 'U': Upper triangular part
= 'L': Lower triangular part
Otherwise: All of the matrix A
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
A (input) DOUBLE PRECISION array, dimension (LDA,N)
The m by n matrix A. If UPLO = 'U', only the upper triangle
or trapezoid is accessed; if UPLO = 'L', only the lower
triangle or trapezoid is accessed.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
B (output) DOUBLE PRECISION array, dimension (LDB,N)
On exit, B = A in the locations specified by UPLO.
LDB (input) INTEGER
The leading dimension of the array B. LDB >= max(1,M).
=====================================================================
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
/* Function Body */
if (lsame_(uplo, "U")) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = min(j,*m);
for (i__ = 1; i__ <= i__2; ++i__) {
b[i__ + j * b_dim1] = a[i__ + j * a_dim1];
/* L10: */
}
/* L20: */
}
} else if (lsame_(uplo, "L")) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = j; i__ <= i__2; ++i__) {
b[i__ + j * b_dim1] = a[i__ + j * a_dim1];
/* L30: */
}
/* L40: */
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
b[i__ + j * b_dim1] = a[i__ + j * a_dim1];
/* L50: */
}
/* L60: */
}
}
return 0;
/* End of DLACPY */
} /* dlacpy_ */
/* Subroutine */ int dladiv_(doublereal *a, doublereal *b, doublereal *c__,
doublereal *d__, doublereal *p, doublereal *q)
{
static doublereal e, f;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLADIV performs complex division in real arithmetic
a + i*b
p + i*q = ---------
c + i*d
The algorithm is due to Robert L. Smith and can be found
in D. Knuth, The art of Computer Programming, Vol.2, p.195
Arguments
=========
A (input) DOUBLE PRECISION
B (input) DOUBLE PRECISION
C (input) DOUBLE PRECISION
D (input) DOUBLE PRECISION
The scalars a, b, c, and d in the above expression.
P (output) DOUBLE PRECISION
Q (output) DOUBLE PRECISION
The scalars p and q in the above expression.
=====================================================================
*/
if (abs(*d__) < abs(*c__)) {
e = *d__ / *c__;
f = *c__ + *d__ * e;
*p = (*a + *b * e) / f;
*q = (*b - *a * e) / f;
} else {
e = *c__ / *d__;
f = *d__ + *c__ * e;
*p = (*b + *a * e) / f;
*q = (-(*a) + *b * e) / f;
}
return 0;
/* End of DLADIV */
} /* dladiv_ */
/* Subroutine */ int dlae2_(doublereal *a, doublereal *b, doublereal *c__,
doublereal *rt1, doublereal *rt2)
{
/* System generated locals */
doublereal d__1;
/* Local variables */
static doublereal ab, df, tb, sm, rt, adf, acmn, acmx;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAE2 computes the eigenvalues of a 2-by-2 symmetric matrix
[ A B ]
[ B C ].
On return, RT1 is the eigenvalue of larger absolute value, and RT2
is the eigenvalue of smaller absolute value.
Arguments
=========
A (input) DOUBLE PRECISION
The (1,1) element of the 2-by-2 matrix.
B (input) DOUBLE PRECISION
The (1,2) and (2,1) elements of the 2-by-2 matrix.
C (input) DOUBLE PRECISION
The (2,2) element of the 2-by-2 matrix.
RT1 (output) DOUBLE PRECISION
The eigenvalue of larger absolute value.
RT2 (output) DOUBLE PRECISION
The eigenvalue of smaller absolute value.
Further Details
===============
RT1 is accurate to a few ulps barring over/underflow.
RT2 may be inaccurate if there is massive cancellation in the
determinant A*C-B*B; higher precision or correctly rounded or
correctly truncated arithmetic would be needed to compute RT2
accurately in all cases.
Overflow is possible only if RT1 is within a factor of 5 of overflow.
Underflow is harmless if the input data is 0 or exceeds
underflow_threshold / macheps.
=====================================================================
Compute the eigenvalues
*/
sm = *a + *c__;
df = *a - *c__;
adf = abs(df);
tb = *b + *b;
ab = abs(tb);
if (abs(*a) > abs(*c__)) {
acmx = *a;
acmn = *c__;
} else {
acmx = *c__;
acmn = *a;
}
if (adf > ab) {
/* Computing 2nd power */
d__1 = ab / adf;
rt = adf * sqrt(d__1 * d__1 + 1.);
} else if (adf < ab) {
/* Computing 2nd power */
d__1 = adf / ab;
rt = ab * sqrt(d__1 * d__1 + 1.);
} else {
/* Includes case AB=ADF=0 */
rt = ab * sqrt(2.);
}
if (sm < 0.) {
*rt1 = (sm - rt) * .5;
/*
Order of execution important.
To get fully accurate smaller eigenvalue,
next line needs to be executed in higher precision.
*/
*rt2 = acmx / *rt1 * acmn - *b / *rt1 * *b;
} else if (sm > 0.) {
*rt1 = (sm + rt) * .5;
/*
Order of execution important.
To get fully accurate smaller eigenvalue,
next line needs to be executed in higher precision.
*/
*rt2 = acmx / *rt1 * acmn - *b / *rt1 * *b;
} else {
/* Includes case RT1 = RT2 = 0 */
*rt1 = rt * .5;
*rt2 = rt * -.5;
}
return 0;
/* End of DLAE2 */
} /* dlae2_ */
/* Subroutine */ int dlaed0_(integer *icompq, integer *qsiz, integer *n,
doublereal *d__, doublereal *e, doublereal *q, integer *ldq,
doublereal *qstore, integer *ldqs, doublereal *work, integer *iwork,
integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, qstore_dim1, qstore_offset, i__1, i__2;
doublereal d__1;
/* Local variables */
static integer i__, j, k, iq, lgn, msd2, smm1, spm1, spm2;
static doublereal temp;
static integer curr;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static integer iperm;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static integer indxq, iwrem;
extern /* Subroutine */ int dlaed1_(integer *, doublereal *, doublereal *,
integer *, integer *, doublereal *, integer *, doublereal *,
integer *, integer *);
static integer iqptr;
extern /* Subroutine */ int dlaed7_(integer *, integer *, integer *,
integer *, integer *, integer *, doublereal *, doublereal *,
integer *, integer *, doublereal *, integer *, doublereal *,
integer *, integer *, integer *, integer *, integer *, doublereal
*, doublereal *, integer *, integer *);
static integer tlvls;
extern /* Subroutine */ int dlacpy_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *);
static integer igivcl;
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static integer igivnm, submat, curprb, subpbs, igivpt;
extern /* Subroutine */ int dsteqr_(char *, integer *, doublereal *,
doublereal *, doublereal *, integer *, doublereal *, integer *);
static integer curlvl, matsiz, iprmpt, smlsiz;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAED0 computes all eigenvalues and corresponding eigenvectors of a
symmetric tridiagonal matrix using the divide and conquer method.
Arguments
=========
ICOMPQ (input) INTEGER
= 0: Compute eigenvalues only.
= 1: Compute eigenvectors of original dense symmetric matrix
also. On entry, Q contains the orthogonal matrix used
to reduce the original matrix to tridiagonal form.
= 2: Compute eigenvalues and eigenvectors of tridiagonal
matrix.
QSIZ (input) INTEGER
The dimension of the orthogonal matrix used to reduce
the full matrix to tridiagonal form. QSIZ >= N if ICOMPQ = 1.
N (input) INTEGER
The dimension of the symmetric tridiagonal matrix. N >= 0.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, the main diagonal of the tridiagonal matrix.
On exit, its eigenvalues.
E (input) DOUBLE PRECISION array, dimension (N-1)
The off-diagonal elements of the tridiagonal matrix.
On exit, E has been destroyed.
Q (input/output) DOUBLE PRECISION array, dimension (LDQ, N)
On entry, Q must contain an N-by-N orthogonal matrix.
If ICOMPQ = 0 Q is not referenced.
If ICOMPQ = 1 On entry, Q is a subset of the columns of the
orthogonal matrix used to reduce the full
matrix to tridiagonal form corresponding to
the subset of the full matrix which is being
decomposed at this time.
If ICOMPQ = 2 On entry, Q will be the identity matrix.
On exit, Q contains the eigenvectors of the
tridiagonal matrix.
LDQ (input) INTEGER
The leading dimension of the array Q. If eigenvectors are
desired, then LDQ >= max(1,N). In any case, LDQ >= 1.
QSTORE (workspace) DOUBLE PRECISION array, dimension (LDQS, N)
Referenced only when ICOMPQ = 1. Used to store parts of
the eigenvector matrix when the updating matrix multiplies
take place.
LDQS (input) INTEGER
The leading dimension of the array QSTORE. If ICOMPQ = 1,
then LDQS >= max(1,N). In any case, LDQS >= 1.
WORK (workspace) DOUBLE PRECISION array,
If ICOMPQ = 0 or 1, the dimension of WORK must be at least
1 + 3*N + 2*N*lg N + 2*N**2
( lg( N ) = smallest integer k
such that 2^k >= N )
If ICOMPQ = 2, the dimension of WORK must be at least
4*N + N**2.
IWORK (workspace) INTEGER array,
If ICOMPQ = 0 or 1, the dimension of IWORK must be at least
6 + 6*N + 5*N*lg N.
( lg( N ) = smallest integer k
such that 2^k >= N )
If ICOMPQ = 2, the dimension of IWORK must be at least
3 + 5*N.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: The algorithm failed to compute an eigenvalue while
working on the submatrix lying in rows and columns
INFO/(N+1) through mod(INFO,N+1).
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--e;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
qstore_dim1 = *ldqs;
qstore_offset = 1 + qstore_dim1;
qstore -= qstore_offset;
--work;
--iwork;
/* Function Body */
*info = 0;
if (*icompq < 0 || *icompq > 2) {
*info = -1;
} else if (*icompq == 1 && *qsiz < max(0,*n)) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*ldq < max(1,*n)) {
*info = -7;
} else if (*ldqs < max(1,*n)) {
*info = -9;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAED0", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
smlsiz = ilaenv_(&c__9, "DLAED0", " ", &c__0, &c__0, &c__0, &c__0, (
ftnlen)6, (ftnlen)1);
/*
Determine the size and placement of the submatrices, and save in
the leading elements of IWORK.
*/
iwork[1] = *n;
subpbs = 1;
tlvls = 0;
L10:
if (iwork[subpbs] > smlsiz) {
for (j = subpbs; j >= 1; --j) {
iwork[j * 2] = (iwork[j] + 1) / 2;
iwork[(j << 1) - 1] = iwork[j] / 2;
/* L20: */
}
++tlvls;
subpbs <<= 1;
goto L10;
}
i__1 = subpbs;
for (j = 2; j <= i__1; ++j) {
iwork[j] += iwork[j - 1];
/* L30: */
}
/*
Divide the matrix into SUBPBS submatrices of size at most SMLSIZ+1
using rank-1 modifications (cuts).
*/
spm1 = subpbs - 1;
i__1 = spm1;
for (i__ = 1; i__ <= i__1; ++i__) {
submat = iwork[i__] + 1;
smm1 = submat - 1;
d__[smm1] -= (d__1 = e[smm1], abs(d__1));
d__[submat] -= (d__1 = e[smm1], abs(d__1));
/* L40: */
}
indxq = (*n << 2) + 3;
if (*icompq != 2) {
/*
Set up workspaces for eigenvalues only/accumulate new vectors
routine
*/
temp = log((doublereal) (*n)) / log(2.);
lgn = (integer) temp;
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
iprmpt = indxq + *n + 1;
iperm = iprmpt + *n * lgn;
iqptr = iperm + *n * lgn;
igivpt = iqptr + *n + 2;
igivcl = igivpt + *n * lgn;
igivnm = 1;
iq = igivnm + (*n << 1) * lgn;
/* Computing 2nd power */
i__1 = *n;
iwrem = iq + i__1 * i__1 + 1;
/* Initialize pointers */
i__1 = subpbs;
for (i__ = 0; i__ <= i__1; ++i__) {
iwork[iprmpt + i__] = 1;
iwork[igivpt + i__] = 1;
/* L50: */
}
iwork[iqptr] = 1;
}
/*
Solve each submatrix eigenproblem at the bottom of the divide and
conquer tree.
*/
curr = 0;
i__1 = spm1;
for (i__ = 0; i__ <= i__1; ++i__) {
if (i__ == 0) {
submat = 1;
matsiz = iwork[1];
} else {
submat = iwork[i__] + 1;
matsiz = iwork[i__ + 1] - iwork[i__];
}
if (*icompq == 2) {
dsteqr_("I", &matsiz, &d__[submat], &e[submat], &q[submat +
submat * q_dim1], ldq, &work[1], info);
if (*info != 0) {
goto L130;
}
} else {
dsteqr_("I", &matsiz, &d__[submat], &e[submat], &work[iq - 1 +
iwork[iqptr + curr]], &matsiz, &work[1], info);
if (*info != 0) {
goto L130;
}
if (*icompq == 1) {
dgemm_("N", "N", qsiz, &matsiz, &matsiz, &c_b15, &q[submat *
q_dim1 + 1], ldq, &work[iq - 1 + iwork[iqptr + curr]],
&matsiz, &c_b29, &qstore[submat * qstore_dim1 + 1],
ldqs);
}
/* Computing 2nd power */
i__2 = matsiz;
iwork[iqptr + curr + 1] = iwork[iqptr + curr] + i__2 * i__2;
++curr;
}
k = 1;
i__2 = iwork[i__ + 1];
for (j = submat; j <= i__2; ++j) {
iwork[indxq + j] = k;
++k;
/* L60: */
}
/* L70: */
}
/*
Successively merge eigensystems of adjacent submatrices
into eigensystem for the corresponding larger matrix.
while ( SUBPBS > 1 )
*/
curlvl = 1;
L80:
if (subpbs > 1) {
spm2 = subpbs - 2;
i__1 = spm2;
for (i__ = 0; i__ <= i__1; i__ += 2) {
if (i__ == 0) {
submat = 1;
matsiz = iwork[2];
msd2 = iwork[1];
curprb = 0;
} else {
submat = iwork[i__] + 1;
matsiz = iwork[i__ + 2] - iwork[i__];
msd2 = matsiz / 2;
++curprb;
}
/*
Merge lower order eigensystems (of size MSD2 and MATSIZ - MSD2)
into an eigensystem of size MATSIZ.
DLAED1 is used only for the full eigensystem of a tridiagonal
matrix.
DLAED7 handles the cases in which eigenvalues only or eigenvalues
and eigenvectors of a full symmetric matrix (which was reduced to
tridiagonal form) are desired.
*/
if (*icompq == 2) {
dlaed1_(&matsiz, &d__[submat], &q[submat + submat * q_dim1],
ldq, &iwork[indxq + submat], &e[submat + msd2 - 1], &
msd2, &work[1], &iwork[subpbs + 1], info);
} else {
dlaed7_(icompq, &matsiz, qsiz, &tlvls, &curlvl, &curprb, &d__[
submat], &qstore[submat * qstore_dim1 + 1], ldqs, &
iwork[indxq + submat], &e[submat + msd2 - 1], &msd2, &
work[iq], &iwork[iqptr], &iwork[iprmpt], &iwork[iperm]
, &iwork[igivpt], &iwork[igivcl], &work[igivnm], &
work[iwrem], &iwork[subpbs + 1], info);
}
if (*info != 0) {
goto L130;
}
iwork[i__ / 2 + 1] = iwork[i__ + 2];
/* L90: */
}
subpbs /= 2;
++curlvl;
goto L80;
}
/*
end while
Re-merge the eigenvalues/vectors which were deflated at the final
merge step.
*/
if (*icompq == 1) {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
j = iwork[indxq + i__];
work[i__] = d__[j];
dcopy_(qsiz, &qstore[j * qstore_dim1 + 1], &c__1, &q[i__ * q_dim1
+ 1], &c__1);
/* L100: */
}
dcopy_(n, &work[1], &c__1, &d__[1], &c__1);
} else if (*icompq == 2) {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
j = iwork[indxq + i__];
work[i__] = d__[j];
dcopy_(n, &q[j * q_dim1 + 1], &c__1, &work[*n * i__ + 1], &c__1);
/* L110: */
}
dcopy_(n, &work[1], &c__1, &d__[1], &c__1);
dlacpy_("A", n, n, &work[*n + 1], n, &q[q_offset], ldq);
} else {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
j = iwork[indxq + i__];
work[i__] = d__[j];
/* L120: */
}
dcopy_(n, &work[1], &c__1, &d__[1], &c__1);
}
goto L140;
L130:
*info = submat * (*n + 1) + submat + matsiz - 1;
L140:
return 0;
/* End of DLAED0 */
} /* dlaed0_ */
/* Subroutine */ int dlaed1_(integer *n, doublereal *d__, doublereal *q,
integer *ldq, integer *indxq, doublereal *rho, integer *cutpnt,
doublereal *work, integer *iwork, integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, i__1, i__2;
/* Local variables */
static integer i__, k, n1, n2, is, iw, iz, iq2, zpp1, indx, indxc;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static integer indxp;
extern /* Subroutine */ int dlaed2_(integer *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *, integer *,
integer *, integer *, integer *, integer *), dlaed3_(integer *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, doublereal *, doublereal *, integer *, integer *,
doublereal *, doublereal *, integer *);
static integer idlmda;
extern /* Subroutine */ int dlamrg_(integer *, integer *, doublereal *,
integer *, integer *, integer *), xerbla_(char *, integer *);
static integer coltyp;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAED1 computes the updated eigensystem of a diagonal
matrix after modification by a rank-one symmetric matrix. This
routine is used only for the eigenproblem which requires all
eigenvalues and eigenvectors of a tridiagonal matrix. DLAED7 handles
the case in which eigenvalues only or eigenvalues and eigenvectors
of a full symmetric matrix (which was reduced to tridiagonal form)
are desired.
T = Q(in) ( D(in) + RHO * Z*Z' ) Q'(in) = Q(out) * D(out) * Q'(out)
where Z = Q'u, u is a vector of length N with ones in the
CUTPNT and CUTPNT + 1 th elements and zeros elsewhere.
The eigenvectors of the original matrix are stored in Q, and the
eigenvalues are in D. The algorithm consists of three stages:
The first stage consists of deflating the size of the problem
when there are multiple eigenvalues or if there is a zero in
the Z vector. For each such occurence the dimension of the
secular equation problem is reduced by one. This stage is
performed by the routine DLAED2.
The second stage consists of calculating the updated
eigenvalues. This is done by finding the roots of the secular
equation via the routine DLAED4 (as called by DLAED3).
This routine also calculates the eigenvectors of the current
problem.
The final stage consists of computing the updated eigenvectors
directly using the updated eigenvalues. The eigenvectors for
the current problem are multiplied with the eigenvectors from
the overall problem.
Arguments
=========
N (input) INTEGER
The dimension of the symmetric tridiagonal matrix. N >= 0.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, the eigenvalues of the rank-1-perturbed matrix.
On exit, the eigenvalues of the repaired matrix.
Q (input/output) DOUBLE PRECISION array, dimension (LDQ,N)
On entry, the eigenvectors of the rank-1-perturbed matrix.
On exit, the eigenvectors of the repaired tridiagonal matrix.
LDQ (input) INTEGER
The leading dimension of the array Q. LDQ >= max(1,N).
INDXQ (input/output) INTEGER array, dimension (N)
On entry, the permutation which separately sorts the two
subproblems in D into ascending order.
On exit, the permutation which will reintegrate the
subproblems back into sorted order,
i.e. D( INDXQ( I = 1, N ) ) will be in ascending order.
RHO (input) DOUBLE PRECISION
The subdiagonal entry used to create the rank-1 modification.
CUTPNT (input) INTEGER
The location of the last eigenvalue in the leading sub-matrix.
min(1,N) <= CUTPNT <= N/2.
WORK (workspace) DOUBLE PRECISION array, dimension (4*N + N**2)
IWORK (workspace) INTEGER array, dimension (4*N)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, an eigenvalue did not converge
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
Modified by Francoise Tisseur, University of Tennessee.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
--indxq;
--work;
--iwork;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -1;
} else if (*ldq < max(1,*n)) {
*info = -4;
} else /* if(complicated condition) */ {
/* Computing MIN */
i__1 = 1, i__2 = *n / 2;
if (min(i__1,i__2) > *cutpnt || *n / 2 < *cutpnt) {
*info = -7;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAED1", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/*
The following values are integer pointers which indicate
the portion of the workspace
used by a particular array in DLAED2 and DLAED3.
*/
iz = 1;
idlmda = iz + *n;
iw = idlmda + *n;
iq2 = iw + *n;
indx = 1;
indxc = indx + *n;
coltyp = indxc + *n;
indxp = coltyp + *n;
/*
Form the z-vector which consists of the last row of Q_1 and the
first row of Q_2.
*/
dcopy_(cutpnt, &q[*cutpnt + q_dim1], ldq, &work[iz], &c__1);
zpp1 = *cutpnt + 1;
i__1 = *n - *cutpnt;
dcopy_(&i__1, &q[zpp1 + zpp1 * q_dim1], ldq, &work[iz + *cutpnt], &c__1);
/* Deflate eigenvalues. */
dlaed2_(&k, n, cutpnt, &d__[1], &q[q_offset], ldq, &indxq[1], rho, &work[
iz], &work[idlmda], &work[iw], &work[iq2], &iwork[indx], &iwork[
indxc], &iwork[indxp], &iwork[coltyp], info);
if (*info != 0) {
goto L20;
}
/* Solve Secular Equation. */
if (k != 0) {
is = (iwork[coltyp] + iwork[coltyp + 1]) * *cutpnt + (iwork[coltyp +
1] + iwork[coltyp + 2]) * (*n - *cutpnt) + iq2;
dlaed3_(&k, n, cutpnt, &d__[1], &q[q_offset], ldq, rho, &work[idlmda],
&work[iq2], &iwork[indxc], &iwork[coltyp], &work[iw], &work[
is], info);
if (*info != 0) {
goto L20;
}
/* Prepare the INDXQ sorting permutation. */
n1 = k;
n2 = *n - k;
dlamrg_(&n1, &n2, &d__[1], &c__1, &c_n1, &indxq[1]);
} else {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
indxq[i__] = i__;
/* L10: */
}
}
L20:
return 0;
/* End of DLAED1 */
} /* dlaed1_ */
/* Subroutine */ int dlaed2_(integer *k, integer *n, integer *n1, doublereal *
d__, doublereal *q, integer *ldq, integer *indxq, doublereal *rho,
doublereal *z__, doublereal *dlamda, doublereal *w, doublereal *q2,
integer *indx, integer *indxc, integer *indxp, integer *coltyp,
integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, i__1, i__2;
doublereal d__1, d__2, d__3, d__4;
/* Local variables */
static doublereal c__;
static integer i__, j;
static doublereal s, t;
static integer k2, n2, ct, nj, pj, js, iq1, iq2, n1p1;
static doublereal eps, tau, tol;
static integer psm[4], imax, jmax;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *);
static integer ctot[4];
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *), dcopy_(integer *, doublereal *, integer *, doublereal
*, integer *);
extern integer idamax_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dlamrg_(integer *, integer *, doublereal *,
integer *, integer *, integer *), dlacpy_(char *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAED2 merges the two sets of eigenvalues together into a single
sorted set. Then it tries to deflate the size of the problem.
There are two ways in which deflation can occur: when two or more
eigenvalues are close together or if there is a tiny entry in the
Z vector. For each such occurrence the order of the related secular
equation problem is reduced by one.
Arguments
=========
K (output) INTEGER
The number of non-deflated eigenvalues, and the order of the
related secular equation. 0 <= K <=N.
N (input) INTEGER
The dimension of the symmetric tridiagonal matrix. N >= 0.
N1 (input) INTEGER
The location of the last eigenvalue in the leading sub-matrix.
min(1,N) <= N1 <= N/2.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, D contains the eigenvalues of the two submatrices to
be combined.
On exit, D contains the trailing (N-K) updated eigenvalues
(those which were deflated) sorted into increasing order.
Q (input/output) DOUBLE PRECISION array, dimension (LDQ, N)
On entry, Q contains the eigenvectors of two submatrices in
the two square blocks with corners at (1,1), (N1,N1)
and (N1+1, N1+1), (N,N).
On exit, Q contains the trailing (N-K) updated eigenvectors
(those which were deflated) in its last N-K columns.
LDQ (input) INTEGER
The leading dimension of the array Q. LDQ >= max(1,N).
INDXQ (input/output) INTEGER array, dimension (N)
The permutation which separately sorts the two sub-problems
in D into ascending order. Note that elements in the second
half of this permutation must first have N1 added to their
values. Destroyed on exit.
RHO (input/output) DOUBLE PRECISION
On entry, the off-diagonal element associated with the rank-1
cut which originally split the two submatrices which are now
being recombined.
On exit, RHO has been modified to the value required by
DLAED3.
Z (input) DOUBLE PRECISION array, dimension (N)
On entry, Z contains the updating vector (the last
row of the first sub-eigenvector matrix and the first row of
the second sub-eigenvector matrix).
On exit, the contents of Z have been destroyed by the updating
process.
DLAMDA (output) DOUBLE PRECISION array, dimension (N)
A copy of the first K eigenvalues which will be used by
DLAED3 to form the secular equation.
W (output) DOUBLE PRECISION array, dimension (N)
The first k values of the final deflation-altered z-vector
which will be passed to DLAED3.
Q2 (output) DOUBLE PRECISION array, dimension (N1**2+(N-N1)**2)
A copy of the first K eigenvectors which will be used by
DLAED3 in a matrix multiply (DGEMM) to solve for the new
eigenvectors.
INDX (workspace) INTEGER array, dimension (N)
The permutation used to sort the contents of DLAMDA into
ascending order.
INDXC (output) INTEGER array, dimension (N)
The permutation used to arrange the columns of the deflated
Q matrix into three groups: the first group contains non-zero
elements only at and above N1, the second contains
non-zero elements only below N1, and the third is dense.
INDXP (workspace) INTEGER array, dimension (N)
The permutation used to place deflated values of D at the end
of the array. INDXP(1:K) points to the nondeflated D-values
and INDXP(K+1:N) points to the deflated eigenvalues.
COLTYP (workspace/output) INTEGER array, dimension (N)
During execution, a label which will indicate which of the
following types a column in the Q2 matrix is:
1 : non-zero in the upper half only;
2 : dense;
3 : non-zero in the lower half only;
4 : deflated.
On exit, COLTYP(i) is the number of columns of type i,
for i=1 to 4 only.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
Modified by Francoise Tisseur, University of Tennessee.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
--indxq;
--z__;
--dlamda;
--w;
--q2;
--indx;
--indxc;
--indxp;
--coltyp;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -2;
} else if (*ldq < max(1,*n)) {
*info = -6;
} else /* if(complicated condition) */ {
/* Computing MIN */
i__1 = 1, i__2 = *n / 2;
if (min(i__1,i__2) > *n1 || *n / 2 < *n1) {
*info = -3;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAED2", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
n2 = *n - *n1;
n1p1 = *n1 + 1;
if (*rho < 0.) {
dscal_(&n2, &c_b151, &z__[n1p1], &c__1);
}
/*
Normalize z so that norm(z) = 1. Since z is the concatenation of
two normalized vectors, norm2(z) = sqrt(2).
*/
t = 1. / sqrt(2.);
dscal_(n, &t, &z__[1], &c__1);
/* RHO = ABS( norm(z)**2 * RHO ) */
*rho = (d__1 = *rho * 2., abs(d__1));
/* Sort the eigenvalues into increasing order */
i__1 = *n;
for (i__ = n1p1; i__ <= i__1; ++i__) {
indxq[i__] += *n1;
/* L10: */
}
/* re-integrate the deflated parts from the last pass */
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
dlamda[i__] = d__[indxq[i__]];
/* L20: */
}
dlamrg_(n1, &n2, &dlamda[1], &c__1, &c__1, &indxc[1]);
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
indx[i__] = indxq[indxc[i__]];
/* L30: */
}
/* Calculate the allowable deflation tolerance */
imax = idamax_(n, &z__[1], &c__1);
jmax = idamax_(n, &d__[1], &c__1);
eps = EPSILON;
/* Computing MAX */
d__3 = (d__1 = d__[jmax], abs(d__1)), d__4 = (d__2 = z__[imax], abs(d__2))
;
tol = eps * 8. * max(d__3,d__4);
/*
If the rank-1 modifier is small enough, no more needs to be done
except to reorganize Q so that its columns correspond with the
elements in D.
*/
if (*rho * (d__1 = z__[imax], abs(d__1)) <= tol) {
*k = 0;
iq2 = 1;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__ = indx[j];
dcopy_(n, &q[i__ * q_dim1 + 1], &c__1, &q2[iq2], &c__1);
dlamda[j] = d__[i__];
iq2 += *n;
/* L40: */
}
dlacpy_("A", n, n, &q2[1], n, &q[q_offset], ldq);
dcopy_(n, &dlamda[1], &c__1, &d__[1], &c__1);
goto L190;
}
/*
If there are multiple eigenvalues then the problem deflates. Here
the number of equal eigenvalues are found. As each equal
eigenvalue is found, an elementary reflector is computed to rotate
the corresponding eigensubspace so that the corresponding
components of Z are zero in this new basis.
*/
i__1 = *n1;
for (i__ = 1; i__ <= i__1; ++i__) {
coltyp[i__] = 1;
/* L50: */
}
i__1 = *n;
for (i__ = n1p1; i__ <= i__1; ++i__) {
coltyp[i__] = 3;
/* L60: */
}
*k = 0;
k2 = *n + 1;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
nj = indx[j];
if (*rho * (d__1 = z__[nj], abs(d__1)) <= tol) {
/* Deflate due to small z component. */
--k2;
coltyp[nj] = 4;
indxp[k2] = nj;
if (j == *n) {
goto L100;
}
} else {
pj = nj;
goto L80;
}
/* L70: */
}
L80:
++j;
nj = indx[j];
if (j > *n) {
goto L100;
}
if (*rho * (d__1 = z__[nj], abs(d__1)) <= tol) {
/* Deflate due to small z component. */
--k2;
coltyp[nj] = 4;
indxp[k2] = nj;
} else {
/* Check if eigenvalues are close enough to allow deflation. */
s = z__[pj];
c__ = z__[nj];
/*
Find sqrt(a**2+b**2) without overflow or
destructive underflow.
*/
tau = dlapy2_(&c__, &s);
t = d__[nj] - d__[pj];
c__ /= tau;
s = -s / tau;
if ((d__1 = t * c__ * s, abs(d__1)) <= tol) {
/* Deflation is possible. */
z__[nj] = tau;
z__[pj] = 0.;
if (coltyp[nj] != coltyp[pj]) {
coltyp[nj] = 2;
}
coltyp[pj] = 4;
drot_(n, &q[pj * q_dim1 + 1], &c__1, &q[nj * q_dim1 + 1], &c__1, &
c__, &s);
/* Computing 2nd power */
d__1 = c__;
/* Computing 2nd power */
d__2 = s;
t = d__[pj] * (d__1 * d__1) + d__[nj] * (d__2 * d__2);
/* Computing 2nd power */
d__1 = s;
/* Computing 2nd power */
d__2 = c__;
d__[nj] = d__[pj] * (d__1 * d__1) + d__[nj] * (d__2 * d__2);
d__[pj] = t;
--k2;
i__ = 1;
L90:
if (k2 + i__ <= *n) {
if (d__[pj] < d__[indxp[k2 + i__]]) {
indxp[k2 + i__ - 1] = indxp[k2 + i__];
indxp[k2 + i__] = pj;
++i__;
goto L90;
} else {
indxp[k2 + i__ - 1] = pj;
}
} else {
indxp[k2 + i__ - 1] = pj;
}
pj = nj;
} else {
++(*k);
dlamda[*k] = d__[pj];
w[*k] = z__[pj];
indxp[*k] = pj;
pj = nj;
}
}
goto L80;
L100:
/* Record the last eigenvalue. */
++(*k);
dlamda[*k] = d__[pj];
w[*k] = z__[pj];
indxp[*k] = pj;
/*
Count up the total number of the various types of columns, then
form a permutation which positions the four column types into
four uniform groups (although one or more of these groups may be
empty).
*/
for (j = 1; j <= 4; ++j) {
ctot[j - 1] = 0;
/* L110: */
}
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
ct = coltyp[j];
++ctot[ct - 1];
/* L120: */
}
/* PSM(*) = Position in SubMatrix (of types 1 through 4) */
psm[0] = 1;
psm[1] = ctot[0] + 1;
psm[2] = psm[1] + ctot[1];
psm[3] = psm[2] + ctot[2];
*k = *n - ctot[3];
/*
Fill out the INDXC array so that the permutation which it induces
will place all type-1 columns first, all type-2 columns next,
then all type-3's, and finally all type-4's.
*/
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
js = indxp[j];
ct = coltyp[js];
indx[psm[ct - 1]] = js;
indxc[psm[ct - 1]] = j;
++psm[ct - 1];
/* L130: */
}
/*
Sort the eigenvalues and corresponding eigenvectors into DLAMDA
and Q2 respectively. The eigenvalues/vectors which were not
deflated go into the first K slots of DLAMDA and Q2 respectively,
while those which were deflated go into the last N - K slots.
*/
i__ = 1;
iq1 = 1;
iq2 = (ctot[0] + ctot[1]) * *n1 + 1;
i__1 = ctot[0];
for (j = 1; j <= i__1; ++j) {
js = indx[i__];
dcopy_(n1, &q[js * q_dim1 + 1], &c__1, &q2[iq1], &c__1);
z__[i__] = d__[js];
++i__;
iq1 += *n1;
/* L140: */
}
i__1 = ctot[1];
for (j = 1; j <= i__1; ++j) {
js = indx[i__];
dcopy_(n1, &q[js * q_dim1 + 1], &c__1, &q2[iq1], &c__1);
dcopy_(&n2, &q[*n1 + 1 + js * q_dim1], &c__1, &q2[iq2], &c__1);
z__[i__] = d__[js];
++i__;
iq1 += *n1;
iq2 += n2;
/* L150: */
}
i__1 = ctot[2];
for (j = 1; j <= i__1; ++j) {
js = indx[i__];
dcopy_(&n2, &q[*n1 + 1 + js * q_dim1], &c__1, &q2[iq2], &c__1);
z__[i__] = d__[js];
++i__;
iq2 += n2;
/* L160: */
}
iq1 = iq2;
i__1 = ctot[3];
for (j = 1; j <= i__1; ++j) {
js = indx[i__];
dcopy_(n, &q[js * q_dim1 + 1], &c__1, &q2[iq2], &c__1);
iq2 += *n;
z__[i__] = d__[js];
++i__;
/* L170: */
}
/*
The deflated eigenvalues and their corresponding vectors go back
into the last N - K slots of D and Q respectively.
*/
dlacpy_("A", n, &ctot[3], &q2[iq1], n, &q[(*k + 1) * q_dim1 + 1], ldq);
i__1 = *n - *k;
dcopy_(&i__1, &z__[*k + 1], &c__1, &d__[*k + 1], &c__1);
/* Copy CTOT into COLTYP for referencing in DLAED3. */
for (j = 1; j <= 4; ++j) {
coltyp[j] = ctot[j - 1];
/* L180: */
}
L190:
return 0;
/* End of DLAED2 */
} /* dlaed2_ */
/* Subroutine */ int dlaed3_(integer *k, integer *n, integer *n1, doublereal *
d__, doublereal *q, integer *ldq, doublereal *rho, doublereal *dlamda,
doublereal *q2, integer *indx, integer *ctot, doublereal *w,
doublereal *s, integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, i__1, i__2;
doublereal d__1;
/* Local variables */
static integer i__, j, n2, n12, ii, n23, iq2;
static doublereal temp;
extern doublereal dnrm2_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *),
dcopy_(integer *, doublereal *, integer *, doublereal *, integer
*), dlaed4_(integer *, integer *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, integer *);
extern doublereal dlamc3_(doublereal *, doublereal *);
extern /* Subroutine */ int dlacpy_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *),
dlaset_(char *, integer *, integer *, doublereal *, doublereal *,
doublereal *, integer *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAED3 finds the roots of the secular equation, as defined by the
values in D, W, and RHO, between 1 and K. It makes the
appropriate calls to DLAED4 and then updates the eigenvectors by
multiplying the matrix of eigenvectors of the pair of eigensystems
being combined by the matrix of eigenvectors of the K-by-K system
which is solved here.
This code makes very mild assumptions about floating point
arithmetic. It will work on machines with a guard digit in
add/subtract, or on those binary machines without guard digits
which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2.
It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none.
Arguments
=========
K (input) INTEGER
The number of terms in the rational function to be solved by
DLAED4. K >= 0.
N (input) INTEGER
The number of rows and columns in the Q matrix.
N >= K (deflation may result in N>K).
N1 (input) INTEGER
The location of the last eigenvalue in the leading submatrix.
min(1,N) <= N1 <= N/2.
D (output) DOUBLE PRECISION array, dimension (N)
D(I) contains the updated eigenvalues for
1 <= I <= K.
Q (output) DOUBLE PRECISION array, dimension (LDQ,N)
Initially the first K columns are used as workspace.
On output the columns 1 to K contain
the updated eigenvectors.
LDQ (input) INTEGER
The leading dimension of the array Q. LDQ >= max(1,N).
RHO (input) DOUBLE PRECISION
The value of the parameter in the rank one update equation.
RHO >= 0 required.
DLAMDA (input/output) DOUBLE PRECISION array, dimension (K)
The first K elements of this array contain the old roots
of the deflated updating problem. These are the poles
of the secular equation. May be changed on output by
having lowest order bit set to zero on Cray X-MP, Cray Y-MP,
Cray-2, or Cray C-90, as described above.
Q2 (input) DOUBLE PRECISION array, dimension (LDQ2, N)
The first K columns of this matrix contain the non-deflated
eigenvectors for the split problem.
INDX (input) INTEGER array, dimension (N)
The permutation used to arrange the columns of the deflated
Q matrix into three groups (see DLAED2).
The rows of the eigenvectors found by DLAED4 must be likewise
permuted before the matrix multiply can take place.
CTOT (input) INTEGER array, dimension (4)
A count of the total number of the various types of columns
in Q, as described in INDX. The fourth column type is any
column which has been deflated.
W (input/output) DOUBLE PRECISION array, dimension (K)
The first K elements of this array contain the components
of the deflation-adjusted updating vector. Destroyed on
output.
S (workspace) DOUBLE PRECISION array, dimension (N1 + 1)*K
Will contain the eigenvectors of the repaired matrix which
will be multiplied by the previously accumulated eigenvectors
to update the system.
LDS (input) INTEGER
The leading dimension of S. LDS >= max(1,K).
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, an eigenvalue did not converge
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
Modified by Francoise Tisseur, University of Tennessee.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
--dlamda;
--q2;
--indx;
--ctot;
--w;
--s;
/* Function Body */
*info = 0;
if (*k < 0) {
*info = -1;
} else if (*n < *k) {
*info = -2;
} else if (*ldq < max(1,*n)) {
*info = -6;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAED3", &i__1);
return 0;
}
/* Quick return if possible */
if (*k == 0) {
return 0;
}
/*
Modify values DLAMDA(i) to make sure all DLAMDA(i)-DLAMDA(j) can
be computed with high relative accuracy (barring over/underflow).
This is a problem on machines without a guard digit in
add/subtract (Cray XMP, Cray YMP, Cray C 90 and Cray 2).
The following code replaces DLAMDA(I) by 2*DLAMDA(I)-DLAMDA(I),
which on any of these machines zeros out the bottommost
bit of DLAMDA(I) if it is 1; this makes the subsequent
subtractions DLAMDA(I)-DLAMDA(J) unproblematic when cancellation
occurs. On binary machines with a guard digit (almost all
machines) it does not change DLAMDA(I) at all. On hexadecimal
and decimal machines with a guard digit, it slightly
changes the bottommost bits of DLAMDA(I). It does not account
for hexadecimal or decimal machines without guard digits
(we know of none). We use a subroutine call to compute
2*DLAMBDA(I) to prevent optimizing compilers from eliminating
this code.
*/
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
dlamda[i__] = dlamc3_(&dlamda[i__], &dlamda[i__]) - dlamda[i__];
/* L10: */
}
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dlaed4_(k, &j, &dlamda[1], &w[1], &q[j * q_dim1 + 1], rho, &d__[j],
info);
/* If the zero finder fails, the computation is terminated. */
if (*info != 0) {
goto L120;
}
/* L20: */
}
if (*k == 1) {
goto L110;
}
if (*k == 2) {
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
w[1] = q[j * q_dim1 + 1];
w[2] = q[j * q_dim1 + 2];
ii = indx[1];
q[j * q_dim1 + 1] = w[ii];
ii = indx[2];
q[j * q_dim1 + 2] = w[ii];
/* L30: */
}
goto L110;
}
/* Compute updated W. */
dcopy_(k, &w[1], &c__1, &s[1], &c__1);
/* Initialize W(I) = Q(I,I) */
i__1 = *ldq + 1;
dcopy_(k, &q[q_offset], &i__1, &w[1], &c__1);
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = j - 1;
for (i__ = 1; i__ <= i__2; ++i__) {
w[i__] *= q[i__ + j * q_dim1] / (dlamda[i__] - dlamda[j]);
/* L40: */
}
i__2 = *k;
for (i__ = j + 1; i__ <= i__2; ++i__) {
w[i__] *= q[i__ + j * q_dim1] / (dlamda[i__] - dlamda[j]);
/* L50: */
}
/* L60: */
}
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
d__1 = sqrt(-w[i__]);
w[i__] = d_sign(&d__1, &s[i__]);
/* L70: */
}
/* Compute eigenvectors of the modified rank-1 modification. */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *k;
for (i__ = 1; i__ <= i__2; ++i__) {
s[i__] = w[i__] / q[i__ + j * q_dim1];
/* L80: */
}
temp = dnrm2_(k, &s[1], &c__1);
i__2 = *k;
for (i__ = 1; i__ <= i__2; ++i__) {
ii = indx[i__];
q[i__ + j * q_dim1] = s[ii] / temp;
/* L90: */
}
/* L100: */
}
/* Compute the updated eigenvectors. */
L110:
n2 = *n - *n1;
n12 = ctot[1] + ctot[2];
n23 = ctot[2] + ctot[3];
dlacpy_("A", &n23, k, &q[ctot[1] + 1 + q_dim1], ldq, &s[1], &n23);
iq2 = *n1 * n12 + 1;
if (n23 != 0) {
dgemm_("N", "N", &n2, k, &n23, &c_b15, &q2[iq2], &n2, &s[1], &n23, &
c_b29, &q[*n1 + 1 + q_dim1], ldq);
} else {
dlaset_("A", &n2, k, &c_b29, &c_b29, &q[*n1 + 1 + q_dim1], ldq);
}
dlacpy_("A", &n12, k, &q[q_offset], ldq, &s[1], &n12);
if (n12 != 0) {
dgemm_("N", "N", n1, k, &n12, &c_b15, &q2[1], n1, &s[1], &n12, &c_b29,
&q[q_offset], ldq);
} else {
dlaset_("A", n1, k, &c_b29, &c_b29, &q[q_dim1 + 1], ldq);
}
L120:
return 0;
/* End of DLAED3 */
} /* dlaed3_ */
/* Subroutine */ int dlaed4_(integer *n, integer *i__, doublereal *d__,
doublereal *z__, doublereal *delta, doublereal *rho, doublereal *dlam,
integer *info)
{
/* System generated locals */
integer i__1;
doublereal d__1;
/* Local variables */
static doublereal a, b, c__;
static integer j;
static doublereal w;
static integer ii;
static doublereal dw, zz[3];
static integer ip1;
static doublereal del, eta, phi, eps, tau, psi;
static integer iim1, iip1;
static doublereal dphi, dpsi;
static integer iter;
static doublereal temp, prew, temp1, dltlb, dltub, midpt;
static integer niter;
static logical swtch;
extern /* Subroutine */ int dlaed5_(integer *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *), dlaed6_(integer *,
logical *, doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *);
static logical swtch3;
static logical orgati;
static doublereal erretm, rhoinv;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
This subroutine computes the I-th updated eigenvalue of a symmetric
rank-one modification to a diagonal matrix whose elements are
given in the array d, and that
D(i) < D(j) for i < j
and that RHO > 0. This is arranged by the calling routine, and is
no loss in generality. The rank-one modified system is thus
diag( D ) + RHO * Z * Z_transpose.
where we assume the Euclidean norm of Z is 1.
The method consists of approximating the rational functions in the
secular equation by simpler interpolating rational functions.
Arguments
=========
N (input) INTEGER
The length of all arrays.
I (input) INTEGER
The index of the eigenvalue to be computed. 1 <= I <= N.
D (input) DOUBLE PRECISION array, dimension (N)
The original eigenvalues. It is assumed that they are in
order, D(I) < D(J) for I < J.
Z (input) DOUBLE PRECISION array, dimension (N)
The components of the updating vector.
DELTA (output) DOUBLE PRECISION array, dimension (N)
If N .GT. 2, DELTA contains (D(j) - lambda_I) in its j-th
component. If N = 1, then DELTA(1) = 1. If N = 2, see DLAED5
for detail. The vector DELTA contains the information necessary
to construct the eigenvectors by DLAED3 and DLAED9.
RHO (input) DOUBLE PRECISION
The scalar in the symmetric updating formula.
DLAM (output) DOUBLE PRECISION
The computed lambda_I, the I-th updated eigenvalue.
INFO (output) INTEGER
= 0: successful exit
> 0: if INFO = 1, the updating process failed.
Internal Parameters
===================
Logical variable ORGATI (origin-at-i?) is used for distinguishing
whether D(i) or D(i+1) is treated as the origin.
ORGATI = .true. origin at i
ORGATI = .false. origin at i+1
Logical variable SWTCH3 (switch-for-3-poles?) is for noting
if we are working with THREE poles!
MAXIT is the maximum number of iterations allowed for each
eigenvalue.
Further Details
===============
Based on contributions by
Ren-Cang Li, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
Since this routine is called in an inner loop, we do no argument
checking.
Quick return for N=1 and 2.
*/
/* Parameter adjustments */
--delta;
--z__;
--d__;
/* Function Body */
*info = 0;
if (*n == 1) {
/* Presumably, I=1 upon entry */
*dlam = d__[1] + *rho * z__[1] * z__[1];
delta[1] = 1.;
return 0;
}
if (*n == 2) {
dlaed5_(i__, &d__[1], &z__[1], &delta[1], rho, dlam);
return 0;
}
/* Compute machine epsilon */
eps = EPSILON;
rhoinv = 1. / *rho;
/* The case I = N */
if (*i__ == *n) {
/* Initialize some basic variables */
ii = *n - 1;
niter = 1;
/* Calculate initial guess */
midpt = *rho / 2.;
/*
If ||Z||_2 is not one, then TEMP should be set to
RHO * ||Z||_2^2 / TWO
*/
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] = d__[j] - d__[*i__] - midpt;
/* L10: */
}
psi = 0.;
i__1 = *n - 2;
for (j = 1; j <= i__1; ++j) {
psi += z__[j] * z__[j] / delta[j];
/* L20: */
}
c__ = rhoinv + psi;
w = c__ + z__[ii] * z__[ii] / delta[ii] + z__[*n] * z__[*n] / delta[*
n];
if (w <= 0.) {
temp = z__[*n - 1] * z__[*n - 1] / (d__[*n] - d__[*n - 1] + *rho)
+ z__[*n] * z__[*n] / *rho;
if (c__ <= temp) {
tau = *rho;
} else {
del = d__[*n] - d__[*n - 1];
a = -c__ * del + z__[*n - 1] * z__[*n - 1] + z__[*n] * z__[*n]
;
b = z__[*n] * z__[*n] * del;
if (a < 0.) {
tau = b * 2. / (sqrt(a * a + b * 4. * c__) - a);
} else {
tau = (a + sqrt(a * a + b * 4. * c__)) / (c__ * 2.);
}
}
/*
It can be proved that
D(N)+RHO/2 <= LAMBDA(N) < D(N)+TAU <= D(N)+RHO
*/
dltlb = midpt;
dltub = *rho;
} else {
del = d__[*n] - d__[*n - 1];
a = -c__ * del + z__[*n - 1] * z__[*n - 1] + z__[*n] * z__[*n];
b = z__[*n] * z__[*n] * del;
if (a < 0.) {
tau = b * 2. / (sqrt(a * a + b * 4. * c__) - a);
} else {
tau = (a + sqrt(a * a + b * 4. * c__)) / (c__ * 2.);
}
/*
It can be proved that
D(N) < D(N)+TAU < LAMBDA(N) < D(N)+RHO/2
*/
dltlb = 0.;
dltub = midpt;
}
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] = d__[j] - d__[*i__] - tau;
/* L30: */
}
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = ii;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / delta[j];
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L40: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
temp = z__[*n] / delta[*n];
phi = z__[*n] * temp;
dphi = temp * temp;
erretm = (-phi - psi) * 8. + erretm - phi + rhoinv + abs(tau) * (dpsi
+ dphi);
w = rhoinv + phi + psi;
/* Test for convergence */
if (abs(w) <= eps * erretm) {
*dlam = d__[*i__] + tau;
goto L250;
}
if (w <= 0.) {
dltlb = max(dltlb,tau);
} else {
dltub = min(dltub,tau);
}
/* Calculate the new step */
++niter;
c__ = w - delta[*n - 1] * dpsi - delta[*n] * dphi;
a = (delta[*n - 1] + delta[*n]) * w - delta[*n - 1] * delta[*n] * (
dpsi + dphi);
b = delta[*n - 1] * delta[*n] * w;
if (c__ < 0.) {
c__ = abs(c__);
}
if (c__ == 0.) {
/*
ETA = B/A
ETA = RHO - TAU
*/
eta = dltub - tau;
} else if (a >= 0.) {
eta = (a + sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (c__
* 2.);
} else {
eta = b * 2. / (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))
);
}
/*
Note, eta should be positive if w is negative, and
eta should be negative otherwise. However,
if for some reason caused by roundoff, eta*w > 0,
we simply use one Newton step instead. This way
will guarantee eta*w < 0.
*/
if (w * eta > 0.) {
eta = -w / (dpsi + dphi);
}
temp = tau + eta;
if (temp > dltub || temp < dltlb) {
if (w < 0.) {
eta = (dltub - tau) / 2.;
} else {
eta = (dltlb - tau) / 2.;
}
}
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] -= eta;
/* L50: */
}
tau += eta;
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = ii;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / delta[j];
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L60: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
temp = z__[*n] / delta[*n];
phi = z__[*n] * temp;
dphi = temp * temp;
erretm = (-phi - psi) * 8. + erretm - phi + rhoinv + abs(tau) * (dpsi
+ dphi);
w = rhoinv + phi + psi;
/* Main loop to update the values of the array DELTA */
iter = niter + 1;
for (niter = iter; niter <= 30; ++niter) {
/* Test for convergence */
if (abs(w) <= eps * erretm) {
*dlam = d__[*i__] + tau;
goto L250;
}
if (w <= 0.) {
dltlb = max(dltlb,tau);
} else {
dltub = min(dltub,tau);
}
/* Calculate the new step */
c__ = w - delta[*n - 1] * dpsi - delta[*n] * dphi;
a = (delta[*n - 1] + delta[*n]) * w - delta[*n - 1] * delta[*n] *
(dpsi + dphi);
b = delta[*n - 1] * delta[*n] * w;
if (a >= 0.) {
eta = (a + sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (
c__ * 2.);
} else {
eta = b * 2. / (a - sqrt((d__1 = a * a - b * 4. * c__, abs(
d__1))));
}
/*
Note, eta should be positive if w is negative, and
eta should be negative otherwise. However,
if for some reason caused by roundoff, eta*w > 0,
we simply use one Newton step instead. This way
will guarantee eta*w < 0.
*/
if (w * eta > 0.) {
eta = -w / (dpsi + dphi);
}
temp = tau + eta;
if (temp > dltub || temp < dltlb) {
if (w < 0.) {
eta = (dltub - tau) / 2.;
} else {
eta = (dltlb - tau) / 2.;
}
}
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] -= eta;
/* L70: */
}
tau += eta;
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = ii;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / delta[j];
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L80: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
temp = z__[*n] / delta[*n];
phi = z__[*n] * temp;
dphi = temp * temp;
erretm = (-phi - psi) * 8. + erretm - phi + rhoinv + abs(tau) * (
dpsi + dphi);
w = rhoinv + phi + psi;
/* L90: */
}
/* Return with INFO = 1, NITER = MAXIT and not converged */
*info = 1;
*dlam = d__[*i__] + tau;
goto L250;
/* End for the case I = N */
} else {
/* The case for I < N */
niter = 1;
ip1 = *i__ + 1;
/* Calculate initial guess */
del = d__[ip1] - d__[*i__];
midpt = del / 2.;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] = d__[j] - d__[*i__] - midpt;
/* L100: */
}
psi = 0.;
i__1 = *i__ - 1;
for (j = 1; j <= i__1; ++j) {
psi += z__[j] * z__[j] / delta[j];
/* L110: */
}
phi = 0.;
i__1 = *i__ + 2;
for (j = *n; j >= i__1; --j) {
phi += z__[j] * z__[j] / delta[j];
/* L120: */
}
c__ = rhoinv + psi + phi;
w = c__ + z__[*i__] * z__[*i__] / delta[*i__] + z__[ip1] * z__[ip1] /
delta[ip1];
if (w > 0.) {
/*
d(i)< the ith eigenvalue < (d(i)+d(i+1))/2
We choose d(i) as origin.
*/
orgati = TRUE_;
a = c__ * del + z__[*i__] * z__[*i__] + z__[ip1] * z__[ip1];
b = z__[*i__] * z__[*i__] * del;
if (a > 0.) {
tau = b * 2. / (a + sqrt((d__1 = a * a - b * 4. * c__, abs(
d__1))));
} else {
tau = (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (
c__ * 2.);
}
dltlb = 0.;
dltub = midpt;
} else {
/*
(d(i)+d(i+1))/2 <= the ith eigenvalue < d(i+1)
We choose d(i+1) as origin.
*/
orgati = FALSE_;
a = c__ * del - z__[*i__] * z__[*i__] - z__[ip1] * z__[ip1];
b = z__[ip1] * z__[ip1] * del;
if (a < 0.) {
tau = b * 2. / (a - sqrt((d__1 = a * a + b * 4. * c__, abs(
d__1))));
} else {
tau = -(a + sqrt((d__1 = a * a + b * 4. * c__, abs(d__1)))) /
(c__ * 2.);
}
dltlb = -midpt;
dltub = 0.;
}
if (orgati) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] = d__[j] - d__[*i__] - tau;
/* L130: */
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] = d__[j] - d__[ip1] - tau;
/* L140: */
}
}
if (orgati) {
ii = *i__;
} else {
ii = *i__ + 1;
}
iim1 = ii - 1;
iip1 = ii + 1;
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = iim1;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / delta[j];
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L150: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
dphi = 0.;
phi = 0.;
i__1 = iip1;
for (j = *n; j >= i__1; --j) {
temp = z__[j] / delta[j];
phi += z__[j] * temp;
dphi += temp * temp;
erretm += phi;
/* L160: */
}
w = rhoinv + phi + psi;
/*
W is the value of the secular function with
its ii-th element removed.
*/
swtch3 = FALSE_;
if (orgati) {
if (w < 0.) {
swtch3 = TRUE_;
}
} else {
if (w > 0.) {
swtch3 = TRUE_;
}
}
if (ii == 1 || ii == *n) {
swtch3 = FALSE_;
}
temp = z__[ii] / delta[ii];
dw = dpsi + dphi + temp * temp;
temp = z__[ii] * temp;
w += temp;
erretm = (phi - psi) * 8. + erretm + rhoinv * 2. + abs(temp) * 3. +
abs(tau) * dw;
/* Test for convergence */
if (abs(w) <= eps * erretm) {
if (orgati) {
*dlam = d__[*i__] + tau;
} else {
*dlam = d__[ip1] + tau;
}
goto L250;
}
if (w <= 0.) {
dltlb = max(dltlb,tau);
} else {
dltub = min(dltub,tau);
}
/* Calculate the new step */
++niter;
if (! swtch3) {
if (orgati) {
/* Computing 2nd power */
d__1 = z__[*i__] / delta[*i__];
c__ = w - delta[ip1] * dw - (d__[*i__] - d__[ip1]) * (d__1 *
d__1);
} else {
/* Computing 2nd power */
d__1 = z__[ip1] / delta[ip1];
c__ = w - delta[*i__] * dw - (d__[ip1] - d__[*i__]) * (d__1 *
d__1);
}
a = (delta[*i__] + delta[ip1]) * w - delta[*i__] * delta[ip1] *
dw;
b = delta[*i__] * delta[ip1] * w;
if (c__ == 0.) {
if (a == 0.) {
if (orgati) {
a = z__[*i__] * z__[*i__] + delta[ip1] * delta[ip1] *
(dpsi + dphi);
} else {
a = z__[ip1] * z__[ip1] + delta[*i__] * delta[*i__] *
(dpsi + dphi);
}
}
eta = b / a;
} else if (a <= 0.) {
eta = (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (
c__ * 2.);
} else {
eta = b * 2. / (a + sqrt((d__1 = a * a - b * 4. * c__, abs(
d__1))));
}
} else {
/* Interpolation using THREE most relevant poles */
temp = rhoinv + psi + phi;
if (orgati) {
temp1 = z__[iim1] / delta[iim1];
temp1 *= temp1;
c__ = temp - delta[iip1] * (dpsi + dphi) - (d__[iim1] - d__[
iip1]) * temp1;
zz[0] = z__[iim1] * z__[iim1];
zz[2] = delta[iip1] * delta[iip1] * (dpsi - temp1 + dphi);
} else {
temp1 = z__[iip1] / delta[iip1];
temp1 *= temp1;
c__ = temp - delta[iim1] * (dpsi + dphi) - (d__[iip1] - d__[
iim1]) * temp1;
zz[0] = delta[iim1] * delta[iim1] * (dpsi + (dphi - temp1));
zz[2] = z__[iip1] * z__[iip1];
}
zz[1] = z__[ii] * z__[ii];
dlaed6_(&niter, &orgati, &c__, &delta[iim1], zz, &w, &eta, info);
if (*info != 0) {
goto L250;
}
}
/*
Note, eta should be positive if w is negative, and
eta should be negative otherwise. However,
if for some reason caused by roundoff, eta*w > 0,
we simply use one Newton step instead. This way
will guarantee eta*w < 0.
*/
if (w * eta >= 0.) {
eta = -w / dw;
}
temp = tau + eta;
if (temp > dltub || temp < dltlb) {
if (w < 0.) {
eta = (dltub - tau) / 2.;
} else {
eta = (dltlb - tau) / 2.;
}
}
prew = w;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] -= eta;
/* L180: */
}
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = iim1;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / delta[j];
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L190: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
dphi = 0.;
phi = 0.;
i__1 = iip1;
for (j = *n; j >= i__1; --j) {
temp = z__[j] / delta[j];
phi += z__[j] * temp;
dphi += temp * temp;
erretm += phi;
/* L200: */
}
temp = z__[ii] / delta[ii];
dw = dpsi + dphi + temp * temp;
temp = z__[ii] * temp;
w = rhoinv + phi + psi + temp;
erretm = (phi - psi) * 8. + erretm + rhoinv * 2. + abs(temp) * 3. + (
d__1 = tau + eta, abs(d__1)) * dw;
swtch = FALSE_;
if (orgati) {
if (-w > abs(prew) / 10.) {
swtch = TRUE_;
}
} else {
if (w > abs(prew) / 10.) {
swtch = TRUE_;
}
}
tau += eta;
/* Main loop to update the values of the array DELTA */
iter = niter + 1;
for (niter = iter; niter <= 30; ++niter) {
/* Test for convergence */
if (abs(w) <= eps * erretm) {
if (orgati) {
*dlam = d__[*i__] + tau;
} else {
*dlam = d__[ip1] + tau;
}
goto L250;
}
if (w <= 0.) {
dltlb = max(dltlb,tau);
} else {
dltub = min(dltub,tau);
}
/* Calculate the new step */
if (! swtch3) {
if (! swtch) {
if (orgati) {
/* Computing 2nd power */
d__1 = z__[*i__] / delta[*i__];
c__ = w - delta[ip1] * dw - (d__[*i__] - d__[ip1]) * (
d__1 * d__1);
} else {
/* Computing 2nd power */
d__1 = z__[ip1] / delta[ip1];
c__ = w - delta[*i__] * dw - (d__[ip1] - d__[*i__]) *
(d__1 * d__1);
}
} else {
temp = z__[ii] / delta[ii];
if (orgati) {
dpsi += temp * temp;
} else {
dphi += temp * temp;
}
c__ = w - delta[*i__] * dpsi - delta[ip1] * dphi;
}
a = (delta[*i__] + delta[ip1]) * w - delta[*i__] * delta[ip1]
* dw;
b = delta[*i__] * delta[ip1] * w;
if (c__ == 0.) {
if (a == 0.) {
if (! swtch) {
if (orgati) {
a = z__[*i__] * z__[*i__] + delta[ip1] *
delta[ip1] * (dpsi + dphi);
} else {
a = z__[ip1] * z__[ip1] + delta[*i__] * delta[
*i__] * (dpsi + dphi);
}
} else {
a = delta[*i__] * delta[*i__] * dpsi + delta[ip1]
* delta[ip1] * dphi;
}
}
eta = b / a;
} else if (a <= 0.) {
eta = (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1))))
/ (c__ * 2.);
} else {
eta = b * 2. / (a + sqrt((d__1 = a * a - b * 4. * c__,
abs(d__1))));
}
} else {
/* Interpolation using THREE most relevant poles */
temp = rhoinv + psi + phi;
if (swtch) {
c__ = temp - delta[iim1] * dpsi - delta[iip1] * dphi;
zz[0] = delta[iim1] * delta[iim1] * dpsi;
zz[2] = delta[iip1] * delta[iip1] * dphi;
} else {
if (orgati) {
temp1 = z__[iim1] / delta[iim1];
temp1 *= temp1;
c__ = temp - delta[iip1] * (dpsi + dphi) - (d__[iim1]
- d__[iip1]) * temp1;
zz[0] = z__[iim1] * z__[iim1];
zz[2] = delta[iip1] * delta[iip1] * (dpsi - temp1 +
dphi);
} else {
temp1 = z__[iip1] / delta[iip1];
temp1 *= temp1;
c__ = temp - delta[iim1] * (dpsi + dphi) - (d__[iip1]
- d__[iim1]) * temp1;
zz[0] = delta[iim1] * delta[iim1] * (dpsi + (dphi -
temp1));
zz[2] = z__[iip1] * z__[iip1];
}
}
dlaed6_(&niter, &orgati, &c__, &delta[iim1], zz, &w, &eta,
info);
if (*info != 0) {
goto L250;
}
}
/*
Note, eta should be positive if w is negative, and
eta should be negative otherwise. However,
if for some reason caused by roundoff, eta*w > 0,
we simply use one Newton step instead. This way
will guarantee eta*w < 0.
*/
if (w * eta >= 0.) {
eta = -w / dw;
}
temp = tau + eta;
if (temp > dltub || temp < dltlb) {
if (w < 0.) {
eta = (dltub - tau) / 2.;
} else {
eta = (dltlb - tau) / 2.;
}
}
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] -= eta;
/* L210: */
}
tau += eta;
prew = w;
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = iim1;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / delta[j];
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L220: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
dphi = 0.;
phi = 0.;
i__1 = iip1;
for (j = *n; j >= i__1; --j) {
temp = z__[j] / delta[j];
phi += z__[j] * temp;
dphi += temp * temp;
erretm += phi;
/* L230: */
}
temp = z__[ii] / delta[ii];
dw = dpsi + dphi + temp * temp;
temp = z__[ii] * temp;
w = rhoinv + phi + psi + temp;
erretm = (phi - psi) * 8. + erretm + rhoinv * 2. + abs(temp) * 3.
+ abs(tau) * dw;
if (w * prew > 0. && abs(w) > abs(prew) / 10.) {
swtch = ! swtch;
}
/* L240: */
}
/* Return with INFO = 1, NITER = MAXIT and not converged */
*info = 1;
if (orgati) {
*dlam = d__[*i__] + tau;
} else {
*dlam = d__[ip1] + tau;
}
}
L250:
return 0;
/* End of DLAED4 */
} /* dlaed4_ */
/* Subroutine */ int dlaed5_(integer *i__, doublereal *d__, doublereal *z__,
doublereal *delta, doublereal *rho, doublereal *dlam)
{
/* System generated locals */
doublereal d__1;
/* Local variables */
static doublereal b, c__, w, del, tau, temp;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
This subroutine computes the I-th eigenvalue of a symmetric rank-one
modification of a 2-by-2 diagonal matrix
diag( D ) + RHO * Z * transpose(Z) .
The diagonal elements in the array D are assumed to satisfy
D(i) < D(j) for i < j .
We also assume RHO > 0 and that the Euclidean norm of the vector
Z is one.
Arguments
=========
I (input) INTEGER
The index of the eigenvalue to be computed. I = 1 or I = 2.
D (input) DOUBLE PRECISION array, dimension (2)
The original eigenvalues. We assume D(1) < D(2).
Z (input) DOUBLE PRECISION array, dimension (2)
The components of the updating vector.
DELTA (output) DOUBLE PRECISION array, dimension (2)
The vector DELTA contains the information necessary
to construct the eigenvectors.
RHO (input) DOUBLE PRECISION
The scalar in the symmetric updating formula.
DLAM (output) DOUBLE PRECISION
The computed lambda_I, the I-th updated eigenvalue.
Further Details
===============
Based on contributions by
Ren-Cang Li, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
*/
/* Parameter adjustments */
--delta;
--z__;
--d__;
/* Function Body */
del = d__[2] - d__[1];
if (*i__ == 1) {
w = *rho * 2. * (z__[2] * z__[2] - z__[1] * z__[1]) / del + 1.;
if (w > 0.) {
b = del + *rho * (z__[1] * z__[1] + z__[2] * z__[2]);
c__ = *rho * z__[1] * z__[1] * del;
/* B > ZERO, always */
tau = c__ * 2. / (b + sqrt((d__1 = b * b - c__ * 4., abs(d__1))));
*dlam = d__[1] + tau;
delta[1] = -z__[1] / tau;
delta[2] = z__[2] / (del - tau);
} else {
b = -del + *rho * (z__[1] * z__[1] + z__[2] * z__[2]);
c__ = *rho * z__[2] * z__[2] * del;
if (b > 0.) {
tau = c__ * -2. / (b + sqrt(b * b + c__ * 4.));
} else {
tau = (b - sqrt(b * b + c__ * 4.)) / 2.;
}
*dlam = d__[2] + tau;
delta[1] = -z__[1] / (del + tau);
delta[2] = -z__[2] / tau;
}
temp = sqrt(delta[1] * delta[1] + delta[2] * delta[2]);
delta[1] /= temp;
delta[2] /= temp;
} else {
/* Now I=2 */
b = -del + *rho * (z__[1] * z__[1] + z__[2] * z__[2]);
c__ = *rho * z__[2] * z__[2] * del;
if (b > 0.) {
tau = (b + sqrt(b * b + c__ * 4.)) / 2.;
} else {
tau = c__ * 2. / (-b + sqrt(b * b + c__ * 4.));
}
*dlam = d__[2] + tau;
delta[1] = -z__[1] / (del + tau);
delta[2] = -z__[2] / tau;
temp = sqrt(delta[1] * delta[1] + delta[2] * delta[2]);
delta[1] /= temp;
delta[2] /= temp;
}
return 0;
/* End OF DLAED5 */
} /* dlaed5_ */
/* Subroutine */ int dlaed6_(integer *kniter, logical *orgati, doublereal *
rho, doublereal *d__, doublereal *z__, doublereal *finit, doublereal *
tau, integer *info)
{
/* System generated locals */
integer i__1;
doublereal d__1, d__2, d__3, d__4;
/* Local variables */
static doublereal a, b, c__, f;
static integer i__;
static doublereal fc, df, ddf, lbd, eta, ubd, eps, base;
static integer iter;
static doublereal temp, temp1, temp2, temp3, temp4;
static logical scale;
static integer niter;
static doublereal small1, small2, sminv1, sminv2;
static doublereal dscale[3], sclfac, zscale[3], erretm, sclinv;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
February 2007
Purpose
=======
DLAED6 computes the positive or negative root (closest to the origin)
of
z(1) z(2) z(3)
f(x) = rho + --------- + ---------- + ---------
d(1)-x d(2)-x d(3)-x
It is assumed that
if ORGATI = .true. the root is between d(2) and d(3);
otherwise it is between d(1) and d(2)
This routine will be called by DLAED4 when necessary. In most cases,
the root sought is the smallest in magnitude, though it might not be
in some extremely rare situations.
Arguments
=========
KNITER (input) INTEGER
Refer to DLAED4 for its significance.
ORGATI (input) LOGICAL
If ORGATI is true, the needed root is between d(2) and
d(3); otherwise it is between d(1) and d(2). See
DLAED4 for further details.
RHO (input) DOUBLE PRECISION
Refer to the equation f(x) above.
D (input) DOUBLE PRECISION array, dimension (3)
D satisfies d(1) < d(2) < d(3).
Z (input) DOUBLE PRECISION array, dimension (3)
Each of the elements in z must be positive.
FINIT (input) DOUBLE PRECISION
The value of f at 0. It is more accurate than the one
evaluated inside this routine (if someone wants to do
so).
TAU (output) DOUBLE PRECISION
The root of the equation f(x).
INFO (output) INTEGER
= 0: successful exit
> 0: if INFO = 1, failure to converge
Further Details
===============
30/06/99: Based on contributions by
Ren-Cang Li, Computer Science Division, University of California
at Berkeley, USA
10/02/03: This version has a few statements commented out for thread
safety (machine parameters are computed on each entry). SJH.
05/10/06: Modified from a new version of Ren-Cang Li, use
Gragg-Thornton-Warner cubic convergent scheme for better stability.
=====================================================================
*/
/* Parameter adjustments */
--z__;
--d__;
/* Function Body */
*info = 0;
if (*orgati) {
lbd = d__[2];
ubd = d__[3];
} else {
lbd = d__[1];
ubd = d__[2];
}
if (*finit < 0.) {
lbd = 0.;
} else {
ubd = 0.;
}
niter = 1;
*tau = 0.;
if (*kniter == 2) {
if (*orgati) {
temp = (d__[3] - d__[2]) / 2.;
c__ = *rho + z__[1] / (d__[1] - d__[2] - temp);
a = c__ * (d__[2] + d__[3]) + z__[2] + z__[3];
b = c__ * d__[2] * d__[3] + z__[2] * d__[3] + z__[3] * d__[2];
} else {
temp = (d__[1] - d__[2]) / 2.;
c__ = *rho + z__[3] / (d__[3] - d__[2] - temp);
a = c__ * (d__[1] + d__[2]) + z__[1] + z__[2];
b = c__ * d__[1] * d__[2] + z__[1] * d__[2] + z__[2] * d__[1];
}
/* Computing MAX */
d__1 = abs(a), d__2 = abs(b), d__1 = max(d__1,d__2), d__2 = abs(c__);
temp = max(d__1,d__2);
a /= temp;
b /= temp;
c__ /= temp;
if (c__ == 0.) {
*tau = b / a;
} else if (a <= 0.) {
*tau = (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (
c__ * 2.);
} else {
*tau = b * 2. / (a + sqrt((d__1 = a * a - b * 4. * c__, abs(d__1))
));
}
if (*tau < lbd || *tau > ubd) {
*tau = (lbd + ubd) / 2.;
}
if (d__[1] == *tau || d__[2] == *tau || d__[3] == *tau) {
*tau = 0.;
} else {
temp = *finit + *tau * z__[1] / (d__[1] * (d__[1] - *tau)) + *tau
* z__[2] / (d__[2] * (d__[2] - *tau)) + *tau * z__[3] / (
d__[3] * (d__[3] - *tau));
if (temp <= 0.) {
lbd = *tau;
} else {
ubd = *tau;
}
if (abs(*finit) <= abs(temp)) {
*tau = 0.;
}
}
}
/*
get machine parameters for possible scaling to avoid overflow
modified by Sven: parameters SMALL1, SMINV1, SMALL2,
SMINV2, EPS are not SAVEd anymore between one call to the
others but recomputed at each call
*/
eps = EPSILON;
base = BASE;
i__1 = (integer) (log(SAFEMINIMUM) / log(base) / 3.);
small1 = pow_di(&base, &i__1);
sminv1 = 1. / small1;
small2 = small1 * small1;
sminv2 = sminv1 * sminv1;
/*
Determine if scaling of inputs necessary to avoid overflow
when computing 1/TEMP**3
*/
if (*orgati) {
/* Computing MIN */
d__3 = (d__1 = d__[2] - *tau, abs(d__1)), d__4 = (d__2 = d__[3] - *
tau, abs(d__2));
temp = min(d__3,d__4);
} else {
/* Computing MIN */
d__3 = (d__1 = d__[1] - *tau, abs(d__1)), d__4 = (d__2 = d__[2] - *
tau, abs(d__2));
temp = min(d__3,d__4);
}
scale = FALSE_;
if (temp <= small1) {
scale = TRUE_;
if (temp <= small2) {
/* Scale up by power of radix nearest 1/SAFMIN**(2/3) */
sclfac = sminv2;
sclinv = small2;
} else {
/* Scale up by power of radix nearest 1/SAFMIN**(1/3) */
sclfac = sminv1;
sclinv = small1;
}
/* Scaling up safe because D, Z, TAU scaled elsewhere to be O(1) */
for (i__ = 1; i__ <= 3; ++i__) {
dscale[i__ - 1] = d__[i__] * sclfac;
zscale[i__ - 1] = z__[i__] * sclfac;
/* L10: */
}
*tau *= sclfac;
lbd *= sclfac;
ubd *= sclfac;
} else {
/* Copy D and Z to DSCALE and ZSCALE */
for (i__ = 1; i__ <= 3; ++i__) {
dscale[i__ - 1] = d__[i__];
zscale[i__ - 1] = z__[i__];
/* L20: */
}
}
fc = 0.;
df = 0.;
ddf = 0.;
for (i__ = 1; i__ <= 3; ++i__) {
temp = 1. / (dscale[i__ - 1] - *tau);
temp1 = zscale[i__ - 1] * temp;
temp2 = temp1 * temp;
temp3 = temp2 * temp;
fc += temp1 / dscale[i__ - 1];
df += temp2;
ddf += temp3;
/* L30: */
}
f = *finit + *tau * fc;
if (abs(f) <= 0.) {
goto L60;
}
if (f <= 0.) {
lbd = *tau;
} else {
ubd = *tau;
}
/*
Iteration begins -- Use Gragg-Thornton-Warner cubic convergent
scheme
It is not hard to see that
1) Iterations will go up monotonically
if FINIT < 0;
2) Iterations will go down monotonically
if FINIT > 0.
*/
iter = niter + 1;
for (niter = iter; niter <= 40; ++niter) {
if (*orgati) {
temp1 = dscale[1] - *tau;
temp2 = dscale[2] - *tau;
} else {
temp1 = dscale[0] - *tau;
temp2 = dscale[1] - *tau;
}
a = (temp1 + temp2) * f - temp1 * temp2 * df;
b = temp1 * temp2 * f;
c__ = f - (temp1 + temp2) * df + temp1 * temp2 * ddf;
/* Computing MAX */
d__1 = abs(a), d__2 = abs(b), d__1 = max(d__1,d__2), d__2 = abs(c__);
temp = max(d__1,d__2);
a /= temp;
b /= temp;
c__ /= temp;
if (c__ == 0.) {
eta = b / a;
} else if (a <= 0.) {
eta = (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (c__
* 2.);
} else {
eta = b * 2. / (a + sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))
);
}
if (f * eta >= 0.) {
eta = -f / df;
}
*tau += eta;
if (*tau < lbd || *tau > ubd) {
*tau = (lbd + ubd) / 2.;
}
fc = 0.;
erretm = 0.;
df = 0.;
ddf = 0.;
for (i__ = 1; i__ <= 3; ++i__) {
temp = 1. / (dscale[i__ - 1] - *tau);
temp1 = zscale[i__ - 1] * temp;
temp2 = temp1 * temp;
temp3 = temp2 * temp;
temp4 = temp1 / dscale[i__ - 1];
fc += temp4;
erretm += abs(temp4);
df += temp2;
ddf += temp3;
/* L40: */
}
f = *finit + *tau * fc;
erretm = (abs(*finit) + abs(*tau) * erretm) * 8. + abs(*tau) * df;
if (abs(f) <= eps * erretm) {
goto L60;
}
if (f <= 0.) {
lbd = *tau;
} else {
ubd = *tau;
}
/* L50: */
}
*info = 1;
L60:
/* Undo scaling */
if (scale) {
*tau *= sclinv;
}
return 0;
/* End of DLAED6 */
} /* dlaed6_ */
/* Subroutine */ int dlaed7_(integer *icompq, integer *n, integer *qsiz,
integer *tlvls, integer *curlvl, integer *curpbm, doublereal *d__,
doublereal *q, integer *ldq, integer *indxq, doublereal *rho, integer
*cutpnt, doublereal *qstore, integer *qptr, integer *prmptr, integer *
perm, integer *givptr, integer *givcol, doublereal *givnum,
doublereal *work, integer *iwork, integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, i__1, i__2;
/* Local variables */
static integer i__, k, n1, n2, is, iw, iz, iq2, ptr, ldq2, indx, curr;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static integer indxc, indxp;
extern /* Subroutine */ int dlaed8_(integer *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, doublereal *,
integer *, doublereal *, integer *, integer *, integer *,
doublereal *, integer *, integer *, integer *), dlaed9_(integer *,
integer *, integer *, integer *, doublereal *, doublereal *,
integer *, doublereal *, doublereal *, doublereal *, doublereal *,
integer *, integer *), dlaeda_(integer *, integer *, integer *,
integer *, integer *, integer *, integer *, integer *, doublereal
*, doublereal *, integer *, doublereal *, doublereal *, integer *)
;
static integer idlmda;
extern /* Subroutine */ int dlamrg_(integer *, integer *, doublereal *,
integer *, integer *, integer *), xerbla_(char *, integer *);
static integer coltyp;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAED7 computes the updated eigensystem of a diagonal
matrix after modification by a rank-one symmetric matrix. This
routine is used only for the eigenproblem which requires all
eigenvalues and optionally eigenvectors of a dense symmetric matrix
that has been reduced to tridiagonal form. DLAED1 handles
the case in which all eigenvalues and eigenvectors of a symmetric
tridiagonal matrix are desired.
T = Q(in) ( D(in) + RHO * Z*Z' ) Q'(in) = Q(out) * D(out) * Q'(out)
where Z = Q'u, u is a vector of length N with ones in the
CUTPNT and CUTPNT + 1 th elements and zeros elsewhere.
The eigenvectors of the original matrix are stored in Q, and the
eigenvalues are in D. The algorithm consists of three stages:
The first stage consists of deflating the size of the problem
when there are multiple eigenvalues or if there is a zero in
the Z vector. For each such occurence the dimension of the
secular equation problem is reduced by one. This stage is
performed by the routine DLAED8.
The second stage consists of calculating the updated
eigenvalues. This is done by finding the roots of the secular
equation via the routine DLAED4 (as called by DLAED9).
This routine also calculates the eigenvectors of the current
problem.
The final stage consists of computing the updated eigenvectors
directly using the updated eigenvalues. The eigenvectors for
the current problem are multiplied with the eigenvectors from
the overall problem.
Arguments
=========
ICOMPQ (input) INTEGER
= 0: Compute eigenvalues only.
= 1: Compute eigenvectors of original dense symmetric matrix
also. On entry, Q contains the orthogonal matrix used
to reduce the original matrix to tridiagonal form.
N (input) INTEGER
The dimension of the symmetric tridiagonal matrix. N >= 0.
QSIZ (input) INTEGER
The dimension of the orthogonal matrix used to reduce
the full matrix to tridiagonal form. QSIZ >= N if ICOMPQ = 1.
TLVLS (input) INTEGER
The total number of merging levels in the overall divide and
conquer tree.
CURLVL (input) INTEGER
The current level in the overall merge routine,
0 <= CURLVL <= TLVLS.
CURPBM (input) INTEGER
The current problem in the current level in the overall
merge routine (counting from upper left to lower right).
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, the eigenvalues of the rank-1-perturbed matrix.
On exit, the eigenvalues of the repaired matrix.
Q (input/output) DOUBLE PRECISION array, dimension (LDQ, N)
On entry, the eigenvectors of the rank-1-perturbed matrix.
On exit, the eigenvectors of the repaired tridiagonal matrix.
LDQ (input) INTEGER
The leading dimension of the array Q. LDQ >= max(1,N).
INDXQ (output) INTEGER array, dimension (N)
The permutation which will reintegrate the subproblem just
solved back into sorted order, i.e., D( INDXQ( I = 1, N ) )
will be in ascending order.
RHO (input) DOUBLE PRECISION
The subdiagonal element used to create the rank-1
modification.
CUTPNT (input) INTEGER
Contains the location of the last eigenvalue in the leading
sub-matrix. min(1,N) <= CUTPNT <= N.
QSTORE (input/output) DOUBLE PRECISION array, dimension (N**2+1)
Stores eigenvectors of submatrices encountered during
divide and conquer, packed together. QPTR points to
beginning of the submatrices.
QPTR (input/output) INTEGER array, dimension (N+2)
List of indices pointing to beginning of submatrices stored
in QSTORE. The submatrices are numbered starting at the
bottom left of the divide and conquer tree, from left to
right and bottom to top.
PRMPTR (input) INTEGER array, dimension (N lg N)
Contains a list of pointers which indicate where in PERM a
level's permutation is stored. PRMPTR(i+1) - PRMPTR(i)
indicates the size of the permutation and also the size of
the full, non-deflated problem.
PERM (input) INTEGER array, dimension (N lg N)
Contains the permutations (from deflation and sorting) to be
applied to each eigenblock.
GIVPTR (input) INTEGER array, dimension (N lg N)
Contains a list of pointers which indicate where in GIVCOL a
level's Givens rotations are stored. GIVPTR(i+1) - GIVPTR(i)
indicates the number of Givens rotations.
GIVCOL (input) INTEGER array, dimension (2, N lg N)
Each pair of numbers indicates a pair of columns to take place
in a Givens rotation.
GIVNUM (input) DOUBLE PRECISION array, dimension (2, N lg N)
Each number indicates the S value to be used in the
corresponding Givens rotation.
WORK (workspace) DOUBLE PRECISION array, dimension (3*N+QSIZ*N)
IWORK (workspace) INTEGER array, dimension (4*N)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, an eigenvalue did not converge
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
--indxq;
--qstore;
--qptr;
--prmptr;
--perm;
--givptr;
givcol -= 3;
givnum -= 3;
--work;
--iwork;
/* Function Body */
*info = 0;
if (*icompq < 0 || *icompq > 1) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*icompq == 1 && *qsiz < *n) {
*info = -4;
} else if (*ldq < max(1,*n)) {
*info = -9;
} else if (min(1,*n) > *cutpnt || *n < *cutpnt) {
*info = -12;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAED7", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/*
The following values are for bookkeeping purposes only. They are
integer pointers which indicate the portion of the workspace
used by a particular array in DLAED8 and DLAED9.
*/
if (*icompq == 1) {
ldq2 = *qsiz;
} else {
ldq2 = *n;
}
iz = 1;
idlmda = iz + *n;
iw = idlmda + *n;
iq2 = iw + *n;
is = iq2 + *n * ldq2;
indx = 1;
indxc = indx + *n;
coltyp = indxc + *n;
indxp = coltyp + *n;
/*
Form the z-vector which consists of the last row of Q_1 and the
first row of Q_2.
*/
ptr = pow_ii(&c__2, tlvls) + 1;
i__1 = *curlvl - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
i__2 = *tlvls - i__;
ptr += pow_ii(&c__2, &i__2);
/* L10: */
}
curr = ptr + *curpbm;
dlaeda_(n, tlvls, curlvl, curpbm, &prmptr[1], &perm[1], &givptr[1], &
givcol[3], &givnum[3], &qstore[1], &qptr[1], &work[iz], &work[iz
+ *n], info);
/*
When solving the final problem, we no longer need the stored data,
so we will overwrite the data from this level onto the previously
used storage space.
*/
if (*curlvl == *tlvls) {
qptr[curr] = 1;
prmptr[curr] = 1;
givptr[curr] = 1;
}
/* Sort and Deflate eigenvalues. */
dlaed8_(icompq, &k, n, qsiz, &d__[1], &q[q_offset], ldq, &indxq[1], rho,
cutpnt, &work[iz], &work[idlmda], &work[iq2], &ldq2, &work[iw], &
perm[prmptr[curr]], &givptr[curr + 1], &givcol[(givptr[curr] << 1)
+ 1], &givnum[(givptr[curr] << 1) + 1], &iwork[indxp], &iwork[
indx], info);
prmptr[curr + 1] = prmptr[curr] + *n;
givptr[curr + 1] += givptr[curr];
/* Solve Secular Equation. */
if (k != 0) {
dlaed9_(&k, &c__1, &k, n, &d__[1], &work[is], &k, rho, &work[idlmda],
&work[iw], &qstore[qptr[curr]], &k, info);
if (*info != 0) {
goto L30;
}
if (*icompq == 1) {
dgemm_("N", "N", qsiz, &k, &k, &c_b15, &work[iq2], &ldq2, &qstore[
qptr[curr]], &k, &c_b29, &q[q_offset], ldq);
}
/* Computing 2nd power */
i__1 = k;
qptr[curr + 1] = qptr[curr] + i__1 * i__1;
/* Prepare the INDXQ sorting permutation. */
n1 = k;
n2 = *n - k;
dlamrg_(&n1, &n2, &d__[1], &c__1, &c_n1, &indxq[1]);
} else {
qptr[curr + 1] = qptr[curr];
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
indxq[i__] = i__;
/* L20: */
}
}
L30:
return 0;
/* End of DLAED7 */
} /* dlaed7_ */
/* Subroutine */ int dlaed8_(integer *icompq, integer *k, integer *n, integer
*qsiz, doublereal *d__, doublereal *q, integer *ldq, integer *indxq,
doublereal *rho, integer *cutpnt, doublereal *z__, doublereal *dlamda,
doublereal *q2, integer *ldq2, doublereal *w, integer *perm, integer
*givptr, integer *givcol, doublereal *givnum, integer *indxp, integer
*indx, integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, q2_dim1, q2_offset, i__1;
doublereal d__1;
/* Local variables */
static doublereal c__;
static integer i__, j;
static doublereal s, t;
static integer k2, n1, n2, jp, n1p1;
static doublereal eps, tau, tol;
static integer jlam, imax, jmax;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *), dscal_(
integer *, doublereal *, doublereal *, integer *), dcopy_(integer
*, doublereal *, integer *, doublereal *, integer *);
extern integer idamax_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dlamrg_(integer *, integer *, doublereal *,
integer *, integer *, integer *), dlacpy_(char *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLAED8 merges the two sets of eigenvalues together into a single
sorted set. Then it tries to deflate the size of the problem.
There are two ways in which deflation can occur: when two or more
eigenvalues are close together or if there is a tiny element in the
Z vector. For each such occurrence the order of the related secular
equation problem is reduced by one.
Arguments
=========
ICOMPQ (input) INTEGER
= 0: Compute eigenvalues only.
= 1: Compute eigenvectors of original dense symmetric matrix
also. On entry, Q contains the orthogonal matrix used
to reduce the original matrix to tridiagonal form.
K (output) INTEGER
The number of non-deflated eigenvalues, and the order of the
related secular equation.
N (input) INTEGER
The dimension of the symmetric tridiagonal matrix. N >= 0.
QSIZ (input) INTEGER
The dimension of the orthogonal matrix used to reduce
the full matrix to tridiagonal form. QSIZ >= N if ICOMPQ = 1.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, the eigenvalues of the two submatrices to be
combined. On exit, the trailing (N-K) updated eigenvalues
(those which were deflated) sorted into increasing order.
Q (input/output) DOUBLE PRECISION array, dimension (LDQ,N)
If ICOMPQ = 0, Q is not referenced. Otherwise,
on entry, Q contains the eigenvectors of the partially solved
system which has been previously updated in matrix
multiplies with other partially solved eigensystems.
On exit, Q contains the trailing (N-K) updated eigenvectors
(those which were deflated) in its last N-K columns.
LDQ (input) INTEGER
The leading dimension of the array Q. LDQ >= max(1,N).
INDXQ (input) INTEGER array, dimension (N)
The permutation which separately sorts the two sub-problems
in D into ascending order. Note that elements in the second
half of this permutation must first have CUTPNT added to
their values in order to be accurate.
RHO (input/output) DOUBLE PRECISION
On entry, the off-diagonal element associated with the rank-1
cut which originally split the two submatrices which are now
being recombined.
On exit, RHO has been modified to the value required by
DLAED3.
CUTPNT (input) INTEGER
The location of the last eigenvalue in the leading
sub-matrix. min(1,N) <= CUTPNT <= N.
Z (input) DOUBLE PRECISION array, dimension (N)
On entry, Z contains the updating vector (the last row of
the first sub-eigenvector matrix and the first row of the
second sub-eigenvector matrix).
On exit, the contents of Z are destroyed by the updating
process.
DLAMDA (output) DOUBLE PRECISION array, dimension (N)
A copy of the first K eigenvalues which will be used by
DLAED3 to form the secular equation.
Q2 (output) DOUBLE PRECISION array, dimension (LDQ2,N)
If ICOMPQ = 0, Q2 is not referenced. Otherwise,
a copy of the first K eigenvectors which will be used by
DLAED7 in a matrix multiply (DGEMM) to update the new
eigenvectors.
LDQ2 (input) INTEGER
The leading dimension of the array Q2. LDQ2 >= max(1,N).
W (output) DOUBLE PRECISION array, dimension (N)
The first k values of the final deflation-altered z-vector and
will be passed to DLAED3.
PERM (output) INTEGER array, dimension (N)
The permutations (from deflation and sorting) to be applied
to each eigenblock.
GIVPTR (output) INTEGER
The number of Givens rotations which took place in this
subproblem.
GIVCOL (output) INTEGER array, dimension (2, N)
Each pair of numbers indicates a pair of columns to take place
in a Givens rotation.
GIVNUM (output) DOUBLE PRECISION array, dimension (2, N)
Each number indicates the S value to be used in the
corresponding Givens rotation.
INDXP (workspace) INTEGER array, dimension (N)
The permutation used to place deflated values of D at the end
of the array. INDXP(1:K) points to the nondeflated D-values
and INDXP(K+1:N) points to the deflated eigenvalues.
INDX (workspace) INTEGER array, dimension (N)
The permutation used to sort the contents of D into ascending
order.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
--indxq;
--z__;
--dlamda;
q2_dim1 = *ldq2;
q2_offset = 1 + q2_dim1;
q2 -= q2_offset;
--w;
--perm;
givcol -= 3;
givnum -= 3;
--indxp;
--indx;
/* Function Body */
*info = 0;
if (*icompq < 0 || *icompq > 1) {
*info = -1;
} else if (*n < 0) {
*info = -3;
} else if (*icompq == 1 && *qsiz < *n) {
*info = -4;
} else if (*ldq < max(1,*n)) {
*info = -7;
} else if (*cutpnt < min(1,*n) || *cutpnt > *n) {
*info = -10;
} else if (*ldq2 < max(1,*n)) {
*info = -14;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAED8", &i__1);
return 0;
}
/*
Need to initialize GIVPTR to O here in case of quick exit
to prevent an unspecified code behavior (usually sigfault)
when IWORK array on entry to *stedc is not zeroed
(or at least some IWORK entries which used in *laed7 for GIVPTR).
*/
*givptr = 0;
/* Quick return if possible */
if (*n == 0) {
return 0;
}
n1 = *cutpnt;
n2 = *n - n1;
n1p1 = n1 + 1;
if (*rho < 0.) {
dscal_(&n2, &c_b151, &z__[n1p1], &c__1);
}
/* Normalize z so that norm(z) = 1 */
t = 1. / sqrt(2.);
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
indx[j] = j;
/* L10: */
}
dscal_(n, &t, &z__[1], &c__1);
*rho = (d__1 = *rho * 2., abs(d__1));
/* Sort the eigenvalues into increasing order */
i__1 = *n;
for (i__ = *cutpnt + 1; i__ <= i__1; ++i__) {
indxq[i__] += *cutpnt;
/* L20: */
}
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
dlamda[i__] = d__[indxq[i__]];
w[i__] = z__[indxq[i__]];
/* L30: */
}
i__ = 1;
j = *cutpnt + 1;
dlamrg_(&n1, &n2, &dlamda[1], &c__1, &c__1, &indx[1]);
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
d__[i__] = dlamda[indx[i__]];
z__[i__] = w[indx[i__]];
/* L40: */
}
/* Calculate the allowable deflation tolerence */
imax = idamax_(n, &z__[1], &c__1);
jmax = idamax_(n, &d__[1], &c__1);
eps = EPSILON;
tol = eps * 8. * (d__1 = d__[jmax], abs(d__1));
/*
If the rank-1 modifier is small enough, no more needs to be done
except to reorganize Q so that its columns correspond with the
elements in D.
*/
if (*rho * (d__1 = z__[imax], abs(d__1)) <= tol) {
*k = 0;
if (*icompq == 0) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
perm[j] = indxq[indx[j]];
/* L50: */
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
perm[j] = indxq[indx[j]];
dcopy_(qsiz, &q[perm[j] * q_dim1 + 1], &c__1, &q2[j * q2_dim1
+ 1], &c__1);
/* L60: */
}
dlacpy_("A", qsiz, n, &q2[q2_dim1 + 1], ldq2, &q[q_dim1 + 1], ldq);
}
return 0;
}
/*
If there are multiple eigenvalues then the problem deflates. Here
the number of equal eigenvalues are found. As each equal
eigenvalue is found, an elementary reflector is computed to rotate
the corresponding eigensubspace so that the corresponding
components of Z are zero in this new basis.
*/
*k = 0;
k2 = *n + 1;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (*rho * (d__1 = z__[j], abs(d__1)) <= tol) {
/* Deflate due to small z component. */
--k2;
indxp[k2] = j;
if (j == *n) {
goto L110;
}
} else {
jlam = j;
goto L80;
}
/* L70: */
}
L80:
++j;
if (j > *n) {
goto L100;
}
if (*rho * (d__1 = z__[j], abs(d__1)) <= tol) {
/* Deflate due to small z component. */
--k2;
indxp[k2] = j;
} else {
/* Check if eigenvalues are close enough to allow deflation. */
s = z__[jlam];
c__ = z__[j];
/*
Find sqrt(a**2+b**2) without overflow or
destructive underflow.
*/
tau = dlapy2_(&c__, &s);
t = d__[j] - d__[jlam];
c__ /= tau;
s = -s / tau;
if ((d__1 = t * c__ * s, abs(d__1)) <= tol) {
/* Deflation is possible. */
z__[j] = tau;
z__[jlam] = 0.;
/* Record the appropriate Givens rotation */
++(*givptr);
givcol[(*givptr << 1) + 1] = indxq[indx[jlam]];
givcol[(*givptr << 1) + 2] = indxq[indx[j]];
givnum[(*givptr << 1) + 1] = c__;
givnum[(*givptr << 1) + 2] = s;
if (*icompq == 1) {
drot_(qsiz, &q[indxq[indx[jlam]] * q_dim1 + 1], &c__1, &q[
indxq[indx[j]] * q_dim1 + 1], &c__1, &c__, &s);
}
t = d__[jlam] * c__ * c__ + d__[j] * s * s;
d__[j] = d__[jlam] * s * s + d__[j] * c__ * c__;
d__[jlam] = t;
--k2;
i__ = 1;
L90:
if (k2 + i__ <= *n) {
if (d__[jlam] < d__[indxp[k2 + i__]]) {
indxp[k2 + i__ - 1] = indxp[k2 + i__];
indxp[k2 + i__] = jlam;
++i__;
goto L90;
} else {
indxp[k2 + i__ - 1] = jlam;
}
} else {
indxp[k2 + i__ - 1] = jlam;
}
jlam = j;
} else {
++(*k);
w[*k] = z__[jlam];
dlamda[*k] = d__[jlam];
indxp[*k] = jlam;
jlam = j;
}
}
goto L80;
L100:
/* Record the last eigenvalue. */
++(*k);
w[*k] = z__[jlam];
dlamda[*k] = d__[jlam];
indxp[*k] = jlam;
L110:
/*
Sort the eigenvalues and corresponding eigenvectors into DLAMDA
and Q2 respectively. The eigenvalues/vectors which were not
deflated go into the first K slots of DLAMDA and Q2 respectively,
while those which were deflated go into the last N - K slots.
*/
if (*icompq == 0) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
jp = indxp[j];
dlamda[j] = d__[jp];
perm[j] = indxq[indx[jp]];
/* L120: */
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
jp = indxp[j];
dlamda[j] = d__[jp];
perm[j] = indxq[indx[jp]];
dcopy_(qsiz, &q[perm[j] * q_dim1 + 1], &c__1, &q2[j * q2_dim1 + 1]
, &c__1);
/* L130: */
}
}
/*
The deflated eigenvalues and their corresponding vectors go back
into the last N - K slots of D and Q respectively.
*/
if (*k < *n) {
if (*icompq == 0) {
i__1 = *n - *k;
dcopy_(&i__1, &dlamda[*k + 1], &c__1, &d__[*k + 1], &c__1);
} else {
i__1 = *n - *k;
dcopy_(&i__1, &dlamda[*k + 1], &c__1, &d__[*k + 1], &c__1);
i__1 = *n - *k;
dlacpy_("A", qsiz, &i__1, &q2[(*k + 1) * q2_dim1 + 1], ldq2, &q[(*
k + 1) * q_dim1 + 1], ldq);
}
}
return 0;
/* End of DLAED8 */
} /* dlaed8_ */
/* Subroutine */ int dlaed9_(integer *k, integer *kstart, integer *kstop,
integer *n, doublereal *d__, doublereal *q, integer *ldq, doublereal *
rho, doublereal *dlamda, doublereal *w, doublereal *s, integer *lds,
integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, s_dim1, s_offset, i__1, i__2;
doublereal d__1;
/* Local variables */
static integer i__, j;
static doublereal temp;
extern doublereal dnrm2_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *), dlaed4_(integer *, integer *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *);
extern doublereal dlamc3_(doublereal *, doublereal *);
extern /* Subroutine */ int xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAED9 finds the roots of the secular equation, as defined by the
values in D, Z, and RHO, between KSTART and KSTOP. It makes the
appropriate calls to DLAED4 and then stores the new matrix of
eigenvectors for use in calculating the next level of Z vectors.
Arguments
=========
K (input) INTEGER
The number of terms in the rational function to be solved by
DLAED4. K >= 0.
KSTART (input) INTEGER
KSTOP (input) INTEGER
The updated eigenvalues Lambda(I), KSTART <= I <= KSTOP
are to be computed. 1 <= KSTART <= KSTOP <= K.
N (input) INTEGER
The number of rows and columns in the Q matrix.
N >= K (delation may result in N > K).
D (output) DOUBLE PRECISION array, dimension (N)
D(I) contains the updated eigenvalues
for KSTART <= I <= KSTOP.
Q (workspace) DOUBLE PRECISION array, dimension (LDQ,N)
LDQ (input) INTEGER
The leading dimension of the array Q. LDQ >= max( 1, N ).
RHO (input) DOUBLE PRECISION
The value of the parameter in the rank one update equation.
RHO >= 0 required.
DLAMDA (input) DOUBLE PRECISION array, dimension (K)
The first K elements of this array contain the old roots
of the deflated updating problem. These are the poles
of the secular equation.
W (input) DOUBLE PRECISION array, dimension (K)
The first K elements of this array contain the components
of the deflation-adjusted updating vector.
S (output) DOUBLE PRECISION array, dimension (LDS, K)
Will contain the eigenvectors of the repaired matrix which
will be stored for subsequent Z vector calculation and
multiplied by the previously accumulated eigenvectors
to update the system.
LDS (input) INTEGER
The leading dimension of S. LDS >= max( 1, K ).
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, an eigenvalue did not converge
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
--dlamda;
--w;
s_dim1 = *lds;
s_offset = 1 + s_dim1;
s -= s_offset;
/* Function Body */
*info = 0;
if (*k < 0) {
*info = -1;
} else if (*kstart < 1 || *kstart > max(1,*k)) {
*info = -2;
} else if (max(1,*kstop) < *kstart || *kstop > max(1,*k)) {
*info = -3;
} else if (*n < *k) {
*info = -4;
} else if (*ldq < max(1,*k)) {
*info = -7;
} else if (*lds < max(1,*k)) {
*info = -12;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAED9", &i__1);
return 0;
}
/* Quick return if possible */
if (*k == 0) {
return 0;
}
/*
Modify values DLAMDA(i) to make sure all DLAMDA(i)-DLAMDA(j) can
be computed with high relative accuracy (barring over/underflow).
This is a problem on machines without a guard digit in
add/subtract (Cray XMP, Cray YMP, Cray C 90 and Cray 2).
The following code replaces DLAMDA(I) by 2*DLAMDA(I)-DLAMDA(I),
which on any of these machines zeros out the bottommost
bit of DLAMDA(I) if it is 1; this makes the subsequent
subtractions DLAMDA(I)-DLAMDA(J) unproblematic when cancellation
occurs. On binary machines with a guard digit (almost all
machines) it does not change DLAMDA(I) at all. On hexadecimal
and decimal machines with a guard digit, it slightly
changes the bottommost bits of DLAMDA(I). It does not account
for hexadecimal or decimal machines without guard digits
(we know of none). We use a subroutine call to compute
2*DLAMBDA(I) to prevent optimizing compilers from eliminating
this code.
*/
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
dlamda[i__] = dlamc3_(&dlamda[i__], &dlamda[i__]) - dlamda[i__];
/* L10: */
}
i__1 = *kstop;
for (j = *kstart; j <= i__1; ++j) {
dlaed4_(k, &j, &dlamda[1], &w[1], &q[j * q_dim1 + 1], rho, &d__[j],
info);
/* If the zero finder fails, the computation is terminated. */
if (*info != 0) {
goto L120;
}
/* L20: */
}
if (*k == 1 || *k == 2) {
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
i__2 = *k;
for (j = 1; j <= i__2; ++j) {
s[j + i__ * s_dim1] = q[j + i__ * q_dim1];
/* L30: */
}
/* L40: */
}
goto L120;
}
/* Compute updated W. */
dcopy_(k, &w[1], &c__1, &s[s_offset], &c__1);
/* Initialize W(I) = Q(I,I) */
i__1 = *ldq + 1;
dcopy_(k, &q[q_offset], &i__1, &w[1], &c__1);
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = j - 1;
for (i__ = 1; i__ <= i__2; ++i__) {
w[i__] *= q[i__ + j * q_dim1] / (dlamda[i__] - dlamda[j]);
/* L50: */
}
i__2 = *k;
for (i__ = j + 1; i__ <= i__2; ++i__) {
w[i__] *= q[i__ + j * q_dim1] / (dlamda[i__] - dlamda[j]);
/* L60: */
}
/* L70: */
}
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
d__1 = sqrt(-w[i__]);
w[i__] = d_sign(&d__1, &s[i__ + s_dim1]);
/* L80: */
}
/* Compute eigenvectors of the modified rank-1 modification. */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = *k;
for (i__ = 1; i__ <= i__2; ++i__) {
q[i__ + j * q_dim1] = w[i__] / q[i__ + j * q_dim1];
/* L90: */
}
temp = dnrm2_(k, &q[j * q_dim1 + 1], &c__1);
i__2 = *k;
for (i__ = 1; i__ <= i__2; ++i__) {
s[i__ + j * s_dim1] = q[i__ + j * q_dim1] / temp;
/* L100: */
}
/* L110: */
}
L120:
return 0;
/* End of DLAED9 */
} /* dlaed9_ */
/* Subroutine */ int dlaeda_(integer *n, integer *tlvls, integer *curlvl,
integer *curpbm, integer *prmptr, integer *perm, integer *givptr,
integer *givcol, doublereal *givnum, doublereal *q, integer *qptr,
doublereal *z__, doublereal *ztemp, integer *info)
{
/* System generated locals */
integer i__1, i__2, i__3;
/* Local variables */
static integer i__, k, mid, ptr;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *);
static integer curr, bsiz1, bsiz2, psiz1, psiz2, zptr1;
extern /* Subroutine */ int dgemv_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *), dcopy_(integer *,
doublereal *, integer *, doublereal *, integer *), xerbla_(char *,
integer *);
/*
-- LAPACK routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLAEDA computes the Z vector corresponding to the merge step in the
CURLVLth step of the merge process with TLVLS steps for the CURPBMth
problem.
Arguments
=========
N (input) INTEGER
The dimension of the symmetric tridiagonal matrix. N >= 0.
TLVLS (input) INTEGER
The total number of merging levels in the overall divide and
conquer tree.
CURLVL (input) INTEGER
The current level in the overall merge routine,
0 <= curlvl <= tlvls.
CURPBM (input) INTEGER
The current problem in the current level in the overall
merge routine (counting from upper left to lower right).
PRMPTR (input) INTEGER array, dimension (N lg N)
Contains a list of pointers which indicate where in PERM a
level's permutation is stored. PRMPTR(i+1) - PRMPTR(i)
indicates the size of the permutation and incidentally the
size of the full, non-deflated problem.
PERM (input) INTEGER array, dimension (N lg N)
Contains the permutations (from deflation and sorting) to be
applied to each eigenblock.
GIVPTR (input) INTEGER array, dimension (N lg N)
Contains a list of pointers which indicate where in GIVCOL a
level's Givens rotations are stored. GIVPTR(i+1) - GIVPTR(i)
indicates the number of Givens rotations.
GIVCOL (input) INTEGER array, dimension (2, N lg N)
Each pair of numbers indicates a pair of columns to take place
in a Givens rotation.
GIVNUM (input) DOUBLE PRECISION array, dimension (2, N lg N)
Each number indicates the S value to be used in the
corresponding Givens rotation.
Q (input) DOUBLE PRECISION array, dimension (N**2)
Contains the square eigenblocks from previous levels, the
starting positions for blocks are given by QPTR.
QPTR (input) INTEGER array, dimension (N+2)
Contains a list of pointers which indicate where in Q an
eigenblock is stored. SQRT( QPTR(i+1) - QPTR(i) ) indicates
the size of the block.
Z (output) DOUBLE PRECISION array, dimension (N)
On output this vector contains the updating vector (the last
row of the first sub-eigenvector matrix and the first row of
the second sub-eigenvector matrix).
ZTEMP (workspace) DOUBLE PRECISION array, dimension (N)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--ztemp;
--z__;
--qptr;
--q;
givnum -= 3;
givcol -= 3;
--givptr;
--perm;
--prmptr;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -1;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAEDA", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/* Determine location of first number in second half. */
mid = *n / 2 + 1;
/* Gather last/first rows of appropriate eigenblocks into center of Z */
ptr = 1;
/*
Determine location of lowest level subproblem in the full storage
scheme
*/
i__1 = *curlvl - 1;
curr = ptr + *curpbm * pow_ii(&c__2, curlvl) + pow_ii(&c__2, &i__1) - 1;
/*
Determine size of these matrices. We add HALF to the value of
the SQRT in case the machine underestimates one of these square
roots.
*/
bsiz1 = (integer) (sqrt((doublereal) (qptr[curr + 1] - qptr[curr])) + .5);
bsiz2 = (integer) (sqrt((doublereal) (qptr[curr + 2] - qptr[curr + 1])) +
.5);
i__1 = mid - bsiz1 - 1;
for (k = 1; k <= i__1; ++k) {
z__[k] = 0.;
/* L10: */
}
dcopy_(&bsiz1, &q[qptr[curr] + bsiz1 - 1], &bsiz1, &z__[mid - bsiz1], &
c__1);
dcopy_(&bsiz2, &q[qptr[curr + 1]], &bsiz2, &z__[mid], &c__1);
i__1 = *n;
for (k = mid + bsiz2; k <= i__1; ++k) {
z__[k] = 0.;
/* L20: */
}
/*
Loop through remaining levels 1 -> CURLVL applying the Givens
rotations and permutation and then multiplying the center matrices
against the current Z.
*/
ptr = pow_ii(&c__2, tlvls) + 1;
i__1 = *curlvl - 1;
for (k = 1; k <= i__1; ++k) {
i__2 = *curlvl - k;
i__3 = *curlvl - k - 1;
curr = ptr + *curpbm * pow_ii(&c__2, &i__2) + pow_ii(&c__2, &i__3) -
1;
psiz1 = prmptr[curr + 1] - prmptr[curr];
psiz2 = prmptr[curr + 2] - prmptr[curr + 1];
zptr1 = mid - psiz1;
/* Apply Givens at CURR and CURR+1 */
i__2 = givptr[curr + 1] - 1;
for (i__ = givptr[curr]; i__ <= i__2; ++i__) {
drot_(&c__1, &z__[zptr1 + givcol[(i__ << 1) + 1] - 1], &c__1, &
z__[zptr1 + givcol[(i__ << 1) + 2] - 1], &c__1, &givnum[(
i__ << 1) + 1], &givnum[(i__ << 1) + 2]);
/* L30: */
}
i__2 = givptr[curr + 2] - 1;
for (i__ = givptr[curr + 1]; i__ <= i__2; ++i__) {
drot_(&c__1, &z__[mid - 1 + givcol[(i__ << 1) + 1]], &c__1, &z__[
mid - 1 + givcol[(i__ << 1) + 2]], &c__1, &givnum[(i__ <<
1) + 1], &givnum[(i__ << 1) + 2]);
/* L40: */
}
psiz1 = prmptr[curr + 1] - prmptr[curr];
psiz2 = prmptr[curr + 2] - prmptr[curr + 1];
i__2 = psiz1 - 1;
for (i__ = 0; i__ <= i__2; ++i__) {
ztemp[i__ + 1] = z__[zptr1 + perm[prmptr[curr] + i__] - 1];
/* L50: */
}
i__2 = psiz2 - 1;
for (i__ = 0; i__ <= i__2; ++i__) {
ztemp[psiz1 + i__ + 1] = z__[mid + perm[prmptr[curr + 1] + i__] -
1];
/* L60: */
}
/*
Multiply Blocks at CURR and CURR+1
Determine size of these matrices. We add HALF to the value of
the SQRT in case the machine underestimates one of these
square roots.
*/
bsiz1 = (integer) (sqrt((doublereal) (qptr[curr + 1] - qptr[curr])) +
.5);
bsiz2 = (integer) (sqrt((doublereal) (qptr[curr + 2] - qptr[curr + 1])
) + .5);
if (bsiz1 > 0) {
dgemv_("T", &bsiz1, &bsiz1, &c_b15, &q[qptr[curr]], &bsiz1, &
ztemp[1], &c__1, &c_b29, &z__[zptr1], &c__1);
}
i__2 = psiz1 - bsiz1;
dcopy_(&i__2, &ztemp[bsiz1 + 1], &c__1, &z__[zptr1 + bsiz1], &c__1);
if (bsiz2 > 0) {
dgemv_("T", &bsiz2, &bsiz2, &c_b15, &q[qptr[curr + 1]], &bsiz2, &
ztemp[psiz1 + 1], &c__1, &c_b29, &z__[mid], &c__1);
}
i__2 = psiz2 - bsiz2;
dcopy_(&i__2, &ztemp[psiz1 + bsiz2 + 1], &c__1, &z__[mid + bsiz2], &
c__1);
i__2 = *tlvls - k;
ptr += pow_ii(&c__2, &i__2);
/* L70: */
}
return 0;
/* End of DLAEDA */
} /* dlaeda_ */
/* Subroutine */ int dlaev2_(doublereal *a, doublereal *b, doublereal *c__,
doublereal *rt1, doublereal *rt2, doublereal *cs1, doublereal *sn1)
{
/* System generated locals */
doublereal d__1;
/* Local variables */
static doublereal ab, df, cs, ct, tb, sm, tn, rt, adf, acs;
static integer sgn1, sgn2;
static doublereal acmn, acmx;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAEV2 computes the eigendecomposition of a 2-by-2 symmetric matrix
[ A B ]
[ B C ].
On return, RT1 is the eigenvalue of larger absolute value, RT2 is the
eigenvalue of smaller absolute value, and (CS1,SN1) is the unit right
eigenvector for RT1, giving the decomposition
[ CS1 SN1 ] [ A B ] [ CS1 -SN1 ] = [ RT1 0 ]
[-SN1 CS1 ] [ B C ] [ SN1 CS1 ] [ 0 RT2 ].
Arguments
=========
A (input) DOUBLE PRECISION
The (1,1) element of the 2-by-2 matrix.
B (input) DOUBLE PRECISION
The (1,2) element and the conjugate of the (2,1) element of
the 2-by-2 matrix.
C (input) DOUBLE PRECISION
The (2,2) element of the 2-by-2 matrix.
RT1 (output) DOUBLE PRECISION
The eigenvalue of larger absolute value.
RT2 (output) DOUBLE PRECISION
The eigenvalue of smaller absolute value.
CS1 (output) DOUBLE PRECISION
SN1 (output) DOUBLE PRECISION
The vector (CS1, SN1) is a unit right eigenvector for RT1.
Further Details
===============
RT1 is accurate to a few ulps barring over/underflow.
RT2 may be inaccurate if there is massive cancellation in the
determinant A*C-B*B; higher precision or correctly rounded or
correctly truncated arithmetic would be needed to compute RT2
accurately in all cases.
CS1 and SN1 are accurate to a few ulps barring over/underflow.
Overflow is possible only if RT1 is within a factor of 5 of overflow.
Underflow is harmless if the input data is 0 or exceeds
underflow_threshold / macheps.
=====================================================================
Compute the eigenvalues
*/
sm = *a + *c__;
df = *a - *c__;
adf = abs(df);
tb = *b + *b;
ab = abs(tb);
if (abs(*a) > abs(*c__)) {
acmx = *a;
acmn = *c__;
} else {
acmx = *c__;
acmn = *a;
}
if (adf > ab) {
/* Computing 2nd power */
d__1 = ab / adf;
rt = adf * sqrt(d__1 * d__1 + 1.);
} else if (adf < ab) {
/* Computing 2nd power */
d__1 = adf / ab;
rt = ab * sqrt(d__1 * d__1 + 1.);
} else {
/* Includes case AB=ADF=0 */
rt = ab * sqrt(2.);
}
if (sm < 0.) {
*rt1 = (sm - rt) * .5;
sgn1 = -1;
/*
Order of execution important.
To get fully accurate smaller eigenvalue,
next line needs to be executed in higher precision.
*/
*rt2 = acmx / *rt1 * acmn - *b / *rt1 * *b;
} else if (sm > 0.) {
*rt1 = (sm + rt) * .5;
sgn1 = 1;
/*
Order of execution important.
To get fully accurate smaller eigenvalue,
next line needs to be executed in higher precision.
*/
*rt2 = acmx / *rt1 * acmn - *b / *rt1 * *b;
} else {
/* Includes case RT1 = RT2 = 0 */
*rt1 = rt * .5;
*rt2 = rt * -.5;
sgn1 = 1;
}
/* Compute the eigenvector */
if (df >= 0.) {
cs = df + rt;
sgn2 = 1;
} else {
cs = df - rt;
sgn2 = -1;
}
acs = abs(cs);
if (acs > ab) {
ct = -tb / cs;
*sn1 = 1. / sqrt(ct * ct + 1.);
*cs1 = ct * *sn1;
} else {
if (ab == 0.) {
*cs1 = 1.;
*sn1 = 0.;
} else {
tn = -cs / tb;
*cs1 = 1. / sqrt(tn * tn + 1.);
*sn1 = tn * *cs1;
}
}
if (sgn1 == sgn2) {
tn = *cs1;
*cs1 = -(*sn1);
*sn1 = tn;
}
return 0;
/* End of DLAEV2 */
} /* dlaev2_ */
/* Subroutine */ int dlaexc_(logical *wantq, integer *n, doublereal *t,
integer *ldt, doublereal *q, integer *ldq, integer *j1, integer *n1,
integer *n2, doublereal *work, integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, t_dim1, t_offset, i__1;
doublereal d__1, d__2, d__3;
/* Local variables */
static doublereal d__[16] /* was [4][4] */;
static integer k;
static doublereal u[3], x[4] /* was [2][2] */;
static integer j2, j3, j4;
static doublereal u1[3], u2[3];
static integer nd;
static doublereal cs, t11, t22, t33, sn, wi1, wi2, wr1, wr2, eps, tau,
tau1, tau2;
static integer ierr;
static doublereal temp;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *);
static doublereal scale, dnorm, xnorm;
extern /* Subroutine */ int dlanv2_(doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *), dlasy2_(
logical *, logical *, integer *, integer *, integer *, doublereal
*, integer *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *);
extern doublereal dlamch_(char *), dlange_(char *, integer *,
integer *, doublereal *, integer *, doublereal *);
extern /* Subroutine */ int dlarfg_(integer *, doublereal *, doublereal *,
integer *, doublereal *), dlacpy_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *),
dlartg_(doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *), dlarfx_(char *, integer *, integer *, doublereal *,
doublereal *, doublereal *, integer *, doublereal *);
static doublereal thresh, smlnum;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLAEXC swaps adjacent diagonal blocks T11 and T22 of order 1 or 2 in
an upper quasi-triangular matrix T by an orthogonal similarity
transformation.
T must be in Schur canonical form, that is, block upper triangular
with 1-by-1 and 2-by-2 diagonal blocks; each 2-by-2 diagonal block
has its diagonal elemnts equal and its off-diagonal elements of
opposite sign.
Arguments
=========
WANTQ (input) LOGICAL
= .TRUE. : accumulate the transformation in the matrix Q;
= .FALSE.: do not accumulate the transformation.
N (input) INTEGER
The order of the matrix T. N >= 0.
T (input/output) DOUBLE PRECISION array, dimension (LDT,N)
On entry, the upper quasi-triangular matrix T, in Schur
canonical form.
On exit, the updated matrix T, again in Schur canonical form.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= max(1,N).
Q (input/output) DOUBLE PRECISION array, dimension (LDQ,N)
On entry, if WANTQ is .TRUE., the orthogonal matrix Q.
On exit, if WANTQ is .TRUE., the updated matrix Q.
If WANTQ is .FALSE., Q is not referenced.
LDQ (input) INTEGER
The leading dimension of the array Q.
LDQ >= 1; and if WANTQ is .TRUE., LDQ >= N.
J1 (input) INTEGER
The index of the first row of the first block T11.
N1 (input) INTEGER
The order of the first block T11. N1 = 0, 1 or 2.
N2 (input) INTEGER
The order of the second block T22. N2 = 0, 1 or 2.
WORK (workspace) DOUBLE PRECISION array, dimension (N)
INFO (output) INTEGER
= 0: successful exit
= 1: the transformed matrix T would be too far from Schur
form; the blocks are not swapped and T and Q are
unchanged.
=====================================================================
*/
/* Parameter adjustments */
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
--work;
/* Function Body */
*info = 0;
/* Quick return if possible */
if (*n == 0 || *n1 == 0 || *n2 == 0) {
return 0;
}
if (*j1 + *n1 > *n) {
return 0;
}
j2 = *j1 + 1;
j3 = *j1 + 2;
j4 = *j1 + 3;
if (*n1 == 1 && *n2 == 1) {
/* Swap two 1-by-1 blocks. */
t11 = t[*j1 + *j1 * t_dim1];
t22 = t[j2 + j2 * t_dim1];
/* Determine the transformation to perform the interchange. */
d__1 = t22 - t11;
dlartg_(&t[*j1 + j2 * t_dim1], &d__1, &cs, &sn, &temp);
/* Apply transformation to the matrix T. */
if (j3 <= *n) {
i__1 = *n - *j1 - 1;
drot_(&i__1, &t[*j1 + j3 * t_dim1], ldt, &t[j2 + j3 * t_dim1],
ldt, &cs, &sn);
}
i__1 = *j1 - 1;
drot_(&i__1, &t[*j1 * t_dim1 + 1], &c__1, &t[j2 * t_dim1 + 1], &c__1,
&cs, &sn);
t[*j1 + *j1 * t_dim1] = t22;
t[j2 + j2 * t_dim1] = t11;
if (*wantq) {
/* Accumulate transformation in the matrix Q. */
drot_(n, &q[*j1 * q_dim1 + 1], &c__1, &q[j2 * q_dim1 + 1], &c__1,
&cs, &sn);
}
} else {
/*
Swapping involves at least one 2-by-2 block.
Copy the diagonal block of order N1+N2 to the local array D
and compute its norm.
*/
nd = *n1 + *n2;
dlacpy_("Full", &nd, &nd, &t[*j1 + *j1 * t_dim1], ldt, d__, &c__4);
dnorm = dlange_("Max", &nd, &nd, d__, &c__4, &work[1]);
/*
Compute machine-dependent threshold for test for accepting
swap.
*/
eps = PRECISION;
smlnum = SAFEMINIMUM / eps;
/* Computing MAX */
d__1 = eps * 10. * dnorm;
thresh = max(d__1,smlnum);
/* Solve T11*X - X*T22 = scale*T12 for X. */
dlasy2_(&c_false, &c_false, &c_n1, n1, n2, d__, &c__4, &d__[*n1 + 1 +
(*n1 + 1 << 2) - 5], &c__4, &d__[(*n1 + 1 << 2) - 4], &c__4, &
scale, x, &c__2, &xnorm, &ierr);
/* Swap the adjacent diagonal blocks. */
k = *n1 + *n1 + *n2 - 3;
switch (k) {
case 1: goto L10;
case 2: goto L20;
case 3: goto L30;
}
L10:
/*
N1 = 1, N2 = 2: generate elementary reflector H so that:
( scale, X11, X12 ) H = ( 0, 0, * )
*/
u[0] = scale;
u[1] = x[0];
u[2] = x[2];
dlarfg_(&c__3, &u[2], u, &c__1, &tau);
u[2] = 1.;
t11 = t[*j1 + *j1 * t_dim1];
/* Perform swap provisionally on diagonal block in D. */
dlarfx_("L", &c__3, &c__3, u, &tau, d__, &c__4, &work[1]);
dlarfx_("R", &c__3, &c__3, u, &tau, d__, &c__4, &work[1]);
/*
Test whether to reject swap.
Computing MAX
*/
d__2 = abs(d__[2]), d__3 = abs(d__[6]), d__2 = max(d__2,d__3), d__3 =
(d__1 = d__[10] - t11, abs(d__1));
if (max(d__2,d__3) > thresh) {
goto L50;
}
/* Accept swap: apply transformation to the entire matrix T. */
i__1 = *n - *j1 + 1;
dlarfx_("L", &c__3, &i__1, u, &tau, &t[*j1 + *j1 * t_dim1], ldt, &
work[1]);
dlarfx_("R", &j2, &c__3, u, &tau, &t[*j1 * t_dim1 + 1], ldt, &work[1]);
t[j3 + *j1 * t_dim1] = 0.;
t[j3 + j2 * t_dim1] = 0.;
t[j3 + j3 * t_dim1] = t11;
if (*wantq) {
/* Accumulate transformation in the matrix Q. */
dlarfx_("R", n, &c__3, u, &tau, &q[*j1 * q_dim1 + 1], ldq, &work[
1]);
}
goto L40;
L20:
/*
N1 = 2, N2 = 1: generate elementary reflector H so that:
H ( -X11 ) = ( * )
( -X21 ) = ( 0 )
( scale ) = ( 0 )
*/
u[0] = -x[0];
u[1] = -x[1];
u[2] = scale;
dlarfg_(&c__3, u, &u[1], &c__1, &tau);
u[0] = 1.;
t33 = t[j3 + j3 * t_dim1];
/* Perform swap provisionally on diagonal block in D. */
dlarfx_("L", &c__3, &c__3, u, &tau, d__, &c__4, &work[1]);
dlarfx_("R", &c__3, &c__3, u, &tau, d__, &c__4, &work[1]);
/*
Test whether to reject swap.
Computing MAX
*/
d__2 = abs(d__[1]), d__3 = abs(d__[2]), d__2 = max(d__2,d__3), d__3 =
(d__1 = d__[0] - t33, abs(d__1));
if (max(d__2,d__3) > thresh) {
goto L50;
}
/* Accept swap: apply transformation to the entire matrix T. */
dlarfx_("R", &j3, &c__3, u, &tau, &t[*j1 * t_dim1 + 1], ldt, &work[1]);
i__1 = *n - *j1;
dlarfx_("L", &c__3, &i__1, u, &tau, &t[*j1 + j2 * t_dim1], ldt, &work[
1]);
t[*j1 + *j1 * t_dim1] = t33;
t[j2 + *j1 * t_dim1] = 0.;
t[j3 + *j1 * t_dim1] = 0.;
if (*wantq) {
/* Accumulate transformation in the matrix Q. */
dlarfx_("R", n, &c__3, u, &tau, &q[*j1 * q_dim1 + 1], ldq, &work[
1]);
}
goto L40;
L30:
/*
N1 = 2, N2 = 2: generate elementary reflectors H(1) and H(2) so
that:
H(2) H(1) ( -X11 -X12 ) = ( * * )
( -X21 -X22 ) ( 0 * )
( scale 0 ) ( 0 0 )
( 0 scale ) ( 0 0 )
*/
u1[0] = -x[0];
u1[1] = -x[1];
u1[2] = scale;
dlarfg_(&c__3, u1, &u1[1], &c__1, &tau1);
u1[0] = 1.;
temp = -tau1 * (x[2] + u1[1] * x[3]);
u2[0] = -temp * u1[1] - x[3];
u2[1] = -temp * u1[2];
u2[2] = scale;
dlarfg_(&c__3, u2, &u2[1], &c__1, &tau2);
u2[0] = 1.;
/* Perform swap provisionally on diagonal block in D. */
dlarfx_("L", &c__3, &c__4, u1, &tau1, d__, &c__4, &work[1])
;
dlarfx_("R", &c__4, &c__3, u1, &tau1, d__, &c__4, &work[1])
;
dlarfx_("L", &c__3, &c__4, u2, &tau2, &d__[1], &c__4, &work[1]);
dlarfx_("R", &c__4, &c__3, u2, &tau2, &d__[4], &c__4, &work[1]);
/*
Test whether to reject swap.
Computing MAX
*/
d__1 = abs(d__[2]), d__2 = abs(d__[6]), d__1 = max(d__1,d__2), d__2 =
abs(d__[3]), d__1 = max(d__1,d__2), d__2 = abs(d__[7]);
if (max(d__1,d__2) > thresh) {
goto L50;
}
/* Accept swap: apply transformation to the entire matrix T. */
i__1 = *n - *j1 + 1;
dlarfx_("L", &c__3, &i__1, u1, &tau1, &t[*j1 + *j1 * t_dim1], ldt, &
work[1]);
dlarfx_("R", &j4, &c__3, u1, &tau1, &t[*j1 * t_dim1 + 1], ldt, &work[
1]);
i__1 = *n - *j1 + 1;
dlarfx_("L", &c__3, &i__1, u2, &tau2, &t[j2 + *j1 * t_dim1], ldt, &
work[1]);
dlarfx_("R", &j4, &c__3, u2, &tau2, &t[j2 * t_dim1 + 1], ldt, &work[1]
);
t[j3 + *j1 * t_dim1] = 0.;
t[j3 + j2 * t_dim1] = 0.;
t[j4 + *j1 * t_dim1] = 0.;
t[j4 + j2 * t_dim1] = 0.;
if (*wantq) {
/* Accumulate transformation in the matrix Q. */
dlarfx_("R", n, &c__3, u1, &tau1, &q[*j1 * q_dim1 + 1], ldq, &
work[1]);
dlarfx_("R", n, &c__3, u2, &tau2, &q[j2 * q_dim1 + 1], ldq, &work[
1]);
}
L40:
if (*n2 == 2) {
/* Standardize new 2-by-2 block T11 */
dlanv2_(&t[*j1 + *j1 * t_dim1], &t[*j1 + j2 * t_dim1], &t[j2 + *
j1 * t_dim1], &t[j2 + j2 * t_dim1], &wr1, &wi1, &wr2, &
wi2, &cs, &sn);
i__1 = *n - *j1 - 1;
drot_(&i__1, &t[*j1 + (*j1 + 2) * t_dim1], ldt, &t[j2 + (*j1 + 2)
* t_dim1], ldt, &cs, &sn);
i__1 = *j1 - 1;
drot_(&i__1, &t[*j1 * t_dim1 + 1], &c__1, &t[j2 * t_dim1 + 1], &
c__1, &cs, &sn);
if (*wantq) {
drot_(n, &q[*j1 * q_dim1 + 1], &c__1, &q[j2 * q_dim1 + 1], &
c__1, &cs, &sn);
}
}
if (*n1 == 2) {
/* Standardize new 2-by-2 block T22 */
j3 = *j1 + *n2;
j4 = j3 + 1;
dlanv2_(&t[j3 + j3 * t_dim1], &t[j3 + j4 * t_dim1], &t[j4 + j3 *
t_dim1], &t[j4 + j4 * t_dim1], &wr1, &wi1, &wr2, &wi2, &
cs, &sn);
if (j3 + 2 <= *n) {
i__1 = *n - j3 - 1;
drot_(&i__1, &t[j3 + (j3 + 2) * t_dim1], ldt, &t[j4 + (j3 + 2)
* t_dim1], ldt, &cs, &sn);
}
i__1 = j3 - 1;
drot_(&i__1, &t[j3 * t_dim1 + 1], &c__1, &t[j4 * t_dim1 + 1], &
c__1, &cs, &sn);
if (*wantq) {
drot_(n, &q[j3 * q_dim1 + 1], &c__1, &q[j4 * q_dim1 + 1], &
c__1, &cs, &sn);
}
}
}
return 0;
/* Exit with INFO = 1 if swap was rejected. */
L50:
*info = 1;
return 0;
/* End of DLAEXC */
} /* dlaexc_ */
/* Subroutine */ int dlahqr_(logical *wantt, logical *wantz, integer *n,
integer *ilo, integer *ihi, doublereal *h__, integer *ldh, doublereal
*wr, doublereal *wi, integer *iloz, integer *ihiz, doublereal *z__,
integer *ldz, integer *info)
{
/* System generated locals */
integer h_dim1, h_offset, z_dim1, z_offset, i__1, i__2, i__3;
doublereal d__1, d__2, d__3, d__4;
/* Local variables */
static integer i__, j, k, l, m;
static doublereal s, v[3];
static integer i1, i2;
static doublereal t1, t2, t3, v2, v3, aa, ab, ba, bb, h11, h12, h21, h22,
cs;
static integer nh;
static doublereal sn;
static integer nr;
static doublereal tr;
static integer nz;
static doublereal det, h21s;
static integer its;
static doublereal ulp, sum, tst, rt1i, rt2i, rt1r, rt2r;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *), dcopy_(
integer *, doublereal *, integer *, doublereal *, integer *),
dlanv2_(doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *), dlabad_(doublereal *, doublereal *);
extern /* Subroutine */ int dlarfg_(integer *, doublereal *, doublereal *,
integer *, doublereal *);
static doublereal safmin, safmax, rtdisc, smlnum;
/*
-- LAPACK auxiliary routine (version 3.2) --
Univ. of Tennessee, Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..
November 2006
Purpose
=======
DLAHQR is an auxiliary routine called by DHSEQR to update the
eigenvalues and Schur decomposition already computed by DHSEQR, by
dealing with the Hessenberg submatrix in rows and columns ILO to
IHI.
Arguments
=========
WANTT (input) LOGICAL
= .TRUE. : the full Schur form T is required;
= .FALSE.: only eigenvalues are required.
WANTZ (input) LOGICAL
= .TRUE. : the matrix of Schur vectors Z is required;
= .FALSE.: Schur vectors are not required.
N (input) INTEGER
The order of the matrix H. N >= 0.
ILO (input) INTEGER
IHI (input) INTEGER
It is assumed that H is already upper quasi-triangular in
rows and columns IHI+1:N, and that H(ILO,ILO-1) = 0 (unless
ILO = 1). DLAHQR works primarily with the Hessenberg
submatrix in rows and columns ILO to IHI, but applies
transformations to all of H if WANTT is .TRUE..
1 <= ILO <= max(1,IHI); IHI <= N.
H (input/output) DOUBLE PRECISION array, dimension (LDH,N)
On entry, the upper Hessenberg matrix H.
On exit, if INFO is zero and if WANTT is .TRUE., H is upper
quasi-triangular in rows and columns ILO:IHI, with any
2-by-2 diagonal blocks in standard form. If INFO is zero
and WANTT is .FALSE., the contents of H are unspecified on
exit. The output state of H if INFO is nonzero is given
below under the description of INFO.
LDH (input) INTEGER
The leading dimension of the array H. LDH >= max(1,N).
WR (output) DOUBLE PRECISION array, dimension (N)
WI (output) DOUBLE PRECISION array, dimension (N)
The real and imaginary parts, respectively, of the computed
eigenvalues ILO to IHI are stored in the corresponding
elements of WR and WI. If two eigenvalues are computed as a
complex conjugate pair, they are stored in consecutive
elements of WR and WI, say the i-th and (i+1)th, with
WI(i) > 0 and WI(i+1) < 0. If WANTT is .TRUE., the
eigenvalues are stored in the same order as on the diagonal
of the Schur form returned in H, with WR(i) = H(i,i), and, if
H(i:i+1,i:i+1) is a 2-by-2 diagonal block,
WI(i) = sqrt(H(i+1,i)*H(i,i+1)) and WI(i+1) = -WI(i).
ILOZ (input) INTEGER
IHIZ (input) INTEGER
Specify the rows of Z to which transformations must be
applied if WANTZ is .TRUE..
1 <= ILOZ <= ILO; IHI <= IHIZ <= N.
Z (input/output) DOUBLE PRECISION array, dimension (LDZ,N)
If WANTZ is .TRUE., on entry Z must contain the current
matrix Z of transformations accumulated by DHSEQR, and on
exit Z has been updated; transformations are applied only to
the submatrix Z(ILOZ:IHIZ,ILO:IHI).
If WANTZ is .FALSE., Z is not referenced.
LDZ (input) INTEGER
The leading dimension of the array Z. LDZ >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
.GT. 0: If INFO = i, DLAHQR failed to compute all the
eigenvalues ILO to IHI in a total of 30 iterations
per eigenvalue; elements i+1:ihi of WR and WI
contain those eigenvalues which have been
successfully computed.
If INFO .GT. 0 and WANTT is .FALSE., then on exit,
the remaining unconverged eigenvalues are the
eigenvalues of the upper Hessenberg matrix rows
and columns ILO thorugh INFO of the final, output
value of H.
If INFO .GT. 0 and WANTT is .TRUE., then on exit
(*) (initial value of H)*U = U*(final value of H)
where U is an orthognal matrix. The final
value of H is upper Hessenberg and triangular in
rows and columns INFO+1 through IHI.
If INFO .GT. 0 and WANTZ is .TRUE., then on exit
(final value of Z) = (initial value of Z)*U
where U is the orthogonal matrix in (*)
(regardless of the value of WANTT.)
Further Details
===============
02-96 Based on modifications by
David Day, Sandia National Laboratory, USA
12-04 Further modifications by
Ralph Byers, University of Kansas, USA
This is a modified version of DLAHQR from LAPACK version 3.0.
It is (1) more robust against overflow and underflow and
(2) adopts the more conservative Ahues & Tisseur stopping
criterion (LAWN 122, 1997).
=========================================================
*/
/* Parameter adjustments */
h_dim1 = *ldh;
h_offset = 1 + h_dim1;
h__ -= h_offset;
--wr;
--wi;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
/* Function Body */
*info = 0;
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*ilo == *ihi) {
wr[*ilo] = h__[*ilo + *ilo * h_dim1];
wi[*ilo] = 0.;
return 0;
}
/* ==== clear out the trash ==== */
i__1 = *ihi - 3;
for (j = *ilo; j <= i__1; ++j) {
h__[j + 2 + j * h_dim1] = 0.;
h__[j + 3 + j * h_dim1] = 0.;
/* L10: */
}
if (*ilo <= *ihi - 2) {
h__[*ihi + (*ihi - 2) * h_dim1] = 0.;
}
nh = *ihi - *ilo + 1;
nz = *ihiz - *iloz + 1;
/* Set machine-dependent constants for the stopping criterion. */
safmin = SAFEMINIMUM;
safmax = 1. / safmin;
dlabad_(&safmin, &safmax);
ulp = PRECISION;
smlnum = safmin * ((doublereal) nh / ulp);
/*
I1 and I2 are the indices of the first row and last column of H
to which transformations must be applied. If eigenvalues only are
being computed, I1 and I2 are set inside the main loop.
*/
if (*wantt) {
i1 = 1;
i2 = *n;
}
/*
The main loop begins here. I is the loop index and decreases from
IHI to ILO in steps of 1 or 2. Each iteration of the loop works
with the active submatrix in rows and columns L to I.
Eigenvalues I+1 to IHI have already converged. Either L = ILO or
H(L,L-1) is negligible so that the matrix splits.
*/
i__ = *ihi;
L20:
l = *ilo;
if (i__ < *ilo) {
goto L160;
}
/*
Perform QR iterations on rows and columns ILO to I until a
submatrix of order 1 or 2 splits off at the bottom because a
subdiagonal element has become negligible.
*/
for (its = 0; its <= 30; ++its) {
/* Look for a single small subdiagonal element. */
i__1 = l + 1;
for (k = i__; k >= i__1; --k) {
if ((d__1 = h__[k + (k - 1) * h_dim1], abs(d__1)) <= smlnum) {
goto L40;
}
tst = (d__1 = h__[k - 1 + (k - 1) * h_dim1], abs(d__1)) + (d__2 =
h__[k + k * h_dim1], abs(d__2));
if (tst == 0.) {
if (k - 2 >= *ilo) {
tst += (d__1 = h__[k - 1 + (k - 2) * h_dim1], abs(d__1));
}
if (k + 1 <= *ihi) {
tst += (d__1 = h__[k + 1 + k * h_dim1], abs(d__1));
}
}
/*
==== The following is a conservative small subdiagonal
. deflation criterion due to Ahues & Tisseur (LAWN 122,
. 1997). It has better mathematical foundation and
. improves accuracy in some cases. ====
*/
if ((d__1 = h__[k + (k - 1) * h_dim1], abs(d__1)) <= ulp * tst) {
/* Computing MAX */
d__3 = (d__1 = h__[k + (k - 1) * h_dim1], abs(d__1)), d__4 = (
d__2 = h__[k - 1 + k * h_dim1], abs(d__2));
ab = max(d__3,d__4);
/* Computing MIN */
d__3 = (d__1 = h__[k + (k - 1) * h_dim1], abs(d__1)), d__4 = (
d__2 = h__[k - 1 + k * h_dim1], abs(d__2));
ba = min(d__3,d__4);
/* Computing MAX */
d__3 = (d__1 = h__[k + k * h_dim1], abs(d__1)), d__4 = (d__2 =
h__[k - 1 + (k - 1) * h_dim1] - h__[k + k * h_dim1],
abs(d__2));
aa = max(d__3,d__4);
/* Computing MIN */
d__3 = (d__1 = h__[k + k * h_dim1], abs(d__1)), d__4 = (d__2 =
h__[k - 1 + (k - 1) * h_dim1] - h__[k + k * h_dim1],
abs(d__2));
bb = min(d__3,d__4);
s = aa + ab;
/* Computing MAX */
d__1 = smlnum, d__2 = ulp * (bb * (aa / s));
if (ba * (ab / s) <= max(d__1,d__2)) {
goto L40;
}
}
/* L30: */
}
L40:
l = k;
if (l > *ilo) {
/* H(L,L-1) is negligible */
h__[l + (l - 1) * h_dim1] = 0.;
}
/* Exit from loop if a submatrix of order 1 or 2 has split off. */
if (l >= i__ - 1) {
goto L150;
}
/*
Now the active submatrix is in rows and columns L to I. If
eigenvalues only are being computed, only the active submatrix
need be transformed.
*/
if (! (*wantt)) {
i1 = l;
i2 = i__;
}
if (its == 10) {
/* Exceptional shift. */
s = (d__1 = h__[l + 1 + l * h_dim1], abs(d__1)) + (d__2 = h__[l +
2 + (l + 1) * h_dim1], abs(d__2));
h11 = s * .75 + h__[l + l * h_dim1];
h12 = s * -.4375;
h21 = s;
h22 = h11;
} else if (its == 20) {
/* Exceptional shift. */
s = (d__1 = h__[i__ + (i__ - 1) * h_dim1], abs(d__1)) + (d__2 =
h__[i__ - 1 + (i__ - 2) * h_dim1], abs(d__2));
h11 = s * .75 + h__[i__ + i__ * h_dim1];
h12 = s * -.4375;
h21 = s;
h22 = h11;
} else {
/*
Prepare to use Francis' double shift
(i.e. 2nd degree generalized Rayleigh quotient)
*/
h11 = h__[i__ - 1 + (i__ - 1) * h_dim1];
h21 = h__[i__ + (i__ - 1) * h_dim1];
h12 = h__[i__ - 1 + i__ * h_dim1];
h22 = h__[i__ + i__ * h_dim1];
}
s = abs(h11) + abs(h12) + abs(h21) + abs(h22);
if (s == 0.) {
rt1r = 0.;
rt1i = 0.;
rt2r = 0.;
rt2i = 0.;
} else {
h11 /= s;
h21 /= s;
h12 /= s;
h22 /= s;
tr = (h11 + h22) / 2.;
det = (h11 - tr) * (h22 - tr) - h12 * h21;
rtdisc = sqrt((abs(det)));
if (det >= 0.) {
/* ==== complex conjugate shifts ==== */
rt1r = tr * s;
rt2r = rt1r;
rt1i = rtdisc * s;
rt2i = -rt1i;
} else {
/* ==== real shifts (use only one of them) ==== */
rt1r = tr + rtdisc;
rt2r = tr - rtdisc;
if ((d__1 = rt1r - h22, abs(d__1)) <= (d__2 = rt2r - h22, abs(
d__2))) {
rt1r *= s;
rt2r = rt1r;
} else {
rt2r *= s;
rt1r = rt2r;
}
rt1i = 0.;
rt2i = 0.;
}
}
/* Look for two consecutive small subdiagonal elements. */
i__1 = l;
for (m = i__ - 2; m >= i__1; --m) {
/*
Determine the effect of starting the double-shift QR
iteration at row M, and see if this would make H(M,M-1)
negligible. (The following uses scaling to avoid
overflows and most underflows.)
*/
h21s = h__[m + 1 + m * h_dim1];
s = (d__1 = h__[m + m * h_dim1] - rt2r, abs(d__1)) + abs(rt2i) +
abs(h21s);
h21s = h__[m + 1 + m * h_dim1] / s;
v[0] = h21s * h__[m + (m + 1) * h_dim1] + (h__[m + m * h_dim1] -
rt1r) * ((h__[m + m * h_dim1] - rt2r) / s) - rt1i * (rt2i
/ s);
v[1] = h21s * (h__[m + m * h_dim1] + h__[m + 1 + (m + 1) * h_dim1]
- rt1r - rt2r);
v[2] = h21s * h__[m + 2 + (m + 1) * h_dim1];
s = abs(v[0]) + abs(v[1]) + abs(v[2]);
v[0] /= s;
v[1] /= s;
v[2] /= s;
if (m == l) {
goto L60;
}
if ((d__1 = h__[m + (m - 1) * h_dim1], abs(d__1)) * (abs(v[1]) +
abs(v[2])) <= ulp * abs(v[0]) * ((d__2 = h__[m - 1 + (m -
1) * h_dim1], abs(d__2)) + (d__3 = h__[m + m * h_dim1],
abs(d__3)) + (d__4 = h__[m + 1 + (m + 1) * h_dim1], abs(
d__4)))) {
goto L60;
}
/* L50: */
}
L60:
/* Double-shift QR step */
i__1 = i__ - 1;
for (k = m; k <= i__1; ++k) {
/*
The first iteration of this loop determines a reflection G
from the vector V and applies it from left and right to H,
thus creating a nonzero bulge below the subdiagonal.
Each subsequent iteration determines a reflection G to
restore the Hessenberg form in the (K-1)th column, and thus
chases the bulge one step toward the bottom of the active
submatrix. NR is the order of G.
Computing MIN
*/
i__2 = 3, i__3 = i__ - k + 1;
nr = min(i__2,i__3);
if (k > m) {
dcopy_(&nr, &h__[k + (k - 1) * h_dim1], &c__1, v, &c__1);
}
dlarfg_(&nr, v, &v[1], &c__1, &t1);
if (k > m) {
h__[k + (k - 1) * h_dim1] = v[0];
h__[k + 1 + (k - 1) * h_dim1] = 0.;
if (k < i__ - 1) {
h__[k + 2 + (k - 1) * h_dim1] = 0.;
}
} else if (m > l) {
/*
==== Use the following instead of
. H( K, K-1 ) = -H( K, K-1 ) to
. avoid a bug when v(2) and v(3)
. underflow. ====
*/
h__[k + (k - 1) * h_dim1] *= 1. - t1;
}
v2 = v[1];
t2 = t1 * v2;
if (nr == 3) {
v3 = v[2];
t3 = t1 * v3;
/*
Apply G from the left to transform the rows of the matrix
in columns K to I2.
*/
i__2 = i2;
for (j = k; j <= i__2; ++j) {
sum = h__[k + j * h_dim1] + v2 * h__[k + 1 + j * h_dim1]
+ v3 * h__[k + 2 + j * h_dim1];
h__[k + j * h_dim1] -= sum * t1;
h__[k + 1 + j * h_dim1] -= sum * t2;
h__[k + 2 + j * h_dim1] -= sum * t3;
/* L70: */
}
/*
Apply G from the right to transform the columns of the
matrix in rows I1 to min(K+3,I).
Computing MIN
*/
i__3 = k + 3;
i__2 = min(i__3,i__);
for (j = i1; j <= i__2; ++j) {
sum = h__[j + k * h_dim1] + v2 * h__[j + (k + 1) * h_dim1]
+ v3 * h__[j + (k + 2) * h_dim1];
h__[j + k * h_dim1] -= sum * t1;
h__[j + (k + 1) * h_dim1] -= sum * t2;
h__[j + (k + 2) * h_dim1] -= sum * t3;
/* L80: */
}
if (*wantz) {
/* Accumulate transformations in the matrix Z */
i__2 = *ihiz;
for (j = *iloz; j <= i__2; ++j) {
sum = z__[j + k * z_dim1] + v2 * z__[j + (k + 1) *
z_dim1] + v3 * z__[j + (k + 2) * z_dim1];
z__[j + k * z_dim1] -= sum * t1;
z__[j + (k + 1) * z_dim1] -= sum * t2;
z__[j + (k + 2) * z_dim1] -= sum * t3;
/* L90: */
}
}
} else if (nr == 2) {
/*
Apply G from the left to transform the rows of the matrix
in columns K to I2.
*/
i__2 = i2;
for (j = k; j <= i__2; ++j) {
sum = h__[k + j * h_dim1] + v2 * h__[k + 1 + j * h_dim1];
h__[k + j * h_dim1] -= sum * t1;
h__[k + 1 + j * h_dim1] -= sum * t2;
/* L100: */
}
/*
Apply G from the right to transform the columns of the
matrix in rows I1 to min(K+3,I).
*/
i__2 = i__;
for (j = i1; j <= i__2; ++j) {
sum = h__[j + k * h_dim1] + v2 * h__[j + (k + 1) * h_dim1]
;
h__[j + k * h_dim1] -= sum * t1;
h__[j + (k + 1) * h_dim1] -= sum * t2;
/* L110: */
}
if (*wantz) {
/* Accumulate transformations in the matrix Z */
i__2 = *ihiz;
for (j = *iloz; j <= i__2; ++j) {
sum = z__[j + k * z_dim1] + v2 * z__[j + (k + 1) *
z_dim1];
z__[j + k * z_dim1] -= sum * t1;
z__[j + (k + 1) * z_dim1] -= sum * t2;
/* L120: */
}
}
}
/* L130: */
}
/* L140: */
}
/* Failure to converge in remaining number of iterations */
*info = i__;
return 0;
L150:
if (l == i__) {
/* H(I,I-1) is negligible: one eigenvalue has converged. */
wr[i__] = h__[i__ + i__ * h_dim1];
wi[i__] = 0.;
} else if (l == i__ - 1) {
/*
H(I-1,I-2) is negligible: a pair of eigenvalues have converged.
Transform the 2-by-2 submatrix to standard Schur form,
and compute and store the eigenvalues.
*/
dlanv2_(&h__[i__ - 1 + (i__ - 1) * h_dim1], &h__[i__ - 1 + i__ *
h_dim1], &h__[i__ + (i__ - 1) * h_dim1], &h__[i__ + i__ *
h_dim1], &wr[i__ - 1], &wi[i__ - 1], &wr[i__], &wi[i__], &cs,
&sn);
if (*wantt) {
/* Apply the transformation to the rest of H. */
if (i2 > i__) {
i__1 = i2 - i__;
drot_(&i__1, &h__[i__ - 1 + (i__ + 1) * h_dim1], ldh, &h__[
i__ + (i__ + 1) * h_dim1], ldh, &cs, &sn);
}
i__1 = i__ - i1 - 1;
drot_(&i__1, &h__[i1 + (i__ - 1) * h_dim1], &c__1, &h__[i1 + i__ *
h_dim1], &c__1, &cs, &sn);
}
if (*wantz) {
/* Apply the transformation to Z. */
drot_(&nz, &z__[*iloz + (i__ - 1) * z_dim1], &c__1, &z__[*iloz +
i__ * z_dim1], &c__1, &cs, &sn);
}
}
/* return to start of the main loop with new value of I. */
i__ = l - 1;
goto L20;
L160:
return 0;
/* End of DLAHQR */
} /* dlahqr_ */
/* Subroutine */ int dlahr2_(integer *n, integer *k, integer *nb, doublereal *
a, integer *lda, doublereal *tau, doublereal *t, integer *ldt,
doublereal *y, integer *ldy)
{
/* System generated locals */
integer a_dim1, a_offset, t_dim1, t_offset, y_dim1, y_offset, i__1, i__2,
i__3;
doublereal d__1;
/* Local variables */
static integer i__;
static doublereal ei;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *), dgemm_(char *, char *, integer *, integer *, integer *
, doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *), dgemv_(
char *, integer *, integer *, doublereal *, doublereal *, integer
*, doublereal *, integer *, doublereal *, doublereal *, integer *), dcopy_(integer *, doublereal *, integer *, doublereal *,
integer *), dtrmm_(char *, char *, char *, char *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *), daxpy_(integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *),
dtrmv_(char *, char *, char *, integer *, doublereal *, integer *,
doublereal *, integer *), dlarfg_(
integer *, doublereal *, doublereal *, integer *, doublereal *),
dlacpy_(char *, integer *, integer *, doublereal *, integer *,
doublereal *, integer *);
/*
-- LAPACK auxiliary routine (version 3.2.1) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
-- April 2009 --
Purpose
=======
DLAHR2 reduces the first NB columns of A real general n-BY-(n-k+1)
matrix A so that elements below the k-th subdiagonal are zero. The
reduction is performed by an orthogonal similarity transformation
Q' * A * Q. The routine returns the matrices V and T which determine
Q as a block reflector I - V*T*V', and also the matrix Y = A * V * T.
This is an auxiliary routine called by DGEHRD.
Arguments
=========
N (input) INTEGER
The order of the matrix A.
K (input) INTEGER
The offset for the reduction. Elements below the k-th
subdiagonal in the first NB columns are reduced to zero.
K < N.
NB (input) INTEGER
The number of columns to be reduced.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N-K+1)
On entry, the n-by-(n-k+1) general matrix A.
On exit, the elements on and above the k-th subdiagonal in
the first NB columns are overwritten with the corresponding
elements of the reduced matrix; the elements below the k-th
subdiagonal, with the array TAU, represent the matrix Q as a
product of elementary reflectors. The other columns of A are
unchanged. See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
TAU (output) DOUBLE PRECISION array, dimension (NB)
The scalar factors of the elementary reflectors. See Further
Details.
T (output) DOUBLE PRECISION array, dimension (LDT,NB)
The upper triangular matrix T.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= NB.
Y (output) DOUBLE PRECISION array, dimension (LDY,NB)
The n-by-nb matrix Y.
LDY (input) INTEGER
The leading dimension of the array Y. LDY >= N.
Further Details
===============
The matrix Q is represented as a product of nb elementary reflectors
Q = H(1) H(2) . . . H(nb).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i+k-1) = 0, v(i+k) = 1; v(i+k+1:n) is stored on exit in
A(i+k+1:n,i), and tau in TAU(i).
The elements of the vectors v together form the (n-k+1)-by-nb matrix
V which is needed, with T and Y, to apply the transformation to the
unreduced part of the matrix, using an update of the form:
A := (I - V*T*V') * (A - Y*V').
The contents of A on exit are illustrated by the following example
with n = 7, k = 3 and nb = 2:
( a a a a a )
( a a a a a )
( a a a a a )
( h h a a a )
( v1 h a a a )
( v1 v2 a a a )
( v1 v2 a a a )
where a denotes an element of the original matrix A, h denotes a
modified element of the upper Hessenberg matrix H, and vi denotes an
element of the vector defining H(i).
This subroutine is a slight modification of LAPACK-3.0's DLAHRD
incorporating improvements proposed by Quintana-Orti and Van de
Gejin. Note that the entries of A(1:K,2:NB) differ from those
returned by the original LAPACK-3.0's DLAHRD routine. (This
subroutine is not backward compatible with LAPACK-3.0's DLAHRD.)
References
==========
Gregorio Quintana-Orti and Robert van de Geijn, "Improving the
performance of reduction to Hessenberg form," ACM Transactions on
Mathematical Software, 32(2):180-194, June 2006.
=====================================================================
Quick return if possible
*/
/* Parameter adjustments */
--tau;
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
y_dim1 = *ldy;
y_offset = 1 + y_dim1;
y -= y_offset;
/* Function Body */
if (*n <= 1) {
return 0;
}
i__1 = *nb;
for (i__ = 1; i__ <= i__1; ++i__) {
if (i__ > 1) {
/*
Update A(K+1:N,I)
Update I-th column of A - Y * V'
*/
i__2 = *n - *k;
i__3 = i__ - 1;
dgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b151, &y[*k + 1 + y_dim1],
ldy, &a[*k + i__ - 1 + a_dim1], lda, &c_b15, &a[*k + 1 +
i__ * a_dim1], &c__1);
/*
Apply I - V * T' * V' to this column (call it b) from the
left, using the last column of T as workspace
Let V = ( V1 ) and b = ( b1 ) (first I-1 rows)
( V2 ) ( b2 )
where V1 is unit lower triangular
w := V1' * b1
*/
i__2 = i__ - 1;
dcopy_(&i__2, &a[*k + 1 + i__ * a_dim1], &c__1, &t[*nb * t_dim1 +
1], &c__1);
i__2 = i__ - 1;
dtrmv_("Lower", "Transpose", "UNIT", &i__2, &a[*k + 1 + a_dim1],
lda, &t[*nb * t_dim1 + 1], &c__1);
/* w := w + V2'*b2 */
i__2 = *n - *k - i__ + 1;
i__3 = i__ - 1;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &a[*k + i__ + a_dim1],
lda, &a[*k + i__ + i__ * a_dim1], &c__1, &c_b15, &t[*nb *
t_dim1 + 1], &c__1);
/* w := T'*w */
i__2 = i__ - 1;
dtrmv_("Upper", "Transpose", "NON-UNIT", &i__2, &t[t_offset], ldt,
&t[*nb * t_dim1 + 1], &c__1);
/* b2 := b2 - V2*w */
i__2 = *n - *k - i__ + 1;
i__3 = i__ - 1;
dgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b151, &a[*k + i__ +
a_dim1], lda, &t[*nb * t_dim1 + 1], &c__1, &c_b15, &a[*k
+ i__ + i__ * a_dim1], &c__1);
/* b1 := b1 - V1*w */
i__2 = i__ - 1;
dtrmv_("Lower", "NO TRANSPOSE", "UNIT", &i__2, &a[*k + 1 + a_dim1]
, lda, &t[*nb * t_dim1 + 1], &c__1);
i__2 = i__ - 1;
daxpy_(&i__2, &c_b151, &t[*nb * t_dim1 + 1], &c__1, &a[*k + 1 +
i__ * a_dim1], &c__1);
a[*k + i__ - 1 + (i__ - 1) * a_dim1] = ei;
}
/*
Generate the elementary reflector H(I) to annihilate
A(K+I+1:N,I)
*/
i__2 = *n - *k - i__ + 1;
/* Computing MIN */
i__3 = *k + i__ + 1;
dlarfg_(&i__2, &a[*k + i__ + i__ * a_dim1], &a[min(i__3,*n) + i__ *
a_dim1], &c__1, &tau[i__]);
ei = a[*k + i__ + i__ * a_dim1];
a[*k + i__ + i__ * a_dim1] = 1.;
/* Compute Y(K+1:N,I) */
i__2 = *n - *k;
i__3 = *n - *k - i__ + 1;
dgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b15, &a[*k + 1 + (i__ + 1) *
a_dim1], lda, &a[*k + i__ + i__ * a_dim1], &c__1, &c_b29, &y[*
k + 1 + i__ * y_dim1], &c__1);
i__2 = *n - *k - i__ + 1;
i__3 = i__ - 1;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &a[*k + i__ + a_dim1], lda,
&a[*k + i__ + i__ * a_dim1], &c__1, &c_b29, &t[i__ * t_dim1 +
1], &c__1);
i__2 = *n - *k;
i__3 = i__ - 1;
dgemv_("NO TRANSPOSE", &i__2, &i__3, &c_b151, &y[*k + 1 + y_dim1],
ldy, &t[i__ * t_dim1 + 1], &c__1, &c_b15, &y[*k + 1 + i__ *
y_dim1], &c__1);
i__2 = *n - *k;
dscal_(&i__2, &tau[i__], &y[*k + 1 + i__ * y_dim1], &c__1);
/* Compute T(1:I,I) */
i__2 = i__ - 1;
d__1 = -tau[i__];
dscal_(&i__2, &d__1, &t[i__ * t_dim1 + 1], &c__1);
i__2 = i__ - 1;
dtrmv_("Upper", "No Transpose", "NON-UNIT", &i__2, &t[t_offset], ldt,
&t[i__ * t_dim1 + 1], &c__1)
;
t[i__ + i__ * t_dim1] = tau[i__];
/* L10: */
}
a[*k + *nb + *nb * a_dim1] = ei;
/* Compute Y(1:K,1:NB) */
dlacpy_("ALL", k, nb, &a[(a_dim1 << 1) + 1], lda, &y[y_offset], ldy);
dtrmm_("RIGHT", "Lower", "NO TRANSPOSE", "UNIT", k, nb, &c_b15, &a[*k + 1
+ a_dim1], lda, &y[y_offset], ldy);
if (*n > *k + *nb) {
i__1 = *n - *k - *nb;
dgemm_("NO TRANSPOSE", "NO TRANSPOSE", k, nb, &i__1, &c_b15, &a[(*nb
+ 2) * a_dim1 + 1], lda, &a[*k + 1 + *nb + a_dim1], lda, &
c_b15, &y[y_offset], ldy);
}
dtrmm_("RIGHT", "Upper", "NO TRANSPOSE", "NON-UNIT", k, nb, &c_b15, &t[
t_offset], ldt, &y[y_offset], ldy);
return 0;
/* End of DLAHR2 */
} /* dlahr2_ */
logical dlaisnan_(doublereal *din1, doublereal *din2)
{
/* System generated locals */
logical ret_val;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
This routine is not for general use. It exists solely to avoid
over-optimization in DISNAN.
DLAISNAN checks for NaNs by comparing its two arguments for
inequality. NaN is the only floating-point value where NaN != NaN
returns .TRUE. To check for NaNs, pass the same variable as both
arguments.
A compiler must assume that the two arguments are
not the same variable, and the test will not be optimized away.
Interprocedural or whole-program optimization may delete this
test. The ISNAN functions will be replaced by the correct
Fortran 03 intrinsic once the intrinsic is widely available.
Arguments
=========
DIN1 (input) DOUBLE PRECISION
DIN2 (input) DOUBLE PRECISION
Two numbers to compare for inequality.
=====================================================================
*/
ret_val = *din1 != *din2;
return ret_val;
} /* dlaisnan_ */
/* Subroutine */ int dlaln2_(logical *ltrans, integer *na, integer *nw,
doublereal *smin, doublereal *ca, doublereal *a, integer *lda,
doublereal *d1, doublereal *d2, doublereal *b, integer *ldb,
doublereal *wr, doublereal *wi, doublereal *x, integer *ldx,
doublereal *scale, doublereal *xnorm, integer *info)
{
/* Initialized data */
static logical zswap[4] = { FALSE_,FALSE_,TRUE_,TRUE_ };
static logical rswap[4] = { FALSE_,TRUE_,FALSE_,TRUE_ };
static integer ipivot[16] /* was [4][4] */ = { 1,2,3,4,2,1,4,3,3,4,1,2,
4,3,2,1 };
/* System generated locals */
integer a_dim1, a_offset, b_dim1, b_offset, x_dim1, x_offset;
doublereal d__1, d__2, d__3, d__4, d__5, d__6;
static doublereal equiv_0[4], equiv_1[4];
/* Local variables */
static integer j;
#define ci (equiv_0)
#define cr (equiv_1)
static doublereal bi1, bi2, br1, br2, xi1, xi2, xr1, xr2, ci21, ci22,
cr21, cr22, li21, csi, ui11, lr21, ui12, ui22;
#define civ (equiv_0)
static doublereal csr, ur11, ur12, ur22;
#define crv (equiv_1)
static doublereal bbnd, cmax, ui11r, ui12s, temp, ur11r, ur12s, u22abs;
static integer icmax;
static doublereal bnorm, cnorm, smini;
extern /* Subroutine */ int dladiv_(doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *);
static doublereal bignum, smlnum;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLALN2 solves a system of the form (ca A - w D ) X = s B
or (ca A' - w D) X = s B with possible scaling ("s") and
perturbation of A. (A' means A-transpose.)
A is an NA x NA real matrix, ca is a real scalar, D is an NA x NA
real diagonal matrix, w is a real or complex value, and X and B are
NA x 1 matrices -- real if w is real, complex if w is complex. NA
may be 1 or 2.
If w is complex, X and B are represented as NA x 2 matrices,
the first column of each being the real part and the second
being the imaginary part.
"s" is a scaling factor (.LE. 1), computed by DLALN2, which is
so chosen that X can be computed without overflow. X is further
scaled if necessary to assure that norm(ca A - w D)*norm(X) is less
than overflow.
If both singular values of (ca A - w D) are less than SMIN,
SMIN*identity will be used instead of (ca A - w D). If only one
singular value is less than SMIN, one element of (ca A - w D) will be
perturbed enough to make the smallest singular value roughly SMIN.
If both singular values are at least SMIN, (ca A - w D) will not be
perturbed. In any case, the perturbation will be at most some small
multiple of max( SMIN, ulp*norm(ca A - w D) ). The singular values
are computed by infinity-norm approximations, and thus will only be
correct to a factor of 2 or so.
Note: all input quantities are assumed to be smaller than overflow
by a reasonable factor. (See BIGNUM.)
Arguments
==========
LTRANS (input) LOGICAL
=.TRUE.: A-transpose will be used.
=.FALSE.: A will be used (not transposed.)
NA (input) INTEGER
The size of the matrix A. It may (only) be 1 or 2.
NW (input) INTEGER
1 if "w" is real, 2 if "w" is complex. It may only be 1
or 2.
SMIN (input) DOUBLE PRECISION
The desired lower bound on the singular values of A. This
should be a safe distance away from underflow or overflow,
say, between (underflow/machine precision) and (machine
precision * overflow ). (See BIGNUM and ULP.)
CA (input) DOUBLE PRECISION
The coefficient c, which A is multiplied by.
A (input) DOUBLE PRECISION array, dimension (LDA,NA)
The NA x NA matrix A.
LDA (input) INTEGER
The leading dimension of A. It must be at least NA.
D1 (input) DOUBLE PRECISION
The 1,1 element in the diagonal matrix D.
D2 (input) DOUBLE PRECISION
The 2,2 element in the diagonal matrix D. Not used if NW=1.
B (input) DOUBLE PRECISION array, dimension (LDB,NW)
The NA x NW matrix B (right-hand side). If NW=2 ("w" is
complex), column 1 contains the real part of B and column 2
contains the imaginary part.
LDB (input) INTEGER
The leading dimension of B. It must be at least NA.
WR (input) DOUBLE PRECISION
The real part of the scalar "w".
WI (input) DOUBLE PRECISION
The imaginary part of the scalar "w". Not used if NW=1.
X (output) DOUBLE PRECISION array, dimension (LDX,NW)
The NA x NW matrix X (unknowns), as computed by DLALN2.
If NW=2 ("w" is complex), on exit, column 1 will contain
the real part of X and column 2 will contain the imaginary
part.
LDX (input) INTEGER
The leading dimension of X. It must be at least NA.
SCALE (output) DOUBLE PRECISION
The scale factor that B must be multiplied by to insure
that overflow does not occur when computing X. Thus,
(ca A - w D) X will be SCALE*B, not B (ignoring
perturbations of A.) It will be at most 1.
XNORM (output) DOUBLE PRECISION
The infinity-norm of X, when X is regarded as an NA x NW
real matrix.
INFO (output) INTEGER
An error flag. It will be set to zero if no error occurs,
a negative number if an argument is in error, or a positive
number if ca A - w D had to be perturbed.
The possible values are:
= 0: No error occurred, and (ca A - w D) did not have to be
perturbed.
= 1: (ca A - w D) had to be perturbed to make its smallest
(or only) singular value greater than SMIN.
NOTE: In the interests of speed, this routine does not
check the inputs for errors.
=====================================================================
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
x_dim1 = *ldx;
x_offset = 1 + x_dim1;
x -= x_offset;
/* Function Body */
/* Compute BIGNUM */
smlnum = 2. * SAFEMINIMUM;
bignum = 1. / smlnum;
smini = max(*smin,smlnum);
/* Don't check for input errors */
*info = 0;
/* Standard Initializations */
*scale = 1.;
if (*na == 1) {
/* 1 x 1 (i.e., scalar) system C X = B */
if (*nw == 1) {
/*
Real 1x1 system.
C = ca A - w D
*/
csr = *ca * a[a_dim1 + 1] - *wr * *d1;
cnorm = abs(csr);
/* If | C | < SMINI, use C = SMINI */
if (cnorm < smini) {
csr = smini;
cnorm = smini;
*info = 1;
}
/* Check scaling for X = B / C */
bnorm = (d__1 = b[b_dim1 + 1], abs(d__1));
if (cnorm < 1. && bnorm > 1.) {
if (bnorm > bignum * cnorm) {
*scale = 1. / bnorm;
}
}
/* Compute X */
x[x_dim1 + 1] = b[b_dim1 + 1] * *scale / csr;
*xnorm = (d__1 = x[x_dim1 + 1], abs(d__1));
} else {
/*
Complex 1x1 system (w is complex)
C = ca A - w D
*/
csr = *ca * a[a_dim1 + 1] - *wr * *d1;
csi = -(*wi) * *d1;
cnorm = abs(csr) + abs(csi);
/* If | C | < SMINI, use C = SMINI */
if (cnorm < smini) {
csr = smini;
csi = 0.;
cnorm = smini;
*info = 1;
}
/* Check scaling for X = B / C */
bnorm = (d__1 = b[b_dim1 + 1], abs(d__1)) + (d__2 = b[(b_dim1 <<
1) + 1], abs(d__2));
if (cnorm < 1. && bnorm > 1.) {
if (bnorm > bignum * cnorm) {
*scale = 1. / bnorm;
}
}
/* Compute X */
d__1 = *scale * b[b_dim1 + 1];
d__2 = *scale * b[(b_dim1 << 1) + 1];
dladiv_(&d__1, &d__2, &csr, &csi, &x[x_dim1 + 1], &x[(x_dim1 << 1)
+ 1]);
*xnorm = (d__1 = x[x_dim1 + 1], abs(d__1)) + (d__2 = x[(x_dim1 <<
1) + 1], abs(d__2));
}
} else {
/*
2x2 System
Compute the real part of C = ca A - w D (or ca A' - w D )
*/
cr[0] = *ca * a[a_dim1 + 1] - *wr * *d1;
cr[3] = *ca * a[(a_dim1 << 1) + 2] - *wr * *d2;
if (*ltrans) {
cr[2] = *ca * a[a_dim1 + 2];
cr[1] = *ca * a[(a_dim1 << 1) + 1];
} else {
cr[1] = *ca * a[a_dim1 + 2];
cr[2] = *ca * a[(a_dim1 << 1) + 1];
}
if (*nw == 1) {
/*
Real 2x2 system (w is real)
Find the largest element in C
*/
cmax = 0.;
icmax = 0;
for (j = 1; j <= 4; ++j) {
if ((d__1 = crv[j - 1], abs(d__1)) > cmax) {
cmax = (d__1 = crv[j - 1], abs(d__1));
icmax = j;
}
/* L10: */
}
/* If norm(C) < SMINI, use SMINI*identity. */
if (cmax < smini) {
/* Computing MAX */
d__3 = (d__1 = b[b_dim1 + 1], abs(d__1)), d__4 = (d__2 = b[
b_dim1 + 2], abs(d__2));
bnorm = max(d__3,d__4);
if (smini < 1. && bnorm > 1.) {
if (bnorm > bignum * smini) {
*scale = 1. / bnorm;
}
}
temp = *scale / smini;
x[x_dim1 + 1] = temp * b[b_dim1 + 1];
x[x_dim1 + 2] = temp * b[b_dim1 + 2];
*xnorm = temp * bnorm;
*info = 1;
return 0;
}
/* Gaussian elimination with complete pivoting. */
ur11 = crv[icmax - 1];
cr21 = crv[ipivot[(icmax << 2) - 3] - 1];
ur12 = crv[ipivot[(icmax << 2) - 2] - 1];
cr22 = crv[ipivot[(icmax << 2) - 1] - 1];
ur11r = 1. / ur11;
lr21 = ur11r * cr21;
ur22 = cr22 - ur12 * lr21;
/* If smaller pivot < SMINI, use SMINI */
if (abs(ur22) < smini) {
ur22 = smini;
*info = 1;
}
if (rswap[icmax - 1]) {
br1 = b[b_dim1 + 2];
br2 = b[b_dim1 + 1];
} else {
br1 = b[b_dim1 + 1];
br2 = b[b_dim1 + 2];
}
br2 -= lr21 * br1;
/* Computing MAX */
d__2 = (d__1 = br1 * (ur22 * ur11r), abs(d__1)), d__3 = abs(br2);
bbnd = max(d__2,d__3);
if (bbnd > 1. && abs(ur22) < 1.) {
if (bbnd >= bignum * abs(ur22)) {
*scale = 1. / bbnd;
}
}
xr2 = br2 * *scale / ur22;
xr1 = *scale * br1 * ur11r - xr2 * (ur11r * ur12);
if (zswap[icmax - 1]) {
x[x_dim1 + 1] = xr2;
x[x_dim1 + 2] = xr1;
} else {
x[x_dim1 + 1] = xr1;
x[x_dim1 + 2] = xr2;
}
/* Computing MAX */
d__1 = abs(xr1), d__2 = abs(xr2);
*xnorm = max(d__1,d__2);
/* Further scaling if norm(A) norm(X) > overflow */
if (*xnorm > 1. && cmax > 1.) {
if (*xnorm > bignum / cmax) {
temp = cmax / bignum;
x[x_dim1 + 1] = temp * x[x_dim1 + 1];
x[x_dim1 + 2] = temp * x[x_dim1 + 2];
*xnorm = temp * *xnorm;
*scale = temp * *scale;
}
}
} else {
/*
Complex 2x2 system (w is complex)
Find the largest element in C
*/
ci[0] = -(*wi) * *d1;
ci[1] = 0.;
ci[2] = 0.;
ci[3] = -(*wi) * *d2;
cmax = 0.;
icmax = 0;
for (j = 1; j <= 4; ++j) {
if ((d__1 = crv[j - 1], abs(d__1)) + (d__2 = civ[j - 1], abs(
d__2)) > cmax) {
cmax = (d__1 = crv[j - 1], abs(d__1)) + (d__2 = civ[j - 1]
, abs(d__2));
icmax = j;
}
/* L20: */
}
/* If norm(C) < SMINI, use SMINI*identity. */
if (cmax < smini) {
/* Computing MAX */
d__5 = (d__1 = b[b_dim1 + 1], abs(d__1)) + (d__2 = b[(b_dim1
<< 1) + 1], abs(d__2)), d__6 = (d__3 = b[b_dim1 + 2],
abs(d__3)) + (d__4 = b[(b_dim1 << 1) + 2], abs(d__4));
bnorm = max(d__5,d__6);
if (smini < 1. && bnorm > 1.) {
if (bnorm > bignum * smini) {
*scale = 1. / bnorm;
}
}
temp = *scale / smini;
x[x_dim1 + 1] = temp * b[b_dim1 + 1];
x[x_dim1 + 2] = temp * b[b_dim1 + 2];
x[(x_dim1 << 1) + 1] = temp * b[(b_dim1 << 1) + 1];
x[(x_dim1 << 1) + 2] = temp * b[(b_dim1 << 1) + 2];
*xnorm = temp * bnorm;
*info = 1;
return 0;
}
/* Gaussian elimination with complete pivoting. */
ur11 = crv[icmax - 1];
ui11 = civ[icmax - 1];
cr21 = crv[ipivot[(icmax << 2) - 3] - 1];
ci21 = civ[ipivot[(icmax << 2) - 3] - 1];
ur12 = crv[ipivot[(icmax << 2) - 2] - 1];
ui12 = civ[ipivot[(icmax << 2) - 2] - 1];
cr22 = crv[ipivot[(icmax << 2) - 1] - 1];
ci22 = civ[ipivot[(icmax << 2) - 1] - 1];
if (icmax == 1 || icmax == 4) {
/* Code when off-diagonals of pivoted C are real */
if (abs(ur11) > abs(ui11)) {
temp = ui11 / ur11;
/* Computing 2nd power */
d__1 = temp;
ur11r = 1. / (ur11 * (d__1 * d__1 + 1.));
ui11r = -temp * ur11r;
} else {
temp = ur11 / ui11;
/* Computing 2nd power */
d__1 = temp;
ui11r = -1. / (ui11 * (d__1 * d__1 + 1.));
ur11r = -temp * ui11r;
}
lr21 = cr21 * ur11r;
li21 = cr21 * ui11r;
ur12s = ur12 * ur11r;
ui12s = ur12 * ui11r;
ur22 = cr22 - ur12 * lr21;
ui22 = ci22 - ur12 * li21;
} else {
/* Code when diagonals of pivoted C are real */
ur11r = 1. / ur11;
ui11r = 0.;
lr21 = cr21 * ur11r;
li21 = ci21 * ur11r;
ur12s = ur12 * ur11r;
ui12s = ui12 * ur11r;
ur22 = cr22 - ur12 * lr21 + ui12 * li21;
ui22 = -ur12 * li21 - ui12 * lr21;
}
u22abs = abs(ur22) + abs(ui22);
/* If smaller pivot < SMINI, use SMINI */
if (u22abs < smini) {
ur22 = smini;
ui22 = 0.;
*info = 1;
}
if (rswap[icmax - 1]) {
br2 = b[b_dim1 + 1];
br1 = b[b_dim1 + 2];
bi2 = b[(b_dim1 << 1) + 1];
bi1 = b[(b_dim1 << 1) + 2];
} else {
br1 = b[b_dim1 + 1];
br2 = b[b_dim1 + 2];
bi1 = b[(b_dim1 << 1) + 1];
bi2 = b[(b_dim1 << 1) + 2];
}
br2 = br2 - lr21 * br1 + li21 * bi1;
bi2 = bi2 - li21 * br1 - lr21 * bi1;
/* Computing MAX */
d__1 = (abs(br1) + abs(bi1)) * (u22abs * (abs(ur11r) + abs(ui11r))
), d__2 = abs(br2) + abs(bi2);
bbnd = max(d__1,d__2);
if (bbnd > 1. && u22abs < 1.) {
if (bbnd >= bignum * u22abs) {
*scale = 1. / bbnd;
br1 = *scale * br1;
bi1 = *scale * bi1;
br2 = *scale * br2;
bi2 = *scale * bi2;
}
}
dladiv_(&br2, &bi2, &ur22, &ui22, &xr2, &xi2);
xr1 = ur11r * br1 - ui11r * bi1 - ur12s * xr2 + ui12s * xi2;
xi1 = ui11r * br1 + ur11r * bi1 - ui12s * xr2 - ur12s * xi2;
if (zswap[icmax - 1]) {
x[x_dim1 + 1] = xr2;
x[x_dim1 + 2] = xr1;
x[(x_dim1 << 1) + 1] = xi2;
x[(x_dim1 << 1) + 2] = xi1;
} else {
x[x_dim1 + 1] = xr1;
x[x_dim1 + 2] = xr2;
x[(x_dim1 << 1) + 1] = xi1;
x[(x_dim1 << 1) + 2] = xi2;
}
/* Computing MAX */
d__1 = abs(xr1) + abs(xi1), d__2 = abs(xr2) + abs(xi2);
*xnorm = max(d__1,d__2);
/* Further scaling if norm(A) norm(X) > overflow */
if (*xnorm > 1. && cmax > 1.) {
if (*xnorm > bignum / cmax) {
temp = cmax / bignum;
x[x_dim1 + 1] = temp * x[x_dim1 + 1];
x[x_dim1 + 2] = temp * x[x_dim1 + 2];
x[(x_dim1 << 1) + 1] = temp * x[(x_dim1 << 1) + 1];
x[(x_dim1 << 1) + 2] = temp * x[(x_dim1 << 1) + 2];
*xnorm = temp * *xnorm;
*scale = temp * *scale;
}
}
}
}
return 0;
/* End of DLALN2 */
} /* dlaln2_ */
#undef crv
#undef civ
#undef cr
#undef ci
/* Subroutine */ int dlals0_(integer *icompq, integer *nl, integer *nr,
integer *sqre, integer *nrhs, doublereal *b, integer *ldb, doublereal
*bx, integer *ldbx, integer *perm, integer *givptr, integer *givcol,
integer *ldgcol, doublereal *givnum, integer *ldgnum, doublereal *
poles, doublereal *difl, doublereal *difr, doublereal *z__, integer *
k, doublereal *c__, doublereal *s, doublereal *work, integer *info)
{
/* System generated locals */
integer givcol_dim1, givcol_offset, b_dim1, b_offset, bx_dim1, bx_offset,
difr_dim1, difr_offset, givnum_dim1, givnum_offset, poles_dim1,
poles_offset, i__1, i__2;
doublereal d__1;
/* Local variables */
static integer i__, j, m, n;
static doublereal dj;
static integer nlp1;
static doublereal temp;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *);
extern doublereal dnrm2_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
static doublereal diflj, difrj, dsigj;
extern /* Subroutine */ int dgemv_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *), dcopy_(integer *,
doublereal *, integer *, doublereal *, integer *);
extern doublereal dlamc3_(doublereal *, doublereal *);
extern /* Subroutine */ int dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *), dlacpy_(char *, integer *, integer
*, doublereal *, integer *, doublereal *, integer *),
xerbla_(char *, integer *);
static doublereal dsigjp;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLALS0 applies back the multiplying factors of either the left or the
right singular vector matrix of a diagonal matrix appended by a row
to the right hand side matrix B in solving the least squares problem
using the divide-and-conquer SVD approach.
For the left singular vector matrix, three types of orthogonal
matrices are involved:
(1L) Givens rotations: the number of such rotations is GIVPTR; the
pairs of columns/rows they were applied to are stored in GIVCOL;
and the C- and S-values of these rotations are stored in GIVNUM.
(2L) Permutation. The (NL+1)-st row of B is to be moved to the first
row, and for J=2:N, PERM(J)-th row of B is to be moved to the
J-th row.
(3L) The left singular vector matrix of the remaining matrix.
For the right singular vector matrix, four types of orthogonal
matrices are involved:
(1R) The right singular vector matrix of the remaining matrix.
(2R) If SQRE = 1, one extra Givens rotation to generate the right
null space.
(3R) The inverse transformation of (2L).
(4R) The inverse transformation of (1L).
Arguments
=========
ICOMPQ (input) INTEGER
Specifies whether singular vectors are to be computed in
factored form:
= 0: Left singular vector matrix.
= 1: Right singular vector matrix.
NL (input) INTEGER
The row dimension of the upper block. NL >= 1.
NR (input) INTEGER
The row dimension of the lower block. NR >= 1.
SQRE (input) INTEGER
= 0: the lower block is an NR-by-NR square matrix.
= 1: the lower block is an NR-by-(NR+1) rectangular matrix.
The bidiagonal matrix has row dimension N = NL + NR + 1,
and column dimension M = N + SQRE.
NRHS (input) INTEGER
The number of columns of B and BX. NRHS must be at least 1.
B (input/output) DOUBLE PRECISION array, dimension ( LDB, NRHS )
On input, B contains the right hand sides of the least
squares problem in rows 1 through M. On output, B contains
the solution X in rows 1 through N.
LDB (input) INTEGER
The leading dimension of B. LDB must be at least
max(1,MAX( M, N ) ).
BX (workspace) DOUBLE PRECISION array, dimension ( LDBX, NRHS )
LDBX (input) INTEGER
The leading dimension of BX.
PERM (input) INTEGER array, dimension ( N )
The permutations (from deflation and sorting) applied
to the two blocks.
GIVPTR (input) INTEGER
The number of Givens rotations which took place in this
subproblem.
GIVCOL (input) INTEGER array, dimension ( LDGCOL, 2 )
Each pair of numbers indicates a pair of rows/columns
involved in a Givens rotation.
LDGCOL (input) INTEGER
The leading dimension of GIVCOL, must be at least N.
GIVNUM (input) DOUBLE PRECISION array, dimension ( LDGNUM, 2 )
Each number indicates the C or S value used in the
corresponding Givens rotation.
LDGNUM (input) INTEGER
The leading dimension of arrays DIFR, POLES and
GIVNUM, must be at least K.
POLES (input) DOUBLE PRECISION array, dimension ( LDGNUM, 2 )
On entry, POLES(1:K, 1) contains the new singular
values obtained from solving the secular equation, and
POLES(1:K, 2) is an array containing the poles in the secular
equation.
DIFL (input) DOUBLE PRECISION array, dimension ( K ).
On entry, DIFL(I) is the distance between I-th updated
(undeflated) singular value and the I-th (undeflated) old
singular value.
DIFR (input) DOUBLE PRECISION array, dimension ( LDGNUM, 2 ).
On entry, DIFR(I, 1) contains the distances between I-th
updated (undeflated) singular value and the I+1-th
(undeflated) old singular value. And DIFR(I, 2) is the
normalizing factor for the I-th right singular vector.
Z (input) DOUBLE PRECISION array, dimension ( K )
Contain the components of the deflation-adjusted updating row
vector.
K (input) INTEGER
Contains the dimension of the non-deflated matrix,
This is the order of the related secular equation. 1 <= K <=N.
C (input) DOUBLE PRECISION
C contains garbage if SQRE =0 and the C-value of a Givens
rotation related to the right null space if SQRE = 1.
S (input) DOUBLE PRECISION
S contains garbage if SQRE =0 and the S-value of a Givens
rotation related to the right null space if SQRE = 1.
WORK (workspace) DOUBLE PRECISION array, dimension ( K )
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
Based on contributions by
Ming Gu and Ren-Cang Li, Computer Science Division, University of
California at Berkeley, USA
Osni Marques, LBNL/NERSC, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
bx_dim1 = *ldbx;
bx_offset = 1 + bx_dim1;
bx -= bx_offset;
--perm;
givcol_dim1 = *ldgcol;
givcol_offset = 1 + givcol_dim1;
givcol -= givcol_offset;
difr_dim1 = *ldgnum;
difr_offset = 1 + difr_dim1;
difr -= difr_offset;
poles_dim1 = *ldgnum;
poles_offset = 1 + poles_dim1;
poles -= poles_offset;
givnum_dim1 = *ldgnum;
givnum_offset = 1 + givnum_dim1;
givnum -= givnum_offset;
--difl;
--z__;
--work;
/* Function Body */
*info = 0;
if (*icompq < 0 || *icompq > 1) {
*info = -1;
} else if (*nl < 1) {
*info = -2;
} else if (*nr < 1) {
*info = -3;
} else if (*sqre < 0 || *sqre > 1) {
*info = -4;
}
n = *nl + *nr + 1;
if (*nrhs < 1) {
*info = -5;
} else if (*ldb < n) {
*info = -7;
} else if (*ldbx < n) {
*info = -9;
} else if (*givptr < 0) {
*info = -11;
} else if (*ldgcol < n) {
*info = -13;
} else if (*ldgnum < n) {
*info = -15;
} else if (*k < 1) {
*info = -20;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLALS0", &i__1);
return 0;
}
m = n + *sqre;
nlp1 = *nl + 1;
if (*icompq == 0) {
/*
Apply back orthogonal transformations from the left.
Step (1L): apply back the Givens rotations performed.
*/
i__1 = *givptr;
for (i__ = 1; i__ <= i__1; ++i__) {
drot_(nrhs, &b[givcol[i__ + (givcol_dim1 << 1)] + b_dim1], ldb, &
b[givcol[i__ + givcol_dim1] + b_dim1], ldb, &givnum[i__ +
(givnum_dim1 << 1)], &givnum[i__ + givnum_dim1]);
/* L10: */
}
/* Step (2L): permute rows of B. */
dcopy_(nrhs, &b[nlp1 + b_dim1], ldb, &bx[bx_dim1 + 1], ldbx);
i__1 = n;
for (i__ = 2; i__ <= i__1; ++i__) {
dcopy_(nrhs, &b[perm[i__] + b_dim1], ldb, &bx[i__ + bx_dim1],
ldbx);
/* L20: */
}
/*
Step (3L): apply the inverse of the left singular vector
matrix to BX.
*/
if (*k == 1) {
dcopy_(nrhs, &bx[bx_offset], ldbx, &b[b_offset], ldb);
if (z__[1] < 0.) {
dscal_(nrhs, &c_b151, &b[b_offset], ldb);
}
} else {
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
diflj = difl[j];
dj = poles[j + poles_dim1];
dsigj = -poles[j + (poles_dim1 << 1)];
if (j < *k) {
difrj = -difr[j + difr_dim1];
dsigjp = -poles[j + 1 + (poles_dim1 << 1)];
}
if (z__[j] == 0. || poles[j + (poles_dim1 << 1)] == 0.) {
work[j] = 0.;
} else {
work[j] = -poles[j + (poles_dim1 << 1)] * z__[j] / diflj /
(poles[j + (poles_dim1 << 1)] + dj);
}
i__2 = j - 1;
for (i__ = 1; i__ <= i__2; ++i__) {
if (z__[i__] == 0. || poles[i__ + (poles_dim1 << 1)] ==
0.) {
work[i__] = 0.;
} else {
work[i__] = poles[i__ + (poles_dim1 << 1)] * z__[i__]
/ (dlamc3_(&poles[i__ + (poles_dim1 << 1)], &
dsigj) - diflj) / (poles[i__ + (poles_dim1 <<
1)] + dj);
}
/* L30: */
}
i__2 = *k;
for (i__ = j + 1; i__ <= i__2; ++i__) {
if (z__[i__] == 0. || poles[i__ + (poles_dim1 << 1)] ==
0.) {
work[i__] = 0.;
} else {
work[i__] = poles[i__ + (poles_dim1 << 1)] * z__[i__]
/ (dlamc3_(&poles[i__ + (poles_dim1 << 1)], &
dsigjp) + difrj) / (poles[i__ + (poles_dim1 <<
1)] + dj);
}
/* L40: */
}
work[1] = -1.;
temp = dnrm2_(k, &work[1], &c__1);
dgemv_("T", k, nrhs, &c_b15, &bx[bx_offset], ldbx, &work[1], &
c__1, &c_b29, &b[j + b_dim1], ldb);
dlascl_("G", &c__0, &c__0, &temp, &c_b15, &c__1, nrhs, &b[j +
b_dim1], ldb, info);
/* L50: */
}
}
/* Move the deflated rows of BX to B also. */
if (*k < max(m,n)) {
i__1 = n - *k;
dlacpy_("A", &i__1, nrhs, &bx[*k + 1 + bx_dim1], ldbx, &b[*k + 1
+ b_dim1], ldb);
}
} else {
/*
Apply back the right orthogonal transformations.
Step (1R): apply back the new right singular vector matrix
to B.
*/
if (*k == 1) {
dcopy_(nrhs, &b[b_offset], ldb, &bx[bx_offset], ldbx);
} else {
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dsigj = poles[j + (poles_dim1 << 1)];
if (z__[j] == 0.) {
work[j] = 0.;
} else {
work[j] = -z__[j] / difl[j] / (dsigj + poles[j +
poles_dim1]) / difr[j + (difr_dim1 << 1)];
}
i__2 = j - 1;
for (i__ = 1; i__ <= i__2; ++i__) {
if (z__[j] == 0.) {
work[i__] = 0.;
} else {
d__1 = -poles[i__ + 1 + (poles_dim1 << 1)];
work[i__] = z__[j] / (dlamc3_(&dsigj, &d__1) - difr[
i__ + difr_dim1]) / (dsigj + poles[i__ +
poles_dim1]) / difr[i__ + (difr_dim1 << 1)];
}
/* L60: */
}
i__2 = *k;
for (i__ = j + 1; i__ <= i__2; ++i__) {
if (z__[j] == 0.) {
work[i__] = 0.;
} else {
d__1 = -poles[i__ + (poles_dim1 << 1)];
work[i__] = z__[j] / (dlamc3_(&dsigj, &d__1) - difl[
i__]) / (dsigj + poles[i__ + poles_dim1]) /
difr[i__ + (difr_dim1 << 1)];
}
/* L70: */
}
dgemv_("T", k, nrhs, &c_b15, &b[b_offset], ldb, &work[1], &
c__1, &c_b29, &bx[j + bx_dim1], ldbx);
/* L80: */
}
}
/*
Step (2R): if SQRE = 1, apply back the rotation that is
related to the right null space of the subproblem.
*/
if (*sqre == 1) {
dcopy_(nrhs, &b[m + b_dim1], ldb, &bx[m + bx_dim1], ldbx);
drot_(nrhs, &bx[bx_dim1 + 1], ldbx, &bx[m + bx_dim1], ldbx, c__,
s);
}
if (*k < max(m,n)) {
i__1 = n - *k;
dlacpy_("A", &i__1, nrhs, &b[*k + 1 + b_dim1], ldb, &bx[*k + 1 +
bx_dim1], ldbx);
}
/* Step (3R): permute rows of B. */
dcopy_(nrhs, &bx[bx_dim1 + 1], ldbx, &b[nlp1 + b_dim1], ldb);
if (*sqre == 1) {
dcopy_(nrhs, &bx[m + bx_dim1], ldbx, &b[m + b_dim1], ldb);
}
i__1 = n;
for (i__ = 2; i__ <= i__1; ++i__) {
dcopy_(nrhs, &bx[i__ + bx_dim1], ldbx, &b[perm[i__] + b_dim1],
ldb);
/* L90: */
}
/* Step (4R): apply back the Givens rotations performed. */
for (i__ = *givptr; i__ >= 1; --i__) {
d__1 = -givnum[i__ + givnum_dim1];
drot_(nrhs, &b[givcol[i__ + (givcol_dim1 << 1)] + b_dim1], ldb, &
b[givcol[i__ + givcol_dim1] + b_dim1], ldb, &givnum[i__ +
(givnum_dim1 << 1)], &d__1);
/* L100: */
}
}
return 0;
/* End of DLALS0 */
} /* dlals0_ */
/* Subroutine */ int dlalsa_(integer *icompq, integer *smlsiz, integer *n,
integer *nrhs, doublereal *b, integer *ldb, doublereal *bx, integer *
ldbx, doublereal *u, integer *ldu, doublereal *vt, integer *k,
doublereal *difl, doublereal *difr, doublereal *z__, doublereal *
poles, integer *givptr, integer *givcol, integer *ldgcol, integer *
perm, doublereal *givnum, doublereal *c__, doublereal *s, doublereal *
work, integer *iwork, integer *info)
{
/* System generated locals */
integer givcol_dim1, givcol_offset, perm_dim1, perm_offset, b_dim1,
b_offset, bx_dim1, bx_offset, difl_dim1, difl_offset, difr_dim1,
difr_offset, givnum_dim1, givnum_offset, poles_dim1, poles_offset,
u_dim1, u_offset, vt_dim1, vt_offset, z_dim1, z_offset, i__1,
i__2;
/* Local variables */
static integer i__, j, i1, ic, lf, nd, ll, nl, nr, im1, nlf, nrf, lvl,
ndb1, nlp1, lvl2, nrp1, nlvl, sqre;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static integer inode, ndiml, ndimr;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *), dlals0_(integer *, integer *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
integer *, integer *, integer *, integer *, integer *, doublereal
*, integer *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *, doublereal *, doublereal *, doublereal *,
integer *), dlasdt_(integer *, integer *, integer *, integer *,
integer *, integer *, integer *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLALSA is an itermediate step in solving the least squares problem
by computing the SVD of the coefficient matrix in compact form (The
singular vectors are computed as products of simple orthorgonal
matrices.).
If ICOMPQ = 0, DLALSA applies the inverse of the left singular vector
matrix of an upper bidiagonal matrix to the right hand side; and if
ICOMPQ = 1, DLALSA applies the right singular vector matrix to the
right hand side. The singular vector matrices were generated in
compact form by DLALSA.
Arguments
=========
ICOMPQ (input) INTEGER
Specifies whether the left or the right singular vector
matrix is involved.
= 0: Left singular vector matrix
= 1: Right singular vector matrix
SMLSIZ (input) INTEGER
The maximum size of the subproblems at the bottom of the
computation tree.
N (input) INTEGER
The row and column dimensions of the upper bidiagonal matrix.
NRHS (input) INTEGER
The number of columns of B and BX. NRHS must be at least 1.
B (input/output) DOUBLE PRECISION array, dimension ( LDB, NRHS )
On input, B contains the right hand sides of the least
squares problem in rows 1 through M.
On output, B contains the solution X in rows 1 through N.
LDB (input) INTEGER
The leading dimension of B in the calling subprogram.
LDB must be at least max(1,MAX( M, N ) ).
BX (output) DOUBLE PRECISION array, dimension ( LDBX, NRHS )
On exit, the result of applying the left or right singular
vector matrix to B.
LDBX (input) INTEGER
The leading dimension of BX.
U (input) DOUBLE PRECISION array, dimension ( LDU, SMLSIZ ).
On entry, U contains the left singular vector matrices of all
subproblems at the bottom level.
LDU (input) INTEGER, LDU = > N.
The leading dimension of arrays U, VT, DIFL, DIFR,
POLES, GIVNUM, and Z.
VT (input) DOUBLE PRECISION array, dimension ( LDU, SMLSIZ+1 ).
On entry, VT' contains the right singular vector matrices of
all subproblems at the bottom level.
K (input) INTEGER array, dimension ( N ).
DIFL (input) DOUBLE PRECISION array, dimension ( LDU, NLVL ).
where NLVL = INT(log_2 (N/(SMLSIZ+1))) + 1.
DIFR (input) DOUBLE PRECISION array, dimension ( LDU, 2 * NLVL ).
On entry, DIFL(*, I) and DIFR(*, 2 * I -1) record
distances between singular values on the I-th level and
singular values on the (I -1)-th level, and DIFR(*, 2 * I)
record the normalizing factors of the right singular vectors
matrices of subproblems on I-th level.
Z (input) DOUBLE PRECISION array, dimension ( LDU, NLVL ).
On entry, Z(1, I) contains the components of the deflation-
adjusted updating row vector for subproblems on the I-th
level.
POLES (input) DOUBLE PRECISION array, dimension ( LDU, 2 * NLVL ).
On entry, POLES(*, 2 * I -1: 2 * I) contains the new and old
singular values involved in the secular equations on the I-th
level.
GIVPTR (input) INTEGER array, dimension ( N ).
On entry, GIVPTR( I ) records the number of Givens
rotations performed on the I-th problem on the computation
tree.
GIVCOL (input) INTEGER array, dimension ( LDGCOL, 2 * NLVL ).
On entry, for each I, GIVCOL(*, 2 * I - 1: 2 * I) records the
locations of Givens rotations performed on the I-th level on
the computation tree.
LDGCOL (input) INTEGER, LDGCOL = > N.
The leading dimension of arrays GIVCOL and PERM.
PERM (input) INTEGER array, dimension ( LDGCOL, NLVL ).
On entry, PERM(*, I) records permutations done on the I-th
level of the computation tree.
GIVNUM (input) DOUBLE PRECISION array, dimension ( LDU, 2 * NLVL ).
On entry, GIVNUM(*, 2 *I -1 : 2 * I) records the C- and S-
values of Givens rotations performed on the I-th level on the
computation tree.
C (input) DOUBLE PRECISION array, dimension ( N ).
On entry, if the I-th subproblem is not square,
C( I ) contains the C-value of a Givens rotation related to
the right null space of the I-th subproblem.
S (input) DOUBLE PRECISION array, dimension ( N ).
On entry, if the I-th subproblem is not square,
S( I ) contains the S-value of a Givens rotation related to
the right null space of the I-th subproblem.
WORK (workspace) DOUBLE PRECISION array.
The dimension must be at least N.
IWORK (workspace) INTEGER array.
The dimension must be at least 3 * N
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
Based on contributions by
Ming Gu and Ren-Cang Li, Computer Science Division, University of
California at Berkeley, USA
Osni Marques, LBNL/NERSC, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
bx_dim1 = *ldbx;
bx_offset = 1 + bx_dim1;
bx -= bx_offset;
givnum_dim1 = *ldu;
givnum_offset = 1 + givnum_dim1;
givnum -= givnum_offset;
poles_dim1 = *ldu;
poles_offset = 1 + poles_dim1;
poles -= poles_offset;
z_dim1 = *ldu;
z_offset = 1 + z_dim1;
z__ -= z_offset;
difr_dim1 = *ldu;
difr_offset = 1 + difr_dim1;
difr -= difr_offset;
difl_dim1 = *ldu;
difl_offset = 1 + difl_dim1;
difl -= difl_offset;
vt_dim1 = *ldu;
vt_offset = 1 + vt_dim1;
vt -= vt_offset;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
--k;
--givptr;
perm_dim1 = *ldgcol;
perm_offset = 1 + perm_dim1;
perm -= perm_offset;
givcol_dim1 = *ldgcol;
givcol_offset = 1 + givcol_dim1;
givcol -= givcol_offset;
--c__;
--s;
--work;
--iwork;
/* Function Body */
*info = 0;
if (*icompq < 0 || *icompq > 1) {
*info = -1;
} else if (*smlsiz < 3) {
*info = -2;
} else if (*n < *smlsiz) {
*info = -3;
} else if (*nrhs < 1) {
*info = -4;
} else if (*ldb < *n) {
*info = -6;
} else if (*ldbx < *n) {
*info = -8;
} else if (*ldu < *n) {
*info = -10;
} else if (*ldgcol < *n) {
*info = -19;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLALSA", &i__1);
return 0;
}
/* Book-keeping and setting up the computation tree. */
inode = 1;
ndiml = inode + *n;
ndimr = ndiml + *n;
dlasdt_(n, &nlvl, &nd, &iwork[inode], &iwork[ndiml], &iwork[ndimr],
smlsiz);
/*
The following code applies back the left singular vector factors.
For applying back the right singular vector factors, go to 50.
*/
if (*icompq == 1) {
goto L50;
}
/*
The nodes on the bottom level of the tree were solved
by DLASDQ. The corresponding left and right singular vector
matrices are in explicit form. First apply back the left
singular vector matrices.
*/
ndb1 = (nd + 1) / 2;
i__1 = nd;
for (i__ = ndb1; i__ <= i__1; ++i__) {
/*
IC : center row of each node
NL : number of rows of left subproblem
NR : number of rows of right subproblem
NLF: starting row of the left subproblem
NRF: starting row of the right subproblem
*/
i1 = i__ - 1;
ic = iwork[inode + i1];
nl = iwork[ndiml + i1];
nr = iwork[ndimr + i1];
nlf = ic - nl;
nrf = ic + 1;
dgemm_("T", "N", &nl, nrhs, &nl, &c_b15, &u[nlf + u_dim1], ldu, &b[
nlf + b_dim1], ldb, &c_b29, &bx[nlf + bx_dim1], ldbx);
dgemm_("T", "N", &nr, nrhs, &nr, &c_b15, &u[nrf + u_dim1], ldu, &b[
nrf + b_dim1], ldb, &c_b29, &bx[nrf + bx_dim1], ldbx);
/* L10: */
}
/*
Next copy the rows of B that correspond to unchanged rows
in the bidiagonal matrix to BX.
*/
i__1 = nd;
for (i__ = 1; i__ <= i__1; ++i__) {
ic = iwork[inode + i__ - 1];
dcopy_(nrhs, &b[ic + b_dim1], ldb, &bx[ic + bx_dim1], ldbx);
/* L20: */
}
/*
Finally go through the left singular vector matrices of all
the other subproblems bottom-up on the tree.
*/
j = pow_ii(&c__2, &nlvl);
sqre = 0;
for (lvl = nlvl; lvl >= 1; --lvl) {
lvl2 = (lvl << 1) - 1;
/*
find the first node LF and last node LL on
the current level LVL
*/
if (lvl == 1) {
lf = 1;
ll = 1;
} else {
i__1 = lvl - 1;
lf = pow_ii(&c__2, &i__1);
ll = (lf << 1) - 1;
}
i__1 = ll;
for (i__ = lf; i__ <= i__1; ++i__) {
im1 = i__ - 1;
ic = iwork[inode + im1];
nl = iwork[ndiml + im1];
nr = iwork[ndimr + im1];
nlf = ic - nl;
nrf = ic + 1;
--j;
dlals0_(icompq, &nl, &nr, &sqre, nrhs, &bx[nlf + bx_dim1], ldbx, &
b[nlf + b_dim1], ldb, &perm[nlf + lvl * perm_dim1], &
givptr[j], &givcol[nlf + lvl2 * givcol_dim1], ldgcol, &
givnum[nlf + lvl2 * givnum_dim1], ldu, &poles[nlf + lvl2 *
poles_dim1], &difl[nlf + lvl * difl_dim1], &difr[nlf +
lvl2 * difr_dim1], &z__[nlf + lvl * z_dim1], &k[j], &c__[
j], &s[j], &work[1], info);
/* L30: */
}
/* L40: */
}
goto L90;
/* ICOMPQ = 1: applying back the right singular vector factors. */
L50:
/*
First now go through the right singular vector matrices of all
the tree nodes top-down.
*/
j = 0;
i__1 = nlvl;
for (lvl = 1; lvl <= i__1; ++lvl) {
lvl2 = (lvl << 1) - 1;
/*
Find the first node LF and last node LL on
the current level LVL.
*/
if (lvl == 1) {
lf = 1;
ll = 1;
} else {
i__2 = lvl - 1;
lf = pow_ii(&c__2, &i__2);
ll = (lf << 1) - 1;
}
i__2 = lf;
for (i__ = ll; i__ >= i__2; --i__) {
im1 = i__ - 1;
ic = iwork[inode + im1];
nl = iwork[ndiml + im1];
nr = iwork[ndimr + im1];
nlf = ic - nl;
nrf = ic + 1;
if (i__ == ll) {
sqre = 0;
} else {
sqre = 1;
}
++j;
dlals0_(icompq, &nl, &nr, &sqre, nrhs, &b[nlf + b_dim1], ldb, &bx[
nlf + bx_dim1], ldbx, &perm[nlf + lvl * perm_dim1], &
givptr[j], &givcol[nlf + lvl2 * givcol_dim1], ldgcol, &
givnum[nlf + lvl2 * givnum_dim1], ldu, &poles[nlf + lvl2 *
poles_dim1], &difl[nlf + lvl * difl_dim1], &difr[nlf +
lvl2 * difr_dim1], &z__[nlf + lvl * z_dim1], &k[j], &c__[
j], &s[j], &work[1], info);
/* L60: */
}
/* L70: */
}
/*
The nodes on the bottom level of the tree were solved
by DLASDQ. The corresponding right singular vector
matrices are in explicit form. Apply them back.
*/
ndb1 = (nd + 1) / 2;
i__1 = nd;
for (i__ = ndb1; i__ <= i__1; ++i__) {
i1 = i__ - 1;
ic = iwork[inode + i1];
nl = iwork[ndiml + i1];
nr = iwork[ndimr + i1];
nlp1 = nl + 1;
if (i__ == nd) {
nrp1 = nr;
} else {
nrp1 = nr + 1;
}
nlf = ic - nl;
nrf = ic + 1;
dgemm_("T", "N", &nlp1, nrhs, &nlp1, &c_b15, &vt[nlf + vt_dim1], ldu,
&b[nlf + b_dim1], ldb, &c_b29, &bx[nlf + bx_dim1], ldbx);
dgemm_("T", "N", &nrp1, nrhs, &nrp1, &c_b15, &vt[nrf + vt_dim1], ldu,
&b[nrf + b_dim1], ldb, &c_b29, &bx[nrf + bx_dim1], ldbx);
/* L80: */
}
L90:
return 0;
/* End of DLALSA */
} /* dlalsa_ */
/* Subroutine */ int dlalsd_(char *uplo, integer *smlsiz, integer *n, integer
*nrhs, doublereal *d__, doublereal *e, doublereal *b, integer *ldb,
doublereal *rcond, integer *rank, doublereal *work, integer *iwork,
integer *info)
{
/* System generated locals */
integer b_dim1, b_offset, i__1, i__2;
doublereal d__1;
/* Local variables */
static integer c__, i__, j, k;
static doublereal r__;
static integer s, u, z__;
static doublereal cs;
static integer bx;
static doublereal sn;
static integer st, vt, nm1, st1;
static doublereal eps;
static integer iwk;
static doublereal tol;
static integer difl, difr;
static doublereal rcnd;
static integer perm, nsub;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *);
static integer nlvl, sqre, bxst;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *),
dcopy_(integer *, doublereal *, integer *, doublereal *, integer
*);
static integer poles, sizei, nsize, nwork, icmpq1, icmpq2;
extern /* Subroutine */ int dlasda_(integer *, integer *, integer *,
integer *, doublereal *, doublereal *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *, integer *, integer *, integer *,
doublereal *, doublereal *, doublereal *, doublereal *, integer *,
integer *), dlalsa_(integer *, integer *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
doublereal *, doublereal *, integer *, integer *, integer *,
integer *, doublereal *, doublereal *, doublereal *, doublereal *,
integer *, integer *), dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *);
extern integer idamax_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dlasdq_(char *, integer *, integer *, integer
*, integer *, integer *, doublereal *, doublereal *, doublereal *,
integer *, doublereal *, integer *, doublereal *, integer *,
doublereal *, integer *), dlacpy_(char *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *), dlartg_(doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *), dlaset_(char *, integer *, integer *,
doublereal *, doublereal *, doublereal *, integer *),
xerbla_(char *, integer *);
static integer givcol;
extern doublereal dlanst_(char *, integer *, doublereal *, doublereal *);
extern /* Subroutine */ int dlasrt_(char *, integer *, doublereal *,
integer *);
static doublereal orgnrm;
static integer givnum, givptr, smlszp;
/*
-- LAPACK routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLALSD uses the singular value decomposition of A to solve the least
squares problem of finding X to minimize the Euclidean norm of each
column of A*X-B, where A is N-by-N upper bidiagonal, and X and B
are N-by-NRHS. The solution X overwrites B.
The singular values of A smaller than RCOND times the largest
singular value are treated as zero in solving the least squares
problem; in this case a minimum norm solution is returned.
The actual singular values are returned in D in ascending order.
This code makes very mild assumptions about floating point
arithmetic. It will work on machines with a guard digit in
add/subtract, or on those binary machines without guard digits
which subtract like the Cray XMP, Cray YMP, Cray C 90, or Cray 2.
It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': D and E define an upper bidiagonal matrix.
= 'L': D and E define a lower bidiagonal matrix.
SMLSIZ (input) INTEGER
The maximum size of the subproblems at the bottom of the
computation tree.
N (input) INTEGER
The dimension of the bidiagonal matrix. N >= 0.
NRHS (input) INTEGER
The number of columns of B. NRHS must be at least 1.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry D contains the main diagonal of the bidiagonal
matrix. On exit, if INFO = 0, D contains its singular values.
E (input/output) DOUBLE PRECISION array, dimension (N-1)
Contains the super-diagonal entries of the bidiagonal matrix.
On exit, E has been destroyed.
B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS)
On input, B contains the right hand sides of the least
squares problem. On output, B contains the solution X.
LDB (input) INTEGER
The leading dimension of B in the calling subprogram.
LDB must be at least max(1,N).
RCOND (input) DOUBLE PRECISION
The singular values of A less than or equal to RCOND times
the largest singular value are treated as zero in solving
the least squares problem. If RCOND is negative,
machine precision is used instead.
For example, if diag(S)*X=B were the least squares problem,
where diag(S) is a diagonal matrix of singular values, the
solution would be X(i) = B(i) / S(i) if S(i) is greater than
RCOND*max(S), and X(i) = 0 if S(i) is less than or equal to
RCOND*max(S).
RANK (output) INTEGER
The number of singular values of A greater than RCOND times
the largest singular value.
WORK (workspace) DOUBLE PRECISION array, dimension at least
(9*N + 2*N*SMLSIZ + 8*N*NLVL + N*NRHS + (SMLSIZ+1)**2),
where NLVL = max(0, INT(log_2 (N/(SMLSIZ+1))) + 1).
IWORK (workspace) INTEGER array, dimension at least
(3*N*NLVL + 11*N)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: The algorithm failed to compute a singular value while
working on the submatrix lying in rows and columns
INFO/(N+1) through MOD(INFO,N+1).
Further Details
===============
Based on contributions by
Ming Gu and Ren-Cang Li, Computer Science Division, University of
California at Berkeley, USA
Osni Marques, LBNL/NERSC, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--e;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
--work;
--iwork;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -3;
} else if (*nrhs < 1) {
*info = -4;
} else if (*ldb < 1 || *ldb < *n) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLALSD", &i__1);
return 0;
}
eps = EPSILON;
/* Set up the tolerance. */
if (*rcond <= 0. || *rcond >= 1.) {
rcnd = eps;
} else {
rcnd = *rcond;
}
*rank = 0;
/* Quick return if possible. */
if (*n == 0) {
return 0;
} else if (*n == 1) {
if (d__[1] == 0.) {
dlaset_("A", &c__1, nrhs, &c_b29, &c_b29, &b[b_offset], ldb);
} else {
*rank = 1;
dlascl_("G", &c__0, &c__0, &d__[1], &c_b15, &c__1, nrhs, &b[
b_offset], ldb, info);
d__[1] = abs(d__[1]);
}
return 0;
}
/* Rotate the matrix if it is lower bidiagonal. */
if (*(unsigned char *)uplo == 'L') {
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
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 (*nrhs == 1) {
drot_(&c__1, &b[i__ + b_dim1], &c__1, &b[i__ + 1 + b_dim1], &
c__1, &cs, &sn);
} else {
work[(i__ << 1) - 1] = cs;
work[i__ * 2] = sn;
}
/* L10: */
}
if (*nrhs > 1) {
i__1 = *nrhs;
for (i__ = 1; i__ <= i__1; ++i__) {
i__2 = *n - 1;
for (j = 1; j <= i__2; ++j) {
cs = work[(j << 1) - 1];
sn = work[j * 2];
drot_(&c__1, &b[j + i__ * b_dim1], &c__1, &b[j + 1 + i__ *
b_dim1], &c__1, &cs, &sn);
/* L20: */
}
/* L30: */
}
}
}
/* Scale. */
nm1 = *n - 1;
orgnrm = dlanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.) {
dlaset_("A", n, nrhs, &c_b29, &c_b29, &b[b_offset], ldb);
return 0;
}
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, n, &c__1, &d__[1], n, info);
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, &nm1, &c__1, &e[1], &nm1,
info);
/*
If N is smaller than the minimum divide size SMLSIZ, then solve
the problem with another solver.
*/
if (*n <= *smlsiz) {
nwork = *n * *n + 1;
dlaset_("A", n, n, &c_b29, &c_b15, &work[1], n);
dlasdq_("U", &c__0, n, n, &c__0, nrhs, &d__[1], &e[1], &work[1], n, &
work[1], n, &b[b_offset], ldb, &work[nwork], info);
if (*info != 0) {
return 0;
}
tol = rcnd * (d__1 = d__[idamax_(n, &d__[1], &c__1)], abs(d__1));
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if (d__[i__] <= tol) {
dlaset_("A", &c__1, nrhs, &c_b29, &c_b29, &b[i__ + b_dim1],
ldb);
} else {
dlascl_("G", &c__0, &c__0, &d__[i__], &c_b15, &c__1, nrhs, &b[
i__ + b_dim1], ldb, info);
++(*rank);
}
/* L40: */
}
dgemm_("T", "N", n, nrhs, n, &c_b15, &work[1], n, &b[b_offset], ldb, &
c_b29, &work[nwork], n);
dlacpy_("A", n, nrhs, &work[nwork], n, &b[b_offset], ldb);
/* Unscale. */
dlascl_("G", &c__0, &c__0, &c_b15, &orgnrm, n, &c__1, &d__[1], n,
info);
dlasrt_("D", n, &d__[1], info);
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, n, nrhs, &b[b_offset],
ldb, info);
return 0;
}
/* Book-keeping and setting up some constants. */
nlvl = (integer) (log((doublereal) (*n) / (doublereal) (*smlsiz + 1)) /
log(2.)) + 1;
smlszp = *smlsiz + 1;
u = 1;
vt = *smlsiz * *n + 1;
difl = vt + smlszp * *n;
difr = difl + nlvl * *n;
z__ = difr + (nlvl * *n << 1);
c__ = z__ + nlvl * *n;
s = c__ + *n;
poles = s + *n;
givnum = poles + (nlvl << 1) * *n;
bx = givnum + (nlvl << 1) * *n;
nwork = bx + *n * *nrhs;
sizei = *n + 1;
k = sizei + *n;
givptr = k + *n;
perm = givptr + *n;
givcol = perm + nlvl * *n;
iwk = givcol + (nlvl * *n << 1);
st = 1;
sqre = 0;
icmpq1 = 1;
icmpq2 = 0;
nsub = 0;
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((d__1 = d__[i__], abs(d__1)) < eps) {
d__[i__] = d_sign(&eps, &d__[i__]);
}
/* L50: */
}
i__1 = nm1;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((d__1 = e[i__], abs(d__1)) < eps || i__ == nm1) {
++nsub;
iwork[nsub] = st;
/*
Subproblem found. First determine its size and then
apply divide and conquer on it.
*/
if (i__ < nm1) {
/* A subproblem with E(I) small for I < NM1. */
nsize = i__ - st + 1;
iwork[sizei + nsub - 1] = nsize;
} else if ((d__1 = e[i__], abs(d__1)) >= eps) {
/* A subproblem with E(NM1) not too small but I = NM1. */
nsize = *n - st + 1;
iwork[sizei + nsub - 1] = nsize;
} else {
/*
A subproblem with E(NM1) small. This implies an
1-by-1 subproblem at D(N), which is not solved
explicitly.
*/
nsize = i__ - st + 1;
iwork[sizei + nsub - 1] = nsize;
++nsub;
iwork[nsub] = *n;
iwork[sizei + nsub - 1] = 1;
dcopy_(nrhs, &b[*n + b_dim1], ldb, &work[bx + nm1], n);
}
st1 = st - 1;
if (nsize == 1) {
/*
This is a 1-by-1 subproblem and is not solved
explicitly.
*/
dcopy_(nrhs, &b[st + b_dim1], ldb, &work[bx + st1], n);
} else if (nsize <= *smlsiz) {
/* This is a small subproblem and is solved by DLASDQ. */
dlaset_("A", &nsize, &nsize, &c_b29, &c_b15, &work[vt + st1],
n);
dlasdq_("U", &c__0, &nsize, &nsize, &c__0, nrhs, &d__[st], &e[
st], &work[vt + st1], n, &work[nwork], n, &b[st +
b_dim1], ldb, &work[nwork], info);
if (*info != 0) {
return 0;
}
dlacpy_("A", &nsize, nrhs, &b[st + b_dim1], ldb, &work[bx +
st1], n);
} else {
/* A large problem. Solve it using divide and conquer. */
dlasda_(&icmpq1, smlsiz, &nsize, &sqre, &d__[st], &e[st], &
work[u + st1], n, &work[vt + st1], &iwork[k + st1], &
work[difl + st1], &work[difr + st1], &work[z__ + st1],
&work[poles + st1], &iwork[givptr + st1], &iwork[
givcol + st1], n, &iwork[perm + st1], &work[givnum +
st1], &work[c__ + st1], &work[s + st1], &work[nwork],
&iwork[iwk], info);
if (*info != 0) {
return 0;
}
bxst = bx + st1;
dlalsa_(&icmpq2, smlsiz, &nsize, nrhs, &b[st + b_dim1], ldb, &
work[bxst], n, &work[u + st1], n, &work[vt + st1], &
iwork[k + st1], &work[difl + st1], &work[difr + st1],
&work[z__ + st1], &work[poles + st1], &iwork[givptr +
st1], &iwork[givcol + st1], n, &iwork[perm + st1], &
work[givnum + st1], &work[c__ + st1], &work[s + st1],
&work[nwork], &iwork[iwk], info);
if (*info != 0) {
return 0;
}
}
st = i__ + 1;
}
/* L60: */
}
/* Apply the singular values and treat the tiny ones as zero. */
tol = rcnd * (d__1 = d__[idamax_(n, &d__[1], &c__1)], abs(d__1));
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
/*
Some of the elements in D can be negative because 1-by-1
subproblems were not solved explicitly.
*/
if ((d__1 = d__[i__], abs(d__1)) <= tol) {
dlaset_("A", &c__1, nrhs, &c_b29, &c_b29, &work[bx + i__ - 1], n);
} else {
++(*rank);
dlascl_("G", &c__0, &c__0, &d__[i__], &c_b15, &c__1, nrhs, &work[
bx + i__ - 1], n, info);
}
d__[i__] = (d__1 = d__[i__], abs(d__1));
/* L70: */
}
/* Now apply back the right singular vectors. */
icmpq2 = 1;
i__1 = nsub;
for (i__ = 1; i__ <= i__1; ++i__) {
st = iwork[i__];
st1 = st - 1;
nsize = iwork[sizei + i__ - 1];
bxst = bx + st1;
if (nsize == 1) {
dcopy_(nrhs, &work[bxst], n, &b[st + b_dim1], ldb);
} else if (nsize <= *smlsiz) {
dgemm_("T", "N", &nsize, nrhs, &nsize, &c_b15, &work[vt + st1], n,
&work[bxst], n, &c_b29, &b[st + b_dim1], ldb);
} else {
dlalsa_(&icmpq2, smlsiz, &nsize, nrhs, &work[bxst], n, &b[st +
b_dim1], ldb, &work[u + st1], n, &work[vt + st1], &iwork[
k + st1], &work[difl + st1], &work[difr + st1], &work[z__
+ st1], &work[poles + st1], &iwork[givptr + st1], &iwork[
givcol + st1], n, &iwork[perm + st1], &work[givnum + st1],
&work[c__ + st1], &work[s + st1], &work[nwork], &iwork[
iwk], info);
if (*info != 0) {
return 0;
}
}
/* L80: */
}
/* Unscale and sort the singular values. */
dlascl_("G", &c__0, &c__0, &c_b15, &orgnrm, n, &c__1, &d__[1], n, info);
dlasrt_("D", n, &d__[1], info);
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, n, nrhs, &b[b_offset], ldb,
info);
return 0;
/* End of DLALSD */
} /* dlalsd_ */
/* Subroutine */ int dlamrg_(integer *n1, integer *n2, doublereal *a, integer
*dtrd1, integer *dtrd2, integer *index)
{
/* System generated locals */
integer i__1;
/* Local variables */
static integer i__, ind1, ind2, n1sv, n2sv;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAMRG will create a permutation list which will merge the elements
of A (which is composed of two independently sorted sets) into a
single set which is sorted in ascending order.
Arguments
=========
N1 (input) INTEGER
N2 (input) INTEGER
These arguements contain the respective lengths of the two
sorted lists to be merged.
A (input) DOUBLE PRECISION array, dimension (N1+N2)
The first N1 elements of A contain a list of numbers which
are sorted in either ascending or descending order. Likewise
for the final N2 elements.
DTRD1 (input) INTEGER
DTRD2 (input) INTEGER
These are the strides to be taken through the array A.
Allowable strides are 1 and -1. They indicate whether a
subset of A is sorted in ascending (DTRDx = 1) or descending
(DTRDx = -1) order.
INDEX (output) INTEGER array, dimension (N1+N2)
On exit this array will contain a permutation such that
if B( I ) = A( INDEX( I ) ) for I=1,N1+N2, then B will be
sorted in ascending order.
=====================================================================
*/
/* Parameter adjustments */
--index;
--a;
/* Function Body */
n1sv = *n1;
n2sv = *n2;
if (*dtrd1 > 0) {
ind1 = 1;
} else {
ind1 = *n1;
}
if (*dtrd2 > 0) {
ind2 = *n1 + 1;
} else {
ind2 = *n1 + *n2;
}
i__ = 1;
/* while ( (N1SV > 0) & (N2SV > 0) ) */
L10:
if (n1sv > 0 && n2sv > 0) {
if (a[ind1] <= a[ind2]) {
index[i__] = ind1;
++i__;
ind1 += *dtrd1;
--n1sv;
} else {
index[i__] = ind2;
++i__;
ind2 += *dtrd2;
--n2sv;
}
goto L10;
}
/* end while */
if (n1sv == 0) {
i__1 = n2sv;
for (n1sv = 1; n1sv <= i__1; ++n1sv) {
index[i__] = ind2;
++i__;
ind2 += *dtrd2;
/* L20: */
}
} else {
/* N2SV .EQ. 0 */
i__1 = n1sv;
for (n2sv = 1; n2sv <= i__1; ++n2sv) {
index[i__] = ind1;
++i__;
ind1 += *dtrd1;
/* L30: */
}
}
return 0;
/* End of DLAMRG */
} /* dlamrg_ */
doublereal dlange_(char *norm, integer *m, integer *n, doublereal *a, integer
*lda, doublereal *work)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2;
doublereal ret_val, d__1, d__2, d__3;
/* Local variables */
static integer i__, j;
static doublereal sum, scale;
extern logical lsame_(char *, char *);
static doublereal value;
extern /* Subroutine */ int dlassq_(integer *, doublereal *, integer *,
doublereal *, doublereal *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLANGE returns the value of the one norm, or the Frobenius norm, or
the infinity norm, or the element of largest absolute value of a
real matrix A.
Description
===========
DLANGE returns the value
DLANGE = ( max(abs(A(i,j))), NORM = 'M' or 'm'
(
( norm1(A), NORM = '1', 'O' or 'o'
(
( normI(A), NORM = 'I' or 'i'
(
( normF(A), NORM = 'F', 'f', 'E' or 'e'
where norm1 denotes the one norm of a matrix (maximum column sum),
normI denotes the infinity norm of a matrix (maximum row sum) and
normF denotes the Frobenius norm of a matrix (square root of sum of
squares). Note that max(abs(A(i,j))) is not a consistent matrix norm.
Arguments
=========
NORM (input) CHARACTER*1
Specifies the value to be returned in DLANGE as described
above.
M (input) INTEGER
The number of rows of the matrix A. M >= 0. When M = 0,
DLANGE is set to zero.
N (input) INTEGER
The number of columns of the matrix A. N >= 0. When N = 0,
DLANGE is set to zero.
A (input) DOUBLE PRECISION array, dimension (LDA,N)
The m by n matrix A.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(M,1).
WORK (workspace) DOUBLE PRECISION array, dimension (MAX(1,LWORK)),
where LWORK >= M when NORM = 'I'; otherwise, WORK is not
referenced.
=====================================================================
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--work;
/* Function Body */
if (min(*m,*n) == 0) {
value = 0.;
} else if (lsame_(norm, "M")) {
/* Find max(abs(A(i,j))). */
value = 0.;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
/* Computing MAX */
d__2 = value, d__3 = (d__1 = a[i__ + j * a_dim1], abs(d__1));
value = max(d__2,d__3);
/* L10: */
}
/* L20: */
}
} else if (lsame_(norm, "O") || *(unsigned char *)
norm == '1') {
/* Find norm1(A). */
value = 0.;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = 0.;
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
sum += (d__1 = a[i__ + j * a_dim1], abs(d__1));
/* L30: */
}
value = max(value,sum);
/* L40: */
}
} else if (lsame_(norm, "I")) {
/* Find normI(A). */
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
work[i__] = 0.;
/* L50: */
}
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
work[i__] += (d__1 = a[i__ + j * a_dim1], abs(d__1));
/* L60: */
}
/* L70: */
}
value = 0.;
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Computing MAX */
d__1 = value, d__2 = work[i__];
value = max(d__1,d__2);
/* L80: */
}
} else if (lsame_(norm, "F") || lsame_(norm, "E")) {
/* Find normF(A). */
scale = 0.;
sum = 1.;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
dlassq_(m, &a[j * a_dim1 + 1], &c__1, &scale, &sum);
/* L90: */
}
value = scale * sqrt(sum);
}
ret_val = value;
return ret_val;
/* End of DLANGE */
} /* dlange_ */
doublereal dlanst_(char *norm, integer *n, doublereal *d__, doublereal *e)
{
/* System generated locals */
integer i__1;
doublereal ret_val, d__1, d__2, d__3, d__4, d__5;
/* Local variables */
static integer i__;
static doublereal sum, scale;
extern logical lsame_(char *, char *);
static doublereal anorm;
extern /* Subroutine */ int dlassq_(integer *, doublereal *, integer *,
doublereal *, doublereal *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLANST returns the value of the one norm, or the Frobenius norm, or
the infinity norm, or the element of largest absolute value of a
real symmetric tridiagonal matrix A.
Description
===========
DLANST returns the value
DLANST = ( max(abs(A(i,j))), NORM = 'M' or 'm'
(
( norm1(A), NORM = '1', 'O' or 'o'
(
( normI(A), NORM = 'I' or 'i'
(
( normF(A), NORM = 'F', 'f', 'E' or 'e'
where norm1 denotes the one norm of a matrix (maximum column sum),
normI denotes the infinity norm of a matrix (maximum row sum) and
normF denotes the Frobenius norm of a matrix (square root of sum of
squares). Note that max(abs(A(i,j))) is not a consistent matrix norm.
Arguments
=========
NORM (input) CHARACTER*1
Specifies the value to be returned in DLANST as described
above.
N (input) INTEGER
The order of the matrix A. N >= 0. When N = 0, DLANST is
set to zero.
D (input) DOUBLE PRECISION array, dimension (N)
The diagonal elements of A.
E (input) DOUBLE PRECISION array, dimension (N-1)
The (n-1) sub-diagonal or super-diagonal elements of A.
=====================================================================
*/
/* Parameter adjustments */
--e;
--d__;
/* Function Body */
if (*n <= 0) {
anorm = 0.;
} else if (lsame_(norm, "M")) {
/* Find max(abs(A(i,j))). */
anorm = (d__1 = d__[*n], abs(d__1));
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Computing MAX */
d__2 = anorm, d__3 = (d__1 = d__[i__], abs(d__1));
anorm = max(d__2,d__3);
/* Computing MAX */
d__2 = anorm, d__3 = (d__1 = e[i__], abs(d__1));
anorm = max(d__2,d__3);
/* L10: */
}
} else if (lsame_(norm, "O") || *(unsigned char *)
norm == '1' || lsame_(norm, "I")) {
/* Find norm1(A). */
if (*n == 1) {
anorm = abs(d__[1]);
} else {
/* Computing MAX */
d__3 = abs(d__[1]) + abs(e[1]), d__4 = (d__1 = e[*n - 1], abs(
d__1)) + (d__2 = d__[*n], abs(d__2));
anorm = max(d__3,d__4);
i__1 = *n - 1;
for (i__ = 2; i__ <= i__1; ++i__) {
/* Computing MAX */
d__4 = anorm, d__5 = (d__1 = d__[i__], abs(d__1)) + (d__2 = e[
i__], abs(d__2)) + (d__3 = e[i__ - 1], abs(d__3));
anorm = max(d__4,d__5);
/* L20: */
}
}
} else if (lsame_(norm, "F") || lsame_(norm, "E")) {
/* Find normF(A). */
scale = 0.;
sum = 1.;
if (*n > 1) {
i__1 = *n - 1;
dlassq_(&i__1, &e[1], &c__1, &scale, &sum);
sum *= 2;
}
dlassq_(n, &d__[1], &c__1, &scale, &sum);
anorm = scale * sqrt(sum);
}
ret_val = anorm;
return ret_val;
/* End of DLANST */
} /* dlanst_ */
doublereal dlansy_(char *norm, char *uplo, integer *n, doublereal *a, integer
*lda, doublereal *work)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2;
doublereal ret_val, d__1, d__2, d__3;
/* Local variables */
static integer i__, j;
static doublereal sum, absa, scale;
extern logical lsame_(char *, char *);
static doublereal value;
extern /* Subroutine */ int dlassq_(integer *, doublereal *, integer *,
doublereal *, doublereal *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLANSY returns the value of the one norm, or the Frobenius norm, or
the infinity norm, or the element of largest absolute value of a
real symmetric matrix A.
Description
===========
DLANSY returns the value
DLANSY = ( max(abs(A(i,j))), NORM = 'M' or 'm'
(
( norm1(A), NORM = '1', 'O' or 'o'
(
( normI(A), NORM = 'I' or 'i'
(
( normF(A), NORM = 'F', 'f', 'E' or 'e'
where norm1 denotes the one norm of a matrix (maximum column sum),
normI denotes the infinity norm of a matrix (maximum row sum) and
normF denotes the Frobenius norm of a matrix (square root of sum of
squares). Note that max(abs(A(i,j))) is not a consistent matrix norm.
Arguments
=========
NORM (input) CHARACTER*1
Specifies the value to be returned in DLANSY as described
above.
UPLO (input) CHARACTER*1
Specifies whether the upper or lower triangular part of the
symmetric matrix A is to be referenced.
= 'U': Upper triangular part of A is referenced
= 'L': Lower triangular part of A is referenced
N (input) INTEGER
The order of the matrix A. N >= 0. When N = 0, DLANSY is
set to zero.
A (input) DOUBLE PRECISION array, dimension (LDA,N)
The symmetric matrix A. If UPLO = 'U', the leading n by n
upper triangular part of A contains the upper triangular part
of the matrix A, and the strictly lower triangular part of A
is not referenced. If UPLO = 'L', the leading n by n lower
triangular part of A contains the lower triangular part of
the matrix A, and the strictly upper triangular part of A is
not referenced.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(N,1).
WORK (workspace) DOUBLE PRECISION array, dimension (MAX(1,LWORK)),
where LWORK >= N when NORM = 'I' or '1' or 'O'; otherwise,
WORK is not referenced.
=====================================================================
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--work;
/* Function Body */
if (*n == 0) {
value = 0.;
} else if (lsame_(norm, "M")) {
/* Find max(abs(A(i,j))). */
value = 0.;
if (lsame_(uplo, "U")) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = j;
for (i__ = 1; i__ <= i__2; ++i__) {
/* Computing MAX */
d__2 = value, d__3 = (d__1 = a[i__ + j * a_dim1], abs(
d__1));
value = max(d__2,d__3);
/* L10: */
}
/* L20: */
}
} else {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *n;
for (i__ = j; i__ <= i__2; ++i__) {
/* Computing MAX */
d__2 = value, d__3 = (d__1 = a[i__ + j * a_dim1], abs(
d__1));
value = max(d__2,d__3);
/* L30: */
}
/* L40: */
}
}
} else if (lsame_(norm, "I") || lsame_(norm, "O") || *(unsigned char *)norm == '1') {
/* Find normI(A) ( = norm1(A), since A is symmetric). */
value = 0.;
if (lsame_(uplo, "U")) {
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = 0.;
i__2 = j - 1;
for (i__ = 1; i__ <= i__2; ++i__) {
absa = (d__1 = a[i__ + j * a_dim1], abs(d__1));
sum += absa;
work[i__] += absa;
/* L50: */
}
work[j] = sum + (d__1 = a[j + j * a_dim1], abs(d__1));
/* L60: */
}
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Computing MAX */
d__1 = value, d__2 = work[i__];
value = max(d__1,d__2);
/* L70: */
}
} else {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
work[i__] = 0.;
/* L80: */
}
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = work[j] + (d__1 = a[j + j * a_dim1], abs(d__1));
i__2 = *n;
for (i__ = j + 1; i__ <= i__2; ++i__) {
absa = (d__1 = a[i__ + j * a_dim1], abs(d__1));
sum += absa;
work[i__] += absa;
/* L90: */
}
value = max(value,sum);
/* L100: */
}
}
} else if (lsame_(norm, "F") || lsame_(norm, "E")) {
/* Find normF(A). */
scale = 0.;
sum = 1.;
if (lsame_(uplo, "U")) {
i__1 = *n;
for (j = 2; j <= i__1; ++j) {
i__2 = j - 1;
dlassq_(&i__2, &a[j * a_dim1 + 1], &c__1, &scale, &sum);
/* L110: */
}
} else {
i__1 = *n - 1;
for (j = 1; j <= i__1; ++j) {
i__2 = *n - j;
dlassq_(&i__2, &a[j + 1 + j * a_dim1], &c__1, &scale, &sum);
/* L120: */
}
}
sum *= 2;
i__1 = *lda + 1;
dlassq_(n, &a[a_offset], &i__1, &scale, &sum);
value = scale * sqrt(sum);
}
ret_val = value;
return ret_val;
/* End of DLANSY */
} /* dlansy_ */
/* Subroutine */ int dlanv2_(doublereal *a, doublereal *b, doublereal *c__,
doublereal *d__, doublereal *rt1r, doublereal *rt1i, doublereal *rt2r,
doublereal *rt2i, doublereal *cs, doublereal *sn)
{
/* System generated locals */
doublereal d__1, d__2;
/* Local variables */
static doublereal p, z__, aa, bb, cc, dd, cs1, sn1, sab, sac, eps, tau,
temp, scale, bcmax, bcmis, sigma;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLANV2 computes the Schur factorization of a real 2-by-2 nonsymmetric
matrix in standard form:
[ A B ] = [ CS -SN ] [ AA BB ] [ CS SN ]
[ C D ] [ SN CS ] [ CC DD ] [-SN CS ]
where either
1) CC = 0 so that AA and DD are real eigenvalues of the matrix, or
2) AA = DD and BB*CC < 0, so that AA + or - sqrt(BB*CC) are complex
conjugate eigenvalues.
Arguments
=========
A (input/output) DOUBLE PRECISION
B (input/output) DOUBLE PRECISION
C (input/output) DOUBLE PRECISION
D (input/output) DOUBLE PRECISION
On entry, the elements of the input matrix.
On exit, they are overwritten by the elements of the
standardised Schur form.
RT1R (output) DOUBLE PRECISION
RT1I (output) DOUBLE PRECISION
RT2R (output) DOUBLE PRECISION
RT2I (output) DOUBLE PRECISION
The real and imaginary parts of the eigenvalues. If the
eigenvalues are a complex conjugate pair, RT1I > 0.
CS (output) DOUBLE PRECISION
SN (output) DOUBLE PRECISION
Parameters of the rotation matrix.
Further Details
===============
Modified by V. Sima, Research Institute for Informatics, Bucharest,
Romania, to reduce the risk of cancellation errors,
when computing real eigenvalues, and to ensure, if possible, that
abs(RT1R) >= abs(RT2R).
=====================================================================
*/
eps = PRECISION;
if (*c__ == 0.) {
*cs = 1.;
*sn = 0.;
goto L10;
} else if (*b == 0.) {
/* Swap rows and columns */
*cs = 0.;
*sn = 1.;
temp = *d__;
*d__ = *a;
*a = temp;
*b = -(*c__);
*c__ = 0.;
goto L10;
} else if (*a - *d__ == 0. && d_sign(&c_b15, b) != d_sign(&c_b15, c__)) {
*cs = 1.;
*sn = 0.;
goto L10;
} else {
temp = *a - *d__;
p = temp * .5;
/* Computing MAX */
d__1 = abs(*b), d__2 = abs(*c__);
bcmax = max(d__1,d__2);
/* Computing MIN */
d__1 = abs(*b), d__2 = abs(*c__);
bcmis = min(d__1,d__2) * d_sign(&c_b15, b) * d_sign(&c_b15, c__);
/* Computing MAX */
d__1 = abs(p);
scale = max(d__1,bcmax);
z__ = p / scale * p + bcmax / scale * bcmis;
/*
If Z is of the order of the machine accuracy, postpone the
decision on the nature of eigenvalues
*/
if (z__ >= eps * 4.) {
/* Real eigenvalues. Compute A and D. */
d__1 = sqrt(scale) * sqrt(z__);
z__ = p + d_sign(&d__1, &p);
*a = *d__ + z__;
*d__ -= bcmax / z__ * bcmis;
/* Compute B and the rotation matrix */
tau = dlapy2_(c__, &z__);
*cs = z__ / tau;
*sn = *c__ / tau;
*b -= *c__;
*c__ = 0.;
} else {
/*
Complex eigenvalues, or real (almost) equal eigenvalues.
Make diagonal elements equal.
*/
sigma = *b + *c__;
tau = dlapy2_(&sigma, &temp);
*cs = sqrt((abs(sigma) / tau + 1.) * .5);
*sn = -(p / (tau * *cs)) * d_sign(&c_b15, &sigma);
/*
Compute [ AA BB ] = [ A B ] [ CS -SN ]
[ CC DD ] [ C D ] [ SN CS ]
*/
aa = *a * *cs + *b * *sn;
bb = -(*a) * *sn + *b * *cs;
cc = *c__ * *cs + *d__ * *sn;
dd = -(*c__) * *sn + *d__ * *cs;
/*
Compute [ A B ] = [ CS SN ] [ AA BB ]
[ C D ] [-SN CS ] [ CC DD ]
*/
*a = aa * *cs + cc * *sn;
*b = bb * *cs + dd * *sn;
*c__ = -aa * *sn + cc * *cs;
*d__ = -bb * *sn + dd * *cs;
temp = (*a + *d__) * .5;
*a = temp;
*d__ = temp;
if (*c__ != 0.) {
if (*b != 0.) {
if (d_sign(&c_b15, b) == d_sign(&c_b15, c__)) {
/* Real eigenvalues: reduce to upper triangular form */
sab = sqrt((abs(*b)));
sac = sqrt((abs(*c__)));
d__1 = sab * sac;
p = d_sign(&d__1, c__);
tau = 1. / sqrt((d__1 = *b + *c__, abs(d__1)));
*a = temp + p;
*d__ = temp - p;
*b -= *c__;
*c__ = 0.;
cs1 = sab * tau;
sn1 = sac * tau;
temp = *cs * cs1 - *sn * sn1;
*sn = *cs * sn1 + *sn * cs1;
*cs = temp;
}
} else {
*b = -(*c__);
*c__ = 0.;
temp = *cs;
*cs = -(*sn);
*sn = temp;
}
}
}
}
L10:
/* Store eigenvalues in (RT1R,RT1I) and (RT2R,RT2I). */
*rt1r = *a;
*rt2r = *d__;
if (*c__ == 0.) {
*rt1i = 0.;
*rt2i = 0.;
} else {
*rt1i = sqrt((abs(*b))) * sqrt((abs(*c__)));
*rt2i = -(*rt1i);
}
return 0;
/* End of DLANV2 */
} /* dlanv2_ */
doublereal dlapy2_(doublereal *x, doublereal *y)
{
/* System generated locals */
doublereal ret_val, d__1;
/* Local variables */
static doublereal w, z__, xabs, yabs;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAPY2 returns sqrt(x**2+y**2), taking care not to cause unnecessary
overflow.
Arguments
=========
X (input) DOUBLE PRECISION
Y (input) DOUBLE PRECISION
X and Y specify the values x and y.
=====================================================================
*/
xabs = abs(*x);
yabs = abs(*y);
w = max(xabs,yabs);
z__ = min(xabs,yabs);
if (z__ == 0.) {
ret_val = w;
} else {
/* Computing 2nd power */
d__1 = z__ / w;
ret_val = w * sqrt(d__1 * d__1 + 1.);
}
return ret_val;
/* End of DLAPY2 */
} /* dlapy2_ */
doublereal dlapy3_(doublereal *x, doublereal *y, doublereal *z__)
{
/* System generated locals */
doublereal ret_val, d__1, d__2, d__3;
/* Local variables */
static doublereal w, xabs, yabs, zabs;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAPY3 returns sqrt(x**2+y**2+z**2), taking care not to cause
unnecessary overflow.
Arguments
=========
X (input) DOUBLE PRECISION
Y (input) DOUBLE PRECISION
Z (input) DOUBLE PRECISION
X, Y and Z specify the values x, y and z.
=====================================================================
*/
xabs = abs(*x);
yabs = abs(*y);
zabs = abs(*z__);
/* Computing MAX */
d__1 = max(xabs,yabs);
w = max(d__1,zabs);
if (w == 0.) {
/*
W can be zero for max(0,nan,0)
adding all three entries together will make sure
NaN will not disappear.
*/
ret_val = xabs + yabs + zabs;
} else {
/* Computing 2nd power */
d__1 = xabs / w;
/* Computing 2nd power */
d__2 = yabs / w;
/* Computing 2nd power */
d__3 = zabs / w;
ret_val = w * sqrt(d__1 * d__1 + d__2 * d__2 + d__3 * d__3);
}
return ret_val;
/* End of DLAPY3 */
} /* dlapy3_ */
/* Subroutine */ int dlaqr0_(logical *wantt, logical *wantz, integer *n,
integer *ilo, integer *ihi, doublereal *h__, integer *ldh, doublereal
*wr, doublereal *wi, integer *iloz, integer *ihiz, doublereal *z__,
integer *ldz, doublereal *work, integer *lwork, integer *info)
{
/* System generated locals */
integer h_dim1, h_offset, z_dim1, z_offset, i__1, i__2, i__3, i__4, i__5;
doublereal d__1, d__2, d__3, d__4;
/* Local variables */
static integer i__, k;
static doublereal aa, bb, cc, dd;
static integer ld;
static doublereal cs;
static integer nh, it, ks, kt;
static doublereal sn;
static integer ku, kv, ls, ns;
static doublereal ss;
static integer nw, inf, kdu, nho, nve, kwh, nsr, nwr, kwv, ndec, ndfl,
kbot, nmin;
static doublereal swap;
static integer ktop;
static doublereal zdum[1] /* was [1][1] */;
static integer kacc22, itmax, nsmax, nwmax, kwtop;
extern /* Subroutine */ int dlanv2_(doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *), dlaqr3_(
logical *, logical *, integer *, integer *, integer *, integer *,
doublereal *, integer *, integer *, integer *, doublereal *,
integer *, integer *, integer *, doublereal *, doublereal *,
doublereal *, integer *, integer *, doublereal *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *),
dlaqr4_(logical *, logical *, integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *,
integer *), dlaqr5_(logical *, logical *, integer *, integer *,
integer *, integer *, integer *, doublereal *, doublereal *,
doublereal *, integer *, integer *, integer *, doublereal *,
integer *, doublereal *, integer *, doublereal *, integer *,
integer *, doublereal *, integer *, integer *, doublereal *,
integer *);
static integer nibble;
extern /* Subroutine */ int dlahqr_(logical *, logical *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, integer *, doublereal *, integer *,
integer *), dlacpy_(char *, integer *, integer *, doublereal *,
integer *, doublereal *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static char jbcmpz[2];
static integer nwupbd;
static logical sorted;
static integer lwkopt;
/*
-- LAPACK auxiliary routine (version 3.2) --
Univ. of Tennessee, Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..
November 2006
Purpose
=======
DLAQR0 computes the eigenvalues of a Hessenberg matrix H
and, optionally, the matrices T and Z from the Schur decomposition
H = Z T Z**T, where T is an upper quasi-triangular matrix (the
Schur form), and Z is the orthogonal matrix of Schur vectors.
Optionally Z may be postmultiplied into an input orthogonal
matrix Q so that this routine can give the Schur factorization
of a matrix A which has been reduced to the Hessenberg form H
by the orthogonal matrix Q: A = Q*H*Q**T = (QZ)*T*(QZ)**T.
Arguments
=========
WANTT (input) LOGICAL
= .TRUE. : the full Schur form T is required;
= .FALSE.: only eigenvalues are required.
WANTZ (input) LOGICAL
= .TRUE. : the matrix of Schur vectors Z is required;
= .FALSE.: Schur vectors are not required.
N (input) INTEGER
The order of the matrix H. N .GE. 0.
ILO (input) INTEGER
IHI (input) INTEGER
It is assumed that H is already upper triangular in rows
and columns 1:ILO-1 and IHI+1:N and, if ILO.GT.1,
H(ILO,ILO-1) is zero. ILO and IHI are normally set by a
previous call to DGEBAL, and then passed to DGEHRD when the
matrix output by DGEBAL is reduced to Hessenberg form.
Otherwise, ILO and IHI should be set to 1 and N,
respectively. If N.GT.0, then 1.LE.ILO.LE.IHI.LE.N.
If N = 0, then ILO = 1 and IHI = 0.
H (input/output) DOUBLE PRECISION array, dimension (LDH,N)
On entry, the upper Hessenberg matrix H.
On exit, if INFO = 0 and WANTT is .TRUE., then H contains
the upper quasi-triangular matrix T from the Schur
decomposition (the Schur form); 2-by-2 diagonal blocks
(corresponding to complex conjugate pairs of eigenvalues)
are returned in standard form, with H(i,i) = H(i+1,i+1)
and H(i+1,i)*H(i,i+1).LT.0. If INFO = 0 and WANTT is
.FALSE., then the contents of H are unspecified on exit.
(The output value of H when INFO.GT.0 is given under the
description of INFO below.)
This subroutine may explicitly set H(i,j) = 0 for i.GT.j and
j = 1, 2, ... ILO-1 or j = IHI+1, IHI+2, ... N.
LDH (input) INTEGER
The leading dimension of the array H. LDH .GE. max(1,N).
WR (output) DOUBLE PRECISION array, dimension (IHI)
WI (output) DOUBLE PRECISION array, dimension (IHI)
The real and imaginary parts, respectively, of the computed
eigenvalues of H(ILO:IHI,ILO:IHI) are stored in WR(ILO:IHI)
and WI(ILO:IHI). If two eigenvalues are computed as a
complex conjugate pair, they are stored in consecutive
elements of WR and WI, say the i-th and (i+1)th, with
WI(i) .GT. 0 and WI(i+1) .LT. 0. If WANTT is .TRUE., then
the eigenvalues are stored in the same order as on the
diagonal of the Schur form returned in H, with
WR(i) = H(i,i) and, if H(i:i+1,i:i+1) is a 2-by-2 diagonal
block, WI(i) = sqrt(-H(i+1,i)*H(i,i+1)) and
WI(i+1) = -WI(i).
ILOZ (input) INTEGER
IHIZ (input) INTEGER
Specify the rows of Z to which transformations must be
applied if WANTZ is .TRUE..
1 .LE. ILOZ .LE. ILO; IHI .LE. IHIZ .LE. N.
Z (input/output) DOUBLE PRECISION array, dimension (LDZ,IHI)
If WANTZ is .FALSE., then Z is not referenced.
If WANTZ is .TRUE., then Z(ILO:IHI,ILOZ:IHIZ) is
replaced by Z(ILO:IHI,ILOZ:IHIZ)*U where U is the
orthogonal Schur factor of H(ILO:IHI,ILO:IHI).
(The output value of Z when INFO.GT.0 is given under
the description of INFO below.)
LDZ (input) INTEGER
The leading dimension of the array Z. if WANTZ is .TRUE.
then LDZ.GE.MAX(1,IHIZ). Otherwize, LDZ.GE.1.
WORK (workspace/output) DOUBLE PRECISION array, dimension LWORK
On exit, if LWORK = -1, WORK(1) returns an estimate of
the optimal value for LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK .GE. max(1,N)
is sufficient, but LWORK typically as large as 6*N may
be required for optimal performance. A workspace query
to determine the optimal workspace size is recommended.
If LWORK = -1, then DLAQR0 does a workspace query.
In this case, DLAQR0 checks the input parameters and
estimates the optimal workspace size for the given
values of N, ILO and IHI. The estimate is returned
in WORK(1). No error message related to LWORK is
issued by XERBLA. Neither H nor Z are accessed.
INFO (output) INTEGER
= 0: successful exit
.GT. 0: if INFO = i, DLAQR0 failed to compute all of
the eigenvalues. Elements 1:ilo-1 and i+1:n of WR
and WI contain those eigenvalues which have been
successfully computed. (Failures are rare.)
If INFO .GT. 0 and WANT is .FALSE., then on exit,
the remaining unconverged eigenvalues are the eigen-
values of the upper Hessenberg matrix rows and
columns ILO through INFO of the final, output
value of H.
If INFO .GT. 0 and WANTT is .TRUE., then on exit
(*) (initial value of H)*U = U*(final value of H)
where U is an orthogonal matrix. The final
value of H is upper Hessenberg and quasi-triangular
in rows and columns INFO+1 through IHI.
If INFO .GT. 0 and WANTZ is .TRUE., then on exit
(final value of Z(ILO:IHI,ILOZ:IHIZ)
= (initial value of Z(ILO:IHI,ILOZ:IHIZ)*U
where U is the orthogonal matrix in (*) (regard-
less of the value of WANTT.)
If INFO .GT. 0 and WANTZ is .FALSE., then Z is not
accessed.
================================================================
Based on contributions by
Karen Braman and Ralph Byers, Department of Mathematics,
University of Kansas, USA
================================================================
References:
K. Braman, R. Byers and R. Mathias, The Multi-Shift QR
Algorithm Part I: Maintaining Well Focused Shifts, and Level 3
Performance, SIAM Journal of Matrix Analysis, volume 23, pages
929--947, 2002.
K. Braman, R. Byers and R. Mathias, The Multi-Shift QR
Algorithm Part II: Aggressive Early Deflation, SIAM Journal
of Matrix Analysis, volume 23, pages 948--973, 2002.
================================================================
==== Matrices of order NTINY or smaller must be processed by
. DLAHQR because of insufficient subdiagonal scratch space.
. (This is a hard limit.) ====
==== Exceptional deflation windows: try to cure rare
. slow convergence by varying the size of the
. deflation window after KEXNW iterations. ====
==== Exceptional shifts: try to cure rare slow convergence
. with ad-hoc exceptional shifts every KEXSH iterations.
. ====
==== The constants WILK1 and WILK2 are used to form the
. exceptional shifts. ====
*/
/* Parameter adjustments */
h_dim1 = *ldh;
h_offset = 1 + h_dim1;
h__ -= h_offset;
--wr;
--wi;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--work;
/* Function Body */
*info = 0;
/* ==== Quick return for N = 0: nothing to do. ==== */
if (*n == 0) {
work[1] = 1.;
return 0;
}
if (*n <= 11) {
/* ==== Tiny matrices must use DLAHQR. ==== */
lwkopt = 1;
if (*lwork != -1) {
dlahqr_(wantt, wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1], &
wi[1], iloz, ihiz, &z__[z_offset], ldz, info);
}
} else {
/*
==== Use small bulge multi-shift QR with aggressive early
. deflation on larger-than-tiny matrices. ====
==== Hope for the best. ====
*/
*info = 0;
/* ==== Set up job flags for ILAENV. ==== */
if (*wantt) {
*(unsigned char *)jbcmpz = 'S';
} else {
*(unsigned char *)jbcmpz = 'E';
}
if (*wantz) {
*(unsigned char *)&jbcmpz[1] = 'V';
} else {
*(unsigned char *)&jbcmpz[1] = 'N';
}
/*
==== NWR = recommended deflation window size. At this
. point, N .GT. NTINY = 11, so there is enough
. subdiagonal workspace for NWR.GE.2 as required.
. (In fact, there is enough subdiagonal space for
. NWR.GE.3.) ====
*/
nwr = ilaenv_(&c__13, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, (ftnlen)6,
(ftnlen)2);
nwr = max(2,nwr);
/* Computing MIN */
i__1 = *ihi - *ilo + 1, i__2 = (*n - 1) / 3, i__1 = min(i__1,i__2);
nwr = min(i__1,nwr);
/*
==== NSR = recommended number of simultaneous shifts.
. At this point N .GT. NTINY = 11, so there is at
. enough subdiagonal workspace for NSR to be even
. and greater than or equal to two as required. ====
*/
nsr = ilaenv_(&c__15, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, (ftnlen)6,
(ftnlen)2);
/* Computing MIN */
i__1 = nsr, i__2 = (*n + 6) / 9, i__1 = min(i__1,i__2), i__2 = *ihi -
*ilo;
nsr = min(i__1,i__2);
/* Computing MAX */
i__1 = 2, i__2 = nsr - nsr % 2;
nsr = max(i__1,i__2);
/*
==== Estimate optimal workspace ====
==== Workspace query call to DLAQR3 ====
*/
i__1 = nwr + 1;
dlaqr3_(wantt, wantz, n, ilo, ihi, &i__1, &h__[h_offset], ldh, iloz,
ihiz, &z__[z_offset], ldz, &ls, &ld, &wr[1], &wi[1], &h__[
h_offset], ldh, n, &h__[h_offset], ldh, n, &h__[h_offset],
ldh, &work[1], &c_n1);
/*
==== Optimal workspace = MAX(DLAQR5, DLAQR3) ====
Computing MAX
*/
i__1 = nsr * 3 / 2, i__2 = (integer) work[1];
lwkopt = max(i__1,i__2);
/* ==== Quick return in case of workspace query. ==== */
if (*lwork == -1) {
work[1] = (doublereal) lwkopt;
return 0;
}
/* ==== DLAHQR/DLAQR0 crossover point ==== */
nmin = ilaenv_(&c__12, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, (ftnlen)
6, (ftnlen)2);
nmin = max(11,nmin);
/* ==== Nibble crossover point ==== */
nibble = ilaenv_(&c__14, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, (
ftnlen)6, (ftnlen)2);
nibble = max(0,nibble);
/*
==== Accumulate reflections during ttswp? Use block
. 2-by-2 structure during matrix-matrix multiply? ====
*/
kacc22 = ilaenv_(&c__16, "DLAQR0", jbcmpz, n, ilo, ihi, lwork, (
ftnlen)6, (ftnlen)2);
kacc22 = max(0,kacc22);
kacc22 = min(2,kacc22);
/*
==== NWMAX = the largest possible deflation window for
. which there is sufficient workspace. ====
Computing MIN
*/
i__1 = (*n - 1) / 3, i__2 = *lwork / 2;
nwmax = min(i__1,i__2);
nw = nwmax;
/*
==== NSMAX = the Largest number of simultaneous shifts
. for which there is sufficient workspace. ====
Computing MIN
*/
i__1 = (*n + 6) / 9, i__2 = (*lwork << 1) / 3;
nsmax = min(i__1,i__2);
nsmax -= nsmax % 2;
/* ==== NDFL: an iteration count restarted at deflation. ==== */
ndfl = 1;
/*
==== ITMAX = iteration limit ====
Computing MAX
*/
i__1 = 10, i__2 = *ihi - *ilo + 1;
itmax = max(i__1,i__2) * 30;
/* ==== Last row and column in the active block ==== */
kbot = *ihi;
/* ==== Main Loop ==== */
i__1 = itmax;
for (it = 1; it <= i__1; ++it) {
/* ==== Done when KBOT falls below ILO ==== */
if (kbot < *ilo) {
goto L90;
}
/* ==== Locate active block ==== */
i__2 = *ilo + 1;
for (k = kbot; k >= i__2; --k) {
if (h__[k + (k - 1) * h_dim1] == 0.) {
goto L20;
}
/* L10: */
}
k = *ilo;
L20:
ktop = k;
/*
==== Select deflation window size:
. Typical Case:
. If possible and advisable, nibble the entire
. active block. If not, use size MIN(NWR,NWMAX)
. or MIN(NWR+1,NWMAX) depending upon which has
. the smaller corresponding subdiagonal entry
. (a heuristic).
.
. Exceptional Case:
. If there have been no deflations in KEXNW or
. more iterations, then vary the deflation window
. size. At first, because, larger windows are,
. in general, more powerful than smaller ones,
. rapidly increase the window to the maximum possible.
. Then, gradually reduce the window size. ====
*/
nh = kbot - ktop + 1;
nwupbd = min(nh,nwmax);
if (ndfl < 5) {
nw = min(nwupbd,nwr);
} else {
/* Computing MIN */
i__2 = nwupbd, i__3 = nw << 1;
nw = min(i__2,i__3);
}
if (nw < nwmax) {
if (nw >= nh - 1) {
nw = nh;
} else {
kwtop = kbot - nw + 1;
if ((d__1 = h__[kwtop + (kwtop - 1) * h_dim1], abs(d__1))
> (d__2 = h__[kwtop - 1 + (kwtop - 2) * h_dim1],
abs(d__2))) {
++nw;
}
}
}
if (ndfl < 5) {
ndec = -1;
} else if (ndec >= 0 || nw >= nwupbd) {
++ndec;
if (nw - ndec < 2) {
ndec = 0;
}
nw -= ndec;
}
/*
==== Aggressive early deflation:
. split workspace under the subdiagonal into
. - an nw-by-nw work array V in the lower
. left-hand-corner,
. - an NW-by-at-least-NW-but-more-is-better
. (NW-by-NHO) horizontal work array along
. the bottom edge,
. - an at-least-NW-but-more-is-better (NHV-by-NW)
. vertical work array along the left-hand-edge.
. ====
*/
kv = *n - nw + 1;
kt = nw + 1;
nho = *n - nw - 1 - kt + 1;
kwv = nw + 2;
nve = *n - nw - kwv + 1;
/* ==== Aggressive early deflation ==== */
dlaqr3_(wantt, wantz, n, &ktop, &kbot, &nw, &h__[h_offset], ldh,
iloz, ihiz, &z__[z_offset], ldz, &ls, &ld, &wr[1], &wi[1],
&h__[kv + h_dim1], ldh, &nho, &h__[kv + kt * h_dim1],
ldh, &nve, &h__[kwv + h_dim1], ldh, &work[1], lwork);
/* ==== Adjust KBOT accounting for new deflations. ==== */
kbot -= ld;
/* ==== KS points to the shifts. ==== */
ks = kbot - ls + 1;
/*
==== Skip an expensive QR sweep if there is a (partly
. heuristic) reason to expect that many eigenvalues
. will deflate without it. Here, the QR sweep is
. skipped if many eigenvalues have just been deflated
. or if the remaining active block is small.
*/
if (ld == 0 || ld * 100 <= nw * nibble && kbot - ktop + 1 > min(
nmin,nwmax)) {
/*
==== NS = nominal number of simultaneous shifts.
. This may be lowered (slightly) if DLAQR3
. did not provide that many shifts. ====
Computing MIN
Computing MAX
*/
i__4 = 2, i__5 = kbot - ktop;
i__2 = min(nsmax,nsr), i__3 = max(i__4,i__5);
ns = min(i__2,i__3);
ns -= ns % 2;
/*
==== If there have been no deflations
. in a multiple of KEXSH iterations,
. then try exceptional shifts.
. Otherwise use shifts provided by
. DLAQR3 above or from the eigenvalues
. of a trailing principal submatrix. ====
*/
if (ndfl % 6 == 0) {
ks = kbot - ns + 1;
/* Computing MAX */
i__3 = ks + 1, i__4 = ktop + 2;
i__2 = max(i__3,i__4);
for (i__ = kbot; i__ >= i__2; i__ += -2) {
ss = (d__1 = h__[i__ + (i__ - 1) * h_dim1], abs(d__1))
+ (d__2 = h__[i__ - 1 + (i__ - 2) * h_dim1],
abs(d__2));
aa = ss * .75 + h__[i__ + i__ * h_dim1];
bb = ss;
cc = ss * -.4375;
dd = aa;
dlanv2_(&aa, &bb, &cc, &dd, &wr[i__ - 1], &wi[i__ - 1]
, &wr[i__], &wi[i__], &cs, &sn);
/* L30: */
}
if (ks == ktop) {
wr[ks + 1] = h__[ks + 1 + (ks + 1) * h_dim1];
wi[ks + 1] = 0.;
wr[ks] = wr[ks + 1];
wi[ks] = wi[ks + 1];
}
} else {
/*
==== Got NS/2 or fewer shifts? Use DLAQR4 or
. DLAHQR on a trailing principal submatrix to
. get more. (Since NS.LE.NSMAX.LE.(N+6)/9,
. there is enough space below the subdiagonal
. to fit an NS-by-NS scratch array.) ====
*/
if (kbot - ks + 1 <= ns / 2) {
ks = kbot - ns + 1;
kt = *n - ns + 1;
dlacpy_("A", &ns, &ns, &h__[ks + ks * h_dim1], ldh, &
h__[kt + h_dim1], ldh);
if (ns > nmin) {
dlaqr4_(&c_false, &c_false, &ns, &c__1, &ns, &h__[
kt + h_dim1], ldh, &wr[ks], &wi[ks], &
c__1, &c__1, zdum, &c__1, &work[1], lwork,
&inf);
} else {
dlahqr_(&c_false, &c_false, &ns, &c__1, &ns, &h__[
kt + h_dim1], ldh, &wr[ks], &wi[ks], &
c__1, &c__1, zdum, &c__1, &inf);
}
ks += inf;
/*
==== In case of a rare QR failure use
. eigenvalues of the trailing 2-by-2
. principal submatrix. ====
*/
if (ks >= kbot) {
aa = h__[kbot - 1 + (kbot - 1) * h_dim1];
cc = h__[kbot + (kbot - 1) * h_dim1];
bb = h__[kbot - 1 + kbot * h_dim1];
dd = h__[kbot + kbot * h_dim1];
dlanv2_(&aa, &bb, &cc, &dd, &wr[kbot - 1], &wi[
kbot - 1], &wr[kbot], &wi[kbot], &cs, &sn)
;
ks = kbot - 1;
}
}
if (kbot - ks + 1 > ns) {
/*
==== Sort the shifts (Helps a little)
. Bubble sort keeps complex conjugate
. pairs together. ====
*/
sorted = FALSE_;
i__2 = ks + 1;
for (k = kbot; k >= i__2; --k) {
if (sorted) {
goto L60;
}
sorted = TRUE_;
i__3 = k - 1;
for (i__ = ks; i__ <= i__3; ++i__) {
if ((d__1 = wr[i__], abs(d__1)) + (d__2 = wi[
i__], abs(d__2)) < (d__3 = wr[i__ + 1]
, abs(d__3)) + (d__4 = wi[i__ + 1],
abs(d__4))) {
sorted = FALSE_;
swap = wr[i__];
wr[i__] = wr[i__ + 1];
wr[i__ + 1] = swap;
swap = wi[i__];
wi[i__] = wi[i__ + 1];
wi[i__ + 1] = swap;
}
/* L40: */
}
/* L50: */
}
L60:
;
}
/*
==== Shuffle shifts into pairs of real shifts
. and pairs of complex conjugate shifts
. assuming complex conjugate shifts are
. already adjacent to one another. (Yes,
. they are.) ====
*/
i__2 = ks + 2;
for (i__ = kbot; i__ >= i__2; i__ += -2) {
if (wi[i__] != -wi[i__ - 1]) {
swap = wr[i__];
wr[i__] = wr[i__ - 1];
wr[i__ - 1] = wr[i__ - 2];
wr[i__ - 2] = swap;
swap = wi[i__];
wi[i__] = wi[i__ - 1];
wi[i__ - 1] = wi[i__ - 2];
wi[i__ - 2] = swap;
}
/* L70: */
}
}
/*
==== If there are only two shifts and both are
. real, then use only one. ====
*/
if (kbot - ks + 1 == 2) {
if (wi[kbot] == 0.) {
if ((d__1 = wr[kbot] - h__[kbot + kbot * h_dim1], abs(
d__1)) < (d__2 = wr[kbot - 1] - h__[kbot +
kbot * h_dim1], abs(d__2))) {
wr[kbot - 1] = wr[kbot];
} else {
wr[kbot] = wr[kbot - 1];
}
}
}
/*
==== Use up to NS of the the smallest magnatiude
. shifts. If there aren't NS shifts available,
. then use them all, possibly dropping one to
. make the number of shifts even. ====
Computing MIN
*/
i__2 = ns, i__3 = kbot - ks + 1;
ns = min(i__2,i__3);
ns -= ns % 2;
ks = kbot - ns + 1;
/*
==== Small-bulge multi-shift QR sweep:
. split workspace under the subdiagonal into
. - a KDU-by-KDU work array U in the lower
. left-hand-corner,
. - a KDU-by-at-least-KDU-but-more-is-better
. (KDU-by-NHo) horizontal work array WH along
. the bottom edge,
. - and an at-least-KDU-but-more-is-better-by-KDU
. (NVE-by-KDU) vertical work WV arrow along
. the left-hand-edge. ====
*/
kdu = ns * 3 - 3;
ku = *n - kdu + 1;
kwh = kdu + 1;
nho = *n - kdu - 3 - (kdu + 1) + 1;
kwv = kdu + 4;
nve = *n - kdu - kwv + 1;
/* ==== Small-bulge multi-shift QR sweep ==== */
dlaqr5_(wantt, wantz, &kacc22, n, &ktop, &kbot, &ns, &wr[ks],
&wi[ks], &h__[h_offset], ldh, iloz, ihiz, &z__[
z_offset], ldz, &work[1], &c__3, &h__[ku + h_dim1],
ldh, &nve, &h__[kwv + h_dim1], ldh, &nho, &h__[ku +
kwh * h_dim1], ldh);
}
/* ==== Note progress (or the lack of it). ==== */
if (ld > 0) {
ndfl = 1;
} else {
++ndfl;
}
/*
==== End of main loop ====
L80:
*/
}
/*
==== Iteration limit exceeded. Set INFO to show where
. the problem occurred and exit. ====
*/
*info = kbot;
L90:
;
}
/* ==== Return the optimal value of LWORK. ==== */
work[1] = (doublereal) lwkopt;
/* ==== End of DLAQR0 ==== */
return 0;
} /* dlaqr0_ */
/* Subroutine */ int dlaqr1_(integer *n, doublereal *h__, integer *ldh,
doublereal *sr1, doublereal *si1, doublereal *sr2, doublereal *si2,
doublereal *v)
{
/* System generated locals */
integer h_dim1, h_offset;
doublereal d__1, d__2, d__3;
/* Local variables */
static doublereal s, h21s, h31s;
/*
-- LAPACK auxiliary routine (version 3.2) --
Univ. of Tennessee, Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..
November 2006
Given a 2-by-2 or 3-by-3 matrix H, DLAQR1 sets v to a
scalar multiple of the first column of the product
(*) K = (H - (sr1 + i*si1)*I)*(H - (sr2 + i*si2)*I)
scaling to avoid overflows and most underflows. It
is assumed that either
1) sr1 = sr2 and si1 = -si2
or
2) si1 = si2 = 0.
This is useful for starting double implicit shift bulges
in the QR algorithm.
N (input) integer
Order of the matrix H. N must be either 2 or 3.
H (input) DOUBLE PRECISION array of dimension (LDH,N)
The 2-by-2 or 3-by-3 matrix H in (*).
LDH (input) integer
The leading dimension of H as declared in
the calling procedure. LDH.GE.N
SR1 (input) DOUBLE PRECISION
SI1 The shifts in (*).
SR2
SI2
V (output) DOUBLE PRECISION array of dimension N
A scalar multiple of the first column of the
matrix K in (*).
================================================================
Based on contributions by
Karen Braman and Ralph Byers, Department of Mathematics,
University of Kansas, USA
================================================================
*/
/* Parameter adjustments */
h_dim1 = *ldh;
h_offset = 1 + h_dim1;
h__ -= h_offset;
--v;
/* Function Body */
if (*n == 2) {
s = (d__1 = h__[h_dim1 + 1] - *sr2, abs(d__1)) + abs(*si2) + (d__2 =
h__[h_dim1 + 2], abs(d__2));
if (s == 0.) {
v[1] = 0.;
v[2] = 0.;
} else {
h21s = h__[h_dim1 + 2] / s;
v[1] = h21s * h__[(h_dim1 << 1) + 1] + (h__[h_dim1 + 1] - *sr1) *
((h__[h_dim1 + 1] - *sr2) / s) - *si1 * (*si2 / s);
v[2] = h21s * (h__[h_dim1 + 1] + h__[(h_dim1 << 1) + 2] - *sr1 - *
sr2);
}
} else {
s = (d__1 = h__[h_dim1 + 1] - *sr2, abs(d__1)) + abs(*si2) + (d__2 =
h__[h_dim1 + 2], abs(d__2)) + (d__3 = h__[h_dim1 + 3], abs(
d__3));
if (s == 0.) {
v[1] = 0.;
v[2] = 0.;
v[3] = 0.;
} else {
h21s = h__[h_dim1 + 2] / s;
h31s = h__[h_dim1 + 3] / s;
v[1] = (h__[h_dim1 + 1] - *sr1) * ((h__[h_dim1 + 1] - *sr2) / s)
- *si1 * (*si2 / s) + h__[(h_dim1 << 1) + 1] * h21s + h__[
h_dim1 * 3 + 1] * h31s;
v[2] = h21s * (h__[h_dim1 + 1] + h__[(h_dim1 << 1) + 2] - *sr1 - *
sr2) + h__[h_dim1 * 3 + 2] * h31s;
v[3] = h31s * (h__[h_dim1 + 1] + h__[h_dim1 * 3 + 3] - *sr1 - *
sr2) + h21s * h__[(h_dim1 << 1) + 3];
}
}
return 0;
} /* dlaqr1_ */
/* Subroutine */ int dlaqr2_(logical *wantt, logical *wantz, integer *n,
integer *ktop, integer *kbot, integer *nw, doublereal *h__, integer *
ldh, integer *iloz, integer *ihiz, doublereal *z__, integer *ldz,
integer *ns, integer *nd, doublereal *sr, doublereal *si, doublereal *
v, integer *ldv, integer *nh, doublereal *t, integer *ldt, integer *
nv, doublereal *wv, integer *ldwv, doublereal *work, integer *lwork)
{
/* System generated locals */
integer h_dim1, h_offset, t_dim1, t_offset, v_dim1, v_offset, wv_dim1,
wv_offset, z_dim1, z_offset, i__1, i__2, i__3, i__4;
doublereal d__1, d__2, d__3, d__4, d__5, d__6;
/* Local variables */
static integer i__, j, k;
static doublereal s, aa, bb, cc, dd, cs, sn;
static integer jw;
static doublereal evi, evk, foo;
static integer kln;
static doublereal tau, ulp;
static integer lwk1, lwk2;
static doublereal beta;
static integer kend, kcol, info, ifst, ilst, ltop, krow;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *), dgemm_(char *, char *, integer *, integer *
, integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static logical bulge;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static integer infqr, kwtop;
extern /* Subroutine */ int dlanv2_(doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *), dlabad_(
doublereal *, doublereal *);
extern /* Subroutine */ int dgehrd_(integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
integer *), dlarfg_(integer *, doublereal *, doublereal *,
integer *, doublereal *), dlahqr_(logical *, logical *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, integer *, doublereal *, integer *,
integer *), dlacpy_(char *, integer *, integer *, doublereal *,
integer *, doublereal *, integer *);
static doublereal safmin;
extern /* Subroutine */ int dlaset_(char *, integer *, integer *,
doublereal *, doublereal *, doublereal *, integer *);
static doublereal safmax;
extern /* Subroutine */ int dtrexc_(char *, integer *, doublereal *,
integer *, doublereal *, integer *, integer *, integer *,
doublereal *, integer *), dormhr_(char *, char *, integer
*, integer *, integer *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
integer *);
static logical sorted;
static doublereal smlnum;
static integer lwkopt;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
Univ. of Tennessee, Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..
-- June 2010 --
This subroutine is identical to DLAQR3 except that it avoids
recursion by calling DLAHQR instead of DLAQR4.
******************************************************************
Aggressive early deflation:
This subroutine accepts as input an upper Hessenberg matrix
H and performs an orthogonal similarity transformation
designed to detect and deflate fully converged eigenvalues from
a trailing principal submatrix. On output H has been over-
written by a new Hessenberg matrix that is a perturbation of
an orthogonal similarity transformation of H. It is to be
hoped that the final version of H has many zero subdiagonal
entries.
******************************************************************
WANTT (input) LOGICAL
If .TRUE., then the Hessenberg matrix H is fully updated
so that the quasi-triangular Schur factor may be
computed (in cooperation with the calling subroutine).
If .FALSE., then only enough of H is updated to preserve
the eigenvalues.
WANTZ (input) LOGICAL
If .TRUE., then the orthogonal matrix Z is updated so
so that the orthogonal Schur factor may be computed
(in cooperation with the calling subroutine).
If .FALSE., then Z is not referenced.
N (input) INTEGER
The order of the matrix H and (if WANTZ is .TRUE.) the
order of the orthogonal matrix Z.
KTOP (input) INTEGER
It is assumed that either KTOP = 1 or H(KTOP,KTOP-1)=0.
KBOT and KTOP together determine an isolated block
along the diagonal of the Hessenberg matrix.
KBOT (input) INTEGER
It is assumed without a check that either
KBOT = N or H(KBOT+1,KBOT)=0. KBOT and KTOP together
determine an isolated block along the diagonal of the
Hessenberg matrix.
NW (input) INTEGER
Deflation window size. 1 .LE. NW .LE. (KBOT-KTOP+1).
H (input/output) DOUBLE PRECISION array, dimension (LDH,N)
On input the initial N-by-N section of H stores the
Hessenberg matrix undergoing aggressive early deflation.
On output H has been transformed by an orthogonal
similarity transformation, perturbed, and the returned
to Hessenberg form that (it is to be hoped) has some
zero subdiagonal entries.
LDH (input) integer
Leading dimension of H just as declared in the calling
subroutine. N .LE. LDH
ILOZ (input) INTEGER
IHIZ (input) INTEGER
Specify the rows of Z to which transformations must be
applied if WANTZ is .TRUE.. 1 .LE. ILOZ .LE. IHIZ .LE. N.
Z (input/output) DOUBLE PRECISION array, dimension (LDZ,N)
IF WANTZ is .TRUE., then on output, the orthogonal
similarity transformation mentioned above has been
accumulated into Z(ILOZ:IHIZ,ILO:IHI) from the right.
If WANTZ is .FALSE., then Z is unreferenced.
LDZ (input) integer
The leading dimension of Z just as declared in the
calling subroutine. 1 .LE. LDZ.
NS (output) integer
The number of unconverged (ie approximate) eigenvalues
returned in SR and SI that may be used as shifts by the
calling subroutine.
ND (output) integer
The number of converged eigenvalues uncovered by this
subroutine.
SR (output) DOUBLE PRECISION array, dimension (KBOT)
SI (output) DOUBLE PRECISION array, dimension (KBOT)
On output, the real and imaginary parts of approximate
eigenvalues that may be used for shifts are stored in
SR(KBOT-ND-NS+1) through SR(KBOT-ND) and
SI(KBOT-ND-NS+1) through SI(KBOT-ND), respectively.
The real and imaginary parts of converged eigenvalues
are stored in SR(KBOT-ND+1) through SR(KBOT) and
SI(KBOT-ND+1) through SI(KBOT), respectively.
V (workspace) DOUBLE PRECISION array, dimension (LDV,NW)
An NW-by-NW work array.
LDV (input) integer scalar
The leading dimension of V just as declared in the
calling subroutine. NW .LE. LDV
NH (input) integer scalar
The number of columns of T. NH.GE.NW.
T (workspace) DOUBLE PRECISION array, dimension (LDT,NW)
LDT (input) integer
The leading dimension of T just as declared in the
calling subroutine. NW .LE. LDT
NV (input) integer
The number of rows of work array WV available for
workspace. NV.GE.NW.
WV (workspace) DOUBLE PRECISION array, dimension (LDWV,NW)
LDWV (input) integer
The leading dimension of W just as declared in the
calling subroutine. NW .LE. LDV
WORK (workspace) DOUBLE PRECISION array, dimension (LWORK)
On exit, WORK(1) is set to an estimate of the optimal value
of LWORK for the given values of N, NW, KTOP and KBOT.
LWORK (input) integer
The dimension of the work array WORK. LWORK = 2*NW
suffices, but greater efficiency may result from larger
values of LWORK.
If LWORK = -1, then a workspace query is assumed; DLAQR2
only estimates the optimal workspace size for the given
values of N, NW, KTOP and KBOT. The estimate is returned
in WORK(1). No error message related to LWORK is issued
by XERBLA. Neither H nor Z are accessed.
================================================================
Based on contributions by
Karen Braman and Ralph Byers, Department of Mathematics,
University of Kansas, USA
================================================================
==== Estimate optimal workspace. ====
*/
/* Parameter adjustments */
h_dim1 = *ldh;
h_offset = 1 + h_dim1;
h__ -= h_offset;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--sr;
--si;
v_dim1 = *ldv;
v_offset = 1 + v_dim1;
v -= v_offset;
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
wv_dim1 = *ldwv;
wv_offset = 1 + wv_dim1;
wv -= wv_offset;
--work;
/* Function Body */
/* Computing MIN */
i__1 = *nw, i__2 = *kbot - *ktop + 1;
jw = min(i__1,i__2);
if (jw <= 2) {
lwkopt = 1;
} else {
/* ==== Workspace query call to DGEHRD ==== */
i__1 = jw - 1;
dgehrd_(&jw, &c__1, &i__1, &t[t_offset], ldt, &work[1], &work[1], &
c_n1, &info);
lwk1 = (integer) work[1];
/* ==== Workspace query call to DORMHR ==== */
i__1 = jw - 1;
dormhr_("R", "N", &jw, &jw, &c__1, &i__1, &t[t_offset], ldt, &work[1],
&v[v_offset], ldv, &work[1], &c_n1, &info);
lwk2 = (integer) work[1];
/* ==== Optimal workspace ==== */
lwkopt = jw + max(lwk1,lwk2);
}
/* ==== Quick return in case of workspace query. ==== */
if (*lwork == -1) {
work[1] = (doublereal) lwkopt;
return 0;
}
/*
==== Nothing to do ...
... for an empty active block ... ====
*/
*ns = 0;
*nd = 0;
work[1] = 1.;
if (*ktop > *kbot) {
return 0;
}
/* ... nor for an empty deflation window. ==== */
if (*nw < 1) {
return 0;
}
/* ==== Machine constants ==== */
safmin = SAFEMINIMUM;
safmax = 1. / safmin;
dlabad_(&safmin, &safmax);
ulp = PRECISION;
smlnum = safmin * ((doublereal) (*n) / ulp);
/*
==== Setup deflation window ====
Computing MIN
*/
i__1 = *nw, i__2 = *kbot - *ktop + 1;
jw = min(i__1,i__2);
kwtop = *kbot - jw + 1;
if (kwtop == *ktop) {
s = 0.;
} else {
s = h__[kwtop + (kwtop - 1) * h_dim1];
}
if (*kbot == kwtop) {
/* ==== 1-by-1 deflation window: not much to do ==== */
sr[kwtop] = h__[kwtop + kwtop * h_dim1];
si[kwtop] = 0.;
*ns = 1;
*nd = 0;
/* Computing MAX */
d__2 = smlnum, d__3 = ulp * (d__1 = h__[kwtop + kwtop * h_dim1], abs(
d__1));
if (abs(s) <= max(d__2,d__3)) {
*ns = 0;
*nd = 1;
if (kwtop > *ktop) {
h__[kwtop + (kwtop - 1) * h_dim1] = 0.;
}
}
work[1] = 1.;
return 0;
}
/*
==== Convert to spike-triangular form. (In case of a
. rare QR failure, this routine continues to do
. aggressive early deflation using that part of
. the deflation window that converged using INFQR
. here and there to keep track.) ====
*/
dlacpy_("U", &jw, &jw, &h__[kwtop + kwtop * h_dim1], ldh, &t[t_offset],
ldt);
i__1 = jw - 1;
i__2 = *ldh + 1;
i__3 = *ldt + 1;
dcopy_(&i__1, &h__[kwtop + 1 + kwtop * h_dim1], &i__2, &t[t_dim1 + 2], &
i__3);
dlaset_("A", &jw, &jw, &c_b29, &c_b15, &v[v_offset], ldv);
dlahqr_(&c_true, &c_true, &jw, &c__1, &jw, &t[t_offset], ldt, &sr[kwtop],
&si[kwtop], &c__1, &jw, &v[v_offset], ldv, &infqr);
/* ==== DTREXC needs a clean margin near the diagonal ==== */
i__1 = jw - 3;
for (j = 1; j <= i__1; ++j) {
t[j + 2 + j * t_dim1] = 0.;
t[j + 3 + j * t_dim1] = 0.;
/* L10: */
}
if (jw > 2) {
t[jw + (jw - 2) * t_dim1] = 0.;
}
/* ==== Deflation detection loop ==== */
*ns = jw;
ilst = infqr + 1;
L20:
if (ilst <= *ns) {
if (*ns == 1) {
bulge = FALSE_;
} else {
bulge = t[*ns + (*ns - 1) * t_dim1] != 0.;
}
/* ==== Small spike tip test for deflation ==== */
if (! bulge) {
/* ==== Real eigenvalue ==== */
foo = (d__1 = t[*ns + *ns * t_dim1], abs(d__1));
if (foo == 0.) {
foo = abs(s);
}
/* Computing MAX */
d__2 = smlnum, d__3 = ulp * foo;
if ((d__1 = s * v[*ns * v_dim1 + 1], abs(d__1)) <= max(d__2,d__3))
{
/* ==== Deflatable ==== */
--(*ns);
} else {
/*
==== Undeflatable. Move it up out of the way.
. (DTREXC can not fail in this case.) ====
*/
ifst = *ns;
dtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst,
&ilst, &work[1], &info);
++ilst;
}
} else {
/* ==== Complex conjugate pair ==== */
foo = (d__3 = t[*ns + *ns * t_dim1], abs(d__3)) + sqrt((d__1 = t[*
ns + (*ns - 1) * t_dim1], abs(d__1))) * sqrt((d__2 = t[*
ns - 1 + *ns * t_dim1], abs(d__2)));
if (foo == 0.) {
foo = abs(s);
}
/* Computing MAX */
d__3 = (d__1 = s * v[*ns * v_dim1 + 1], abs(d__1)), d__4 = (d__2 =
s * v[(*ns - 1) * v_dim1 + 1], abs(d__2));
/* Computing MAX */
d__5 = smlnum, d__6 = ulp * foo;
if (max(d__3,d__4) <= max(d__5,d__6)) {
/* ==== Deflatable ==== */
*ns += -2;
} else {
/*
==== Undeflatable. Move them up out of the way.
. Fortunately, DTREXC does the right thing with
. ILST in case of a rare exchange failure. ====
*/
ifst = *ns;
dtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst,
&ilst, &work[1], &info);
ilst += 2;
}
}
/* ==== End deflation detection loop ==== */
goto L20;
}
/* ==== Return to Hessenberg form ==== */
if (*ns == 0) {
s = 0.;
}
if (*ns < jw) {
/*
==== sorting diagonal blocks of T improves accuracy for
. graded matrices. Bubble sort deals well with
. exchange failures. ====
*/
sorted = FALSE_;
i__ = *ns + 1;
L30:
if (sorted) {
goto L50;
}
sorted = TRUE_;
kend = i__ - 1;
i__ = infqr + 1;
if (i__ == *ns) {
k = i__ + 1;
} else if (t[i__ + 1 + i__ * t_dim1] == 0.) {
k = i__ + 1;
} else {
k = i__ + 2;
}
L40:
if (k <= kend) {
if (k == i__ + 1) {
evi = (d__1 = t[i__ + i__ * t_dim1], abs(d__1));
} else {
evi = (d__3 = t[i__ + i__ * t_dim1], abs(d__3)) + sqrt((d__1 =
t[i__ + 1 + i__ * t_dim1], abs(d__1))) * sqrt((d__2 =
t[i__ + (i__ + 1) * t_dim1], abs(d__2)));
}
if (k == kend) {
evk = (d__1 = t[k + k * t_dim1], abs(d__1));
} else if (t[k + 1 + k * t_dim1] == 0.) {
evk = (d__1 = t[k + k * t_dim1], abs(d__1));
} else {
evk = (d__3 = t[k + k * t_dim1], abs(d__3)) + sqrt((d__1 = t[
k + 1 + k * t_dim1], abs(d__1))) * sqrt((d__2 = t[k +
(k + 1) * t_dim1], abs(d__2)));
}
if (evi >= evk) {
i__ = k;
} else {
sorted = FALSE_;
ifst = i__;
ilst = k;
dtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst,
&ilst, &work[1], &info);
if (info == 0) {
i__ = ilst;
} else {
i__ = k;
}
}
if (i__ == kend) {
k = i__ + 1;
} else if (t[i__ + 1 + i__ * t_dim1] == 0.) {
k = i__ + 1;
} else {
k = i__ + 2;
}
goto L40;
}
goto L30;
L50:
;
}
/* ==== Restore shift/eigenvalue array from T ==== */
i__ = jw;
L60:
if (i__ >= infqr + 1) {
if (i__ == infqr + 1) {
sr[kwtop + i__ - 1] = t[i__ + i__ * t_dim1];
si[kwtop + i__ - 1] = 0.;
--i__;
} else if (t[i__ + (i__ - 1) * t_dim1] == 0.) {
sr[kwtop + i__ - 1] = t[i__ + i__ * t_dim1];
si[kwtop + i__ - 1] = 0.;
--i__;
} else {
aa = t[i__ - 1 + (i__ - 1) * t_dim1];
cc = t[i__ + (i__ - 1) * t_dim1];
bb = t[i__ - 1 + i__ * t_dim1];
dd = t[i__ + i__ * t_dim1];
dlanv2_(&aa, &bb, &cc, &dd, &sr[kwtop + i__ - 2], &si[kwtop + i__
- 2], &sr[kwtop + i__ - 1], &si[kwtop + i__ - 1], &cs, &
sn);
i__ += -2;
}
goto L60;
}
if (*ns < jw || s == 0.) {
if (*ns > 1 && s != 0.) {
/* ==== Reflect spike back into lower triangle ==== */
dcopy_(ns, &v[v_offset], ldv, &work[1], &c__1);
beta = work[1];
dlarfg_(ns, &beta, &work[2], &c__1, &tau);
work[1] = 1.;
i__1 = jw - 2;
i__2 = jw - 2;
dlaset_("L", &i__1, &i__2, &c_b29, &c_b29, &t[t_dim1 + 3], ldt);
dlarf_("L", ns, &jw, &work[1], &c__1, &tau, &t[t_offset], ldt, &
work[jw + 1]);
dlarf_("R", ns, ns, &work[1], &c__1, &tau, &t[t_offset], ldt, &
work[jw + 1]);
dlarf_("R", &jw, ns, &work[1], &c__1, &tau, &v[v_offset], ldv, &
work[jw + 1]);
i__1 = *lwork - jw;
dgehrd_(&jw, &c__1, ns, &t[t_offset], ldt, &work[1], &work[jw + 1]
, &i__1, &info);
}
/* ==== Copy updated reduced window into place ==== */
if (kwtop > 1) {
h__[kwtop + (kwtop - 1) * h_dim1] = s * v[v_dim1 + 1];
}
dlacpy_("U", &jw, &jw, &t[t_offset], ldt, &h__[kwtop + kwtop * h_dim1]
, ldh);
i__1 = jw - 1;
i__2 = *ldt + 1;
i__3 = *ldh + 1;
dcopy_(&i__1, &t[t_dim1 + 2], &i__2, &h__[kwtop + 1 + kwtop * h_dim1],
&i__3);
/*
==== Accumulate orthogonal matrix in order update
. H and Z, if requested. ====
*/
if (*ns > 1 && s != 0.) {
i__1 = *lwork - jw;
dormhr_("R", "N", &jw, ns, &c__1, ns, &t[t_offset], ldt, &work[1],
&v[v_offset], ldv, &work[jw + 1], &i__1, &info);
}
/* ==== Update vertical slab in H ==== */
if (*wantt) {
ltop = 1;
} else {
ltop = *ktop;
}
i__1 = kwtop - 1;
i__2 = *nv;
for (krow = ltop; i__2 < 0 ? krow >= i__1 : krow <= i__1; krow +=
i__2) {
/* Computing MIN */
i__3 = *nv, i__4 = kwtop - krow;
kln = min(i__3,i__4);
dgemm_("N", "N", &kln, &jw, &jw, &c_b15, &h__[krow + kwtop *
h_dim1], ldh, &v[v_offset], ldv, &c_b29, &wv[wv_offset],
ldwv);
dlacpy_("A", &kln, &jw, &wv[wv_offset], ldwv, &h__[krow + kwtop *
h_dim1], ldh);
/* L70: */
}
/* ==== Update horizontal slab in H ==== */
if (*wantt) {
i__2 = *n;
i__1 = *nh;
for (kcol = *kbot + 1; i__1 < 0 ? kcol >= i__2 : kcol <= i__2;
kcol += i__1) {
/* Computing MIN */
i__3 = *nh, i__4 = *n - kcol + 1;
kln = min(i__3,i__4);
dgemm_("C", "N", &jw, &kln, &jw, &c_b15, &v[v_offset], ldv, &
h__[kwtop + kcol * h_dim1], ldh, &c_b29, &t[t_offset],
ldt);
dlacpy_("A", &jw, &kln, &t[t_offset], ldt, &h__[kwtop + kcol *
h_dim1], ldh);
/* L80: */
}
}
/* ==== Update vertical slab in Z ==== */
if (*wantz) {
i__1 = *ihiz;
i__2 = *nv;
for (krow = *iloz; i__2 < 0 ? krow >= i__1 : krow <= i__1; krow +=
i__2) {
/* Computing MIN */
i__3 = *nv, i__4 = *ihiz - krow + 1;
kln = min(i__3,i__4);
dgemm_("N", "N", &kln, &jw, &jw, &c_b15, &z__[krow + kwtop *
z_dim1], ldz, &v[v_offset], ldv, &c_b29, &wv[
wv_offset], ldwv);
dlacpy_("A", &kln, &jw, &wv[wv_offset], ldwv, &z__[krow +
kwtop * z_dim1], ldz);
/* L90: */
}
}
}
/* ==== Return the number of deflations ... ==== */
*nd = jw - *ns;
/*
==== ... and the number of shifts. (Subtracting
. INFQR from the spike length takes care
. of the case of a rare QR failure while
. calculating eigenvalues of the deflation
. window.) ====
*/
*ns -= infqr;
/* ==== Return optimal workspace. ==== */
work[1] = (doublereal) lwkopt;
/* ==== End of DLAQR2 ==== */
return 0;
} /* dlaqr2_ */
/* Subroutine */ int dlaqr3_(logical *wantt, logical *wantz, integer *n,
integer *ktop, integer *kbot, integer *nw, doublereal *h__, integer *
ldh, integer *iloz, integer *ihiz, doublereal *z__, integer *ldz,
integer *ns, integer *nd, doublereal *sr, doublereal *si, doublereal *
v, integer *ldv, integer *nh, doublereal *t, integer *ldt, integer *
nv, doublereal *wv, integer *ldwv, doublereal *work, integer *lwork)
{
/* System generated locals */
integer h_dim1, h_offset, t_dim1, t_offset, v_dim1, v_offset, wv_dim1,
wv_offset, z_dim1, z_offset, i__1, i__2, i__3, i__4;
doublereal d__1, d__2, d__3, d__4, d__5, d__6;
/* Local variables */
static integer i__, j, k;
static doublereal s, aa, bb, cc, dd, cs, sn;
static integer jw;
static doublereal evi, evk, foo;
static integer kln;
static doublereal tau, ulp;
static integer lwk1, lwk2, lwk3;
static doublereal beta;
static integer kend, kcol, info, nmin, ifst, ilst, ltop, krow;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *), dgemm_(char *, char *, integer *, integer *
, integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static logical bulge;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static integer infqr, kwtop;
extern /* Subroutine */ int dlanv2_(doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *), dlaqr4_(
logical *, logical *, integer *, integer *, integer *, doublereal
*, integer *, doublereal *, doublereal *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *, integer *),
dlabad_(doublereal *, doublereal *);
extern /* Subroutine */ int dgehrd_(integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
integer *), dlarfg_(integer *, doublereal *, doublereal *,
integer *, doublereal *), dlahqr_(logical *, logical *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, integer *, doublereal *, integer *,
integer *), dlacpy_(char *, integer *, integer *, doublereal *,
integer *, doublereal *, integer *);
static doublereal safmin;
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static doublereal safmax;
extern /* Subroutine */ int dlaset_(char *, integer *, integer *,
doublereal *, doublereal *, doublereal *, integer *),
dtrexc_(char *, integer *, doublereal *, integer *, doublereal *,
integer *, integer *, integer *, doublereal *, integer *),
dormhr_(char *, char *, integer *, integer *, integer *, integer
*, doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *, integer *);
static logical sorted;
static doublereal smlnum;
static integer lwkopt;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
Univ. of Tennessee, Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..
-- June 2010 --
******************************************************************
Aggressive early deflation:
This subroutine accepts as input an upper Hessenberg matrix
H and performs an orthogonal similarity transformation
designed to detect and deflate fully converged eigenvalues from
a trailing principal submatrix. On output H has been over-
written by a new Hessenberg matrix that is a perturbation of
an orthogonal similarity transformation of H. It is to be
hoped that the final version of H has many zero subdiagonal
entries.
******************************************************************
WANTT (input) LOGICAL
If .TRUE., then the Hessenberg matrix H is fully updated
so that the quasi-triangular Schur factor may be
computed (in cooperation with the calling subroutine).
If .FALSE., then only enough of H is updated to preserve
the eigenvalues.
WANTZ (input) LOGICAL
If .TRUE., then the orthogonal matrix Z is updated so
so that the orthogonal Schur factor may be computed
(in cooperation with the calling subroutine).
If .FALSE., then Z is not referenced.
N (input) INTEGER
The order of the matrix H and (if WANTZ is .TRUE.) the
order of the orthogonal matrix Z.
KTOP (input) INTEGER
It is assumed that either KTOP = 1 or H(KTOP,KTOP-1)=0.
KBOT and KTOP together determine an isolated block
along the diagonal of the Hessenberg matrix.
KBOT (input) INTEGER
It is assumed without a check that either
KBOT = N or H(KBOT+1,KBOT)=0. KBOT and KTOP together
determine an isolated block along the diagonal of the
Hessenberg matrix.
NW (input) INTEGER
Deflation window size. 1 .LE. NW .LE. (KBOT-KTOP+1).
H (input/output) DOUBLE PRECISION array, dimension (LDH,N)
On input the initial N-by-N section of H stores the
Hessenberg matrix undergoing aggressive early deflation.
On output H has been transformed by an orthogonal
similarity transformation, perturbed, and the returned
to Hessenberg form that (it is to be hoped) has some
zero subdiagonal entries.
LDH (input) integer
Leading dimension of H just as declared in the calling
subroutine. N .LE. LDH
ILOZ (input) INTEGER
IHIZ (input) INTEGER
Specify the rows of Z to which transformations must be
applied if WANTZ is .TRUE.. 1 .LE. ILOZ .LE. IHIZ .LE. N.
Z (input/output) DOUBLE PRECISION array, dimension (LDZ,N)
IF WANTZ is .TRUE., then on output, the orthogonal
similarity transformation mentioned above has been
accumulated into Z(ILOZ:IHIZ,ILO:IHI) from the right.
If WANTZ is .FALSE., then Z is unreferenced.
LDZ (input) integer
The leading dimension of Z just as declared in the
calling subroutine. 1 .LE. LDZ.
NS (output) integer
The number of unconverged (ie approximate) eigenvalues
returned in SR and SI that may be used as shifts by the
calling subroutine.
ND (output) integer
The number of converged eigenvalues uncovered by this
subroutine.
SR (output) DOUBLE PRECISION array, dimension (KBOT)
SI (output) DOUBLE PRECISION array, dimension (KBOT)
On output, the real and imaginary parts of approximate
eigenvalues that may be used for shifts are stored in
SR(KBOT-ND-NS+1) through SR(KBOT-ND) and
SI(KBOT-ND-NS+1) through SI(KBOT-ND), respectively.
The real and imaginary parts of converged eigenvalues
are stored in SR(KBOT-ND+1) through SR(KBOT) and
SI(KBOT-ND+1) through SI(KBOT), respectively.
V (workspace) DOUBLE PRECISION array, dimension (LDV,NW)
An NW-by-NW work array.
LDV (input) integer scalar
The leading dimension of V just as declared in the
calling subroutine. NW .LE. LDV
NH (input) integer scalar
The number of columns of T. NH.GE.NW.
T (workspace) DOUBLE PRECISION array, dimension (LDT,NW)
LDT (input) integer
The leading dimension of T just as declared in the
calling subroutine. NW .LE. LDT
NV (input) integer
The number of rows of work array WV available for
workspace. NV.GE.NW.
WV (workspace) DOUBLE PRECISION array, dimension (LDWV,NW)
LDWV (input) integer
The leading dimension of W just as declared in the
calling subroutine. NW .LE. LDV
WORK (workspace) DOUBLE PRECISION array, dimension (LWORK)
On exit, WORK(1) is set to an estimate of the optimal value
of LWORK for the given values of N, NW, KTOP and KBOT.
LWORK (input) integer
The dimension of the work array WORK. LWORK = 2*NW
suffices, but greater efficiency may result from larger
values of LWORK.
If LWORK = -1, then a workspace query is assumed; DLAQR3
only estimates the optimal workspace size for the given
values of N, NW, KTOP and KBOT. The estimate is returned
in WORK(1). No error message related to LWORK is issued
by XERBLA. Neither H nor Z are accessed.
================================================================
Based on contributions by
Karen Braman and Ralph Byers, Department of Mathematics,
University of Kansas, USA
================================================================
==== Estimate optimal workspace. ====
*/
/* Parameter adjustments */
h_dim1 = *ldh;
h_offset = 1 + h_dim1;
h__ -= h_offset;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--sr;
--si;
v_dim1 = *ldv;
v_offset = 1 + v_dim1;
v -= v_offset;
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
wv_dim1 = *ldwv;
wv_offset = 1 + wv_dim1;
wv -= wv_offset;
--work;
/* Function Body */
/* Computing MIN */
i__1 = *nw, i__2 = *kbot - *ktop + 1;
jw = min(i__1,i__2);
if (jw <= 2) {
lwkopt = 1;
} else {
/* ==== Workspace query call to DGEHRD ==== */
i__1 = jw - 1;
dgehrd_(&jw, &c__1, &i__1, &t[t_offset], ldt, &work[1], &work[1], &
c_n1, &info);
lwk1 = (integer) work[1];
/* ==== Workspace query call to DORMHR ==== */
i__1 = jw - 1;
dormhr_("R", "N", &jw, &jw, &c__1, &i__1, &t[t_offset], ldt, &work[1],
&v[v_offset], ldv, &work[1], &c_n1, &info);
lwk2 = (integer) work[1];
/* ==== Workspace query call to DLAQR4 ==== */
dlaqr4_(&c_true, &c_true, &jw, &c__1, &jw, &t[t_offset], ldt, &sr[1],
&si[1], &c__1, &jw, &v[v_offset], ldv, &work[1], &c_n1, &
infqr);
lwk3 = (integer) work[1];
/*
==== Optimal workspace ====
Computing MAX
*/
i__1 = jw + max(lwk1,lwk2);
lwkopt = max(i__1,lwk3);
}
/* ==== Quick return in case of workspace query. ==== */
if (*lwork == -1) {
work[1] = (doublereal) lwkopt;
return 0;
}
/*
==== Nothing to do ...
... for an empty active block ... ====
*/
*ns = 0;
*nd = 0;
work[1] = 1.;
if (*ktop > *kbot) {
return 0;
}
/* ... nor for an empty deflation window. ==== */
if (*nw < 1) {
return 0;
}
/* ==== Machine constants ==== */
safmin = SAFEMINIMUM;
safmax = 1. / safmin;
dlabad_(&safmin, &safmax);
ulp = PRECISION;
smlnum = safmin * ((doublereal) (*n) / ulp);
/*
==== Setup deflation window ====
Computing MIN
*/
i__1 = *nw, i__2 = *kbot - *ktop + 1;
jw = min(i__1,i__2);
kwtop = *kbot - jw + 1;
if (kwtop == *ktop) {
s = 0.;
} else {
s = h__[kwtop + (kwtop - 1) * h_dim1];
}
if (*kbot == kwtop) {
/* ==== 1-by-1 deflation window: not much to do ==== */
sr[kwtop] = h__[kwtop + kwtop * h_dim1];
si[kwtop] = 0.;
*ns = 1;
*nd = 0;
/* Computing MAX */
d__2 = smlnum, d__3 = ulp * (d__1 = h__[kwtop + kwtop * h_dim1], abs(
d__1));
if (abs(s) <= max(d__2,d__3)) {
*ns = 0;
*nd = 1;
if (kwtop > *ktop) {
h__[kwtop + (kwtop - 1) * h_dim1] = 0.;
}
}
work[1] = 1.;
return 0;
}
/*
==== Convert to spike-triangular form. (In case of a
. rare QR failure, this routine continues to do
. aggressive early deflation using that part of
. the deflation window that converged using INFQR
. here and there to keep track.) ====
*/
dlacpy_("U", &jw, &jw, &h__[kwtop + kwtop * h_dim1], ldh, &t[t_offset],
ldt);
i__1 = jw - 1;
i__2 = *ldh + 1;
i__3 = *ldt + 1;
dcopy_(&i__1, &h__[kwtop + 1 + kwtop * h_dim1], &i__2, &t[t_dim1 + 2], &
i__3);
dlaset_("A", &jw, &jw, &c_b29, &c_b15, &v[v_offset], ldv);
nmin = ilaenv_(&c__12, "DLAQR3", "SV", &jw, &c__1, &jw, lwork, (ftnlen)6,
(ftnlen)2);
if (jw > nmin) {
dlaqr4_(&c_true, &c_true, &jw, &c__1, &jw, &t[t_offset], ldt, &sr[
kwtop], &si[kwtop], &c__1, &jw, &v[v_offset], ldv, &work[1],
lwork, &infqr);
} else {
dlahqr_(&c_true, &c_true, &jw, &c__1, &jw, &t[t_offset], ldt, &sr[
kwtop], &si[kwtop], &c__1, &jw, &v[v_offset], ldv, &infqr);
}
/* ==== DTREXC needs a clean margin near the diagonal ==== */
i__1 = jw - 3;
for (j = 1; j <= i__1; ++j) {
t[j + 2 + j * t_dim1] = 0.;
t[j + 3 + j * t_dim1] = 0.;
/* L10: */
}
if (jw > 2) {
t[jw + (jw - 2) * t_dim1] = 0.;
}
/* ==== Deflation detection loop ==== */
*ns = jw;
ilst = infqr + 1;
L20:
if (ilst <= *ns) {
if (*ns == 1) {
bulge = FALSE_;
} else {
bulge = t[*ns + (*ns - 1) * t_dim1] != 0.;
}
/* ==== Small spike tip test for deflation ==== */
if (! bulge) {
/* ==== Real eigenvalue ==== */
foo = (d__1 = t[*ns + *ns * t_dim1], abs(d__1));
if (foo == 0.) {
foo = abs(s);
}
/* Computing MAX */
d__2 = smlnum, d__3 = ulp * foo;
if ((d__1 = s * v[*ns * v_dim1 + 1], abs(d__1)) <= max(d__2,d__3))
{
/* ==== Deflatable ==== */
--(*ns);
} else {
/*
==== Undeflatable. Move it up out of the way.
. (DTREXC can not fail in this case.) ====
*/
ifst = *ns;
dtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst,
&ilst, &work[1], &info);
++ilst;
}
} else {
/* ==== Complex conjugate pair ==== */
foo = (d__3 = t[*ns + *ns * t_dim1], abs(d__3)) + sqrt((d__1 = t[*
ns + (*ns - 1) * t_dim1], abs(d__1))) * sqrt((d__2 = t[*
ns - 1 + *ns * t_dim1], abs(d__2)));
if (foo == 0.) {
foo = abs(s);
}
/* Computing MAX */
d__3 = (d__1 = s * v[*ns * v_dim1 + 1], abs(d__1)), d__4 = (d__2 =
s * v[(*ns - 1) * v_dim1 + 1], abs(d__2));
/* Computing MAX */
d__5 = smlnum, d__6 = ulp * foo;
if (max(d__3,d__4) <= max(d__5,d__6)) {
/* ==== Deflatable ==== */
*ns += -2;
} else {
/*
==== Undeflatable. Move them up out of the way.
. Fortunately, DTREXC does the right thing with
. ILST in case of a rare exchange failure. ====
*/
ifst = *ns;
dtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst,
&ilst, &work[1], &info);
ilst += 2;
}
}
/* ==== End deflation detection loop ==== */
goto L20;
}
/* ==== Return to Hessenberg form ==== */
if (*ns == 0) {
s = 0.;
}
if (*ns < jw) {
/*
==== sorting diagonal blocks of T improves accuracy for
. graded matrices. Bubble sort deals well with
. exchange failures. ====
*/
sorted = FALSE_;
i__ = *ns + 1;
L30:
if (sorted) {
goto L50;
}
sorted = TRUE_;
kend = i__ - 1;
i__ = infqr + 1;
if (i__ == *ns) {
k = i__ + 1;
} else if (t[i__ + 1 + i__ * t_dim1] == 0.) {
k = i__ + 1;
} else {
k = i__ + 2;
}
L40:
if (k <= kend) {
if (k == i__ + 1) {
evi = (d__1 = t[i__ + i__ * t_dim1], abs(d__1));
} else {
evi = (d__3 = t[i__ + i__ * t_dim1], abs(d__3)) + sqrt((d__1 =
t[i__ + 1 + i__ * t_dim1], abs(d__1))) * sqrt((d__2 =
t[i__ + (i__ + 1) * t_dim1], abs(d__2)));
}
if (k == kend) {
evk = (d__1 = t[k + k * t_dim1], abs(d__1));
} else if (t[k + 1 + k * t_dim1] == 0.) {
evk = (d__1 = t[k + k * t_dim1], abs(d__1));
} else {
evk = (d__3 = t[k + k * t_dim1], abs(d__3)) + sqrt((d__1 = t[
k + 1 + k * t_dim1], abs(d__1))) * sqrt((d__2 = t[k +
(k + 1) * t_dim1], abs(d__2)));
}
if (evi >= evk) {
i__ = k;
} else {
sorted = FALSE_;
ifst = i__;
ilst = k;
dtrexc_("V", &jw, &t[t_offset], ldt, &v[v_offset], ldv, &ifst,
&ilst, &work[1], &info);
if (info == 0) {
i__ = ilst;
} else {
i__ = k;
}
}
if (i__ == kend) {
k = i__ + 1;
} else if (t[i__ + 1 + i__ * t_dim1] == 0.) {
k = i__ + 1;
} else {
k = i__ + 2;
}
goto L40;
}
goto L30;
L50:
;
}
/* ==== Restore shift/eigenvalue array from T ==== */
i__ = jw;
L60:
if (i__ >= infqr + 1) {
if (i__ == infqr + 1) {
sr[kwtop + i__ - 1] = t[i__ + i__ * t_dim1];
si[kwtop + i__ - 1] = 0.;
--i__;
} else if (t[i__ + (i__ - 1) * t_dim1] == 0.) {
sr[kwtop + i__ - 1] = t[i__ + i__ * t_dim1];
si[kwtop + i__ - 1] = 0.;
--i__;
} else {
aa = t[i__ - 1 + (i__ - 1) * t_dim1];
cc = t[i__ + (i__ - 1) * t_dim1];
bb = t[i__ - 1 + i__ * t_dim1];
dd = t[i__ + i__ * t_dim1];
dlanv2_(&aa, &bb, &cc, &dd, &sr[kwtop + i__ - 2], &si[kwtop + i__
- 2], &sr[kwtop + i__ - 1], &si[kwtop + i__ - 1], &cs, &
sn);
i__ += -2;
}
goto L60;
}
if (*ns < jw || s == 0.) {
if (*ns > 1 && s != 0.) {
/* ==== Reflect spike back into lower triangle ==== */
dcopy_(ns, &v[v_offset], ldv, &work[1], &c__1);
beta = work[1];
dlarfg_(ns, &beta, &work[2], &c__1, &tau);
work[1] = 1.;
i__1 = jw - 2;
i__2 = jw - 2;
dlaset_("L", &i__1, &i__2, &c_b29, &c_b29, &t[t_dim1 + 3], ldt);
dlarf_("L", ns, &jw, &work[1], &c__1, &tau, &t[t_offset], ldt, &
work[jw + 1]);
dlarf_("R", ns, ns, &work[1], &c__1, &tau, &t[t_offset], ldt, &
work[jw + 1]);
dlarf_("R", &jw, ns, &work[1], &c__1, &tau, &v[v_offset], ldv, &
work[jw + 1]);
i__1 = *lwork - jw;
dgehrd_(&jw, &c__1, ns, &t[t_offset], ldt, &work[1], &work[jw + 1]
, &i__1, &info);
}
/* ==== Copy updated reduced window into place ==== */
if (kwtop > 1) {
h__[kwtop + (kwtop - 1) * h_dim1] = s * v[v_dim1 + 1];
}
dlacpy_("U", &jw, &jw, &t[t_offset], ldt, &h__[kwtop + kwtop * h_dim1]
, ldh);
i__1 = jw - 1;
i__2 = *ldt + 1;
i__3 = *ldh + 1;
dcopy_(&i__1, &t[t_dim1 + 2], &i__2, &h__[kwtop + 1 + kwtop * h_dim1],
&i__3);
/*
==== Accumulate orthogonal matrix in order update
. H and Z, if requested. ====
*/
if (*ns > 1 && s != 0.) {
i__1 = *lwork - jw;
dormhr_("R", "N", &jw, ns, &c__1, ns, &t[t_offset], ldt, &work[1],
&v[v_offset], ldv, &work[jw + 1], &i__1, &info);
}
/* ==== Update vertical slab in H ==== */
if (*wantt) {
ltop = 1;
} else {
ltop = *ktop;
}
i__1 = kwtop - 1;
i__2 = *nv;
for (krow = ltop; i__2 < 0 ? krow >= i__1 : krow <= i__1; krow +=
i__2) {
/* Computing MIN */
i__3 = *nv, i__4 = kwtop - krow;
kln = min(i__3,i__4);
dgemm_("N", "N", &kln, &jw, &jw, &c_b15, &h__[krow + kwtop *
h_dim1], ldh, &v[v_offset], ldv, &c_b29, &wv[wv_offset],
ldwv);
dlacpy_("A", &kln, &jw, &wv[wv_offset], ldwv, &h__[krow + kwtop *
h_dim1], ldh);
/* L70: */
}
/* ==== Update horizontal slab in H ==== */
if (*wantt) {
i__2 = *n;
i__1 = *nh;
for (kcol = *kbot + 1; i__1 < 0 ? kcol >= i__2 : kcol <= i__2;
kcol += i__1) {
/* Computing MIN */
i__3 = *nh, i__4 = *n - kcol + 1;
kln = min(i__3,i__4);
dgemm_("C", "N", &jw, &kln, &jw, &c_b15, &v[v_offset], ldv, &
h__[kwtop + kcol * h_dim1], ldh, &c_b29, &t[t_offset],
ldt);
dlacpy_("A", &jw, &kln, &t[t_offset], ldt, &h__[kwtop + kcol *
h_dim1], ldh);
/* L80: */
}
}
/* ==== Update vertical slab in Z ==== */
if (*wantz) {
i__1 = *ihiz;
i__2 = *nv;
for (krow = *iloz; i__2 < 0 ? krow >= i__1 : krow <= i__1; krow +=
i__2) {
/* Computing MIN */
i__3 = *nv, i__4 = *ihiz - krow + 1;
kln = min(i__3,i__4);
dgemm_("N", "N", &kln, &jw, &jw, &c_b15, &z__[krow + kwtop *
z_dim1], ldz, &v[v_offset], ldv, &c_b29, &wv[
wv_offset], ldwv);
dlacpy_("A", &kln, &jw, &wv[wv_offset], ldwv, &z__[krow +
kwtop * z_dim1], ldz);
/* L90: */
}
}
}
/* ==== Return the number of deflations ... ==== */
*nd = jw - *ns;
/*
==== ... and the number of shifts. (Subtracting
. INFQR from the spike length takes care
. of the case of a rare QR failure while
. calculating eigenvalues of the deflation
. window.) ====
*/
*ns -= infqr;
/* ==== Return optimal workspace. ==== */
work[1] = (doublereal) lwkopt;
/* ==== End of DLAQR3 ==== */
return 0;
} /* dlaqr3_ */
/* Subroutine */ int dlaqr4_(logical *wantt, logical *wantz, integer *n,
integer *ilo, integer *ihi, doublereal *h__, integer *ldh, doublereal
*wr, doublereal *wi, integer *iloz, integer *ihiz, doublereal *z__,
integer *ldz, doublereal *work, integer *lwork, integer *info)
{
/* System generated locals */
integer h_dim1, h_offset, z_dim1, z_offset, i__1, i__2, i__3, i__4, i__5;
doublereal d__1, d__2, d__3, d__4;
/* Local variables */
static integer i__, k;
static doublereal aa, bb, cc, dd;
static integer ld;
static doublereal cs;
static integer nh, it, ks, kt;
static doublereal sn;
static integer ku, kv, ls, ns;
static doublereal ss;
static integer nw, inf, kdu, nho, nve, kwh, nsr, nwr, kwv, ndec, ndfl,
kbot, nmin;
static doublereal swap;
static integer ktop;
static doublereal zdum[1] /* was [1][1] */;
static integer kacc22, itmax, nsmax, nwmax, kwtop;
extern /* Subroutine */ int dlaqr2_(logical *, logical *, integer *,
integer *, integer *, integer *, doublereal *, integer *, integer
*, integer *, doublereal *, integer *, integer *, integer *,
doublereal *, doublereal *, doublereal *, integer *, integer *,
doublereal *, integer *, integer *, doublereal *, integer *,
doublereal *, integer *), dlanv2_(doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *), dlaqr5_(
logical *, logical *, integer *, integer *, integer *, integer *,
integer *, doublereal *, doublereal *, doublereal *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
integer *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *, doublereal *, integer *);
static integer nibble;
extern /* Subroutine */ int dlahqr_(logical *, logical *, integer *,
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, integer *, doublereal *, integer *,
integer *), dlacpy_(char *, integer *, integer *, doublereal *,
integer *, doublereal *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static char jbcmpz[2];
static integer nwupbd;
static logical sorted;
static integer lwkopt;
/*
-- LAPACK auxiliary routine (version 3.2) --
Univ. of Tennessee, Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..
November 2006
This subroutine implements one level of recursion for DLAQR0.
It is a complete implementation of the small bulge multi-shift
QR algorithm. It may be called by DLAQR0 and, for large enough
deflation window size, it may be called by DLAQR3. This
subroutine is identical to DLAQR0 except that it calls DLAQR2
instead of DLAQR3.
Purpose
=======
DLAQR4 computes the eigenvalues of a Hessenberg matrix H
and, optionally, the matrices T and Z from the Schur decomposition
H = Z T Z**T, where T is an upper quasi-triangular matrix (the
Schur form), and Z is the orthogonal matrix of Schur vectors.
Optionally Z may be postmultiplied into an input orthogonal
matrix Q so that this routine can give the Schur factorization
of a matrix A which has been reduced to the Hessenberg form H
by the orthogonal matrix Q: A = Q*H*Q**T = (QZ)*T*(QZ)**T.
Arguments
=========
WANTT (input) LOGICAL
= .TRUE. : the full Schur form T is required;
= .FALSE.: only eigenvalues are required.
WANTZ (input) LOGICAL
= .TRUE. : the matrix of Schur vectors Z is required;
= .FALSE.: Schur vectors are not required.
N (input) INTEGER
The order of the matrix H. N .GE. 0.
ILO (input) INTEGER
IHI (input) INTEGER
It is assumed that H is already upper triangular in rows
and columns 1:ILO-1 and IHI+1:N and, if ILO.GT.1,
H(ILO,ILO-1) is zero. ILO and IHI are normally set by a
previous call to DGEBAL, and then passed to DGEHRD when the
matrix output by DGEBAL is reduced to Hessenberg form.
Otherwise, ILO and IHI should be set to 1 and N,
respectively. If N.GT.0, then 1.LE.ILO.LE.IHI.LE.N.
If N = 0, then ILO = 1 and IHI = 0.
H (input/output) DOUBLE PRECISION array, dimension (LDH,N)
On entry, the upper Hessenberg matrix H.
On exit, if INFO = 0 and WANTT is .TRUE., then H contains
the upper quasi-triangular matrix T from the Schur
decomposition (the Schur form); 2-by-2 diagonal blocks
(corresponding to complex conjugate pairs of eigenvalues)
are returned in standard form, with H(i,i) = H(i+1,i+1)
and H(i+1,i)*H(i,i+1).LT.0. If INFO = 0 and WANTT is
.FALSE., then the contents of H are unspecified on exit.
(The output value of H when INFO.GT.0 is given under the
description of INFO below.)
This subroutine may explicitly set H(i,j) = 0 for i.GT.j and
j = 1, 2, ... ILO-1 or j = IHI+1, IHI+2, ... N.
LDH (input) INTEGER
The leading dimension of the array H. LDH .GE. max(1,N).
WR (output) DOUBLE PRECISION array, dimension (IHI)
WI (output) DOUBLE PRECISION array, dimension (IHI)
The real and imaginary parts, respectively, of the computed
eigenvalues of H(ILO:IHI,ILO:IHI) are stored in WR(ILO:IHI)
and WI(ILO:IHI). If two eigenvalues are computed as a
complex conjugate pair, they are stored in consecutive
elements of WR and WI, say the i-th and (i+1)th, with
WI(i) .GT. 0 and WI(i+1) .LT. 0. If WANTT is .TRUE., then
the eigenvalues are stored in the same order as on the
diagonal of the Schur form returned in H, with
WR(i) = H(i,i) and, if H(i:i+1,i:i+1) is a 2-by-2 diagonal
block, WI(i) = sqrt(-H(i+1,i)*H(i,i+1)) and
WI(i+1) = -WI(i).
ILOZ (input) INTEGER
IHIZ (input) INTEGER
Specify the rows of Z to which transformations must be
applied if WANTZ is .TRUE..
1 .LE. ILOZ .LE. ILO; IHI .LE. IHIZ .LE. N.
Z (input/output) DOUBLE PRECISION array, dimension (LDZ,IHI)
If WANTZ is .FALSE., then Z is not referenced.
If WANTZ is .TRUE., then Z(ILO:IHI,ILOZ:IHIZ) is
replaced by Z(ILO:IHI,ILOZ:IHIZ)*U where U is the
orthogonal Schur factor of H(ILO:IHI,ILO:IHI).
(The output value of Z when INFO.GT.0 is given under
the description of INFO below.)
LDZ (input) INTEGER
The leading dimension of the array Z. if WANTZ is .TRUE.
then LDZ.GE.MAX(1,IHIZ). Otherwize, LDZ.GE.1.
WORK (workspace/output) DOUBLE PRECISION array, dimension LWORK
On exit, if LWORK = -1, WORK(1) returns an estimate of
the optimal value for LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK .GE. max(1,N)
is sufficient, but LWORK typically as large as 6*N may
be required for optimal performance. A workspace query
to determine the optimal workspace size is recommended.
If LWORK = -1, then DLAQR4 does a workspace query.
In this case, DLAQR4 checks the input parameters and
estimates the optimal workspace size for the given
values of N, ILO and IHI. The estimate is returned
in WORK(1). No error message related to LWORK is
issued by XERBLA. Neither H nor Z are accessed.
INFO (output) INTEGER
= 0: successful exit
.GT. 0: if INFO = i, DLAQR4 failed to compute all of
the eigenvalues. Elements 1:ilo-1 and i+1:n of WR
and WI contain those eigenvalues which have been
successfully computed. (Failures are rare.)
If INFO .GT. 0 and WANT is .FALSE., then on exit,
the remaining unconverged eigenvalues are the eigen-
values of the upper Hessenberg matrix rows and
columns ILO through INFO of the final, output
value of H.
If INFO .GT. 0 and WANTT is .TRUE., then on exit
(*) (initial value of H)*U = U*(final value of H)
where U is an orthogonal matrix. The final
value of H is upper Hessenberg and quasi-triangular
in rows and columns INFO+1 through IHI.
If INFO .GT. 0 and WANTZ is .TRUE., then on exit
(final value of Z(ILO:IHI,ILOZ:IHIZ)
= (initial value of Z(ILO:IHI,ILOZ:IHIZ)*U
where U is the orthogonal matrix in (*) (regard-
less of the value of WANTT.)
If INFO .GT. 0 and WANTZ is .FALSE., then Z is not
accessed.
================================================================
Based on contributions by
Karen Braman and Ralph Byers, Department of Mathematics,
University of Kansas, USA
================================================================
References:
K. Braman, R. Byers and R. Mathias, The Multi-Shift QR
Algorithm Part I: Maintaining Well Focused Shifts, and Level 3
Performance, SIAM Journal of Matrix Analysis, volume 23, pages
929--947, 2002.
K. Braman, R. Byers and R. Mathias, The Multi-Shift QR
Algorithm Part II: Aggressive Early Deflation, SIAM Journal
of Matrix Analysis, volume 23, pages 948--973, 2002.
================================================================
==== Matrices of order NTINY or smaller must be processed by
. DLAHQR because of insufficient subdiagonal scratch space.
. (This is a hard limit.) ====
==== Exceptional deflation windows: try to cure rare
. slow convergence by varying the size of the
. deflation window after KEXNW iterations. ====
==== Exceptional shifts: try to cure rare slow convergence
. with ad-hoc exceptional shifts every KEXSH iterations.
. ====
==== The constants WILK1 and WILK2 are used to form the
. exceptional shifts. ====
*/
/* Parameter adjustments */
h_dim1 = *ldh;
h_offset = 1 + h_dim1;
h__ -= h_offset;
--wr;
--wi;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--work;
/* Function Body */
*info = 0;
/* ==== Quick return for N = 0: nothing to do. ==== */
if (*n == 0) {
work[1] = 1.;
return 0;
}
if (*n <= 11) {
/* ==== Tiny matrices must use DLAHQR. ==== */
lwkopt = 1;
if (*lwork != -1) {
dlahqr_(wantt, wantz, n, ilo, ihi, &h__[h_offset], ldh, &wr[1], &
wi[1], iloz, ihiz, &z__[z_offset], ldz, info);
}
} else {
/*
==== Use small bulge multi-shift QR with aggressive early
. deflation on larger-than-tiny matrices. ====
==== Hope for the best. ====
*/
*info = 0;
/* ==== Set up job flags for ILAENV. ==== */
if (*wantt) {
*(unsigned char *)jbcmpz = 'S';
} else {
*(unsigned char *)jbcmpz = 'E';
}
if (*wantz) {
*(unsigned char *)&jbcmpz[1] = 'V';
} else {
*(unsigned char *)&jbcmpz[1] = 'N';
}
/*
==== NWR = recommended deflation window size. At this
. point, N .GT. NTINY = 11, so there is enough
. subdiagonal workspace for NWR.GE.2 as required.
. (In fact, there is enough subdiagonal space for
. NWR.GE.3.) ====
*/
nwr = ilaenv_(&c__13, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, (ftnlen)6,
(ftnlen)2);
nwr = max(2,nwr);
/* Computing MIN */
i__1 = *ihi - *ilo + 1, i__2 = (*n - 1) / 3, i__1 = min(i__1,i__2);
nwr = min(i__1,nwr);
/*
==== NSR = recommended number of simultaneous shifts.
. At this point N .GT. NTINY = 11, so there is at
. enough subdiagonal workspace for NSR to be even
. and greater than or equal to two as required. ====
*/
nsr = ilaenv_(&c__15, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, (ftnlen)6,
(ftnlen)2);
/* Computing MIN */
i__1 = nsr, i__2 = (*n + 6) / 9, i__1 = min(i__1,i__2), i__2 = *ihi -
*ilo;
nsr = min(i__1,i__2);
/* Computing MAX */
i__1 = 2, i__2 = nsr - nsr % 2;
nsr = max(i__1,i__2);
/*
==== Estimate optimal workspace ====
==== Workspace query call to DLAQR2 ====
*/
i__1 = nwr + 1;
dlaqr2_(wantt, wantz, n, ilo, ihi, &i__1, &h__[h_offset], ldh, iloz,
ihiz, &z__[z_offset], ldz, &ls, &ld, &wr[1], &wi[1], &h__[
h_offset], ldh, n, &h__[h_offset], ldh, n, &h__[h_offset],
ldh, &work[1], &c_n1);
/*
==== Optimal workspace = MAX(DLAQR5, DLAQR2) ====
Computing MAX
*/
i__1 = nsr * 3 / 2, i__2 = (integer) work[1];
lwkopt = max(i__1,i__2);
/* ==== Quick return in case of workspace query. ==== */
if (*lwork == -1) {
work[1] = (doublereal) lwkopt;
return 0;
}
/* ==== DLAHQR/DLAQR0 crossover point ==== */
nmin = ilaenv_(&c__12, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, (ftnlen)
6, (ftnlen)2);
nmin = max(11,nmin);
/* ==== Nibble crossover point ==== */
nibble = ilaenv_(&c__14, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, (
ftnlen)6, (ftnlen)2);
nibble = max(0,nibble);
/*
==== Accumulate reflections during ttswp? Use block
. 2-by-2 structure during matrix-matrix multiply? ====
*/
kacc22 = ilaenv_(&c__16, "DLAQR4", jbcmpz, n, ilo, ihi, lwork, (
ftnlen)6, (ftnlen)2);
kacc22 = max(0,kacc22);
kacc22 = min(2,kacc22);
/*
==== NWMAX = the largest possible deflation window for
. which there is sufficient workspace. ====
Computing MIN
*/
i__1 = (*n - 1) / 3, i__2 = *lwork / 2;
nwmax = min(i__1,i__2);
nw = nwmax;
/*
==== NSMAX = the Largest number of simultaneous shifts
. for which there is sufficient workspace. ====
Computing MIN
*/
i__1 = (*n + 6) / 9, i__2 = (*lwork << 1) / 3;
nsmax = min(i__1,i__2);
nsmax -= nsmax % 2;
/* ==== NDFL: an iteration count restarted at deflation. ==== */
ndfl = 1;
/*
==== ITMAX = iteration limit ====
Computing MAX
*/
i__1 = 10, i__2 = *ihi - *ilo + 1;
itmax = max(i__1,i__2) * 30;
/* ==== Last row and column in the active block ==== */
kbot = *ihi;
/* ==== Main Loop ==== */
i__1 = itmax;
for (it = 1; it <= i__1; ++it) {
/* ==== Done when KBOT falls below ILO ==== */
if (kbot < *ilo) {
goto L90;
}
/* ==== Locate active block ==== */
i__2 = *ilo + 1;
for (k = kbot; k >= i__2; --k) {
if (h__[k + (k - 1) * h_dim1] == 0.) {
goto L20;
}
/* L10: */
}
k = *ilo;
L20:
ktop = k;
/*
==== Select deflation window size:
. Typical Case:
. If possible and advisable, nibble the entire
. active block. If not, use size MIN(NWR,NWMAX)
. or MIN(NWR+1,NWMAX) depending upon which has
. the smaller corresponding subdiagonal entry
. (a heuristic).
.
. Exceptional Case:
. If there have been no deflations in KEXNW or
. more iterations, then vary the deflation window
. size. At first, because, larger windows are,
. in general, more powerful than smaller ones,
. rapidly increase the window to the maximum possible.
. Then, gradually reduce the window size. ====
*/
nh = kbot - ktop + 1;
nwupbd = min(nh,nwmax);
if (ndfl < 5) {
nw = min(nwupbd,nwr);
} else {
/* Computing MIN */
i__2 = nwupbd, i__3 = nw << 1;
nw = min(i__2,i__3);
}
if (nw < nwmax) {
if (nw >= nh - 1) {
nw = nh;
} else {
kwtop = kbot - nw + 1;
if ((d__1 = h__[kwtop + (kwtop - 1) * h_dim1], abs(d__1))
> (d__2 = h__[kwtop - 1 + (kwtop - 2) * h_dim1],
abs(d__2))) {
++nw;
}
}
}
if (ndfl < 5) {
ndec = -1;
} else if (ndec >= 0 || nw >= nwupbd) {
++ndec;
if (nw - ndec < 2) {
ndec = 0;
}
nw -= ndec;
}
/*
==== Aggressive early deflation:
. split workspace under the subdiagonal into
. - an nw-by-nw work array V in the lower
. left-hand-corner,
. - an NW-by-at-least-NW-but-more-is-better
. (NW-by-NHO) horizontal work array along
. the bottom edge,
. - an at-least-NW-but-more-is-better (NHV-by-NW)
. vertical work array along the left-hand-edge.
. ====
*/
kv = *n - nw + 1;
kt = nw + 1;
nho = *n - nw - 1 - kt + 1;
kwv = nw + 2;
nve = *n - nw - kwv + 1;
/* ==== Aggressive early deflation ==== */
dlaqr2_(wantt, wantz, n, &ktop, &kbot, &nw, &h__[h_offset], ldh,
iloz, ihiz, &z__[z_offset], ldz, &ls, &ld, &wr[1], &wi[1],
&h__[kv + h_dim1], ldh, &nho, &h__[kv + kt * h_dim1],
ldh, &nve, &h__[kwv + h_dim1], ldh, &work[1], lwork);
/* ==== Adjust KBOT accounting for new deflations. ==== */
kbot -= ld;
/* ==== KS points to the shifts. ==== */
ks = kbot - ls + 1;
/*
==== Skip an expensive QR sweep if there is a (partly
. heuristic) reason to expect that many eigenvalues
. will deflate without it. Here, the QR sweep is
. skipped if many eigenvalues have just been deflated
. or if the remaining active block is small.
*/
if (ld == 0 || ld * 100 <= nw * nibble && kbot - ktop + 1 > min(
nmin,nwmax)) {
/*
==== NS = nominal number of simultaneous shifts.
. This may be lowered (slightly) if DLAQR2
. did not provide that many shifts. ====
Computing MIN
Computing MAX
*/
i__4 = 2, i__5 = kbot - ktop;
i__2 = min(nsmax,nsr), i__3 = max(i__4,i__5);
ns = min(i__2,i__3);
ns -= ns % 2;
/*
==== If there have been no deflations
. in a multiple of KEXSH iterations,
. then try exceptional shifts.
. Otherwise use shifts provided by
. DLAQR2 above or from the eigenvalues
. of a trailing principal submatrix. ====
*/
if (ndfl % 6 == 0) {
ks = kbot - ns + 1;
/* Computing MAX */
i__3 = ks + 1, i__4 = ktop + 2;
i__2 = max(i__3,i__4);
for (i__ = kbot; i__ >= i__2; i__ += -2) {
ss = (d__1 = h__[i__ + (i__ - 1) * h_dim1], abs(d__1))
+ (d__2 = h__[i__ - 1 + (i__ - 2) * h_dim1],
abs(d__2));
aa = ss * .75 + h__[i__ + i__ * h_dim1];
bb = ss;
cc = ss * -.4375;
dd = aa;
dlanv2_(&aa, &bb, &cc, &dd, &wr[i__ - 1], &wi[i__ - 1]
, &wr[i__], &wi[i__], &cs, &sn);
/* L30: */
}
if (ks == ktop) {
wr[ks + 1] = h__[ks + 1 + (ks + 1) * h_dim1];
wi[ks + 1] = 0.;
wr[ks] = wr[ks + 1];
wi[ks] = wi[ks + 1];
}
} else {
/*
==== Got NS/2 or fewer shifts? Use DLAHQR
. on a trailing principal submatrix to
. get more. (Since NS.LE.NSMAX.LE.(N+6)/9,
. there is enough space below the subdiagonal
. to fit an NS-by-NS scratch array.) ====
*/
if (kbot - ks + 1 <= ns / 2) {
ks = kbot - ns + 1;
kt = *n - ns + 1;
dlacpy_("A", &ns, &ns, &h__[ks + ks * h_dim1], ldh, &
h__[kt + h_dim1], ldh);
dlahqr_(&c_false, &c_false, &ns, &c__1, &ns, &h__[kt
+ h_dim1], ldh, &wr[ks], &wi[ks], &c__1, &
c__1, zdum, &c__1, &inf);
ks += inf;
/*
==== In case of a rare QR failure use
. eigenvalues of the trailing 2-by-2
. principal submatrix. ====
*/
if (ks >= kbot) {
aa = h__[kbot - 1 + (kbot - 1) * h_dim1];
cc = h__[kbot + (kbot - 1) * h_dim1];
bb = h__[kbot - 1 + kbot * h_dim1];
dd = h__[kbot + kbot * h_dim1];
dlanv2_(&aa, &bb, &cc, &dd, &wr[kbot - 1], &wi[
kbot - 1], &wr[kbot], &wi[kbot], &cs, &sn)
;
ks = kbot - 1;
}
}
if (kbot - ks + 1 > ns) {
/*
==== Sort the shifts (Helps a little)
. Bubble sort keeps complex conjugate
. pairs together. ====
*/
sorted = FALSE_;
i__2 = ks + 1;
for (k = kbot; k >= i__2; --k) {
if (sorted) {
goto L60;
}
sorted = TRUE_;
i__3 = k - 1;
for (i__ = ks; i__ <= i__3; ++i__) {
if ((d__1 = wr[i__], abs(d__1)) + (d__2 = wi[
i__], abs(d__2)) < (d__3 = wr[i__ + 1]
, abs(d__3)) + (d__4 = wi[i__ + 1],
abs(d__4))) {
sorted = FALSE_;
swap = wr[i__];
wr[i__] = wr[i__ + 1];
wr[i__ + 1] = swap;
swap = wi[i__];
wi[i__] = wi[i__ + 1];
wi[i__ + 1] = swap;
}
/* L40: */
}
/* L50: */
}
L60:
;
}
/*
==== Shuffle shifts into pairs of real shifts
. and pairs of complex conjugate shifts
. assuming complex conjugate shifts are
. already adjacent to one another. (Yes,
. they are.) ====
*/
i__2 = ks + 2;
for (i__ = kbot; i__ >= i__2; i__ += -2) {
if (wi[i__] != -wi[i__ - 1]) {
swap = wr[i__];
wr[i__] = wr[i__ - 1];
wr[i__ - 1] = wr[i__ - 2];
wr[i__ - 2] = swap;
swap = wi[i__];
wi[i__] = wi[i__ - 1];
wi[i__ - 1] = wi[i__ - 2];
wi[i__ - 2] = swap;
}
/* L70: */
}
}
/*
==== If there are only two shifts and both are
. real, then use only one. ====
*/
if (kbot - ks + 1 == 2) {
if (wi[kbot] == 0.) {
if ((d__1 = wr[kbot] - h__[kbot + kbot * h_dim1], abs(
d__1)) < (d__2 = wr[kbot - 1] - h__[kbot +
kbot * h_dim1], abs(d__2))) {
wr[kbot - 1] = wr[kbot];
} else {
wr[kbot] = wr[kbot - 1];
}
}
}
/*
==== Use up to NS of the the smallest magnatiude
. shifts. If there aren't NS shifts available,
. then use them all, possibly dropping one to
. make the number of shifts even. ====
Computing MIN
*/
i__2 = ns, i__3 = kbot - ks + 1;
ns = min(i__2,i__3);
ns -= ns % 2;
ks = kbot - ns + 1;
/*
==== Small-bulge multi-shift QR sweep:
. split workspace under the subdiagonal into
. - a KDU-by-KDU work array U in the lower
. left-hand-corner,
. - a KDU-by-at-least-KDU-but-more-is-better
. (KDU-by-NHo) horizontal work array WH along
. the bottom edge,
. - and an at-least-KDU-but-more-is-better-by-KDU
. (NVE-by-KDU) vertical work WV arrow along
. the left-hand-edge. ====
*/
kdu = ns * 3 - 3;
ku = *n - kdu + 1;
kwh = kdu + 1;
nho = *n - kdu - 3 - (kdu + 1) + 1;
kwv = kdu + 4;
nve = *n - kdu - kwv + 1;
/* ==== Small-bulge multi-shift QR sweep ==== */
dlaqr5_(wantt, wantz, &kacc22, n, &ktop, &kbot, &ns, &wr[ks],
&wi[ks], &h__[h_offset], ldh, iloz, ihiz, &z__[
z_offset], ldz, &work[1], &c__3, &h__[ku + h_dim1],
ldh, &nve, &h__[kwv + h_dim1], ldh, &nho, &h__[ku +
kwh * h_dim1], ldh);
}
/* ==== Note progress (or the lack of it). ==== */
if (ld > 0) {
ndfl = 1;
} else {
++ndfl;
}
/*
==== End of main loop ====
L80:
*/
}
/*
==== Iteration limit exceeded. Set INFO to show where
. the problem occurred and exit. ====
*/
*info = kbot;
L90:
;
}
/* ==== Return the optimal value of LWORK. ==== */
work[1] = (doublereal) lwkopt;
/* ==== End of DLAQR4 ==== */
return 0;
} /* dlaqr4_ */
/* Subroutine */ int dlaqr5_(logical *wantt, logical *wantz, integer *kacc22,
integer *n, integer *ktop, integer *kbot, integer *nshfts, doublereal
*sr, doublereal *si, doublereal *h__, integer *ldh, integer *iloz,
integer *ihiz, doublereal *z__, integer *ldz, doublereal *v, integer *
ldv, doublereal *u, integer *ldu, integer *nv, doublereal *wv,
integer *ldwv, integer *nh, doublereal *wh, integer *ldwh)
{
/* System generated locals */
integer h_dim1, h_offset, u_dim1, u_offset, v_dim1, v_offset, wh_dim1,
wh_offset, wv_dim1, wv_offset, z_dim1, z_offset, i__1, i__2, i__3,
i__4, i__5, i__6, i__7;
doublereal d__1, d__2, d__3, d__4, d__5;
/* Local variables */
static integer i__, j, k, m, i2, j2, i4, j4, k1;
static doublereal h11, h12, h21, h22;
static integer m22, ns, nu;
static doublereal vt[3], scl;
static integer kdu, kms;
static doublereal ulp;
static integer knz, kzs;
static doublereal tst1, tst2, beta;
static logical blk22, bmp22;
static integer mend, jcol, jlen, jbot, mbot;
static doublereal swap;
static integer jtop, jrow, mtop;
static doublereal alpha;
static logical accum;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static integer ndcol, incol, krcol, nbmps;
extern /* Subroutine */ int dtrmm_(char *, char *, char *, char *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *), dlaqr1_(
integer *, doublereal *, integer *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *), dlabad_(doublereal *,
doublereal *);
extern /* Subroutine */ int dlarfg_(integer *, doublereal *, doublereal *,
integer *, doublereal *), dlacpy_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *);
static doublereal safmin;
extern /* Subroutine */ int dlaset_(char *, integer *, integer *,
doublereal *, doublereal *, doublereal *, integer *);
static doublereal safmax, refsum;
static integer mstart;
static doublereal smlnum;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
This auxiliary subroutine called by DLAQR0 performs a
single small-bulge multi-shift QR sweep.
WANTT (input) logical scalar
WANTT = .true. if the quasi-triangular Schur factor
is being computed. WANTT is set to .false. otherwise.
WANTZ (input) logical scalar
WANTZ = .true. if the orthogonal Schur factor is being
computed. WANTZ is set to .false. otherwise.
KACC22 (input) integer with value 0, 1, or 2.
Specifies the computation mode of far-from-diagonal
orthogonal updates.
= 0: DLAQR5 does not accumulate reflections and does not
use matrix-matrix multiply to update far-from-diagonal
matrix entries.
= 1: DLAQR5 accumulates reflections and uses matrix-matrix
multiply to update the far-from-diagonal matrix entries.
= 2: DLAQR5 accumulates reflections, uses matrix-matrix
multiply to update the far-from-diagonal matrix entries,
and takes advantage of 2-by-2 block structure during
matrix multiplies.
N (input) integer scalar
N is the order of the Hessenberg matrix H upon which this
subroutine operates.
KTOP (input) integer scalar
KBOT (input) integer scalar
These are the first and last rows and columns of an
isolated diagonal block upon which the QR sweep is to be
applied. It is assumed without a check that
either KTOP = 1 or H(KTOP,KTOP-1) = 0
and
either KBOT = N or H(KBOT+1,KBOT) = 0.
NSHFTS (input) integer scalar
NSHFTS gives the number of simultaneous shifts. NSHFTS
must be positive and even.
SR (input/output) DOUBLE PRECISION array of size (NSHFTS)
SI (input/output) DOUBLE PRECISION array of size (NSHFTS)
SR contains the real parts and SI contains the imaginary
parts of the NSHFTS shifts of origin that define the
multi-shift QR sweep. On output SR and SI may be
reordered.
H (input/output) DOUBLE PRECISION array of size (LDH,N)
On input H contains a Hessenberg matrix. On output a
multi-shift QR sweep with shifts SR(J)+i*SI(J) is applied
to the isolated diagonal block in rows and columns KTOP
through KBOT.
LDH (input) integer scalar
LDH is the leading dimension of H just as declared in the
calling procedure. LDH.GE.MAX(1,N).
ILOZ (input) INTEGER
IHIZ (input) INTEGER
Specify the rows of Z to which transformations must be
applied if WANTZ is .TRUE.. 1 .LE. ILOZ .LE. IHIZ .LE. N
Z (input/output) DOUBLE PRECISION array of size (LDZ,IHI)
If WANTZ = .TRUE., then the QR Sweep orthogonal
similarity transformation is accumulated into
Z(ILOZ:IHIZ,ILO:IHI) from the right.
If WANTZ = .FALSE., then Z is unreferenced.
LDZ (input) integer scalar
LDA is the leading dimension of Z just as declared in
the calling procedure. LDZ.GE.N.
V (workspace) DOUBLE PRECISION array of size (LDV,NSHFTS/2)
LDV (input) integer scalar
LDV is the leading dimension of V as declared in the
calling procedure. LDV.GE.3.
U (workspace) DOUBLE PRECISION array of size
(LDU,3*NSHFTS-3)
LDU (input) integer scalar
LDU is the leading dimension of U just as declared in the
in the calling subroutine. LDU.GE.3*NSHFTS-3.
NH (input) integer scalar
NH is the number of columns in array WH available for
workspace. NH.GE.1.
WH (workspace) DOUBLE PRECISION array of size (LDWH,NH)
LDWH (input) integer scalar
Leading dimension of WH just as declared in the
calling procedure. LDWH.GE.3*NSHFTS-3.
NV (input) integer scalar
NV is the number of rows in WV agailable for workspace.
NV.GE.1.
WV (workspace) DOUBLE PRECISION array of size
(LDWV,3*NSHFTS-3)
LDWV (input) integer scalar
LDWV is the leading dimension of WV as declared in the
in the calling subroutine. LDWV.GE.NV.
================================================================
Based on contributions by
Karen Braman and Ralph Byers, Department of Mathematics,
University of Kansas, USA
================================================================
Reference:
K. Braman, R. Byers and R. Mathias, The Multi-Shift QR
Algorithm Part I: Maintaining Well Focused Shifts, and
Level 3 Performance, SIAM Journal of Matrix Analysis,
volume 23, pages 929--947, 2002.
================================================================
==== If there are no shifts, then there is nothing to do. ====
*/
/* Parameter adjustments */
--sr;
--si;
h_dim1 = *ldh;
h_offset = 1 + h_dim1;
h__ -= h_offset;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
v_dim1 = *ldv;
v_offset = 1 + v_dim1;
v -= v_offset;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
wv_dim1 = *ldwv;
wv_offset = 1 + wv_dim1;
wv -= wv_offset;
wh_dim1 = *ldwh;
wh_offset = 1 + wh_dim1;
wh -= wh_offset;
/* Function Body */
if (*nshfts < 2) {
return 0;
}
/*
==== If the active block is empty or 1-by-1, then there
. is nothing to do. ====
*/
if (*ktop >= *kbot) {
return 0;
}
/*
==== Shuffle shifts into pairs of real shifts and pairs
. of complex conjugate shifts assuming complex
. conjugate shifts are already adjacent to one
. another. ====
*/
i__1 = *nshfts - 2;
for (i__ = 1; i__ <= i__1; i__ += 2) {
if (si[i__] != -si[i__ + 1]) {
swap = sr[i__];
sr[i__] = sr[i__ + 1];
sr[i__ + 1] = sr[i__ + 2];
sr[i__ + 2] = swap;
swap = si[i__];
si[i__] = si[i__ + 1];
si[i__ + 1] = si[i__ + 2];
si[i__ + 2] = swap;
}
/* L10: */
}
/*
==== NSHFTS is supposed to be even, but if it is odd,
. then simply reduce it by one. The shuffle above
. ensures that the dropped shift is real and that
. the remaining shifts are paired. ====
*/
ns = *nshfts - *nshfts % 2;
/* ==== Machine constants for deflation ==== */
safmin = SAFEMINIMUM;
safmax = 1. / safmin;
dlabad_(&safmin, &safmax);
ulp = PRECISION;
smlnum = safmin * ((doublereal) (*n) / ulp);
/*
==== Use accumulated reflections to update far-from-diagonal
. entries ? ====
*/
accum = *kacc22 == 1 || *kacc22 == 2;
/* ==== If so, exploit the 2-by-2 block structure? ==== */
blk22 = ns > 2 && *kacc22 == 2;
/* ==== clear trash ==== */
if (*ktop + 2 <= *kbot) {
h__[*ktop + 2 + *ktop * h_dim1] = 0.;
}
/* ==== NBMPS = number of 2-shift bulges in the chain ==== */
nbmps = ns / 2;
/* ==== KDU = width of slab ==== */
kdu = nbmps * 6 - 3;
/* ==== Create and chase chains of NBMPS bulges ==== */
i__1 = *kbot - 2;
i__2 = nbmps * 3 - 2;
for (incol = (1 - nbmps) * 3 + *ktop - 1; i__2 < 0 ? incol >= i__1 :
incol <= i__1; incol += i__2) {
ndcol = incol + kdu;
if (accum) {
dlaset_("ALL", &kdu, &kdu, &c_b29, &c_b15, &u[u_offset], ldu);
}
/*
==== Near-the-diagonal bulge chase. The following loop
. performs the near-the-diagonal part of a small bulge
. multi-shift QR sweep. Each 6*NBMPS-2 column diagonal
. chunk extends from column INCOL to column NDCOL
. (including both column INCOL and column NDCOL). The
. following loop chases a 3*NBMPS column long chain of
. NBMPS bulges 3*NBMPS-2 columns to the right. (INCOL
. may be less than KTOP and and NDCOL may be greater than
. KBOT indicating phantom columns from which to chase
. bulges before they are actually introduced or to which
. to chase bulges beyond column KBOT.) ====
Computing MIN
*/
i__4 = incol + nbmps * 3 - 3, i__5 = *kbot - 2;
i__3 = min(i__4,i__5);
for (krcol = incol; krcol <= i__3; ++krcol) {
/*
==== Bulges number MTOP to MBOT are active double implicit
. shift bulges. There may or may not also be small
. 2-by-2 bulge, if there is room. The inactive bulges
. (if any) must wait until the active bulges have moved
. down the diagonal to make room. The phantom matrix
. paradigm described above helps keep track. ====
Computing MAX
*/
i__4 = 1, i__5 = (*ktop - 1 - krcol + 2) / 3 + 1;
mtop = max(i__4,i__5);
/* Computing MIN */
i__4 = nbmps, i__5 = (*kbot - krcol) / 3;
mbot = min(i__4,i__5);
m22 = mbot + 1;
bmp22 = mbot < nbmps && krcol + (m22 - 1) * 3 == *kbot - 2;
/*
==== Generate reflections to chase the chain right
. one column. (The minimum value of K is KTOP-1.) ====
*/
i__4 = mbot;
for (m = mtop; m <= i__4; ++m) {
k = krcol + (m - 1) * 3;
if (k == *ktop - 1) {
dlaqr1_(&c__3, &h__[*ktop + *ktop * h_dim1], ldh, &sr[(m
<< 1) - 1], &si[(m << 1) - 1], &sr[m * 2], &si[m *
2], &v[m * v_dim1 + 1]);
alpha = v[m * v_dim1 + 1];
dlarfg_(&c__3, &alpha, &v[m * v_dim1 + 2], &c__1, &v[m *
v_dim1 + 1]);
} else {
beta = h__[k + 1 + k * h_dim1];
v[m * v_dim1 + 2] = h__[k + 2 + k * h_dim1];
v[m * v_dim1 + 3] = h__[k + 3 + k * h_dim1];
dlarfg_(&c__3, &beta, &v[m * v_dim1 + 2], &c__1, &v[m *
v_dim1 + 1]);
/*
==== A Bulge may collapse because of vigilant
. deflation or destructive underflow. In the
. underflow case, try the two-small-subdiagonals
. trick to try to reinflate the bulge. ====
*/
if (h__[k + 3 + k * h_dim1] != 0. || h__[k + 3 + (k + 1) *
h_dim1] != 0. || h__[k + 3 + (k + 2) * h_dim1] ==
0.) {
/* ==== Typical case: not collapsed (yet). ==== */
h__[k + 1 + k * h_dim1] = beta;
h__[k + 2 + k * h_dim1] = 0.;
h__[k + 3 + k * h_dim1] = 0.;
} else {
/*
==== Atypical case: collapsed. Attempt to
. reintroduce ignoring H(K+1,K) and H(K+2,K).
. If the fill resulting from the new
. reflector is too large, then abandon it.
. Otherwise, use the new one. ====
*/
dlaqr1_(&c__3, &h__[k + 1 + (k + 1) * h_dim1], ldh, &
sr[(m << 1) - 1], &si[(m << 1) - 1], &sr[m *
2], &si[m * 2], vt);
alpha = vt[0];
dlarfg_(&c__3, &alpha, &vt[1], &c__1, vt);
refsum = vt[0] * (h__[k + 1 + k * h_dim1] + vt[1] *
h__[k + 2 + k * h_dim1]);
if ((d__1 = h__[k + 2 + k * h_dim1] - refsum * vt[1],
abs(d__1)) + (d__2 = refsum * vt[2], abs(d__2)
) > ulp * ((d__3 = h__[k + k * h_dim1], abs(
d__3)) + (d__4 = h__[k + 1 + (k + 1) * h_dim1]
, abs(d__4)) + (d__5 = h__[k + 2 + (k + 2) *
h_dim1], abs(d__5)))) {
/*
==== Starting a new bulge here would
. create non-negligible fill. Use
. the old one with trepidation. ====
*/
h__[k + 1 + k * h_dim1] = beta;
h__[k + 2 + k * h_dim1] = 0.;
h__[k + 3 + k * h_dim1] = 0.;
} else {
/*
==== Stating a new bulge here would
. create only negligible fill.
. Replace the old reflector with
. the new one. ====
*/
h__[k + 1 + k * h_dim1] -= refsum;
h__[k + 2 + k * h_dim1] = 0.;
h__[k + 3 + k * h_dim1] = 0.;
v[m * v_dim1 + 1] = vt[0];
v[m * v_dim1 + 2] = vt[1];
v[m * v_dim1 + 3] = vt[2];
}
}
}
/* L20: */
}
/* ==== Generate a 2-by-2 reflection, if needed. ==== */
k = krcol + (m22 - 1) * 3;
if (bmp22) {
if (k == *ktop - 1) {
dlaqr1_(&c__2, &h__[k + 1 + (k + 1) * h_dim1], ldh, &sr[(
m22 << 1) - 1], &si[(m22 << 1) - 1], &sr[m22 * 2],
&si[m22 * 2], &v[m22 * v_dim1 + 1]);
beta = v[m22 * v_dim1 + 1];
dlarfg_(&c__2, &beta, &v[m22 * v_dim1 + 2], &c__1, &v[m22
* v_dim1 + 1]);
} else {
beta = h__[k + 1 + k * h_dim1];
v[m22 * v_dim1 + 2] = h__[k + 2 + k * h_dim1];
dlarfg_(&c__2, &beta, &v[m22 * v_dim1 + 2], &c__1, &v[m22
* v_dim1 + 1]);
h__[k + 1 + k * h_dim1] = beta;
h__[k + 2 + k * h_dim1] = 0.;
}
}
/* ==== Multiply H by reflections from the left ==== */
if (accum) {
jbot = min(ndcol,*kbot);
} else if (*wantt) {
jbot = *n;
} else {
jbot = *kbot;
}
i__4 = jbot;
for (j = max(*ktop,krcol); j <= i__4; ++j) {
/* Computing MIN */
i__5 = mbot, i__6 = (j - krcol + 2) / 3;
mend = min(i__5,i__6);
i__5 = mend;
for (m = mtop; m <= i__5; ++m) {
k = krcol + (m - 1) * 3;
refsum = v[m * v_dim1 + 1] * (h__[k + 1 + j * h_dim1] + v[
m * v_dim1 + 2] * h__[k + 2 + j * h_dim1] + v[m *
v_dim1 + 3] * h__[k + 3 + j * h_dim1]);
h__[k + 1 + j * h_dim1] -= refsum;
h__[k + 2 + j * h_dim1] -= refsum * v[m * v_dim1 + 2];
h__[k + 3 + j * h_dim1] -= refsum * v[m * v_dim1 + 3];
/* L30: */
}
/* L40: */
}
if (bmp22) {
k = krcol + (m22 - 1) * 3;
/* Computing MAX */
i__4 = k + 1;
i__5 = jbot;
for (j = max(i__4,*ktop); j <= i__5; ++j) {
refsum = v[m22 * v_dim1 + 1] * (h__[k + 1 + j * h_dim1] +
v[m22 * v_dim1 + 2] * h__[k + 2 + j * h_dim1]);
h__[k + 1 + j * h_dim1] -= refsum;
h__[k + 2 + j * h_dim1] -= refsum * v[m22 * v_dim1 + 2];
/* L50: */
}
}
/*
==== Multiply H by reflections from the right.
. Delay filling in the last row until the
. vigilant deflation check is complete. ====
*/
if (accum) {
jtop = max(*ktop,incol);
} else if (*wantt) {
jtop = 1;
} else {
jtop = *ktop;
}
i__5 = mbot;
for (m = mtop; m <= i__5; ++m) {
if (v[m * v_dim1 + 1] != 0.) {
k = krcol + (m - 1) * 3;
/* Computing MIN */
i__6 = *kbot, i__7 = k + 3;
i__4 = min(i__6,i__7);
for (j = jtop; j <= i__4; ++j) {
refsum = v[m * v_dim1 + 1] * (h__[j + (k + 1) *
h_dim1] + v[m * v_dim1 + 2] * h__[j + (k + 2)
* h_dim1] + v[m * v_dim1 + 3] * h__[j + (k +
3) * h_dim1]);
h__[j + (k + 1) * h_dim1] -= refsum;
h__[j + (k + 2) * h_dim1] -= refsum * v[m * v_dim1 +
2];
h__[j + (k + 3) * h_dim1] -= refsum * v[m * v_dim1 +
3];
/* L60: */
}
if (accum) {
/*
==== Accumulate U. (If necessary, update Z later
. with with an efficient matrix-matrix
. multiply.) ====
*/
kms = k - incol;
/* Computing MAX */
i__4 = 1, i__6 = *ktop - incol;
i__7 = kdu;
for (j = max(i__4,i__6); j <= i__7; ++j) {
refsum = v[m * v_dim1 + 1] * (u[j + (kms + 1) *
u_dim1] + v[m * v_dim1 + 2] * u[j + (kms
+ 2) * u_dim1] + v[m * v_dim1 + 3] * u[j
+ (kms + 3) * u_dim1]);
u[j + (kms + 1) * u_dim1] -= refsum;
u[j + (kms + 2) * u_dim1] -= refsum * v[m *
v_dim1 + 2];
u[j + (kms + 3) * u_dim1] -= refsum * v[m *
v_dim1 + 3];
/* L70: */
}
} else if (*wantz) {
/*
==== U is not accumulated, so update Z
. now by multiplying by reflections
. from the right. ====
*/
i__7 = *ihiz;
for (j = *iloz; j <= i__7; ++j) {
refsum = v[m * v_dim1 + 1] * (z__[j + (k + 1) *
z_dim1] + v[m * v_dim1 + 2] * z__[j + (k
+ 2) * z_dim1] + v[m * v_dim1 + 3] * z__[
j + (k + 3) * z_dim1]);
z__[j + (k + 1) * z_dim1] -= refsum;
z__[j + (k + 2) * z_dim1] -= refsum * v[m *
v_dim1 + 2];
z__[j + (k + 3) * z_dim1] -= refsum * v[m *
v_dim1 + 3];
/* L80: */
}
}
}
/* L90: */
}
/* ==== Special case: 2-by-2 reflection (if needed) ==== */
k = krcol + (m22 - 1) * 3;
if (bmp22 && v[m22 * v_dim1 + 1] != 0.) {
/* Computing MIN */
i__7 = *kbot, i__4 = k + 3;
i__5 = min(i__7,i__4);
for (j = jtop; j <= i__5; ++j) {
refsum = v[m22 * v_dim1 + 1] * (h__[j + (k + 1) * h_dim1]
+ v[m22 * v_dim1 + 2] * h__[j + (k + 2) * h_dim1])
;
h__[j + (k + 1) * h_dim1] -= refsum;
h__[j + (k + 2) * h_dim1] -= refsum * v[m22 * v_dim1 + 2];
/* L100: */
}
if (accum) {
kms = k - incol;
/* Computing MAX */
i__5 = 1, i__7 = *ktop - incol;
i__4 = kdu;
for (j = max(i__5,i__7); j <= i__4; ++j) {
refsum = v[m22 * v_dim1 + 1] * (u[j + (kms + 1) *
u_dim1] + v[m22 * v_dim1 + 2] * u[j + (kms +
2) * u_dim1]);
u[j + (kms + 1) * u_dim1] -= refsum;
u[j + (kms + 2) * u_dim1] -= refsum * v[m22 * v_dim1
+ 2];
/* L110: */
}
} else if (*wantz) {
i__4 = *ihiz;
for (j = *iloz; j <= i__4; ++j) {
refsum = v[m22 * v_dim1 + 1] * (z__[j + (k + 1) *
z_dim1] + v[m22 * v_dim1 + 2] * z__[j + (k +
2) * z_dim1]);
z__[j + (k + 1) * z_dim1] -= refsum;
z__[j + (k + 2) * z_dim1] -= refsum * v[m22 * v_dim1
+ 2];
/* L120: */
}
}
}
/* ==== Vigilant deflation check ==== */
mstart = mtop;
if (krcol + (mstart - 1) * 3 < *ktop) {
++mstart;
}
mend = mbot;
if (bmp22) {
++mend;
}
if (krcol == *kbot - 2) {
++mend;
}
i__4 = mend;
for (m = mstart; m <= i__4; ++m) {
/* Computing MIN */
i__5 = *kbot - 1, i__7 = krcol + (m - 1) * 3;
k = min(i__5,i__7);
/*
==== The following convergence test requires that
. the tradition small-compared-to-nearby-diagonals
. criterion and the Ahues & Tisseur (LAWN 122, 1997)
. criteria both be satisfied. The latter improves
. accuracy in some examples. Falling back on an
. alternate convergence criterion when TST1 or TST2
. is zero (as done here) is traditional but probably
. unnecessary. ====
*/
if (h__[k + 1 + k * h_dim1] != 0.) {
tst1 = (d__1 = h__[k + k * h_dim1], abs(d__1)) + (d__2 =
h__[k + 1 + (k + 1) * h_dim1], abs(d__2));
if (tst1 == 0.) {
if (k >= *ktop + 1) {
tst1 += (d__1 = h__[k + (k - 1) * h_dim1], abs(
d__1));
}
if (k >= *ktop + 2) {
tst1 += (d__1 = h__[k + (k - 2) * h_dim1], abs(
d__1));
}
if (k >= *ktop + 3) {
tst1 += (d__1 = h__[k + (k - 3) * h_dim1], abs(
d__1));
}
if (k <= *kbot - 2) {
tst1 += (d__1 = h__[k + 2 + (k + 1) * h_dim1],
abs(d__1));
}
if (k <= *kbot - 3) {
tst1 += (d__1 = h__[k + 3 + (k + 1) * h_dim1],
abs(d__1));
}
if (k <= *kbot - 4) {
tst1 += (d__1 = h__[k + 4 + (k + 1) * h_dim1],
abs(d__1));
}
}
/* Computing MAX */
d__2 = smlnum, d__3 = ulp * tst1;
if ((d__1 = h__[k + 1 + k * h_dim1], abs(d__1)) <= max(
d__2,d__3)) {
/* Computing MAX */
d__3 = (d__1 = h__[k + 1 + k * h_dim1], abs(d__1)),
d__4 = (d__2 = h__[k + (k + 1) * h_dim1], abs(
d__2));
h12 = max(d__3,d__4);
/* Computing MIN */
d__3 = (d__1 = h__[k + 1 + k * h_dim1], abs(d__1)),
d__4 = (d__2 = h__[k + (k + 1) * h_dim1], abs(
d__2));
h21 = min(d__3,d__4);
/* Computing MAX */
d__3 = (d__1 = h__[k + 1 + (k + 1) * h_dim1], abs(
d__1)), d__4 = (d__2 = h__[k + k * h_dim1] -
h__[k + 1 + (k + 1) * h_dim1], abs(d__2));
h11 = max(d__3,d__4);
/* Computing MIN */
d__3 = (d__1 = h__[k + 1 + (k + 1) * h_dim1], abs(
d__1)), d__4 = (d__2 = h__[k + k * h_dim1] -
h__[k + 1 + (k + 1) * h_dim1], abs(d__2));
h22 = min(d__3,d__4);
scl = h11 + h12;
tst2 = h22 * (h11 / scl);
/* Computing MAX */
d__1 = smlnum, d__2 = ulp * tst2;
if (tst2 == 0. || h21 * (h12 / scl) <= max(d__1,d__2))
{
h__[k + 1 + k * h_dim1] = 0.;
}
}
}
/* L130: */
}
/*
==== Fill in the last row of each bulge. ====
Computing MIN
*/
i__4 = nbmps, i__5 = (*kbot - krcol - 1) / 3;
mend = min(i__4,i__5);
i__4 = mend;
for (m = mtop; m <= i__4; ++m) {
k = krcol + (m - 1) * 3;
refsum = v[m * v_dim1 + 1] * v[m * v_dim1 + 3] * h__[k + 4 + (
k + 3) * h_dim1];
h__[k + 4 + (k + 1) * h_dim1] = -refsum;
h__[k + 4 + (k + 2) * h_dim1] = -refsum * v[m * v_dim1 + 2];
h__[k + 4 + (k + 3) * h_dim1] -= refsum * v[m * v_dim1 + 3];
/* L140: */
}
/*
==== End of near-the-diagonal bulge chase. ====
L150:
*/
}
/*
==== Use U (if accumulated) to update far-from-diagonal
. entries in H. If required, use U to update Z as
. well. ====
*/
if (accum) {
if (*wantt) {
jtop = 1;
jbot = *n;
} else {
jtop = *ktop;
jbot = *kbot;
}
if (! blk22 || incol < *ktop || ndcol > *kbot || ns <= 2) {
/*
==== Updates not exploiting the 2-by-2 block
. structure of U. K1 and NU keep track of
. the location and size of U in the special
. cases of introducing bulges and chasing
. bulges off the bottom. In these special
. cases and in case the number of shifts
. is NS = 2, there is no 2-by-2 block
. structure to exploit. ====
Computing MAX
*/
i__3 = 1, i__4 = *ktop - incol;
k1 = max(i__3,i__4);
/* Computing MAX */
i__3 = 0, i__4 = ndcol - *kbot;
nu = kdu - max(i__3,i__4) - k1 + 1;
/* ==== Horizontal Multiply ==== */
i__3 = jbot;
i__4 = *nh;
for (jcol = min(ndcol,*kbot) + 1; i__4 < 0 ? jcol >= i__3 :
jcol <= i__3; jcol += i__4) {
/* Computing MIN */
i__5 = *nh, i__7 = jbot - jcol + 1;
jlen = min(i__5,i__7);
dgemm_("C", "N", &nu, &jlen, &nu, &c_b15, &u[k1 + k1 *
u_dim1], ldu, &h__[incol + k1 + jcol * h_dim1],
ldh, &c_b29, &wh[wh_offset], ldwh);
dlacpy_("ALL", &nu, &jlen, &wh[wh_offset], ldwh, &h__[
incol + k1 + jcol * h_dim1], ldh);
/* L160: */
}
/* ==== Vertical multiply ==== */
i__4 = max(*ktop,incol) - 1;
i__3 = *nv;
for (jrow = jtop; i__3 < 0 ? jrow >= i__4 : jrow <= i__4;
jrow += i__3) {
/* Computing MIN */
i__5 = *nv, i__7 = max(*ktop,incol) - jrow;
jlen = min(i__5,i__7);
dgemm_("N", "N", &jlen, &nu, &nu, &c_b15, &h__[jrow + (
incol + k1) * h_dim1], ldh, &u[k1 + k1 * u_dim1],
ldu, &c_b29, &wv[wv_offset], ldwv);
dlacpy_("ALL", &jlen, &nu, &wv[wv_offset], ldwv, &h__[
jrow + (incol + k1) * h_dim1], ldh);
/* L170: */
}
/* ==== Z multiply (also vertical) ==== */
if (*wantz) {
i__3 = *ihiz;
i__4 = *nv;
for (jrow = *iloz; i__4 < 0 ? jrow >= i__3 : jrow <= i__3;
jrow += i__4) {
/* Computing MIN */
i__5 = *nv, i__7 = *ihiz - jrow + 1;
jlen = min(i__5,i__7);
dgemm_("N", "N", &jlen, &nu, &nu, &c_b15, &z__[jrow +
(incol + k1) * z_dim1], ldz, &u[k1 + k1 *
u_dim1], ldu, &c_b29, &wv[wv_offset], ldwv);
dlacpy_("ALL", &jlen, &nu, &wv[wv_offset], ldwv, &z__[
jrow + (incol + k1) * z_dim1], ldz)
;
/* L180: */
}
}
} else {
/*
==== Updates exploiting U's 2-by-2 block structure.
. (I2, I4, J2, J4 are the last rows and columns
. of the blocks.) ====
*/
i2 = (kdu + 1) / 2;
i4 = kdu;
j2 = i4 - i2;
j4 = kdu;
/*
==== KZS and KNZ deal with the band of zeros
. along the diagonal of one of the triangular
. blocks. ====
*/
kzs = j4 - j2 - (ns + 1);
knz = ns + 1;
/* ==== Horizontal multiply ==== */
i__4 = jbot;
i__3 = *nh;
for (jcol = min(ndcol,*kbot) + 1; i__3 < 0 ? jcol >= i__4 :
jcol <= i__4; jcol += i__3) {
/* Computing MIN */
i__5 = *nh, i__7 = jbot - jcol + 1;
jlen = min(i__5,i__7);
/*
==== Copy bottom of H to top+KZS of scratch ====
(The first KZS rows get multiplied by zero.) ====
*/
dlacpy_("ALL", &knz, &jlen, &h__[incol + 1 + j2 + jcol *
h_dim1], ldh, &wh[kzs + 1 + wh_dim1], ldwh);
/* ==== Multiply by U21' ==== */
dlaset_("ALL", &kzs, &jlen, &c_b29, &c_b29, &wh[wh_offset]
, ldwh);
dtrmm_("L", "U", "C", "N", &knz, &jlen, &c_b15, &u[j2 + 1
+ (kzs + 1) * u_dim1], ldu, &wh[kzs + 1 + wh_dim1]
, ldwh);
/* ==== Multiply top of H by U11' ==== */
dgemm_("C", "N", &i2, &jlen, &j2, &c_b15, &u[u_offset],
ldu, &h__[incol + 1 + jcol * h_dim1], ldh, &c_b15,
&wh[wh_offset], ldwh);
/* ==== Copy top of H to bottom of WH ==== */
dlacpy_("ALL", &j2, &jlen, &h__[incol + 1 + jcol * h_dim1]
, ldh, &wh[i2 + 1 + wh_dim1], ldwh);
/* ==== Multiply by U21' ==== */
dtrmm_("L", "L", "C", "N", &j2, &jlen, &c_b15, &u[(i2 + 1)
* u_dim1 + 1], ldu, &wh[i2 + 1 + wh_dim1], ldwh);
/* ==== Multiply by U22 ==== */
i__5 = i4 - i2;
i__7 = j4 - j2;
dgemm_("C", "N", &i__5, &jlen, &i__7, &c_b15, &u[j2 + 1 +
(i2 + 1) * u_dim1], ldu, &h__[incol + 1 + j2 +
jcol * h_dim1], ldh, &c_b15, &wh[i2 + 1 + wh_dim1]
, ldwh);
/* ==== Copy it back ==== */
dlacpy_("ALL", &kdu, &jlen, &wh[wh_offset], ldwh, &h__[
incol + 1 + jcol * h_dim1], ldh);
/* L190: */
}
/* ==== Vertical multiply ==== */
i__3 = max(incol,*ktop) - 1;
i__4 = *nv;
for (jrow = jtop; i__4 < 0 ? jrow >= i__3 : jrow <= i__3;
jrow += i__4) {
/* Computing MIN */
i__5 = *nv, i__7 = max(incol,*ktop) - jrow;
jlen = min(i__5,i__7);
/*
==== Copy right of H to scratch (the first KZS
. columns get multiplied by zero) ====
*/
dlacpy_("ALL", &jlen, &knz, &h__[jrow + (incol + 1 + j2) *
h_dim1], ldh, &wv[(kzs + 1) * wv_dim1 + 1], ldwv);
/* ==== Multiply by U21 ==== */
dlaset_("ALL", &jlen, &kzs, &c_b29, &c_b29, &wv[wv_offset]
, ldwv);
dtrmm_("R", "U", "N", "N", &jlen, &knz, &c_b15, &u[j2 + 1
+ (kzs + 1) * u_dim1], ldu, &wv[(kzs + 1) *
wv_dim1 + 1], ldwv);
/* ==== Multiply by U11 ==== */
dgemm_("N", "N", &jlen, &i2, &j2, &c_b15, &h__[jrow + (
incol + 1) * h_dim1], ldh, &u[u_offset], ldu, &
c_b15, &wv[wv_offset], ldwv)
;
/* ==== Copy left of H to right of scratch ==== */
dlacpy_("ALL", &jlen, &j2, &h__[jrow + (incol + 1) *
h_dim1], ldh, &wv[(i2 + 1) * wv_dim1 + 1], ldwv);
/* ==== Multiply by U21 ==== */
i__5 = i4 - i2;
dtrmm_("R", "L", "N", "N", &jlen, &i__5, &c_b15, &u[(i2 +
1) * u_dim1 + 1], ldu, &wv[(i2 + 1) * wv_dim1 + 1]
, ldwv);
/* ==== Multiply by U22 ==== */
i__5 = i4 - i2;
i__7 = j4 - j2;
dgemm_("N", "N", &jlen, &i__5, &i__7, &c_b15, &h__[jrow +
(incol + 1 + j2) * h_dim1], ldh, &u[j2 + 1 + (i2
+ 1) * u_dim1], ldu, &c_b15, &wv[(i2 + 1) *
wv_dim1 + 1], ldwv);
/* ==== Copy it back ==== */
dlacpy_("ALL", &jlen, &kdu, &wv[wv_offset], ldwv, &h__[
jrow + (incol + 1) * h_dim1], ldh);
/* L200: */
}
/* ==== Multiply Z (also vertical) ==== */
if (*wantz) {
i__4 = *ihiz;
i__3 = *nv;
for (jrow = *iloz; i__3 < 0 ? jrow >= i__4 : jrow <= i__4;
jrow += i__3) {
/* Computing MIN */
i__5 = *nv, i__7 = *ihiz - jrow + 1;
jlen = min(i__5,i__7);
/*
==== Copy right of Z to left of scratch (first
. KZS columns get multiplied by zero) ====
*/
dlacpy_("ALL", &jlen, &knz, &z__[jrow + (incol + 1 +
j2) * z_dim1], ldz, &wv[(kzs + 1) * wv_dim1 +
1], ldwv);
/* ==== Multiply by U12 ==== */
dlaset_("ALL", &jlen, &kzs, &c_b29, &c_b29, &wv[
wv_offset], ldwv);
dtrmm_("R", "U", "N", "N", &jlen, &knz, &c_b15, &u[j2
+ 1 + (kzs + 1) * u_dim1], ldu, &wv[(kzs + 1)
* wv_dim1 + 1], ldwv);
/* ==== Multiply by U11 ==== */
dgemm_("N", "N", &jlen, &i2, &j2, &c_b15, &z__[jrow +
(incol + 1) * z_dim1], ldz, &u[u_offset], ldu,
&c_b15, &wv[wv_offset], ldwv);
/* ==== Copy left of Z to right of scratch ==== */
dlacpy_("ALL", &jlen, &j2, &z__[jrow + (incol + 1) *
z_dim1], ldz, &wv[(i2 + 1) * wv_dim1 + 1],
ldwv);
/* ==== Multiply by U21 ==== */
i__5 = i4 - i2;
dtrmm_("R", "L", "N", "N", &jlen, &i__5, &c_b15, &u[(
i2 + 1) * u_dim1 + 1], ldu, &wv[(i2 + 1) *
wv_dim1 + 1], ldwv);
/* ==== Multiply by U22 ==== */
i__5 = i4 - i2;
i__7 = j4 - j2;
dgemm_("N", "N", &jlen, &i__5, &i__7, &c_b15, &z__[
jrow + (incol + 1 + j2) * z_dim1], ldz, &u[j2
+ 1 + (i2 + 1) * u_dim1], ldu, &c_b15, &wv[(
i2 + 1) * wv_dim1 + 1], ldwv);
/* ==== Copy the result back to Z ==== */
dlacpy_("ALL", &jlen, &kdu, &wv[wv_offset], ldwv, &
z__[jrow + (incol + 1) * z_dim1], ldz);
/* L210: */
}
}
}
}
/* L220: */
}
/* ==== End of DLAQR5 ==== */
return 0;
} /* dlaqr5_ */
/* Subroutine */ int dlarf_(char *side, integer *m, integer *n, doublereal *v,
integer *incv, doublereal *tau, doublereal *c__, integer *ldc,
doublereal *work)
{
/* System generated locals */
integer c_dim1, c_offset;
doublereal d__1;
/* Local variables */
static integer i__;
static logical applyleft;
extern /* Subroutine */ int dger_(integer *, integer *, doublereal *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dgemv_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *);
static integer lastc, lastv;
extern integer iladlc_(integer *, integer *, doublereal *, integer *),
iladlr_(integer *, integer *, doublereal *, integer *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLARF applies a real elementary reflector H to a real m by n matrix
C, from either the left or the right. H is represented in the form
H = I - tau * v * v'
where tau is a real scalar and v is a real vector.
If tau = 0, then H is taken to be the unit matrix.
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': form H * C
= 'R': form C * H
M (input) INTEGER
The number of rows of the matrix C.
N (input) INTEGER
The number of columns of the matrix C.
V (input) DOUBLE PRECISION array, dimension
(1 + (M-1)*abs(INCV)) if SIDE = 'L'
or (1 + (N-1)*abs(INCV)) if SIDE = 'R'
The vector v in the representation of H. V is not used if
TAU = 0.
INCV (input) INTEGER
The increment between elements of v. INCV <> 0.
TAU (input) DOUBLE PRECISION
The value tau in the representation of H.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the m by n matrix C.
On exit, C is overwritten by the matrix H * C if SIDE = 'L',
or C * H if SIDE = 'R'.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace) DOUBLE PRECISION array, dimension
(N) if SIDE = 'L'
or (M) if SIDE = 'R'
=====================================================================
*/
/* Parameter adjustments */
--v;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
applyleft = lsame_(side, "L");
lastv = 0;
lastc = 0;
if (*tau != 0.) {
/*
Set up variables for scanning V. LASTV begins pointing to the end
of V.
*/
if (applyleft) {
lastv = *m;
} else {
lastv = *n;
}
if (*incv > 0) {
i__ = (lastv - 1) * *incv + 1;
} else {
i__ = 1;
}
/* Look for the last non-zero row in V. */
while(lastv > 0 && v[i__] == 0.) {
--lastv;
i__ -= *incv;
}
if (applyleft) {
/* Scan for the last non-zero column in C(1:lastv,:). */
lastc = iladlc_(&lastv, n, &c__[c_offset], ldc);
} else {
/* Scan for the last non-zero row in C(:,1:lastv). */
lastc = iladlr_(m, &lastv, &c__[c_offset], ldc);
}
}
/*
Note that lastc.eq.0 renders the BLAS operations null; no special
case is needed at this level.
*/
if (applyleft) {
/* Form H * C */
if (lastv > 0) {
/* w(1:lastc,1) := C(1:lastv,1:lastc)' * v(1:lastv,1) */
dgemv_("Transpose", &lastv, &lastc, &c_b15, &c__[c_offset], ldc, &
v[1], incv, &c_b29, &work[1], &c__1);
/* C(1:lastv,1:lastc) := C(...) - v(1:lastv,1) * w(1:lastc,1)' */
d__1 = -(*tau);
dger_(&lastv, &lastc, &d__1, &v[1], incv, &work[1], &c__1, &c__[
c_offset], ldc);
}
} else {
/* Form C * H */
if (lastv > 0) {
/* w(1:lastc,1) := C(1:lastc,1:lastv) * v(1:lastv,1) */
dgemv_("No transpose", &lastc, &lastv, &c_b15, &c__[c_offset],
ldc, &v[1], incv, &c_b29, &work[1], &c__1);
/* C(1:lastc,1:lastv) := C(...) - w(1:lastc,1) * v(1:lastv,1)' */
d__1 = -(*tau);
dger_(&lastc, &lastv, &d__1, &work[1], &c__1, &v[1], incv, &c__[
c_offset], ldc);
}
}
return 0;
/* End of DLARF */
} /* dlarf_ */
/* Subroutine */ int dlarfb_(char *side, char *trans, char *direct, char *
storev, integer *m, integer *n, integer *k, doublereal *v, integer *
ldv, doublereal *t, integer *ldt, doublereal *c__, integer *ldc,
doublereal *work, integer *ldwork)
{
/* System generated locals */
integer c_dim1, c_offset, t_dim1, t_offset, v_dim1, v_offset, work_dim1,
work_offset, i__1, i__2;
/* Local variables */
static integer i__, j;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
extern logical lsame_(char *, char *);
static integer lastc;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *), dtrmm_(char *, char *, char *, char *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *);
static integer lastv;
extern integer iladlc_(integer *, integer *, doublereal *, integer *),
iladlr_(integer *, integer *, doublereal *, integer *);
static char transt[1];
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLARFB applies a real block reflector H or its transpose H' to a
real m by n matrix C, from either the left or the right.
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': apply H or H' from the Left
= 'R': apply H or H' from the Right
TRANS (input) CHARACTER*1
= 'N': apply H (No transpose)
= 'T': apply H' (Transpose)
DIRECT (input) CHARACTER*1
Indicates how H is formed from a product of elementary
reflectors
= 'F': H = H(1) H(2) . . . H(k) (Forward)
= 'B': H = H(k) . . . H(2) H(1) (Backward)
STOREV (input) CHARACTER*1
Indicates how the vectors which define the elementary
reflectors are stored:
= 'C': Columnwise
= 'R': Rowwise
M (input) INTEGER
The number of rows of the matrix C.
N (input) INTEGER
The number of columns of the matrix C.
K (input) INTEGER
The order of the matrix T (= the number of elementary
reflectors whose product defines the block reflector).
V (input) DOUBLE PRECISION array, dimension
(LDV,K) if STOREV = 'C'
(LDV,M) if STOREV = 'R' and SIDE = 'L'
(LDV,N) if STOREV = 'R' and SIDE = 'R'
The matrix V. See further details.
LDV (input) INTEGER
The leading dimension of the array V.
If STOREV = 'C' and SIDE = 'L', LDV >= max(1,M);
if STOREV = 'C' and SIDE = 'R', LDV >= max(1,N);
if STOREV = 'R', LDV >= K.
T (input) DOUBLE PRECISION array, dimension (LDT,K)
The triangular k by k matrix T in the representation of the
block reflector.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= K.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the m by n matrix C.
On exit, C is overwritten by H*C or H'*C or C*H or C*H'.
LDC (input) INTEGER
The leading dimension of the array C. LDA >= max(1,M).
WORK (workspace) DOUBLE PRECISION array, dimension (LDWORK,K)
LDWORK (input) INTEGER
The leading dimension of the array WORK.
If SIDE = 'L', LDWORK >= max(1,N);
if SIDE = 'R', LDWORK >= max(1,M).
=====================================================================
Quick return if possible
*/
/* Parameter adjustments */
v_dim1 = *ldv;
v_offset = 1 + v_dim1;
v -= v_offset;
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
work_dim1 = *ldwork;
work_offset = 1 + work_dim1;
work -= work_offset;
/* Function Body */
if (*m <= 0 || *n <= 0) {
return 0;
}
if (lsame_(trans, "N")) {
*(unsigned char *)transt = 'T';
} else {
*(unsigned char *)transt = 'N';
}
if (lsame_(storev, "C")) {
if (lsame_(direct, "F")) {
/*
Let V = ( V1 ) (first K rows)
( V2 )
where V1 is unit lower triangular.
*/
if (lsame_(side, "L")) {
/*
Form H * C or H' * C where C = ( C1 )
( C2 )
Computing MAX
*/
i__1 = *k, i__2 = iladlr_(m, k, &v[v_offset], ldv);
lastv = max(i__1,i__2);
lastc = iladlc_(&lastv, n, &c__[c_offset], ldc);
/*
W := C' * V = (C1'*V1 + C2'*V2) (stored in WORK)
W := C1'
*/
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(&lastc, &c__[j + c_dim1], ldc, &work[j * work_dim1
+ 1], &c__1);
/* L10: */
}
/* W := W * V1 */
dtrmm_("Right", "Lower", "No transpose", "Unit", &lastc, k, &
c_b15, &v[v_offset], ldv, &work[work_offset], ldwork);
if (lastv > *k) {
/* W := W + C2'*V2 */
i__1 = lastv - *k;
dgemm_("Transpose", "No transpose", &lastc, k, &i__1, &
c_b15, &c__[*k + 1 + c_dim1], ldc, &v[*k + 1 +
v_dim1], ldv, &c_b15, &work[work_offset], ldwork);
}
/* W := W * T' or W * T */
dtrmm_("Right", "Upper", transt, "Non-unit", &lastc, k, &
c_b15, &t[t_offset], ldt, &work[work_offset], ldwork);
/* C := C - V * W' */
if (lastv > *k) {
/* C2 := C2 - V2 * W' */
i__1 = lastv - *k;
dgemm_("No transpose", "Transpose", &i__1, &lastc, k, &
c_b151, &v[*k + 1 + v_dim1], ldv, &work[
work_offset], ldwork, &c_b15, &c__[*k + 1 +
c_dim1], ldc);
}
/* W := W * V1' */
dtrmm_("Right", "Lower", "Transpose", "Unit", &lastc, k, &
c_b15, &v[v_offset], ldv, &work[work_offset], ldwork);
/* C1 := C1 - W' */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = lastc;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[j + i__ * c_dim1] -= work[i__ + j * work_dim1];
/* L20: */
}
/* L30: */
}
} else if (lsame_(side, "R")) {
/*
Form C * H or C * H' where C = ( C1 C2 )
Computing MAX
*/
i__1 = *k, i__2 = iladlr_(n, k, &v[v_offset], ldv);
lastv = max(i__1,i__2);
lastc = iladlr_(m, &lastv, &c__[c_offset], ldc);
/*
W := C * V = (C1*V1 + C2*V2) (stored in WORK)
W := C1
*/
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(&lastc, &c__[j * c_dim1 + 1], &c__1, &work[j *
work_dim1 + 1], &c__1);
/* L40: */
}
/* W := W * V1 */
dtrmm_("Right", "Lower", "No transpose", "Unit", &lastc, k, &
c_b15, &v[v_offset], ldv, &work[work_offset], ldwork);
if (lastv > *k) {
/* W := W + C2 * V2 */
i__1 = lastv - *k;
dgemm_("No transpose", "No transpose", &lastc, k, &i__1, &
c_b15, &c__[(*k + 1) * c_dim1 + 1], ldc, &v[*k +
1 + v_dim1], ldv, &c_b15, &work[work_offset],
ldwork);
}
/* W := W * T or W * T' */
dtrmm_("Right", "Upper", trans, "Non-unit", &lastc, k, &c_b15,
&t[t_offset], ldt, &work[work_offset], ldwork);
/* C := C - W * V' */
if (lastv > *k) {
/* C2 := C2 - W * V2' */
i__1 = lastv - *k;
dgemm_("No transpose", "Transpose", &lastc, &i__1, k, &
c_b151, &work[work_offset], ldwork, &v[*k + 1 +
v_dim1], ldv, &c_b15, &c__[(*k + 1) * c_dim1 + 1],
ldc);
}
/* W := W * V1' */
dtrmm_("Right", "Lower", "Transpose", "Unit", &lastc, k, &
c_b15, &v[v_offset], ldv, &work[work_offset], ldwork);
/* C1 := C1 - W */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = lastc;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] -= work[i__ + j * work_dim1];
/* L50: */
}
/* L60: */
}
}
} else {
/*
Let V = ( V1 )
( V2 ) (last K rows)
where V2 is unit upper triangular.
*/
if (lsame_(side, "L")) {
/*
Form H * C or H' * C where C = ( C1 )
( C2 )
Computing MAX
*/
i__1 = *k, i__2 = iladlr_(m, k, &v[v_offset], ldv);
lastv = max(i__1,i__2);
lastc = iladlc_(&lastv, n, &c__[c_offset], ldc);
/*
W := C' * V = (C1'*V1 + C2'*V2) (stored in WORK)
W := C2'
*/
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(&lastc, &c__[lastv - *k + j + c_dim1], ldc, &work[
j * work_dim1 + 1], &c__1);
/* L70: */
}
/* W := W * V2 */
dtrmm_("Right", "Upper", "No transpose", "Unit", &lastc, k, &
c_b15, &v[lastv - *k + 1 + v_dim1], ldv, &work[
work_offset], ldwork);
if (lastv > *k) {
/* W := W + C1'*V1 */
i__1 = lastv - *k;
dgemm_("Transpose", "No transpose", &lastc, k, &i__1, &
c_b15, &c__[c_offset], ldc, &v[v_offset], ldv, &
c_b15, &work[work_offset], ldwork);
}
/* W := W * T' or W * T */
dtrmm_("Right", "Lower", transt, "Non-unit", &lastc, k, &
c_b15, &t[t_offset], ldt, &work[work_offset], ldwork);
/* C := C - V * W' */
if (lastv > *k) {
/* C1 := C1 - V1 * W' */
i__1 = lastv - *k;
dgemm_("No transpose", "Transpose", &i__1, &lastc, k, &
c_b151, &v[v_offset], ldv, &work[work_offset],
ldwork, &c_b15, &c__[c_offset], ldc);
}
/* W := W * V2' */
dtrmm_("Right", "Upper", "Transpose", "Unit", &lastc, k, &
c_b15, &v[lastv - *k + 1 + v_dim1], ldv, &work[
work_offset], ldwork);
/* C2 := C2 - W' */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = lastc;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[lastv - *k + j + i__ * c_dim1] -= work[i__ + j *
work_dim1];
/* L80: */
}
/* L90: */
}
} else if (lsame_(side, "R")) {
/*
Form C * H or C * H' where C = ( C1 C2 )
Computing MAX
*/
i__1 = *k, i__2 = iladlr_(n, k, &v[v_offset], ldv);
lastv = max(i__1,i__2);
lastc = iladlr_(m, &lastv, &c__[c_offset], ldc);
/*
W := C * V = (C1*V1 + C2*V2) (stored in WORK)
W := C2
*/
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(&lastc, &c__[(*n - *k + j) * c_dim1 + 1], &c__1, &
work[j * work_dim1 + 1], &c__1);
/* L100: */
}
/* W := W * V2 */
dtrmm_("Right", "Upper", "No transpose", "Unit", &lastc, k, &
c_b15, &v[lastv - *k + 1 + v_dim1], ldv, &work[
work_offset], ldwork);
if (lastv > *k) {
/* W := W + C1 * V1 */
i__1 = lastv - *k;
dgemm_("No transpose", "No transpose", &lastc, k, &i__1, &
c_b15, &c__[c_offset], ldc, &v[v_offset], ldv, &
c_b15, &work[work_offset], ldwork);
}
/* W := W * T or W * T' */
dtrmm_("Right", "Lower", trans, "Non-unit", &lastc, k, &c_b15,
&t[t_offset], ldt, &work[work_offset], ldwork);
/* C := C - W * V' */
if (lastv > *k) {
/* C1 := C1 - W * V1' */
i__1 = lastv - *k;
dgemm_("No transpose", "Transpose", &lastc, &i__1, k, &
c_b151, &work[work_offset], ldwork, &v[v_offset],
ldv, &c_b15, &c__[c_offset], ldc);
}
/* W := W * V2' */
dtrmm_("Right", "Upper", "Transpose", "Unit", &lastc, k, &
c_b15, &v[lastv - *k + 1 + v_dim1], ldv, &work[
work_offset], ldwork);
/* C2 := C2 - W */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = lastc;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + (lastv - *k + j) * c_dim1] -= work[i__ + j *
work_dim1];
/* L110: */
}
/* L120: */
}
}
}
} else if (lsame_(storev, "R")) {
if (lsame_(direct, "F")) {
/*
Let V = ( V1 V2 ) (V1: first K columns)
where V1 is unit upper triangular.
*/
if (lsame_(side, "L")) {
/*
Form H * C or H' * C where C = ( C1 )
( C2 )
Computing MAX
*/
i__1 = *k, i__2 = iladlc_(k, m, &v[v_offset], ldv);
lastv = max(i__1,i__2);
lastc = iladlc_(&lastv, n, &c__[c_offset], ldc);
/*
W := C' * V' = (C1'*V1' + C2'*V2') (stored in WORK)
W := C1'
*/
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(&lastc, &c__[j + c_dim1], ldc, &work[j * work_dim1
+ 1], &c__1);
/* L130: */
}
/* W := W * V1' */
dtrmm_("Right", "Upper", "Transpose", "Unit", &lastc, k, &
c_b15, &v[v_offset], ldv, &work[work_offset], ldwork);
if (lastv > *k) {
/* W := W + C2'*V2' */
i__1 = lastv - *k;
dgemm_("Transpose", "Transpose", &lastc, k, &i__1, &c_b15,
&c__[*k + 1 + c_dim1], ldc, &v[(*k + 1) * v_dim1
+ 1], ldv, &c_b15, &work[work_offset], ldwork);
}
/* W := W * T' or W * T */
dtrmm_("Right", "Upper", transt, "Non-unit", &lastc, k, &
c_b15, &t[t_offset], ldt, &work[work_offset], ldwork);
/* C := C - V' * W' */
if (lastv > *k) {
/* C2 := C2 - V2' * W' */
i__1 = lastv - *k;
dgemm_("Transpose", "Transpose", &i__1, &lastc, k, &
c_b151, &v[(*k + 1) * v_dim1 + 1], ldv, &work[
work_offset], ldwork, &c_b15, &c__[*k + 1 +
c_dim1], ldc);
}
/* W := W * V1 */
dtrmm_("Right", "Upper", "No transpose", "Unit", &lastc, k, &
c_b15, &v[v_offset], ldv, &work[work_offset], ldwork);
/* C1 := C1 - W' */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = lastc;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[j + i__ * c_dim1] -= work[i__ + j * work_dim1];
/* L140: */
}
/* L150: */
}
} else if (lsame_(side, "R")) {
/*
Form C * H or C * H' where C = ( C1 C2 )
Computing MAX
*/
i__1 = *k, i__2 = iladlc_(k, n, &v[v_offset], ldv);
lastv = max(i__1,i__2);
lastc = iladlr_(m, &lastv, &c__[c_offset], ldc);
/*
W := C * V' = (C1*V1' + C2*V2') (stored in WORK)
W := C1
*/
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(&lastc, &c__[j * c_dim1 + 1], &c__1, &work[j *
work_dim1 + 1], &c__1);
/* L160: */
}
/* W := W * V1' */
dtrmm_("Right", "Upper", "Transpose", "Unit", &lastc, k, &
c_b15, &v[v_offset], ldv, &work[work_offset], ldwork);
if (lastv > *k) {
/* W := W + C2 * V2' */
i__1 = lastv - *k;
dgemm_("No transpose", "Transpose", &lastc, k, &i__1, &
c_b15, &c__[(*k + 1) * c_dim1 + 1], ldc, &v[(*k +
1) * v_dim1 + 1], ldv, &c_b15, &work[work_offset],
ldwork);
}
/* W := W * T or W * T' */
dtrmm_("Right", "Upper", trans, "Non-unit", &lastc, k, &c_b15,
&t[t_offset], ldt, &work[work_offset], ldwork);
/* C := C - W * V */
if (lastv > *k) {
/* C2 := C2 - W * V2 */
i__1 = lastv - *k;
dgemm_("No transpose", "No transpose", &lastc, &i__1, k, &
c_b151, &work[work_offset], ldwork, &v[(*k + 1) *
v_dim1 + 1], ldv, &c_b15, &c__[(*k + 1) * c_dim1
+ 1], ldc);
}
/* W := W * V1 */
dtrmm_("Right", "Upper", "No transpose", "Unit", &lastc, k, &
c_b15, &v[v_offset], ldv, &work[work_offset], ldwork);
/* C1 := C1 - W */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = lastc;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + j * c_dim1] -= work[i__ + j * work_dim1];
/* L170: */
}
/* L180: */
}
}
} else {
/*
Let V = ( V1 V2 ) (V2: last K columns)
where V2 is unit lower triangular.
*/
if (lsame_(side, "L")) {
/*
Form H * C or H' * C where C = ( C1 )
( C2 )
Computing MAX
*/
i__1 = *k, i__2 = iladlc_(k, m, &v[v_offset], ldv);
lastv = max(i__1,i__2);
lastc = iladlc_(&lastv, n, &c__[c_offset], ldc);
/*
W := C' * V' = (C1'*V1' + C2'*V2') (stored in WORK)
W := C2'
*/
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(&lastc, &c__[lastv - *k + j + c_dim1], ldc, &work[
j * work_dim1 + 1], &c__1);
/* L190: */
}
/* W := W * V2' */
dtrmm_("Right", "Lower", "Transpose", "Unit", &lastc, k, &
c_b15, &v[(lastv - *k + 1) * v_dim1 + 1], ldv, &work[
work_offset], ldwork);
if (lastv > *k) {
/* W := W + C1'*V1' */
i__1 = lastv - *k;
dgemm_("Transpose", "Transpose", &lastc, k, &i__1, &c_b15,
&c__[c_offset], ldc, &v[v_offset], ldv, &c_b15, &
work[work_offset], ldwork);
}
/* W := W * T' or W * T */
dtrmm_("Right", "Lower", transt, "Non-unit", &lastc, k, &
c_b15, &t[t_offset], ldt, &work[work_offset], ldwork);
/* C := C - V' * W' */
if (lastv > *k) {
/* C1 := C1 - V1' * W' */
i__1 = lastv - *k;
dgemm_("Transpose", "Transpose", &i__1, &lastc, k, &
c_b151, &v[v_offset], ldv, &work[work_offset],
ldwork, &c_b15, &c__[c_offset], ldc);
}
/* W := W * V2 */
dtrmm_("Right", "Lower", "No transpose", "Unit", &lastc, k, &
c_b15, &v[(lastv - *k + 1) * v_dim1 + 1], ldv, &work[
work_offset], ldwork);
/* C2 := C2 - W' */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = lastc;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[lastv - *k + j + i__ * c_dim1] -= work[i__ + j *
work_dim1];
/* L200: */
}
/* L210: */
}
} else if (lsame_(side, "R")) {
/*
Form C * H or C * H' where C = ( C1 C2 )
Computing MAX
*/
i__1 = *k, i__2 = iladlc_(k, n, &v[v_offset], ldv);
lastv = max(i__1,i__2);
lastc = iladlr_(m, &lastv, &c__[c_offset], ldc);
/*
W := C * V' = (C1*V1' + C2*V2') (stored in WORK)
W := C2
*/
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dcopy_(&lastc, &c__[(lastv - *k + j) * c_dim1 + 1], &c__1,
&work[j * work_dim1 + 1], &c__1);
/* L220: */
}
/* W := W * V2' */
dtrmm_("Right", "Lower", "Transpose", "Unit", &lastc, k, &
c_b15, &v[(lastv - *k + 1) * v_dim1 + 1], ldv, &work[
work_offset], ldwork);
if (lastv > *k) {
/* W := W + C1 * V1' */
i__1 = lastv - *k;
dgemm_("No transpose", "Transpose", &lastc, k, &i__1, &
c_b15, &c__[c_offset], ldc, &v[v_offset], ldv, &
c_b15, &work[work_offset], ldwork);
}
/* W := W * T or W * T' */
dtrmm_("Right", "Lower", trans, "Non-unit", &lastc, k, &c_b15,
&t[t_offset], ldt, &work[work_offset], ldwork);
/* C := C - W * V */
if (lastv > *k) {
/* C1 := C1 - W * V1 */
i__1 = lastv - *k;
dgemm_("No transpose", "No transpose", &lastc, &i__1, k, &
c_b151, &work[work_offset], ldwork, &v[v_offset],
ldv, &c_b15, &c__[c_offset], ldc);
}
/* W := W * V2 */
dtrmm_("Right", "Lower", "No transpose", "Unit", &lastc, k, &
c_b15, &v[(lastv - *k + 1) * v_dim1 + 1], ldv, &work[
work_offset], ldwork);
/* C1 := C1 - W */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
i__2 = lastc;
for (i__ = 1; i__ <= i__2; ++i__) {
c__[i__ + (lastv - *k + j) * c_dim1] -= work[i__ + j *
work_dim1];
/* L230: */
}
/* L240: */
}
}
}
}
return 0;
/* End of DLARFB */
} /* dlarfb_ */
/* Subroutine */ int dlarfg_(integer *n, doublereal *alpha, doublereal *x,
integer *incx, doublereal *tau)
{
/* System generated locals */
integer i__1;
doublereal d__1;
/* Local variables */
static integer j, knt;
static doublereal beta;
extern doublereal dnrm2_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
static doublereal xnorm;
static doublereal safmin, rsafmn;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLARFG generates a real elementary reflector H of order n, such
that
H * ( alpha ) = ( beta ), H' * H = I.
( x ) ( 0 )
where alpha and beta are scalars, and x is an (n-1)-element real
vector. H is represented in the form
H = I - tau * ( 1 ) * ( 1 v' ) ,
( v )
where tau is a real scalar and v is a real (n-1)-element
vector.
If the elements of x are all zero, then tau = 0 and H is taken to be
the unit matrix.
Otherwise 1 <= tau <= 2.
Arguments
=========
N (input) INTEGER
The order of the elementary reflector.
ALPHA (input/output) DOUBLE PRECISION
On entry, the value alpha.
On exit, it is overwritten with the value beta.
X (input/output) DOUBLE PRECISION array, dimension
(1+(N-2)*abs(INCX))
On entry, the vector x.
On exit, it is overwritten with the vector v.
INCX (input) INTEGER
The increment between elements of X. INCX > 0.
TAU (output) DOUBLE PRECISION
The value tau.
=====================================================================
*/
/* Parameter adjustments */
--x;
/* Function Body */
if (*n <= 1) {
*tau = 0.;
return 0;
}
i__1 = *n - 1;
xnorm = dnrm2_(&i__1, &x[1], incx);
if (xnorm == 0.) {
/* H = I */
*tau = 0.;
} else {
/* general case */
d__1 = dlapy2_(alpha, &xnorm);
beta = -d_sign(&d__1, alpha);
safmin = SAFEMINIMUM / EPSILON;
knt = 0;
if (abs(beta) < safmin) {
/* XNORM, BETA may be inaccurate; scale X and recompute them */
rsafmn = 1. / safmin;
L10:
++knt;
i__1 = *n - 1;
dscal_(&i__1, &rsafmn, &x[1], incx);
beta *= rsafmn;
*alpha *= rsafmn;
if (abs(beta) < safmin) {
goto L10;
}
/* New BETA is at most 1, at least SAFMIN */
i__1 = *n - 1;
xnorm = dnrm2_(&i__1, &x[1], incx);
d__1 = dlapy2_(alpha, &xnorm);
beta = -d_sign(&d__1, alpha);
}
*tau = (beta - *alpha) / beta;
i__1 = *n - 1;
d__1 = 1. / (*alpha - beta);
dscal_(&i__1, &d__1, &x[1], incx);
/* If ALPHA is subnormal, it may lose relative accuracy */
i__1 = knt;
for (j = 1; j <= i__1; ++j) {
beta *= safmin;
/* L20: */
}
*alpha = beta;
}
return 0;
/* End of DLARFG */
} /* dlarfg_ */
/* Subroutine */ int dlarft_(char *direct, char *storev, integer *n, integer *
k, doublereal *v, integer *ldv, doublereal *tau, doublereal *t,
integer *ldt)
{
/* System generated locals */
integer t_dim1, t_offset, v_dim1, v_offset, i__1, i__2, i__3;
doublereal d__1;
/* Local variables */
static integer i__, j, prevlastv;
static doublereal vii;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dgemv_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *);
static integer lastv;
extern /* Subroutine */ int dtrmv_(char *, char *, char *, integer *,
doublereal *, integer *, doublereal *, integer *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLARFT forms the triangular factor T of a real block reflector H
of order n, which is defined as a product of k elementary reflectors.
If DIRECT = 'F', H = H(1) H(2) . . . H(k) and T is upper triangular;
If DIRECT = 'B', H = H(k) . . . H(2) H(1) and T is lower triangular.
If STOREV = 'C', the vector which defines the elementary reflector
H(i) is stored in the i-th column of the array V, and
H = I - V * T * V'
If STOREV = 'R', the vector which defines the elementary reflector
H(i) is stored in the i-th row of the array V, and
H = I - V' * T * V
Arguments
=========
DIRECT (input) CHARACTER*1
Specifies the order in which the elementary reflectors are
multiplied to form the block reflector:
= 'F': H = H(1) H(2) . . . H(k) (Forward)
= 'B': H = H(k) . . . H(2) H(1) (Backward)
STOREV (input) CHARACTER*1
Specifies how the vectors which define the elementary
reflectors are stored (see also Further Details):
= 'C': columnwise
= 'R': rowwise
N (input) INTEGER
The order of the block reflector H. N >= 0.
K (input) INTEGER
The order of the triangular factor T (= the number of
elementary reflectors). K >= 1.
V (input/output) DOUBLE PRECISION array, dimension
(LDV,K) if STOREV = 'C'
(LDV,N) if STOREV = 'R'
The matrix V. See further details.
LDV (input) INTEGER
The leading dimension of the array V.
If STOREV = 'C', LDV >= max(1,N); if STOREV = 'R', LDV >= K.
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i).
T (output) DOUBLE PRECISION array, dimension (LDT,K)
The k by k triangular factor T of the block reflector.
If DIRECT = 'F', T is upper triangular; if DIRECT = 'B', T is
lower triangular. The rest of the array is not used.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= K.
Further Details
===============
The shape of the matrix V and the storage of the vectors which define
the H(i) is best illustrated by the following example with n = 5 and
k = 3. The elements equal to 1 are not stored; the corresponding
array elements are modified but restored on exit. The rest of the
array is not used.
DIRECT = 'F' and STOREV = 'C': DIRECT = 'F' and STOREV = 'R':
V = ( 1 ) V = ( 1 v1 v1 v1 v1 )
( v1 1 ) ( 1 v2 v2 v2 )
( v1 v2 1 ) ( 1 v3 v3 )
( v1 v2 v3 )
( v1 v2 v3 )
DIRECT = 'B' and STOREV = 'C': DIRECT = 'B' and STOREV = 'R':
V = ( v1 v2 v3 ) V = ( v1 v1 1 )
( v1 v2 v3 ) ( v2 v2 v2 1 )
( 1 v2 v3 ) ( v3 v3 v3 v3 1 )
( 1 v3 )
( 1 )
=====================================================================
Quick return if possible
*/
/* Parameter adjustments */
v_dim1 = *ldv;
v_offset = 1 + v_dim1;
v -= v_offset;
--tau;
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
/* Function Body */
if (*n == 0) {
return 0;
}
if (lsame_(direct, "F")) {
prevlastv = *n;
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
prevlastv = max(i__,prevlastv);
if (tau[i__] == 0.) {
/* H(i) = I */
i__2 = i__;
for (j = 1; j <= i__2; ++j) {
t[j + i__ * t_dim1] = 0.;
/* L10: */
}
} else {
/* general case */
vii = v[i__ + i__ * v_dim1];
v[i__ + i__ * v_dim1] = 1.;
if (lsame_(storev, "C")) {
/* Skip any trailing zeros. */
i__2 = i__ + 1;
for (lastv = *n; lastv >= i__2; --lastv) {
if (v[lastv + i__ * v_dim1] != 0.) {
goto L15;
}
}
L15:
j = min(lastv,prevlastv);
/* T(1:i-1,i) := - tau(i) * V(i:j,1:i-1)' * V(i:j,i) */
i__2 = j - i__ + 1;
i__3 = i__ - 1;
d__1 = -tau[i__];
dgemv_("Transpose", &i__2, &i__3, &d__1, &v[i__ + v_dim1],
ldv, &v[i__ + i__ * v_dim1], &c__1, &c_b29, &t[
i__ * t_dim1 + 1], &c__1);
} else {
/* Skip any trailing zeros. */
i__2 = i__ + 1;
for (lastv = *n; lastv >= i__2; --lastv) {
if (v[i__ + lastv * v_dim1] != 0.) {
goto L16;
}
}
L16:
j = min(lastv,prevlastv);
/* T(1:i-1,i) := - tau(i) * V(1:i-1,i:j) * V(i,i:j)' */
i__2 = i__ - 1;
i__3 = j - i__ + 1;
d__1 = -tau[i__];
dgemv_("No transpose", &i__2, &i__3, &d__1, &v[i__ *
v_dim1 + 1], ldv, &v[i__ + i__ * v_dim1], ldv, &
c_b29, &t[i__ * t_dim1 + 1], &c__1);
}
v[i__ + i__ * v_dim1] = vii;
/* T(1:i-1,i) := T(1:i-1,1:i-1) * T(1:i-1,i) */
i__2 = i__ - 1;
dtrmv_("Upper", "No transpose", "Non-unit", &i__2, &t[
t_offset], ldt, &t[i__ * t_dim1 + 1], &c__1);
t[i__ + i__ * t_dim1] = tau[i__];
if (i__ > 1) {
prevlastv = max(prevlastv,lastv);
} else {
prevlastv = lastv;
}
}
/* L20: */
}
} else {
prevlastv = 1;
for (i__ = *k; i__ >= 1; --i__) {
if (tau[i__] == 0.) {
/* H(i) = I */
i__1 = *k;
for (j = i__; j <= i__1; ++j) {
t[j + i__ * t_dim1] = 0.;
/* L30: */
}
} else {
/* general case */
if (i__ < *k) {
if (lsame_(storev, "C")) {
vii = v[*n - *k + i__ + i__ * v_dim1];
v[*n - *k + i__ + i__ * v_dim1] = 1.;
/* Skip any leading zeros. */
i__1 = i__ - 1;
for (lastv = 1; lastv <= i__1; ++lastv) {
if (v[lastv + i__ * v_dim1] != 0.) {
goto L35;
}
}
L35:
j = max(lastv,prevlastv);
/*
T(i+1:k,i) :=
- tau(i) * V(j:n-k+i,i+1:k)' * V(j:n-k+i,i)
*/
i__1 = *n - *k + i__ - j + 1;
i__2 = *k - i__;
d__1 = -tau[i__];
dgemv_("Transpose", &i__1, &i__2, &d__1, &v[j + (i__
+ 1) * v_dim1], ldv, &v[j + i__ * v_dim1], &
c__1, &c_b29, &t[i__ + 1 + i__ * t_dim1], &
c__1);
v[*n - *k + i__ + i__ * v_dim1] = vii;
} else {
vii = v[i__ + (*n - *k + i__) * v_dim1];
v[i__ + (*n - *k + i__) * v_dim1] = 1.;
/* Skip any leading zeros. */
i__1 = i__ - 1;
for (lastv = 1; lastv <= i__1; ++lastv) {
if (v[i__ + lastv * v_dim1] != 0.) {
goto L36;
}
}
L36:
j = max(lastv,prevlastv);
/*
T(i+1:k,i) :=
- tau(i) * V(i+1:k,j:n-k+i) * V(i,j:n-k+i)'
*/
i__1 = *k - i__;
i__2 = *n - *k + i__ - j + 1;
d__1 = -tau[i__];
dgemv_("No transpose", &i__1, &i__2, &d__1, &v[i__ +
1 + j * v_dim1], ldv, &v[i__ + j * v_dim1],
ldv, &c_b29, &t[i__ + 1 + i__ * t_dim1], &
c__1);
v[i__ + (*n - *k + i__) * v_dim1] = vii;
}
/* T(i+1:k,i) := T(i+1:k,i+1:k) * T(i+1:k,i) */
i__1 = *k - i__;
dtrmv_("Lower", "No transpose", "Non-unit", &i__1, &t[i__
+ 1 + (i__ + 1) * t_dim1], ldt, &t[i__ + 1 + i__ *
t_dim1], &c__1)
;
if (i__ > 1) {
prevlastv = min(prevlastv,lastv);
} else {
prevlastv = lastv;
}
}
t[i__ + i__ * t_dim1] = tau[i__];
}
/* L40: */
}
}
return 0;
/* End of DLARFT */
} /* dlarft_ */
/* Subroutine */ int dlarfx_(char *side, integer *m, integer *n, doublereal *
v, doublereal *tau, doublereal *c__, integer *ldc, doublereal *work)
{
/* System generated locals */
integer c_dim1, c_offset, i__1;
/* Local variables */
static integer j;
static doublereal t1, t2, t3, t4, t5, t6, t7, t8, t9, v1, v2, v3, v4, v5,
v6, v7, v8, v9, t10, v10, sum;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *);
extern logical lsame_(char *, char *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLARFX applies a real elementary reflector H to a real m by n
matrix C, from either the left or the right. H is represented in the
form
H = I - tau * v * v'
where tau is a real scalar and v is a real vector.
If tau = 0, then H is taken to be the unit matrix
This version uses inline code if H has order < 11.
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': form H * C
= 'R': form C * H
M (input) INTEGER
The number of rows of the matrix C.
N (input) INTEGER
The number of columns of the matrix C.
V (input) DOUBLE PRECISION array, dimension (M) if SIDE = 'L'
or (N) if SIDE = 'R'
The vector v in the representation of H.
TAU (input) DOUBLE PRECISION
The value tau in the representation of H.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the m by n matrix C.
On exit, C is overwritten by the matrix H * C if SIDE = 'L',
or C * H if SIDE = 'R'.
LDC (input) INTEGER
The leading dimension of the array C. LDA >= (1,M).
WORK (workspace) DOUBLE PRECISION array, dimension
(N) if SIDE = 'L'
or (M) if SIDE = 'R'
WORK is not referenced if H has order < 11.
=====================================================================
*/
/* Parameter adjustments */
--v;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
if (*tau == 0.) {
return 0;
}
if (lsame_(side, "L")) {
/* Form H * C, where H has order m. */
switch (*m) {
case 1: goto L10;
case 2: goto L30;
case 3: goto L50;
case 4: goto L70;
case 5: goto L90;
case 6: goto L110;
case 7: goto L130;
case 8: goto L150;
case 9: goto L170;
case 10: goto L190;
}
/* Code for general M */
dlarf_(side, m, n, &v[1], &c__1, tau, &c__[c_offset], ldc, &work[1]);
goto L410;
L10:
/* Special code for 1 x 1 Householder */
t1 = 1. - *tau * v[1] * v[1];
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
c__[j * c_dim1 + 1] = t1 * c__[j * c_dim1 + 1];
/* L20: */
}
goto L410;
L30:
/* Special code for 2 x 2 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2];
c__[j * c_dim1 + 1] -= sum * t1;
c__[j * c_dim1 + 2] -= sum * t2;
/* L40: */
}
goto L410;
L50:
/* Special code for 3 x 3 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 *
c__[j * c_dim1 + 3];
c__[j * c_dim1 + 1] -= sum * t1;
c__[j * c_dim1 + 2] -= sum * t2;
c__[j * c_dim1 + 3] -= sum * t3;
/* L60: */
}
goto L410;
L70:
/* Special code for 4 x 4 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 *
c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4];
c__[j * c_dim1 + 1] -= sum * t1;
c__[j * c_dim1 + 2] -= sum * t2;
c__[j * c_dim1 + 3] -= sum * t3;
c__[j * c_dim1 + 4] -= sum * t4;
/* L80: */
}
goto L410;
L90:
/* Special code for 5 x 5 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 *
c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[
j * c_dim1 + 5];
c__[j * c_dim1 + 1] -= sum * t1;
c__[j * c_dim1 + 2] -= sum * t2;
c__[j * c_dim1 + 3] -= sum * t3;
c__[j * c_dim1 + 4] -= sum * t4;
c__[j * c_dim1 + 5] -= sum * t5;
/* L100: */
}
goto L410;
L110:
/* Special code for 6 x 6 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 *
c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[
j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6];
c__[j * c_dim1 + 1] -= sum * t1;
c__[j * c_dim1 + 2] -= sum * t2;
c__[j * c_dim1 + 3] -= sum * t3;
c__[j * c_dim1 + 4] -= sum * t4;
c__[j * c_dim1 + 5] -= sum * t5;
c__[j * c_dim1 + 6] -= sum * t6;
/* L120: */
}
goto L410;
L130:
/* Special code for 7 x 7 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
v7 = v[7];
t7 = *tau * v7;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 *
c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[
j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6] + v7 * c__[j *
c_dim1 + 7];
c__[j * c_dim1 + 1] -= sum * t1;
c__[j * c_dim1 + 2] -= sum * t2;
c__[j * c_dim1 + 3] -= sum * t3;
c__[j * c_dim1 + 4] -= sum * t4;
c__[j * c_dim1 + 5] -= sum * t5;
c__[j * c_dim1 + 6] -= sum * t6;
c__[j * c_dim1 + 7] -= sum * t7;
/* L140: */
}
goto L410;
L150:
/* Special code for 8 x 8 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
v7 = v[7];
t7 = *tau * v7;
v8 = v[8];
t8 = *tau * v8;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 *
c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[
j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6] + v7 * c__[j *
c_dim1 + 7] + v8 * c__[j * c_dim1 + 8];
c__[j * c_dim1 + 1] -= sum * t1;
c__[j * c_dim1 + 2] -= sum * t2;
c__[j * c_dim1 + 3] -= sum * t3;
c__[j * c_dim1 + 4] -= sum * t4;
c__[j * c_dim1 + 5] -= sum * t5;
c__[j * c_dim1 + 6] -= sum * t6;
c__[j * c_dim1 + 7] -= sum * t7;
c__[j * c_dim1 + 8] -= sum * t8;
/* L160: */
}
goto L410;
L170:
/* Special code for 9 x 9 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
v7 = v[7];
t7 = *tau * v7;
v8 = v[8];
t8 = *tau * v8;
v9 = v[9];
t9 = *tau * v9;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 *
c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[
j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6] + v7 * c__[j *
c_dim1 + 7] + v8 * c__[j * c_dim1 + 8] + v9 * c__[j *
c_dim1 + 9];
c__[j * c_dim1 + 1] -= sum * t1;
c__[j * c_dim1 + 2] -= sum * t2;
c__[j * c_dim1 + 3] -= sum * t3;
c__[j * c_dim1 + 4] -= sum * t4;
c__[j * c_dim1 + 5] -= sum * t5;
c__[j * c_dim1 + 6] -= sum * t6;
c__[j * c_dim1 + 7] -= sum * t7;
c__[j * c_dim1 + 8] -= sum * t8;
c__[j * c_dim1 + 9] -= sum * t9;
/* L180: */
}
goto L410;
L190:
/* Special code for 10 x 10 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
v7 = v[7];
t7 = *tau * v7;
v8 = v[8];
t8 = *tau * v8;
v9 = v[9];
t9 = *tau * v9;
v10 = v[10];
t10 = *tau * v10;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j * c_dim1 + 1] + v2 * c__[j * c_dim1 + 2] + v3 *
c__[j * c_dim1 + 3] + v4 * c__[j * c_dim1 + 4] + v5 * c__[
j * c_dim1 + 5] + v6 * c__[j * c_dim1 + 6] + v7 * c__[j *
c_dim1 + 7] + v8 * c__[j * c_dim1 + 8] + v9 * c__[j *
c_dim1 + 9] + v10 * c__[j * c_dim1 + 10];
c__[j * c_dim1 + 1] -= sum * t1;
c__[j * c_dim1 + 2] -= sum * t2;
c__[j * c_dim1 + 3] -= sum * t3;
c__[j * c_dim1 + 4] -= sum * t4;
c__[j * c_dim1 + 5] -= sum * t5;
c__[j * c_dim1 + 6] -= sum * t6;
c__[j * c_dim1 + 7] -= sum * t7;
c__[j * c_dim1 + 8] -= sum * t8;
c__[j * c_dim1 + 9] -= sum * t9;
c__[j * c_dim1 + 10] -= sum * t10;
/* L200: */
}
goto L410;
} else {
/* Form C * H, where H has order n. */
switch (*n) {
case 1: goto L210;
case 2: goto L230;
case 3: goto L250;
case 4: goto L270;
case 5: goto L290;
case 6: goto L310;
case 7: goto L330;
case 8: goto L350;
case 9: goto L370;
case 10: goto L390;
}
/* Code for general N */
dlarf_(side, m, n, &v[1], &c__1, tau, &c__[c_offset], ldc, &work[1]);
goto L410;
L210:
/* Special code for 1 x 1 Householder */
t1 = 1. - *tau * v[1] * v[1];
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
c__[j + c_dim1] = t1 * c__[j + c_dim1];
/* L220: */
}
goto L410;
L230:
/* Special code for 2 x 2 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)];
c__[j + c_dim1] -= sum * t1;
c__[j + (c_dim1 << 1)] -= sum * t2;
/* L240: */
}
goto L410;
L250:
/* Special code for 3 x 3 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 *
c__[j + c_dim1 * 3];
c__[j + c_dim1] -= sum * t1;
c__[j + (c_dim1 << 1)] -= sum * t2;
c__[j + c_dim1 * 3] -= sum * t3;
/* L260: */
}
goto L410;
L270:
/* Special code for 4 x 4 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 *
c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)];
c__[j + c_dim1] -= sum * t1;
c__[j + (c_dim1 << 1)] -= sum * t2;
c__[j + c_dim1 * 3] -= sum * t3;
c__[j + (c_dim1 << 2)] -= sum * t4;
/* L280: */
}
goto L410;
L290:
/* Special code for 5 x 5 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 *
c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 *
c__[j + c_dim1 * 5];
c__[j + c_dim1] -= sum * t1;
c__[j + (c_dim1 << 1)] -= sum * t2;
c__[j + c_dim1 * 3] -= sum * t3;
c__[j + (c_dim1 << 2)] -= sum * t4;
c__[j + c_dim1 * 5] -= sum * t5;
/* L300: */
}
goto L410;
L310:
/* Special code for 6 x 6 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 *
c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 *
c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6];
c__[j + c_dim1] -= sum * t1;
c__[j + (c_dim1 << 1)] -= sum * t2;
c__[j + c_dim1 * 3] -= sum * t3;
c__[j + (c_dim1 << 2)] -= sum * t4;
c__[j + c_dim1 * 5] -= sum * t5;
c__[j + c_dim1 * 6] -= sum * t6;
/* L320: */
}
goto L410;
L330:
/* Special code for 7 x 7 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
v7 = v[7];
t7 = *tau * v7;
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 *
c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 *
c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6] + v7 * c__[
j + c_dim1 * 7];
c__[j + c_dim1] -= sum * t1;
c__[j + (c_dim1 << 1)] -= sum * t2;
c__[j + c_dim1 * 3] -= sum * t3;
c__[j + (c_dim1 << 2)] -= sum * t4;
c__[j + c_dim1 * 5] -= sum * t5;
c__[j + c_dim1 * 6] -= sum * t6;
c__[j + c_dim1 * 7] -= sum * t7;
/* L340: */
}
goto L410;
L350:
/* Special code for 8 x 8 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
v7 = v[7];
t7 = *tau * v7;
v8 = v[8];
t8 = *tau * v8;
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 *
c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 *
c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6] + v7 * c__[
j + c_dim1 * 7] + v8 * c__[j + (c_dim1 << 3)];
c__[j + c_dim1] -= sum * t1;
c__[j + (c_dim1 << 1)] -= sum * t2;
c__[j + c_dim1 * 3] -= sum * t3;
c__[j + (c_dim1 << 2)] -= sum * t4;
c__[j + c_dim1 * 5] -= sum * t5;
c__[j + c_dim1 * 6] -= sum * t6;
c__[j + c_dim1 * 7] -= sum * t7;
c__[j + (c_dim1 << 3)] -= sum * t8;
/* L360: */
}
goto L410;
L370:
/* Special code for 9 x 9 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
v7 = v[7];
t7 = *tau * v7;
v8 = v[8];
t8 = *tau * v8;
v9 = v[9];
t9 = *tau * v9;
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 *
c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 *
c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6] + v7 * c__[
j + c_dim1 * 7] + v8 * c__[j + (c_dim1 << 3)] + v9 * c__[
j + c_dim1 * 9];
c__[j + c_dim1] -= sum * t1;
c__[j + (c_dim1 << 1)] -= sum * t2;
c__[j + c_dim1 * 3] -= sum * t3;
c__[j + (c_dim1 << 2)] -= sum * t4;
c__[j + c_dim1 * 5] -= sum * t5;
c__[j + c_dim1 * 6] -= sum * t6;
c__[j + c_dim1 * 7] -= sum * t7;
c__[j + (c_dim1 << 3)] -= sum * t8;
c__[j + c_dim1 * 9] -= sum * t9;
/* L380: */
}
goto L410;
L390:
/* Special code for 10 x 10 Householder */
v1 = v[1];
t1 = *tau * v1;
v2 = v[2];
t2 = *tau * v2;
v3 = v[3];
t3 = *tau * v3;
v4 = v[4];
t4 = *tau * v4;
v5 = v[5];
t5 = *tau * v5;
v6 = v[6];
t6 = *tau * v6;
v7 = v[7];
t7 = *tau * v7;
v8 = v[8];
t8 = *tau * v8;
v9 = v[9];
t9 = *tau * v9;
v10 = v[10];
t10 = *tau * v10;
i__1 = *m;
for (j = 1; j <= i__1; ++j) {
sum = v1 * c__[j + c_dim1] + v2 * c__[j + (c_dim1 << 1)] + v3 *
c__[j + c_dim1 * 3] + v4 * c__[j + (c_dim1 << 2)] + v5 *
c__[j + c_dim1 * 5] + v6 * c__[j + c_dim1 * 6] + v7 * c__[
j + c_dim1 * 7] + v8 * c__[j + (c_dim1 << 3)] + v9 * c__[
j + c_dim1 * 9] + v10 * c__[j + c_dim1 * 10];
c__[j + c_dim1] -= sum * t1;
c__[j + (c_dim1 << 1)] -= sum * t2;
c__[j + c_dim1 * 3] -= sum * t3;
c__[j + (c_dim1 << 2)] -= sum * t4;
c__[j + c_dim1 * 5] -= sum * t5;
c__[j + c_dim1 * 6] -= sum * t6;
c__[j + c_dim1 * 7] -= sum * t7;
c__[j + (c_dim1 << 3)] -= sum * t8;
c__[j + c_dim1 * 9] -= sum * t9;
c__[j + c_dim1 * 10] -= sum * t10;
/* L400: */
}
goto L410;
}
L410:
return 0;
/* End of DLARFX */
} /* dlarfx_ */
/* Subroutine */ int dlartg_(doublereal *f, doublereal *g, doublereal *cs,
doublereal *sn, doublereal *r__)
{
/* System generated locals */
integer i__1;
doublereal d__1, d__2;
/* Local variables */
static integer i__;
static doublereal f1, g1, eps, scale;
static integer count;
static doublereal safmn2, safmx2;
static doublereal safmin;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLARTG generate a plane rotation so that
[ CS SN ] . [ F ] = [ R ] where CS**2 + SN**2 = 1.
[ -SN CS ] [ G ] [ 0 ]
This is a slower, more accurate version of the BLAS1 routine DROTG,
with the following other differences:
F and G are unchanged on return.
If G=0, then CS=1 and SN=0.
If F=0 and (G .ne. 0), then CS=0 and SN=1 without doing any
floating point operations (saves work in DBDSQR when
there are zeros on the diagonal).
If F exceeds G in magnitude, CS will be positive.
Arguments
=========
F (input) DOUBLE PRECISION
The first component of vector to be rotated.
G (input) DOUBLE PRECISION
The second component of vector to be rotated.
CS (output) DOUBLE PRECISION
The cosine of the rotation.
SN (output) DOUBLE PRECISION
The sine of the rotation.
R (output) DOUBLE PRECISION
The nonzero component of the rotated vector.
This version has a few statements commented out for thread safety
(machine parameters are computed on each entry). 10 feb 03, SJH.
=====================================================================
LOGICAL FIRST
SAVE FIRST, SAFMX2, SAFMIN, SAFMN2
DATA FIRST / .TRUE. /
IF( FIRST ) THEN
*/
safmin = SAFEMINIMUM;
eps = EPSILON;
d__1 = BASE;
i__1 = (integer) (log(safmin / eps) / log(BASE) / 2.);
safmn2 = pow_di(&d__1, &i__1);
safmx2 = 1. / safmn2;
/*
FIRST = .FALSE.
END IF
*/
if (*g == 0.) {
*cs = 1.;
*sn = 0.;
*r__ = *f;
} else if (*f == 0.) {
*cs = 0.;
*sn = 1.;
*r__ = *g;
} else {
f1 = *f;
g1 = *g;
/* Computing MAX */
d__1 = abs(f1), d__2 = abs(g1);
scale = max(d__1,d__2);
if (scale >= safmx2) {
count = 0;
L10:
++count;
f1 *= safmn2;
g1 *= safmn2;
/* Computing MAX */
d__1 = abs(f1), d__2 = abs(g1);
scale = max(d__1,d__2);
if (scale >= safmx2) {
goto L10;
}
/* Computing 2nd power */
d__1 = f1;
/* Computing 2nd power */
d__2 = g1;
*r__ = sqrt(d__1 * d__1 + d__2 * d__2);
*cs = f1 / *r__;
*sn = g1 / *r__;
i__1 = count;
for (i__ = 1; i__ <= i__1; ++i__) {
*r__ *= safmx2;
/* L20: */
}
} else if (scale <= safmn2) {
count = 0;
L30:
++count;
f1 *= safmx2;
g1 *= safmx2;
/* Computing MAX */
d__1 = abs(f1), d__2 = abs(g1);
scale = max(d__1,d__2);
if (scale <= safmn2) {
goto L30;
}
/* Computing 2nd power */
d__1 = f1;
/* Computing 2nd power */
d__2 = g1;
*r__ = sqrt(d__1 * d__1 + d__2 * d__2);
*cs = f1 / *r__;
*sn = g1 / *r__;
i__1 = count;
for (i__ = 1; i__ <= i__1; ++i__) {
*r__ *= safmn2;
/* L40: */
}
} else {
/* Computing 2nd power */
d__1 = f1;
/* Computing 2nd power */
d__2 = g1;
*r__ = sqrt(d__1 * d__1 + d__2 * d__2);
*cs = f1 / *r__;
*sn = g1 / *r__;
}
if (abs(*f) > abs(*g) && *cs < 0.) {
*cs = -(*cs);
*sn = -(*sn);
*r__ = -(*r__);
}
}
return 0;
/* End of DLARTG */
} /* dlartg_ */
/* Subroutine */ int dlas2_(doublereal *f, doublereal *g, doublereal *h__,
doublereal *ssmin, doublereal *ssmax)
{
/* System generated locals */
doublereal d__1, d__2;
/* Local variables */
static doublereal c__, fa, ga, ha, as, at, au, fhmn, fhmx;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAS2 computes the singular values of the 2-by-2 matrix
[ F G ]
[ 0 H ].
On return, SSMIN is the smaller singular value and SSMAX is the
larger singular value.
Arguments
=========
F (input) DOUBLE PRECISION
The (1,1) element of the 2-by-2 matrix.
G (input) DOUBLE PRECISION
The (1,2) element of the 2-by-2 matrix.
H (input) DOUBLE PRECISION
The (2,2) element of the 2-by-2 matrix.
SSMIN (output) DOUBLE PRECISION
The smaller singular value.
SSMAX (output) DOUBLE PRECISION
The larger singular value.
Further Details
===============
Barring over/underflow, all output quantities are correct to within
a few units in the last place (ulps), even in the absence of a guard
digit in addition/subtraction.
In IEEE arithmetic, the code works correctly if one matrix element is
infinite.
Overflow will not occur unless the largest singular value itself
overflows, or is within a few ulps of overflow. (On machines with
partial overflow, like the Cray, overflow may occur if the largest
singular value is within a factor of 2 of overflow.)
Underflow is harmless if underflow is gradual. Otherwise, results
may correspond to a matrix modified by perturbations of size near
the underflow threshold.
====================================================================
*/
fa = abs(*f);
ga = abs(*g);
ha = abs(*h__);
fhmn = min(fa,ha);
fhmx = max(fa,ha);
if (fhmn == 0.) {
*ssmin = 0.;
if (fhmx == 0.) {
*ssmax = ga;
} else {
/* Computing 2nd power */
d__1 = min(fhmx,ga) / max(fhmx,ga);
*ssmax = max(fhmx,ga) * sqrt(d__1 * d__1 + 1.);
}
} else {
if (ga < fhmx) {
as = fhmn / fhmx + 1.;
at = (fhmx - fhmn) / fhmx;
/* Computing 2nd power */
d__1 = ga / fhmx;
au = d__1 * d__1;
c__ = 2. / (sqrt(as * as + au) + sqrt(at * at + au));
*ssmin = fhmn * c__;
*ssmax = fhmx / c__;
} else {
au = fhmx / ga;
if (au == 0.) {
/*
Avoid possible harmful underflow if exponent range
asymmetric (true SSMIN may not underflow even if
AU underflows)
*/
*ssmin = fhmn * fhmx / ga;
*ssmax = ga;
} else {
as = fhmn / fhmx + 1.;
at = (fhmx - fhmn) / fhmx;
/* Computing 2nd power */
d__1 = as * au;
/* Computing 2nd power */
d__2 = at * au;
c__ = 1. / (sqrt(d__1 * d__1 + 1.) + sqrt(d__2 * d__2 + 1.));
*ssmin = fhmn * c__ * au;
*ssmin += *ssmin;
*ssmax = ga / (c__ + c__);
}
}
}
return 0;
/* End of DLAS2 */
} /* dlas2_ */
/* Subroutine */ int dlascl_(char *type__, integer *kl, integer *ku,
doublereal *cfrom, doublereal *cto, integer *m, integer *n,
doublereal *a, integer *lda, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4, i__5;
/* Local variables */
static integer i__, j, k1, k2, k3, k4;
static doublereal mul, cto1;
static logical done;
static doublereal ctoc;
extern logical lsame_(char *, char *);
static integer itype;
static doublereal cfrom1;
static doublereal cfromc;
extern logical disnan_(doublereal *);
extern /* Subroutine */ int xerbla_(char *, integer *);
static doublereal bignum, smlnum;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLASCL multiplies the M by N real matrix A by the real scalar
CTO/CFROM. This is done without over/underflow as long as the final
result CTO*A(I,J)/CFROM does not over/underflow. TYPE specifies that
A may be full, upper triangular, lower triangular, upper Hessenberg,
or banded.
Arguments
=========
TYPE (input) CHARACTER*1
TYPE indices the storage type of the input matrix.
= 'G': A is a full matrix.
= 'L': A is a lower triangular matrix.
= 'U': A is an upper triangular matrix.
= 'H': A is an upper Hessenberg matrix.
= 'B': A is a symmetric band matrix with lower bandwidth KL
and upper bandwidth KU and with the only the lower
half stored.
= 'Q': A is a symmetric band matrix with lower bandwidth KL
and upper bandwidth KU and with the only the upper
half stored.
= 'Z': A is a band matrix with lower bandwidth KL and upper
bandwidth KU.
KL (input) INTEGER
The lower bandwidth of A. Referenced only if TYPE = 'B',
'Q' or 'Z'.
KU (input) INTEGER
The upper bandwidth of A. Referenced only if TYPE = 'B',
'Q' or 'Z'.
CFROM (input) DOUBLE PRECISION
CTO (input) DOUBLE PRECISION
The matrix A is multiplied by CTO/CFROM. A(I,J) is computed
without over/underflow if the final result CTO*A(I,J)/CFROM
can be represented without over/underflow. CFROM must be
nonzero.
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
The matrix to be multiplied by CTO/CFROM. See TYPE for the
storage type.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
INFO (output) INTEGER
0 - successful exit
<0 - if INFO = -i, the i-th argument had an illegal value.
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
*info = 0;
if (lsame_(type__, "G")) {
itype = 0;
} else if (lsame_(type__, "L")) {
itype = 1;
} else if (lsame_(type__, "U")) {
itype = 2;
} else if (lsame_(type__, "H")) {
itype = 3;
} else if (lsame_(type__, "B")) {
itype = 4;
} else if (lsame_(type__, "Q")) {
itype = 5;
} else if (lsame_(type__, "Z")) {
itype = 6;
} else {
itype = -1;
}
if (itype == -1) {
*info = -1;
} else if (*cfrom == 0. || disnan_(cfrom)) {
*info = -4;
} else if (disnan_(cto)) {
*info = -5;
} else if (*m < 0) {
*info = -6;
} else if (*n < 0 || itype == 4 && *n != *m || itype == 5 && *n != *m) {
*info = -7;
} else if (itype <= 3 && *lda < max(1,*m)) {
*info = -9;
} else if (itype >= 4) {
/* Computing MAX */
i__1 = *m - 1;
if (*kl < 0 || *kl > max(i__1,0)) {
*info = -2;
} else /* if(complicated condition) */ {
/* Computing MAX */
i__1 = *n - 1;
if (*ku < 0 || *ku > max(i__1,0) || (itype == 4 || itype == 5) &&
*kl != *ku) {
*info = -3;
} else if (itype == 4 && *lda < *kl + 1 || itype == 5 && *lda < *
ku + 1 || itype == 6 && *lda < (*kl << 1) + *ku + 1) {
*info = -9;
}
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASCL", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0 || *m == 0) {
return 0;
}
/* Get machine parameters */
smlnum = SAFEMINIMUM;
bignum = 1. / smlnum;
cfromc = *cfrom;
ctoc = *cto;
L10:
cfrom1 = cfromc * smlnum;
if (cfrom1 == cfromc) {
/*
CFROMC is an inf. Multiply by a correctly signed zero for
finite CTOC, or a NaN if CTOC is infinite.
*/
mul = ctoc / cfromc;
done = TRUE_;
cto1 = ctoc;
} else {
cto1 = ctoc / bignum;
if (cto1 == ctoc) {
/*
CTOC is either 0 or an inf. In both cases, CTOC itself
serves as the correct multiplication factor.
*/
mul = ctoc;
done = TRUE_;
cfromc = 1.;
} else if (abs(cfrom1) > abs(ctoc) && ctoc != 0.) {
mul = smlnum;
done = FALSE_;
cfromc = cfrom1;
} else if (abs(cto1) > abs(cfromc)) {
mul = bignum;
done = FALSE_;
ctoc = cto1;
} else {
mul = ctoc / cfromc;
done = TRUE_;
}
}
if (itype == 0) {
/* Full matrix */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] *= mul;
/* L20: */
}
/* L30: */
}
} else if (itype == 1) {
/* Lower triangular matrix */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = j; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] *= mul;
/* L40: */
}
/* L50: */
}
} else if (itype == 2) {
/* Upper triangular matrix */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = min(j,*m);
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] *= mul;
/* L60: */
}
/* L70: */
}
} else if (itype == 3) {
/* Upper Hessenberg matrix */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
/* Computing MIN */
i__3 = j + 1;
i__2 = min(i__3,*m);
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] *= mul;
/* L80: */
}
/* L90: */
}
} else if (itype == 4) {
/* Lower half of a symmetric band matrix */
k3 = *kl + 1;
k4 = *n + 1;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
/* Computing MIN */
i__3 = k3, i__4 = k4 - j;
i__2 = min(i__3,i__4);
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] *= mul;
/* L100: */
}
/* L110: */
}
} else if (itype == 5) {
/* Upper half of a symmetric band matrix */
k1 = *ku + 2;
k3 = *ku + 1;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
/* Computing MAX */
i__2 = k1 - j;
i__3 = k3;
for (i__ = max(i__2,1); i__ <= i__3; ++i__) {
a[i__ + j * a_dim1] *= mul;
/* L120: */
}
/* L130: */
}
} else if (itype == 6) {
/* Band matrix */
k1 = *kl + *ku + 2;
k2 = *kl + 1;
k3 = (*kl << 1) + *ku + 1;
k4 = *kl + *ku + 1 + *m;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
/* Computing MAX */
i__3 = k1 - j;
/* Computing MIN */
i__4 = k3, i__5 = k4 - j;
i__2 = min(i__4,i__5);
for (i__ = max(i__3,k2); i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] *= mul;
/* L140: */
}
/* L150: */
}
}
if (! done) {
goto L10;
}
return 0;
/* End of DLASCL */
} /* dlascl_ */
/* Subroutine */ int dlasd0_(integer *n, integer *sqre, doublereal *d__,
doublereal *e, doublereal *u, integer *ldu, doublereal *vt, integer *
ldvt, integer *smlsiz, integer *iwork, doublereal *work, integer *
info)
{
/* System generated locals */
integer u_dim1, u_offset, vt_dim1, vt_offset, i__1, i__2;
/* Local variables */
static integer i__, j, m, i1, ic, lf, nd, ll, nl, nr, im1, ncc, nlf, nrf,
iwk, lvl, ndb1, nlp1, nrp1;
static doublereal beta;
static integer idxq, nlvl;
static doublereal alpha;
static integer inode, ndiml, idxqc, ndimr, itemp, sqrei;
extern /* Subroutine */ int dlasd1_(integer *, integer *, integer *,
doublereal *, doublereal *, doublereal *, doublereal *, integer *,
doublereal *, integer *, integer *, integer *, doublereal *,
integer *), dlasdq_(char *, integer *, integer *, integer *,
integer *, integer *, doublereal *, doublereal *, doublereal *,
integer *, doublereal *, integer *, doublereal *, integer *,
doublereal *, integer *), dlasdt_(integer *, integer *,
integer *, integer *, integer *, integer *, integer *), xerbla_(
char *, integer *);
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
Using a divide and conquer approach, DLASD0 computes the singular
value decomposition (SVD) of a real upper bidiagonal N-by-M
matrix B with diagonal D and offdiagonal E, where M = N + SQRE.
The algorithm computes orthogonal matrices U and VT such that
B = U * S * VT. The singular values S are overwritten on D.
A related subroutine, DLASDA, computes only the singular values,
and optionally, the singular vectors in compact form.
Arguments
=========
N (input) INTEGER
On entry, the row dimension of the upper bidiagonal matrix.
This is also the dimension of the main diagonal array D.
SQRE (input) INTEGER
Specifies the column dimension of the bidiagonal matrix.
= 0: The bidiagonal matrix has column dimension M = N;
= 1: The bidiagonal matrix has column dimension M = N+1;
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry D contains the main diagonal of the bidiagonal
matrix.
On exit D, if INFO = 0, contains its singular values.
E (input) DOUBLE PRECISION array, dimension (M-1)
Contains the subdiagonal entries of the bidiagonal matrix.
On exit, E has been destroyed.
U (output) DOUBLE PRECISION array, dimension at least (LDQ, N)
On exit, U contains the left singular vectors.
LDU (input) INTEGER
On entry, leading dimension of U.
VT (output) DOUBLE PRECISION array, dimension at least (LDVT, M)
On exit, VT' contains the right singular vectors.
LDVT (input) INTEGER
On entry, leading dimension of VT.
SMLSIZ (input) INTEGER
On entry, maximum size of the subproblems at the
bottom of the computation tree.
IWORK (workspace) INTEGER work array.
Dimension must be at least (8 * N)
WORK (workspace) DOUBLE PRECISION work array.
Dimension must be at least (3 * M**2 + 2 * M)
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, a singular value did not converge
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--e;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
vt_dim1 = *ldvt;
vt_offset = 1 + vt_dim1;
vt -= vt_offset;
--iwork;
--work;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -1;
} else if (*sqre < 0 || *sqre > 1) {
*info = -2;
}
m = *n + *sqre;
if (*ldu < *n) {
*info = -6;
} else if (*ldvt < m) {
*info = -8;
} else if (*smlsiz < 3) {
*info = -9;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASD0", &i__1);
return 0;
}
/* If the input matrix is too small, call DLASDQ to find the SVD. */
if (*n <= *smlsiz) {
dlasdq_("U", sqre, n, &m, n, &c__0, &d__[1], &e[1], &vt[vt_offset],
ldvt, &u[u_offset], ldu, &u[u_offset], ldu, &work[1], info);
return 0;
}
/* Set up the computation tree. */
inode = 1;
ndiml = inode + *n;
ndimr = ndiml + *n;
idxq = ndimr + *n;
iwk = idxq + *n;
dlasdt_(n, &nlvl, &nd, &iwork[inode], &iwork[ndiml], &iwork[ndimr],
smlsiz);
/*
For the nodes on bottom level of the tree, solve
their subproblems by DLASDQ.
*/
ndb1 = (nd + 1) / 2;
ncc = 0;
i__1 = nd;
for (i__ = ndb1; i__ <= i__1; ++i__) {
/*
IC : center row of each node
NL : number of rows of left subproblem
NR : number of rows of right subproblem
NLF: starting row of the left subproblem
NRF: starting row of the right subproblem
*/
i1 = i__ - 1;
ic = iwork[inode + i1];
nl = iwork[ndiml + i1];
nlp1 = nl + 1;
nr = iwork[ndimr + i1];
nrp1 = nr + 1;
nlf = ic - nl;
nrf = ic + 1;
sqrei = 1;
dlasdq_("U", &sqrei, &nl, &nlp1, &nl, &ncc, &d__[nlf], &e[nlf], &vt[
nlf + nlf * vt_dim1], ldvt, &u[nlf + nlf * u_dim1], ldu, &u[
nlf + nlf * u_dim1], ldu, &work[1], info);
if (*info != 0) {
return 0;
}
itemp = idxq + nlf - 2;
i__2 = nl;
for (j = 1; j <= i__2; ++j) {
iwork[itemp + j] = j;
/* L10: */
}
if (i__ == nd) {
sqrei = *sqre;
} else {
sqrei = 1;
}
nrp1 = nr + sqrei;
dlasdq_("U", &sqrei, &nr, &nrp1, &nr, &ncc, &d__[nrf], &e[nrf], &vt[
nrf + nrf * vt_dim1], ldvt, &u[nrf + nrf * u_dim1], ldu, &u[
nrf + nrf * u_dim1], ldu, &work[1], info);
if (*info != 0) {
return 0;
}
itemp = idxq + ic;
i__2 = nr;
for (j = 1; j <= i__2; ++j) {
iwork[itemp + j - 1] = j;
/* L20: */
}
/* L30: */
}
/* Now conquer each subproblem bottom-up. */
for (lvl = nlvl; lvl >= 1; --lvl) {
/*
Find the first node LF and last node LL on the
current level LVL.
*/
if (lvl == 1) {
lf = 1;
ll = 1;
} else {
i__1 = lvl - 1;
lf = pow_ii(&c__2, &i__1);
ll = (lf << 1) - 1;
}
i__1 = ll;
for (i__ = lf; i__ <= i__1; ++i__) {
im1 = i__ - 1;
ic = iwork[inode + im1];
nl = iwork[ndiml + im1];
nr = iwork[ndimr + im1];
nlf = ic - nl;
if (*sqre == 0 && i__ == ll) {
sqrei = *sqre;
} else {
sqrei = 1;
}
idxqc = idxq + nlf - 1;
alpha = d__[ic];
beta = e[ic];
dlasd1_(&nl, &nr, &sqrei, &d__[nlf], &alpha, &beta, &u[nlf + nlf *
u_dim1], ldu, &vt[nlf + nlf * vt_dim1], ldvt, &iwork[
idxqc], &iwork[iwk], &work[1], info);
if (*info != 0) {
return 0;
}
/* L40: */
}
/* L50: */
}
return 0;
/* End of DLASD0 */
} /* dlasd0_ */
/* Subroutine */ int dlasd1_(integer *nl, integer *nr, integer *sqre,
doublereal *d__, doublereal *alpha, doublereal *beta, doublereal *u,
integer *ldu, doublereal *vt, integer *ldvt, integer *idxq, integer *
iwork, doublereal *work, integer *info)
{
/* System generated locals */
integer u_dim1, u_offset, vt_dim1, vt_offset, i__1;
doublereal d__1, d__2;
/* Local variables */
static integer i__, k, m, n, n1, n2, iq, iz, iu2, ldq, idx, ldu2, ivt2,
idxc, idxp, ldvt2;
extern /* Subroutine */ int dlasd2_(integer *, integer *, integer *,
integer *, doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *, doublereal *, integer *, integer *,
integer *, integer *, integer *, integer *, integer *), dlasd3_(
integer *, integer *, integer *, integer *, doublereal *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *, integer *, integer *, doublereal *, integer *),
dlascl_(char *, integer *, integer *, doublereal *, doublereal *,
integer *, integer *, doublereal *, integer *, integer *),
dlamrg_(integer *, integer *, doublereal *, integer *, integer *,
integer *);
static integer isigma;
extern /* Subroutine */ int xerbla_(char *, integer *);
static doublereal orgnrm;
static integer coltyp;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLASD1 computes the SVD of an upper bidiagonal N-by-M matrix B,
where N = NL + NR + 1 and M = N + SQRE. DLASD1 is called from DLASD0.
A related subroutine DLASD7 handles the case in which the singular
values (and the singular vectors in factored form) are desired.
DLASD1 computes the SVD as follows:
( D1(in) 0 0 0 )
B = U(in) * ( Z1' a Z2' b ) * VT(in)
( 0 0 D2(in) 0 )
= U(out) * ( D(out) 0) * VT(out)
where Z' = (Z1' a Z2' b) = u' VT', and u is a vector of dimension M
with ALPHA and BETA in the NL+1 and NL+2 th entries and zeros
elsewhere; and the entry b is empty if SQRE = 0.
The left singular vectors of the original matrix are stored in U, and
the transpose of the right singular vectors are stored in VT, and the
singular values are in D. The algorithm consists of three stages:
The first stage consists of deflating the size of the problem
when there are multiple singular values or when there are zeros in
the Z vector. For each such occurence the dimension of the
secular equation problem is reduced by one. This stage is
performed by the routine DLASD2.
The second stage consists of calculating the updated
singular values. This is done by finding the square roots of the
roots of the secular equation via the routine DLASD4 (as called
by DLASD3). This routine also calculates the singular vectors of
the current problem.
The final stage consists of computing the updated singular vectors
directly using the updated singular values. The singular vectors
for the current problem are multiplied with the singular vectors
from the overall problem.
Arguments
=========
NL (input) INTEGER
The row dimension of the upper block. NL >= 1.
NR (input) INTEGER
The row dimension of the lower block. NR >= 1.
SQRE (input) INTEGER
= 0: the lower block is an NR-by-NR square matrix.
= 1: the lower block is an NR-by-(NR+1) rectangular matrix.
The bidiagonal matrix has row dimension N = NL + NR + 1,
and column dimension M = N + SQRE.
D (input/output) DOUBLE PRECISION array,
dimension (N = NL+NR+1).
On entry D(1:NL,1:NL) contains the singular values of the
upper block; and D(NL+2:N) contains the singular values of
the lower block. On exit D(1:N) contains the singular values
of the modified matrix.
ALPHA (input/output) DOUBLE PRECISION
Contains the diagonal element associated with the added row.
BETA (input/output) DOUBLE PRECISION
Contains the off-diagonal element associated with the added
row.
U (input/output) DOUBLE PRECISION array, dimension(LDU,N)
On entry U(1:NL, 1:NL) contains the left singular vectors of
the upper block; U(NL+2:N, NL+2:N) contains the left singular
vectors of the lower block. On exit U contains the left
singular vectors of the bidiagonal matrix.
LDU (input) INTEGER
The leading dimension of the array U. LDU >= max( 1, N ).
VT (input/output) DOUBLE PRECISION array, dimension(LDVT,M)
where M = N + SQRE.
On entry VT(1:NL+1, 1:NL+1)' contains the right singular
vectors of the upper block; VT(NL+2:M, NL+2:M)' contains
the right singular vectors of the lower block. On exit
VT' contains the right singular vectors of the
bidiagonal matrix.
LDVT (input) INTEGER
The leading dimension of the array VT. LDVT >= max( 1, M ).
IDXQ (output) INTEGER array, dimension(N)
This contains the permutation which will reintegrate the
subproblem just solved back into sorted order, i.e.
D( IDXQ( I = 1, N ) ) will be in ascending order.
IWORK (workspace) INTEGER array, dimension( 4 * N )
WORK (workspace) DOUBLE PRECISION array, dimension( 3*M**2 + 2*M )
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, a singular value did not converge
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
vt_dim1 = *ldvt;
vt_offset = 1 + vt_dim1;
vt -= vt_offset;
--idxq;
--iwork;
--work;
/* Function Body */
*info = 0;
if (*nl < 1) {
*info = -1;
} else if (*nr < 1) {
*info = -2;
} else if (*sqre < 0 || *sqre > 1) {
*info = -3;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASD1", &i__1);
return 0;
}
n = *nl + *nr + 1;
m = n + *sqre;
/*
The following values are for bookkeeping purposes only. They are
integer pointers which indicate the portion of the workspace
used by a particular array in DLASD2 and DLASD3.
*/
ldu2 = n;
ldvt2 = m;
iz = 1;
isigma = iz + m;
iu2 = isigma + n;
ivt2 = iu2 + ldu2 * n;
iq = ivt2 + ldvt2 * m;
idx = 1;
idxc = idx + n;
coltyp = idxc + n;
idxp = coltyp + n;
/*
Scale.
Computing MAX
*/
d__1 = abs(*alpha), d__2 = abs(*beta);
orgnrm = max(d__1,d__2);
d__[*nl + 1] = 0.;
i__1 = n;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((d__1 = d__[i__], abs(d__1)) > orgnrm) {
orgnrm = (d__1 = d__[i__], abs(d__1));
}
/* L10: */
}
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, &n, &c__1, &d__[1], &n, info);
*alpha /= orgnrm;
*beta /= orgnrm;
/* Deflate singular values. */
dlasd2_(nl, nr, sqre, &k, &d__[1], &work[iz], alpha, beta, &u[u_offset],
ldu, &vt[vt_offset], ldvt, &work[isigma], &work[iu2], &ldu2, &
work[ivt2], &ldvt2, &iwork[idxp], &iwork[idx], &iwork[idxc], &
idxq[1], &iwork[coltyp], info);
/* Solve Secular Equation and update singular vectors. */
ldq = k;
dlasd3_(nl, nr, sqre, &k, &d__[1], &work[iq], &ldq, &work[isigma], &u[
u_offset], ldu, &work[iu2], &ldu2, &vt[vt_offset], ldvt, &work[
ivt2], &ldvt2, &iwork[idxc], &iwork[coltyp], &work[iz], info);
if (*info != 0) {
return 0;
}
/* Unscale. */
dlascl_("G", &c__0, &c__0, &c_b15, &orgnrm, &n, &c__1, &d__[1], &n, info);
/* Prepare the IDXQ sorting permutation. */
n1 = k;
n2 = n - k;
dlamrg_(&n1, &n2, &d__[1], &c__1, &c_n1, &idxq[1]);
return 0;
/* End of DLASD1 */
} /* dlasd1_ */
/* Subroutine */ int dlasd2_(integer *nl, integer *nr, integer *sqre, integer
*k, doublereal *d__, doublereal *z__, doublereal *alpha, doublereal *
beta, doublereal *u, integer *ldu, doublereal *vt, integer *ldvt,
doublereal *dsigma, doublereal *u2, integer *ldu2, doublereal *vt2,
integer *ldvt2, integer *idxp, integer *idx, integer *idxc, integer *
idxq, integer *coltyp, integer *info)
{
/* System generated locals */
integer u_dim1, u_offset, u2_dim1, u2_offset, vt_dim1, vt_offset,
vt2_dim1, vt2_offset, i__1;
doublereal d__1, d__2;
/* Local variables */
static doublereal c__;
static integer i__, j, m, n;
static doublereal s;
static integer k2;
static doublereal z1;
static integer ct, jp;
static doublereal eps, tau, tol;
static integer psm[4], nlp1, nlp2, idxi, idxj;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *);
static integer ctot[4], idxjp;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static integer jprev;
extern /* Subroutine */ int dlamrg_(integer *, integer *, doublereal *,
integer *, integer *, integer *), dlacpy_(char *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *), dlaset_(char *, integer *, integer *, doublereal *,
doublereal *, doublereal *, integer *), xerbla_(char *,
integer *);
static doublereal hlftol;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLASD2 merges the two sets of singular values together into a single
sorted set. Then it tries to deflate the size of the problem.
There are two ways in which deflation can occur: when two or more
singular values are close together or if there is a tiny entry in the
Z vector. For each such occurrence the order of the related secular
equation problem is reduced by one.
DLASD2 is called from DLASD1.
Arguments
=========
NL (input) INTEGER
The row dimension of the upper block. NL >= 1.
NR (input) INTEGER
The row dimension of the lower block. NR >= 1.
SQRE (input) INTEGER
= 0: the lower block is an NR-by-NR square matrix.
= 1: the lower block is an NR-by-(NR+1) rectangular matrix.
The bidiagonal matrix has N = NL + NR + 1 rows and
M = N + SQRE >= N columns.
K (output) INTEGER
Contains the dimension of the non-deflated matrix,
This is the order of the related secular equation. 1 <= K <=N.
D (input/output) DOUBLE PRECISION array, dimension(N)
On entry D contains the singular values of the two submatrices
to be combined. On exit D contains the trailing (N-K) updated
singular values (those which were deflated) sorted into
increasing order.
Z (output) DOUBLE PRECISION array, dimension(N)
On exit Z contains the updating row vector in the secular
equation.
ALPHA (input) DOUBLE PRECISION
Contains the diagonal element associated with the added row.
BETA (input) DOUBLE PRECISION
Contains the off-diagonal element associated with the added
row.
U (input/output) DOUBLE PRECISION array, dimension(LDU,N)
On entry U contains the left singular vectors of two
submatrices in the two square blocks with corners at (1,1),
(NL, NL), and (NL+2, NL+2), (N,N).
On exit U contains the trailing (N-K) updated left singular
vectors (those which were deflated) in its last N-K columns.
LDU (input) INTEGER
The leading dimension of the array U. LDU >= N.
VT (input/output) DOUBLE PRECISION array, dimension(LDVT,M)
On entry VT' contains the right singular vectors of two
submatrices in the two square blocks with corners at (1,1),
(NL+1, NL+1), and (NL+2, NL+2), (M,M).
On exit VT' contains the trailing (N-K) updated right singular
vectors (those which were deflated) in its last N-K columns.
In case SQRE =1, the last row of VT spans the right null
space.
LDVT (input) INTEGER
The leading dimension of the array VT. LDVT >= M.
DSIGMA (output) DOUBLE PRECISION array, dimension (N)
Contains a copy of the diagonal elements (K-1 singular values
and one zero) in the secular equation.
U2 (output) DOUBLE PRECISION array, dimension(LDU2,N)
Contains a copy of the first K-1 left singular vectors which
will be used by DLASD3 in a matrix multiply (DGEMM) to solve
for the new left singular vectors. U2 is arranged into four
blocks. The first block contains a column with 1 at NL+1 and
zero everywhere else; the second block contains non-zero
entries only at and above NL; the third contains non-zero
entries only below NL+1; and the fourth is dense.
LDU2 (input) INTEGER
The leading dimension of the array U2. LDU2 >= N.
VT2 (output) DOUBLE PRECISION array, dimension(LDVT2,N)
VT2' contains a copy of the first K right singular vectors
which will be used by DLASD3 in a matrix multiply (DGEMM) to
solve for the new right singular vectors. VT2 is arranged into
three blocks. The first block contains a row that corresponds
to the special 0 diagonal element in SIGMA; the second block
contains non-zeros only at and before NL +1; the third block
contains non-zeros only at and after NL +2.
LDVT2 (input) INTEGER
The leading dimension of the array VT2. LDVT2 >= M.
IDXP (workspace) INTEGER array dimension(N)
This will contain the permutation used to place deflated
values of D at the end of the array. On output IDXP(2:K)
points to the nondeflated D-values and IDXP(K+1:N)
points to the deflated singular values.
IDX (workspace) INTEGER array dimension(N)
This will contain the permutation used to sort the contents of
D into ascending order.
IDXC (output) INTEGER array dimension(N)
This will contain the permutation used to arrange the columns
of the deflated U matrix into three groups: the first group
contains non-zero entries only at and above NL, the second
contains non-zero entries only below NL+2, and the third is
dense.
IDXQ (input/output) INTEGER array dimension(N)
This contains the permutation which separately sorts the two
sub-problems in D into ascending order. Note that entries in
the first hlaf of this permutation must first be moved one
position backward; and entries in the second half
must first have NL+1 added to their values.
COLTYP (workspace/output) INTEGER array dimension(N)
As workspace, this will contain a label which will indicate
which of the following types a column in the U2 matrix or a
row in the VT2 matrix is:
1 : non-zero in the upper half only
2 : non-zero in the lower half only
3 : dense
4 : deflated
On exit, it is an array of dimension 4, with COLTYP(I) being
the dimension of the I-th type columns.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--z__;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
vt_dim1 = *ldvt;
vt_offset = 1 + vt_dim1;
vt -= vt_offset;
--dsigma;
u2_dim1 = *ldu2;
u2_offset = 1 + u2_dim1;
u2 -= u2_offset;
vt2_dim1 = *ldvt2;
vt2_offset = 1 + vt2_dim1;
vt2 -= vt2_offset;
--idxp;
--idx;
--idxc;
--idxq;
--coltyp;
/* Function Body */
*info = 0;
if (*nl < 1) {
*info = -1;
} else if (*nr < 1) {
*info = -2;
} else if (*sqre != 1 && *sqre != 0) {
*info = -3;
}
n = *nl + *nr + 1;
m = n + *sqre;
if (*ldu < n) {
*info = -10;
} else if (*ldvt < m) {
*info = -12;
} else if (*ldu2 < n) {
*info = -15;
} else if (*ldvt2 < m) {
*info = -17;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASD2", &i__1);
return 0;
}
nlp1 = *nl + 1;
nlp2 = *nl + 2;
/*
Generate the first part of the vector Z; and move the singular
values in the first part of D one position backward.
*/
z1 = *alpha * vt[nlp1 + nlp1 * vt_dim1];
z__[1] = z1;
for (i__ = *nl; i__ >= 1; --i__) {
z__[i__ + 1] = *alpha * vt[i__ + nlp1 * vt_dim1];
d__[i__ + 1] = d__[i__];
idxq[i__ + 1] = idxq[i__] + 1;
/* L10: */
}
/* Generate the second part of the vector Z. */
i__1 = m;
for (i__ = nlp2; i__ <= i__1; ++i__) {
z__[i__] = *beta * vt[i__ + nlp2 * vt_dim1];
/* L20: */
}
/* Initialize some reference arrays. */
i__1 = nlp1;
for (i__ = 2; i__ <= i__1; ++i__) {
coltyp[i__] = 1;
/* L30: */
}
i__1 = n;
for (i__ = nlp2; i__ <= i__1; ++i__) {
coltyp[i__] = 2;
/* L40: */
}
/* Sort the singular values into increasing order */
i__1 = n;
for (i__ = nlp2; i__ <= i__1; ++i__) {
idxq[i__] += nlp1;
/* L50: */
}
/*
DSIGMA, IDXC, IDXC, and the first column of U2
are used as storage space.
*/
i__1 = n;
for (i__ = 2; i__ <= i__1; ++i__) {
dsigma[i__] = d__[idxq[i__]];
u2[i__ + u2_dim1] = z__[idxq[i__]];
idxc[i__] = coltyp[idxq[i__]];
/* L60: */
}
dlamrg_(nl, nr, &dsigma[2], &c__1, &c__1, &idx[2]);
i__1 = n;
for (i__ = 2; i__ <= i__1; ++i__) {
idxi = idx[i__] + 1;
d__[i__] = dsigma[idxi];
z__[i__] = u2[idxi + u2_dim1];
coltyp[i__] = idxc[idxi];
/* L70: */
}
/* Calculate the allowable deflation tolerance */
eps = EPSILON;
/* Computing MAX */
d__1 = abs(*alpha), d__2 = abs(*beta);
tol = max(d__1,d__2);
/* Computing MAX */
d__2 = (d__1 = d__[n], abs(d__1));
tol = eps * 8. * max(d__2,tol);
/*
There are 2 kinds of deflation -- first a value in the z-vector
is small, second two (or more) singular values are very close
together (their difference is small).
If the value in the z-vector is small, we simply permute the
array so that the corresponding singular value is moved to the
end.
If two values in the D-vector are close, we perform a two-sided
rotation designed to make one of the corresponding z-vector
entries zero, and then permute the array so that the deflated
singular value is moved to the end.
If there are multiple singular values then the problem deflates.
Here the number of equal singular values are found. As each equal
singular value is found, an elementary reflector is computed to
rotate the corresponding singular subspace so that the
corresponding components of Z are zero in this new basis.
*/
*k = 1;
k2 = n + 1;
i__1 = n;
for (j = 2; j <= i__1; ++j) {
if ((d__1 = z__[j], abs(d__1)) <= tol) {
/* Deflate due to small z component. */
--k2;
idxp[k2] = j;
coltyp[j] = 4;
if (j == n) {
goto L120;
}
} else {
jprev = j;
goto L90;
}
/* L80: */
}
L90:
j = jprev;
L100:
++j;
if (j > n) {
goto L110;
}
if ((d__1 = z__[j], abs(d__1)) <= tol) {
/* Deflate due to small z component. */
--k2;
idxp[k2] = j;
coltyp[j] = 4;
} else {
/* Check if singular values are close enough to allow deflation. */
if ((d__1 = d__[j] - d__[jprev], abs(d__1)) <= tol) {
/* Deflation is possible. */
s = z__[jprev];
c__ = z__[j];
/*
Find sqrt(a**2+b**2) without overflow or
destructive underflow.
*/
tau = dlapy2_(&c__, &s);
c__ /= tau;
s = -s / tau;
z__[j] = tau;
z__[jprev] = 0.;
/*
Apply back the Givens rotation to the left and right
singular vector matrices.
*/
idxjp = idxq[idx[jprev] + 1];
idxj = idxq[idx[j] + 1];
if (idxjp <= nlp1) {
--idxjp;
}
if (idxj <= nlp1) {
--idxj;
}
drot_(&n, &u[idxjp * u_dim1 + 1], &c__1, &u[idxj * u_dim1 + 1], &
c__1, &c__, &s);
drot_(&m, &vt[idxjp + vt_dim1], ldvt, &vt[idxj + vt_dim1], ldvt, &
c__, &s);
if (coltyp[j] != coltyp[jprev]) {
coltyp[j] = 3;
}
coltyp[jprev] = 4;
--k2;
idxp[k2] = jprev;
jprev = j;
} else {
++(*k);
u2[*k + u2_dim1] = z__[jprev];
dsigma[*k] = d__[jprev];
idxp[*k] = jprev;
jprev = j;
}
}
goto L100;
L110:
/* Record the last singular value. */
++(*k);
u2[*k + u2_dim1] = z__[jprev];
dsigma[*k] = d__[jprev];
idxp[*k] = jprev;
L120:
/*
Count up the total number of the various types of columns, then
form a permutation which positions the four column types into
four groups of uniform structure (although one or more of these
groups may be empty).
*/
for (j = 1; j <= 4; ++j) {
ctot[j - 1] = 0;
/* L130: */
}
i__1 = n;
for (j = 2; j <= i__1; ++j) {
ct = coltyp[j];
++ctot[ct - 1];
/* L140: */
}
/* PSM(*) = Position in SubMatrix (of types 1 through 4) */
psm[0] = 2;
psm[1] = ctot[0] + 2;
psm[2] = psm[1] + ctot[1];
psm[3] = psm[2] + ctot[2];
/*
Fill out the IDXC array so that the permutation which it induces
will place all type-1 columns first, all type-2 columns next,
then all type-3's, and finally all type-4's, starting from the
second column. This applies similarly to the rows of VT.
*/
i__1 = n;
for (j = 2; j <= i__1; ++j) {
jp = idxp[j];
ct = coltyp[jp];
idxc[psm[ct - 1]] = j;
++psm[ct - 1];
/* L150: */
}
/*
Sort the singular values and corresponding singular vectors into
DSIGMA, U2, and VT2 respectively. The singular values/vectors
which were not deflated go into the first K slots of DSIGMA, U2,
and VT2 respectively, while those which were deflated go into the
last N - K slots, except that the first column/row will be treated
separately.
*/
i__1 = n;
for (j = 2; j <= i__1; ++j) {
jp = idxp[j];
dsigma[j] = d__[jp];
idxj = idxq[idx[idxp[idxc[j]]] + 1];
if (idxj <= nlp1) {
--idxj;
}
dcopy_(&n, &u[idxj * u_dim1 + 1], &c__1, &u2[j * u2_dim1 + 1], &c__1);
dcopy_(&m, &vt[idxj + vt_dim1], ldvt, &vt2[j + vt2_dim1], ldvt2);
/* L160: */
}
/* Determine DSIGMA(1), DSIGMA(2) and Z(1) */
dsigma[1] = 0.;
hlftol = tol / 2.;
if (abs(dsigma[2]) <= hlftol) {
dsigma[2] = hlftol;
}
if (m > n) {
z__[1] = dlapy2_(&z1, &z__[m]);
if (z__[1] <= tol) {
c__ = 1.;
s = 0.;
z__[1] = tol;
} else {
c__ = z1 / z__[1];
s = z__[m] / z__[1];
}
} else {
if (abs(z1) <= tol) {
z__[1] = tol;
} else {
z__[1] = z1;
}
}
/* Move the rest of the updating row to Z. */
i__1 = *k - 1;
dcopy_(&i__1, &u2[u2_dim1 + 2], &c__1, &z__[2], &c__1);
/*
Determine the first column of U2, the first row of VT2 and the
last row of VT.
*/
dlaset_("A", &n, &c__1, &c_b29, &c_b29, &u2[u2_offset], ldu2);
u2[nlp1 + u2_dim1] = 1.;
if (m > n) {
i__1 = nlp1;
for (i__ = 1; i__ <= i__1; ++i__) {
vt[m + i__ * vt_dim1] = -s * vt[nlp1 + i__ * vt_dim1];
vt2[i__ * vt2_dim1 + 1] = c__ * vt[nlp1 + i__ * vt_dim1];
/* L170: */
}
i__1 = m;
for (i__ = nlp2; i__ <= i__1; ++i__) {
vt2[i__ * vt2_dim1 + 1] = s * vt[m + i__ * vt_dim1];
vt[m + i__ * vt_dim1] = c__ * vt[m + i__ * vt_dim1];
/* L180: */
}
} else {
dcopy_(&m, &vt[nlp1 + vt_dim1], ldvt, &vt2[vt2_dim1 + 1], ldvt2);
}
if (m > n) {
dcopy_(&m, &vt[m + vt_dim1], ldvt, &vt2[m + vt2_dim1], ldvt2);
}
/*
The deflated singular values and their corresponding vectors go
into the back of D, U, and V respectively.
*/
if (n > *k) {
i__1 = n - *k;
dcopy_(&i__1, &dsigma[*k + 1], &c__1, &d__[*k + 1], &c__1);
i__1 = n - *k;
dlacpy_("A", &n, &i__1, &u2[(*k + 1) * u2_dim1 + 1], ldu2, &u[(*k + 1)
* u_dim1 + 1], ldu);
i__1 = n - *k;
dlacpy_("A", &i__1, &m, &vt2[*k + 1 + vt2_dim1], ldvt2, &vt[*k + 1 +
vt_dim1], ldvt);
}
/* Copy CTOT into COLTYP for referencing in DLASD3. */
for (j = 1; j <= 4; ++j) {
coltyp[j] = ctot[j - 1];
/* L190: */
}
return 0;
/* End of DLASD2 */
} /* dlasd2_ */
/* Subroutine */ int dlasd3_(integer *nl, integer *nr, integer *sqre, integer
*k, doublereal *d__, doublereal *q, integer *ldq, doublereal *dsigma,
doublereal *u, integer *ldu, doublereal *u2, integer *ldu2,
doublereal *vt, integer *ldvt, doublereal *vt2, integer *ldvt2,
integer *idxc, integer *ctot, doublereal *z__, integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, u_dim1, u_offset, u2_dim1, u2_offset, vt_dim1,
vt_offset, vt2_dim1, vt2_offset, i__1, i__2;
doublereal d__1, d__2;
/* Local variables */
static integer i__, j, m, n, jc;
static doublereal rho;
static integer nlp1, nlp2, nrp1;
static doublereal temp;
extern doublereal dnrm2_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
static integer ctemp;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static integer ktemp;
extern doublereal dlamc3_(doublereal *, doublereal *);
extern /* Subroutine */ int dlasd4_(integer *, integer *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *), dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *), dlacpy_(char *, integer *, integer
*, doublereal *, integer *, doublereal *, integer *),
xerbla_(char *, integer *);
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLASD3 finds all the square roots of the roots of the secular
equation, as defined by the values in D and Z. It makes the
appropriate calls to DLASD4 and then updates the singular
vectors by matrix multiplication.
This code makes very mild assumptions about floating point
arithmetic. It will work on machines with a guard digit in
add/subtract, or on those binary machines without guard digits
which subtract like the Cray XMP, Cray YMP, Cray C 90, or Cray 2.
It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none.
DLASD3 is called from DLASD1.
Arguments
=========
NL (input) INTEGER
The row dimension of the upper block. NL >= 1.
NR (input) INTEGER
The row dimension of the lower block. NR >= 1.
SQRE (input) INTEGER
= 0: the lower block is an NR-by-NR square matrix.
= 1: the lower block is an NR-by-(NR+1) rectangular matrix.
The bidiagonal matrix has N = NL + NR + 1 rows and
M = N + SQRE >= N columns.
K (input) INTEGER
The size of the secular equation, 1 =< K = < N.
D (output) DOUBLE PRECISION array, dimension(K)
On exit the square roots of the roots of the secular equation,
in ascending order.
Q (workspace) DOUBLE PRECISION array,
dimension at least (LDQ,K).
LDQ (input) INTEGER
The leading dimension of the array Q. LDQ >= K.
DSIGMA (input) DOUBLE PRECISION array, dimension(K)
The first K elements of this array contain the old roots
of the deflated updating problem. These are the poles
of the secular equation.
U (output) DOUBLE PRECISION array, dimension (LDU, N)
The last N - K columns of this matrix contain the deflated
left singular vectors.
LDU (input) INTEGER
The leading dimension of the array U. LDU >= N.
U2 (input/output) DOUBLE PRECISION array, dimension (LDU2, N)
The first K columns of this matrix contain the non-deflated
left singular vectors for the split problem.
LDU2 (input) INTEGER
The leading dimension of the array U2. LDU2 >= N.
VT (output) DOUBLE PRECISION array, dimension (LDVT, M)
The last M - K columns of VT' contain the deflated
right singular vectors.
LDVT (input) INTEGER
The leading dimension of the array VT. LDVT >= N.
VT2 (input/output) DOUBLE PRECISION array, dimension (LDVT2, N)
The first K columns of VT2' contain the non-deflated
right singular vectors for the split problem.
LDVT2 (input) INTEGER
The leading dimension of the array VT2. LDVT2 >= N.
IDXC (input) INTEGER array, dimension ( N )
The permutation used to arrange the columns of U (and rows of
VT) into three groups: the first group contains non-zero
entries only at and above (or before) NL +1; the second
contains non-zero entries only at and below (or after) NL+2;
and the third is dense. The first column of U and the row of
VT are treated separately, however.
The rows of the singular vectors found by DLASD4
must be likewise permuted before the matrix multiplies can
take place.
CTOT (input) INTEGER array, dimension ( 4 )
A count of the total number of the various types of columns
in U (or rows in VT), as described in IDXC. The fourth column
type is any column which has been deflated.
Z (input) DOUBLE PRECISION array, dimension (K)
The first K elements of this array contain the components
of the deflation-adjusted updating row vector.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, a singular value did not converge
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
--dsigma;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
u2_dim1 = *ldu2;
u2_offset = 1 + u2_dim1;
u2 -= u2_offset;
vt_dim1 = *ldvt;
vt_offset = 1 + vt_dim1;
vt -= vt_offset;
vt2_dim1 = *ldvt2;
vt2_offset = 1 + vt2_dim1;
vt2 -= vt2_offset;
--idxc;
--ctot;
--z__;
/* Function Body */
*info = 0;
if (*nl < 1) {
*info = -1;
} else if (*nr < 1) {
*info = -2;
} else if (*sqre != 1 && *sqre != 0) {
*info = -3;
}
n = *nl + *nr + 1;
m = n + *sqre;
nlp1 = *nl + 1;
nlp2 = *nl + 2;
if (*k < 1 || *k > n) {
*info = -4;
} else if (*ldq < *k) {
*info = -7;
} else if (*ldu < n) {
*info = -10;
} else if (*ldu2 < n) {
*info = -12;
} else if (*ldvt < m) {
*info = -14;
} else if (*ldvt2 < m) {
*info = -16;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASD3", &i__1);
return 0;
}
/* Quick return if possible */
if (*k == 1) {
d__[1] = abs(z__[1]);
dcopy_(&m, &vt2[vt2_dim1 + 1], ldvt2, &vt[vt_dim1 + 1], ldvt);
if (z__[1] > 0.) {
dcopy_(&n, &u2[u2_dim1 + 1], &c__1, &u[u_dim1 + 1], &c__1);
} else {
i__1 = n;
for (i__ = 1; i__ <= i__1; ++i__) {
u[i__ + u_dim1] = -u2[i__ + u2_dim1];
/* L10: */
}
}
return 0;
}
/*
Modify values DSIGMA(i) to make sure all DSIGMA(i)-DSIGMA(j) can
be computed with high relative accuracy (barring over/underflow).
This is a problem on machines without a guard digit in
add/subtract (Cray XMP, Cray YMP, Cray C 90 and Cray 2).
The following code replaces DSIGMA(I) by 2*DSIGMA(I)-DSIGMA(I),
which on any of these machines zeros out the bottommost
bit of DSIGMA(I) if it is 1; this makes the subsequent
subtractions DSIGMA(I)-DSIGMA(J) unproblematic when cancellation
occurs. On binary machines with a guard digit (almost all
machines) it does not change DSIGMA(I) at all. On hexadecimal
and decimal machines with a guard digit, it slightly
changes the bottommost bits of DSIGMA(I). It does not account
for hexadecimal or decimal machines without guard digits
(we know of none). We use a subroutine call to compute
2*DSIGMA(I) to prevent optimizing compilers from eliminating
this code.
*/
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
dsigma[i__] = dlamc3_(&dsigma[i__], &dsigma[i__]) - dsigma[i__];
/* L20: */
}
/* Keep a copy of Z. */
dcopy_(k, &z__[1], &c__1, &q[q_offset], &c__1);
/* Normalize Z. */
rho = dnrm2_(k, &z__[1], &c__1);
dlascl_("G", &c__0, &c__0, &rho, &c_b15, k, &c__1, &z__[1], k, info);
rho *= rho;
/* Find the new singular values. */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dlasd4_(k, &j, &dsigma[1], &z__[1], &u[j * u_dim1 + 1], &rho, &d__[j],
&vt[j * vt_dim1 + 1], info);
/* If the zero finder fails, the computation is terminated. */
if (*info != 0) {
return 0;
}
/* L30: */
}
/* Compute updated Z. */
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
z__[i__] = u[i__ + *k * u_dim1] * vt[i__ + *k * vt_dim1];
i__2 = i__ - 1;
for (j = 1; j <= i__2; ++j) {
z__[i__] *= u[i__ + j * u_dim1] * vt[i__ + j * vt_dim1] / (dsigma[
i__] - dsigma[j]) / (dsigma[i__] + dsigma[j]);
/* L40: */
}
i__2 = *k - 1;
for (j = i__; j <= i__2; ++j) {
z__[i__] *= u[i__ + j * u_dim1] * vt[i__ + j * vt_dim1] / (dsigma[
i__] - dsigma[j + 1]) / (dsigma[i__] + dsigma[j + 1]);
/* L50: */
}
d__2 = sqrt((d__1 = z__[i__], abs(d__1)));
z__[i__] = d_sign(&d__2, &q[i__ + q_dim1]);
/* L60: */
}
/*
Compute left singular vectors of the modified diagonal matrix,
and store related information for the right singular vectors.
*/
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
vt[i__ * vt_dim1 + 1] = z__[1] / u[i__ * u_dim1 + 1] / vt[i__ *
vt_dim1 + 1];
u[i__ * u_dim1 + 1] = -1.;
i__2 = *k;
for (j = 2; j <= i__2; ++j) {
vt[j + i__ * vt_dim1] = z__[j] / u[j + i__ * u_dim1] / vt[j + i__
* vt_dim1];
u[j + i__ * u_dim1] = dsigma[j] * vt[j + i__ * vt_dim1];
/* L70: */
}
temp = dnrm2_(k, &u[i__ * u_dim1 + 1], &c__1);
q[i__ * q_dim1 + 1] = u[i__ * u_dim1 + 1] / temp;
i__2 = *k;
for (j = 2; j <= i__2; ++j) {
jc = idxc[j];
q[j + i__ * q_dim1] = u[jc + i__ * u_dim1] / temp;
/* L80: */
}
/* L90: */
}
/* Update the left singular vector matrix. */
if (*k == 2) {
dgemm_("N", "N", &n, k, k, &c_b15, &u2[u2_offset], ldu2, &q[q_offset],
ldq, &c_b29, &u[u_offset], ldu);
goto L100;
}
if (ctot[1] > 0) {
dgemm_("N", "N", nl, k, &ctot[1], &c_b15, &u2[(u2_dim1 << 1) + 1],
ldu2, &q[q_dim1 + 2], ldq, &c_b29, &u[u_dim1 + 1], ldu);
if (ctot[3] > 0) {
ktemp = ctot[1] + 2 + ctot[2];
dgemm_("N", "N", nl, k, &ctot[3], &c_b15, &u2[ktemp * u2_dim1 + 1]
, ldu2, &q[ktemp + q_dim1], ldq, &c_b15, &u[u_dim1 + 1],
ldu);
}
} else if (ctot[3] > 0) {
ktemp = ctot[1] + 2 + ctot[2];
dgemm_("N", "N", nl, k, &ctot[3], &c_b15, &u2[ktemp * u2_dim1 + 1],
ldu2, &q[ktemp + q_dim1], ldq, &c_b29, &u[u_dim1 + 1], ldu);
} else {
dlacpy_("F", nl, k, &u2[u2_offset], ldu2, &u[u_offset], ldu);
}
dcopy_(k, &q[q_dim1 + 1], ldq, &u[nlp1 + u_dim1], ldu);
ktemp = ctot[1] + 2;
ctemp = ctot[2] + ctot[3];
dgemm_("N", "N", nr, k, &ctemp, &c_b15, &u2[nlp2 + ktemp * u2_dim1], ldu2,
&q[ktemp + q_dim1], ldq, &c_b29, &u[nlp2 + u_dim1], ldu);
/* Generate the right singular vectors. */
L100:
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
temp = dnrm2_(k, &vt[i__ * vt_dim1 + 1], &c__1);
q[i__ + q_dim1] = vt[i__ * vt_dim1 + 1] / temp;
i__2 = *k;
for (j = 2; j <= i__2; ++j) {
jc = idxc[j];
q[i__ + j * q_dim1] = vt[jc + i__ * vt_dim1] / temp;
/* L110: */
}
/* L120: */
}
/* Update the right singular vector matrix. */
if (*k == 2) {
dgemm_("N", "N", k, &m, k, &c_b15, &q[q_offset], ldq, &vt2[vt2_offset]
, ldvt2, &c_b29, &vt[vt_offset], ldvt);
return 0;
}
ktemp = ctot[1] + 1;
dgemm_("N", "N", k, &nlp1, &ktemp, &c_b15, &q[q_dim1 + 1], ldq, &vt2[
vt2_dim1 + 1], ldvt2, &c_b29, &vt[vt_dim1 + 1], ldvt);
ktemp = ctot[1] + 2 + ctot[2];
if (ktemp <= *ldvt2) {
dgemm_("N", "N", k, &nlp1, &ctot[3], &c_b15, &q[ktemp * q_dim1 + 1],
ldq, &vt2[ktemp + vt2_dim1], ldvt2, &c_b15, &vt[vt_dim1 + 1],
ldvt);
}
ktemp = ctot[1] + 1;
nrp1 = *nr + *sqre;
if (ktemp > 1) {
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
q[i__ + ktemp * q_dim1] = q[i__ + q_dim1];
/* L130: */
}
i__1 = m;
for (i__ = nlp2; i__ <= i__1; ++i__) {
vt2[ktemp + i__ * vt2_dim1] = vt2[i__ * vt2_dim1 + 1];
/* L140: */
}
}
ctemp = ctot[2] + 1 + ctot[3];
dgemm_("N", "N", k, &nrp1, &ctemp, &c_b15, &q[ktemp * q_dim1 + 1], ldq, &
vt2[ktemp + nlp2 * vt2_dim1], ldvt2, &c_b29, &vt[nlp2 * vt_dim1 +
1], ldvt);
return 0;
/* End of DLASD3 */
} /* dlasd3_ */
/* Subroutine */ int dlasd4_(integer *n, integer *i__, doublereal *d__,
doublereal *z__, doublereal *delta, doublereal *rho, doublereal *
sigma, doublereal *work, integer *info)
{
/* System generated locals */
integer i__1;
doublereal d__1;
/* Local variables */
static doublereal a, b, c__;
static integer j;
static doublereal w, dd[3];
static integer ii;
static doublereal dw, zz[3];
static integer ip1;
static doublereal eta, phi, eps, tau, psi;
static integer iim1, iip1;
static doublereal dphi, dpsi;
static integer iter;
static doublereal temp, prew, sg2lb, sg2ub, temp1, temp2, dtiim, delsq,
dtiip;
static integer niter;
static doublereal dtisq;
static logical swtch;
static doublereal dtnsq;
extern /* Subroutine */ int dlaed6_(integer *, logical *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *, integer *)
, dlasd5_(integer *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *);
static doublereal delsq2, dtnsq1;
static logical swtch3;
static logical orgati;
static doublereal erretm, dtipsq, rhoinv;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
This subroutine computes the square root of the I-th updated
eigenvalue of a positive symmetric rank-one modification to
a positive diagonal matrix whose entries are given as the squares
of the corresponding entries in the array d, and that
0 <= D(i) < D(j) for i < j
and that RHO > 0. This is arranged by the calling routine, and is
no loss in generality. The rank-one modified system is thus
diag( D ) * diag( D ) + RHO * Z * Z_transpose.
where we assume the Euclidean norm of Z is 1.
The method consists of approximating the rational functions in the
secular equation by simpler interpolating rational functions.
Arguments
=========
N (input) INTEGER
The length of all arrays.
I (input) INTEGER
The index of the eigenvalue to be computed. 1 <= I <= N.
D (input) DOUBLE PRECISION array, dimension ( N )
The original eigenvalues. It is assumed that they are in
order, 0 <= D(I) < D(J) for I < J.
Z (input) DOUBLE PRECISION array, dimension ( N )
The components of the updating vector.
DELTA (output) DOUBLE PRECISION array, dimension ( N )
If N .ne. 1, DELTA contains (D(j) - sigma_I) in its j-th
component. If N = 1, then DELTA(1) = 1. The vector DELTA
contains the information necessary to construct the
(singular) eigenvectors.
RHO (input) DOUBLE PRECISION
The scalar in the symmetric updating formula.
SIGMA (output) DOUBLE PRECISION
The computed sigma_I, the I-th updated eigenvalue.
WORK (workspace) DOUBLE PRECISION array, dimension ( N )
If N .ne. 1, WORK contains (D(j) + sigma_I) in its j-th
component. If N = 1, then WORK( 1 ) = 1.
INFO (output) INTEGER
= 0: successful exit
> 0: if INFO = 1, the updating process failed.
Internal Parameters
===================
Logical variable ORGATI (origin-at-i?) is used for distinguishing
whether D(i) or D(i+1) is treated as the origin.
ORGATI = .true. origin at i
ORGATI = .false. origin at i+1
Logical variable SWTCH3 (switch-for-3-poles?) is for noting
if we are working with THREE poles!
MAXIT is the maximum number of iterations allowed for each
eigenvalue.
Further Details
===============
Based on contributions by
Ren-Cang Li, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
Since this routine is called in an inner loop, we do no argument
checking.
Quick return for N=1 and 2.
*/
/* Parameter adjustments */
--work;
--delta;
--z__;
--d__;
/* Function Body */
*info = 0;
if (*n == 1) {
/* Presumably, I=1 upon entry */
*sigma = sqrt(d__[1] * d__[1] + *rho * z__[1] * z__[1]);
delta[1] = 1.;
work[1] = 1.;
return 0;
}
if (*n == 2) {
dlasd5_(i__, &d__[1], &z__[1], &delta[1], rho, sigma, &work[1]);
return 0;
}
/* Compute machine epsilon */
eps = EPSILON;
rhoinv = 1. / *rho;
/* The case I = N */
if (*i__ == *n) {
/* Initialize some basic variables */
ii = *n - 1;
niter = 1;
/* Calculate initial guess */
temp = *rho / 2.;
/*
If ||Z||_2 is not one, then TEMP should be set to
RHO * ||Z||_2^2 / TWO
*/
temp1 = temp / (d__[*n] + sqrt(d__[*n] * d__[*n] + temp));
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
work[j] = d__[j] + d__[*n] + temp1;
delta[j] = d__[j] - d__[*n] - temp1;
/* L10: */
}
psi = 0.;
i__1 = *n - 2;
for (j = 1; j <= i__1; ++j) {
psi += z__[j] * z__[j] / (delta[j] * work[j]);
/* L20: */
}
c__ = rhoinv + psi;
w = c__ + z__[ii] * z__[ii] / (delta[ii] * work[ii]) + z__[*n] * z__[*
n] / (delta[*n] * work[*n]);
if (w <= 0.) {
temp1 = sqrt(d__[*n] * d__[*n] + *rho);
temp = z__[*n - 1] * z__[*n - 1] / ((d__[*n - 1] + temp1) * (d__[*
n] - d__[*n - 1] + *rho / (d__[*n] + temp1))) + z__[*n] *
z__[*n] / *rho;
/*
The following TAU is to approximate
SIGMA_n^2 - D( N )*D( N )
*/
if (c__ <= temp) {
tau = *rho;
} else {
delsq = (d__[*n] - d__[*n - 1]) * (d__[*n] + d__[*n - 1]);
a = -c__ * delsq + z__[*n - 1] * z__[*n - 1] + z__[*n] * z__[*
n];
b = z__[*n] * z__[*n] * delsq;
if (a < 0.) {
tau = b * 2. / (sqrt(a * a + b * 4. * c__) - a);
} else {
tau = (a + sqrt(a * a + b * 4. * c__)) / (c__ * 2.);
}
}
/*
It can be proved that
D(N)^2+RHO/2 <= SIGMA_n^2 < D(N)^2+TAU <= D(N)^2+RHO
*/
} else {
delsq = (d__[*n] - d__[*n - 1]) * (d__[*n] + d__[*n - 1]);
a = -c__ * delsq + z__[*n - 1] * z__[*n - 1] + z__[*n] * z__[*n];
b = z__[*n] * z__[*n] * delsq;
/*
The following TAU is to approximate
SIGMA_n^2 - D( N )*D( N )
*/
if (a < 0.) {
tau = b * 2. / (sqrt(a * a + b * 4. * c__) - a);
} else {
tau = (a + sqrt(a * a + b * 4. * c__)) / (c__ * 2.);
}
/*
It can be proved that
D(N)^2 < D(N)^2+TAU < SIGMA(N)^2 < D(N)^2+RHO/2
*/
}
/* The following ETA is to approximate SIGMA_n - D( N ) */
eta = tau / (d__[*n] + sqrt(d__[*n] * d__[*n] + tau));
*sigma = d__[*n] + eta;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] = d__[j] - d__[*i__] - eta;
work[j] = d__[j] + d__[*i__] + eta;
/* L30: */
}
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = ii;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / (delta[j] * work[j]);
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L40: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
temp = z__[*n] / (delta[*n] * work[*n]);
phi = z__[*n] * temp;
dphi = temp * temp;
erretm = (-phi - psi) * 8. + erretm - phi + rhoinv + abs(tau) * (dpsi
+ dphi);
w = rhoinv + phi + psi;
/* Test for convergence */
if (abs(w) <= eps * erretm) {
goto L240;
}
/* Calculate the new step */
++niter;
dtnsq1 = work[*n - 1] * delta[*n - 1];
dtnsq = work[*n] * delta[*n];
c__ = w - dtnsq1 * dpsi - dtnsq * dphi;
a = (dtnsq + dtnsq1) * w - dtnsq * dtnsq1 * (dpsi + dphi);
b = dtnsq * dtnsq1 * w;
if (c__ < 0.) {
c__ = abs(c__);
}
if (c__ == 0.) {
eta = *rho - *sigma * *sigma;
} else if (a >= 0.) {
eta = (a + sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (c__
* 2.);
} else {
eta = b * 2. / (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))
);
}
/*
Note, eta should be positive if w is negative, and
eta should be negative otherwise. However,
if for some reason caused by roundoff, eta*w > 0,
we simply use one Newton step instead. This way
will guarantee eta*w < 0.
*/
if (w * eta > 0.) {
eta = -w / (dpsi + dphi);
}
temp = eta - dtnsq;
if (temp > *rho) {
eta = *rho + dtnsq;
}
tau += eta;
eta /= *sigma + sqrt(eta + *sigma * *sigma);
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] -= eta;
work[j] += eta;
/* L50: */
}
*sigma += eta;
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = ii;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / (work[j] * delta[j]);
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L60: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
temp = z__[*n] / (work[*n] * delta[*n]);
phi = z__[*n] * temp;
dphi = temp * temp;
erretm = (-phi - psi) * 8. + erretm - phi + rhoinv + abs(tau) * (dpsi
+ dphi);
w = rhoinv + phi + psi;
/* Main loop to update the values of the array DELTA */
iter = niter + 1;
for (niter = iter; niter <= 20; ++niter) {
/* Test for convergence */
if (abs(w) <= eps * erretm) {
goto L240;
}
/* Calculate the new step */
dtnsq1 = work[*n - 1] * delta[*n - 1];
dtnsq = work[*n] * delta[*n];
c__ = w - dtnsq1 * dpsi - dtnsq * dphi;
a = (dtnsq + dtnsq1) * w - dtnsq1 * dtnsq * (dpsi + dphi);
b = dtnsq1 * dtnsq * w;
if (a >= 0.) {
eta = (a + sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (
c__ * 2.);
} else {
eta = b * 2. / (a - sqrt((d__1 = a * a - b * 4. * c__, abs(
d__1))));
}
/*
Note, eta should be positive if w is negative, and
eta should be negative otherwise. However,
if for some reason caused by roundoff, eta*w > 0,
we simply use one Newton step instead. This way
will guarantee eta*w < 0.
*/
if (w * eta > 0.) {
eta = -w / (dpsi + dphi);
}
temp = eta - dtnsq;
if (temp <= 0.) {
eta /= 2.;
}
tau += eta;
eta /= *sigma + sqrt(eta + *sigma * *sigma);
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
delta[j] -= eta;
work[j] += eta;
/* L70: */
}
*sigma += eta;
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = ii;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / (work[j] * delta[j]);
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L80: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
temp = z__[*n] / (work[*n] * delta[*n]);
phi = z__[*n] * temp;
dphi = temp * temp;
erretm = (-phi - psi) * 8. + erretm - phi + rhoinv + abs(tau) * (
dpsi + dphi);
w = rhoinv + phi + psi;
/* L90: */
}
/* Return with INFO = 1, NITER = MAXIT and not converged */
*info = 1;
goto L240;
/* End for the case I = N */
} else {
/* The case for I < N */
niter = 1;
ip1 = *i__ + 1;
/* Calculate initial guess */
delsq = (d__[ip1] - d__[*i__]) * (d__[ip1] + d__[*i__]);
delsq2 = delsq / 2.;
temp = delsq2 / (d__[*i__] + sqrt(d__[*i__] * d__[*i__] + delsq2));
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
work[j] = d__[j] + d__[*i__] + temp;
delta[j] = d__[j] - d__[*i__] - temp;
/* L100: */
}
psi = 0.;
i__1 = *i__ - 1;
for (j = 1; j <= i__1; ++j) {
psi += z__[j] * z__[j] / (work[j] * delta[j]);
/* L110: */
}
phi = 0.;
i__1 = *i__ + 2;
for (j = *n; j >= i__1; --j) {
phi += z__[j] * z__[j] / (work[j] * delta[j]);
/* L120: */
}
c__ = rhoinv + psi + phi;
w = c__ + z__[*i__] * z__[*i__] / (work[*i__] * delta[*i__]) + z__[
ip1] * z__[ip1] / (work[ip1] * delta[ip1]);
if (w > 0.) {
/*
d(i)^2 < the ith sigma^2 < (d(i)^2+d(i+1)^2)/2
We choose d(i) as origin.
*/
orgati = TRUE_;
sg2lb = 0.;
sg2ub = delsq2;
a = c__ * delsq + z__[*i__] * z__[*i__] + z__[ip1] * z__[ip1];
b = z__[*i__] * z__[*i__] * delsq;
if (a > 0.) {
tau = b * 2. / (a + sqrt((d__1 = a * a - b * 4. * c__, abs(
d__1))));
} else {
tau = (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (
c__ * 2.);
}
/*
TAU now is an estimation of SIGMA^2 - D( I )^2. The
following, however, is the corresponding estimation of
SIGMA - D( I ).
*/
eta = tau / (d__[*i__] + sqrt(d__[*i__] * d__[*i__] + tau));
} else {
/*
(d(i)^2+d(i+1)^2)/2 <= the ith sigma^2 < d(i+1)^2/2
We choose d(i+1) as origin.
*/
orgati = FALSE_;
sg2lb = -delsq2;
sg2ub = 0.;
a = c__ * delsq - z__[*i__] * z__[*i__] - z__[ip1] * z__[ip1];
b = z__[ip1] * z__[ip1] * delsq;
if (a < 0.) {
tau = b * 2. / (a - sqrt((d__1 = a * a + b * 4. * c__, abs(
d__1))));
} else {
tau = -(a + sqrt((d__1 = a * a + b * 4. * c__, abs(d__1)))) /
(c__ * 2.);
}
/*
TAU now is an estimation of SIGMA^2 - D( IP1 )^2. The
following, however, is the corresponding estimation of
SIGMA - D( IP1 ).
*/
eta = tau / (d__[ip1] + sqrt((d__1 = d__[ip1] * d__[ip1] + tau,
abs(d__1))));
}
if (orgati) {
ii = *i__;
*sigma = d__[*i__] + eta;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
work[j] = d__[j] + d__[*i__] + eta;
delta[j] = d__[j] - d__[*i__] - eta;
/* L130: */
}
} else {
ii = *i__ + 1;
*sigma = d__[ip1] + eta;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
work[j] = d__[j] + d__[ip1] + eta;
delta[j] = d__[j] - d__[ip1] - eta;
/* L140: */
}
}
iim1 = ii - 1;
iip1 = ii + 1;
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = iim1;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / (work[j] * delta[j]);
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L150: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
dphi = 0.;
phi = 0.;
i__1 = iip1;
for (j = *n; j >= i__1; --j) {
temp = z__[j] / (work[j] * delta[j]);
phi += z__[j] * temp;
dphi += temp * temp;
erretm += phi;
/* L160: */
}
w = rhoinv + phi + psi;
/*
W is the value of the secular function with
its ii-th element removed.
*/
swtch3 = FALSE_;
if (orgati) {
if (w < 0.) {
swtch3 = TRUE_;
}
} else {
if (w > 0.) {
swtch3 = TRUE_;
}
}
if (ii == 1 || ii == *n) {
swtch3 = FALSE_;
}
temp = z__[ii] / (work[ii] * delta[ii]);
dw = dpsi + dphi + temp * temp;
temp = z__[ii] * temp;
w += temp;
erretm = (phi - psi) * 8. + erretm + rhoinv * 2. + abs(temp) * 3. +
abs(tau) * dw;
/* Test for convergence */
if (abs(w) <= eps * erretm) {
goto L240;
}
if (w <= 0.) {
sg2lb = max(sg2lb,tau);
} else {
sg2ub = min(sg2ub,tau);
}
/* Calculate the new step */
++niter;
if (! swtch3) {
dtipsq = work[ip1] * delta[ip1];
dtisq = work[*i__] * delta[*i__];
if (orgati) {
/* Computing 2nd power */
d__1 = z__[*i__] / dtisq;
c__ = w - dtipsq * dw + delsq * (d__1 * d__1);
} else {
/* Computing 2nd power */
d__1 = z__[ip1] / dtipsq;
c__ = w - dtisq * dw - delsq * (d__1 * d__1);
}
a = (dtipsq + dtisq) * w - dtipsq * dtisq * dw;
b = dtipsq * dtisq * w;
if (c__ == 0.) {
if (a == 0.) {
if (orgati) {
a = z__[*i__] * z__[*i__] + dtipsq * dtipsq * (dpsi +
dphi);
} else {
a = z__[ip1] * z__[ip1] + dtisq * dtisq * (dpsi +
dphi);
}
}
eta = b / a;
} else if (a <= 0.) {
eta = (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1)))) / (
c__ * 2.);
} else {
eta = b * 2. / (a + sqrt((d__1 = a * a - b * 4. * c__, abs(
d__1))));
}
} else {
/* Interpolation using THREE most relevant poles */
dtiim = work[iim1] * delta[iim1];
dtiip = work[iip1] * delta[iip1];
temp = rhoinv + psi + phi;
if (orgati) {
temp1 = z__[iim1] / dtiim;
temp1 *= temp1;
c__ = temp - dtiip * (dpsi + dphi) - (d__[iim1] - d__[iip1]) *
(d__[iim1] + d__[iip1]) * temp1;
zz[0] = z__[iim1] * z__[iim1];
if (dpsi < temp1) {
zz[2] = dtiip * dtiip * dphi;
} else {
zz[2] = dtiip * dtiip * (dpsi - temp1 + dphi);
}
} else {
temp1 = z__[iip1] / dtiip;
temp1 *= temp1;
c__ = temp - dtiim * (dpsi + dphi) - (d__[iip1] - d__[iim1]) *
(d__[iim1] + d__[iip1]) * temp1;
if (dphi < temp1) {
zz[0] = dtiim * dtiim * dpsi;
} else {
zz[0] = dtiim * dtiim * (dpsi + (dphi - temp1));
}
zz[2] = z__[iip1] * z__[iip1];
}
zz[1] = z__[ii] * z__[ii];
dd[0] = dtiim;
dd[1] = delta[ii] * work[ii];
dd[2] = dtiip;
dlaed6_(&niter, &orgati, &c__, dd, zz, &w, &eta, info);
if (*info != 0) {
goto L240;
}
}
/*
Note, eta should be positive if w is negative, and
eta should be negative otherwise. However,
if for some reason caused by roundoff, eta*w > 0,
we simply use one Newton step instead. This way
will guarantee eta*w < 0.
*/
if (w * eta >= 0.) {
eta = -w / dw;
}
if (orgati) {
temp1 = work[*i__] * delta[*i__];
temp = eta - temp1;
} else {
temp1 = work[ip1] * delta[ip1];
temp = eta - temp1;
}
if (temp > sg2ub || temp < sg2lb) {
if (w < 0.) {
eta = (sg2ub - tau) / 2.;
} else {
eta = (sg2lb - tau) / 2.;
}
}
tau += eta;
eta /= *sigma + sqrt(*sigma * *sigma + eta);
prew = w;
*sigma += eta;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
work[j] += eta;
delta[j] -= eta;
/* L170: */
}
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = iim1;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / (work[j] * delta[j]);
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L180: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
dphi = 0.;
phi = 0.;
i__1 = iip1;
for (j = *n; j >= i__1; --j) {
temp = z__[j] / (work[j] * delta[j]);
phi += z__[j] * temp;
dphi += temp * temp;
erretm += phi;
/* L190: */
}
temp = z__[ii] / (work[ii] * delta[ii]);
dw = dpsi + dphi + temp * temp;
temp = z__[ii] * temp;
w = rhoinv + phi + psi + temp;
erretm = (phi - psi) * 8. + erretm + rhoinv * 2. + abs(temp) * 3. +
abs(tau) * dw;
if (w <= 0.) {
sg2lb = max(sg2lb,tau);
} else {
sg2ub = min(sg2ub,tau);
}
swtch = FALSE_;
if (orgati) {
if (-w > abs(prew) / 10.) {
swtch = TRUE_;
}
} else {
if (w > abs(prew) / 10.) {
swtch = TRUE_;
}
}
/* Main loop to update the values of the array DELTA and WORK */
iter = niter + 1;
for (niter = iter; niter <= 20; ++niter) {
/* Test for convergence */
if (abs(w) <= eps * erretm) {
goto L240;
}
/* Calculate the new step */
if (! swtch3) {
dtipsq = work[ip1] * delta[ip1];
dtisq = work[*i__] * delta[*i__];
if (! swtch) {
if (orgati) {
/* Computing 2nd power */
d__1 = z__[*i__] / dtisq;
c__ = w - dtipsq * dw + delsq * (d__1 * d__1);
} else {
/* Computing 2nd power */
d__1 = z__[ip1] / dtipsq;
c__ = w - dtisq * dw - delsq * (d__1 * d__1);
}
} else {
temp = z__[ii] / (work[ii] * delta[ii]);
if (orgati) {
dpsi += temp * temp;
} else {
dphi += temp * temp;
}
c__ = w - dtisq * dpsi - dtipsq * dphi;
}
a = (dtipsq + dtisq) * w - dtipsq * dtisq * dw;
b = dtipsq * dtisq * w;
if (c__ == 0.) {
if (a == 0.) {
if (! swtch) {
if (orgati) {
a = z__[*i__] * z__[*i__] + dtipsq * dtipsq *
(dpsi + dphi);
} else {
a = z__[ip1] * z__[ip1] + dtisq * dtisq * (
dpsi + dphi);
}
} else {
a = dtisq * dtisq * dpsi + dtipsq * dtipsq * dphi;
}
}
eta = b / a;
} else if (a <= 0.) {
eta = (a - sqrt((d__1 = a * a - b * 4. * c__, abs(d__1))))
/ (c__ * 2.);
} else {
eta = b * 2. / (a + sqrt((d__1 = a * a - b * 4. * c__,
abs(d__1))));
}
} else {
/* Interpolation using THREE most relevant poles */
dtiim = work[iim1] * delta[iim1];
dtiip = work[iip1] * delta[iip1];
temp = rhoinv + psi + phi;
if (swtch) {
c__ = temp - dtiim * dpsi - dtiip * dphi;
zz[0] = dtiim * dtiim * dpsi;
zz[2] = dtiip * dtiip * dphi;
} else {
if (orgati) {
temp1 = z__[iim1] / dtiim;
temp1 *= temp1;
temp2 = (d__[iim1] - d__[iip1]) * (d__[iim1] + d__[
iip1]) * temp1;
c__ = temp - dtiip * (dpsi + dphi) - temp2;
zz[0] = z__[iim1] * z__[iim1];
if (dpsi < temp1) {
zz[2] = dtiip * dtiip * dphi;
} else {
zz[2] = dtiip * dtiip * (dpsi - temp1 + dphi);
}
} else {
temp1 = z__[iip1] / dtiip;
temp1 *= temp1;
temp2 = (d__[iip1] - d__[iim1]) * (d__[iim1] + d__[
iip1]) * temp1;
c__ = temp - dtiim * (dpsi + dphi) - temp2;
if (dphi < temp1) {
zz[0] = dtiim * dtiim * dpsi;
} else {
zz[0] = dtiim * dtiim * (dpsi + (dphi - temp1));
}
zz[2] = z__[iip1] * z__[iip1];
}
}
dd[0] = dtiim;
dd[1] = delta[ii] * work[ii];
dd[2] = dtiip;
dlaed6_(&niter, &orgati, &c__, dd, zz, &w, &eta, info);
if (*info != 0) {
goto L240;
}
}
/*
Note, eta should be positive if w is negative, and
eta should be negative otherwise. However,
if for some reason caused by roundoff, eta*w > 0,
we simply use one Newton step instead. This way
will guarantee eta*w < 0.
*/
if (w * eta >= 0.) {
eta = -w / dw;
}
if (orgati) {
temp1 = work[*i__] * delta[*i__];
temp = eta - temp1;
} else {
temp1 = work[ip1] * delta[ip1];
temp = eta - temp1;
}
if (temp > sg2ub || temp < sg2lb) {
if (w < 0.) {
eta = (sg2ub - tau) / 2.;
} else {
eta = (sg2lb - tau) / 2.;
}
}
tau += eta;
eta /= *sigma + sqrt(*sigma * *sigma + eta);
*sigma += eta;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
work[j] += eta;
delta[j] -= eta;
/* L200: */
}
prew = w;
/* Evaluate PSI and the derivative DPSI */
dpsi = 0.;
psi = 0.;
erretm = 0.;
i__1 = iim1;
for (j = 1; j <= i__1; ++j) {
temp = z__[j] / (work[j] * delta[j]);
psi += z__[j] * temp;
dpsi += temp * temp;
erretm += psi;
/* L210: */
}
erretm = abs(erretm);
/* Evaluate PHI and the derivative DPHI */
dphi = 0.;
phi = 0.;
i__1 = iip1;
for (j = *n; j >= i__1; --j) {
temp = z__[j] / (work[j] * delta[j]);
phi += z__[j] * temp;
dphi += temp * temp;
erretm += phi;
/* L220: */
}
temp = z__[ii] / (work[ii] * delta[ii]);
dw = dpsi + dphi + temp * temp;
temp = z__[ii] * temp;
w = rhoinv + phi + psi + temp;
erretm = (phi - psi) * 8. + erretm + rhoinv * 2. + abs(temp) * 3.
+ abs(tau) * dw;
if (w * prew > 0. && abs(w) > abs(prew) / 10.) {
swtch = ! swtch;
}
if (w <= 0.) {
sg2lb = max(sg2lb,tau);
} else {
sg2ub = min(sg2ub,tau);
}
/* L230: */
}
/* Return with INFO = 1, NITER = MAXIT and not converged */
*info = 1;
}
L240:
return 0;
/* End of DLASD4 */
} /* dlasd4_ */
/* Subroutine */ int dlasd5_(integer *i__, doublereal *d__, doublereal *z__,
doublereal *delta, doublereal *rho, doublereal *dsigma, doublereal *
work)
{
/* System generated locals */
doublereal d__1;
/* Local variables */
static doublereal b, c__, w, del, tau, delsq;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
This subroutine computes the square root of the I-th eigenvalue
of a positive symmetric rank-one modification of a 2-by-2 diagonal
matrix
diag( D ) * diag( D ) + RHO * Z * transpose(Z) .
The diagonal entries in the array D are assumed to satisfy
0 <= D(i) < D(j) for i < j .
We also assume RHO > 0 and that the Euclidean norm of the vector
Z is one.
Arguments
=========
I (input) INTEGER
The index of the eigenvalue to be computed. I = 1 or I = 2.
D (input) DOUBLE PRECISION array, dimension ( 2 )
The original eigenvalues. We assume 0 <= D(1) < D(2).
Z (input) DOUBLE PRECISION array, dimension ( 2 )
The components of the updating vector.
DELTA (output) DOUBLE PRECISION array, dimension ( 2 )
Contains (D(j) - sigma_I) in its j-th component.
The vector DELTA contains the information necessary
to construct the eigenvectors.
RHO (input) DOUBLE PRECISION
The scalar in the symmetric updating formula.
DSIGMA (output) DOUBLE PRECISION
The computed sigma_I, the I-th updated eigenvalue.
WORK (workspace) DOUBLE PRECISION array, dimension ( 2 )
WORK contains (D(j) + sigma_I) in its j-th component.
Further Details
===============
Based on contributions by
Ren-Cang Li, Computer Science Division, University of California
at Berkeley, USA
=====================================================================
*/
/* Parameter adjustments */
--work;
--delta;
--z__;
--d__;
/* Function Body */
del = d__[2] - d__[1];
delsq = del * (d__[2] + d__[1]);
if (*i__ == 1) {
w = *rho * 4. * (z__[2] * z__[2] / (d__[1] + d__[2] * 3.) - z__[1] *
z__[1] / (d__[1] * 3. + d__[2])) / del + 1.;
if (w > 0.) {
b = delsq + *rho * (z__[1] * z__[1] + z__[2] * z__[2]);
c__ = *rho * z__[1] * z__[1] * delsq;
/*
B > ZERO, always
The following TAU is DSIGMA * DSIGMA - D( 1 ) * D( 1 )
*/
tau = c__ * 2. / (b + sqrt((d__1 = b * b - c__ * 4., abs(d__1))));
/* The following TAU is DSIGMA - D( 1 ) */
tau /= d__[1] + sqrt(d__[1] * d__[1] + tau);
*dsigma = d__[1] + tau;
delta[1] = -tau;
delta[2] = del - tau;
work[1] = d__[1] * 2. + tau;
work[2] = d__[1] + tau + d__[2];
/*
DELTA( 1 ) = -Z( 1 ) / TAU
DELTA( 2 ) = Z( 2 ) / ( DEL-TAU )
*/
} else {
b = -delsq + *rho * (z__[1] * z__[1] + z__[2] * z__[2]);
c__ = *rho * z__[2] * z__[2] * delsq;
/* The following TAU is DSIGMA * DSIGMA - D( 2 ) * D( 2 ) */
if (b > 0.) {
tau = c__ * -2. / (b + sqrt(b * b + c__ * 4.));
} else {
tau = (b - sqrt(b * b + c__ * 4.)) / 2.;
}
/* The following TAU is DSIGMA - D( 2 ) */
tau /= d__[2] + sqrt((d__1 = d__[2] * d__[2] + tau, abs(d__1)));
*dsigma = d__[2] + tau;
delta[1] = -(del + tau);
delta[2] = -tau;
work[1] = d__[1] + tau + d__[2];
work[2] = d__[2] * 2. + tau;
/*
DELTA( 1 ) = -Z( 1 ) / ( DEL+TAU )
DELTA( 2 ) = -Z( 2 ) / TAU
*/
}
/*
TEMP = SQRT( DELTA( 1 )*DELTA( 1 )+DELTA( 2 )*DELTA( 2 ) )
DELTA( 1 ) = DELTA( 1 ) / TEMP
DELTA( 2 ) = DELTA( 2 ) / TEMP
*/
} else {
/* Now I=2 */
b = -delsq + *rho * (z__[1] * z__[1] + z__[2] * z__[2]);
c__ = *rho * z__[2] * z__[2] * delsq;
/* The following TAU is DSIGMA * DSIGMA - D( 2 ) * D( 2 ) */
if (b > 0.) {
tau = (b + sqrt(b * b + c__ * 4.)) / 2.;
} else {
tau = c__ * 2. / (-b + sqrt(b * b + c__ * 4.));
}
/* The following TAU is DSIGMA - D( 2 ) */
tau /= d__[2] + sqrt(d__[2] * d__[2] + tau);
*dsigma = d__[2] + tau;
delta[1] = -(del + tau);
delta[2] = -tau;
work[1] = d__[1] + tau + d__[2];
work[2] = d__[2] * 2. + tau;
/*
DELTA( 1 ) = -Z( 1 ) / ( DEL+TAU )
DELTA( 2 ) = -Z( 2 ) / TAU
TEMP = SQRT( DELTA( 1 )*DELTA( 1 )+DELTA( 2 )*DELTA( 2 ) )
DELTA( 1 ) = DELTA( 1 ) / TEMP
DELTA( 2 ) = DELTA( 2 ) / TEMP
*/
}
return 0;
/* End of DLASD5 */
} /* dlasd5_ */
/* Subroutine */ int dlasd6_(integer *icompq, integer *nl, integer *nr,
integer *sqre, doublereal *d__, doublereal *vf, doublereal *vl,
doublereal *alpha, doublereal *beta, integer *idxq, integer *perm,
integer *givptr, integer *givcol, integer *ldgcol, doublereal *givnum,
integer *ldgnum, doublereal *poles, doublereal *difl, doublereal *
difr, doublereal *z__, integer *k, doublereal *c__, doublereal *s,
doublereal *work, integer *iwork, integer *info)
{
/* System generated locals */
integer givcol_dim1, givcol_offset, givnum_dim1, givnum_offset,
poles_dim1, poles_offset, i__1;
doublereal d__1, d__2;
/* Local variables */
static integer i__, m, n, n1, n2, iw, idx, idxc, idxp, ivfw, ivlw;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *), dlasd7_(integer *, integer *, integer *,
integer *, integer *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, integer *, integer *,
integer *, integer *, integer *, integer *, integer *, doublereal
*, integer *, doublereal *, doublereal *, integer *), dlasd8_(
integer *, integer *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, integer *, doublereal *,
doublereal *, integer *), dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *), dlamrg_(integer *, integer *,
doublereal *, integer *, integer *, integer *);
static integer isigma;
extern /* Subroutine */ int xerbla_(char *, integer *);
static doublereal orgnrm;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLASD6 computes the SVD of an updated upper bidiagonal matrix B
obtained by merging two smaller ones by appending a row. This
routine is used only for the problem which requires all singular
values and optionally singular vector matrices in factored form.
B is an N-by-M matrix with N = NL + NR + 1 and M = N + SQRE.
A related subroutine, DLASD1, handles the case in which all singular
values and singular vectors of the bidiagonal matrix are desired.
DLASD6 computes the SVD as follows:
( D1(in) 0 0 0 )
B = U(in) * ( Z1' a Z2' b ) * VT(in)
( 0 0 D2(in) 0 )
= U(out) * ( D(out) 0) * VT(out)
where Z' = (Z1' a Z2' b) = u' VT', and u is a vector of dimension M
with ALPHA and BETA in the NL+1 and NL+2 th entries and zeros
elsewhere; and the entry b is empty if SQRE = 0.
The singular values of B can be computed using D1, D2, the first
components of all the right singular vectors of the lower block, and
the last components of all the right singular vectors of the upper
block. These components are stored and updated in VF and VL,
respectively, in DLASD6. Hence U and VT are not explicitly
referenced.
The singular values are stored in D. The algorithm consists of two
stages:
The first stage consists of deflating the size of the problem
when there are multiple singular values or if there is a zero
in the Z vector. For each such occurence the dimension of the
secular equation problem is reduced by one. This stage is
performed by the routine DLASD7.
The second stage consists of calculating the updated
singular values. This is done by finding the roots of the
secular equation via the routine DLASD4 (as called by DLASD8).
This routine also updates VF and VL and computes the distances
between the updated singular values and the old singular
values.
DLASD6 is called from DLASDA.
Arguments
=========
ICOMPQ (input) INTEGER
Specifies whether singular vectors are to be computed in
factored form:
= 0: Compute singular values only.
= 1: Compute singular vectors in factored form as well.
NL (input) INTEGER
The row dimension of the upper block. NL >= 1.
NR (input) INTEGER
The row dimension of the lower block. NR >= 1.
SQRE (input) INTEGER
= 0: the lower block is an NR-by-NR square matrix.
= 1: the lower block is an NR-by-(NR+1) rectangular matrix.
The bidiagonal matrix has row dimension N = NL + NR + 1,
and column dimension M = N + SQRE.
D (input/output) DOUBLE PRECISION array, dimension ( NL+NR+1 ).
On entry D(1:NL,1:NL) contains the singular values of the
upper block, and D(NL+2:N) contains the singular values
of the lower block. On exit D(1:N) contains the singular
values of the modified matrix.
VF (input/output) DOUBLE PRECISION array, dimension ( M )
On entry, VF(1:NL+1) contains the first components of all
right singular vectors of the upper block; and VF(NL+2:M)
contains the first components of all right singular vectors
of the lower block. On exit, VF contains the first components
of all right singular vectors of the bidiagonal matrix.
VL (input/output) DOUBLE PRECISION array, dimension ( M )
On entry, VL(1:NL+1) contains the last components of all
right singular vectors of the upper block; and VL(NL+2:M)
contains the last components of all right singular vectors of
the lower block. On exit, VL contains the last components of
all right singular vectors of the bidiagonal matrix.
ALPHA (input/output) DOUBLE PRECISION
Contains the diagonal element associated with the added row.
BETA (input/output) DOUBLE PRECISION
Contains the off-diagonal element associated with the added
row.
IDXQ (output) INTEGER array, dimension ( N )
This contains the permutation which will reintegrate the
subproblem just solved back into sorted order, i.e.
D( IDXQ( I = 1, N ) ) will be in ascending order.
PERM (output) INTEGER array, dimension ( N )
The permutations (from deflation and sorting) to be applied
to each block. Not referenced if ICOMPQ = 0.
GIVPTR (output) INTEGER
The number of Givens rotations which took place in this
subproblem. Not referenced if ICOMPQ = 0.
GIVCOL (output) INTEGER array, dimension ( LDGCOL, 2 )
Each pair of numbers indicates a pair of columns to take place
in a Givens rotation. Not referenced if ICOMPQ = 0.
LDGCOL (input) INTEGER
leading dimension of GIVCOL, must be at least N.
GIVNUM (output) DOUBLE PRECISION array, dimension ( LDGNUM, 2 )
Each number indicates the C or S value to be used in the
corresponding Givens rotation. Not referenced if ICOMPQ = 0.
LDGNUM (input) INTEGER
The leading dimension of GIVNUM and POLES, must be at least N.
POLES (output) DOUBLE PRECISION array, dimension ( LDGNUM, 2 )
On exit, POLES(1,*) is an array containing the new singular
values obtained from solving the secular equation, and
POLES(2,*) is an array containing the poles in the secular
equation. Not referenced if ICOMPQ = 0.
DIFL (output) DOUBLE PRECISION array, dimension ( N )
On exit, DIFL(I) is the distance between I-th updated
(undeflated) singular value and the I-th (undeflated) old
singular value.
DIFR (output) DOUBLE PRECISION array,
dimension ( LDGNUM, 2 ) if ICOMPQ = 1 and
dimension ( N ) if ICOMPQ = 0.
On exit, DIFR(I, 1) is the distance between I-th updated
(undeflated) singular value and the I+1-th (undeflated) old
singular value.
If ICOMPQ = 1, DIFR(1:K,2) is an array containing the
normalizing factors for the right singular vector matrix.
See DLASD8 for details on DIFL and DIFR.
Z (output) DOUBLE PRECISION array, dimension ( M )
The first elements of this array contain the components
of the deflation-adjusted updating row vector.
K (output) INTEGER
Contains the dimension of the non-deflated matrix,
This is the order of the related secular equation. 1 <= K <=N.
C (output) DOUBLE PRECISION
C contains garbage if SQRE =0 and the C-value of a Givens
rotation related to the right null space if SQRE = 1.
S (output) DOUBLE PRECISION
S contains garbage if SQRE =0 and the S-value of a Givens
rotation related to the right null space if SQRE = 1.
WORK (workspace) DOUBLE PRECISION array, dimension ( 4 * M )
IWORK (workspace) INTEGER array, dimension ( 3 * N )
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, a singular value did not converge
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--vf;
--vl;
--idxq;
--perm;
givcol_dim1 = *ldgcol;
givcol_offset = 1 + givcol_dim1;
givcol -= givcol_offset;
poles_dim1 = *ldgnum;
poles_offset = 1 + poles_dim1;
poles -= poles_offset;
givnum_dim1 = *ldgnum;
givnum_offset = 1 + givnum_dim1;
givnum -= givnum_offset;
--difl;
--difr;
--z__;
--work;
--iwork;
/* Function Body */
*info = 0;
n = *nl + *nr + 1;
m = n + *sqre;
if (*icompq < 0 || *icompq > 1) {
*info = -1;
} else if (*nl < 1) {
*info = -2;
} else if (*nr < 1) {
*info = -3;
} else if (*sqre < 0 || *sqre > 1) {
*info = -4;
} else if (*ldgcol < n) {
*info = -14;
} else if (*ldgnum < n) {
*info = -16;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASD6", &i__1);
return 0;
}
/*
The following values are for bookkeeping purposes only. They are
integer pointers which indicate the portion of the workspace
used by a particular array in DLASD7 and DLASD8.
*/
isigma = 1;
iw = isigma + n;
ivfw = iw + m;
ivlw = ivfw + m;
idx = 1;
idxc = idx + n;
idxp = idxc + n;
/*
Scale.
Computing MAX
*/
d__1 = abs(*alpha), d__2 = abs(*beta);
orgnrm = max(d__1,d__2);
d__[*nl + 1] = 0.;
i__1 = n;
for (i__ = 1; i__ <= i__1; ++i__) {
if ((d__1 = d__[i__], abs(d__1)) > orgnrm) {
orgnrm = (d__1 = d__[i__], abs(d__1));
}
/* L10: */
}
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, &n, &c__1, &d__[1], &n, info);
*alpha /= orgnrm;
*beta /= orgnrm;
/* Sort and Deflate singular values. */
dlasd7_(icompq, nl, nr, sqre, k, &d__[1], &z__[1], &work[iw], &vf[1], &
work[ivfw], &vl[1], &work[ivlw], alpha, beta, &work[isigma], &
iwork[idx], &iwork[idxp], &idxq[1], &perm[1], givptr, &givcol[
givcol_offset], ldgcol, &givnum[givnum_offset], ldgnum, c__, s,
info);
/* Solve Secular Equation, compute DIFL, DIFR, and update VF, VL. */
dlasd8_(icompq, k, &d__[1], &z__[1], &vf[1], &vl[1], &difl[1], &difr[1],
ldgnum, &work[isigma], &work[iw], info);
/* Save the poles if ICOMPQ = 1. */
if (*icompq == 1) {
dcopy_(k, &d__[1], &c__1, &poles[poles_dim1 + 1], &c__1);
dcopy_(k, &work[isigma], &c__1, &poles[(poles_dim1 << 1) + 1], &c__1);
}
/* Unscale. */
dlascl_("G", &c__0, &c__0, &c_b15, &orgnrm, &n, &c__1, &d__[1], &n, info);
/* Prepare the IDXQ sorting permutation. */
n1 = *k;
n2 = n - *k;
dlamrg_(&n1, &n2, &d__[1], &c__1, &c_n1, &idxq[1]);
return 0;
/* End of DLASD6 */
} /* dlasd6_ */
/* Subroutine */ int dlasd7_(integer *icompq, integer *nl, integer *nr,
integer *sqre, integer *k, doublereal *d__, doublereal *z__,
doublereal *zw, doublereal *vf, doublereal *vfw, doublereal *vl,
doublereal *vlw, doublereal *alpha, doublereal *beta, doublereal *
dsigma, integer *idx, integer *idxp, integer *idxq, integer *perm,
integer *givptr, integer *givcol, integer *ldgcol, doublereal *givnum,
integer *ldgnum, doublereal *c__, doublereal *s, integer *info)
{
/* System generated locals */
integer givcol_dim1, givcol_offset, givnum_dim1, givnum_offset, i__1;
doublereal d__1, d__2;
/* Local variables */
static integer i__, j, m, n, k2;
static doublereal z1;
static integer jp;
static doublereal eps, tau, tol;
static integer nlp1, nlp2, idxi, idxj;
extern /* Subroutine */ int drot_(integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *);
static integer idxjp;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static integer jprev;
extern /* Subroutine */ int dlamrg_(integer *, integer *, doublereal *,
integer *, integer *, integer *), xerbla_(char *, integer *);
static doublereal hlftol;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLASD7 merges the two sets of singular values together into a single
sorted set. Then it tries to deflate the size of the problem. There
are two ways in which deflation can occur: when two or more singular
values are close together or if there is a tiny entry in the Z
vector. For each such occurrence the order of the related
secular equation problem is reduced by one.
DLASD7 is called from DLASD6.
Arguments
=========
ICOMPQ (input) INTEGER
Specifies whether singular vectors are to be computed
in compact form, as follows:
= 0: Compute singular values only.
= 1: Compute singular vectors of upper
bidiagonal matrix in compact form.
NL (input) INTEGER
The row dimension of the upper block. NL >= 1.
NR (input) INTEGER
The row dimension of the lower block. NR >= 1.
SQRE (input) INTEGER
= 0: the lower block is an NR-by-NR square matrix.
= 1: the lower block is an NR-by-(NR+1) rectangular matrix.
The bidiagonal matrix has
N = NL + NR + 1 rows and
M = N + SQRE >= N columns.
K (output) INTEGER
Contains the dimension of the non-deflated matrix, this is
the order of the related secular equation. 1 <= K <=N.
D (input/output) DOUBLE PRECISION array, dimension ( N )
On entry D contains the singular values of the two submatrices
to be combined. On exit D contains the trailing (N-K) updated
singular values (those which were deflated) sorted into
increasing order.
Z (output) DOUBLE PRECISION array, dimension ( M )
On exit Z contains the updating row vector in the secular
equation.
ZW (workspace) DOUBLE PRECISION array, dimension ( M )
Workspace for Z.
VF (input/output) DOUBLE PRECISION array, dimension ( M )
On entry, VF(1:NL+1) contains the first components of all
right singular vectors of the upper block; and VF(NL+2:M)
contains the first components of all right singular vectors
of the lower block. On exit, VF contains the first components
of all right singular vectors of the bidiagonal matrix.
VFW (workspace) DOUBLE PRECISION array, dimension ( M )
Workspace for VF.
VL (input/output) DOUBLE PRECISION array, dimension ( M )
On entry, VL(1:NL+1) contains the last components of all
right singular vectors of the upper block; and VL(NL+2:M)
contains the last components of all right singular vectors
of the lower block. On exit, VL contains the last components
of all right singular vectors of the bidiagonal matrix.
VLW (workspace) DOUBLE PRECISION array, dimension ( M )
Workspace for VL.
ALPHA (input) DOUBLE PRECISION
Contains the diagonal element associated with the added row.
BETA (input) DOUBLE PRECISION
Contains the off-diagonal element associated with the added
row.
DSIGMA (output) DOUBLE PRECISION array, dimension ( N )
Contains a copy of the diagonal elements (K-1 singular values
and one zero) in the secular equation.
IDX (workspace) INTEGER array, dimension ( N )
This will contain the permutation used to sort the contents of
D into ascending order.
IDXP (workspace) INTEGER array, dimension ( N )
This will contain the permutation used to place deflated
values of D at the end of the array. On output IDXP(2:K)
points to the nondeflated D-values and IDXP(K+1:N)
points to the deflated singular values.
IDXQ (input) INTEGER array, dimension ( N )
This contains the permutation which separately sorts the two
sub-problems in D into ascending order. Note that entries in
the first half of this permutation must first be moved one
position backward; and entries in the second half
must first have NL+1 added to their values.
PERM (output) INTEGER array, dimension ( N )
The permutations (from deflation and sorting) to be applied
to each singular block. Not referenced if ICOMPQ = 0.
GIVPTR (output) INTEGER
The number of Givens rotations which took place in this
subproblem. Not referenced if ICOMPQ = 0.
GIVCOL (output) INTEGER array, dimension ( LDGCOL, 2 )
Each pair of numbers indicates a pair of columns to take place
in a Givens rotation. Not referenced if ICOMPQ = 0.
LDGCOL (input) INTEGER
The leading dimension of GIVCOL, must be at least N.
GIVNUM (output) DOUBLE PRECISION array, dimension ( LDGNUM, 2 )
Each number indicates the C or S value to be used in the
corresponding Givens rotation. Not referenced if ICOMPQ = 0.
LDGNUM (input) INTEGER
The leading dimension of GIVNUM, must be at least N.
C (output) DOUBLE PRECISION
C contains garbage if SQRE =0 and the C-value of a Givens
rotation related to the right null space if SQRE = 1.
S (output) DOUBLE PRECISION
S contains garbage if SQRE =0 and the S-value of a Givens
rotation related to the right null space if SQRE = 1.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--z__;
--zw;
--vf;
--vfw;
--vl;
--vlw;
--dsigma;
--idx;
--idxp;
--idxq;
--perm;
givcol_dim1 = *ldgcol;
givcol_offset = 1 + givcol_dim1;
givcol -= givcol_offset;
givnum_dim1 = *ldgnum;
givnum_offset = 1 + givnum_dim1;
givnum -= givnum_offset;
/* Function Body */
*info = 0;
n = *nl + *nr + 1;
m = n + *sqre;
if (*icompq < 0 || *icompq > 1) {
*info = -1;
} else if (*nl < 1) {
*info = -2;
} else if (*nr < 1) {
*info = -3;
} else if (*sqre < 0 || *sqre > 1) {
*info = -4;
} else if (*ldgcol < n) {
*info = -22;
} else if (*ldgnum < n) {
*info = -24;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASD7", &i__1);
return 0;
}
nlp1 = *nl + 1;
nlp2 = *nl + 2;
if (*icompq == 1) {
*givptr = 0;
}
/*
Generate the first part of the vector Z and move the singular
values in the first part of D one position backward.
*/
z1 = *alpha * vl[nlp1];
vl[nlp1] = 0.;
tau = vf[nlp1];
for (i__ = *nl; i__ >= 1; --i__) {
z__[i__ + 1] = *alpha * vl[i__];
vl[i__] = 0.;
vf[i__ + 1] = vf[i__];
d__[i__ + 1] = d__[i__];
idxq[i__ + 1] = idxq[i__] + 1;
/* L10: */
}
vf[1] = tau;
/* Generate the second part of the vector Z. */
i__1 = m;
for (i__ = nlp2; i__ <= i__1; ++i__) {
z__[i__] = *beta * vf[i__];
vf[i__] = 0.;
/* L20: */
}
/* Sort the singular values into increasing order */
i__1 = n;
for (i__ = nlp2; i__ <= i__1; ++i__) {
idxq[i__] += nlp1;
/* L30: */
}
/* DSIGMA, IDXC, IDXC, and ZW are used as storage space. */
i__1 = n;
for (i__ = 2; i__ <= i__1; ++i__) {
dsigma[i__] = d__[idxq[i__]];
zw[i__] = z__[idxq[i__]];
vfw[i__] = vf[idxq[i__]];
vlw[i__] = vl[idxq[i__]];
/* L40: */
}
dlamrg_(nl, nr, &dsigma[2], &c__1, &c__1, &idx[2]);
i__1 = n;
for (i__ = 2; i__ <= i__1; ++i__) {
idxi = idx[i__] + 1;
d__[i__] = dsigma[idxi];
z__[i__] = zw[idxi];
vf[i__] = vfw[idxi];
vl[i__] = vlw[idxi];
/* L50: */
}
/* Calculate the allowable deflation tolerence */
eps = EPSILON;
/* Computing MAX */
d__1 = abs(*alpha), d__2 = abs(*beta);
tol = max(d__1,d__2);
/* Computing MAX */
d__2 = (d__1 = d__[n], abs(d__1));
tol = eps * 64. * max(d__2,tol);
/*
There are 2 kinds of deflation -- first a value in the z-vector
is small, second two (or more) singular values are very close
together (their difference is small).
If the value in the z-vector is small, we simply permute the
array so that the corresponding singular value is moved to the
end.
If two values in the D-vector are close, we perform a two-sided
rotation designed to make one of the corresponding z-vector
entries zero, and then permute the array so that the deflated
singular value is moved to the end.
If there are multiple singular values then the problem deflates.
Here the number of equal singular values are found. As each equal
singular value is found, an elementary reflector is computed to
rotate the corresponding singular subspace so that the
corresponding components of Z are zero in this new basis.
*/
*k = 1;
k2 = n + 1;
i__1 = n;
for (j = 2; j <= i__1; ++j) {
if ((d__1 = z__[j], abs(d__1)) <= tol) {
/* Deflate due to small z component. */
--k2;
idxp[k2] = j;
if (j == n) {
goto L100;
}
} else {
jprev = j;
goto L70;
}
/* L60: */
}
L70:
j = jprev;
L80:
++j;
if (j > n) {
goto L90;
}
if ((d__1 = z__[j], abs(d__1)) <= tol) {
/* Deflate due to small z component. */
--k2;
idxp[k2] = j;
} else {
/* Check if singular values are close enough to allow deflation. */
if ((d__1 = d__[j] - d__[jprev], abs(d__1)) <= tol) {
/* Deflation is possible. */
*s = z__[jprev];
*c__ = z__[j];
/*
Find sqrt(a**2+b**2) without overflow or
destructive underflow.
*/
tau = dlapy2_(c__, s);
z__[j] = tau;
z__[jprev] = 0.;
*c__ /= tau;
*s = -(*s) / tau;
/* Record the appropriate Givens rotation */
if (*icompq == 1) {
++(*givptr);
idxjp = idxq[idx[jprev] + 1];
idxj = idxq[idx[j] + 1];
if (idxjp <= nlp1) {
--idxjp;
}
if (idxj <= nlp1) {
--idxj;
}
givcol[*givptr + (givcol_dim1 << 1)] = idxjp;
givcol[*givptr + givcol_dim1] = idxj;
givnum[*givptr + (givnum_dim1 << 1)] = *c__;
givnum[*givptr + givnum_dim1] = *s;
}
drot_(&c__1, &vf[jprev], &c__1, &vf[j], &c__1, c__, s);
drot_(&c__1, &vl[jprev], &c__1, &vl[j], &c__1, c__, s);
--k2;
idxp[k2] = jprev;
jprev = j;
} else {
++(*k);
zw[*k] = z__[jprev];
dsigma[*k] = d__[jprev];
idxp[*k] = jprev;
jprev = j;
}
}
goto L80;
L90:
/* Record the last singular value. */
++(*k);
zw[*k] = z__[jprev];
dsigma[*k] = d__[jprev];
idxp[*k] = jprev;
L100:
/*
Sort the singular values into DSIGMA. The singular values which
were not deflated go into the first K slots of DSIGMA, except
that DSIGMA(1) is treated separately.
*/
i__1 = n;
for (j = 2; j <= i__1; ++j) {
jp = idxp[j];
dsigma[j] = d__[jp];
vfw[j] = vf[jp];
vlw[j] = vl[jp];
/* L110: */
}
if (*icompq == 1) {
i__1 = n;
for (j = 2; j <= i__1; ++j) {
jp = idxp[j];
perm[j] = idxq[idx[jp] + 1];
if (perm[j] <= nlp1) {
--perm[j];
}
/* L120: */
}
}
/*
The deflated singular values go back into the last N - K slots of
D.
*/
i__1 = n - *k;
dcopy_(&i__1, &dsigma[*k + 1], &c__1, &d__[*k + 1], &c__1);
/*
Determine DSIGMA(1), DSIGMA(2), Z(1), VF(1), VL(1), VF(M), and
VL(M).
*/
dsigma[1] = 0.;
hlftol = tol / 2.;
if (abs(dsigma[2]) <= hlftol) {
dsigma[2] = hlftol;
}
if (m > n) {
z__[1] = dlapy2_(&z1, &z__[m]);
if (z__[1] <= tol) {
*c__ = 1.;
*s = 0.;
z__[1] = tol;
} else {
*c__ = z1 / z__[1];
*s = -z__[m] / z__[1];
}
drot_(&c__1, &vf[m], &c__1, &vf[1], &c__1, c__, s);
drot_(&c__1, &vl[m], &c__1, &vl[1], &c__1, c__, s);
} else {
if (abs(z1) <= tol) {
z__[1] = tol;
} else {
z__[1] = z1;
}
}
/* Restore Z, VF, and VL. */
i__1 = *k - 1;
dcopy_(&i__1, &zw[2], &c__1, &z__[2], &c__1);
i__1 = n - 1;
dcopy_(&i__1, &vfw[2], &c__1, &vf[2], &c__1);
i__1 = n - 1;
dcopy_(&i__1, &vlw[2], &c__1, &vl[2], &c__1);
return 0;
/* End of DLASD7 */
} /* dlasd7_ */
/* Subroutine */ int dlasd8_(integer *icompq, integer *k, doublereal *d__,
doublereal *z__, doublereal *vf, doublereal *vl, doublereal *difl,
doublereal *difr, integer *lddifr, doublereal *dsigma, doublereal *
work, integer *info)
{
/* System generated locals */
integer difr_dim1, difr_offset, i__1, i__2;
doublereal d__1, d__2;
/* Local variables */
static integer i__, j;
static doublereal dj, rho;
static integer iwk1, iwk2, iwk3;
extern doublereal ddot_(integer *, doublereal *, integer *, doublereal *,
integer *);
static doublereal temp;
extern doublereal dnrm2_(integer *, doublereal *, integer *);
static integer iwk2i, iwk3i;
static doublereal diflj, difrj, dsigj;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
extern doublereal dlamc3_(doublereal *, doublereal *);
extern /* Subroutine */ int dlasd4_(integer *, integer *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *), dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *), dlaset_(char *, integer *, integer
*, doublereal *, doublereal *, doublereal *, integer *),
xerbla_(char *, integer *);
static doublereal dsigjp;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLASD8 finds the square roots of the roots of the secular equation,
as defined by the values in DSIGMA and Z. It makes the appropriate
calls to DLASD4, and stores, for each element in D, the distance
to its two nearest poles (elements in DSIGMA). It also updates
the arrays VF and VL, the first and last components of all the
right singular vectors of the original bidiagonal matrix.
DLASD8 is called from DLASD6.
Arguments
=========
ICOMPQ (input) INTEGER
Specifies whether singular vectors are to be computed in
factored form in the calling routine:
= 0: Compute singular values only.
= 1: Compute singular vectors in factored form as well.
K (input) INTEGER
The number of terms in the rational function to be solved
by DLASD4. K >= 1.
D (output) DOUBLE PRECISION array, dimension ( K )
On output, D contains the updated singular values.
Z (input/output) DOUBLE PRECISION array, dimension ( K )
On entry, the first K elements of this array contain the
components of the deflation-adjusted updating row vector.
On exit, Z is updated.
VF (input/output) DOUBLE PRECISION array, dimension ( K )
On entry, VF contains information passed through DBEDE8.
On exit, VF contains the first K components of the first
components of all right singular vectors of the bidiagonal
matrix.
VL (input/output) DOUBLE PRECISION array, dimension ( K )
On entry, VL contains information passed through DBEDE8.
On exit, VL contains the first K components of the last
components of all right singular vectors of the bidiagonal
matrix.
DIFL (output) DOUBLE PRECISION array, dimension ( K )
On exit, DIFL(I) = D(I) - DSIGMA(I).
DIFR (output) DOUBLE PRECISION array,
dimension ( LDDIFR, 2 ) if ICOMPQ = 1 and
dimension ( K ) if ICOMPQ = 0.
On exit, DIFR(I,1) = D(I) - DSIGMA(I+1), DIFR(K,1) is not
defined and will not be referenced.
If ICOMPQ = 1, DIFR(1:K,2) is an array containing the
normalizing factors for the right singular vector matrix.
LDDIFR (input) INTEGER
The leading dimension of DIFR, must be at least K.
DSIGMA (input/output) DOUBLE PRECISION array, dimension ( K )
On entry, the first K elements of this array contain the old
roots of the deflated updating problem. These are the poles
of the secular equation.
On exit, the elements of DSIGMA may be very slightly altered
in value.
WORK (workspace) DOUBLE PRECISION array, dimension at least 3 * K
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, a singular value did not converge
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--z__;
--vf;
--vl;
--difl;
difr_dim1 = *lddifr;
difr_offset = 1 + difr_dim1;
difr -= difr_offset;
--dsigma;
--work;
/* Function Body */
*info = 0;
if (*icompq < 0 || *icompq > 1) {
*info = -1;
} else if (*k < 1) {
*info = -2;
} else if (*lddifr < *k) {
*info = -9;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASD8", &i__1);
return 0;
}
/* Quick return if possible */
if (*k == 1) {
d__[1] = abs(z__[1]);
difl[1] = d__[1];
if (*icompq == 1) {
difl[2] = 1.;
difr[(difr_dim1 << 1) + 1] = 1.;
}
return 0;
}
/*
Modify values DSIGMA(i) to make sure all DSIGMA(i)-DSIGMA(j) can
be computed with high relative accuracy (barring over/underflow).
This is a problem on machines without a guard digit in
add/subtract (Cray XMP, Cray YMP, Cray C 90 and Cray 2).
The following code replaces DSIGMA(I) by 2*DSIGMA(I)-DSIGMA(I),
which on any of these machines zeros out the bottommost
bit of DSIGMA(I) if it is 1; this makes the subsequent
subtractions DSIGMA(I)-DSIGMA(J) unproblematic when cancellation
occurs. On binary machines with a guard digit (almost all
machines) it does not change DSIGMA(I) at all. On hexadecimal
and decimal machines with a guard digit, it slightly
changes the bottommost bits of DSIGMA(I). It does not account
for hexadecimal or decimal machines without guard digits
(we know of none). We use a subroutine call to compute
2*DLAMBDA(I) to prevent optimizing compilers from eliminating
this code.
*/
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
dsigma[i__] = dlamc3_(&dsigma[i__], &dsigma[i__]) - dsigma[i__];
/* L10: */
}
/* Book keeping. */
iwk1 = 1;
iwk2 = iwk1 + *k;
iwk3 = iwk2 + *k;
iwk2i = iwk2 - 1;
iwk3i = iwk3 - 1;
/* Normalize Z. */
rho = dnrm2_(k, &z__[1], &c__1);
dlascl_("G", &c__0, &c__0, &rho, &c_b15, k, &c__1, &z__[1], k, info);
rho *= rho;
/* Initialize WORK(IWK3). */
dlaset_("A", k, &c__1, &c_b15, &c_b15, &work[iwk3], k);
/*
Compute the updated singular values, the arrays DIFL, DIFR,
and the updated Z.
*/
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
dlasd4_(k, &j, &dsigma[1], &z__[1], &work[iwk1], &rho, &d__[j], &work[
iwk2], info);
/* If the root finder fails, the computation is terminated. */
if (*info != 0) {
return 0;
}
work[iwk3i + j] = work[iwk3i + j] * work[j] * work[iwk2i + j];
difl[j] = -work[j];
difr[j + difr_dim1] = -work[j + 1];
i__2 = j - 1;
for (i__ = 1; i__ <= i__2; ++i__) {
work[iwk3i + i__] = work[iwk3i + i__] * work[i__] * work[iwk2i +
i__] / (dsigma[i__] - dsigma[j]) / (dsigma[i__] + dsigma[
j]);
/* L20: */
}
i__2 = *k;
for (i__ = j + 1; i__ <= i__2; ++i__) {
work[iwk3i + i__] = work[iwk3i + i__] * work[i__] * work[iwk2i +
i__] / (dsigma[i__] - dsigma[j]) / (dsigma[i__] + dsigma[
j]);
/* L30: */
}
/* L40: */
}
/* Compute updated Z. */
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
d__2 = sqrt((d__1 = work[iwk3i + i__], abs(d__1)));
z__[i__] = d_sign(&d__2, &z__[i__]);
/* L50: */
}
/* Update VF and VL. */
i__1 = *k;
for (j = 1; j <= i__1; ++j) {
diflj = difl[j];
dj = d__[j];
dsigj = -dsigma[j];
if (j < *k) {
difrj = -difr[j + difr_dim1];
dsigjp = -dsigma[j + 1];
}
work[j] = -z__[j] / diflj / (dsigma[j] + dj);
i__2 = j - 1;
for (i__ = 1; i__ <= i__2; ++i__) {
work[i__] = z__[i__] / (dlamc3_(&dsigma[i__], &dsigj) - diflj) / (
dsigma[i__] + dj);
/* L60: */
}
i__2 = *k;
for (i__ = j + 1; i__ <= i__2; ++i__) {
work[i__] = z__[i__] / (dlamc3_(&dsigma[i__], &dsigjp) + difrj) /
(dsigma[i__] + dj);
/* L70: */
}
temp = dnrm2_(k, &work[1], &c__1);
work[iwk2i + j] = ddot_(k, &work[1], &c__1, &vf[1], &c__1) / temp;
work[iwk3i + j] = ddot_(k, &work[1], &c__1, &vl[1], &c__1) / temp;
if (*icompq == 1) {
difr[j + (difr_dim1 << 1)] = temp;
}
/* L80: */
}
dcopy_(k, &work[iwk2], &c__1, &vf[1], &c__1);
dcopy_(k, &work[iwk3], &c__1, &vl[1], &c__1);
return 0;
/* End of DLASD8 */
} /* dlasd8_ */
/* Subroutine */ int dlasda_(integer *icompq, integer *smlsiz, integer *n,
integer *sqre, doublereal *d__, doublereal *e, doublereal *u, integer
*ldu, doublereal *vt, integer *k, doublereal *difl, doublereal *difr,
doublereal *z__, doublereal *poles, integer *givptr, integer *givcol,
integer *ldgcol, integer *perm, doublereal *givnum, doublereal *c__,
doublereal *s, doublereal *work, integer *iwork, integer *info)
{
/* System generated locals */
integer givcol_dim1, givcol_offset, perm_dim1, perm_offset, difl_dim1,
difl_offset, difr_dim1, difr_offset, givnum_dim1, givnum_offset,
poles_dim1, poles_offset, u_dim1, u_offset, vt_dim1, vt_offset,
z_dim1, z_offset, i__1, i__2;
/* Local variables */
static integer i__, j, m, i1, ic, lf, nd, ll, nl, vf, nr, vl, im1, ncc,
nlf, nrf, vfi, iwk, vli, lvl, nru, ndb1, nlp1, lvl2, nrp1;
static doublereal beta;
static integer idxq, nlvl;
static doublereal alpha;
static integer inode, ndiml, ndimr, idxqi, itemp;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static integer sqrei;
extern /* Subroutine */ int dlasd6_(integer *, integer *, integer *,
integer *, doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, integer *, integer *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
doublereal *, doublereal *, integer *, doublereal *, doublereal *,
doublereal *, integer *, integer *);
static integer nwork1, nwork2;
extern /* Subroutine */ int dlasdq_(char *, integer *, integer *, integer
*, integer *, integer *, doublereal *, doublereal *, doublereal *,
integer *, doublereal *, integer *, doublereal *, integer *,
doublereal *, integer *), dlasdt_(integer *, integer *,
integer *, integer *, integer *, integer *, integer *), dlaset_(
char *, integer *, integer *, doublereal *, doublereal *,
doublereal *, integer *), xerbla_(char *, integer *);
static integer smlszp;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
Using a divide and conquer approach, DLASDA computes the singular
value decomposition (SVD) of a real upper bidiagonal N-by-M matrix
B with diagonal D and offdiagonal E, where M = N + SQRE. The
algorithm computes the singular values in the SVD B = U * S * VT.
The orthogonal matrices U and VT are optionally computed in
compact form.
A related subroutine, DLASD0, computes the singular values and
the singular vectors in explicit form.
Arguments
=========
ICOMPQ (input) INTEGER
Specifies whether singular vectors are to be computed
in compact form, as follows
= 0: Compute singular values only.
= 1: Compute singular vectors of upper bidiagonal
matrix in compact form.
SMLSIZ (input) INTEGER
The maximum size of the subproblems at the bottom of the
computation tree.
N (input) INTEGER
The row dimension of the upper bidiagonal matrix. This is
also the dimension of the main diagonal array D.
SQRE (input) INTEGER
Specifies the column dimension of the bidiagonal matrix.
= 0: The bidiagonal matrix has column dimension M = N;
= 1: The bidiagonal matrix has column dimension M = N + 1.
D (input/output) DOUBLE PRECISION array, dimension ( N )
On entry D contains the main diagonal of the bidiagonal
matrix. On exit D, if INFO = 0, contains its singular values.
E (input) DOUBLE PRECISION array, dimension ( M-1 )
Contains the subdiagonal entries of the bidiagonal matrix.
On exit, E has been destroyed.
U (output) DOUBLE PRECISION array,
dimension ( LDU, SMLSIZ ) if ICOMPQ = 1, and not referenced
if ICOMPQ = 0. If ICOMPQ = 1, on exit, U contains the left
singular vector matrices of all subproblems at the bottom
level.
LDU (input) INTEGER, LDU = > N.
The leading dimension of arrays U, VT, DIFL, DIFR, POLES,
GIVNUM, and Z.
VT (output) DOUBLE PRECISION array,
dimension ( LDU, SMLSIZ+1 ) if ICOMPQ = 1, and not referenced
if ICOMPQ = 0. If ICOMPQ = 1, on exit, VT' contains the right
singular vector matrices of all subproblems at the bottom
level.
K (output) INTEGER array,
dimension ( N ) if ICOMPQ = 1 and dimension 1 if ICOMPQ = 0.
If ICOMPQ = 1, on exit, K(I) is the dimension of the I-th
secular equation on the computation tree.
DIFL (output) DOUBLE PRECISION array, dimension ( LDU, NLVL ),
where NLVL = floor(log_2 (N/SMLSIZ))).
DIFR (output) DOUBLE PRECISION array,
dimension ( LDU, 2 * NLVL ) if ICOMPQ = 1 and
dimension ( N ) if ICOMPQ = 0.
If ICOMPQ = 1, on exit, DIFL(1:N, I) and DIFR(1:N, 2 * I - 1)
record distances between singular values on the I-th
level and singular values on the (I -1)-th level, and
DIFR(1:N, 2 * I ) contains the normalizing factors for
the right singular vector matrix. See DLASD8 for details.
Z (output) DOUBLE PRECISION array,
dimension ( LDU, NLVL ) if ICOMPQ = 1 and
dimension ( N ) if ICOMPQ = 0.
The first K elements of Z(1, I) contain the components of
the deflation-adjusted updating row vector for subproblems
on the I-th level.
POLES (output) DOUBLE PRECISION array,
dimension ( LDU, 2 * NLVL ) if ICOMPQ = 1, and not referenced
if ICOMPQ = 0. If ICOMPQ = 1, on exit, POLES(1, 2*I - 1) and
POLES(1, 2*I) contain the new and old singular values
involved in the secular equations on the I-th level.
GIVPTR (output) INTEGER array,
dimension ( N ) if ICOMPQ = 1, and not referenced if
ICOMPQ = 0. If ICOMPQ = 1, on exit, GIVPTR( I ) records
the number of Givens rotations performed on the I-th
problem on the computation tree.
GIVCOL (output) INTEGER array,
dimension ( LDGCOL, 2 * NLVL ) if ICOMPQ = 1, and not
referenced if ICOMPQ = 0. If ICOMPQ = 1, on exit, for each I,
GIVCOL(1, 2 *I - 1) and GIVCOL(1, 2 *I) record the locations
of Givens rotations performed on the I-th level on the
computation tree.
LDGCOL (input) INTEGER, LDGCOL = > N.
The leading dimension of arrays GIVCOL and PERM.
PERM (output) INTEGER array,
dimension ( LDGCOL, NLVL ) if ICOMPQ = 1, and not referenced
if ICOMPQ = 0. If ICOMPQ = 1, on exit, PERM(1, I) records
permutations done on the I-th level of the computation tree.
GIVNUM (output) DOUBLE PRECISION array,
dimension ( LDU, 2 * NLVL ) if ICOMPQ = 1, and not
referenced if ICOMPQ = 0. If ICOMPQ = 1, on exit, for each I,
GIVNUM(1, 2 *I - 1) and GIVNUM(1, 2 *I) record the C- and S-
values of Givens rotations performed on the I-th level on
the computation tree.
C (output) DOUBLE PRECISION array,
dimension ( N ) if ICOMPQ = 1, and dimension 1 if ICOMPQ = 0.
If ICOMPQ = 1 and the I-th subproblem is not square, on exit,
C( I ) contains the C-value of a Givens rotation related to
the right null space of the I-th subproblem.
S (output) DOUBLE PRECISION array, dimension ( N ) if
ICOMPQ = 1, and dimension 1 if ICOMPQ = 0. If ICOMPQ = 1
and the I-th subproblem is not square, on exit, S( I )
contains the S-value of a Givens rotation related to
the right null space of the I-th subproblem.
WORK (workspace) DOUBLE PRECISION array, dimension
(6 * N + (SMLSIZ + 1)*(SMLSIZ + 1)).
IWORK (workspace) INTEGER array.
Dimension must be at least (7 * N).
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: if INFO = 1, a singular value did not converge
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--e;
givnum_dim1 = *ldu;
givnum_offset = 1 + givnum_dim1;
givnum -= givnum_offset;
poles_dim1 = *ldu;
poles_offset = 1 + poles_dim1;
poles -= poles_offset;
z_dim1 = *ldu;
z_offset = 1 + z_dim1;
z__ -= z_offset;
difr_dim1 = *ldu;
difr_offset = 1 + difr_dim1;
difr -= difr_offset;
difl_dim1 = *ldu;
difl_offset = 1 + difl_dim1;
difl -= difl_offset;
vt_dim1 = *ldu;
vt_offset = 1 + vt_dim1;
vt -= vt_offset;
u_dim1 = *ldu;
u_offset = 1 + u_dim1;
u -= u_offset;
--k;
--givptr;
perm_dim1 = *ldgcol;
perm_offset = 1 + perm_dim1;
perm -= perm_offset;
givcol_dim1 = *ldgcol;
givcol_offset = 1 + givcol_dim1;
givcol -= givcol_offset;
--c__;
--s;
--work;
--iwork;
/* Function Body */
*info = 0;
if (*icompq < 0 || *icompq > 1) {
*info = -1;
} else if (*smlsiz < 3) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*sqre < 0 || *sqre > 1) {
*info = -4;
} else if (*ldu < *n + *sqre) {
*info = -8;
} else if (*ldgcol < *n) {
*info = -17;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASDA", &i__1);
return 0;
}
m = *n + *sqre;
/* If the input matrix is too small, call DLASDQ to find the SVD. */
if (*n <= *smlsiz) {
if (*icompq == 0) {
dlasdq_("U", sqre, n, &c__0, &c__0, &c__0, &d__[1], &e[1], &vt[
vt_offset], ldu, &u[u_offset], ldu, &u[u_offset], ldu, &
work[1], info);
} else {
dlasdq_("U", sqre, n, &m, n, &c__0, &d__[1], &e[1], &vt[vt_offset]
, ldu, &u[u_offset], ldu, &u[u_offset], ldu, &work[1],
info);
}
return 0;
}
/* Book-keeping and set up the computation tree. */
inode = 1;
ndiml = inode + *n;
ndimr = ndiml + *n;
idxq = ndimr + *n;
iwk = idxq + *n;
ncc = 0;
nru = 0;
smlszp = *smlsiz + 1;
vf = 1;
vl = vf + m;
nwork1 = vl + m;
nwork2 = nwork1 + smlszp * smlszp;
dlasdt_(n, &nlvl, &nd, &iwork[inode], &iwork[ndiml], &iwork[ndimr],
smlsiz);
/*
for the nodes on bottom level of the tree, solve
their subproblems by DLASDQ.
*/
ndb1 = (nd + 1) / 2;
i__1 = nd;
for (i__ = ndb1; i__ <= i__1; ++i__) {
/*
IC : center row of each node
NL : number of rows of left subproblem
NR : number of rows of right subproblem
NLF: starting row of the left subproblem
NRF: starting row of the right subproblem
*/
i1 = i__ - 1;
ic = iwork[inode + i1];
nl = iwork[ndiml + i1];
nlp1 = nl + 1;
nr = iwork[ndimr + i1];
nlf = ic - nl;
nrf = ic + 1;
idxqi = idxq + nlf - 2;
vfi = vf + nlf - 1;
vli = vl + nlf - 1;
sqrei = 1;
if (*icompq == 0) {
dlaset_("A", &nlp1, &nlp1, &c_b29, &c_b15, &work[nwork1], &smlszp);
dlasdq_("U", &sqrei, &nl, &nlp1, &nru, &ncc, &d__[nlf], &e[nlf], &
work[nwork1], &smlszp, &work[nwork2], &nl, &work[nwork2],
&nl, &work[nwork2], info);
itemp = nwork1 + nl * smlszp;
dcopy_(&nlp1, &work[nwork1], &c__1, &work[vfi], &c__1);
dcopy_(&nlp1, &work[itemp], &c__1, &work[vli], &c__1);
} else {
dlaset_("A", &nl, &nl, &c_b29, &c_b15, &u[nlf + u_dim1], ldu);
dlaset_("A", &nlp1, &nlp1, &c_b29, &c_b15, &vt[nlf + vt_dim1],
ldu);
dlasdq_("U", &sqrei, &nl, &nlp1, &nl, &ncc, &d__[nlf], &e[nlf], &
vt[nlf + vt_dim1], ldu, &u[nlf + u_dim1], ldu, &u[nlf +
u_dim1], ldu, &work[nwork1], info);
dcopy_(&nlp1, &vt[nlf + vt_dim1], &c__1, &work[vfi], &c__1);
dcopy_(&nlp1, &vt[nlf + nlp1 * vt_dim1], &c__1, &work[vli], &c__1)
;
}
if (*info != 0) {
return 0;
}
i__2 = nl;
for (j = 1; j <= i__2; ++j) {
iwork[idxqi + j] = j;
/* L10: */
}
if (i__ == nd && *sqre == 0) {
sqrei = 0;
} else {
sqrei = 1;
}
idxqi += nlp1;
vfi += nlp1;
vli += nlp1;
nrp1 = nr + sqrei;
if (*icompq == 0) {
dlaset_("A", &nrp1, &nrp1, &c_b29, &c_b15, &work[nwork1], &smlszp);
dlasdq_("U", &sqrei, &nr, &nrp1, &nru, &ncc, &d__[nrf], &e[nrf], &
work[nwork1], &smlszp, &work[nwork2], &nr, &work[nwork2],
&nr, &work[nwork2], info);
itemp = nwork1 + (nrp1 - 1) * smlszp;
dcopy_(&nrp1, &work[nwork1], &c__1, &work[vfi], &c__1);
dcopy_(&nrp1, &work[itemp], &c__1, &work[vli], &c__1);
} else {
dlaset_("A", &nr, &nr, &c_b29, &c_b15, &u[nrf + u_dim1], ldu);
dlaset_("A", &nrp1, &nrp1, &c_b29, &c_b15, &vt[nrf + vt_dim1],
ldu);
dlasdq_("U", &sqrei, &nr, &nrp1, &nr, &ncc, &d__[nrf], &e[nrf], &
vt[nrf + vt_dim1], ldu, &u[nrf + u_dim1], ldu, &u[nrf +
u_dim1], ldu, &work[nwork1], info);
dcopy_(&nrp1, &vt[nrf + vt_dim1], &c__1, &work[vfi], &c__1);
dcopy_(&nrp1, &vt[nrf + nrp1 * vt_dim1], &c__1, &work[vli], &c__1)
;
}
if (*info != 0) {
return 0;
}
i__2 = nr;
for (j = 1; j <= i__2; ++j) {
iwork[idxqi + j] = j;
/* L20: */
}
/* L30: */
}
/* Now conquer each subproblem bottom-up. */
j = pow_ii(&c__2, &nlvl);
for (lvl = nlvl; lvl >= 1; --lvl) {
lvl2 = (lvl << 1) - 1;
/*
Find the first node LF and last node LL on
the current level LVL.
*/
if (lvl == 1) {
lf = 1;
ll = 1;
} else {
i__1 = lvl - 1;
lf = pow_ii(&c__2, &i__1);
ll = (lf << 1) - 1;
}
i__1 = ll;
for (i__ = lf; i__ <= i__1; ++i__) {
im1 = i__ - 1;
ic = iwork[inode + im1];
nl = iwork[ndiml + im1];
nr = iwork[ndimr + im1];
nlf = ic - nl;
nrf = ic + 1;
if (i__ == ll) {
sqrei = *sqre;
} else {
sqrei = 1;
}
vfi = vf + nlf - 1;
vli = vl + nlf - 1;
idxqi = idxq + nlf - 1;
alpha = d__[ic];
beta = e[ic];
if (*icompq == 0) {
dlasd6_(icompq, &nl, &nr, &sqrei, &d__[nlf], &work[vfi], &
work[vli], &alpha, &beta, &iwork[idxqi], &perm[
perm_offset], &givptr[1], &givcol[givcol_offset],
ldgcol, &givnum[givnum_offset], ldu, &poles[
poles_offset], &difl[difl_offset], &difr[difr_offset],
&z__[z_offset], &k[1], &c__[1], &s[1], &work[nwork1],
&iwork[iwk], info);
} else {
--j;
dlasd6_(icompq, &nl, &nr, &sqrei, &d__[nlf], &work[vfi], &
work[vli], &alpha, &beta, &iwork[idxqi], &perm[nlf +
lvl * perm_dim1], &givptr[j], &givcol[nlf + lvl2 *
givcol_dim1], ldgcol, &givnum[nlf + lvl2 *
givnum_dim1], ldu, &poles[nlf + lvl2 * poles_dim1], &
difl[nlf + lvl * difl_dim1], &difr[nlf + lvl2 *
difr_dim1], &z__[nlf + lvl * z_dim1], &k[j], &c__[j],
&s[j], &work[nwork1], &iwork[iwk], info);
}
if (*info != 0) {
return 0;
}
/* L40: */
}
/* L50: */
}
return 0;
/* End of DLASDA */
} /* dlasda_ */
/* 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 */
static integer i__, j;
static doublereal r__, cs, sn;
static integer np1, isub;
static doublereal smin;
static 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 *);
static 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 *);
static logical rotate;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
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
=====================================================================
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_ */
/* Subroutine */ int dlasdt_(integer *n, integer *lvl, integer *nd, integer *
inode, integer *ndiml, integer *ndimr, integer *msub)
{
/* System generated locals */
integer i__1, i__2;
/* Local variables */
static integer i__, il, ir, maxn;
static doublereal temp;
static integer nlvl, llst, ncrnt;
/*
-- LAPACK auxiliary routine (version 3.2.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
June 2010
Purpose
=======
DLASDT creates a tree of subproblems for bidiagonal divide and
conquer.
Arguments
=========
N (input) INTEGER
On entry, the number of diagonal elements of the
bidiagonal matrix.
LVL (output) INTEGER
On exit, the number of levels on the computation tree.
ND (output) INTEGER
On exit, the number of nodes on the tree.
INODE (output) INTEGER array, dimension ( N )
On exit, centers of subproblems.
NDIML (output) INTEGER array, dimension ( N )
On exit, row dimensions of left children.
NDIMR (output) INTEGER array, dimension ( N )
On exit, row dimensions of right children.
MSUB (input) INTEGER
On entry, the maximum row dimension each subproblem at the
bottom of the tree can be of.
Further Details
===============
Based on contributions by
Ming Gu and Huan Ren, Computer Science Division, University of
California at Berkeley, USA
=====================================================================
Find the number of levels on the tree.
*/
/* Parameter adjustments */
--ndimr;
--ndiml;
--inode;
/* Function Body */
maxn = max(1,*n);
temp = log((doublereal) maxn / (doublereal) (*msub + 1)) / log(2.);
*lvl = (integer) temp + 1;
i__ = *n / 2;
inode[1] = i__ + 1;
ndiml[1] = i__;
ndimr[1] = *n - i__ - 1;
il = 0;
ir = 1;
llst = 1;
i__1 = *lvl - 1;
for (nlvl = 1; nlvl <= i__1; ++nlvl) {
/*
Constructing the tree at (NLVL+1)-st level. The number of
nodes created on this level is LLST * 2.
*/
i__2 = llst - 1;
for (i__ = 0; i__ <= i__2; ++i__) {
il += 2;
ir += 2;
ncrnt = llst + i__;
ndiml[il] = ndiml[ncrnt] / 2;
ndimr[il] = ndiml[ncrnt] - ndiml[il] - 1;
inode[il] = inode[ncrnt] - ndimr[il] - 1;
ndiml[ir] = ndimr[ncrnt] / 2;
ndimr[ir] = ndimr[ncrnt] - ndiml[ir] - 1;
inode[ir] = inode[ncrnt] + ndiml[ir] + 1;
/* L10: */
}
llst <<= 1;
/* L20: */
}
*nd = (llst << 1) - 1;
return 0;
/* End of DLASDT */
} /* dlasdt_ */
/* Subroutine */ int dlaset_(char *uplo, integer *m, integer *n, doublereal *
alpha, doublereal *beta, doublereal *a, integer *lda)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__, j;
extern logical lsame_(char *, char *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLASET initializes an m-by-n matrix A to BETA on the diagonal and
ALPHA on the offdiagonals.
Arguments
=========
UPLO (input) CHARACTER*1
Specifies the part of the matrix A to be set.
= 'U': Upper triangular part is set; the strictly lower
triangular part of A is not changed.
= 'L': Lower triangular part is set; the strictly upper
triangular part of A is not changed.
Otherwise: All of the matrix A is set.
M (input) INTEGER
The number of rows of the matrix A. M >= 0.
N (input) INTEGER
The number of columns of the matrix A. N >= 0.
ALPHA (input) DOUBLE PRECISION
The constant to which the offdiagonal elements are to be set.
BETA (input) DOUBLE PRECISION
The constant to which the diagonal elements are to be set.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On exit, the leading m-by-n submatrix of A is set as follows:
if UPLO = 'U', A(i,j) = ALPHA, 1<=i<=j-1, 1<=j<=n,
if UPLO = 'L', A(i,j) = ALPHA, j+1<=i<=m, 1<=j<=n,
otherwise, A(i,j) = ALPHA, 1<=i<=m, 1<=j<=n, i.ne.j,
and, for all UPLO, A(i,i) = BETA, 1<=i<=min(m,n).
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
=====================================================================
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
if (lsame_(uplo, "U")) {
/*
Set the strictly upper triangular or trapezoidal part of the
array to ALPHA.
*/
i__1 = *n;
for (j = 2; j <= i__1; ++j) {
/* Computing MIN */
i__3 = j - 1;
i__2 = min(i__3,*m);
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = *alpha;
/* L10: */
}
/* L20: */
}
} else if (lsame_(uplo, "L")) {
/*
Set the strictly lower triangular or trapezoidal part of the
array to ALPHA.
*/
i__1 = min(*m,*n);
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = j + 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = *alpha;
/* L30: */
}
/* L40: */
}
} else {
/* Set the leading m-by-n submatrix to ALPHA. */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = *alpha;
/* L50: */
}
/* L60: */
}
}
/* Set the first min(M,N) diagonal elements to BETA. */
i__1 = min(*m,*n);
for (i__ = 1; i__ <= i__1; ++i__) {
a[i__ + i__ * a_dim1] = *beta;
/* L70: */
}
return 0;
/* End of DLASET */
} /* dlaset_ */
/* Subroutine */ int dlasq1_(integer *n, doublereal *d__, doublereal *e,
doublereal *work, integer *info)
{
/* System generated locals */
integer i__1, i__2;
doublereal d__1, d__2, d__3;
/* Local variables */
static integer i__;
static doublereal eps;
extern /* Subroutine */ int dlas2_(doublereal *, doublereal *, doublereal
*, doublereal *, doublereal *);
static doublereal scale;
static integer iinfo;
static doublereal sigmn;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static doublereal sigmx;
extern /* Subroutine */ int dlasq2_(integer *, doublereal *, integer *);
extern /* Subroutine */ int dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *);
static doublereal safmin;
extern /* Subroutine */ int xerbla_(char *, integer *), dlasrt_(
char *, integer *, doublereal *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- Contributed by Osni Marques of the Lawrence Berkeley National --
-- Laboratory and Beresford Parlett of the Univ. of California at --
-- Berkeley --
-- November 2008 --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
Purpose
=======
DLASQ1 computes the singular values of a real N-by-N bidiagonal
matrix with diagonal D and off-diagonal E. The singular values
are computed to high relative accuracy, in the absence of
denormalization, underflow and overflow. The algorithm was first
presented in
"Accurate singular values and differential qd algorithms" by K. V.
Fernando and B. N. Parlett, Numer. Math., Vol-67, No. 2, pp. 191-230,
1994,
and the present implementation is described in "An implementation of
the dqds Algorithm (Positive Case)", LAPACK Working Note.
Arguments
=========
N (input) INTEGER
The number of rows and columns in the matrix. N >= 0.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, D contains the diagonal elements of the
bidiagonal matrix whose SVD is desired. On normal exit,
D contains the singular values in decreasing order.
E (input/output) DOUBLE PRECISION array, dimension (N)
On entry, elements E(1:N-1) contain the off-diagonal elements
of the bidiagonal matrix whose SVD is desired.
On exit, E is overwritten.
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 failed
= 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)
=====================================================================
*/
/* Parameter adjustments */
--work;
--e;
--d__;
/* Function Body */
*info = 0;
if (*n < 0) {
*info = -2;
i__1 = -(*info);
xerbla_("DLASQ1", &i__1);
return 0;
} else if (*n == 0) {
return 0;
} else if (*n == 1) {
d__[1] = abs(d__[1]);
return 0;
} else if (*n == 2) {
dlas2_(&d__[1], &e[1], &d__[2], &sigmn, &sigmx);
d__[1] = sigmx;
d__[2] = sigmn;
return 0;
}
/* Estimate the largest singular value. */
sigmx = 0.;
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
d__[i__] = (d__1 = d__[i__], abs(d__1));
/* Computing MAX */
d__2 = sigmx, d__3 = (d__1 = e[i__], abs(d__1));
sigmx = max(d__2,d__3);
/* L10: */
}
d__[*n] = (d__1 = d__[*n], abs(d__1));
/* Early return if SIGMX is zero (matrix is already diagonal). */
if (sigmx == 0.) {
dlasrt_("D", n, &d__[1], &iinfo);
return 0;
}
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Computing MAX */
d__1 = sigmx, d__2 = d__[i__];
sigmx = max(d__1,d__2);
/* L20: */
}
/*
Copy D and E into WORK (in the Z format) and scale (squaring the
input data makes scaling by a power of the radix pointless).
*/
eps = PRECISION;
safmin = SAFEMINIMUM;
scale = sqrt(eps / safmin);
dcopy_(n, &d__[1], &c__1, &work[1], &c__2);
i__1 = *n - 1;
dcopy_(&i__1, &e[1], &c__1, &work[2], &c__2);
i__1 = (*n << 1) - 1;
i__2 = (*n << 1) - 1;
dlascl_("G", &c__0, &c__0, &sigmx, &scale, &i__1, &c__1, &work[1], &i__2,
&iinfo);
/* Compute the q's and e's. */
i__1 = (*n << 1) - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Computing 2nd power */
d__1 = work[i__];
work[i__] = d__1 * d__1;
/* L30: */
}
work[*n * 2] = 0.;
dlasq2_(n, &work[1], info);
if (*info == 0) {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
d__[i__] = sqrt(work[i__]);
/* L40: */
}
dlascl_("G", &c__0, &c__0, &scale, &sigmx, n, &c__1, &d__[1], n, &
iinfo);
}
return 0;
/* End of DLASQ1 */
} /* dlasq1_ */
/* Subroutine */ int dlasq2_(integer *n, doublereal *z__, integer *info)
{
/* System generated locals */
integer i__1, i__2, i__3;
doublereal d__1, d__2;
/* Local variables */
static doublereal d__, e, g;
static integer k;
static doublereal s, t;
static integer i0, i4, n0;
static doublereal dn;
static integer pp;
static doublereal dn1, dn2, dee, eps, tau, tol;
static integer ipn4;
static doublereal tol2;
static logical ieee;
static integer nbig;
static doublereal dmin__, emin, emax;
static integer kmin, ndiv, iter;
static doublereal qmin, temp, qmax, zmax;
static integer splt;
static doublereal dmin1, dmin2;
static integer nfail;
static doublereal desig, trace, sigma;
static integer iinfo, ttype;
extern /* Subroutine */ int dlasq3_(integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, doublereal *, doublereal *,
integer *, integer *, integer *, logical *, integer *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *);
static doublereal deemin;
static integer iwhila, iwhilb;
static doublereal oldemn, safmin;
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int dlasrt_(char *, integer *, doublereal *,
integer *);
/*
-- LAPACK routine (version 3.2) --
-- Contributed by Osni Marques of the Lawrence Berkeley National --
-- Laboratory and Beresford Parlett of the Univ. of California at --
-- Berkeley --
-- November 2008 --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
Purpose
=======
DLASQ2 computes all the eigenvalues of the symmetric positive
definite tridiagonal matrix associated with the qd array Z to high
relative accuracy are computed to high relative accuracy, in the
absence of denormalization, underflow and overflow.
To see the relation of Z to the tridiagonal matrix, let L be a
unit lower bidiagonal matrix with subdiagonals Z(2,4,6,,..) and
let U be an upper bidiagonal matrix with 1's above and diagonal
Z(1,3,5,,..). The tridiagonal is L*U or, if you prefer, the
symmetric tridiagonal to which it is similar.
Note : DLASQ2 defines a logical variable, IEEE, which is true
on machines which follow ieee-754 floating-point standard in their
handling of infinities and NaNs, and false otherwise. This variable
is passed to DLASQ3.
Arguments
=========
N (input) INTEGER
The number of rows and columns in the matrix. N >= 0.
Z (input/output) DOUBLE PRECISION array, dimension ( 4*N )
On entry Z holds the qd array. On exit, entries 1 to N hold
the eigenvalues in decreasing order, Z( 2*N+1 ) holds the
trace, and Z( 2*N+2 ) holds the sum of the eigenvalues. If
N > 2, then Z( 2*N+3 ) holds the iteration count, Z( 2*N+4 )
holds NDIVS/NIN^2, and Z( 2*N+5 ) holds the percentage of
shifts that failed.
INFO (output) INTEGER
= 0: successful exit
< 0: if the i-th argument is a scalar and had an illegal
value, then INFO = -i, if the i-th argument is an
array and the j-entry had an illegal value, then
INFO = -(i*100+j)
> 0: the algorithm failed
= 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)
Further Details
===============
Local Variables: I0:N0 defines a current unreduced segment of Z.
The shifts are accumulated in SIGMA. Iteration count is in ITER.
Ping-pong is controlled by PP (alternates between 0 and 1).
=====================================================================
Test the input arguments.
(in case DLASQ2 is not called by DLASQ1)
*/
/* Parameter adjustments */
--z__;
/* Function Body */
*info = 0;
eps = PRECISION;
safmin = SAFEMINIMUM;
tol = eps * 100.;
/* Computing 2nd power */
d__1 = tol;
tol2 = d__1 * d__1;
if (*n < 0) {
*info = -1;
xerbla_("DLASQ2", &c__1);
return 0;
} else if (*n == 0) {
return 0;
} else if (*n == 1) {
/* 1-by-1 case. */
if (z__[1] < 0.) {
*info = -201;
xerbla_("DLASQ2", &c__2);
}
return 0;
} else if (*n == 2) {
/* 2-by-2 case. */
if (z__[2] < 0. || z__[3] < 0.) {
*info = -2;
xerbla_("DLASQ2", &c__2);
return 0;
} else if (z__[3] > z__[1]) {
d__ = z__[3];
z__[3] = z__[1];
z__[1] = d__;
}
z__[5] = z__[1] + z__[2] + z__[3];
if (z__[2] > z__[3] * tol2) {
t = (z__[1] - z__[3] + z__[2]) * .5;
s = z__[3] * (z__[2] / t);
if (s <= t) {
s = z__[3] * (z__[2] / (t * (sqrt(s / t + 1.) + 1.)));
} else {
s = z__[3] * (z__[2] / (t + sqrt(t) * sqrt(t + s)));
}
t = z__[1] + (s + z__[2]);
z__[3] *= z__[1] / t;
z__[1] = t;
}
z__[2] = z__[3];
z__[6] = z__[2] + z__[1];
return 0;
}
/* Check for negative data and compute sums of q's and e's. */
z__[*n * 2] = 0.;
emin = z__[2];
qmax = 0.;
zmax = 0.;
d__ = 0.;
e = 0.;
i__1 = *n - 1 << 1;
for (k = 1; k <= i__1; k += 2) {
if (z__[k] < 0.) {
*info = -(k + 200);
xerbla_("DLASQ2", &c__2);
return 0;
} else if (z__[k + 1] < 0.) {
*info = -(k + 201);
xerbla_("DLASQ2", &c__2);
return 0;
}
d__ += z__[k];
e += z__[k + 1];
/* Computing MAX */
d__1 = qmax, d__2 = z__[k];
qmax = max(d__1,d__2);
/* Computing MIN */
d__1 = emin, d__2 = z__[k + 1];
emin = min(d__1,d__2);
/* Computing MAX */
d__1 = max(qmax,zmax), d__2 = z__[k + 1];
zmax = max(d__1,d__2);
/* L10: */
}
if (z__[(*n << 1) - 1] < 0.) {
*info = -((*n << 1) + 199);
xerbla_("DLASQ2", &c__2);
return 0;
}
d__ += z__[(*n << 1) - 1];
/* Computing MAX */
d__1 = qmax, d__2 = z__[(*n << 1) - 1];
qmax = max(d__1,d__2);
zmax = max(qmax,zmax);
/* Check for diagonality. */
if (e == 0.) {
i__1 = *n;
for (k = 2; k <= i__1; ++k) {
z__[k] = z__[(k << 1) - 1];
/* L20: */
}
dlasrt_("D", n, &z__[1], &iinfo);
z__[(*n << 1) - 1] = d__;
return 0;
}
trace = d__ + e;
/* Check for zero data. */
if (trace == 0.) {
z__[(*n << 1) - 1] = 0.;
return 0;
}
/* Check whether the machine is IEEE conformable. */
ieee = ilaenv_(&c__10, "DLASQ2", "N", &c__1, &c__2, &c__3, &c__4, (ftnlen)
6, (ftnlen)1) == 1 && ilaenv_(&c__11, "DLASQ2", "N", &c__1, &c__2,
&c__3, &c__4, (ftnlen)6, (ftnlen)1) == 1;
/* Rearrange data for locality: Z=(q1,qq1,e1,ee1,q2,qq2,e2,ee2,...). */
for (k = *n << 1; k >= 2; k += -2) {
z__[k * 2] = 0.;
z__[(k << 1) - 1] = z__[k];
z__[(k << 1) - 2] = 0.;
z__[(k << 1) - 3] = z__[k - 1];
/* L30: */
}
i0 = 1;
n0 = *n;
/* Reverse the qd-array, if warranted. */
if (z__[(i0 << 2) - 3] * 1.5 < z__[(n0 << 2) - 3]) {
ipn4 = i0 + n0 << 2;
i__1 = i0 + n0 - 1 << 1;
for (i4 = i0 << 2; i4 <= i__1; i4 += 4) {
temp = z__[i4 - 3];
z__[i4 - 3] = z__[ipn4 - i4 - 3];
z__[ipn4 - i4 - 3] = temp;
temp = z__[i4 - 1];
z__[i4 - 1] = z__[ipn4 - i4 - 5];
z__[ipn4 - i4 - 5] = temp;
/* L40: */
}
}
/* Initial split checking via dqd and Li's test. */
pp = 0;
for (k = 1; k <= 2; ++k) {
d__ = z__[(n0 << 2) + pp - 3];
i__1 = (i0 << 2) + pp;
for (i4 = (n0 - 1 << 2) + pp; i4 >= i__1; i4 += -4) {
if (z__[i4 - 1] <= tol2 * d__) {
z__[i4 - 1] = -0.;
d__ = z__[i4 - 3];
} else {
d__ = z__[i4 - 3] * (d__ / (d__ + z__[i4 - 1]));
}
/* L50: */
}
/* dqd maps Z to ZZ plus Li's test. */
emin = z__[(i0 << 2) + pp + 1];
d__ = z__[(i0 << 2) + pp - 3];
i__1 = (n0 - 1 << 2) + pp;
for (i4 = (i0 << 2) + pp; i4 <= i__1; i4 += 4) {
z__[i4 - (pp << 1) - 2] = d__ + z__[i4 - 1];
if (z__[i4 - 1] <= tol2 * d__) {
z__[i4 - 1] = -0.;
z__[i4 - (pp << 1) - 2] = d__;
z__[i4 - (pp << 1)] = 0.;
d__ = z__[i4 + 1];
} else if (safmin * z__[i4 + 1] < z__[i4 - (pp << 1) - 2] &&
safmin * z__[i4 - (pp << 1) - 2] < z__[i4 + 1]) {
temp = z__[i4 + 1] / z__[i4 - (pp << 1) - 2];
z__[i4 - (pp << 1)] = z__[i4 - 1] * temp;
d__ *= temp;
} else {
z__[i4 - (pp << 1)] = z__[i4 + 1] * (z__[i4 - 1] / z__[i4 - (
pp << 1) - 2]);
d__ = z__[i4 + 1] * (d__ / z__[i4 - (pp << 1) - 2]);
}
/* Computing MIN */
d__1 = emin, d__2 = z__[i4 - (pp << 1)];
emin = min(d__1,d__2);
/* L60: */
}
z__[(n0 << 2) - pp - 2] = d__;
/* Now find qmax. */
qmax = z__[(i0 << 2) - pp - 2];
i__1 = (n0 << 2) - pp - 2;
for (i4 = (i0 << 2) - pp + 2; i4 <= i__1; i4 += 4) {
/* Computing MAX */
d__1 = qmax, d__2 = z__[i4];
qmax = max(d__1,d__2);
/* L70: */
}
/* Prepare for the next iteration on K. */
pp = 1 - pp;
/* L80: */
}
/* Initialise variables to pass to DLASQ3. */
ttype = 0;
dmin1 = 0.;
dmin2 = 0.;
dn = 0.;
dn1 = 0.;
dn2 = 0.;
g = 0.;
tau = 0.;
iter = 2;
nfail = 0;
ndiv = n0 - i0 << 1;
i__1 = *n + 1;
for (iwhila = 1; iwhila <= i__1; ++iwhila) {
if (n0 < 1) {
goto L170;
}
/*
While array unfinished do
E(N0) holds the value of SIGMA when submatrix in I0:N0
splits from the rest of the array, but is negated.
*/
desig = 0.;
if (n0 == *n) {
sigma = 0.;
} else {
sigma = -z__[(n0 << 2) - 1];
}
if (sigma < 0.) {
*info = 1;
return 0;
}
/*
Find last unreduced submatrix's top index I0, find QMAX and
EMIN. Find Gershgorin-type bound if Q's much greater than E's.
*/
emax = 0.;
if (n0 > i0) {
emin = (d__1 = z__[(n0 << 2) - 5], abs(d__1));
} else {
emin = 0.;
}
qmin = z__[(n0 << 2) - 3];
qmax = qmin;
for (i4 = n0 << 2; i4 >= 8; i4 += -4) {
if (z__[i4 - 5] <= 0.) {
goto L100;
}
if (qmin >= emax * 4.) {
/* Computing MIN */
d__1 = qmin, d__2 = z__[i4 - 3];
qmin = min(d__1,d__2);
/* Computing MAX */
d__1 = emax, d__2 = z__[i4 - 5];
emax = max(d__1,d__2);
}
/* Computing MAX */
d__1 = qmax, d__2 = z__[i4 - 7] + z__[i4 - 5];
qmax = max(d__1,d__2);
/* Computing MIN */
d__1 = emin, d__2 = z__[i4 - 5];
emin = min(d__1,d__2);
/* L90: */
}
i4 = 4;
L100:
i0 = i4 / 4;
pp = 0;
if (n0 - i0 > 1) {
dee = z__[(i0 << 2) - 3];
deemin = dee;
kmin = i0;
i__2 = (n0 << 2) - 3;
for (i4 = (i0 << 2) + 1; i4 <= i__2; i4 += 4) {
dee = z__[i4] * (dee / (dee + z__[i4 - 2]));
if (dee <= deemin) {
deemin = dee;
kmin = (i4 + 3) / 4;
}
/* L110: */
}
if (kmin - i0 << 1 < n0 - kmin && deemin <= z__[(n0 << 2) - 3] *
.5) {
ipn4 = i0 + n0 << 2;
pp = 2;
i__2 = i0 + n0 - 1 << 1;
for (i4 = i0 << 2; i4 <= i__2; i4 += 4) {
temp = z__[i4 - 3];
z__[i4 - 3] = z__[ipn4 - i4 - 3];
z__[ipn4 - i4 - 3] = temp;
temp = z__[i4 - 2];
z__[i4 - 2] = z__[ipn4 - i4 - 2];
z__[ipn4 - i4 - 2] = temp;
temp = z__[i4 - 1];
z__[i4 - 1] = z__[ipn4 - i4 - 5];
z__[ipn4 - i4 - 5] = temp;
temp = z__[i4];
z__[i4] = z__[ipn4 - i4 - 4];
z__[ipn4 - i4 - 4] = temp;
/* L120: */
}
}
}
/*
Put -(initial shift) into DMIN.
Computing MAX
*/
d__1 = 0., d__2 = qmin - sqrt(qmin) * 2. * sqrt(emax);
dmin__ = -max(d__1,d__2);
/*
Now I0:N0 is unreduced.
PP = 0 for ping, PP = 1 for pong.
PP = 2 indicates that flipping was applied to the Z array and
and that the tests for deflation upon entry in DLASQ3
should not be performed.
*/
nbig = (n0 - i0 + 1) * 30;
i__2 = nbig;
for (iwhilb = 1; iwhilb <= i__2; ++iwhilb) {
if (i0 > n0) {
goto L150;
}
/* While submatrix unfinished take a good dqds step. */
dlasq3_(&i0, &n0, &z__[1], &pp, &dmin__, &sigma, &desig, &qmax, &
nfail, &iter, &ndiv, &ieee, &ttype, &dmin1, &dmin2, &dn, &
dn1, &dn2, &g, &tau);
pp = 1 - pp;
/* When EMIN is very small check for splits. */
if (pp == 0 && n0 - i0 >= 3) {
if (z__[n0 * 4] <= tol2 * qmax || z__[(n0 << 2) - 1] <= tol2 *
sigma) {
splt = i0 - 1;
qmax = z__[(i0 << 2) - 3];
emin = z__[(i0 << 2) - 1];
oldemn = z__[i0 * 4];
i__3 = n0 - 3 << 2;
for (i4 = i0 << 2; i4 <= i__3; i4 += 4) {
if (z__[i4] <= tol2 * z__[i4 - 3] || z__[i4 - 1] <=
tol2 * sigma) {
z__[i4 - 1] = -sigma;
splt = i4 / 4;
qmax = 0.;
emin = z__[i4 + 3];
oldemn = z__[i4 + 4];
} else {
/* Computing MAX */
d__1 = qmax, d__2 = z__[i4 + 1];
qmax = max(d__1,d__2);
/* Computing MIN */
d__1 = emin, d__2 = z__[i4 - 1];
emin = min(d__1,d__2);
/* Computing MIN */
d__1 = oldemn, d__2 = z__[i4];
oldemn = min(d__1,d__2);
}
/* L130: */
}
z__[(n0 << 2) - 1] = emin;
z__[n0 * 4] = oldemn;
i0 = splt + 1;
}
}
/* L140: */
}
*info = 2;
return 0;
/* end IWHILB */
L150:
/* L160: */
;
}
*info = 3;
return 0;
/* end IWHILA */
L170:
/* Move q's to the front. */
i__1 = *n;
for (k = 2; k <= i__1; ++k) {
z__[k] = z__[(k << 2) - 3];
/* L180: */
}
/* Sort and compute sum of eigenvalues. */
dlasrt_("D", n, &z__[1], &iinfo);
e = 0.;
for (k = *n; k >= 1; --k) {
e += z__[k];
/* L190: */
}
/* Store trace, sum(eigenvalues) and information on performance. */
z__[(*n << 1) + 1] = trace;
z__[(*n << 1) + 2] = e;
z__[(*n << 1) + 3] = (doublereal) iter;
/* Computing 2nd power */
i__1 = *n;
z__[(*n << 1) + 4] = (doublereal) ndiv / (doublereal) (i__1 * i__1);
z__[(*n << 1) + 5] = nfail * 100. / (doublereal) iter;
return 0;
/* End of DLASQ2 */
} /* dlasq2_ */
/* Subroutine */ int dlasq3_(integer *i0, integer *n0, doublereal *z__,
integer *pp, doublereal *dmin__, doublereal *sigma, doublereal *desig,
doublereal *qmax, integer *nfail, integer *iter, integer *ndiv,
logical *ieee, integer *ttype, doublereal *dmin1, doublereal *dmin2,
doublereal *dn, doublereal *dn1, doublereal *dn2, doublereal *g,
doublereal *tau)
{
/* System generated locals */
integer i__1;
doublereal d__1, d__2;
/* Local variables */
static doublereal s, t;
static integer j4, nn;
static doublereal eps, tol;
static integer n0in, ipn4;
static doublereal tol2, temp;
extern /* Subroutine */ int dlasq4_(integer *, integer *, doublereal *,
integer *, integer *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *, integer *,
doublereal *), dlasq5_(integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, logical *), dlasq6_(
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *);
extern logical disnan_(doublereal *);
/*
-- LAPACK routine (version 3.2.2) --
-- Contributed by Osni Marques of the Lawrence Berkeley National --
-- Laboratory and Beresford Parlett of the Univ. of California at --
-- Berkeley --
-- June 2010 --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
Purpose
=======
DLASQ3 checks for deflation, computes a shift (TAU) and calls dqds.
In case of failure it changes shifts, and tries again until output
is positive.
Arguments
=========
I0 (input) INTEGER
First index.
N0 (input/output) INTEGER
Last index.
Z (input) DOUBLE PRECISION array, dimension ( 4*N )
Z holds the qd array.
PP (input/output) INTEGER
PP=0 for ping, PP=1 for pong.
PP=2 indicates that flipping was applied to the Z array
and that the initial tests for deflation should not be
performed.
DMIN (output) DOUBLE PRECISION
Minimum value of d.
SIGMA (output) DOUBLE PRECISION
Sum of shifts used in current segment.
DESIG (input/output) DOUBLE PRECISION
Lower order part of SIGMA
QMAX (input) DOUBLE PRECISION
Maximum value of q.
NFAIL (output) INTEGER
Number of times shift was too big.
ITER (output) INTEGER
Number of iterations.
NDIV (output) INTEGER
Number of divisions.
IEEE (input) LOGICAL
Flag for IEEE or non IEEE arithmetic (passed to DLASQ5).
TTYPE (input/output) INTEGER
Shift type.
DMIN1 (input/output) DOUBLE PRECISION
DMIN2 (input/output) DOUBLE PRECISION
DN (input/output) DOUBLE PRECISION
DN1 (input/output) DOUBLE PRECISION
DN2 (input/output) DOUBLE PRECISION
G (input/output) DOUBLE PRECISION
TAU (input/output) DOUBLE PRECISION
These are passed as arguments in order to save their values
between calls to DLASQ3.
=====================================================================
*/
/* Parameter adjustments */
--z__;
/* Function Body */
n0in = *n0;
eps = PRECISION;
tol = eps * 100.;
/* Computing 2nd power */
d__1 = tol;
tol2 = d__1 * d__1;
/* Check for deflation. */
L10:
if (*n0 < *i0) {
return 0;
}
if (*n0 == *i0) {
goto L20;
}
nn = (*n0 << 2) + *pp;
if (*n0 == *i0 + 1) {
goto L40;
}
/* Check whether E(N0-1) is negligible, 1 eigenvalue. */
if (z__[nn - 5] > tol2 * (*sigma + z__[nn - 3]) && z__[nn - (*pp << 1) -
4] > tol2 * z__[nn - 7]) {
goto L30;
}
L20:
z__[(*n0 << 2) - 3] = z__[(*n0 << 2) + *pp - 3] + *sigma;
--(*n0);
goto L10;
/* Check whether E(N0-2) is negligible, 2 eigenvalues. */
L30:
if (z__[nn - 9] > tol2 * *sigma && z__[nn - (*pp << 1) - 8] > tol2 * z__[
nn - 11]) {
goto L50;
}
L40:
if (z__[nn - 3] > z__[nn - 7]) {
s = z__[nn - 3];
z__[nn - 3] = z__[nn - 7];
z__[nn - 7] = s;
}
if (z__[nn - 5] > z__[nn - 3] * tol2) {
t = (z__[nn - 7] - z__[nn - 3] + z__[nn - 5]) * .5;
s = z__[nn - 3] * (z__[nn - 5] / t);
if (s <= t) {
s = z__[nn - 3] * (z__[nn - 5] / (t * (sqrt(s / t + 1.) + 1.)));
} else {
s = z__[nn - 3] * (z__[nn - 5] / (t + sqrt(t) * sqrt(t + s)));
}
t = z__[nn - 7] + (s + z__[nn - 5]);
z__[nn - 3] *= z__[nn - 7] / t;
z__[nn - 7] = t;
}
z__[(*n0 << 2) - 7] = z__[nn - 7] + *sigma;
z__[(*n0 << 2) - 3] = z__[nn - 3] + *sigma;
*n0 += -2;
goto L10;
L50:
if (*pp == 2) {
*pp = 0;
}
/* Reverse the qd-array, if warranted. */
if (*dmin__ <= 0. || *n0 < n0in) {
if (z__[(*i0 << 2) + *pp - 3] * 1.5 < z__[(*n0 << 2) + *pp - 3]) {
ipn4 = *i0 + *n0 << 2;
i__1 = *i0 + *n0 - 1 << 1;
for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) {
temp = z__[j4 - 3];
z__[j4 - 3] = z__[ipn4 - j4 - 3];
z__[ipn4 - j4 - 3] = temp;
temp = z__[j4 - 2];
z__[j4 - 2] = z__[ipn4 - j4 - 2];
z__[ipn4 - j4 - 2] = temp;
temp = z__[j4 - 1];
z__[j4 - 1] = z__[ipn4 - j4 - 5];
z__[ipn4 - j4 - 5] = temp;
temp = z__[j4];
z__[j4] = z__[ipn4 - j4 - 4];
z__[ipn4 - j4 - 4] = temp;
/* L60: */
}
if (*n0 - *i0 <= 4) {
z__[(*n0 << 2) + *pp - 1] = z__[(*i0 << 2) + *pp - 1];
z__[(*n0 << 2) - *pp] = z__[(*i0 << 2) - *pp];
}
/* Computing MIN */
d__1 = *dmin2, d__2 = z__[(*n0 << 2) + *pp - 1];
*dmin2 = min(d__1,d__2);
/* Computing MIN */
d__1 = z__[(*n0 << 2) + *pp - 1], d__2 = z__[(*i0 << 2) + *pp - 1]
, d__1 = min(d__1,d__2), d__2 = z__[(*i0 << 2) + *pp + 3];
z__[(*n0 << 2) + *pp - 1] = min(d__1,d__2);
/* Computing MIN */
d__1 = z__[(*n0 << 2) - *pp], d__2 = z__[(*i0 << 2) - *pp], d__1 =
min(d__1,d__2), d__2 = z__[(*i0 << 2) - *pp + 4];
z__[(*n0 << 2) - *pp] = min(d__1,d__2);
/* Computing MAX */
d__1 = *qmax, d__2 = z__[(*i0 << 2) + *pp - 3], d__1 = max(d__1,
d__2), d__2 = z__[(*i0 << 2) + *pp + 1];
*qmax = max(d__1,d__2);
*dmin__ = -0.;
}
}
/* Choose a shift. */
dlasq4_(i0, n0, &z__[1], pp, &n0in, dmin__, dmin1, dmin2, dn, dn1, dn2,
tau, ttype, g);
/* Call dqds until DMIN > 0. */
L70:
dlasq5_(i0, n0, &z__[1], pp, tau, dmin__, dmin1, dmin2, dn, dn1, dn2,
ieee);
*ndiv += *n0 - *i0 + 2;
++(*iter);
/* Check status. */
if (*dmin__ >= 0. && *dmin1 > 0.) {
/* Success. */
goto L90;
} else if (*dmin__ < 0. && *dmin1 > 0. && z__[(*n0 - 1 << 2) - *pp] < tol
* (*sigma + *dn1) && abs(*dn) < tol * *sigma) {
/* Convergence hidden by negative DN. */
z__[(*n0 - 1 << 2) - *pp + 2] = 0.;
*dmin__ = 0.;
goto L90;
} else if (*dmin__ < 0.) {
/* TAU too big. Select new TAU and try again. */
++(*nfail);
if (*ttype < -22) {
/* Failed twice. Play it safe. */
*tau = 0.;
} else if (*dmin1 > 0.) {
/* Late failure. Gives excellent shift. */
*tau = (*tau + *dmin__) * (1. - eps * 2.);
*ttype += -11;
} else {
/* Early failure. Divide by 4. */
*tau *= .25;
*ttype += -12;
}
goto L70;
} else if (disnan_(dmin__)) {
/* NaN. */
if (*tau == 0.) {
goto L80;
} else {
*tau = 0.;
goto L70;
}
} else {
/* Possible underflow. Play it safe. */
goto L80;
}
/* Risk of underflow. */
L80:
dlasq6_(i0, n0, &z__[1], pp, dmin__, dmin1, dmin2, dn, dn1, dn2);
*ndiv += *n0 - *i0 + 2;
++(*iter);
*tau = 0.;
L90:
if (*tau < *sigma) {
*desig += *tau;
t = *sigma + *desig;
*desig -= t - *sigma;
} else {
t = *sigma + *tau;
*desig = *sigma - (t - *tau) + *desig;
}
*sigma = t;
return 0;
/* End of DLASQ3 */
} /* dlasq3_ */
/* Subroutine */ int dlasq4_(integer *i0, integer *n0, doublereal *z__,
integer *pp, integer *n0in, doublereal *dmin__, doublereal *dmin1,
doublereal *dmin2, doublereal *dn, doublereal *dn1, doublereal *dn2,
doublereal *tau, integer *ttype, doublereal *g)
{
/* System generated locals */
integer i__1;
doublereal d__1, d__2;
/* Local variables */
static doublereal s, a2, b1, b2;
static integer i4, nn, np;
static doublereal gam, gap1, gap2;
/*
-- LAPACK routine (version 3.2) --
-- Contributed by Osni Marques of the Lawrence Berkeley National --
-- Laboratory and Beresford Parlett of the Univ. of California at --
-- Berkeley --
-- November 2008 --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
Purpose
=======
DLASQ4 computes an approximation TAU to the smallest eigenvalue
using values of d from the previous transform.
I0 (input) INTEGER
First index.
N0 (input) INTEGER
Last index.
Z (input) DOUBLE PRECISION array, dimension ( 4*N )
Z holds the qd array.
PP (input) INTEGER
PP=0 for ping, PP=1 for pong.
NOIN (input) INTEGER
The value of N0 at start of EIGTEST.
DMIN (input) DOUBLE PRECISION
Minimum value of d.
DMIN1 (input) DOUBLE PRECISION
Minimum value of d, excluding D( N0 ).
DMIN2 (input) DOUBLE PRECISION
Minimum value of d, excluding D( N0 ) and D( N0-1 ).
DN (input) DOUBLE PRECISION
d(N)
DN1 (input) DOUBLE PRECISION
d(N-1)
DN2 (input) DOUBLE PRECISION
d(N-2)
TAU (output) DOUBLE PRECISION
This is the shift.
TTYPE (output) INTEGER
Shift type.
G (input/output) REAL
G is passed as an argument in order to save its value between
calls to DLASQ4.
Further Details
===============
CNST1 = 9/16
=====================================================================
A negative DMIN forces the shift to take that absolute value
TTYPE records the type of shift.
*/
/* Parameter adjustments */
--z__;
/* Function Body */
if (*dmin__ <= 0.) {
*tau = -(*dmin__);
*ttype = -1;
return 0;
}
nn = (*n0 << 2) + *pp;
if (*n0in == *n0) {
/* No eigenvalues deflated. */
if (*dmin__ == *dn || *dmin__ == *dn1) {
b1 = sqrt(z__[nn - 3]) * sqrt(z__[nn - 5]);
b2 = sqrt(z__[nn - 7]) * sqrt(z__[nn - 9]);
a2 = z__[nn - 7] + z__[nn - 5];
/* Cases 2 and 3. */
if (*dmin__ == *dn && *dmin1 == *dn1) {
gap2 = *dmin2 - a2 - *dmin2 * .25;
if (gap2 > 0. && gap2 > b2) {
gap1 = a2 - *dn - b2 / gap2 * b2;
} else {
gap1 = a2 - *dn - (b1 + b2);
}
if (gap1 > 0. && gap1 > b1) {
/* Computing MAX */
d__1 = *dn - b1 / gap1 * b1, d__2 = *dmin__ * .5;
s = max(d__1,d__2);
*ttype = -2;
} else {
s = 0.;
if (*dn > b1) {
s = *dn - b1;
}
if (a2 > b1 + b2) {
/* Computing MIN */
d__1 = s, d__2 = a2 - (b1 + b2);
s = min(d__1,d__2);
}
/* Computing MAX */
d__1 = s, d__2 = *dmin__ * .333;
s = max(d__1,d__2);
*ttype = -3;
}
} else {
/* Case 4. */
*ttype = -4;
s = *dmin__ * .25;
if (*dmin__ == *dn) {
gam = *dn;
a2 = 0.;
if (z__[nn - 5] > z__[nn - 7]) {
return 0;
}
b2 = z__[nn - 5] / z__[nn - 7];
np = nn - 9;
} else {
np = nn - (*pp << 1);
b2 = z__[np - 2];
gam = *dn1;
if (z__[np - 4] > z__[np - 2]) {
return 0;
}
a2 = z__[np - 4] / z__[np - 2];
if (z__[nn - 9] > z__[nn - 11]) {
return 0;
}
b2 = z__[nn - 9] / z__[nn - 11];
np = nn - 13;
}
/* Approximate contribution to norm squared from I < NN-1. */
a2 += b2;
i__1 = (*i0 << 2) - 1 + *pp;
for (i4 = np; i4 >= i__1; i4 += -4) {
if (b2 == 0.) {
goto L20;
}
b1 = b2;
if (z__[i4] > z__[i4 - 2]) {
return 0;
}
b2 *= z__[i4] / z__[i4 - 2];
a2 += b2;
if (max(b2,b1) * 100. < a2 || .563 < a2) {
goto L20;
}
/* L10: */
}
L20:
a2 *= 1.05;
/* Rayleigh quotient residual bound. */
if (a2 < .563) {
s = gam * (1. - sqrt(a2)) / (a2 + 1.);
}
}
} else if (*dmin__ == *dn2) {
/* Case 5. */
*ttype = -5;
s = *dmin__ * .25;
/* Compute contribution to norm squared from I > NN-2. */
np = nn - (*pp << 1);
b1 = z__[np - 2];
b2 = z__[np - 6];
gam = *dn2;
if (z__[np - 8] > b2 || z__[np - 4] > b1) {
return 0;
}
a2 = z__[np - 8] / b2 * (z__[np - 4] / b1 + 1.);
/* Approximate contribution to norm squared from I < NN-2. */
if (*n0 - *i0 > 2) {
b2 = z__[nn - 13] / z__[nn - 15];
a2 += b2;
i__1 = (*i0 << 2) - 1 + *pp;
for (i4 = nn - 17; i4 >= i__1; i4 += -4) {
if (b2 == 0.) {
goto L40;
}
b1 = b2;
if (z__[i4] > z__[i4 - 2]) {
return 0;
}
b2 *= z__[i4] / z__[i4 - 2];
a2 += b2;
if (max(b2,b1) * 100. < a2 || .563 < a2) {
goto L40;
}
/* L30: */
}
L40:
a2 *= 1.05;
}
if (a2 < .563) {
s = gam * (1. - sqrt(a2)) / (a2 + 1.);
}
} else {
/* Case 6, no information to guide us. */
if (*ttype == -6) {
*g += (1. - *g) * .333;
} else if (*ttype == -18) {
*g = .083250000000000005;
} else {
*g = .25;
}
s = *g * *dmin__;
*ttype = -6;
}
} else if (*n0in == *n0 + 1) {
/* One eigenvalue just deflated. Use DMIN1, DN1 for DMIN and DN. */
if (*dmin1 == *dn1 && *dmin2 == *dn2) {
/* Cases 7 and 8. */
*ttype = -7;
s = *dmin1 * .333;
if (z__[nn - 5] > z__[nn - 7]) {
return 0;
}
b1 = z__[nn - 5] / z__[nn - 7];
b2 = b1;
if (b2 == 0.) {
goto L60;
}
i__1 = (*i0 << 2) - 1 + *pp;
for (i4 = (*n0 << 2) - 9 + *pp; i4 >= i__1; i4 += -4) {
a2 = b1;
if (z__[i4] > z__[i4 - 2]) {
return 0;
}
b1 *= z__[i4] / z__[i4 - 2];
b2 += b1;
if (max(b1,a2) * 100. < b2) {
goto L60;
}
/* L50: */
}
L60:
b2 = sqrt(b2 * 1.05);
/* Computing 2nd power */
d__1 = b2;
a2 = *dmin1 / (d__1 * d__1 + 1.);
gap2 = *dmin2 * .5 - a2;
if (gap2 > 0. && gap2 > b2 * a2) {
/* Computing MAX */
d__1 = s, d__2 = a2 * (1. - a2 * 1.01 * (b2 / gap2) * b2);
s = max(d__1,d__2);
} else {
/* Computing MAX */
d__1 = s, d__2 = a2 * (1. - b2 * 1.01);
s = max(d__1,d__2);
*ttype = -8;
}
} else {
/* Case 9. */
s = *dmin1 * .25;
if (*dmin1 == *dn1) {
s = *dmin1 * .5;
}
*ttype = -9;
}
} else if (*n0in == *n0 + 2) {
/*
Two eigenvalues deflated. Use DMIN2, DN2 for DMIN and DN.
Cases 10 and 11.
*/
if (*dmin2 == *dn2 && z__[nn - 5] * 2. < z__[nn - 7]) {
*ttype = -10;
s = *dmin2 * .333;
if (z__[nn - 5] > z__[nn - 7]) {
return 0;
}
b1 = z__[nn - 5] / z__[nn - 7];
b2 = b1;
if (b2 == 0.) {
goto L80;
}
i__1 = (*i0 << 2) - 1 + *pp;
for (i4 = (*n0 << 2) - 9 + *pp; i4 >= i__1; i4 += -4) {
if (z__[i4] > z__[i4 - 2]) {
return 0;
}
b1 *= z__[i4] / z__[i4 - 2];
b2 += b1;
if (b1 * 100. < b2) {
goto L80;
}
/* L70: */
}
L80:
b2 = sqrt(b2 * 1.05);
/* Computing 2nd power */
d__1 = b2;
a2 = *dmin2 / (d__1 * d__1 + 1.);
gap2 = z__[nn - 7] + z__[nn - 9] - sqrt(z__[nn - 11]) * sqrt(z__[
nn - 9]) - a2;
if (gap2 > 0. && gap2 > b2 * a2) {
/* Computing MAX */
d__1 = s, d__2 = a2 * (1. - a2 * 1.01 * (b2 / gap2) * b2);
s = max(d__1,d__2);
} else {
/* Computing MAX */
d__1 = s, d__2 = a2 * (1. - b2 * 1.01);
s = max(d__1,d__2);
}
} else {
s = *dmin2 * .25;
*ttype = -11;
}
} else if (*n0in > *n0 + 2) {
/* Case 12, more than two eigenvalues deflated. No information. */
s = 0.;
*ttype = -12;
}
*tau = s;
return 0;
/* End of DLASQ4 */
} /* dlasq4_ */
/* Subroutine */ int dlasq5_(integer *i0, integer *n0, doublereal *z__,
integer *pp, doublereal *tau, doublereal *dmin__, doublereal *dmin1,
doublereal *dmin2, doublereal *dn, doublereal *dnm1, doublereal *dnm2,
logical *ieee)
{
/* System generated locals */
integer i__1;
doublereal d__1, d__2;
/* Local variables */
static doublereal d__;
static integer j4, j4p2;
static doublereal emin, temp;
/*
-- LAPACK routine (version 3.2) --
-- Contributed by Osni Marques of the Lawrence Berkeley National --
-- Laboratory and Beresford Parlett of the Univ. of California at --
-- Berkeley --
-- November 2008 --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
Purpose
=======
DLASQ5 computes one dqds transform in ping-pong form, one
version for IEEE machines another for non IEEE machines.
Arguments
=========
I0 (input) INTEGER
First index.
N0 (input) INTEGER
Last index.
Z (input) DOUBLE PRECISION array, dimension ( 4*N )
Z holds the qd array. EMIN is stored in Z(4*N0) to avoid
an extra argument.
PP (input) INTEGER
PP=0 for ping, PP=1 for pong.
TAU (input) DOUBLE PRECISION
This is the shift.
DMIN (output) DOUBLE PRECISION
Minimum value of d.
DMIN1 (output) DOUBLE PRECISION
Minimum value of d, excluding D( N0 ).
DMIN2 (output) DOUBLE PRECISION
Minimum value of d, excluding D( N0 ) and D( N0-1 ).
DN (output) DOUBLE PRECISION
d(N0), the last value of d.
DNM1 (output) DOUBLE PRECISION
d(N0-1).
DNM2 (output) DOUBLE PRECISION
d(N0-2).
IEEE (input) LOGICAL
Flag for IEEE or non IEEE arithmetic.
=====================================================================
*/
/* Parameter adjustments */
--z__;
/* Function Body */
if (*n0 - *i0 - 1 <= 0) {
return 0;
}
j4 = (*i0 << 2) + *pp - 3;
emin = z__[j4 + 4];
d__ = z__[j4] - *tau;
*dmin__ = d__;
*dmin1 = -z__[j4];
if (*ieee) {
/* Code for IEEE arithmetic. */
if (*pp == 0) {
i__1 = *n0 - 3 << 2;
for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) {
z__[j4 - 2] = d__ + z__[j4 - 1];
temp = z__[j4 + 1] / z__[j4 - 2];
d__ = d__ * temp - *tau;
*dmin__ = min(*dmin__,d__);
z__[j4] = z__[j4 - 1] * temp;
/* Computing MIN */
d__1 = z__[j4];
emin = min(d__1,emin);
/* L10: */
}
} else {
i__1 = *n0 - 3 << 2;
for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) {
z__[j4 - 3] = d__ + z__[j4];
temp = z__[j4 + 2] / z__[j4 - 3];
d__ = d__ * temp - *tau;
*dmin__ = min(*dmin__,d__);
z__[j4 - 1] = z__[j4] * temp;
/* Computing MIN */
d__1 = z__[j4 - 1];
emin = min(d__1,emin);
/* L20: */
}
}
/* Unroll last two steps. */
*dnm2 = d__;
*dmin2 = *dmin__;
j4 = (*n0 - 2 << 2) - *pp;
j4p2 = j4 + (*pp << 1) - 1;
z__[j4 - 2] = *dnm2 + z__[j4p2];
z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]);
*dnm1 = z__[j4p2 + 2] * (*dnm2 / z__[j4 - 2]) - *tau;
*dmin__ = min(*dmin__,*dnm1);
*dmin1 = *dmin__;
j4 += 4;
j4p2 = j4 + (*pp << 1) - 1;
z__[j4 - 2] = *dnm1 + z__[j4p2];
z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]);
*dn = z__[j4p2 + 2] * (*dnm1 / z__[j4 - 2]) - *tau;
*dmin__ = min(*dmin__,*dn);
} else {
/* Code for non IEEE arithmetic. */
if (*pp == 0) {
i__1 = *n0 - 3 << 2;
for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) {
z__[j4 - 2] = d__ + z__[j4 - 1];
if (d__ < 0.) {
return 0;
} else {
z__[j4] = z__[j4 + 1] * (z__[j4 - 1] / z__[j4 - 2]);
d__ = z__[j4 + 1] * (d__ / z__[j4 - 2]) - *tau;
}
*dmin__ = min(*dmin__,d__);
/* Computing MIN */
d__1 = emin, d__2 = z__[j4];
emin = min(d__1,d__2);
/* L30: */
}
} else {
i__1 = *n0 - 3 << 2;
for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) {
z__[j4 - 3] = d__ + z__[j4];
if (d__ < 0.) {
return 0;
} else {
z__[j4 - 1] = z__[j4 + 2] * (z__[j4] / z__[j4 - 3]);
d__ = z__[j4 + 2] * (d__ / z__[j4 - 3]) - *tau;
}
*dmin__ = min(*dmin__,d__);
/* Computing MIN */
d__1 = emin, d__2 = z__[j4 - 1];
emin = min(d__1,d__2);
/* L40: */
}
}
/* Unroll last two steps. */
*dnm2 = d__;
*dmin2 = *dmin__;
j4 = (*n0 - 2 << 2) - *pp;
j4p2 = j4 + (*pp << 1) - 1;
z__[j4 - 2] = *dnm2 + z__[j4p2];
if (*dnm2 < 0.) {
return 0;
} else {
z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]);
*dnm1 = z__[j4p2 + 2] * (*dnm2 / z__[j4 - 2]) - *tau;
}
*dmin__ = min(*dmin__,*dnm1);
*dmin1 = *dmin__;
j4 += 4;
j4p2 = j4 + (*pp << 1) - 1;
z__[j4 - 2] = *dnm1 + z__[j4p2];
if (*dnm1 < 0.) {
return 0;
} else {
z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]);
*dn = z__[j4p2 + 2] * (*dnm1 / z__[j4 - 2]) - *tau;
}
*dmin__ = min(*dmin__,*dn);
}
z__[j4 + 2] = *dn;
z__[(*n0 << 2) - *pp] = emin;
return 0;
/* End of DLASQ5 */
} /* dlasq5_ */
/* Subroutine */ int dlasq6_(integer *i0, integer *n0, doublereal *z__,
integer *pp, doublereal *dmin__, doublereal *dmin1, doublereal *dmin2,
doublereal *dn, doublereal *dnm1, doublereal *dnm2)
{
/* System generated locals */
integer i__1;
doublereal d__1, d__2;
/* Local variables */
static doublereal d__;
static integer j4, j4p2;
static doublereal emin, temp;
static doublereal safmin;
/*
-- LAPACK routine (version 3.2) --
-- Contributed by Osni Marques of the Lawrence Berkeley National --
-- Laboratory and Beresford Parlett of the Univ. of California at --
-- Berkeley --
-- November 2008 --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
Purpose
=======
DLASQ6 computes one dqd (shift equal to zero) transform in
ping-pong form, with protection against underflow and overflow.
Arguments
=========
I0 (input) INTEGER
First index.
N0 (input) INTEGER
Last index.
Z (input) DOUBLE PRECISION array, dimension ( 4*N )
Z holds the qd array. EMIN is stored in Z(4*N0) to avoid
an extra argument.
PP (input) INTEGER
PP=0 for ping, PP=1 for pong.
DMIN (output) DOUBLE PRECISION
Minimum value of d.
DMIN1 (output) DOUBLE PRECISION
Minimum value of d, excluding D( N0 ).
DMIN2 (output) DOUBLE PRECISION
Minimum value of d, excluding D( N0 ) and D( N0-1 ).
DN (output) DOUBLE PRECISION
d(N0), the last value of d.
DNM1 (output) DOUBLE PRECISION
d(N0-1).
DNM2 (output) DOUBLE PRECISION
d(N0-2).
=====================================================================
*/
/* Parameter adjustments */
--z__;
/* Function Body */
if (*n0 - *i0 - 1 <= 0) {
return 0;
}
safmin = SAFEMINIMUM;
j4 = (*i0 << 2) + *pp - 3;
emin = z__[j4 + 4];
d__ = z__[j4];
*dmin__ = d__;
if (*pp == 0) {
i__1 = *n0 - 3 << 2;
for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) {
z__[j4 - 2] = d__ + z__[j4 - 1];
if (z__[j4 - 2] == 0.) {
z__[j4] = 0.;
d__ = z__[j4 + 1];
*dmin__ = d__;
emin = 0.;
} else if (safmin * z__[j4 + 1] < z__[j4 - 2] && safmin * z__[j4
- 2] < z__[j4 + 1]) {
temp = z__[j4 + 1] / z__[j4 - 2];
z__[j4] = z__[j4 - 1] * temp;
d__ *= temp;
} else {
z__[j4] = z__[j4 + 1] * (z__[j4 - 1] / z__[j4 - 2]);
d__ = z__[j4 + 1] * (d__ / z__[j4 - 2]);
}
*dmin__ = min(*dmin__,d__);
/* Computing MIN */
d__1 = emin, d__2 = z__[j4];
emin = min(d__1,d__2);
/* L10: */
}
} else {
i__1 = *n0 - 3 << 2;
for (j4 = *i0 << 2; j4 <= i__1; j4 += 4) {
z__[j4 - 3] = d__ + z__[j4];
if (z__[j4 - 3] == 0.) {
z__[j4 - 1] = 0.;
d__ = z__[j4 + 2];
*dmin__ = d__;
emin = 0.;
} else if (safmin * z__[j4 + 2] < z__[j4 - 3] && safmin * z__[j4
- 3] < z__[j4 + 2]) {
temp = z__[j4 + 2] / z__[j4 - 3];
z__[j4 - 1] = z__[j4] * temp;
d__ *= temp;
} else {
z__[j4 - 1] = z__[j4 + 2] * (z__[j4] / z__[j4 - 3]);
d__ = z__[j4 + 2] * (d__ / z__[j4 - 3]);
}
*dmin__ = min(*dmin__,d__);
/* Computing MIN */
d__1 = emin, d__2 = z__[j4 - 1];
emin = min(d__1,d__2);
/* L20: */
}
}
/* Unroll last two steps. */
*dnm2 = d__;
*dmin2 = *dmin__;
j4 = (*n0 - 2 << 2) - *pp;
j4p2 = j4 + (*pp << 1) - 1;
z__[j4 - 2] = *dnm2 + z__[j4p2];
if (z__[j4 - 2] == 0.) {
z__[j4] = 0.;
*dnm1 = z__[j4p2 + 2];
*dmin__ = *dnm1;
emin = 0.;
} else if (safmin * z__[j4p2 + 2] < z__[j4 - 2] && safmin * z__[j4 - 2] <
z__[j4p2 + 2]) {
temp = z__[j4p2 + 2] / z__[j4 - 2];
z__[j4] = z__[j4p2] * temp;
*dnm1 = *dnm2 * temp;
} else {
z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]);
*dnm1 = z__[j4p2 + 2] * (*dnm2 / z__[j4 - 2]);
}
*dmin__ = min(*dmin__,*dnm1);
*dmin1 = *dmin__;
j4 += 4;
j4p2 = j4 + (*pp << 1) - 1;
z__[j4 - 2] = *dnm1 + z__[j4p2];
if (z__[j4 - 2] == 0.) {
z__[j4] = 0.;
*dn = z__[j4p2 + 2];
*dmin__ = *dn;
emin = 0.;
} else if (safmin * z__[j4p2 + 2] < z__[j4 - 2] && safmin * z__[j4 - 2] <
z__[j4p2 + 2]) {
temp = z__[j4p2 + 2] / z__[j4 - 2];
z__[j4] = z__[j4p2] * temp;
*dn = *dnm1 * temp;
} else {
z__[j4] = z__[j4p2 + 2] * (z__[j4p2] / z__[j4 - 2]);
*dn = z__[j4p2 + 2] * (*dnm1 / z__[j4 - 2]);
}
*dmin__ = min(*dmin__,*dn);
z__[j4 + 2] = *dn;
z__[(*n0 << 2) - *pp] = emin;
return 0;
/* End of DLASQ6 */
} /* dlasq6_ */
/* Subroutine */ int dlasr_(char *side, char *pivot, char *direct, integer *m,
integer *n, doublereal *c__, doublereal *s, doublereal *a, integer *
lda)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2;
/* Local variables */
static integer i__, j, info;
static doublereal temp;
extern logical lsame_(char *, char *);
static doublereal ctemp, stemp;
extern /* Subroutine */ int xerbla_(char *, integer *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLASR applies a sequence of plane rotations to a real matrix A,
from either the left or the right.
When SIDE = 'L', the transformation takes the form
A := P*A
and when SIDE = 'R', the transformation takes the form
A := A*P**T
where P is an orthogonal matrix consisting of a sequence of z plane
rotations, with z = M when SIDE = 'L' and z = N when SIDE = 'R',
and P**T is the transpose of P.
When DIRECT = 'F' (Forward sequence), then
P = P(z-1) * ... * P(2) * P(1)
and when DIRECT = 'B' (Backward sequence), then
P = P(1) * P(2) * ... * P(z-1)
where P(k) is a plane rotation matrix defined by the 2-by-2 rotation
R(k) = ( c(k) s(k) )
= ( -s(k) c(k) ).
When PIVOT = 'V' (Variable pivot), the rotation is performed
for the plane (k,k+1), i.e., P(k) has the form
P(k) = ( 1 )
( ... )
( 1 )
( c(k) s(k) )
( -s(k) c(k) )
( 1 )
( ... )
( 1 )
where R(k) appears as a rank-2 modification to the identity matrix in
rows and columns k and k+1.
When PIVOT = 'T' (Top pivot), the rotation is performed for the
plane (1,k+1), so P(k) has the form
P(k) = ( c(k) s(k) )
( 1 )
( ... )
( 1 )
( -s(k) c(k) )
( 1 )
( ... )
( 1 )
where R(k) appears in rows and columns 1 and k+1.
Similarly, when PIVOT = 'B' (Bottom pivot), the rotation is
performed for the plane (k,z), giving P(k) the form
P(k) = ( 1 )
( ... )
( 1 )
( c(k) s(k) )
( 1 )
( ... )
( 1 )
( -s(k) c(k) )
where R(k) appears in rows and columns k and z. The rotations are
performed without ever forming P(k) explicitly.
Arguments
=========
SIDE (input) CHARACTER*1
Specifies whether the plane rotation matrix P is applied to
A on the left or the right.
= 'L': Left, compute A := P*A
= 'R': Right, compute A:= A*P**T
PIVOT (input) CHARACTER*1
Specifies the plane for which P(k) is a plane rotation
matrix.
= 'V': Variable pivot, the plane (k,k+1)
= 'T': Top pivot, the plane (1,k+1)
= 'B': Bottom pivot, the plane (k,z)
DIRECT (input) CHARACTER*1
Specifies whether P is a forward or backward sequence of
plane rotations.
= 'F': Forward, P = P(z-1)*...*P(2)*P(1)
= 'B': Backward, P = P(1)*P(2)*...*P(z-1)
M (input) INTEGER
The number of rows of the matrix A. If m <= 1, an immediate
return is effected.
N (input) INTEGER
The number of columns of the matrix A. If n <= 1, an
immediate return is effected.
C (input) DOUBLE PRECISION array, dimension
(M-1) if SIDE = 'L'
(N-1) if SIDE = 'R'
The cosines c(k) of the plane rotations.
S (input) DOUBLE PRECISION array, dimension
(M-1) if SIDE = 'L'
(N-1) if SIDE = 'R'
The sines s(k) of the plane rotations. The 2-by-2 plane
rotation part of the matrix P(k), R(k), has the form
R(k) = ( c(k) s(k) )
( -s(k) c(k) ).
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
The M-by-N matrix A. On exit, A is overwritten by P*A if
SIDE = 'R' or by A*P**T if SIDE = 'L'.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
=====================================================================
Test the input parameters
*/
/* Parameter adjustments */
--c__;
--s;
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
info = 0;
if (! (lsame_(side, "L") || lsame_(side, "R"))) {
info = 1;
} else if (! (lsame_(pivot, "V") || lsame_(pivot,
"T") || lsame_(pivot, "B"))) {
info = 2;
} else if (! (lsame_(direct, "F") || lsame_(direct,
"B"))) {
info = 3;
} else if (*m < 0) {
info = 4;
} else if (*n < 0) {
info = 5;
} else if (*lda < max(1,*m)) {
info = 9;
}
if (info != 0) {
xerbla_("DLASR ", &info);
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0) {
return 0;
}
if (lsame_(side, "L")) {
/* Form P * A */
if (lsame_(pivot, "V")) {
if (lsame_(direct, "F")) {
i__1 = *m - 1;
for (j = 1; j <= i__1; ++j) {
ctemp = c__[j];
stemp = s[j];
if (ctemp != 1. || stemp != 0.) {
i__2 = *n;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = a[j + 1 + i__ * a_dim1];
a[j + 1 + i__ * a_dim1] = ctemp * temp - stemp *
a[j + i__ * a_dim1];
a[j + i__ * a_dim1] = stemp * temp + ctemp * a[j
+ i__ * a_dim1];
/* L10: */
}
}
/* L20: */
}
} else if (lsame_(direct, "B")) {
for (j = *m - 1; j >= 1; --j) {
ctemp = c__[j];
stemp = s[j];
if (ctemp != 1. || stemp != 0.) {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
temp = a[j + 1 + i__ * a_dim1];
a[j + 1 + i__ * a_dim1] = ctemp * temp - stemp *
a[j + i__ * a_dim1];
a[j + i__ * a_dim1] = stemp * temp + ctemp * a[j
+ i__ * a_dim1];
/* L30: */
}
}
/* L40: */
}
}
} else if (lsame_(pivot, "T")) {
if (lsame_(direct, "F")) {
i__1 = *m;
for (j = 2; j <= i__1; ++j) {
ctemp = c__[j - 1];
stemp = s[j - 1];
if (ctemp != 1. || stemp != 0.) {
i__2 = *n;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = a[j + i__ * a_dim1];
a[j + i__ * a_dim1] = ctemp * temp - stemp * a[
i__ * a_dim1 + 1];
a[i__ * a_dim1 + 1] = stemp * temp + ctemp * a[
i__ * a_dim1 + 1];
/* L50: */
}
}
/* L60: */
}
} else if (lsame_(direct, "B")) {
for (j = *m; j >= 2; --j) {
ctemp = c__[j - 1];
stemp = s[j - 1];
if (ctemp != 1. || stemp != 0.) {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
temp = a[j + i__ * a_dim1];
a[j + i__ * a_dim1] = ctemp * temp - stemp * a[
i__ * a_dim1 + 1];
a[i__ * a_dim1 + 1] = stemp * temp + ctemp * a[
i__ * a_dim1 + 1];
/* L70: */
}
}
/* L80: */
}
}
} else if (lsame_(pivot, "B")) {
if (lsame_(direct, "F")) {
i__1 = *m - 1;
for (j = 1; j <= i__1; ++j) {
ctemp = c__[j];
stemp = s[j];
if (ctemp != 1. || stemp != 0.) {
i__2 = *n;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = a[j + i__ * a_dim1];
a[j + i__ * a_dim1] = stemp * a[*m + i__ * a_dim1]
+ ctemp * temp;
a[*m + i__ * a_dim1] = ctemp * a[*m + i__ *
a_dim1] - stemp * temp;
/* L90: */
}
}
/* L100: */
}
} else if (lsame_(direct, "B")) {
for (j = *m - 1; j >= 1; --j) {
ctemp = c__[j];
stemp = s[j];
if (ctemp != 1. || stemp != 0.) {
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
temp = a[j + i__ * a_dim1];
a[j + i__ * a_dim1] = stemp * a[*m + i__ * a_dim1]
+ ctemp * temp;
a[*m + i__ * a_dim1] = ctemp * a[*m + i__ *
a_dim1] - stemp * temp;
/* L110: */
}
}
/* L120: */
}
}
}
} else if (lsame_(side, "R")) {
/* Form A * P' */
if (lsame_(pivot, "V")) {
if (lsame_(direct, "F")) {
i__1 = *n - 1;
for (j = 1; j <= i__1; ++j) {
ctemp = c__[j];
stemp = s[j];
if (ctemp != 1. || stemp != 0.) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = a[i__ + (j + 1) * a_dim1];
a[i__ + (j + 1) * a_dim1] = ctemp * temp - stemp *
a[i__ + j * a_dim1];
a[i__ + j * a_dim1] = stemp * temp + ctemp * a[
i__ + j * a_dim1];
/* L130: */
}
}
/* L140: */
}
} else if (lsame_(direct, "B")) {
for (j = *n - 1; j >= 1; --j) {
ctemp = c__[j];
stemp = s[j];
if (ctemp != 1. || stemp != 0.) {
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
temp = a[i__ + (j + 1) * a_dim1];
a[i__ + (j + 1) * a_dim1] = ctemp * temp - stemp *
a[i__ + j * a_dim1];
a[i__ + j * a_dim1] = stemp * temp + ctemp * a[
i__ + j * a_dim1];
/* L150: */
}
}
/* L160: */
}
}
} else if (lsame_(pivot, "T")) {
if (lsame_(direct, "F")) {
i__1 = *n;
for (j = 2; j <= i__1; ++j) {
ctemp = c__[j - 1];
stemp = s[j - 1];
if (ctemp != 1. || stemp != 0.) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = a[i__ + j * a_dim1];
a[i__ + j * a_dim1] = ctemp * temp - stemp * a[
i__ + a_dim1];
a[i__ + a_dim1] = stemp * temp + ctemp * a[i__ +
a_dim1];
/* L170: */
}
}
/* L180: */
}
} else if (lsame_(direct, "B")) {
for (j = *n; j >= 2; --j) {
ctemp = c__[j - 1];
stemp = s[j - 1];
if (ctemp != 1. || stemp != 0.) {
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
temp = a[i__ + j * a_dim1];
a[i__ + j * a_dim1] = ctemp * temp - stemp * a[
i__ + a_dim1];
a[i__ + a_dim1] = stemp * temp + ctemp * a[i__ +
a_dim1];
/* L190: */
}
}
/* L200: */
}
}
} else if (lsame_(pivot, "B")) {
if (lsame_(direct, "F")) {
i__1 = *n - 1;
for (j = 1; j <= i__1; ++j) {
ctemp = c__[j];
stemp = s[j];
if (ctemp != 1. || stemp != 0.) {
i__2 = *m;
for (i__ = 1; i__ <= i__2; ++i__) {
temp = a[i__ + j * a_dim1];
a[i__ + j * a_dim1] = stemp * a[i__ + *n * a_dim1]
+ ctemp * temp;
a[i__ + *n * a_dim1] = ctemp * a[i__ + *n *
a_dim1] - stemp * temp;
/* L210: */
}
}
/* L220: */
}
} else if (lsame_(direct, "B")) {
for (j = *n - 1; j >= 1; --j) {
ctemp = c__[j];
stemp = s[j];
if (ctemp != 1. || stemp != 0.) {
i__1 = *m;
for (i__ = 1; i__ <= i__1; ++i__) {
temp = a[i__ + j * a_dim1];
a[i__ + j * a_dim1] = stemp * a[i__ + *n * a_dim1]
+ ctemp * temp;
a[i__ + *n * a_dim1] = ctemp * a[i__ + *n *
a_dim1] - stemp * temp;
/* L230: */
}
}
/* L240: */
}
}
}
}
return 0;
/* End of DLASR */
} /* dlasr_ */
/* Subroutine */ int dlasrt_(char *id, integer *n, doublereal *d__, integer *
info)
{
/* System generated locals */
integer i__1, i__2;
/* Local variables */
static integer i__, j;
static doublereal d1, d2, d3;
static integer dir;
static doublereal tmp;
static integer endd;
extern logical lsame_(char *, char *);
static integer stack[64] /* was [2][32] */;
static doublereal dmnmx;
static integer start;
extern /* Subroutine */ int xerbla_(char *, integer *);
static integer stkpnt;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
Sort the numbers in D in increasing order (if ID = 'I') or
in decreasing order (if ID = 'D' ).
Use Quick Sort, reverting to Insertion sort on arrays of
size <= 20. Dimension of STACK limits N to about 2**32.
Arguments
=========
ID (input) CHARACTER*1
= 'I': sort D in increasing order;
= 'D': sort D in decreasing order.
N (input) INTEGER
The length of the array D.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, the array to be sorted.
On exit, D has been sorted into increasing order
(D(1) <= ... <= D(N) ) or into decreasing order
(D(1) >= ... >= D(N) ), depending on ID.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input paramters.
*/
/* Parameter adjustments */
--d__;
/* Function Body */
*info = 0;
dir = -1;
if (lsame_(id, "D")) {
dir = 0;
} else if (lsame_(id, "I")) {
dir = 1;
}
if (dir == -1) {
*info = -1;
} else if (*n < 0) {
*info = -2;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLASRT", &i__1);
return 0;
}
/* Quick return if possible */
if (*n <= 1) {
return 0;
}
stkpnt = 1;
stack[0] = 1;
stack[1] = *n;
L10:
start = stack[(stkpnt << 1) - 2];
endd = stack[(stkpnt << 1) - 1];
--stkpnt;
if (endd - start <= 20 && endd - start > 0) {
/* Do Insertion sort on D( START:ENDD ) */
if (dir == 0) {
/* Sort into decreasing order */
i__1 = endd;
for (i__ = start + 1; i__ <= i__1; ++i__) {
i__2 = start + 1;
for (j = i__; j >= i__2; --j) {
if (d__[j] > d__[j - 1]) {
dmnmx = d__[j];
d__[j] = d__[j - 1];
d__[j - 1] = dmnmx;
} else {
goto L30;
}
/* L20: */
}
L30:
;
}
} else {
/* Sort into increasing order */
i__1 = endd;
for (i__ = start + 1; i__ <= i__1; ++i__) {
i__2 = start + 1;
for (j = i__; j >= i__2; --j) {
if (d__[j] < d__[j - 1]) {
dmnmx = d__[j];
d__[j] = d__[j - 1];
d__[j - 1] = dmnmx;
} else {
goto L50;
}
/* L40: */
}
L50:
;
}
}
} else if (endd - start > 20) {
/*
Partition D( START:ENDD ) and stack parts, largest one first
Choose partition entry as median of 3
*/
d1 = d__[start];
d2 = d__[endd];
i__ = (start + endd) / 2;
d3 = d__[i__];
if (d1 < d2) {
if (d3 < d1) {
dmnmx = d1;
} else if (d3 < d2) {
dmnmx = d3;
} else {
dmnmx = d2;
}
} else {
if (d3 < d2) {
dmnmx = d2;
} else if (d3 < d1) {
dmnmx = d3;
} else {
dmnmx = d1;
}
}
if (dir == 0) {
/* Sort into decreasing order */
i__ = start - 1;
j = endd + 1;
L60:
L70:
--j;
if (d__[j] < dmnmx) {
goto L70;
}
L80:
++i__;
if (d__[i__] > dmnmx) {
goto L80;
}
if (i__ < j) {
tmp = d__[i__];
d__[i__] = d__[j];
d__[j] = tmp;
goto L60;
}
if (j - start > endd - j - 1) {
++stkpnt;
stack[(stkpnt << 1) - 2] = start;
stack[(stkpnt << 1) - 1] = j;
++stkpnt;
stack[(stkpnt << 1) - 2] = j + 1;
stack[(stkpnt << 1) - 1] = endd;
} else {
++stkpnt;
stack[(stkpnt << 1) - 2] = j + 1;
stack[(stkpnt << 1) - 1] = endd;
++stkpnt;
stack[(stkpnt << 1) - 2] = start;
stack[(stkpnt << 1) - 1] = j;
}
} else {
/* Sort into increasing order */
i__ = start - 1;
j = endd + 1;
L90:
L100:
--j;
if (d__[j] > dmnmx) {
goto L100;
}
L110:
++i__;
if (d__[i__] < dmnmx) {
goto L110;
}
if (i__ < j) {
tmp = d__[i__];
d__[i__] = d__[j];
d__[j] = tmp;
goto L90;
}
if (j - start > endd - j - 1) {
++stkpnt;
stack[(stkpnt << 1) - 2] = start;
stack[(stkpnt << 1) - 1] = j;
++stkpnt;
stack[(stkpnt << 1) - 2] = j + 1;
stack[(stkpnt << 1) - 1] = endd;
} else {
++stkpnt;
stack[(stkpnt << 1) - 2] = j + 1;
stack[(stkpnt << 1) - 1] = endd;
++stkpnt;
stack[(stkpnt << 1) - 2] = start;
stack[(stkpnt << 1) - 1] = j;
}
}
}
if (stkpnt > 0) {
goto L10;
}
return 0;
/* End of DLASRT */
} /* dlasrt_ */
/* Subroutine */ int dlassq_(integer *n, doublereal *x, integer *incx,
doublereal *scale, doublereal *sumsq)
{
/* System generated locals */
integer i__1, i__2;
doublereal d__1;
/* Local variables */
static integer ix;
static doublereal absxi;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLASSQ returns the values scl and smsq such that
( scl**2 )*smsq = x( 1 )**2 +...+ x( n )**2 + ( scale**2 )*sumsq,
where x( i ) = X( 1 + ( i - 1 )*INCX ). The value of sumsq is
assumed to be non-negative and scl returns the value
scl = max( scale, abs( x( i ) ) ).
scale and sumsq must be supplied in SCALE and SUMSQ and
scl and smsq are overwritten on SCALE and SUMSQ respectively.
The routine makes only one pass through the vector x.
Arguments
=========
N (input) INTEGER
The number of elements to be used from the vector X.
X (input) DOUBLE PRECISION array, dimension (N)
The vector for which a scaled sum of squares is computed.
x( i ) = X( 1 + ( i - 1 )*INCX ), 1 <= i <= n.
INCX (input) INTEGER
The increment between successive values of the vector X.
INCX > 0.
SCALE (input/output) DOUBLE PRECISION
On entry, the value scale in the equation above.
On exit, SCALE is overwritten with scl , the scaling factor
for the sum of squares.
SUMSQ (input/output) DOUBLE PRECISION
On entry, the value sumsq in the equation above.
On exit, SUMSQ is overwritten with smsq , the basic sum of
squares from which scl has been factored out.
=====================================================================
*/
/* Parameter adjustments */
--x;
/* Function Body */
if (*n > 0) {
i__1 = (*n - 1) * *incx + 1;
i__2 = *incx;
for (ix = 1; i__2 < 0 ? ix >= i__1 : ix <= i__1; ix += i__2) {
if (x[ix] != 0.) {
absxi = (d__1 = x[ix], abs(d__1));
if (*scale < absxi) {
/* Computing 2nd power */
d__1 = *scale / absxi;
*sumsq = *sumsq * (d__1 * d__1) + 1;
*scale = absxi;
} else {
/* Computing 2nd power */
d__1 = absxi / *scale;
*sumsq += d__1 * d__1;
}
}
/* L10: */
}
}
return 0;
/* End of DLASSQ */
} /* dlassq_ */
/* Subroutine */ int dlasv2_(doublereal *f, doublereal *g, doublereal *h__,
doublereal *ssmin, doublereal *ssmax, doublereal *snr, doublereal *
csr, doublereal *snl, doublereal *csl)
{
/* System generated locals */
doublereal d__1;
/* Local variables */
static doublereal a, d__, l, m, r__, s, t, fa, ga, ha, ft, gt, ht, mm, tt,
clt, crt, slt, srt;
static integer pmax;
static doublereal temp;
static logical swap;
static doublereal tsign;
static logical gasmal;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLASV2 computes the singular value decomposition of a 2-by-2
triangular matrix
[ F G ]
[ 0 H ].
On return, abs(SSMAX) is the larger singular value, abs(SSMIN) is the
smaller singular value, and (CSL,SNL) and (CSR,SNR) are the left and
right singular vectors for abs(SSMAX), giving the decomposition
[ CSL SNL ] [ F G ] [ CSR -SNR ] = [ SSMAX 0 ]
[-SNL CSL ] [ 0 H ] [ SNR CSR ] [ 0 SSMIN ].
Arguments
=========
F (input) DOUBLE PRECISION
The (1,1) element of the 2-by-2 matrix.
G (input) DOUBLE PRECISION
The (1,2) element of the 2-by-2 matrix.
H (input) DOUBLE PRECISION
The (2,2) element of the 2-by-2 matrix.
SSMIN (output) DOUBLE PRECISION
abs(SSMIN) is the smaller singular value.
SSMAX (output) DOUBLE PRECISION
abs(SSMAX) is the larger singular value.
SNL (output) DOUBLE PRECISION
CSL (output) DOUBLE PRECISION
The vector (CSL, SNL) is a unit left singular vector for the
singular value abs(SSMAX).
SNR (output) DOUBLE PRECISION
CSR (output) DOUBLE PRECISION
The vector (CSR, SNR) is a unit right singular vector for the
singular value abs(SSMAX).
Further Details
===============
Any input parameter may be aliased with any output parameter.
Barring over/underflow and assuming a guard digit in subtraction, all
output quantities are correct to within a few units in the last
place (ulps).
In IEEE arithmetic, the code works correctly if one matrix element is
infinite.
Overflow will not occur unless the largest singular value itself
overflows or is within a few ulps of overflow. (On machines with
partial overflow, like the Cray, overflow may occur if the largest
singular value is within a factor of 2 of overflow.)
Underflow is harmless if underflow is gradual. Otherwise, results
may correspond to a matrix modified by perturbations of size near
the underflow threshold.
=====================================================================
*/
ft = *f;
fa = abs(ft);
ht = *h__;
ha = abs(*h__);
/*
PMAX points to the maximum absolute element of matrix
PMAX = 1 if F largest in absolute values
PMAX = 2 if G largest in absolute values
PMAX = 3 if H largest in absolute values
*/
pmax = 1;
swap = ha > fa;
if (swap) {
pmax = 3;
temp = ft;
ft = ht;
ht = temp;
temp = fa;
fa = ha;
ha = temp;
/* Now FA .ge. HA */
}
gt = *g;
ga = abs(gt);
if (ga == 0.) {
/* Diagonal matrix */
*ssmin = ha;
*ssmax = fa;
clt = 1.;
crt = 1.;
slt = 0.;
srt = 0.;
} else {
gasmal = TRUE_;
if (ga > fa) {
pmax = 2;
if (fa / ga < EPSILON) {
/* Case of very large GA */
gasmal = FALSE_;
*ssmax = ga;
if (ha > 1.) {
*ssmin = fa / (ga / ha);
} else {
*ssmin = fa / ga * ha;
}
clt = 1.;
slt = ht / gt;
srt = 1.;
crt = ft / gt;
}
}
if (gasmal) {
/* Normal case */
d__ = fa - ha;
if (d__ == fa) {
/* Copes with infinite F or H */
l = 1.;
} else {
l = d__ / fa;
}
/* Note that 0 .le. L .le. 1 */
m = gt / ft;
/* Note that abs(M) .le. 1/macheps */
t = 2. - l;
/* Note that T .ge. 1 */
mm = m * m;
tt = t * t;
s = sqrt(tt + mm);
/* Note that 1 .le. S .le. 1 + 1/macheps */
if (l == 0.) {
r__ = abs(m);
} else {
r__ = sqrt(l * l + mm);
}
/* Note that 0 .le. R .le. 1 + 1/macheps */
a = (s + r__) * .5;
/* Note that 1 .le. A .le. 1 + abs(M) */
*ssmin = ha / a;
*ssmax = fa * a;
if (mm == 0.) {
/* Note that M is very tiny */
if (l == 0.) {
t = d_sign(&c_b3192, &ft) * d_sign(&c_b15, >);
} else {
t = gt / d_sign(&d__, &ft) + m / t;
}
} else {
t = (m / (s + t) + m / (r__ + l)) * (a + 1.);
}
l = sqrt(t * t + 4.);
crt = 2. / l;
srt = t / l;
clt = (crt + srt * m) / a;
slt = ht / ft * srt / a;
}
}
if (swap) {
*csl = srt;
*snl = crt;
*csr = slt;
*snr = clt;
} else {
*csl = clt;
*snl = slt;
*csr = crt;
*snr = srt;
}
/* Correct signs of SSMAX and SSMIN */
if (pmax == 1) {
tsign = d_sign(&c_b15, csr) * d_sign(&c_b15, csl) * d_sign(&c_b15, f);
}
if (pmax == 2) {
tsign = d_sign(&c_b15, snr) * d_sign(&c_b15, csl) * d_sign(&c_b15, g);
}
if (pmax == 3) {
tsign = d_sign(&c_b15, snr) * d_sign(&c_b15, snl) * d_sign(&c_b15,
h__);
}
*ssmax = d_sign(ssmax, &tsign);
d__1 = tsign * d_sign(&c_b15, f) * d_sign(&c_b15, h__);
*ssmin = d_sign(ssmin, &d__1);
return 0;
/* End of DLASV2 */
} /* dlasv2_ */
/* Subroutine */ int dlaswp_(integer *n, doublereal *a, integer *lda, integer
*k1, integer *k2, integer *ipiv, integer *incx)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer i__, j, k, i1, i2, n32, ip, ix, ix0, inc;
static doublereal temp;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLASWP performs a series of row interchanges on the matrix A.
One row interchange is initiated for each of rows K1 through K2 of A.
Arguments
=========
N (input) INTEGER
The number of columns of the matrix A.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the matrix of column dimension N to which the row
interchanges will be applied.
On exit, the permuted matrix.
LDA (input) INTEGER
The leading dimension of the array A.
K1 (input) INTEGER
The first element of IPIV for which a row interchange will
be done.
K2 (input) INTEGER
The last element of IPIV for which a row interchange will
be done.
IPIV (input) INTEGER array, dimension (K2*abs(INCX))
The vector of pivot indices. Only the elements in positions
K1 through K2 of IPIV are accessed.
IPIV(K) = L implies rows K and L are to be interchanged.
INCX (input) INTEGER
The increment between successive values of IPIV. If IPIV
is negative, the pivots are applied in reverse order.
Further Details
===============
Modified by
R. C. Whaley, Computer Science Dept., Univ. of Tenn., Knoxville, USA
=====================================================================
Interchange row I with row IPIV(I) for each of rows K1 through K2.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--ipiv;
/* Function Body */
if (*incx > 0) {
ix0 = *k1;
i1 = *k1;
i2 = *k2;
inc = 1;
} else if (*incx < 0) {
ix0 = (1 - *k2) * *incx + 1;
i1 = *k2;
i2 = *k1;
inc = -1;
} else {
return 0;
}
n32 = *n / 32 << 5;
if (n32 != 0) {
i__1 = n32;
for (j = 1; j <= i__1; j += 32) {
ix = ix0;
i__2 = i2;
i__3 = inc;
for (i__ = i1; i__3 < 0 ? i__ >= i__2 : i__ <= i__2; i__ += i__3)
{
ip = ipiv[ix];
if (ip != i__) {
i__4 = j + 31;
for (k = j; k <= i__4; ++k) {
temp = a[i__ + k * a_dim1];
a[i__ + k * a_dim1] = a[ip + k * a_dim1];
a[ip + k * a_dim1] = temp;
/* L10: */
}
}
ix += *incx;
/* L20: */
}
/* L30: */
}
}
if (n32 != *n) {
++n32;
ix = ix0;
i__1 = i2;
i__3 = inc;
for (i__ = i1; i__3 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__3) {
ip = ipiv[ix];
if (ip != i__) {
i__2 = *n;
for (k = n32; k <= i__2; ++k) {
temp = a[i__ + k * a_dim1];
a[i__ + k * a_dim1] = a[ip + k * a_dim1];
a[ip + k * a_dim1] = temp;
/* L40: */
}
}
ix += *incx;
/* L50: */
}
}
return 0;
/* End of DLASWP */
} /* dlaswp_ */
/* Subroutine */ int dlasy2_(logical *ltranl, logical *ltranr, integer *isgn,
integer *n1, integer *n2, doublereal *tl, integer *ldtl, doublereal *
tr, integer *ldtr, doublereal *b, integer *ldb, doublereal *scale,
doublereal *x, integer *ldx, doublereal *xnorm, integer *info)
{
/* Initialized data */
static integer locu12[4] = { 3,4,1,2 };
static integer locl21[4] = { 2,1,4,3 };
static integer locu22[4] = { 4,3,2,1 };
static logical xswpiv[4] = { FALSE_,FALSE_,TRUE_,TRUE_ };
static logical bswpiv[4] = { FALSE_,TRUE_,FALSE_,TRUE_ };
/* System generated locals */
integer b_dim1, b_offset, tl_dim1, tl_offset, tr_dim1, tr_offset, x_dim1,
x_offset;
doublereal d__1, d__2, d__3, d__4, d__5, d__6, d__7, d__8;
/* Local variables */
static integer i__, j, k;
static doublereal x2[2], l21, u11, u12;
static integer ip, jp;
static doublereal u22, t16[16] /* was [4][4] */, gam, bet, eps, sgn,
tmp[4], tau1, btmp[4], smin;
static integer ipiv;
static doublereal temp;
static integer jpiv[4];
static doublereal xmax;
static integer ipsv, jpsv;
static logical bswap;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *), dswap_(integer *, doublereal *, integer
*, doublereal *, integer *);
static logical xswap;
extern integer idamax_(integer *, doublereal *, integer *);
static doublereal smlnum;
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLASY2 solves for the N1 by N2 matrix X, 1 <= N1,N2 <= 2, in
op(TL)*X + ISGN*X*op(TR) = SCALE*B,
where TL is N1 by N1, TR is N2 by N2, B is N1 by N2, and ISGN = 1 or
-1. op(T) = T or T', where T' denotes the transpose of T.
Arguments
=========
LTRANL (input) LOGICAL
On entry, LTRANL specifies the op(TL):
= .FALSE., op(TL) = TL,
= .TRUE., op(TL) = TL'.
LTRANR (input) LOGICAL
On entry, LTRANR specifies the op(TR):
= .FALSE., op(TR) = TR,
= .TRUE., op(TR) = TR'.
ISGN (input) INTEGER
On entry, ISGN specifies the sign of the equation
as described before. ISGN may only be 1 or -1.
N1 (input) INTEGER
On entry, N1 specifies the order of matrix TL.
N1 may only be 0, 1 or 2.
N2 (input) INTEGER
On entry, N2 specifies the order of matrix TR.
N2 may only be 0, 1 or 2.
TL (input) DOUBLE PRECISION array, dimension (LDTL,2)
On entry, TL contains an N1 by N1 matrix.
LDTL (input) INTEGER
The leading dimension of the matrix TL. LDTL >= max(1,N1).
TR (input) DOUBLE PRECISION array, dimension (LDTR,2)
On entry, TR contains an N2 by N2 matrix.
LDTR (input) INTEGER
The leading dimension of the matrix TR. LDTR >= max(1,N2).
B (input) DOUBLE PRECISION array, dimension (LDB,2)
On entry, the N1 by N2 matrix B contains the right-hand
side of the equation.
LDB (input) INTEGER
The leading dimension of the matrix B. LDB >= max(1,N1).
SCALE (output) DOUBLE PRECISION
On exit, SCALE contains the scale factor. SCALE is chosen
less than or equal to 1 to prevent the solution overflowing.
X (output) DOUBLE PRECISION array, dimension (LDX,2)
On exit, X contains the N1 by N2 solution.
LDX (input) INTEGER
The leading dimension of the matrix X. LDX >= max(1,N1).
XNORM (output) DOUBLE PRECISION
On exit, XNORM is the infinity-norm of the solution.
INFO (output) INTEGER
On exit, INFO is set to
0: successful exit.
1: TL and TR have too close eigenvalues, so TL or
TR is perturbed to get a nonsingular equation.
NOTE: In the interests of speed, this routine does not
check the inputs for errors.
=====================================================================
*/
/* Parameter adjustments */
tl_dim1 = *ldtl;
tl_offset = 1 + tl_dim1;
tl -= tl_offset;
tr_dim1 = *ldtr;
tr_offset = 1 + tr_dim1;
tr -= tr_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
x_dim1 = *ldx;
x_offset = 1 + x_dim1;
x -= x_offset;
/* Function Body */
/* Do not check the input parameters for errors */
*info = 0;
/* Quick return if possible */
if (*n1 == 0 || *n2 == 0) {
return 0;
}
/* Set constants to control overflow */
eps = PRECISION;
smlnum = SAFEMINIMUM / eps;
sgn = (doublereal) (*isgn);
k = *n1 + *n1 + *n2 - 2;
switch (k) {
case 1: goto L10;
case 2: goto L20;
case 3: goto L30;
case 4: goto L50;
}
/* 1 by 1: TL11*X + SGN*X*TR11 = B11 */
L10:
tau1 = tl[tl_dim1 + 1] + sgn * tr[tr_dim1 + 1];
bet = abs(tau1);
if (bet <= smlnum) {
tau1 = smlnum;
bet = smlnum;
*info = 1;
}
*scale = 1.;
gam = (d__1 = b[b_dim1 + 1], abs(d__1));
if (smlnum * gam > bet) {
*scale = 1. / gam;
}
x[x_dim1 + 1] = b[b_dim1 + 1] * *scale / tau1;
*xnorm = (d__1 = x[x_dim1 + 1], abs(d__1));
return 0;
/*
1 by 2:
TL11*[X11 X12] + ISGN*[X11 X12]*op[TR11 TR12] = [B11 B12]
[TR21 TR22]
*/
L20:
/*
Computing MAX
Computing MAX
*/
d__7 = (d__1 = tl[tl_dim1 + 1], abs(d__1)), d__8 = (d__2 = tr[tr_dim1 + 1]
, abs(d__2)), d__7 = max(d__7,d__8), d__8 = (d__3 = tr[(tr_dim1 <<
1) + 1], abs(d__3)), d__7 = max(d__7,d__8), d__8 = (d__4 = tr[
tr_dim1 + 2], abs(d__4)), d__7 = max(d__7,d__8), d__8 = (d__5 =
tr[(tr_dim1 << 1) + 2], abs(d__5));
d__6 = eps * max(d__7,d__8);
smin = max(d__6,smlnum);
tmp[0] = tl[tl_dim1 + 1] + sgn * tr[tr_dim1 + 1];
tmp[3] = tl[tl_dim1 + 1] + sgn * tr[(tr_dim1 << 1) + 2];
if (*ltranr) {
tmp[1] = sgn * tr[tr_dim1 + 2];
tmp[2] = sgn * tr[(tr_dim1 << 1) + 1];
} else {
tmp[1] = sgn * tr[(tr_dim1 << 1) + 1];
tmp[2] = sgn * tr[tr_dim1 + 2];
}
btmp[0] = b[b_dim1 + 1];
btmp[1] = b[(b_dim1 << 1) + 1];
goto L40;
/*
2 by 1:
op[TL11 TL12]*[X11] + ISGN* [X11]*TR11 = [B11]
[TL21 TL22] [X21] [X21] [B21]
*/
L30:
/*
Computing MAX
Computing MAX
*/
d__7 = (d__1 = tr[tr_dim1 + 1], abs(d__1)), d__8 = (d__2 = tl[tl_dim1 + 1]
, abs(d__2)), d__7 = max(d__7,d__8), d__8 = (d__3 = tl[(tl_dim1 <<
1) + 1], abs(d__3)), d__7 = max(d__7,d__8), d__8 = (d__4 = tl[
tl_dim1 + 2], abs(d__4)), d__7 = max(d__7,d__8), d__8 = (d__5 =
tl[(tl_dim1 << 1) + 2], abs(d__5));
d__6 = eps * max(d__7,d__8);
smin = max(d__6,smlnum);
tmp[0] = tl[tl_dim1 + 1] + sgn * tr[tr_dim1 + 1];
tmp[3] = tl[(tl_dim1 << 1) + 2] + sgn * tr[tr_dim1 + 1];
if (*ltranl) {
tmp[1] = tl[(tl_dim1 << 1) + 1];
tmp[2] = tl[tl_dim1 + 2];
} else {
tmp[1] = tl[tl_dim1 + 2];
tmp[2] = tl[(tl_dim1 << 1) + 1];
}
btmp[0] = b[b_dim1 + 1];
btmp[1] = b[b_dim1 + 2];
L40:
/*
Solve 2 by 2 system using complete pivoting.
Set pivots less than SMIN to SMIN.
*/
ipiv = idamax_(&c__4, tmp, &c__1);
u11 = tmp[ipiv - 1];
if (abs(u11) <= smin) {
*info = 1;
u11 = smin;
}
u12 = tmp[locu12[ipiv - 1] - 1];
l21 = tmp[locl21[ipiv - 1] - 1] / u11;
u22 = tmp[locu22[ipiv - 1] - 1] - u12 * l21;
xswap = xswpiv[ipiv - 1];
bswap = bswpiv[ipiv - 1];
if (abs(u22) <= smin) {
*info = 1;
u22 = smin;
}
if (bswap) {
temp = btmp[1];
btmp[1] = btmp[0] - l21 * temp;
btmp[0] = temp;
} else {
btmp[1] -= l21 * btmp[0];
}
*scale = 1.;
if (smlnum * 2. * abs(btmp[1]) > abs(u22) || smlnum * 2. * abs(btmp[0]) >
abs(u11)) {
/* Computing MAX */
d__1 = abs(btmp[0]), d__2 = abs(btmp[1]);
*scale = .5 / max(d__1,d__2);
btmp[0] *= *scale;
btmp[1] *= *scale;
}
x2[1] = btmp[1] / u22;
x2[0] = btmp[0] / u11 - u12 / u11 * x2[1];
if (xswap) {
temp = x2[1];
x2[1] = x2[0];
x2[0] = temp;
}
x[x_dim1 + 1] = x2[0];
if (*n1 == 1) {
x[(x_dim1 << 1) + 1] = x2[1];
*xnorm = (d__1 = x[x_dim1 + 1], abs(d__1)) + (d__2 = x[(x_dim1 << 1)
+ 1], abs(d__2));
} else {
x[x_dim1 + 2] = x2[1];
/* Computing MAX */
d__3 = (d__1 = x[x_dim1 + 1], abs(d__1)), d__4 = (d__2 = x[x_dim1 + 2]
, abs(d__2));
*xnorm = max(d__3,d__4);
}
return 0;
/*
2 by 2:
op[TL11 TL12]*[X11 X12] +ISGN* [X11 X12]*op[TR11 TR12] = [B11 B12]
[TL21 TL22] [X21 X22] [X21 X22] [TR21 TR22] [B21 B22]
Solve equivalent 4 by 4 system using complete pivoting.
Set pivots less than SMIN to SMIN.
*/
L50:
/* Computing MAX */
d__5 = (d__1 = tr[tr_dim1 + 1], abs(d__1)), d__6 = (d__2 = tr[(tr_dim1 <<
1) + 1], abs(d__2)), d__5 = max(d__5,d__6), d__6 = (d__3 = tr[
tr_dim1 + 2], abs(d__3)), d__5 = max(d__5,d__6), d__6 = (d__4 =
tr[(tr_dim1 << 1) + 2], abs(d__4));
smin = max(d__5,d__6);
/* Computing MAX */
d__5 = smin, d__6 = (d__1 = tl[tl_dim1 + 1], abs(d__1)), d__5 = max(d__5,
d__6), d__6 = (d__2 = tl[(tl_dim1 << 1) + 1], abs(d__2)), d__5 =
max(d__5,d__6), d__6 = (d__3 = tl[tl_dim1 + 2], abs(d__3)), d__5 =
max(d__5,d__6), d__6 = (d__4 = tl[(tl_dim1 << 1) + 2], abs(d__4))
;
smin = max(d__5,d__6);
/* Computing MAX */
d__1 = eps * smin;
smin = max(d__1,smlnum);
btmp[0] = 0.;
dcopy_(&c__16, btmp, &c__0, t16, &c__1);
t16[0] = tl[tl_dim1 + 1] + sgn * tr[tr_dim1 + 1];
t16[5] = tl[(tl_dim1 << 1) + 2] + sgn * tr[tr_dim1 + 1];
t16[10] = tl[tl_dim1 + 1] + sgn * tr[(tr_dim1 << 1) + 2];
t16[15] = tl[(tl_dim1 << 1) + 2] + sgn * tr[(tr_dim1 << 1) + 2];
if (*ltranl) {
t16[4] = tl[tl_dim1 + 2];
t16[1] = tl[(tl_dim1 << 1) + 1];
t16[14] = tl[tl_dim1 + 2];
t16[11] = tl[(tl_dim1 << 1) + 1];
} else {
t16[4] = tl[(tl_dim1 << 1) + 1];
t16[1] = tl[tl_dim1 + 2];
t16[14] = tl[(tl_dim1 << 1) + 1];
t16[11] = tl[tl_dim1 + 2];
}
if (*ltranr) {
t16[8] = sgn * tr[(tr_dim1 << 1) + 1];
t16[13] = sgn * tr[(tr_dim1 << 1) + 1];
t16[2] = sgn * tr[tr_dim1 + 2];
t16[7] = sgn * tr[tr_dim1 + 2];
} else {
t16[8] = sgn * tr[tr_dim1 + 2];
t16[13] = sgn * tr[tr_dim1 + 2];
t16[2] = sgn * tr[(tr_dim1 << 1) + 1];
t16[7] = sgn * tr[(tr_dim1 << 1) + 1];
}
btmp[0] = b[b_dim1 + 1];
btmp[1] = b[b_dim1 + 2];
btmp[2] = b[(b_dim1 << 1) + 1];
btmp[3] = b[(b_dim1 << 1) + 2];
/* Perform elimination */
for (i__ = 1; i__ <= 3; ++i__) {
xmax = 0.;
for (ip = i__; ip <= 4; ++ip) {
for (jp = i__; jp <= 4; ++jp) {
if ((d__1 = t16[ip + (jp << 2) - 5], abs(d__1)) >= xmax) {
xmax = (d__1 = t16[ip + (jp << 2) - 5], abs(d__1));
ipsv = ip;
jpsv = jp;
}
/* L60: */
}
/* L70: */
}
if (ipsv != i__) {
dswap_(&c__4, &t16[ipsv - 1], &c__4, &t16[i__ - 1], &c__4);
temp = btmp[i__ - 1];
btmp[i__ - 1] = btmp[ipsv - 1];
btmp[ipsv - 1] = temp;
}
if (jpsv != i__) {
dswap_(&c__4, &t16[(jpsv << 2) - 4], &c__1, &t16[(i__ << 2) - 4],
&c__1);
}
jpiv[i__ - 1] = jpsv;
if ((d__1 = t16[i__ + (i__ << 2) - 5], abs(d__1)) < smin) {
*info = 1;
t16[i__ + (i__ << 2) - 5] = smin;
}
for (j = i__ + 1; j <= 4; ++j) {
t16[j + (i__ << 2) - 5] /= t16[i__ + (i__ << 2) - 5];
btmp[j - 1] -= t16[j + (i__ << 2) - 5] * btmp[i__ - 1];
for (k = i__ + 1; k <= 4; ++k) {
t16[j + (k << 2) - 5] -= t16[j + (i__ << 2) - 5] * t16[i__ + (
k << 2) - 5];
/* L80: */
}
/* L90: */
}
/* L100: */
}
if (abs(t16[15]) < smin) {
t16[15] = smin;
}
*scale = 1.;
if (smlnum * 8. * abs(btmp[0]) > abs(t16[0]) || smlnum * 8. * abs(btmp[1])
> abs(t16[5]) || smlnum * 8. * abs(btmp[2]) > abs(t16[10]) ||
smlnum * 8. * abs(btmp[3]) > abs(t16[15])) {
/* Computing MAX */
d__1 = abs(btmp[0]), d__2 = abs(btmp[1]), d__1 = max(d__1,d__2), d__2
= abs(btmp[2]), d__1 = max(d__1,d__2), d__2 = abs(btmp[3]);
*scale = .125 / max(d__1,d__2);
btmp[0] *= *scale;
btmp[1] *= *scale;
btmp[2] *= *scale;
btmp[3] *= *scale;
}
for (i__ = 1; i__ <= 4; ++i__) {
k = 5 - i__;
temp = 1. / t16[k + (k << 2) - 5];
tmp[k - 1] = btmp[k - 1] * temp;
for (j = k + 1; j <= 4; ++j) {
tmp[k - 1] -= temp * t16[k + (j << 2) - 5] * tmp[j - 1];
/* L110: */
}
/* L120: */
}
for (i__ = 1; i__ <= 3; ++i__) {
if (jpiv[4 - i__ - 1] != 4 - i__) {
temp = tmp[4 - i__ - 1];
tmp[4 - i__ - 1] = tmp[jpiv[4 - i__ - 1] - 1];
tmp[jpiv[4 - i__ - 1] - 1] = temp;
}
/* L130: */
}
x[x_dim1 + 1] = tmp[0];
x[x_dim1 + 2] = tmp[1];
x[(x_dim1 << 1) + 1] = tmp[2];
x[(x_dim1 << 1) + 2] = tmp[3];
/* Computing MAX */
d__1 = abs(tmp[0]) + abs(tmp[2]), d__2 = abs(tmp[1]) + abs(tmp[3]);
*xnorm = max(d__1,d__2);
return 0;
/* End of DLASY2 */
} /* dlasy2_ */
/* Subroutine */ int dlatrd_(char *uplo, integer *n, integer *nb, doublereal *
a, integer *lda, doublereal *e, doublereal *tau, doublereal *w,
integer *ldw)
{
/* System generated locals */
integer a_dim1, a_offset, w_dim1, w_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__, iw;
extern doublereal ddot_(integer *, doublereal *, integer *, doublereal *,
integer *);
static doublereal alpha;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dgemv_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *), daxpy_(integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *),
dsymv_(char *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *), dlarfg_(integer *, doublereal *, doublereal *, integer *,
doublereal *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLATRD reduces NB rows and columns of a real symmetric matrix A to
symmetric tridiagonal form by an orthogonal similarity
transformation Q' * A * Q, and returns the matrices V and W which are
needed to apply the transformation to the unreduced part of A.
If UPLO = 'U', DLATRD reduces the last NB rows and columns of a
matrix, of which the upper triangle is supplied;
if UPLO = 'L', DLATRD reduces the first NB rows and columns of a
matrix, of which the lower triangle is supplied.
This is an auxiliary routine called by DSYTRD.
Arguments
=========
UPLO (input) CHARACTER*1
Specifies whether the upper or lower triangular part of the
symmetric matrix A is stored:
= 'U': Upper triangular
= 'L': Lower triangular
N (input) INTEGER
The order of the matrix A.
NB (input) INTEGER
The number of rows and columns to be reduced.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the symmetric matrix A. If UPLO = 'U', the leading
n-by-n upper triangular part of A contains the upper
triangular part of the matrix A, and the strictly lower
triangular part of A is not referenced. If UPLO = 'L', the
leading n-by-n lower triangular part of A contains the lower
triangular part of the matrix A, and the strictly upper
triangular part of A is not referenced.
On exit:
if UPLO = 'U', the last NB columns have been reduced to
tridiagonal form, with the diagonal elements overwriting
the diagonal elements of A; the elements above the diagonal
with the array TAU, represent the orthogonal matrix Q as a
product of elementary reflectors;
if UPLO = 'L', the first NB columns have been reduced to
tridiagonal form, with the diagonal elements overwriting
the diagonal elements of A; the elements below the diagonal
with the array TAU, represent the orthogonal matrix Q as a
product of elementary reflectors.
See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= (1,N).
E (output) DOUBLE PRECISION array, dimension (N-1)
If UPLO = 'U', E(n-nb:n-1) contains the superdiagonal
elements of the last NB columns of the reduced matrix;
if UPLO = 'L', E(1:nb) contains the subdiagonal elements of
the first NB columns of the reduced matrix.
TAU (output) DOUBLE PRECISION array, dimension (N-1)
The scalar factors of the elementary reflectors, stored in
TAU(n-nb:n-1) if UPLO = 'U', and in TAU(1:nb) if UPLO = 'L'.
See Further Details.
W (output) DOUBLE PRECISION array, dimension (LDW,NB)
The n-by-nb matrix W required to update the unreduced part
of A.
LDW (input) INTEGER
The leading dimension of the array W. LDW >= max(1,N).
Further Details
===============
If UPLO = 'U', the matrix Q is represented as a product of elementary
reflectors
Q = H(n) H(n-1) . . . H(n-nb+1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(i:n) = 0 and v(i-1) = 1; v(1:i-1) is stored on exit in A(1:i-1,i),
and tau in TAU(i-1).
If UPLO = 'L', the matrix Q is represented as a product of elementary
reflectors
Q = H(1) H(2) . . . H(nb).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i) = 0 and v(i+1) = 1; v(i+1:n) is stored on exit in A(i+1:n,i),
and tau in TAU(i).
The elements of the vectors v together form the n-by-nb matrix V
which is needed, with W, to apply the transformation to the unreduced
part of the matrix, using a symmetric rank-2k update of the form:
A := A - V*W' - W*V'.
The contents of A on exit are illustrated by the following examples
with n = 5 and nb = 2:
if UPLO = 'U': if UPLO = 'L':
( a a a v4 v5 ) ( d )
( a a v4 v5 ) ( 1 d )
( a 1 v5 ) ( v1 1 a )
( d 1 ) ( v1 v2 a a )
( d ) ( v1 v2 a a a )
where d denotes a diagonal element of the reduced matrix, a denotes
an element of the original matrix that is unchanged, and vi denotes
an element of the vector defining H(i).
=====================================================================
Quick return if possible
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--e;
--tau;
w_dim1 = *ldw;
w_offset = 1 + w_dim1;
w -= w_offset;
/* Function Body */
if (*n <= 0) {
return 0;
}
if (lsame_(uplo, "U")) {
/* Reduce last NB columns of upper triangle */
i__1 = *n - *nb + 1;
for (i__ = *n; i__ >= i__1; --i__) {
iw = i__ - *n + *nb;
if (i__ < *n) {
/* Update A(1:i,i) */
i__2 = *n - i__;
dgemv_("No transpose", &i__, &i__2, &c_b151, &a[(i__ + 1) *
a_dim1 + 1], lda, &w[i__ + (iw + 1) * w_dim1], ldw, &
c_b15, &a[i__ * a_dim1 + 1], &c__1);
i__2 = *n - i__;
dgemv_("No transpose", &i__, &i__2, &c_b151, &w[(iw + 1) *
w_dim1 + 1], ldw, &a[i__ + (i__ + 1) * a_dim1], lda, &
c_b15, &a[i__ * a_dim1 + 1], &c__1);
}
if (i__ > 1) {
/*
Generate elementary reflector H(i) to annihilate
A(1:i-2,i)
*/
i__2 = i__ - 1;
dlarfg_(&i__2, &a[i__ - 1 + i__ * a_dim1], &a[i__ * a_dim1 +
1], &c__1, &tau[i__ - 1]);
e[i__ - 1] = a[i__ - 1 + i__ * a_dim1];
a[i__ - 1 + i__ * a_dim1] = 1.;
/* Compute W(1:i-1,i) */
i__2 = i__ - 1;
dsymv_("Upper", &i__2, &c_b15, &a[a_offset], lda, &a[i__ *
a_dim1 + 1], &c__1, &c_b29, &w[iw * w_dim1 + 1], &
c__1);
if (i__ < *n) {
i__2 = i__ - 1;
i__3 = *n - i__;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &w[(iw + 1) *
w_dim1 + 1], ldw, &a[i__ * a_dim1 + 1], &c__1, &
c_b29, &w[i__ + 1 + iw * w_dim1], &c__1);
i__2 = i__ - 1;
i__3 = *n - i__;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &a[(i__ + 1)
* a_dim1 + 1], lda, &w[i__ + 1 + iw * w_dim1], &
c__1, &c_b15, &w[iw * w_dim1 + 1], &c__1);
i__2 = i__ - 1;
i__3 = *n - i__;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &a[(i__ + 1) *
a_dim1 + 1], lda, &a[i__ * a_dim1 + 1], &c__1, &
c_b29, &w[i__ + 1 + iw * w_dim1], &c__1);
i__2 = i__ - 1;
i__3 = *n - i__;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &w[(iw + 1)
* w_dim1 + 1], ldw, &w[i__ + 1 + iw * w_dim1], &
c__1, &c_b15, &w[iw * w_dim1 + 1], &c__1);
}
i__2 = i__ - 1;
dscal_(&i__2, &tau[i__ - 1], &w[iw * w_dim1 + 1], &c__1);
i__2 = i__ - 1;
alpha = tau[i__ - 1] * -.5 * ddot_(&i__2, &w[iw * w_dim1 + 1],
&c__1, &a[i__ * a_dim1 + 1], &c__1);
i__2 = i__ - 1;
daxpy_(&i__2, &alpha, &a[i__ * a_dim1 + 1], &c__1, &w[iw *
w_dim1 + 1], &c__1);
}
/* L10: */
}
} else {
/* Reduce first NB columns of lower triangle */
i__1 = *nb;
for (i__ = 1; i__ <= i__1; ++i__) {
/* Update A(i:n,i) */
i__2 = *n - i__ + 1;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &a[i__ + a_dim1],
lda, &w[i__ + w_dim1], ldw, &c_b15, &a[i__ + i__ * a_dim1]
, &c__1);
i__2 = *n - i__ + 1;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &w[i__ + w_dim1],
ldw, &a[i__ + a_dim1], lda, &c_b15, &a[i__ + i__ * a_dim1]
, &c__1);
if (i__ < *n) {
/*
Generate elementary reflector H(i) to annihilate
A(i+2:n,i)
*/
i__2 = *n - i__;
/* Computing MIN */
i__3 = i__ + 2;
dlarfg_(&i__2, &a[i__ + 1 + i__ * a_dim1], &a[min(i__3,*n) +
i__ * a_dim1], &c__1, &tau[i__]);
e[i__] = a[i__ + 1 + i__ * a_dim1];
a[i__ + 1 + i__ * a_dim1] = 1.;
/* Compute W(i+1:n,i) */
i__2 = *n - i__;
dsymv_("Lower", &i__2, &c_b15, &a[i__ + 1 + (i__ + 1) *
a_dim1], lda, &a[i__ + 1 + i__ * a_dim1], &c__1, &
c_b29, &w[i__ + 1 + i__ * w_dim1], &c__1);
i__2 = *n - i__;
i__3 = i__ - 1;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &w[i__ + 1 + w_dim1]
, ldw, &a[i__ + 1 + i__ * a_dim1], &c__1, &c_b29, &w[
i__ * w_dim1 + 1], &c__1);
i__2 = *n - i__;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &a[i__ + 1 +
a_dim1], lda, &w[i__ * w_dim1 + 1], &c__1, &c_b15, &w[
i__ + 1 + i__ * w_dim1], &c__1);
i__2 = *n - i__;
i__3 = i__ - 1;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &a[i__ + 1 + a_dim1]
, lda, &a[i__ + 1 + i__ * a_dim1], &c__1, &c_b29, &w[
i__ * w_dim1 + 1], &c__1);
i__2 = *n - i__;
i__3 = i__ - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &w[i__ + 1 +
w_dim1], ldw, &w[i__ * w_dim1 + 1], &c__1, &c_b15, &w[
i__ + 1 + i__ * w_dim1], &c__1);
i__2 = *n - i__;
dscal_(&i__2, &tau[i__], &w[i__ + 1 + i__ * w_dim1], &c__1);
i__2 = *n - i__;
alpha = tau[i__] * -.5 * ddot_(&i__2, &w[i__ + 1 + i__ *
w_dim1], &c__1, &a[i__ + 1 + i__ * a_dim1], &c__1);
i__2 = *n - i__;
daxpy_(&i__2, &alpha, &a[i__ + 1 + i__ * a_dim1], &c__1, &w[
i__ + 1 + i__ * w_dim1], &c__1);
}
/* L20: */
}
}
return 0;
/* End of DLATRD */
} /* dlatrd_ */
/* Subroutine */ int dlauu2_(char *uplo, integer *n, doublereal *a, integer *
lda, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__;
static doublereal aii;
extern doublereal ddot_(integer *, doublereal *, integer *, doublereal *,
integer *);
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dgemv_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *);
static logical upper;
extern /* Subroutine */ int xerbla_(char *, integer *);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAUU2 computes the product U * U' or L' * L, where the triangular
factor U or L is stored in the upper or lower triangular part of
the array A.
If UPLO = 'U' or 'u' then the upper triangle of the result is stored,
overwriting the factor U in A.
If UPLO = 'L' or 'l' then the lower triangle of the result is stored,
overwriting the factor L in A.
This is the unblocked form of the algorithm, calling Level 2 BLAS.
Arguments
=========
UPLO (input) CHARACTER*1
Specifies whether the triangular factor stored in the array A
is upper or lower triangular:
= 'U': Upper triangular
= 'L': Lower triangular
N (input) INTEGER
The order of the triangular factor U or L. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the triangular factor U or L.
On exit, if UPLO = 'U', the upper triangle of A is
overwritten with the upper triangle of the product U * U';
if UPLO = 'L', the lower triangle of A is overwritten with
the lower triangle of the product L' * L.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -k, the k-th argument had an illegal value
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAUU2", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (upper) {
/* Compute the product U * U'. */
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
aii = a[i__ + i__ * a_dim1];
if (i__ < *n) {
i__2 = *n - i__ + 1;
a[i__ + i__ * a_dim1] = ddot_(&i__2, &a[i__ + i__ * a_dim1],
lda, &a[i__ + i__ * a_dim1], lda);
i__2 = i__ - 1;
i__3 = *n - i__;
dgemv_("No transpose", &i__2, &i__3, &c_b15, &a[(i__ + 1) *
a_dim1 + 1], lda, &a[i__ + (i__ + 1) * a_dim1], lda, &
aii, &a[i__ * a_dim1 + 1], &c__1);
} else {
dscal_(&i__, &aii, &a[i__ * a_dim1 + 1], &c__1);
}
/* L10: */
}
} else {
/* Compute the product L' * L. */
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
aii = a[i__ + i__ * a_dim1];
if (i__ < *n) {
i__2 = *n - i__ + 1;
a[i__ + i__ * a_dim1] = ddot_(&i__2, &a[i__ + i__ * a_dim1], &
c__1, &a[i__ + i__ * a_dim1], &c__1);
i__2 = *n - i__;
i__3 = i__ - 1;
dgemv_("Transpose", &i__2, &i__3, &c_b15, &a[i__ + 1 + a_dim1]
, lda, &a[i__ + 1 + i__ * a_dim1], &c__1, &aii, &a[
i__ + a_dim1], lda);
} else {
dscal_(&i__, &aii, &a[i__ + a_dim1], lda);
}
/* L20: */
}
}
return 0;
/* End of DLAUU2 */
} /* dlauu2_ */
/* Subroutine */ int dlauum_(char *uplo, integer *n, doublereal *a, integer *
lda, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer i__, ib, nb;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dtrmm_(char *, char *, char *, char *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *);
static logical upper;
extern /* Subroutine */ int dsyrk_(char *, char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, doublereal *,
integer *), dlauu2_(char *, integer *,
doublereal *, integer *, integer *), xerbla_(char *,
integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
/*
-- LAPACK auxiliary routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DLAUUM computes the product U * U' or L' * L, where the triangular
factor U or L is stored in the upper or lower triangular part of
the array A.
If UPLO = 'U' or 'u' then the upper triangle of the result is stored,
overwriting the factor U in A.
If UPLO = 'L' or 'l' then the lower triangle of the result is stored,
overwriting the factor L in A.
This is the blocked form of the algorithm, calling Level 3 BLAS.
Arguments
=========
UPLO (input) CHARACTER*1
Specifies whether the triangular factor stored in the array A
is upper or lower triangular:
= 'U': Upper triangular
= 'L': Lower triangular
N (input) INTEGER
The order of the triangular factor U or L. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the triangular factor U or L.
On exit, if UPLO = 'U', the upper triangle of A is
overwritten with the upper triangle of the product U * U';
if UPLO = 'L', the lower triangle of A is overwritten with
the lower triangle of the product L' * L.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -k, the k-th argument had an illegal value
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DLAUUM", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/* Determine the block size for this environment. */
nb = ilaenv_(&c__1, "DLAUUM", uplo, n, &c_n1, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
if (nb <= 1 || nb >= *n) {
/* Use unblocked code */
dlauu2_(uplo, n, &a[a_offset], lda, info);
} else {
/* Use blocked code */
if (upper) {
/* Compute the product U * U'. */
i__1 = *n;
i__2 = nb;
for (i__ = 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/* Computing MIN */
i__3 = nb, i__4 = *n - i__ + 1;
ib = min(i__3,i__4);
i__3 = i__ - 1;
dtrmm_("Right", "Upper", "Transpose", "Non-unit", &i__3, &ib,
&c_b15, &a[i__ + i__ * a_dim1], lda, &a[i__ * a_dim1
+ 1], lda)
;
dlauu2_("Upper", &ib, &a[i__ + i__ * a_dim1], lda, info);
if (i__ + ib <= *n) {
i__3 = i__ - 1;
i__4 = *n - i__ - ib + 1;
dgemm_("No transpose", "Transpose", &i__3, &ib, &i__4, &
c_b15, &a[(i__ + ib) * a_dim1 + 1], lda, &a[i__ +
(i__ + ib) * a_dim1], lda, &c_b15, &a[i__ *
a_dim1 + 1], lda);
i__3 = *n - i__ - ib + 1;
dsyrk_("Upper", "No transpose", &ib, &i__3, &c_b15, &a[
i__ + (i__ + ib) * a_dim1], lda, &c_b15, &a[i__ +
i__ * a_dim1], lda);
}
/* L10: */
}
} else {
/* Compute the product L' * L. */
i__2 = *n;
i__1 = nb;
for (i__ = 1; i__1 < 0 ? i__ >= i__2 : i__ <= i__2; i__ += i__1) {
/* Computing MIN */
i__3 = nb, i__4 = *n - i__ + 1;
ib = min(i__3,i__4);
i__3 = i__ - 1;
dtrmm_("Left", "Lower", "Transpose", "Non-unit", &ib, &i__3, &
c_b15, &a[i__ + i__ * a_dim1], lda, &a[i__ + a_dim1],
lda);
dlauu2_("Lower", &ib, &a[i__ + i__ * a_dim1], lda, info);
if (i__ + ib <= *n) {
i__3 = i__ - 1;
i__4 = *n - i__ - ib + 1;
dgemm_("Transpose", "No transpose", &ib, &i__3, &i__4, &
c_b15, &a[i__ + ib + i__ * a_dim1], lda, &a[i__ +
ib + a_dim1], lda, &c_b15, &a[i__ + a_dim1], lda);
i__3 = *n - i__ - ib + 1;
dsyrk_("Lower", "Transpose", &ib, &i__3, &c_b15, &a[i__ +
ib + i__ * a_dim1], lda, &c_b15, &a[i__ + i__ *
a_dim1], lda);
}
/* L20: */
}
}
}
return 0;
/* End of DLAUUM */
} /* dlauum_ */
/* Subroutine */ int dorg2r_(integer *m, integer *n, integer *k, doublereal *
a, integer *lda, doublereal *tau, doublereal *work, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2;
doublereal d__1;
/* Local variables */
static integer i__, j, l;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *), dlarf_(char *, integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *, doublereal *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORG2R generates an m by n real matrix Q with orthonormal columns,
which is defined as the first n columns of a product of k elementary
reflectors of order m
Q = H(1) H(2) . . . H(k)
as returned by DGEQRF.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix Q. M >= 0.
N (input) INTEGER
The number of columns of the matrix Q. M >= N >= 0.
K (input) INTEGER
The number of elementary reflectors whose product defines the
matrix Q. N >= K >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the i-th column must contain the vector which
defines the elementary reflector H(i), for i = 1,2,...,k, as
returned by DGEQRF in the first k columns of its array
argument A.
On exit, the m-by-n matrix Q.
LDA (input) INTEGER
The first dimension of the array A. LDA >= max(1,M).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGEQRF.
WORK (workspace) DOUBLE PRECISION array, dimension (N)
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument has an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
if (*m < 0) {
*info = -1;
} else if (*n < 0 || *n > *m) {
*info = -2;
} else if (*k < 0 || *k > *n) {
*info = -3;
} else if (*lda < max(1,*m)) {
*info = -5;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORG2R", &i__1);
return 0;
}
/* Quick return if possible */
if (*n <= 0) {
return 0;
}
/* Initialise columns k+1:n to columns of the unit matrix */
i__1 = *n;
for (j = *k + 1; j <= i__1; ++j) {
i__2 = *m;
for (l = 1; l <= i__2; ++l) {
a[l + j * a_dim1] = 0.;
/* L10: */
}
a[j + j * a_dim1] = 1.;
/* L20: */
}
for (i__ = *k; i__ >= 1; --i__) {
/* Apply H(i) to A(i:m,i:n) from the left */
if (i__ < *n) {
a[i__ + i__ * a_dim1] = 1.;
i__1 = *m - i__ + 1;
i__2 = *n - i__;
dlarf_("Left", &i__1, &i__2, &a[i__ + i__ * a_dim1], &c__1, &tau[
i__], &a[i__ + (i__ + 1) * a_dim1], lda, &work[1]);
}
if (i__ < *m) {
i__1 = *m - i__;
d__1 = -tau[i__];
dscal_(&i__1, &d__1, &a[i__ + 1 + i__ * a_dim1], &c__1);
}
a[i__ + i__ * a_dim1] = 1. - tau[i__];
/* Set A(1:i-1,i) to zero */
i__1 = i__ - 1;
for (l = 1; l <= i__1; ++l) {
a[l + i__ * a_dim1] = 0.;
/* L30: */
}
/* L40: */
}
return 0;
/* End of DORG2R */
} /* dorg2r_ */
/* Subroutine */ int dorgbr_(char *vect, integer *m, integer *n, integer *k,
doublereal *a, integer *lda, doublereal *tau, doublereal *work,
integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__, j, nb, mn;
extern logical lsame_(char *, char *);
static integer iinfo;
static logical wantq;
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int dorglq_(integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
integer *), dorgqr_(integer *, integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *, integer *);
static integer lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORGBR generates one of the real orthogonal matrices Q or P**T
determined by DGEBRD when reducing a real matrix A to bidiagonal
form: A = Q * B * P**T. Q and P**T are defined as products of
elementary reflectors H(i) or G(i) respectively.
If VECT = 'Q', A is assumed to have been an M-by-K matrix, and Q
is of order M:
if m >= k, Q = H(1) H(2) . . . H(k) and DORGBR returns the first n
columns of Q, where m >= n >= k;
if m < k, Q = H(1) H(2) . . . H(m-1) and DORGBR returns Q as an
M-by-M matrix.
If VECT = 'P', A is assumed to have been a K-by-N matrix, and P**T
is of order N:
if k < n, P**T = G(k) . . . G(2) G(1) and DORGBR returns the first m
rows of P**T, where n >= m >= k;
if k >= n, P**T = G(n-1) . . . G(2) G(1) and DORGBR returns P**T as
an N-by-N matrix.
Arguments
=========
VECT (input) CHARACTER*1
Specifies whether the matrix Q or the matrix P**T is
required, as defined in the transformation applied by DGEBRD:
= 'Q': generate Q;
= 'P': generate P**T.
M (input) INTEGER
The number of rows of the matrix Q or P**T to be returned.
M >= 0.
N (input) INTEGER
The number of columns of the matrix Q or P**T to be returned.
N >= 0.
If VECT = 'Q', M >= N >= min(M,K);
if VECT = 'P', N >= M >= min(N,K).
K (input) INTEGER
If VECT = 'Q', the number of columns in the original M-by-K
matrix reduced by DGEBRD.
If VECT = 'P', the number of rows in the original K-by-N
matrix reduced by DGEBRD.
K >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the vectors which define the elementary reflectors,
as returned by DGEBRD.
On exit, the M-by-N matrix Q or P**T.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,M).
TAU (input) DOUBLE PRECISION array, dimension
(min(M,K)) if VECT = 'Q'
(min(N,K)) if VECT = 'P'
TAU(i) must contain the scalar factor of the elementary
reflector H(i) or G(i), which determines Q or P**T, as
returned by DGEBRD in its array argument TAUQ or TAUP.
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= max(1,min(M,N)).
For optimum performance LWORK >= min(M,N)*NB, where NB
is the optimal blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
wantq = lsame_(vect, "Q");
mn = min(*m,*n);
lquery = *lwork == -1;
if (! wantq && ! lsame_(vect, "P")) {
*info = -1;
} else if (*m < 0) {
*info = -2;
} else if (*n < 0 || wantq && (*n > *m || *n < min(*m,*k)) || ! wantq && (
*m > *n || *m < min(*n,*k))) {
*info = -3;
} else if (*k < 0) {
*info = -4;
} else if (*lda < max(1,*m)) {
*info = -6;
} else if (*lwork < max(1,mn) && ! lquery) {
*info = -9;
}
if (*info == 0) {
if (wantq) {
nb = ilaenv_(&c__1, "DORGQR", " ", m, n, k, &c_n1, (ftnlen)6, (
ftnlen)1);
} else {
nb = ilaenv_(&c__1, "DORGLQ", " ", m, n, k, &c_n1, (ftnlen)6, (
ftnlen)1);
}
lwkopt = max(1,mn) * nb;
work[1] = (doublereal) lwkopt;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORGBR", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0) {
work[1] = 1.;
return 0;
}
if (wantq) {
/*
Form Q, determined by a call to DGEBRD to reduce an m-by-k
matrix
*/
if (*m >= *k) {
/* If m >= k, assume m >= n >= k */
dorgqr_(m, n, k, &a[a_offset], lda, &tau[1], &work[1], lwork, &
iinfo);
} else {
/*
If m < k, assume m = n
Shift the vectors which define the elementary reflectors one
column to the right, and set the first row and column of Q
to those of the unit matrix
*/
for (j = *m; j >= 2; --j) {
a[j * a_dim1 + 1] = 0.;
i__1 = *m;
for (i__ = j + 1; i__ <= i__1; ++i__) {
a[i__ + j * a_dim1] = a[i__ + (j - 1) * a_dim1];
/* L10: */
}
/* L20: */
}
a[a_dim1 + 1] = 1.;
i__1 = *m;
for (i__ = 2; i__ <= i__1; ++i__) {
a[i__ + a_dim1] = 0.;
/* L30: */
}
if (*m > 1) {
/* Form Q(2:m,2:m) */
i__1 = *m - 1;
i__2 = *m - 1;
i__3 = *m - 1;
dorgqr_(&i__1, &i__2, &i__3, &a[(a_dim1 << 1) + 2], lda, &tau[
1], &work[1], lwork, &iinfo);
}
}
} else {
/*
Form P', determined by a call to DGEBRD to reduce a k-by-n
matrix
*/
if (*k < *n) {
/* If k < n, assume k <= m <= n */
dorglq_(m, n, k, &a[a_offset], lda, &tau[1], &work[1], lwork, &
iinfo);
} else {
/*
If k >= n, assume m = n
Shift the vectors which define the elementary reflectors one
row downward, and set the first row and column of P' to
those of the unit matrix
*/
a[a_dim1 + 1] = 1.;
i__1 = *n;
for (i__ = 2; i__ <= i__1; ++i__) {
a[i__ + a_dim1] = 0.;
/* L40: */
}
i__1 = *n;
for (j = 2; j <= i__1; ++j) {
for (i__ = j - 1; i__ >= 2; --i__) {
a[i__ + j * a_dim1] = a[i__ - 1 + j * a_dim1];
/* L50: */
}
a[j * a_dim1 + 1] = 0.;
/* L60: */
}
if (*n > 1) {
/* Form P'(2:n,2:n) */
i__1 = *n - 1;
i__2 = *n - 1;
i__3 = *n - 1;
dorglq_(&i__1, &i__2, &i__3, &a[(a_dim1 << 1) + 2], lda, &tau[
1], &work[1], lwork, &iinfo);
}
}
}
work[1] = (doublereal) lwkopt;
return 0;
/* End of DORGBR */
} /* dorgbr_ */
/* Subroutine */ int dorghr_(integer *n, integer *ilo, integer *ihi,
doublereal *a, integer *lda, doublereal *tau, doublereal *work,
integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2;
/* Local variables */
static integer i__, j, nb, nh, iinfo;
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int dorgqr_(integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
integer *);
static integer lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORGHR generates a real orthogonal matrix Q which is defined as the
product of IHI-ILO elementary reflectors of order N, as returned by
DGEHRD:
Q = H(ilo) H(ilo+1) . . . H(ihi-1).
Arguments
=========
N (input) INTEGER
The order of the matrix Q. N >= 0.
ILO (input) INTEGER
IHI (input) INTEGER
ILO and IHI must have the same values as in the previous call
of DGEHRD. Q is equal to the unit matrix except in the
submatrix Q(ilo+1:ihi,ilo+1:ihi).
1 <= ILO <= IHI <= N, if N > 0; ILO=1 and IHI=0, if N=0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the vectors which define the elementary reflectors,
as returned by DGEHRD.
On exit, the N-by-N orthogonal matrix Q.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
TAU (input) DOUBLE PRECISION array, dimension (N-1)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGEHRD.
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= IHI-ILO.
For optimum performance LWORK >= (IHI-ILO)*NB, where NB is
the optimal blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
nh = *ihi - *ilo;
lquery = *lwork == -1;
if (*n < 0) {
*info = -1;
} else if (*ilo < 1 || *ilo > max(1,*n)) {
*info = -2;
} else if (*ihi < min(*ilo,*n) || *ihi > *n) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
} else if (*lwork < max(1,nh) && ! lquery) {
*info = -8;
}
if (*info == 0) {
nb = ilaenv_(&c__1, "DORGQR", " ", &nh, &nh, &nh, &c_n1, (ftnlen)6, (
ftnlen)1);
lwkopt = max(1,nh) * nb;
work[1] = (doublereal) lwkopt;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORGHR", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n == 0) {
work[1] = 1.;
return 0;
}
/*
Shift the vectors which define the elementary reflectors one
column to the right, and set the first ilo and the last n-ihi
rows and columns to those of the unit matrix
*/
i__1 = *ilo + 1;
for (j = *ihi; j >= i__1; --j) {
i__2 = j - 1;
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = 0.;
/* L10: */
}
i__2 = *ihi;
for (i__ = j + 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = a[i__ + (j - 1) * a_dim1];
/* L20: */
}
i__2 = *n;
for (i__ = *ihi + 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = 0.;
/* L30: */
}
/* L40: */
}
i__1 = *ilo;
for (j = 1; j <= i__1; ++j) {
i__2 = *n;
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = 0.;
/* L50: */
}
a[j + j * a_dim1] = 1.;
/* L60: */
}
i__1 = *n;
for (j = *ihi + 1; j <= i__1; ++j) {
i__2 = *n;
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = 0.;
/* L70: */
}
a[j + j * a_dim1] = 1.;
/* L80: */
}
if (nh > 0) {
/* Generate Q(ilo+1:ihi,ilo+1:ihi) */
dorgqr_(&nh, &nh, &nh, &a[*ilo + 1 + (*ilo + 1) * a_dim1], lda, &tau[*
ilo], &work[1], lwork, &iinfo);
}
work[1] = (doublereal) lwkopt;
return 0;
/* End of DORGHR */
} /* dorghr_ */
/* Subroutine */ int dorgl2_(integer *m, integer *n, integer *k, doublereal *
a, integer *lda, doublereal *tau, doublereal *work, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2;
doublereal d__1;
/* Local variables */
static integer i__, j, l;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *), dlarf_(char *, integer *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *, doublereal *), xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORGL2 generates an m by n real matrix Q with orthonormal rows,
which is defined as the first m rows of a product of k elementary
reflectors of order n
Q = H(k) . . . H(2) H(1)
as returned by DGELQF.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix Q. M >= 0.
N (input) INTEGER
The number of columns of the matrix Q. N >= M.
K (input) INTEGER
The number of elementary reflectors whose product defines the
matrix Q. M >= K >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the i-th row must contain the vector which defines
the elementary reflector H(i), for i = 1,2,...,k, as returned
by DGELQF in the first k rows of its array argument A.
On exit, the m-by-n matrix Q.
LDA (input) INTEGER
The first dimension of the array A. LDA >= max(1,M).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGELQF.
WORK (workspace) DOUBLE PRECISION array, dimension (M)
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument has an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
if (*m < 0) {
*info = -1;
} else if (*n < *m) {
*info = -2;
} else if (*k < 0 || *k > *m) {
*info = -3;
} else if (*lda < max(1,*m)) {
*info = -5;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORGL2", &i__1);
return 0;
}
/* Quick return if possible */
if (*m <= 0) {
return 0;
}
if (*k < *m) {
/* Initialise rows k+1:m to rows of the unit matrix */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (l = *k + 1; l <= i__2; ++l) {
a[l + j * a_dim1] = 0.;
/* L10: */
}
if (j > *k && j <= *m) {
a[j + j * a_dim1] = 1.;
}
/* L20: */
}
}
for (i__ = *k; i__ >= 1; --i__) {
/* Apply H(i) to A(i:m,i:n) from the right */
if (i__ < *n) {
if (i__ < *m) {
a[i__ + i__ * a_dim1] = 1.;
i__1 = *m - i__;
i__2 = *n - i__ + 1;
dlarf_("Right", &i__1, &i__2, &a[i__ + i__ * a_dim1], lda, &
tau[i__], &a[i__ + 1 + i__ * a_dim1], lda, &work[1]);
}
i__1 = *n - i__;
d__1 = -tau[i__];
dscal_(&i__1, &d__1, &a[i__ + (i__ + 1) * a_dim1], lda);
}
a[i__ + i__ * a_dim1] = 1. - tau[i__];
/* Set A(i,1:i-1) to zero */
i__1 = i__ - 1;
for (l = 1; l <= i__1; ++l) {
a[i__ + l * a_dim1] = 0.;
/* L30: */
}
/* L40: */
}
return 0;
/* End of DORGL2 */
} /* dorgl2_ */
/* Subroutine */ int dorglq_(integer *m, integer *n, integer *k, doublereal *
a, integer *lda, doublereal *tau, doublereal *work, integer *lwork,
integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__, j, l, ib, nb, ki, kk, nx, iws, nbmin, iinfo;
extern /* Subroutine */ int dorgl2_(integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *),
dlarfb_(char *, char *, char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, integer *), dlarft_(char *, char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static integer ldwork, lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORGLQ generates an M-by-N real matrix Q with orthonormal rows,
which is defined as the first M rows of a product of K elementary
reflectors of order N
Q = H(k) . . . H(2) H(1)
as returned by DGELQF.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix Q. M >= 0.
N (input) INTEGER
The number of columns of the matrix Q. N >= M.
K (input) INTEGER
The number of elementary reflectors whose product defines the
matrix Q. M >= K >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the i-th row must contain the vector which defines
the elementary reflector H(i), for i = 1,2,...,k, as returned
by DGELQF in the first k rows of its array argument A.
On exit, the M-by-N matrix Q.
LDA (input) INTEGER
The first dimension of the array A. LDA >= max(1,M).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGELQF.
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= max(1,M).
For optimum performance LWORK >= M*NB, where NB is
the optimal blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument has an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
nb = ilaenv_(&c__1, "DORGLQ", " ", m, n, k, &c_n1, (ftnlen)6, (ftnlen)1);
lwkopt = max(1,*m) * nb;
work[1] = (doublereal) lwkopt;
lquery = *lwork == -1;
if (*m < 0) {
*info = -1;
} else if (*n < *m) {
*info = -2;
} else if (*k < 0 || *k > *m) {
*info = -3;
} else if (*lda < max(1,*m)) {
*info = -5;
} else if (*lwork < max(1,*m) && ! lquery) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORGLQ", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m <= 0) {
work[1] = 1.;
return 0;
}
nbmin = 2;
nx = 0;
iws = *m;
if (nb > 1 && nb < *k) {
/*
Determine when to cross over from blocked to unblocked code.
Computing MAX
*/
i__1 = 0, i__2 = ilaenv_(&c__3, "DORGLQ", " ", m, n, k, &c_n1, (
ftnlen)6, (ftnlen)1);
nx = max(i__1,i__2);
if (nx < *k) {
/* Determine if workspace is large enough for blocked code. */
ldwork = *m;
iws = ldwork * nb;
if (*lwork < iws) {
/*
Not enough workspace to use optimal NB: reduce NB and
determine the minimum value of NB.
*/
nb = *lwork / ldwork;
/* Computing MAX */
i__1 = 2, i__2 = ilaenv_(&c__2, "DORGLQ", " ", m, n, k, &c_n1,
(ftnlen)6, (ftnlen)1);
nbmin = max(i__1,i__2);
}
}
}
if (nb >= nbmin && nb < *k && nx < *k) {
/*
Use blocked code after the last block.
The first kk rows are handled by the block method.
*/
ki = (*k - nx - 1) / nb * nb;
/* Computing MIN */
i__1 = *k, i__2 = ki + nb;
kk = min(i__1,i__2);
/* Set A(kk+1:m,1:kk) to zero. */
i__1 = kk;
for (j = 1; j <= i__1; ++j) {
i__2 = *m;
for (i__ = kk + 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = 0.;
/* L10: */
}
/* L20: */
}
} else {
kk = 0;
}
/* Use unblocked code for the last or only block. */
if (kk < *m) {
i__1 = *m - kk;
i__2 = *n - kk;
i__3 = *k - kk;
dorgl2_(&i__1, &i__2, &i__3, &a[kk + 1 + (kk + 1) * a_dim1], lda, &
tau[kk + 1], &work[1], &iinfo);
}
if (kk > 0) {
/* Use blocked code */
i__1 = -nb;
for (i__ = ki + 1; i__1 < 0 ? i__ >= 1 : i__ <= 1; i__ += i__1) {
/* Computing MIN */
i__2 = nb, i__3 = *k - i__ + 1;
ib = min(i__2,i__3);
if (i__ + ib <= *m) {
/*
Form the triangular factor of the block reflector
H = H(i) H(i+1) . . . H(i+ib-1)
*/
i__2 = *n - i__ + 1;
dlarft_("Forward", "Rowwise", &i__2, &ib, &a[i__ + i__ *
a_dim1], lda, &tau[i__], &work[1], &ldwork);
/* Apply H' to A(i+ib:m,i:n) from the right */
i__2 = *m - i__ - ib + 1;
i__3 = *n - i__ + 1;
dlarfb_("Right", "Transpose", "Forward", "Rowwise", &i__2, &
i__3, &ib, &a[i__ + i__ * a_dim1], lda, &work[1], &
ldwork, &a[i__ + ib + i__ * a_dim1], lda, &work[ib +
1], &ldwork);
}
/* Apply H' to columns i:n of current block */
i__2 = *n - i__ + 1;
dorgl2_(&ib, &i__2, &ib, &a[i__ + i__ * a_dim1], lda, &tau[i__], &
work[1], &iinfo);
/* Set columns 1:i-1 of current block to zero */
i__2 = i__ - 1;
for (j = 1; j <= i__2; ++j) {
i__3 = i__ + ib - 1;
for (l = i__; l <= i__3; ++l) {
a[l + j * a_dim1] = 0.;
/* L30: */
}
/* L40: */
}
/* L50: */
}
}
work[1] = (doublereal) iws;
return 0;
/* End of DORGLQ */
} /* dorglq_ */
/* Subroutine */ int dorgqr_(integer *m, integer *n, integer *k, doublereal *
a, integer *lda, doublereal *tau, doublereal *work, integer *lwork,
integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__, j, l, ib, nb, ki, kk, nx, iws, nbmin, iinfo;
extern /* Subroutine */ int dorg2r_(integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *),
dlarfb_(char *, char *, char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, integer *,
doublereal *, integer *, doublereal *, integer *), dlarft_(char *, char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static integer ldwork, lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORGQR generates an M-by-N real matrix Q with orthonormal columns,
which is defined as the first N columns of a product of K elementary
reflectors of order M
Q = H(1) H(2) . . . H(k)
as returned by DGEQRF.
Arguments
=========
M (input) INTEGER
The number of rows of the matrix Q. M >= 0.
N (input) INTEGER
The number of columns of the matrix Q. M >= N >= 0.
K (input) INTEGER
The number of elementary reflectors whose product defines the
matrix Q. N >= K >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the i-th column must contain the vector which
defines the elementary reflector H(i), for i = 1,2,...,k, as
returned by DGEQRF in the first k columns of its array
argument A.
On exit, the M-by-N matrix Q.
LDA (input) INTEGER
The first dimension of the array A. LDA >= max(1,M).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGEQRF.
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= max(1,N).
For optimum performance LWORK >= N*NB, where NB is the
optimal blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument has an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
--work;
/* Function Body */
*info = 0;
nb = ilaenv_(&c__1, "DORGQR", " ", m, n, k, &c_n1, (ftnlen)6, (ftnlen)1);
lwkopt = max(1,*n) * nb;
work[1] = (doublereal) lwkopt;
lquery = *lwork == -1;
if (*m < 0) {
*info = -1;
} else if (*n < 0 || *n > *m) {
*info = -2;
} else if (*k < 0 || *k > *n) {
*info = -3;
} else if (*lda < max(1,*m)) {
*info = -5;
} else if (*lwork < max(1,*n) && ! lquery) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORGQR", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n <= 0) {
work[1] = 1.;
return 0;
}
nbmin = 2;
nx = 0;
iws = *n;
if (nb > 1 && nb < *k) {
/*
Determine when to cross over from blocked to unblocked code.
Computing MAX
*/
i__1 = 0, i__2 = ilaenv_(&c__3, "DORGQR", " ", m, n, k, &c_n1, (
ftnlen)6, (ftnlen)1);
nx = max(i__1,i__2);
if (nx < *k) {
/* Determine if workspace is large enough for blocked code. */
ldwork = *n;
iws = ldwork * nb;
if (*lwork < iws) {
/*
Not enough workspace to use optimal NB: reduce NB and
determine the minimum value of NB.
*/
nb = *lwork / ldwork;
/* Computing MAX */
i__1 = 2, i__2 = ilaenv_(&c__2, "DORGQR", " ", m, n, k, &c_n1,
(ftnlen)6, (ftnlen)1);
nbmin = max(i__1,i__2);
}
}
}
if (nb >= nbmin && nb < *k && nx < *k) {
/*
Use blocked code after the last block.
The first kk columns are handled by the block method.
*/
ki = (*k - nx - 1) / nb * nb;
/* Computing MIN */
i__1 = *k, i__2 = ki + nb;
kk = min(i__1,i__2);
/* Set A(1:kk,kk+1:n) to zero. */
i__1 = *n;
for (j = kk + 1; j <= i__1; ++j) {
i__2 = kk;
for (i__ = 1; i__ <= i__2; ++i__) {
a[i__ + j * a_dim1] = 0.;
/* L10: */
}
/* L20: */
}
} else {
kk = 0;
}
/* Use unblocked code for the last or only block. */
if (kk < *n) {
i__1 = *m - kk;
i__2 = *n - kk;
i__3 = *k - kk;
dorg2r_(&i__1, &i__2, &i__3, &a[kk + 1 + (kk + 1) * a_dim1], lda, &
tau[kk + 1], &work[1], &iinfo);
}
if (kk > 0) {
/* Use blocked code */
i__1 = -nb;
for (i__ = ki + 1; i__1 < 0 ? i__ >= 1 : i__ <= 1; i__ += i__1) {
/* Computing MIN */
i__2 = nb, i__3 = *k - i__ + 1;
ib = min(i__2,i__3);
if (i__ + ib <= *n) {
/*
Form the triangular factor of the block reflector
H = H(i) H(i+1) . . . H(i+ib-1)
*/
i__2 = *m - i__ + 1;
dlarft_("Forward", "Columnwise", &i__2, &ib, &a[i__ + i__ *
a_dim1], lda, &tau[i__], &work[1], &ldwork);
/* Apply H to A(i:m,i+ib:n) from the left */
i__2 = *m - i__ + 1;
i__3 = *n - i__ - ib + 1;
dlarfb_("Left", "No transpose", "Forward", "Columnwise", &
i__2, &i__3, &ib, &a[i__ + i__ * a_dim1], lda, &work[
1], &ldwork, &a[i__ + (i__ + ib) * a_dim1], lda, &
work[ib + 1], &ldwork);
}
/* Apply H to rows i:m of current block */
i__2 = *m - i__ + 1;
dorg2r_(&i__2, &ib, &ib, &a[i__ + i__ * a_dim1], lda, &tau[i__], &
work[1], &iinfo);
/* Set rows 1:i-1 of current block to zero */
i__2 = i__ + ib - 1;
for (j = i__; j <= i__2; ++j) {
i__3 = i__ - 1;
for (l = 1; l <= i__3; ++l) {
a[l + j * a_dim1] = 0.;
/* L30: */
}
/* L40: */
}
/* L50: */
}
}
work[1] = (doublereal) iws;
return 0;
/* End of DORGQR */
} /* dorgqr_ */
/* Subroutine */ int dorm2l_(char *side, char *trans, integer *m, integer *n,
integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal *
c__, integer *ldc, doublereal *work, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2;
/* Local variables */
static integer i__, i1, i2, i3, mi, ni, nq;
static doublereal aii;
static logical left;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int xerbla_(char *, integer *);
static logical notran;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORM2L overwrites the general real m by n matrix C with
Q * C if SIDE = 'L' and TRANS = 'N', or
Q'* C if SIDE = 'L' and TRANS = 'T', or
C * Q if SIDE = 'R' and TRANS = 'N', or
C * Q' if SIDE = 'R' and TRANS = 'T',
where Q is a real orthogonal matrix defined as the product of k
elementary reflectors
Q = H(k) . . . H(2) H(1)
as returned by DGEQLF. Q is of order m if SIDE = 'L' and of order n
if SIDE = 'R'.
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': apply Q or Q' from the Left
= 'R': apply Q or Q' from the Right
TRANS (input) CHARACTER*1
= 'N': apply Q (No transpose)
= 'T': apply Q' (Transpose)
M (input) INTEGER
The number of rows of the matrix C. M >= 0.
N (input) INTEGER
The number of columns of the matrix C. N >= 0.
K (input) INTEGER
The number of elementary reflectors whose product defines
the matrix Q.
If SIDE = 'L', M >= K >= 0;
if SIDE = 'R', N >= K >= 0.
A (input) DOUBLE PRECISION array, dimension (LDA,K)
The i-th column must contain the vector which defines the
elementary reflector H(i), for i = 1,2,...,k, as returned by
DGEQLF in the last k columns of its array argument A.
A is modified by the routine but restored on exit.
LDA (input) INTEGER
The leading dimension of the array A.
If SIDE = 'L', LDA >= max(1,M);
if SIDE = 'R', LDA >= max(1,N).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGEQLF.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the m by n matrix C.
On exit, C is overwritten by Q*C or Q'*C or C*Q' or C*Q.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace) DOUBLE PRECISION array, dimension
(N) if SIDE = 'L',
(M) if SIDE = 'R'
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
*info = 0;
left = lsame_(side, "L");
notran = lsame_(trans, "N");
/* NQ is the order of Q */
if (left) {
nq = *m;
} else {
nq = *n;
}
if (! left && ! lsame_(side, "R")) {
*info = -1;
} else if (! notran && ! lsame_(trans, "T")) {
*info = -2;
} else if (*m < 0) {
*info = -3;
} else if (*n < 0) {
*info = -4;
} else if (*k < 0 || *k > nq) {
*info = -5;
} else if (*lda < max(1,nq)) {
*info = -7;
} else if (*ldc < max(1,*m)) {
*info = -10;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORM2L", &i__1);
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0 || *k == 0) {
return 0;
}
if (left && notran || ! left && ! notran) {
i1 = 1;
i2 = *k;
i3 = 1;
} else {
i1 = *k;
i2 = 1;
i3 = -1;
}
if (left) {
ni = *n;
} else {
mi = *m;
}
i__1 = i2;
i__2 = i3;
for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
if (left) {
/* H(i) is applied to C(1:m-k+i,1:n) */
mi = *m - *k + i__;
} else {
/* H(i) is applied to C(1:m,1:n-k+i) */
ni = *n - *k + i__;
}
/* Apply H(i) */
aii = a[nq - *k + i__ + i__ * a_dim1];
a[nq - *k + i__ + i__ * a_dim1] = 1.;
dlarf_(side, &mi, &ni, &a[i__ * a_dim1 + 1], &c__1, &tau[i__], &c__[
c_offset], ldc, &work[1]);
a[nq - *k + i__ + i__ * a_dim1] = aii;
/* L10: */
}
return 0;
/* End of DORM2L */
} /* dorm2l_ */
/* Subroutine */ int dorm2r_(char *side, char *trans, integer *m, integer *n,
integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal *
c__, integer *ldc, doublereal *work, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2;
/* Local variables */
static integer i__, i1, i2, i3, ic, jc, mi, ni, nq;
static doublereal aii;
static logical left;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int xerbla_(char *, integer *);
static logical notran;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORM2R overwrites the general real m by n matrix C with
Q * C if SIDE = 'L' and TRANS = 'N', or
Q'* C if SIDE = 'L' and TRANS = 'T', or
C * Q if SIDE = 'R' and TRANS = 'N', or
C * Q' if SIDE = 'R' and TRANS = 'T',
where Q is a real orthogonal matrix defined as the product of k
elementary reflectors
Q = H(1) H(2) . . . H(k)
as returned by DGEQRF. Q is of order m if SIDE = 'L' and of order n
if SIDE = 'R'.
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': apply Q or Q' from the Left
= 'R': apply Q or Q' from the Right
TRANS (input) CHARACTER*1
= 'N': apply Q (No transpose)
= 'T': apply Q' (Transpose)
M (input) INTEGER
The number of rows of the matrix C. M >= 0.
N (input) INTEGER
The number of columns of the matrix C. N >= 0.
K (input) INTEGER
The number of elementary reflectors whose product defines
the matrix Q.
If SIDE = 'L', M >= K >= 0;
if SIDE = 'R', N >= K >= 0.
A (input) DOUBLE PRECISION array, dimension (LDA,K)
The i-th column must contain the vector which defines the
elementary reflector H(i), for i = 1,2,...,k, as returned by
DGEQRF in the first k columns of its array argument A.
A is modified by the routine but restored on exit.
LDA (input) INTEGER
The leading dimension of the array A.
If SIDE = 'L', LDA >= max(1,M);
if SIDE = 'R', LDA >= max(1,N).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGEQRF.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the m by n matrix C.
On exit, C is overwritten by Q*C or Q'*C or C*Q' or C*Q.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace) DOUBLE PRECISION array, dimension
(N) if SIDE = 'L',
(M) if SIDE = 'R'
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
*info = 0;
left = lsame_(side, "L");
notran = lsame_(trans, "N");
/* NQ is the order of Q */
if (left) {
nq = *m;
} else {
nq = *n;
}
if (! left && ! lsame_(side, "R")) {
*info = -1;
} else if (! notran && ! lsame_(trans, "T")) {
*info = -2;
} else if (*m < 0) {
*info = -3;
} else if (*n < 0) {
*info = -4;
} else if (*k < 0 || *k > nq) {
*info = -5;
} else if (*lda < max(1,nq)) {
*info = -7;
} else if (*ldc < max(1,*m)) {
*info = -10;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORM2R", &i__1);
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0 || *k == 0) {
return 0;
}
if (left && ! notran || ! left && notran) {
i1 = 1;
i2 = *k;
i3 = 1;
} else {
i1 = *k;
i2 = 1;
i3 = -1;
}
if (left) {
ni = *n;
jc = 1;
} else {
mi = *m;
ic = 1;
}
i__1 = i2;
i__2 = i3;
for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
if (left) {
/* H(i) is applied to C(i:m,1:n) */
mi = *m - i__ + 1;
ic = i__;
} else {
/* H(i) is applied to C(1:m,i:n) */
ni = *n - i__ + 1;
jc = i__;
}
/* Apply H(i) */
aii = a[i__ + i__ * a_dim1];
a[i__ + i__ * a_dim1] = 1.;
dlarf_(side, &mi, &ni, &a[i__ + i__ * a_dim1], &c__1, &tau[i__], &c__[
ic + jc * c_dim1], ldc, &work[1]);
a[i__ + i__ * a_dim1] = aii;
/* L10: */
}
return 0;
/* End of DORM2R */
} /* dorm2r_ */
/* Subroutine */ int dormbr_(char *vect, char *side, char *trans, integer *m,
integer *n, integer *k, doublereal *a, integer *lda, doublereal *tau,
doublereal *c__, integer *ldc, doublereal *work, integer *lwork,
integer *info)
{
/* System generated locals */
address a__1[2];
integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2, i__3[2];
char ch__1[2];
/* Local variables */
static integer i1, i2, nb, mi, ni, nq, nw;
static logical left;
extern logical lsame_(char *, char *);
static integer iinfo;
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int dormlq_(char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *, integer *);
static logical notran;
extern /* Subroutine */ int dormqr_(char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *, integer *);
static logical applyq;
static char transt[1];
static integer lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
If VECT = 'Q', DORMBR overwrites the general real M-by-N matrix C
with
SIDE = 'L' SIDE = 'R'
TRANS = 'N': Q * C C * Q
TRANS = 'T': Q**T * C C * Q**T
If VECT = 'P', DORMBR overwrites the general real M-by-N matrix C
with
SIDE = 'L' SIDE = 'R'
TRANS = 'N': P * C C * P
TRANS = 'T': P**T * C C * P**T
Here Q and P**T are the orthogonal matrices determined by DGEBRD when
reducing a real matrix A to bidiagonal form: A = Q * B * P**T. Q and
P**T are defined as products of elementary reflectors H(i) and G(i)
respectively.
Let nq = m if SIDE = 'L' and nq = n if SIDE = 'R'. Thus nq is the
order of the orthogonal matrix Q or P**T that is applied.
If VECT = 'Q', A is assumed to have been an NQ-by-K matrix:
if nq >= k, Q = H(1) H(2) . . . H(k);
if nq < k, Q = H(1) H(2) . . . H(nq-1).
If VECT = 'P', A is assumed to have been a K-by-NQ matrix:
if k < nq, P = G(1) G(2) . . . G(k);
if k >= nq, P = G(1) G(2) . . . G(nq-1).
Arguments
=========
VECT (input) CHARACTER*1
= 'Q': apply Q or Q**T;
= 'P': apply P or P**T.
SIDE (input) CHARACTER*1
= 'L': apply Q, Q**T, P or P**T from the Left;
= 'R': apply Q, Q**T, P or P**T from the Right.
TRANS (input) CHARACTER*1
= 'N': No transpose, apply Q or P;
= 'T': Transpose, apply Q**T or P**T.
M (input) INTEGER
The number of rows of the matrix C. M >= 0.
N (input) INTEGER
The number of columns of the matrix C. N >= 0.
K (input) INTEGER
If VECT = 'Q', the number of columns in the original
matrix reduced by DGEBRD.
If VECT = 'P', the number of rows in the original
matrix reduced by DGEBRD.
K >= 0.
A (input) DOUBLE PRECISION array, dimension
(LDA,min(nq,K)) if VECT = 'Q'
(LDA,nq) if VECT = 'P'
The vectors which define the elementary reflectors H(i) and
G(i), whose products determine the matrices Q and P, as
returned by DGEBRD.
LDA (input) INTEGER
The leading dimension of the array A.
If VECT = 'Q', LDA >= max(1,nq);
if VECT = 'P', LDA >= max(1,min(nq,K)).
TAU (input) DOUBLE PRECISION array, dimension (min(nq,K))
TAU(i) must contain the scalar factor of the elementary
reflector H(i) or G(i) which determines Q or P, as returned
by DGEBRD in the array argument TAUQ or TAUP.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the M-by-N matrix C.
On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q
or P*C or P**T*C or C*P or C*P**T.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If SIDE = 'L', LWORK >= max(1,N);
if SIDE = 'R', LWORK >= max(1,M).
For optimum performance LWORK >= N*NB if SIDE = 'L', and
LWORK >= M*NB if SIDE = 'R', where NB is the optimal
blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
*info = 0;
applyq = lsame_(vect, "Q");
left = lsame_(side, "L");
notran = lsame_(trans, "N");
lquery = *lwork == -1;
/* NQ is the order of Q or P and NW is the minimum dimension of WORK */
if (left) {
nq = *m;
nw = *n;
} else {
nq = *n;
nw = *m;
}
if (! applyq && ! lsame_(vect, "P")) {
*info = -1;
} else if (! left && ! lsame_(side, "R")) {
*info = -2;
} else if (! notran && ! lsame_(trans, "T")) {
*info = -3;
} else if (*m < 0) {
*info = -4;
} else if (*n < 0) {
*info = -5;
} else if (*k < 0) {
*info = -6;
} else /* if(complicated condition) */ {
/* Computing MAX */
i__1 = 1, i__2 = min(nq,*k);
if (applyq && *lda < max(1,nq) || ! applyq && *lda < max(i__1,i__2)) {
*info = -8;
} else if (*ldc < max(1,*m)) {
*info = -11;
} else if (*lwork < max(1,nw) && ! lquery) {
*info = -13;
}
}
if (*info == 0) {
if (applyq) {
if (left) {
/* Writing concatenation */
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = *m - 1;
i__2 = *m - 1;
nb = ilaenv_(&c__1, "DORMQR", ch__1, &i__1, n, &i__2, &c_n1, (
ftnlen)6, (ftnlen)2);
} else {
/* Writing concatenation */
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = *n - 1;
i__2 = *n - 1;
nb = ilaenv_(&c__1, "DORMQR", ch__1, m, &i__1, &i__2, &c_n1, (
ftnlen)6, (ftnlen)2);
}
} else {
if (left) {
/* Writing concatenation */
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = *m - 1;
i__2 = *m - 1;
nb = ilaenv_(&c__1, "DORMLQ", ch__1, &i__1, n, &i__2, &c_n1, (
ftnlen)6, (ftnlen)2);
} else {
/* Writing concatenation */
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = *n - 1;
i__2 = *n - 1;
nb = ilaenv_(&c__1, "DORMLQ", ch__1, m, &i__1, &i__2, &c_n1, (
ftnlen)6, (ftnlen)2);
}
}
lwkopt = max(1,nw) * nb;
work[1] = (doublereal) lwkopt;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORMBR", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
work[1] = 1.;
if (*m == 0 || *n == 0) {
return 0;
}
if (applyq) {
/* Apply Q */
if (nq >= *k) {
/* Q was determined by a call to DGEBRD with nq >= k */
dormqr_(side, trans, m, n, k, &a[a_offset], lda, &tau[1], &c__[
c_offset], ldc, &work[1], lwork, &iinfo);
} else if (nq > 1) {
/* Q was determined by a call to DGEBRD with nq < k */
if (left) {
mi = *m - 1;
ni = *n;
i1 = 2;
i2 = 1;
} else {
mi = *m;
ni = *n - 1;
i1 = 1;
i2 = 2;
}
i__1 = nq - 1;
dormqr_(side, trans, &mi, &ni, &i__1, &a[a_dim1 + 2], lda, &tau[1]
, &c__[i1 + i2 * c_dim1], ldc, &work[1], lwork, &iinfo);
}
} else {
/* Apply P */
if (notran) {
*(unsigned char *)transt = 'T';
} else {
*(unsigned char *)transt = 'N';
}
if (nq > *k) {
/* P was determined by a call to DGEBRD with nq > k */
dormlq_(side, transt, m, n, k, &a[a_offset], lda, &tau[1], &c__[
c_offset], ldc, &work[1], lwork, &iinfo);
} else if (nq > 1) {
/* P was determined by a call to DGEBRD with nq <= k */
if (left) {
mi = *m - 1;
ni = *n;
i1 = 2;
i2 = 1;
} else {
mi = *m;
ni = *n - 1;
i1 = 1;
i2 = 2;
}
i__1 = nq - 1;
dormlq_(side, transt, &mi, &ni, &i__1, &a[(a_dim1 << 1) + 1], lda,
&tau[1], &c__[i1 + i2 * c_dim1], ldc, &work[1], lwork, &
iinfo);
}
}
work[1] = (doublereal) lwkopt;
return 0;
/* End of DORMBR */
} /* dormbr_ */
/* Subroutine */ int dormhr_(char *side, char *trans, integer *m, integer *n,
integer *ilo, integer *ihi, doublereal *a, integer *lda, doublereal *
tau, doublereal *c__, integer *ldc, doublereal *work, integer *lwork,
integer *info)
{
/* System generated locals */
address a__1[2];
integer a_dim1, a_offset, c_dim1, c_offset, i__1[2], i__2;
char ch__1[2];
/* Local variables */
static integer i1, i2, nb, mi, nh, ni, nq, nw;
static logical left;
extern logical lsame_(char *, char *);
static integer iinfo;
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int dormqr_(char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *, integer *);
static integer lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORMHR overwrites the general real M-by-N matrix C with
SIDE = 'L' SIDE = 'R'
TRANS = 'N': Q * C C * Q
TRANS = 'T': Q**T * C C * Q**T
where Q is a real orthogonal matrix of order nq, with nq = m if
SIDE = 'L' and nq = n if SIDE = 'R'. Q is defined as the product of
IHI-ILO elementary reflectors, as returned by DGEHRD:
Q = H(ilo) H(ilo+1) . . . H(ihi-1).
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': apply Q or Q**T from the Left;
= 'R': apply Q or Q**T from the Right.
TRANS (input) CHARACTER*1
= 'N': No transpose, apply Q;
= 'T': Transpose, apply Q**T.
M (input) INTEGER
The number of rows of the matrix C. M >= 0.
N (input) INTEGER
The number of columns of the matrix C. N >= 0.
ILO (input) INTEGER
IHI (input) INTEGER
ILO and IHI must have the same values as in the previous call
of DGEHRD. Q is equal to the unit matrix except in the
submatrix Q(ilo+1:ihi,ilo+1:ihi).
If SIDE = 'L', then 1 <= ILO <= IHI <= M, if M > 0, and
ILO = 1 and IHI = 0, if M = 0;
if SIDE = 'R', then 1 <= ILO <= IHI <= N, if N > 0, and
ILO = 1 and IHI = 0, if N = 0.
A (input) DOUBLE PRECISION array, dimension
(LDA,M) if SIDE = 'L'
(LDA,N) if SIDE = 'R'
The vectors which define the elementary reflectors, as
returned by DGEHRD.
LDA (input) INTEGER
The leading dimension of the array A.
LDA >= max(1,M) if SIDE = 'L'; LDA >= max(1,N) if SIDE = 'R'.
TAU (input) DOUBLE PRECISION array, dimension
(M-1) if SIDE = 'L'
(N-1) if SIDE = 'R'
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGEHRD.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the M-by-N matrix C.
On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If SIDE = 'L', LWORK >= max(1,N);
if SIDE = 'R', LWORK >= max(1,M).
For optimum performance LWORK >= N*NB if SIDE = 'L', and
LWORK >= M*NB if SIDE = 'R', where NB is the optimal
blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
*info = 0;
nh = *ihi - *ilo;
left = lsame_(side, "L");
lquery = *lwork == -1;
/* NQ is the order of Q and NW is the minimum dimension of WORK */
if (left) {
nq = *m;
nw = *n;
} else {
nq = *n;
nw = *m;
}
if (! left && ! lsame_(side, "R")) {
*info = -1;
} else if (! lsame_(trans, "N") && ! lsame_(trans,
"T")) {
*info = -2;
} else if (*m < 0) {
*info = -3;
} else if (*n < 0) {
*info = -4;
} else if (*ilo < 1 || *ilo > max(1,nq)) {
*info = -5;
} else if (*ihi < min(*ilo,nq) || *ihi > nq) {
*info = -6;
} else if (*lda < max(1,nq)) {
*info = -8;
} else if (*ldc < max(1,*m)) {
*info = -11;
} else if (*lwork < max(1,nw) && ! lquery) {
*info = -13;
}
if (*info == 0) {
if (left) {
/* Writing concatenation */
i__1[0] = 1, a__1[0] = side;
i__1[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2);
nb = ilaenv_(&c__1, "DORMQR", ch__1, &nh, n, &nh, &c_n1, (ftnlen)
6, (ftnlen)2);
} else {
/* Writing concatenation */
i__1[0] = 1, a__1[0] = side;
i__1[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2);
nb = ilaenv_(&c__1, "DORMQR", ch__1, m, &nh, &nh, &c_n1, (ftnlen)
6, (ftnlen)2);
}
lwkopt = max(1,nw) * nb;
work[1] = (doublereal) lwkopt;
}
if (*info != 0) {
i__2 = -(*info);
xerbla_("DORMHR", &i__2);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0 || nh == 0) {
work[1] = 1.;
return 0;
}
if (left) {
mi = nh;
ni = *n;
i1 = *ilo + 1;
i2 = 1;
} else {
mi = *m;
ni = nh;
i1 = 1;
i2 = *ilo + 1;
}
dormqr_(side, trans, &mi, &ni, &nh, &a[*ilo + 1 + *ilo * a_dim1], lda, &
tau[*ilo], &c__[i1 + i2 * c_dim1], ldc, &work[1], lwork, &iinfo);
work[1] = (doublereal) lwkopt;
return 0;
/* End of DORMHR */
} /* dormhr_ */
/* Subroutine */ int dorml2_(char *side, char *trans, integer *m, integer *n,
integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal *
c__, integer *ldc, doublereal *work, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2;
/* Local variables */
static integer i__, i1, i2, i3, ic, jc, mi, ni, nq;
static doublereal aii;
static logical left;
extern /* Subroutine */ int dlarf_(char *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int xerbla_(char *, integer *);
static logical notran;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORML2 overwrites the general real m by n matrix C with
Q * C if SIDE = 'L' and TRANS = 'N', or
Q'* C if SIDE = 'L' and TRANS = 'T', or
C * Q if SIDE = 'R' and TRANS = 'N', or
C * Q' if SIDE = 'R' and TRANS = 'T',
where Q is a real orthogonal matrix defined as the product of k
elementary reflectors
Q = H(k) . . . H(2) H(1)
as returned by DGELQF. Q is of order m if SIDE = 'L' and of order n
if SIDE = 'R'.
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': apply Q or Q' from the Left
= 'R': apply Q or Q' from the Right
TRANS (input) CHARACTER*1
= 'N': apply Q (No transpose)
= 'T': apply Q' (Transpose)
M (input) INTEGER
The number of rows of the matrix C. M >= 0.
N (input) INTEGER
The number of columns of the matrix C. N >= 0.
K (input) INTEGER
The number of elementary reflectors whose product defines
the matrix Q.
If SIDE = 'L', M >= K >= 0;
if SIDE = 'R', N >= K >= 0.
A (input) DOUBLE PRECISION array, dimension
(LDA,M) if SIDE = 'L',
(LDA,N) if SIDE = 'R'
The i-th row must contain the vector which defines the
elementary reflector H(i), for i = 1,2,...,k, as returned by
DGELQF in the first k rows of its array argument A.
A is modified by the routine but restored on exit.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,K).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGELQF.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the m by n matrix C.
On exit, C is overwritten by Q*C or Q'*C or C*Q' or C*Q.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace) DOUBLE PRECISION array, dimension
(N) if SIDE = 'L',
(M) if SIDE = 'R'
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
*info = 0;
left = lsame_(side, "L");
notran = lsame_(trans, "N");
/* NQ is the order of Q */
if (left) {
nq = *m;
} else {
nq = *n;
}
if (! left && ! lsame_(side, "R")) {
*info = -1;
} else if (! notran && ! lsame_(trans, "T")) {
*info = -2;
} else if (*m < 0) {
*info = -3;
} else if (*n < 0) {
*info = -4;
} else if (*k < 0 || *k > nq) {
*info = -5;
} else if (*lda < max(1,*k)) {
*info = -7;
} else if (*ldc < max(1,*m)) {
*info = -10;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORML2", &i__1);
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0 || *k == 0) {
return 0;
}
if (left && notran || ! left && ! notran) {
i1 = 1;
i2 = *k;
i3 = 1;
} else {
i1 = *k;
i2 = 1;
i3 = -1;
}
if (left) {
ni = *n;
jc = 1;
} else {
mi = *m;
ic = 1;
}
i__1 = i2;
i__2 = i3;
for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
if (left) {
/* H(i) is applied to C(i:m,1:n) */
mi = *m - i__ + 1;
ic = i__;
} else {
/* H(i) is applied to C(1:m,i:n) */
ni = *n - i__ + 1;
jc = i__;
}
/* Apply H(i) */
aii = a[i__ + i__ * a_dim1];
a[i__ + i__ * a_dim1] = 1.;
dlarf_(side, &mi, &ni, &a[i__ + i__ * a_dim1], lda, &tau[i__], &c__[
ic + jc * c_dim1], ldc, &work[1]);
a[i__ + i__ * a_dim1] = aii;
/* L10: */
}
return 0;
/* End of DORML2 */
} /* dorml2_ */
/* Subroutine */ int dormlq_(char *side, char *trans, integer *m, integer *n,
integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal *
c__, integer *ldc, doublereal *work, integer *lwork, integer *info)
{
/* System generated locals */
address a__1[2];
integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2, i__3[2], i__4,
i__5;
char ch__1[2];
/* Local variables */
static integer i__;
static doublereal t[4160] /* was [65][64] */;
static integer i1, i2, i3, ib, ic, jc, nb, mi, ni, nq, nw, iws;
static logical left;
extern logical lsame_(char *, char *);
static integer nbmin, iinfo;
extern /* Subroutine */ int dorml2_(char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *), dlarfb_(char
*, char *, char *, char *, integer *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *, doublereal *, integer *), dlarft_(char *, char *, integer *, integer *, doublereal
*, integer *, doublereal *, doublereal *, integer *), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static logical notran;
static integer ldwork;
static char transt[1];
static integer lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORMLQ overwrites the general real M-by-N matrix C with
SIDE = 'L' SIDE = 'R'
TRANS = 'N': Q * C C * Q
TRANS = 'T': Q**T * C C * Q**T
where Q is a real orthogonal matrix defined as the product of k
elementary reflectors
Q = H(k) . . . H(2) H(1)
as returned by DGELQF. Q is of order M if SIDE = 'L' and of order N
if SIDE = 'R'.
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': apply Q or Q**T from the Left;
= 'R': apply Q or Q**T from the Right.
TRANS (input) CHARACTER*1
= 'N': No transpose, apply Q;
= 'T': Transpose, apply Q**T.
M (input) INTEGER
The number of rows of the matrix C. M >= 0.
N (input) INTEGER
The number of columns of the matrix C. N >= 0.
K (input) INTEGER
The number of elementary reflectors whose product defines
the matrix Q.
If SIDE = 'L', M >= K >= 0;
if SIDE = 'R', N >= K >= 0.
A (input) DOUBLE PRECISION array, dimension
(LDA,M) if SIDE = 'L',
(LDA,N) if SIDE = 'R'
The i-th row must contain the vector which defines the
elementary reflector H(i), for i = 1,2,...,k, as returned by
DGELQF in the first k rows of its array argument A.
A is modified by the routine but restored on exit.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,K).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGELQF.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the M-by-N matrix C.
On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If SIDE = 'L', LWORK >= max(1,N);
if SIDE = 'R', LWORK >= max(1,M).
For optimum performance LWORK >= N*NB if SIDE = 'L', and
LWORK >= M*NB if SIDE = 'R', where NB is the optimal
blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
*info = 0;
left = lsame_(side, "L");
notran = lsame_(trans, "N");
lquery = *lwork == -1;
/* NQ is the order of Q and NW is the minimum dimension of WORK */
if (left) {
nq = *m;
nw = *n;
} else {
nq = *n;
nw = *m;
}
if (! left && ! lsame_(side, "R")) {
*info = -1;
} else if (! notran && ! lsame_(trans, "T")) {
*info = -2;
} else if (*m < 0) {
*info = -3;
} else if (*n < 0) {
*info = -4;
} else if (*k < 0 || *k > nq) {
*info = -5;
} else if (*lda < max(1,*k)) {
*info = -7;
} else if (*ldc < max(1,*m)) {
*info = -10;
} else if (*lwork < max(1,nw) && ! lquery) {
*info = -12;
}
if (*info == 0) {
/*
Determine the block size. NB may be at most NBMAX, where NBMAX
is used to define the local array T.
Computing MIN
Writing concatenation
*/
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = 64, i__2 = ilaenv_(&c__1, "DORMLQ", ch__1, m, n, k, &c_n1, (
ftnlen)6, (ftnlen)2);
nb = min(i__1,i__2);
lwkopt = max(1,nw) * nb;
work[1] = (doublereal) lwkopt;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORMLQ", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0 || *k == 0) {
work[1] = 1.;
return 0;
}
nbmin = 2;
ldwork = nw;
if (nb > 1 && nb < *k) {
iws = nw * nb;
if (*lwork < iws) {
nb = *lwork / ldwork;
/*
Computing MAX
Writing concatenation
*/
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = 2, i__2 = ilaenv_(&c__2, "DORMLQ", ch__1, m, n, k, &c_n1, (
ftnlen)6, (ftnlen)2);
nbmin = max(i__1,i__2);
}
} else {
iws = nw;
}
if (nb < nbmin || nb >= *k) {
/* Use unblocked code */
dorml2_(side, trans, m, n, k, &a[a_offset], lda, &tau[1], &c__[
c_offset], ldc, &work[1], &iinfo);
} else {
/* Use blocked code */
if (left && notran || ! left && ! notran) {
i1 = 1;
i2 = *k;
i3 = nb;
} else {
i1 = (*k - 1) / nb * nb + 1;
i2 = 1;
i3 = -nb;
}
if (left) {
ni = *n;
jc = 1;
} else {
mi = *m;
ic = 1;
}
if (notran) {
*(unsigned char *)transt = 'T';
} else {
*(unsigned char *)transt = 'N';
}
i__1 = i2;
i__2 = i3;
for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/* Computing MIN */
i__4 = nb, i__5 = *k - i__ + 1;
ib = min(i__4,i__5);
/*
Form the triangular factor of the block reflector
H = H(i) H(i+1) . . . H(i+ib-1)
*/
i__4 = nq - i__ + 1;
dlarft_("Forward", "Rowwise", &i__4, &ib, &a[i__ + i__ * a_dim1],
lda, &tau[i__], t, &c__65);
if (left) {
/* H or H' is applied to C(i:m,1:n) */
mi = *m - i__ + 1;
ic = i__;
} else {
/* H or H' is applied to C(1:m,i:n) */
ni = *n - i__ + 1;
jc = i__;
}
/* Apply H or H' */
dlarfb_(side, transt, "Forward", "Rowwise", &mi, &ni, &ib, &a[i__
+ i__ * a_dim1], lda, t, &c__65, &c__[ic + jc * c_dim1],
ldc, &work[1], &ldwork);
/* L10: */
}
}
work[1] = (doublereal) lwkopt;
return 0;
/* End of DORMLQ */
} /* dormlq_ */
/* Subroutine */ int dormql_(char *side, char *trans, integer *m, integer *n,
integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal *
c__, integer *ldc, doublereal *work, integer *lwork, integer *info)
{
/* System generated locals */
address a__1[2];
integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2, i__3[2], i__4,
i__5;
char ch__1[2];
/* Local variables */
static integer i__;
static doublereal t[4160] /* was [65][64] */;
static integer i1, i2, i3, ib, nb, mi, ni, nq, nw, iws;
static logical left;
extern logical lsame_(char *, char *);
static integer nbmin, iinfo;
extern /* Subroutine */ int dorm2l_(char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *), dlarfb_(char
*, char *, char *, char *, integer *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *, doublereal *, integer *), dlarft_(char *, char *, integer *, integer *, doublereal
*, integer *, doublereal *, doublereal *, integer *), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static logical notran;
static integer ldwork, lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORMQL overwrites the general real M-by-N matrix C with
SIDE = 'L' SIDE = 'R'
TRANS = 'N': Q * C C * Q
TRANS = 'T': Q**T * C C * Q**T
where Q is a real orthogonal matrix defined as the product of k
elementary reflectors
Q = H(k) . . . H(2) H(1)
as returned by DGEQLF. Q is of order M if SIDE = 'L' and of order N
if SIDE = 'R'.
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': apply Q or Q**T from the Left;
= 'R': apply Q or Q**T from the Right.
TRANS (input) CHARACTER*1
= 'N': No transpose, apply Q;
= 'T': Transpose, apply Q**T.
M (input) INTEGER
The number of rows of the matrix C. M >= 0.
N (input) INTEGER
The number of columns of the matrix C. N >= 0.
K (input) INTEGER
The number of elementary reflectors whose product defines
the matrix Q.
If SIDE = 'L', M >= K >= 0;
if SIDE = 'R', N >= K >= 0.
A (input) DOUBLE PRECISION array, dimension (LDA,K)
The i-th column must contain the vector which defines the
elementary reflector H(i), for i = 1,2,...,k, as returned by
DGEQLF in the last k columns of its array argument A.
A is modified by the routine but restored on exit.
LDA (input) INTEGER
The leading dimension of the array A.
If SIDE = 'L', LDA >= max(1,M);
if SIDE = 'R', LDA >= max(1,N).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGEQLF.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the M-by-N matrix C.
On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If SIDE = 'L', LWORK >= max(1,N);
if SIDE = 'R', LWORK >= max(1,M).
For optimum performance LWORK >= N*NB if SIDE = 'L', and
LWORK >= M*NB if SIDE = 'R', where NB is the optimal
blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
*info = 0;
left = lsame_(side, "L");
notran = lsame_(trans, "N");
lquery = *lwork == -1;
/* NQ is the order of Q and NW is the minimum dimension of WORK */
if (left) {
nq = *m;
nw = max(1,*n);
} else {
nq = *n;
nw = max(1,*m);
}
if (! left && ! lsame_(side, "R")) {
*info = -1;
} else if (! notran && ! lsame_(trans, "T")) {
*info = -2;
} else if (*m < 0) {
*info = -3;
} else if (*n < 0) {
*info = -4;
} else if (*k < 0 || *k > nq) {
*info = -5;
} else if (*lda < max(1,nq)) {
*info = -7;
} else if (*ldc < max(1,*m)) {
*info = -10;
}
if (*info == 0) {
if (*m == 0 || *n == 0) {
lwkopt = 1;
} else {
/*
Determine the block size. NB may be at most NBMAX, where
NBMAX is used to define the local array T.
Computing MIN
Writing concatenation
*/
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = 64, i__2 = ilaenv_(&c__1, "DORMQL", ch__1, m, n, k, &c_n1,
(ftnlen)6, (ftnlen)2);
nb = min(i__1,i__2);
lwkopt = nw * nb;
}
work[1] = (doublereal) lwkopt;
if (*lwork < nw && ! lquery) {
*info = -12;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORMQL", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0) {
return 0;
}
nbmin = 2;
ldwork = nw;
if (nb > 1 && nb < *k) {
iws = nw * nb;
if (*lwork < iws) {
nb = *lwork / ldwork;
/*
Computing MAX
Writing concatenation
*/
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = 2, i__2 = ilaenv_(&c__2, "DORMQL", ch__1, m, n, k, &c_n1, (
ftnlen)6, (ftnlen)2);
nbmin = max(i__1,i__2);
}
} else {
iws = nw;
}
if (nb < nbmin || nb >= *k) {
/* Use unblocked code */
dorm2l_(side, trans, m, n, k, &a[a_offset], lda, &tau[1], &c__[
c_offset], ldc, &work[1], &iinfo);
} else {
/* Use blocked code */
if (left && notran || ! left && ! notran) {
i1 = 1;
i2 = *k;
i3 = nb;
} else {
i1 = (*k - 1) / nb * nb + 1;
i2 = 1;
i3 = -nb;
}
if (left) {
ni = *n;
} else {
mi = *m;
}
i__1 = i2;
i__2 = i3;
for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/* Computing MIN */
i__4 = nb, i__5 = *k - i__ + 1;
ib = min(i__4,i__5);
/*
Form the triangular factor of the block reflector
H = H(i+ib-1) . . . H(i+1) H(i)
*/
i__4 = nq - *k + i__ + ib - 1;
dlarft_("Backward", "Columnwise", &i__4, &ib, &a[i__ * a_dim1 + 1]
, lda, &tau[i__], t, &c__65);
if (left) {
/* H or H' is applied to C(1:m-k+i+ib-1,1:n) */
mi = *m - *k + i__ + ib - 1;
} else {
/* H or H' is applied to C(1:m,1:n-k+i+ib-1) */
ni = *n - *k + i__ + ib - 1;
}
/* Apply H or H' */
dlarfb_(side, trans, "Backward", "Columnwise", &mi, &ni, &ib, &a[
i__ * a_dim1 + 1], lda, t, &c__65, &c__[c_offset], ldc, &
work[1], &ldwork);
/* L10: */
}
}
work[1] = (doublereal) lwkopt;
return 0;
/* End of DORMQL */
} /* dormql_ */
/* Subroutine */ int dormqr_(char *side, char *trans, integer *m, integer *n,
integer *k, doublereal *a, integer *lda, doublereal *tau, doublereal *
c__, integer *ldc, doublereal *work, integer *lwork, integer *info)
{
/* System generated locals */
address a__1[2];
integer a_dim1, a_offset, c_dim1, c_offset, i__1, i__2, i__3[2], i__4,
i__5;
char ch__1[2];
/* Local variables */
static integer i__;
static doublereal t[4160] /* was [65][64] */;
static integer i1, i2, i3, ib, ic, jc, nb, mi, ni, nq, nw, iws;
static logical left;
extern logical lsame_(char *, char *);
static integer nbmin, iinfo;
extern /* Subroutine */ int dorm2r_(char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *), dlarfb_(char
*, char *, char *, char *, integer *, integer *, integer *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *, doublereal *, integer *), dlarft_(char *, char *, integer *, integer *, doublereal
*, integer *, doublereal *, doublereal *, integer *), xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static logical notran;
static integer ldwork, lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORMQR overwrites the general real M-by-N matrix C with
SIDE = 'L' SIDE = 'R'
TRANS = 'N': Q * C C * Q
TRANS = 'T': Q**T * C C * Q**T
where Q is a real orthogonal matrix defined as the product of k
elementary reflectors
Q = H(1) H(2) . . . H(k)
as returned by DGEQRF. Q is of order M if SIDE = 'L' and of order N
if SIDE = 'R'.
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': apply Q or Q**T from the Left;
= 'R': apply Q or Q**T from the Right.
TRANS (input) CHARACTER*1
= 'N': No transpose, apply Q;
= 'T': Transpose, apply Q**T.
M (input) INTEGER
The number of rows of the matrix C. M >= 0.
N (input) INTEGER
The number of columns of the matrix C. N >= 0.
K (input) INTEGER
The number of elementary reflectors whose product defines
the matrix Q.
If SIDE = 'L', M >= K >= 0;
if SIDE = 'R', N >= K >= 0.
A (input) DOUBLE PRECISION array, dimension (LDA,K)
The i-th column must contain the vector which defines the
elementary reflector H(i), for i = 1,2,...,k, as returned by
DGEQRF in the first k columns of its array argument A.
A is modified by the routine but restored on exit.
LDA (input) INTEGER
The leading dimension of the array A.
If SIDE = 'L', LDA >= max(1,M);
if SIDE = 'R', LDA >= max(1,N).
TAU (input) DOUBLE PRECISION array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DGEQRF.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the M-by-N matrix C.
On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If SIDE = 'L', LWORK >= max(1,N);
if SIDE = 'R', LWORK >= max(1,M).
For optimum performance LWORK >= N*NB if SIDE = 'L', and
LWORK >= M*NB if SIDE = 'R', where NB is the optimal
blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
*info = 0;
left = lsame_(side, "L");
notran = lsame_(trans, "N");
lquery = *lwork == -1;
/* NQ is the order of Q and NW is the minimum dimension of WORK */
if (left) {
nq = *m;
nw = *n;
} else {
nq = *n;
nw = *m;
}
if (! left && ! lsame_(side, "R")) {
*info = -1;
} else if (! notran && ! lsame_(trans, "T")) {
*info = -2;
} else if (*m < 0) {
*info = -3;
} else if (*n < 0) {
*info = -4;
} else if (*k < 0 || *k > nq) {
*info = -5;
} else if (*lda < max(1,nq)) {
*info = -7;
} else if (*ldc < max(1,*m)) {
*info = -10;
} else if (*lwork < max(1,nw) && ! lquery) {
*info = -12;
}
if (*info == 0) {
/*
Determine the block size. NB may be at most NBMAX, where NBMAX
is used to define the local array T.
Computing MIN
Writing concatenation
*/
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = 64, i__2 = ilaenv_(&c__1, "DORMQR", ch__1, m, n, k, &c_n1, (
ftnlen)6, (ftnlen)2);
nb = min(i__1,i__2);
lwkopt = max(1,nw) * nb;
work[1] = (doublereal) lwkopt;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DORMQR", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0 || *k == 0) {
work[1] = 1.;
return 0;
}
nbmin = 2;
ldwork = nw;
if (nb > 1 && nb < *k) {
iws = nw * nb;
if (*lwork < iws) {
nb = *lwork / ldwork;
/*
Computing MAX
Writing concatenation
*/
i__3[0] = 1, a__1[0] = side;
i__3[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__3, &c__2, (ftnlen)2);
i__1 = 2, i__2 = ilaenv_(&c__2, "DORMQR", ch__1, m, n, k, &c_n1, (
ftnlen)6, (ftnlen)2);
nbmin = max(i__1,i__2);
}
} else {
iws = nw;
}
if (nb < nbmin || nb >= *k) {
/* Use unblocked code */
dorm2r_(side, trans, m, n, k, &a[a_offset], lda, &tau[1], &c__[
c_offset], ldc, &work[1], &iinfo);
} else {
/* Use blocked code */
if (left && ! notran || ! left && notran) {
i1 = 1;
i2 = *k;
i3 = nb;
} else {
i1 = (*k - 1) / nb * nb + 1;
i2 = 1;
i3 = -nb;
}
if (left) {
ni = *n;
jc = 1;
} else {
mi = *m;
ic = 1;
}
i__1 = i2;
i__2 = i3;
for (i__ = i1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ += i__2) {
/* Computing MIN */
i__4 = nb, i__5 = *k - i__ + 1;
ib = min(i__4,i__5);
/*
Form the triangular factor of the block reflector
H = H(i) H(i+1) . . . H(i+ib-1)
*/
i__4 = nq - i__ + 1;
dlarft_("Forward", "Columnwise", &i__4, &ib, &a[i__ + i__ *
a_dim1], lda, &tau[i__], t, &c__65)
;
if (left) {
/* H or H' is applied to C(i:m,1:n) */
mi = *m - i__ + 1;
ic = i__;
} else {
/* H or H' is applied to C(1:m,i:n) */
ni = *n - i__ + 1;
jc = i__;
}
/* Apply H or H' */
dlarfb_(side, trans, "Forward", "Columnwise", &mi, &ni, &ib, &a[
i__ + i__ * a_dim1], lda, t, &c__65, &c__[ic + jc *
c_dim1], ldc, &work[1], &ldwork);
/* L10: */
}
}
work[1] = (doublereal) lwkopt;
return 0;
/* End of DORMQR */
} /* dormqr_ */
/* Subroutine */ int dormtr_(char *side, char *uplo, char *trans, integer *m,
integer *n, doublereal *a, integer *lda, doublereal *tau, doublereal *
c__, integer *ldc, doublereal *work, integer *lwork, integer *info)
{
/* System generated locals */
address a__1[2];
integer a_dim1, a_offset, c_dim1, c_offset, i__1[2], i__2, i__3;
char ch__1[2];
/* Local variables */
static integer i1, i2, nb, mi, ni, nq, nw;
static logical left;
extern logical lsame_(char *, char *);
static integer iinfo;
static logical upper;
extern /* Subroutine */ int xerbla_(char *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int dormql_(char *, char *, integer *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *, integer *),
dormqr_(char *, char *, integer *, integer *, integer *,
doublereal *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *, integer *);
static integer lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DORMTR overwrites the general real M-by-N matrix C with
SIDE = 'L' SIDE = 'R'
TRANS = 'N': Q * C C * Q
TRANS = 'T': Q**T * C C * Q**T
where Q is a real orthogonal matrix of order nq, with nq = m if
SIDE = 'L' and nq = n if SIDE = 'R'. Q is defined as the product of
nq-1 elementary reflectors, as returned by DSYTRD:
if UPLO = 'U', Q = H(nq-1) . . . H(2) H(1);
if UPLO = 'L', Q = H(1) H(2) . . . H(nq-1).
Arguments
=========
SIDE (input) CHARACTER*1
= 'L': apply Q or Q**T from the Left;
= 'R': apply Q or Q**T from the Right.
UPLO (input) CHARACTER*1
= 'U': Upper triangle of A contains elementary reflectors
from DSYTRD;
= 'L': Lower triangle of A contains elementary reflectors
from DSYTRD.
TRANS (input) CHARACTER*1
= 'N': No transpose, apply Q;
= 'T': Transpose, apply Q**T.
M (input) INTEGER
The number of rows of the matrix C. M >= 0.
N (input) INTEGER
The number of columns of the matrix C. N >= 0.
A (input) DOUBLE PRECISION array, dimension
(LDA,M) if SIDE = 'L'
(LDA,N) if SIDE = 'R'
The vectors which define the elementary reflectors, as
returned by DSYTRD.
LDA (input) INTEGER
The leading dimension of the array A.
LDA >= max(1,M) if SIDE = 'L'; LDA >= max(1,N) if SIDE = 'R'.
TAU (input) DOUBLE PRECISION array, dimension
(M-1) if SIDE = 'L'
(N-1) if SIDE = 'R'
TAU(i) must contain the scalar factor of the elementary
reflector H(i), as returned by DSYTRD.
C (input/output) DOUBLE PRECISION array, dimension (LDC,N)
On entry, the M-by-N matrix C.
On exit, C is overwritten by Q*C or Q**T*C or C*Q**T or C*Q.
LDC (input) INTEGER
The leading dimension of the array C. LDC >= max(1,M).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If SIDE = 'L', LWORK >= max(1,N);
if SIDE = 'R', LWORK >= max(1,M).
For optimum performance LWORK >= N*NB if SIDE = 'L', and
LWORK >= M*NB if SIDE = 'R', where NB is the optimal
blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input arguments
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--tau;
c_dim1 = *ldc;
c_offset = 1 + c_dim1;
c__ -= c_offset;
--work;
/* Function Body */
*info = 0;
left = lsame_(side, "L");
upper = lsame_(uplo, "U");
lquery = *lwork == -1;
/* NQ is the order of Q and NW is the minimum dimension of WORK */
if (left) {
nq = *m;
nw = *n;
} else {
nq = *n;
nw = *m;
}
if (! left && ! lsame_(side, "R")) {
*info = -1;
} else if (! upper && ! lsame_(uplo, "L")) {
*info = -2;
} else if (! lsame_(trans, "N") && ! lsame_(trans,
"T")) {
*info = -3;
} else if (*m < 0) {
*info = -4;
} else if (*n < 0) {
*info = -5;
} else if (*lda < max(1,nq)) {
*info = -7;
} else if (*ldc < max(1,*m)) {
*info = -10;
} else if (*lwork < max(1,nw) && ! lquery) {
*info = -12;
}
if (*info == 0) {
if (upper) {
if (left) {
/* Writing concatenation */
i__1[0] = 1, a__1[0] = side;
i__1[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2);
i__2 = *m - 1;
i__3 = *m - 1;
nb = ilaenv_(&c__1, "DORMQL", ch__1, &i__2, n, &i__3, &c_n1, (
ftnlen)6, (ftnlen)2);
} else {
/* Writing concatenation */
i__1[0] = 1, a__1[0] = side;
i__1[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2);
i__2 = *n - 1;
i__3 = *n - 1;
nb = ilaenv_(&c__1, "DORMQL", ch__1, m, &i__2, &i__3, &c_n1, (
ftnlen)6, (ftnlen)2);
}
} else {
if (left) {
/* Writing concatenation */
i__1[0] = 1, a__1[0] = side;
i__1[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2);
i__2 = *m - 1;
i__3 = *m - 1;
nb = ilaenv_(&c__1, "DORMQR", ch__1, &i__2, n, &i__3, &c_n1, (
ftnlen)6, (ftnlen)2);
} else {
/* Writing concatenation */
i__1[0] = 1, a__1[0] = side;
i__1[1] = 1, a__1[1] = trans;
s_cat(ch__1, a__1, i__1, &c__2, (ftnlen)2);
i__2 = *n - 1;
i__3 = *n - 1;
nb = ilaenv_(&c__1, "DORMQR", ch__1, m, &i__2, &i__3, &c_n1, (
ftnlen)6, (ftnlen)2);
}
}
lwkopt = max(1,nw) * nb;
work[1] = (doublereal) lwkopt;
}
if (*info != 0) {
i__2 = -(*info);
xerbla_("DORMTR", &i__2);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m == 0 || *n == 0 || nq == 1) {
work[1] = 1.;
return 0;
}
if (left) {
mi = *m - 1;
ni = *n;
} else {
mi = *m;
ni = *n - 1;
}
if (upper) {
/* Q was determined by a call to DSYTRD with UPLO = 'U' */
i__2 = nq - 1;
dormql_(side, trans, &mi, &ni, &i__2, &a[(a_dim1 << 1) + 1], lda, &
tau[1], &c__[c_offset], ldc, &work[1], lwork, &iinfo);
} else {
/* Q was determined by a call to DSYTRD with UPLO = 'L' */
if (left) {
i1 = 2;
i2 = 1;
} else {
i1 = 1;
i2 = 2;
}
i__2 = nq - 1;
dormqr_(side, trans, &mi, &ni, &i__2, &a[a_dim1 + 2], lda, &tau[1], &
c__[i1 + i2 * c_dim1], ldc, &work[1], lwork, &iinfo);
}
work[1] = (doublereal) lwkopt;
return 0;
/* End of DORMTR */
} /* dormtr_ */
/* Subroutine */ int dpotf2_(char *uplo, integer *n, doublereal *a, integer *
lda, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
doublereal d__1;
/* Local variables */
static integer j;
static doublereal ajj;
extern doublereal ddot_(integer *, doublereal *, integer *, doublereal *,
integer *);
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dgemv_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *);
static logical upper;
extern logical disnan_(doublereal *);
extern /* Subroutine */ int xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DPOTF2 computes the Cholesky factorization of a real symmetric
positive definite matrix A.
The factorization has the form
A = U' * U , if UPLO = 'U', or
A = L * L', if UPLO = 'L',
where U is an upper triangular matrix and L is lower triangular.
This is the unblocked version of the algorithm, calling Level 2 BLAS.
Arguments
=========
UPLO (input) CHARACTER*1
Specifies whether the upper or lower triangular part of the
symmetric matrix A is stored.
= 'U': Upper triangular
= 'L': Lower triangular
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the symmetric matrix A. If UPLO = 'U', the leading
n by n upper triangular part of A contains the upper
triangular part of the matrix A, and the strictly lower
triangular part of A is not referenced. If UPLO = 'L', the
leading n by n lower triangular part of A contains the lower
triangular part of the matrix A, and the strictly upper
triangular part of A is not referenced.
On exit, if INFO = 0, the factor U or L from the Cholesky
factorization A = U'*U or A = L*L'.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -k, the k-th argument had an illegal value
> 0: if INFO = k, the leading minor of order k is not
positive definite, and the factorization could not be
completed.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DPOTF2", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (upper) {
/* Compute the Cholesky factorization A = U'*U. */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
/* Compute U(J,J) and test for non-positive-definiteness. */
i__2 = j - 1;
ajj = a[j + j * a_dim1] - ddot_(&i__2, &a[j * a_dim1 + 1], &c__1,
&a[j * a_dim1 + 1], &c__1);
if (ajj <= 0. || disnan_(&ajj)) {
a[j + j * a_dim1] = ajj;
goto L30;
}
ajj = sqrt(ajj);
a[j + j * a_dim1] = ajj;
/* Compute elements J+1:N of row J. */
if (j < *n) {
i__2 = j - 1;
i__3 = *n - j;
dgemv_("Transpose", &i__2, &i__3, &c_b151, &a[(j + 1) *
a_dim1 + 1], lda, &a[j * a_dim1 + 1], &c__1, &c_b15, &
a[j + (j + 1) * a_dim1], lda);
i__2 = *n - j;
d__1 = 1. / ajj;
dscal_(&i__2, &d__1, &a[j + (j + 1) * a_dim1], lda);
}
/* L10: */
}
} else {
/* Compute the Cholesky factorization A = L*L'. */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
/* Compute L(J,J) and test for non-positive-definiteness. */
i__2 = j - 1;
ajj = a[j + j * a_dim1] - ddot_(&i__2, &a[j + a_dim1], lda, &a[j
+ a_dim1], lda);
if (ajj <= 0. || disnan_(&ajj)) {
a[j + j * a_dim1] = ajj;
goto L30;
}
ajj = sqrt(ajj);
a[j + j * a_dim1] = ajj;
/* Compute elements J+1:N of column J. */
if (j < *n) {
i__2 = *n - j;
i__3 = j - 1;
dgemv_("No transpose", &i__2, &i__3, &c_b151, &a[j + 1 +
a_dim1], lda, &a[j + a_dim1], lda, &c_b15, &a[j + 1 +
j * a_dim1], &c__1);
i__2 = *n - j;
d__1 = 1. / ajj;
dscal_(&i__2, &d__1, &a[j + 1 + j * a_dim1], &c__1);
}
/* L20: */
}
}
goto L40;
L30:
*info = j;
L40:
return 0;
/* End of DPOTF2 */
} /* dpotf2_ */
/* Subroutine */ int dpotrf_(char *uplo, integer *n, doublereal *a, integer *
lda, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3, i__4;
/* Local variables */
static integer j, jb, nb;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dtrsm_(char *, char *, char *, char *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *);
static logical upper;
extern /* Subroutine */ int dsyrk_(char *, char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, doublereal *,
integer *), dpotf2_(char *, integer *,
doublereal *, integer *, integer *), xerbla_(char *,
integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DPOTRF computes the Cholesky factorization of a real symmetric
positive definite matrix A.
The factorization has the form
A = U**T * U, if UPLO = 'U', or
A = L * L**T, if UPLO = 'L',
where U is an upper triangular matrix and L is lower triangular.
This is the block version of the algorithm, calling Level 3 BLAS.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': Upper triangle of A is stored;
= 'L': Lower triangle of A is stored.
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the symmetric matrix A. If UPLO = 'U', the leading
N-by-N upper triangular part of A contains the upper
triangular part of the matrix A, and the strictly lower
triangular part of A is not referenced. If UPLO = 'L', the
leading N-by-N lower triangular part of A contains the lower
triangular part of the matrix A, and the strictly upper
triangular part of A is not referenced.
On exit, if INFO = 0, the factor U or L from the Cholesky
factorization A = U**T*U or A = L*L**T.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, the leading minor of order i is not
positive definite, and the factorization could not be
completed.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DPOTRF", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/* Determine the block size for this environment. */
nb = ilaenv_(&c__1, "DPOTRF", uplo, n, &c_n1, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)1);
if (nb <= 1 || nb >= *n) {
/* Use unblocked code. */
dpotf2_(uplo, n, &a[a_offset], lda, info);
} else {
/* Use blocked code. */
if (upper) {
/* Compute the Cholesky factorization A = U'*U. */
i__1 = *n;
i__2 = nb;
for (j = 1; i__2 < 0 ? j >= i__1 : j <= i__1; j += i__2) {
/*
Update and factorize the current diagonal block and test
for non-positive-definiteness.
Computing MIN
*/
i__3 = nb, i__4 = *n - j + 1;
jb = min(i__3,i__4);
i__3 = j - 1;
dsyrk_("Upper", "Transpose", &jb, &i__3, &c_b151, &a[j *
a_dim1 + 1], lda, &c_b15, &a[j + j * a_dim1], lda);
dpotf2_("Upper", &jb, &a[j + j * a_dim1], lda, info);
if (*info != 0) {
goto L30;
}
if (j + jb <= *n) {
/* Compute the current block row. */
i__3 = *n - j - jb + 1;
i__4 = j - 1;
dgemm_("Transpose", "No transpose", &jb, &i__3, &i__4, &
c_b151, &a[j * a_dim1 + 1], lda, &a[(j + jb) *
a_dim1 + 1], lda, &c_b15, &a[j + (j + jb) *
a_dim1], lda);
i__3 = *n - j - jb + 1;
dtrsm_("Left", "Upper", "Transpose", "Non-unit", &jb, &
i__3, &c_b15, &a[j + j * a_dim1], lda, &a[j + (j
+ jb) * a_dim1], lda);
}
/* L10: */
}
} else {
/* Compute the Cholesky factorization A = L*L'. */
i__2 = *n;
i__1 = nb;
for (j = 1; i__1 < 0 ? j >= i__2 : j <= i__2; j += i__1) {
/*
Update and factorize the current diagonal block and test
for non-positive-definiteness.
Computing MIN
*/
i__3 = nb, i__4 = *n - j + 1;
jb = min(i__3,i__4);
i__3 = j - 1;
dsyrk_("Lower", "No transpose", &jb, &i__3, &c_b151, &a[j +
a_dim1], lda, &c_b15, &a[j + j * a_dim1], lda);
dpotf2_("Lower", &jb, &a[j + j * a_dim1], lda, info);
if (*info != 0) {
goto L30;
}
if (j + jb <= *n) {
/* Compute the current block column. */
i__3 = *n - j - jb + 1;
i__4 = j - 1;
dgemm_("No transpose", "Transpose", &i__3, &jb, &i__4, &
c_b151, &a[j + jb + a_dim1], lda, &a[j + a_dim1],
lda, &c_b15, &a[j + jb + j * a_dim1], lda);
i__3 = *n - j - jb + 1;
dtrsm_("Right", "Lower", "Transpose", "Non-unit", &i__3, &
jb, &c_b15, &a[j + j * a_dim1], lda, &a[j + jb +
j * a_dim1], lda);
}
/* L20: */
}
}
}
goto L40;
L30:
*info = *info + j - 1;
L40:
return 0;
/* End of DPOTRF */
} /* dpotrf_ */
/* Subroutine */ int dpotri_(char *uplo, integer *n, doublereal *a, integer *
lda, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1;
/* Local variables */
extern logical lsame_(char *, char *);
extern /* Subroutine */ int xerbla_(char *, integer *), dlauum_(
char *, integer *, doublereal *, integer *, integer *),
dtrtri_(char *, char *, integer *, doublereal *, integer *,
integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DPOTRI computes the inverse of a real symmetric positive definite
matrix A using the Cholesky factorization A = U**T*U or A = L*L**T
computed by DPOTRF.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': Upper triangle of A is stored;
= 'L': Lower triangle of A is stored.
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the triangular factor U or L from the Cholesky
factorization A = U**T*U or A = L*L**T, as computed by
DPOTRF.
On exit, the upper or lower triangle of the (symmetric)
inverse of A, overwriting the input factor U or L.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, the (i,i) element of the factor U or L is
zero, and the inverse could not be computed.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
*info = 0;
if (! lsame_(uplo, "U") && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DPOTRI", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/* Invert the triangular Cholesky factor U or L. */
dtrtri_(uplo, "Non-unit", n, &a[a_offset], lda, info);
if (*info > 0) {
return 0;
}
/* Form inv(U)*inv(U)' or inv(L)'*inv(L). */
dlauum_(uplo, n, &a[a_offset], lda, info);
return 0;
/* End of DPOTRI */
} /* dpotri_ */
/* Subroutine */ int dpotrs_(char *uplo, integer *n, integer *nrhs,
doublereal *a, integer *lda, doublereal *b, integer *ldb, integer *
info)
{
/* System generated locals */
integer a_dim1, a_offset, b_dim1, b_offset, i__1;
/* Local variables */
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dtrsm_(char *, char *, char *, char *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *);
static logical upper;
extern /* Subroutine */ int xerbla_(char *, integer *);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DPOTRS solves a system of linear equations A*X = B with a symmetric
positive definite matrix A using the Cholesky factorization
A = U**T*U or A = L*L**T computed by DPOTRF.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': Upper triangle of A is stored;
= 'L': Lower triangle of A is stored.
N (input) INTEGER
The order of the matrix A. N >= 0.
NRHS (input) INTEGER
The number of right hand sides, i.e., the number of columns
of the matrix B. NRHS >= 0.
A (input) DOUBLE PRECISION array, dimension (LDA,N)
The triangular factor U or L from the Cholesky factorization
A = U**T*U or A = L*L**T, as computed by DPOTRF.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
B (input/output) DOUBLE PRECISION array, dimension (LDB,NRHS)
On entry, the right hand side matrix B.
On exit, the solution matrix X.
LDB (input) INTEGER
The leading dimension of the array B. LDB >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
b_dim1 = *ldb;
b_offset = 1 + b_dim1;
b -= b_offset;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*nrhs < 0) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
} else if (*ldb < max(1,*n)) {
*info = -7;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DPOTRS", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0 || *nrhs == 0) {
return 0;
}
if (upper) {
/*
Solve A*X = B where A = U'*U.
Solve U'*X = B, overwriting B with X.
*/
dtrsm_("Left", "Upper", "Transpose", "Non-unit", n, nrhs, &c_b15, &a[
a_offset], lda, &b[b_offset], ldb);
/* Solve U*X = B, overwriting B with X. */
dtrsm_("Left", "Upper", "No transpose", "Non-unit", n, nrhs, &c_b15, &
a[a_offset], lda, &b[b_offset], ldb);
} else {
/*
Solve A*X = B where A = L*L'.
Solve L*X = B, overwriting B with X.
*/
dtrsm_("Left", "Lower", "No transpose", "Non-unit", n, nrhs, &c_b15, &
a[a_offset], lda, &b[b_offset], ldb);
/* Solve L'*X = B, overwriting B with X. */
dtrsm_("Left", "Lower", "Transpose", "Non-unit", n, nrhs, &c_b15, &a[
a_offset], lda, &b[b_offset], ldb);
}
return 0;
/* End of DPOTRS */
} /* dpotrs_ */
/* Subroutine */ int dstedc_(char *compz, integer *n, doublereal *d__,
doublereal *e, doublereal *z__, integer *ldz, doublereal *work,
integer *lwork, integer *iwork, integer *liwork, integer *info)
{
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2;
doublereal d__1, d__2;
/* Local variables */
static integer i__, j, k, m;
static doublereal p;
static integer ii, lgn;
static doublereal eps, tiny;
extern /* Subroutine */ int dgemm_(char *, char *, integer *, integer *,
integer *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, doublereal *, integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dswap_(integer *, doublereal *, integer *,
doublereal *, integer *);
static integer lwmin;
extern /* Subroutine */ int dlaed0_(integer *, integer *, integer *,
doublereal *, doublereal *, doublereal *, integer *, doublereal *,
integer *, doublereal *, integer *, integer *);
static integer start;
extern /* Subroutine */ int dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *), dlacpy_(char *, integer *, integer
*, doublereal *, integer *, doublereal *, integer *),
dlaset_(char *, integer *, integer *, doublereal *, doublereal *,
doublereal *, integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int xerbla_(char *, integer *);
static integer finish;
extern doublereal dlanst_(char *, integer *, doublereal *, doublereal *);
extern /* Subroutine */ int dsterf_(integer *, doublereal *, doublereal *,
integer *), dlasrt_(char *, integer *, doublereal *, integer *);
static integer liwmin, icompz;
extern /* Subroutine */ int dsteqr_(char *, integer *, doublereal *,
doublereal *, doublereal *, integer *, doublereal *, integer *);
static doublereal orgnrm;
static logical lquery;
static integer smlsiz, storez, strtrw;
/*
-- LAPACK driver routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DSTEDC computes all eigenvalues and, optionally, eigenvectors of a
symmetric tridiagonal matrix using the divide and conquer method.
The eigenvectors of a full or band real symmetric matrix can also be
found if DSYTRD or DSPTRD or DSBTRD has been used to reduce this
matrix to tridiagonal form.
This code makes very mild assumptions about floating point
arithmetic. It will work on machines with a guard digit in
add/subtract, or on those binary machines without guard digits
which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or Cray-2.
It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none. See DLAED3 for details.
Arguments
=========
COMPZ (input) CHARACTER*1
= 'N': Compute eigenvalues only.
= 'I': Compute eigenvectors of tridiagonal matrix also.
= 'V': Compute eigenvectors of original dense symmetric
matrix also. On entry, Z contains the orthogonal
matrix used to reduce the original matrix to
tridiagonal form.
N (input) INTEGER
The dimension of the symmetric tridiagonal matrix. N >= 0.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, the diagonal elements of the tridiagonal matrix.
On exit, if INFO = 0, the eigenvalues in ascending order.
E (input/output) DOUBLE PRECISION array, dimension (N-1)
On entry, the subdiagonal elements of the tridiagonal matrix.
On exit, E has been destroyed.
Z (input/output) DOUBLE PRECISION array, dimension (LDZ,N)
On entry, if COMPZ = 'V', then Z contains the orthogonal
matrix used in the reduction to tridiagonal form.
On exit, if INFO = 0, then if COMPZ = 'V', Z contains the
orthonormal eigenvectors of the original symmetric matrix,
and if COMPZ = 'I', Z contains the orthonormal eigenvectors
of the symmetric tridiagonal matrix.
If COMPZ = 'N', then Z is not referenced.
LDZ (input) INTEGER
The leading dimension of the array Z. LDZ >= 1.
If eigenvectors are desired, then LDZ >= max(1,N).
WORK (workspace/output) DOUBLE PRECISION array,
dimension (LWORK)
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If COMPZ = 'N' or N <= 1 then LWORK must be at least 1.
If COMPZ = 'V' and N > 1 then LWORK must be at least
( 1 + 3*N + 2*N*lg N + 3*N**2 ),
where lg( N ) = smallest integer k such
that 2**k >= N.
If COMPZ = 'I' and N > 1 then LWORK must be at least
( 1 + 4*N + N**2 ).
Note that for COMPZ = 'I' or 'V', then if N is less than or
equal to the minimum divide size, usually 25, then LWORK need
only be max(1,2*(N-1)).
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
IWORK (workspace/output) INTEGER array, dimension (MAX(1,LIWORK))
On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.
LIWORK (input) INTEGER
The dimension of the array IWORK.
If COMPZ = 'N' or N <= 1 then LIWORK must be at least 1.
If COMPZ = 'V' and N > 1 then LIWORK must be at least
( 6 + 6*N + 5*N*lg N ).
If COMPZ = 'I' and N > 1 then LIWORK must be at least
( 3 + 5*N ).
Note that for COMPZ = 'I' or 'V', then if N is less than or
equal to the minimum divide size, usually 25, then LIWORK
need only be 1.
If LIWORK = -1, then a workspace query is assumed; the
routine only calculates the optimal size of the IWORK array,
returns this value as the first entry of the IWORK array, and
no error message related to LIWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit.
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: The algorithm failed to compute an eigenvalue while
working on the submatrix lying in rows and columns
INFO/(N+1) through mod(INFO,N+1).
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
Modified by Francoise Tisseur, University of Tennessee.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--e;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--work;
--iwork;
/* Function Body */
*info = 0;
lquery = *lwork == -1 || *liwork == -1;
if (lsame_(compz, "N")) {
icompz = 0;
} else if (lsame_(compz, "V")) {
icompz = 1;
} else if (lsame_(compz, "I")) {
icompz = 2;
} else {
icompz = -1;
}
if (icompz < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*ldz < 1 || icompz > 0 && *ldz < max(1,*n)) {
*info = -6;
}
if (*info == 0) {
/* Compute the workspace requirements */
smlsiz = ilaenv_(&c__9, "DSTEDC", " ", &c__0, &c__0, &c__0, &c__0, (
ftnlen)6, (ftnlen)1);
if (*n <= 1 || icompz == 0) {
liwmin = 1;
lwmin = 1;
} else if (*n <= smlsiz) {
liwmin = 1;
lwmin = *n - 1 << 1;
} else {
lgn = (integer) (log((doublereal) (*n)) / log(2.));
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
if (pow_ii(&c__2, &lgn) < *n) {
++lgn;
}
if (icompz == 1) {
/* Computing 2nd power */
i__1 = *n;
lwmin = *n * 3 + 1 + (*n << 1) * lgn + i__1 * i__1 * 3;
liwmin = *n * 6 + 6 + *n * 5 * lgn;
} else if (icompz == 2) {
/* Computing 2nd power */
i__1 = *n;
lwmin = (*n << 2) + 1 + i__1 * i__1;
liwmin = *n * 5 + 3;
}
}
work[1] = (doublereal) lwmin;
iwork[1] = liwmin;
if (*lwork < lwmin && ! lquery) {
*info = -8;
} else if (*liwork < liwmin && ! lquery) {
*info = -10;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DSTEDC", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (icompz != 0) {
z__[z_dim1 + 1] = 1.;
}
return 0;
}
/*
If the following conditional clause is removed, then the routine
will use the Divide and Conquer routine to compute only the
eigenvalues, which requires (3N + 3N**2) real workspace and
(2 + 5N + 2N lg(N)) integer workspace.
Since on many architectures DSTERF is much faster than any other
algorithm for finding eigenvalues only, it is used here
as the default. If the conditional clause is removed, then
information on the size of workspace needs to be changed.
If COMPZ = 'N', use DSTERF to compute the eigenvalues.
*/
if (icompz == 0) {
dsterf_(n, &d__[1], &e[1], info);
goto L50;
}
/*
If N is smaller than the minimum divide size (SMLSIZ+1), then
solve the problem with another solver.
*/
if (*n <= smlsiz) {
dsteqr_(compz, n, &d__[1], &e[1], &z__[z_offset], ldz, &work[1], info);
} else {
/*
If COMPZ = 'V', the Z matrix must be stored elsewhere for later
use.
*/
if (icompz == 1) {
storez = *n * *n + 1;
} else {
storez = 1;
}
if (icompz == 2) {
dlaset_("Full", n, n, &c_b29, &c_b15, &z__[z_offset], ldz);
}
/* Scale. */
orgnrm = dlanst_("M", n, &d__[1], &e[1]);
if (orgnrm == 0.) {
goto L50;
}
eps = EPSILON;
start = 1;
/* while ( START <= N ) */
L10:
if (start <= *n) {
/*
Let FINISH be the position of the next subdiagonal entry
such that E( FINISH ) <= TINY or FINISH = N if no such
subdiagonal exists. The matrix identified by the elements
between START and FINISH constitutes an independent
sub-problem.
*/
finish = start;
L20:
if (finish < *n) {
tiny = eps * sqrt((d__1 = d__[finish], abs(d__1))) * sqrt((
d__2 = d__[finish + 1], abs(d__2)));
if ((d__1 = e[finish], abs(d__1)) > tiny) {
++finish;
goto L20;
}
}
/* (Sub) Problem determined. Compute its size and solve it. */
m = finish - start + 1;
if (m == 1) {
start = finish + 1;
goto L10;
}
if (m > smlsiz) {
/* Scale. */
orgnrm = dlanst_("M", &m, &d__[start], &e[start]);
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, &m, &c__1, &d__[
start], &m, info);
i__1 = m - 1;
i__2 = m - 1;
dlascl_("G", &c__0, &c__0, &orgnrm, &c_b15, &i__1, &c__1, &e[
start], &i__2, info);
if (icompz == 1) {
strtrw = 1;
} else {
strtrw = start;
}
dlaed0_(&icompz, n, &m, &d__[start], &e[start], &z__[strtrw +
start * z_dim1], ldz, &work[1], n, &work[storez], &
iwork[1], info);
if (*info != 0) {
*info = (*info / (m + 1) + start - 1) * (*n + 1) + *info %
(m + 1) + start - 1;
goto L50;
}
/* Scale back. */
dlascl_("G", &c__0, &c__0, &c_b15, &orgnrm, &m, &c__1, &d__[
start], &m, info);
} else {
if (icompz == 1) {
/*
Since QR won't update a Z matrix which is larger than
the length of D, we must solve the sub-problem in a
workspace and then multiply back into Z.
*/
dsteqr_("I", &m, &d__[start], &e[start], &work[1], &m, &
work[m * m + 1], info);
dlacpy_("A", n, &m, &z__[start * z_dim1 + 1], ldz, &work[
storez], n);
dgemm_("N", "N", n, &m, &m, &c_b15, &work[storez], n, &
work[1], &m, &c_b29, &z__[start * z_dim1 + 1],
ldz);
} else if (icompz == 2) {
dsteqr_("I", &m, &d__[start], &e[start], &z__[start +
start * z_dim1], ldz, &work[1], info);
} else {
dsterf_(&m, &d__[start], &e[start], info);
}
if (*info != 0) {
*info = start * (*n + 1) + finish;
goto L50;
}
}
start = finish + 1;
goto L10;
}
/*
endwhile
If the problem split any number of times, then the eigenvalues
will not be properly ordered. Here we permute the eigenvalues
(and the associated eigenvectors) into ascending order.
*/
if (m != *n) {
if (icompz == 0) {
/* Use Quick Sort */
dlasrt_("I", n, &d__[1], info);
} else {
/* Use Selection Sort to minimize swaps of eigenvectors */
i__1 = *n;
for (ii = 2; ii <= i__1; ++ii) {
i__ = ii - 1;
k = i__;
p = d__[i__];
i__2 = *n;
for (j = ii; j <= i__2; ++j) {
if (d__[j] < p) {
k = j;
p = d__[j];
}
/* L30: */
}
if (k != i__) {
d__[k] = d__[i__];
d__[i__] = p;
dswap_(n, &z__[i__ * z_dim1 + 1], &c__1, &z__[k *
z_dim1 + 1], &c__1);
}
/* L40: */
}
}
}
}
L50:
work[1] = (doublereal) lwmin;
iwork[1] = liwmin;
return 0;
/* End of DSTEDC */
} /* dstedc_ */
/* Subroutine */ int dsteqr_(char *compz, integer *n, doublereal *d__,
doublereal *e, doublereal *z__, integer *ldz, doublereal *work,
integer *info)
{
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2;
doublereal d__1, d__2;
/* Local variables */
static doublereal b, c__, f, g;
static integer i__, j, k, l, m;
static doublereal p, r__, s;
static integer l1, ii, mm, lm1, mm1, nm1;
static doublereal rt1, rt2, eps;
static integer lsv;
static doublereal tst, eps2;
static integer lend, jtot;
extern /* Subroutine */ int dlae2_(doublereal *, doublereal *, doublereal
*, doublereal *, doublereal *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dlasr_(char *, char *, char *, integer *,
integer *, doublereal *, doublereal *, doublereal *, integer *);
static doublereal anorm;
extern /* Subroutine */ int dswap_(integer *, doublereal *, integer *,
doublereal *, integer *), dlaev2_(doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *, doublereal *,
doublereal *);
static integer lendm1, lendp1;
static integer iscale;
extern /* Subroutine */ int dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *), dlaset_(char *, integer *, integer
*, doublereal *, doublereal *, doublereal *, integer *);
static doublereal safmin;
extern /* Subroutine */ int dlartg_(doublereal *, doublereal *,
doublereal *, doublereal *, doublereal *);
static doublereal safmax;
extern /* Subroutine */ int xerbla_(char *, integer *);
extern doublereal dlanst_(char *, integer *, doublereal *, doublereal *);
extern /* Subroutine */ int dlasrt_(char *, integer *, doublereal *,
integer *);
static integer lendsv;
static doublereal ssfmin;
static integer nmaxit, icompz;
static doublereal ssfmax;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DSTEQR computes all eigenvalues and, optionally, eigenvectors of a
symmetric tridiagonal matrix using the implicit QL or QR method.
The eigenvectors of a full or band symmetric matrix can also be found
if DSYTRD or DSPTRD or DSBTRD has been used to reduce this matrix to
tridiagonal form.
Arguments
=========
COMPZ (input) CHARACTER*1
= 'N': Compute eigenvalues only.
= 'V': Compute eigenvalues and eigenvectors of the original
symmetric matrix. On entry, Z must contain the
orthogonal matrix used to reduce the original matrix
to tridiagonal form.
= 'I': Compute eigenvalues and eigenvectors of the
tridiagonal matrix. Z is initialized to the identity
matrix.
N (input) INTEGER
The order of the matrix. N >= 0.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, the diagonal elements of the tridiagonal matrix.
On exit, if INFO = 0, the eigenvalues in ascending order.
E (input/output) DOUBLE PRECISION array, dimension (N-1)
On entry, the (n-1) subdiagonal elements of the tridiagonal
matrix.
On exit, E has been destroyed.
Z (input/output) DOUBLE PRECISION array, dimension (LDZ, N)
On entry, if COMPZ = 'V', then Z contains the orthogonal
matrix used in the reduction to tridiagonal form.
On exit, if INFO = 0, then if COMPZ = 'V', Z contains the
orthonormal eigenvectors of the original symmetric matrix,
and if COMPZ = 'I', Z contains the orthonormal eigenvectors
of the symmetric tridiagonal matrix.
If COMPZ = 'N', then Z is not referenced.
LDZ (input) INTEGER
The leading dimension of the array Z. LDZ >= 1, and if
eigenvectors are desired, then LDZ >= max(1,N).
WORK (workspace) DOUBLE PRECISION array, dimension (max(1,2*N-2))
If COMPZ = 'N', then WORK is not referenced.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: the algorithm has failed to find all the eigenvalues in
a total of 30*N iterations; if INFO = i, then i
elements of E have not converged to zero; on exit, D
and E contain the elements of a symmetric tridiagonal
matrix which is orthogonally similar to the original
matrix.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--d__;
--e;
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--work;
/* Function Body */
*info = 0;
if (lsame_(compz, "N")) {
icompz = 0;
} else if (lsame_(compz, "V")) {
icompz = 1;
} else if (lsame_(compz, "I")) {
icompz = 2;
} else {
icompz = -1;
}
if (icompz < 0) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*ldz < 1 || icompz > 0 && *ldz < max(1,*n)) {
*info = -6;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DSTEQR", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*n == 1) {
if (icompz == 2) {
z__[z_dim1 + 1] = 1.;
}
return 0;
}
/* Determine the unit roundoff and over/underflow thresholds. */
eps = EPSILON;
/* Computing 2nd power */
d__1 = eps;
eps2 = d__1 * d__1;
safmin = SAFEMINIMUM;
safmax = 1. / safmin;
ssfmax = sqrt(safmax) / 3.;
ssfmin = sqrt(safmin) / eps2;
/*
Compute the eigenvalues and eigenvectors of the tridiagonal
matrix.
*/
if (icompz == 2) {
dlaset_("Full", n, n, &c_b29, &c_b15, &z__[z_offset], ldz);
}
nmaxit = *n * 30;
jtot = 0;
/*
Determine where the matrix splits and choose QL or QR iteration
for each block, according to whether top or bottom diagonal
element is smaller.
*/
l1 = 1;
nm1 = *n - 1;
L10:
if (l1 > *n) {
goto L160;
}
if (l1 > 1) {
e[l1 - 1] = 0.;
}
if (l1 <= nm1) {
i__1 = nm1;
for (m = l1; m <= i__1; ++m) {
tst = (d__1 = e[m], abs(d__1));
if (tst == 0.) {
goto L30;
}
if (tst <= sqrt((d__1 = d__[m], abs(d__1))) * sqrt((d__2 = d__[m
+ 1], abs(d__2))) * eps) {
e[m] = 0.;
goto L30;
}
/* L20: */
}
}
m = *n;
L30:
l = l1;
lsv = l;
lend = m;
lendsv = lend;
l1 = m + 1;
if (lend == l) {
goto L10;
}
/* Scale submatrix in rows and columns L to LEND */
i__1 = lend - l + 1;
anorm = dlanst_("I", &i__1, &d__[l], &e[l]);
iscale = 0;
if (anorm == 0.) {
goto L10;
}
if (anorm > ssfmax) {
iscale = 1;
i__1 = lend - l + 1;
dlascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &d__[l], n,
info);
i__1 = lend - l;
dlascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &e[l], n,
info);
} else if (anorm < ssfmin) {
iscale = 2;
i__1 = lend - l + 1;
dlascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &d__[l], n,
info);
i__1 = lend - l;
dlascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &e[l], n,
info);
}
/* Choose between QL and QR iteration */
if ((d__1 = d__[lend], abs(d__1)) < (d__2 = d__[l], abs(d__2))) {
lend = lsv;
l = lendsv;
}
if (lend > l) {
/*
QL Iteration
Look for small subdiagonal element.
*/
L40:
if (l != lend) {
lendm1 = lend - 1;
i__1 = lendm1;
for (m = l; m <= i__1; ++m) {
/* Computing 2nd power */
d__2 = (d__1 = e[m], abs(d__1));
tst = d__2 * d__2;
if (tst <= eps2 * (d__1 = d__[m], abs(d__1)) * (d__2 = d__[m
+ 1], abs(d__2)) + safmin) {
goto L60;
}
/* L50: */
}
}
m = lend;
L60:
if (m < lend) {
e[m] = 0.;
}
p = d__[l];
if (m == l) {
goto L80;
}
/*
If remaining matrix is 2-by-2, use DLAE2 or SLAEV2
to compute its eigensystem.
*/
if (m == l + 1) {
if (icompz > 0) {
dlaev2_(&d__[l], &e[l], &d__[l + 1], &rt1, &rt2, &c__, &s);
work[l] = c__;
work[*n - 1 + l] = s;
dlasr_("R", "V", "B", n, &c__2, &work[l], &work[*n - 1 + l], &
z__[l * z_dim1 + 1], ldz);
} else {
dlae2_(&d__[l], &e[l], &d__[l + 1], &rt1, &rt2);
}
d__[l] = rt1;
d__[l + 1] = rt2;
e[l] = 0.;
l += 2;
if (l <= lend) {
goto L40;
}
goto L140;
}
if (jtot == nmaxit) {
goto L140;
}
++jtot;
/* Form shift. */
g = (d__[l + 1] - p) / (e[l] * 2.);
r__ = dlapy2_(&g, &c_b15);
g = d__[m] - p + e[l] / (g + d_sign(&r__, &g));
s = 1.;
c__ = 1.;
p = 0.;
/* Inner loop */
mm1 = m - 1;
i__1 = l;
for (i__ = mm1; i__ >= i__1; --i__) {
f = s * e[i__];
b = c__ * e[i__];
dlartg_(&g, &f, &c__, &s, &r__);
if (i__ != m - 1) {
e[i__ + 1] = r__;
}
g = d__[i__ + 1] - p;
r__ = (d__[i__] - g) * s + c__ * 2. * b;
p = s * r__;
d__[i__ + 1] = g + p;
g = c__ * r__ - b;
/* If eigenvectors are desired, then save rotations. */
if (icompz > 0) {
work[i__] = c__;
work[*n - 1 + i__] = -s;
}
/* L70: */
}
/* If eigenvectors are desired, then apply saved rotations. */
if (icompz > 0) {
mm = m - l + 1;
dlasr_("R", "V", "B", n, &mm, &work[l], &work[*n - 1 + l], &z__[l
* z_dim1 + 1], ldz);
}
d__[l] -= p;
e[l] = g;
goto L40;
/* Eigenvalue found. */
L80:
d__[l] = p;
++l;
if (l <= lend) {
goto L40;
}
goto L140;
} else {
/*
QR Iteration
Look for small superdiagonal element.
*/
L90:
if (l != lend) {
lendp1 = lend + 1;
i__1 = lendp1;
for (m = l; m >= i__1; --m) {
/* Computing 2nd power */
d__2 = (d__1 = e[m - 1], abs(d__1));
tst = d__2 * d__2;
if (tst <= eps2 * (d__1 = d__[m], abs(d__1)) * (d__2 = d__[m
- 1], abs(d__2)) + safmin) {
goto L110;
}
/* L100: */
}
}
m = lend;
L110:
if (m > lend) {
e[m - 1] = 0.;
}
p = d__[l];
if (m == l) {
goto L130;
}
/*
If remaining matrix is 2-by-2, use DLAE2 or SLAEV2
to compute its eigensystem.
*/
if (m == l - 1) {
if (icompz > 0) {
dlaev2_(&d__[l - 1], &e[l - 1], &d__[l], &rt1, &rt2, &c__, &s)
;
work[m] = c__;
work[*n - 1 + m] = s;
dlasr_("R", "V", "F", n, &c__2, &work[m], &work[*n - 1 + m], &
z__[(l - 1) * z_dim1 + 1], ldz);
} else {
dlae2_(&d__[l - 1], &e[l - 1], &d__[l], &rt1, &rt2);
}
d__[l - 1] = rt1;
d__[l] = rt2;
e[l - 1] = 0.;
l += -2;
if (l >= lend) {
goto L90;
}
goto L140;
}
if (jtot == nmaxit) {
goto L140;
}
++jtot;
/* Form shift. */
g = (d__[l - 1] - p) / (e[l - 1] * 2.);
r__ = dlapy2_(&g, &c_b15);
g = d__[m] - p + e[l - 1] / (g + d_sign(&r__, &g));
s = 1.;
c__ = 1.;
p = 0.;
/* Inner loop */
lm1 = l - 1;
i__1 = lm1;
for (i__ = m; i__ <= i__1; ++i__) {
f = s * e[i__];
b = c__ * e[i__];
dlartg_(&g, &f, &c__, &s, &r__);
if (i__ != m) {
e[i__ - 1] = r__;
}
g = d__[i__] - p;
r__ = (d__[i__ + 1] - g) * s + c__ * 2. * b;
p = s * r__;
d__[i__] = g + p;
g = c__ * r__ - b;
/* If eigenvectors are desired, then save rotations. */
if (icompz > 0) {
work[i__] = c__;
work[*n - 1 + i__] = s;
}
/* L120: */
}
/* If eigenvectors are desired, then apply saved rotations. */
if (icompz > 0) {
mm = l - m + 1;
dlasr_("R", "V", "F", n, &mm, &work[m], &work[*n - 1 + m], &z__[m
* z_dim1 + 1], ldz);
}
d__[l] -= p;
e[lm1] = g;
goto L90;
/* Eigenvalue found. */
L130:
d__[l] = p;
--l;
if (l >= lend) {
goto L90;
}
goto L140;
}
/* Undo scaling if necessary */
L140:
if (iscale == 1) {
i__1 = lendsv - lsv + 1;
dlascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &d__[lsv],
n, info);
i__1 = lendsv - lsv;
dlascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &e[lsv], n,
info);
} else if (iscale == 2) {
i__1 = lendsv - lsv + 1;
dlascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &d__[lsv],
n, info);
i__1 = lendsv - lsv;
dlascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &e[lsv], n,
info);
}
/*
Check for no convergence to an eigenvalue after a total
of N*MAXIT iterations.
*/
if (jtot < nmaxit) {
goto L10;
}
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
if (e[i__] != 0.) {
++(*info);
}
/* L150: */
}
goto L190;
/* Order eigenvalues and eigenvectors. */
L160:
if (icompz == 0) {
/* Use Quick Sort */
dlasrt_("I", n, &d__[1], info);
} else {
/* Use Selection Sort to minimize swaps of eigenvectors */
i__1 = *n;
for (ii = 2; ii <= i__1; ++ii) {
i__ = ii - 1;
k = i__;
p = d__[i__];
i__2 = *n;
for (j = ii; j <= i__2; ++j) {
if (d__[j] < p) {
k = j;
p = d__[j];
}
/* L170: */
}
if (k != i__) {
d__[k] = d__[i__];
d__[i__] = p;
dswap_(n, &z__[i__ * z_dim1 + 1], &c__1, &z__[k * z_dim1 + 1],
&c__1);
}
/* L180: */
}
}
L190:
return 0;
/* End of DSTEQR */
} /* dsteqr_ */
/* Subroutine */ int dsterf_(integer *n, doublereal *d__, doublereal *e,
integer *info)
{
/* System generated locals */
integer i__1;
doublereal d__1, d__2, d__3;
/* Local variables */
static doublereal c__;
static integer i__, l, m;
static doublereal p, r__, s;
static integer l1;
static doublereal bb, rt1, rt2, eps, rte;
static integer lsv;
static doublereal eps2, oldc;
static integer lend, jtot;
extern /* Subroutine */ int dlae2_(doublereal *, doublereal *, doublereal
*, doublereal *, doublereal *);
static doublereal gamma, alpha, sigma, anorm;
static integer iscale;
extern /* Subroutine */ int dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *);
static doublereal oldgam, safmin;
extern /* Subroutine */ int xerbla_(char *, integer *);
static doublereal safmax;
extern doublereal dlanst_(char *, integer *, doublereal *, doublereal *);
extern /* Subroutine */ int dlasrt_(char *, integer *, doublereal *,
integer *);
static integer lendsv;
static doublereal ssfmin;
static integer nmaxit;
static doublereal ssfmax;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DSTERF computes all eigenvalues of a symmetric tridiagonal matrix
using the Pal-Walker-Kahan variant of the QL or QR algorithm.
Arguments
=========
N (input) INTEGER
The order of the matrix. N >= 0.
D (input/output) DOUBLE PRECISION array, dimension (N)
On entry, the n diagonal elements of the tridiagonal matrix.
On exit, if INFO = 0, the eigenvalues in ascending order.
E (input/output) DOUBLE PRECISION array, dimension (N-1)
On entry, the (n-1) subdiagonal elements of the tridiagonal
matrix.
On exit, E has been destroyed.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: the algorithm failed to find all of the eigenvalues in
a total of 30*N iterations; if INFO = i, then i
elements of E have not converged to zero.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
--e;
--d__;
/* Function Body */
*info = 0;
/* Quick return if possible */
if (*n < 0) {
*info = -1;
i__1 = -(*info);
xerbla_("DSTERF", &i__1);
return 0;
}
if (*n <= 1) {
return 0;
}
/* Determine the unit roundoff for this environment. */
eps = EPSILON;
/* Computing 2nd power */
d__1 = eps;
eps2 = d__1 * d__1;
safmin = SAFEMINIMUM;
safmax = 1. / safmin;
ssfmax = sqrt(safmax) / 3.;
ssfmin = sqrt(safmin) / eps2;
/* Compute the eigenvalues of the tridiagonal matrix. */
nmaxit = *n * 30;
sigma = 0.;
jtot = 0;
/*
Determine where the matrix splits and choose QL or QR iteration
for each block, according to whether top or bottom diagonal
element is smaller.
*/
l1 = 1;
L10:
if (l1 > *n) {
goto L170;
}
if (l1 > 1) {
e[l1 - 1] = 0.;
}
i__1 = *n - 1;
for (m = l1; m <= i__1; ++m) {
if ((d__3 = e[m], abs(d__3)) <= sqrt((d__1 = d__[m], abs(d__1))) *
sqrt((d__2 = d__[m + 1], abs(d__2))) * eps) {
e[m] = 0.;
goto L30;
}
/* L20: */
}
m = *n;
L30:
l = l1;
lsv = l;
lend = m;
lendsv = lend;
l1 = m + 1;
if (lend == l) {
goto L10;
}
/* Scale submatrix in rows and columns L to LEND */
i__1 = lend - l + 1;
anorm = dlanst_("I", &i__1, &d__[l], &e[l]);
iscale = 0;
if (anorm > ssfmax) {
iscale = 1;
i__1 = lend - l + 1;
dlascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &d__[l], n,
info);
i__1 = lend - l;
dlascl_("G", &c__0, &c__0, &anorm, &ssfmax, &i__1, &c__1, &e[l], n,
info);
} else if (anorm < ssfmin) {
iscale = 2;
i__1 = lend - l + 1;
dlascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &d__[l], n,
info);
i__1 = lend - l;
dlascl_("G", &c__0, &c__0, &anorm, &ssfmin, &i__1, &c__1, &e[l], n,
info);
}
i__1 = lend - 1;
for (i__ = l; i__ <= i__1; ++i__) {
/* Computing 2nd power */
d__1 = e[i__];
e[i__] = d__1 * d__1;
/* L40: */
}
/* Choose between QL and QR iteration */
if ((d__1 = d__[lend], abs(d__1)) < (d__2 = d__[l], abs(d__2))) {
lend = lsv;
l = lendsv;
}
if (lend >= l) {
/*
QL Iteration
Look for small subdiagonal element.
*/
L50:
if (l != lend) {
i__1 = lend - 1;
for (m = l; m <= i__1; ++m) {
if ((d__2 = e[m], abs(d__2)) <= eps2 * (d__1 = d__[m] * d__[m
+ 1], abs(d__1))) {
goto L70;
}
/* L60: */
}
}
m = lend;
L70:
if (m < lend) {
e[m] = 0.;
}
p = d__[l];
if (m == l) {
goto L90;
}
/*
If remaining matrix is 2 by 2, use DLAE2 to compute its
eigenvalues.
*/
if (m == l + 1) {
rte = sqrt(e[l]);
dlae2_(&d__[l], &rte, &d__[l + 1], &rt1, &rt2);
d__[l] = rt1;
d__[l + 1] = rt2;
e[l] = 0.;
l += 2;
if (l <= lend) {
goto L50;
}
goto L150;
}
if (jtot == nmaxit) {
goto L150;
}
++jtot;
/* Form shift. */
rte = sqrt(e[l]);
sigma = (d__[l + 1] - p) / (rte * 2.);
r__ = dlapy2_(&sigma, &c_b15);
sigma = p - rte / (sigma + d_sign(&r__, &sigma));
c__ = 1.;
s = 0.;
gamma = d__[m] - sigma;
p = gamma * gamma;
/* Inner loop */
i__1 = l;
for (i__ = m - 1; i__ >= i__1; --i__) {
bb = e[i__];
r__ = p + bb;
if (i__ != m - 1) {
e[i__ + 1] = s * r__;
}
oldc = c__;
c__ = p / r__;
s = bb / r__;
oldgam = gamma;
alpha = d__[i__];
gamma = c__ * (alpha - sigma) - s * oldgam;
d__[i__ + 1] = oldgam + (alpha - gamma);
if (c__ != 0.) {
p = gamma * gamma / c__;
} else {
p = oldc * bb;
}
/* L80: */
}
e[l] = s * p;
d__[l] = sigma + gamma;
goto L50;
/* Eigenvalue found. */
L90:
d__[l] = p;
++l;
if (l <= lend) {
goto L50;
}
goto L150;
} else {
/*
QR Iteration
Look for small superdiagonal element.
*/
L100:
i__1 = lend + 1;
for (m = l; m >= i__1; --m) {
if ((d__2 = e[m - 1], abs(d__2)) <= eps2 * (d__1 = d__[m] * d__[m
- 1], abs(d__1))) {
goto L120;
}
/* L110: */
}
m = lend;
L120:
if (m > lend) {
e[m - 1] = 0.;
}
p = d__[l];
if (m == l) {
goto L140;
}
/*
If remaining matrix is 2 by 2, use DLAE2 to compute its
eigenvalues.
*/
if (m == l - 1) {
rte = sqrt(e[l - 1]);
dlae2_(&d__[l], &rte, &d__[l - 1], &rt1, &rt2);
d__[l] = rt1;
d__[l - 1] = rt2;
e[l - 1] = 0.;
l += -2;
if (l >= lend) {
goto L100;
}
goto L150;
}
if (jtot == nmaxit) {
goto L150;
}
++jtot;
/* Form shift. */
rte = sqrt(e[l - 1]);
sigma = (d__[l - 1] - p) / (rte * 2.);
r__ = dlapy2_(&sigma, &c_b15);
sigma = p - rte / (sigma + d_sign(&r__, &sigma));
c__ = 1.;
s = 0.;
gamma = d__[m] - sigma;
p = gamma * gamma;
/* Inner loop */
i__1 = l - 1;
for (i__ = m; i__ <= i__1; ++i__) {
bb = e[i__];
r__ = p + bb;
if (i__ != m) {
e[i__ - 1] = s * r__;
}
oldc = c__;
c__ = p / r__;
s = bb / r__;
oldgam = gamma;
alpha = d__[i__ + 1];
gamma = c__ * (alpha - sigma) - s * oldgam;
d__[i__] = oldgam + (alpha - gamma);
if (c__ != 0.) {
p = gamma * gamma / c__;
} else {
p = oldc * bb;
}
/* L130: */
}
e[l - 1] = s * p;
d__[l] = sigma + gamma;
goto L100;
/* Eigenvalue found. */
L140:
d__[l] = p;
--l;
if (l >= lend) {
goto L100;
}
goto L150;
}
/* Undo scaling if necessary */
L150:
if (iscale == 1) {
i__1 = lendsv - lsv + 1;
dlascl_("G", &c__0, &c__0, &ssfmax, &anorm, &i__1, &c__1, &d__[lsv],
n, info);
}
if (iscale == 2) {
i__1 = lendsv - lsv + 1;
dlascl_("G", &c__0, &c__0, &ssfmin, &anorm, &i__1, &c__1, &d__[lsv],
n, info);
}
/*
Check for no convergence to an eigenvalue after a total
of N*MAXIT iterations.
*/
if (jtot < nmaxit) {
goto L10;
}
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
if (e[i__] != 0.) {
++(*info);
}
/* L160: */
}
goto L180;
/* Sort eigenvalues in increasing order. */
L170:
dlasrt_("I", n, &d__[1], info);
L180:
return 0;
/* End of DSTERF */
} /* dsterf_ */
/* Subroutine */ int dsyevd_(char *jobz, char *uplo, integer *n, doublereal *
a, integer *lda, doublereal *w, doublereal *work, integer *lwork,
integer *iwork, integer *liwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
doublereal d__1;
/* Local variables */
static doublereal eps;
static integer inde;
static doublereal anrm, rmin, rmax;
static integer lopt;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
static doublereal sigma;
extern logical lsame_(char *, char *);
static integer iinfo, lwmin, liopt;
static logical lower, wantz;
static integer indwk2, llwrk2;
static integer iscale;
extern /* Subroutine */ int dlascl_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, integer *, doublereal *,
integer *, integer *), dstedc_(char *, integer *,
doublereal *, doublereal *, doublereal *, integer *, doublereal *,
integer *, integer *, integer *, integer *), dlacpy_(
char *, integer *, integer *, doublereal *, integer *, doublereal
*, integer *);
static doublereal safmin;
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int xerbla_(char *, integer *);
static doublereal bignum;
static integer indtau;
extern /* Subroutine */ int dsterf_(integer *, doublereal *, doublereal *,
integer *);
extern doublereal dlansy_(char *, char *, integer *, doublereal *,
integer *, doublereal *);
static integer indwrk, liwmin;
extern /* Subroutine */ int dormtr_(char *, char *, char *, integer *,
integer *, doublereal *, integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *, integer *), dsytrd_(char *, integer *, doublereal *, integer *,
doublereal *, doublereal *, doublereal *, doublereal *, integer *,
integer *);
static integer llwork;
static doublereal smlnum;
static logical lquery;
/*
-- LAPACK driver routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DSYEVD computes all eigenvalues and, optionally, eigenvectors of a
real symmetric matrix A. If eigenvectors are desired, it uses a
divide and conquer algorithm.
The divide and conquer algorithm makes very mild assumptions about
floating point arithmetic. It will work on machines with a guard
digit in add/subtract, or on those binary machines without guard
digits which subtract like the Cray X-MP, Cray Y-MP, Cray C-90, or
Cray-2. It could conceivably fail on hexadecimal or decimal machines
without guard digits, but we know of none.
Because of large use of BLAS of level 3, DSYEVD needs N**2 more
workspace than DSYEVX.
Arguments
=========
JOBZ (input) CHARACTER*1
= 'N': Compute eigenvalues only;
= 'V': Compute eigenvalues and eigenvectors.
UPLO (input) CHARACTER*1
= 'U': Upper triangle of A is stored;
= 'L': Lower triangle of A is stored.
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA, N)
On entry, the symmetric matrix A. If UPLO = 'U', the
leading N-by-N upper triangular part of A contains the
upper triangular part of the matrix A. If UPLO = 'L',
the leading N-by-N lower triangular part of A contains
the lower triangular part of the matrix A.
On exit, if JOBZ = 'V', then if INFO = 0, A contains the
orthonormal eigenvectors of the matrix A.
If JOBZ = 'N', then on exit the lower triangle (if UPLO='L')
or the upper triangle (if UPLO='U') of A, including the
diagonal, is destroyed.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
W (output) DOUBLE PRECISION array, dimension (N)
If INFO = 0, the eigenvalues in ascending order.
WORK (workspace/output) DOUBLE PRECISION array,
dimension (LWORK)
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If N <= 1, LWORK must be at least 1.
If JOBZ = 'N' and N > 1, LWORK must be at least 2*N+1.
If JOBZ = 'V' and N > 1, LWORK must be at least
1 + 6*N + 2*N**2.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal sizes of the WORK and IWORK
arrays, returns these values as the first entries of the WORK
and IWORK arrays, and no error message related to LWORK or
LIWORK is issued by XERBLA.
IWORK (workspace/output) INTEGER array, dimension (MAX(1,LIWORK))
On exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.
LIWORK (input) INTEGER
The dimension of the array IWORK.
If N <= 1, LIWORK must be at least 1.
If JOBZ = 'N' and N > 1, LIWORK must be at least 1.
If JOBZ = 'V' and N > 1, LIWORK must be at least 3 + 5*N.
If LIWORK = -1, then a workspace query is assumed; the
routine only calculates the optimal sizes of the WORK and
IWORK arrays, returns these values as the first entries of
the WORK and IWORK arrays, and no error message related to
LWORK or LIWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i and JOBZ = 'N', then the algorithm failed
to converge; i off-diagonal elements of an intermediate
tridiagonal form did not converge to zero;
if INFO = i and JOBZ = 'V', then the algorithm failed
to compute an eigenvalue while working on the submatrix
lying in rows and columns INFO/(N+1) through
mod(INFO,N+1).
Further Details
===============
Based on contributions by
Jeff Rutter, Computer Science Division, University of California
at Berkeley, USA
Modified by Francoise Tisseur, University of Tennessee.
Modified description of INFO. Sven, 16 Feb 05.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--w;
--work;
--iwork;
/* Function Body */
wantz = lsame_(jobz, "V");
lower = lsame_(uplo, "L");
lquery = *lwork == -1 || *liwork == -1;
*info = 0;
if (! (wantz || lsame_(jobz, "N"))) {
*info = -1;
} else if (! (lower || lsame_(uplo, "U"))) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
}
if (*info == 0) {
if (*n <= 1) {
liwmin = 1;
lwmin = 1;
lopt = lwmin;
liopt = liwmin;
} else {
if (wantz) {
liwmin = *n * 5 + 3;
/* Computing 2nd power */
i__1 = *n;
lwmin = *n * 6 + 1 + (i__1 * i__1 << 1);
} else {
liwmin = 1;
lwmin = (*n << 1) + 1;
}
/* Computing MAX */
i__1 = lwmin, i__2 = (*n << 1) + ilaenv_(&c__1, "DSYTRD", uplo, n,
&c_n1, &c_n1, &c_n1, (ftnlen)6, (ftnlen)1);
lopt = max(i__1,i__2);
liopt = liwmin;
}
work[1] = (doublereal) lopt;
iwork[1] = liopt;
if (*lwork < lwmin && ! lquery) {
*info = -8;
} else if (*liwork < liwmin && ! lquery) {
*info = -10;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DSYEVD", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
if (*n == 1) {
w[1] = a[a_dim1 + 1];
if (wantz) {
a[a_dim1 + 1] = 1.;
}
return 0;
}
/* Get machine constants. */
safmin = SAFEMINIMUM;
eps = PRECISION;
smlnum = safmin / eps;
bignum = 1. / smlnum;
rmin = sqrt(smlnum);
rmax = sqrt(bignum);
/* Scale matrix to allowable range, if necessary. */
anrm = dlansy_("M", uplo, n, &a[a_offset], lda, &work[1]);
iscale = 0;
if (anrm > 0. && anrm < rmin) {
iscale = 1;
sigma = rmin / anrm;
} else if (anrm > rmax) {
iscale = 1;
sigma = rmax / anrm;
}
if (iscale == 1) {
dlascl_(uplo, &c__0, &c__0, &c_b15, &sigma, n, n, &a[a_offset], lda,
info);
}
/* Call DSYTRD to reduce symmetric matrix to tridiagonal form. */
inde = 1;
indtau = inde + *n;
indwrk = indtau + *n;
llwork = *lwork - indwrk + 1;
indwk2 = indwrk + *n * *n;
llwrk2 = *lwork - indwk2 + 1;
dsytrd_(uplo, n, &a[a_offset], lda, &w[1], &work[inde], &work[indtau], &
work[indwrk], &llwork, &iinfo);
lopt = (integer) ((*n << 1) + work[indwrk]);
/*
For eigenvalues only, call DSTERF. For eigenvectors, first call
DSTEDC to generate the eigenvector matrix, WORK(INDWRK), of the
tridiagonal matrix, then call DORMTR to multiply it by the
Householder transformations stored in A.
*/
if (! wantz) {
dsterf_(n, &w[1], &work[inde], info);
} else {
dstedc_("I", n, &w[1], &work[inde], &work[indwrk], n, &work[indwk2], &
llwrk2, &iwork[1], liwork, info);
dormtr_("L", uplo, "N", n, n, &a[a_offset], lda, &work[indtau], &work[
indwrk], n, &work[indwk2], &llwrk2, &iinfo);
dlacpy_("A", n, n, &work[indwrk], n, &a[a_offset], lda);
/*
Computing MAX
Computing 2nd power
*/
i__3 = *n;
i__1 = lopt, i__2 = *n * 6 + 1 + (i__3 * i__3 << 1);
lopt = max(i__1,i__2);
}
/* If matrix was scaled, then rescale eigenvalues appropriately. */
if (iscale == 1) {
d__1 = 1. / sigma;
dscal_(n, &d__1, &w[1], &c__1);
}
work[1] = (doublereal) lopt;
iwork[1] = liopt;
return 0;
/* End of DSYEVD */
} /* dsyevd_ */
/* Subroutine */ int dsytd2_(char *uplo, integer *n, doublereal *a, integer *
lda, doublereal *d__, doublereal *e, doublereal *tau, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__;
extern doublereal ddot_(integer *, doublereal *, integer *, doublereal *,
integer *);
static doublereal taui;
extern /* Subroutine */ int dsyr2_(char *, integer *, doublereal *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
integer *);
static doublereal alpha;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int daxpy_(integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *);
static logical upper;
extern /* Subroutine */ int dsymv_(char *, integer *, doublereal *,
doublereal *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *), dlarfg_(integer *, doublereal *,
doublereal *, integer *, doublereal *), xerbla_(char *, integer *
);
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DSYTD2 reduces a real symmetric matrix A to symmetric tridiagonal
form T by an orthogonal similarity transformation: Q' * A * Q = T.
Arguments
=========
UPLO (input) CHARACTER*1
Specifies whether the upper or lower triangular part of the
symmetric matrix A is stored:
= 'U': Upper triangular
= 'L': Lower triangular
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the symmetric matrix A. If UPLO = 'U', the leading
n-by-n upper triangular part of A contains the upper
triangular part of the matrix A, and the strictly lower
triangular part of A is not referenced. If UPLO = 'L', the
leading n-by-n lower triangular part of A contains the lower
triangular part of the matrix A, and the strictly upper
triangular part of A is not referenced.
On exit, if UPLO = 'U', the diagonal and first superdiagonal
of A are overwritten by the corresponding elements of the
tridiagonal matrix T, and the elements above the first
superdiagonal, with the array TAU, represent the orthogonal
matrix Q as a product of elementary reflectors; if UPLO
= 'L', the diagonal and first subdiagonal of A are over-
written by the corresponding elements of the tridiagonal
matrix T, and the elements below the first subdiagonal, with
the array TAU, represent the orthogonal matrix Q as a product
of elementary reflectors. See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
D (output) DOUBLE PRECISION array, dimension (N)
The diagonal elements of the tridiagonal matrix T:
D(i) = A(i,i).
E (output) DOUBLE PRECISION array, dimension (N-1)
The off-diagonal elements of the tridiagonal matrix T:
E(i) = A(i,i+1) if UPLO = 'U', E(i) = A(i+1,i) if UPLO = 'L'.
TAU (output) DOUBLE PRECISION array, dimension (N-1)
The scalar factors of the elementary reflectors (see Further
Details).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
Further Details
===============
If UPLO = 'U', the matrix Q is represented as a product of elementary
reflectors
Q = H(n-1) . . . H(2) H(1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(i+1:n) = 0 and v(i) = 1; v(1:i-1) is stored on exit in
A(1:i-1,i+1), and tau in TAU(i).
If UPLO = 'L', the matrix Q is represented as a product of elementary
reflectors
Q = H(1) H(2) . . . H(n-1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i) = 0 and v(i+1) = 1; v(i+2:n) is stored on exit in A(i+2:n,i),
and tau in TAU(i).
The contents of A on exit are illustrated by the following examples
with n = 5:
if UPLO = 'U': if UPLO = 'L':
( d e v2 v3 v4 ) ( d )
( d e v3 v4 ) ( e d )
( d e v4 ) ( v1 e d )
( d e ) ( v1 v2 e d )
( d ) ( v1 v2 v3 e d )
where d and e denote diagonal and off-diagonal elements of T, and vi
denotes an element of the vector defining H(i).
=====================================================================
Test the input parameters
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--d__;
--e;
--tau;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DSYTD2", &i__1);
return 0;
}
/* Quick return if possible */
if (*n <= 0) {
return 0;
}
if (upper) {
/* Reduce the upper triangle of A */
for (i__ = *n - 1; i__ >= 1; --i__) {
/*
Generate elementary reflector H(i) = I - tau * v * v'
to annihilate A(1:i-1,i+1)
*/
dlarfg_(&i__, &a[i__ + (i__ + 1) * a_dim1], &a[(i__ + 1) * a_dim1
+ 1], &c__1, &taui);
e[i__] = a[i__ + (i__ + 1) * a_dim1];
if (taui != 0.) {
/* Apply H(i) from both sides to A(1:i,1:i) */
a[i__ + (i__ + 1) * a_dim1] = 1.;
/* Compute x := tau * A * v storing x in TAU(1:i) */
dsymv_(uplo, &i__, &taui, &a[a_offset], lda, &a[(i__ + 1) *
a_dim1 + 1], &c__1, &c_b29, &tau[1], &c__1)
;
/* Compute w := x - 1/2 * tau * (x'*v) * v */
alpha = taui * -.5 * ddot_(&i__, &tau[1], &c__1, &a[(i__ + 1)
* a_dim1 + 1], &c__1);
daxpy_(&i__, &alpha, &a[(i__ + 1) * a_dim1 + 1], &c__1, &tau[
1], &c__1);
/*
Apply the transformation as a rank-2 update:
A := A - v * w' - w * v'
*/
dsyr2_(uplo, &i__, &c_b151, &a[(i__ + 1) * a_dim1 + 1], &c__1,
&tau[1], &c__1, &a[a_offset], lda);
a[i__ + (i__ + 1) * a_dim1] = e[i__];
}
d__[i__ + 1] = a[i__ + 1 + (i__ + 1) * a_dim1];
tau[i__] = taui;
/* L10: */
}
d__[1] = a[a_dim1 + 1];
} else {
/* Reduce the lower triangle of A */
i__1 = *n - 1;
for (i__ = 1; i__ <= i__1; ++i__) {
/*
Generate elementary reflector H(i) = I - tau * v * v'
to annihilate A(i+2:n,i)
*/
i__2 = *n - i__;
/* Computing MIN */
i__3 = i__ + 2;
dlarfg_(&i__2, &a[i__ + 1 + i__ * a_dim1], &a[min(i__3,*n) + i__ *
a_dim1], &c__1, &taui);
e[i__] = a[i__ + 1 + i__ * a_dim1];
if (taui != 0.) {
/* Apply H(i) from both sides to A(i+1:n,i+1:n) */
a[i__ + 1 + i__ * a_dim1] = 1.;
/* Compute x := tau * A * v storing y in TAU(i:n-1) */
i__2 = *n - i__;
dsymv_(uplo, &i__2, &taui, &a[i__ + 1 + (i__ + 1) * a_dim1],
lda, &a[i__ + 1 + i__ * a_dim1], &c__1, &c_b29, &tau[
i__], &c__1);
/* Compute w := x - 1/2 * tau * (x'*v) * v */
i__2 = *n - i__;
alpha = taui * -.5 * ddot_(&i__2, &tau[i__], &c__1, &a[i__ +
1 + i__ * a_dim1], &c__1);
i__2 = *n - i__;
daxpy_(&i__2, &alpha, &a[i__ + 1 + i__ * a_dim1], &c__1, &tau[
i__], &c__1);
/*
Apply the transformation as a rank-2 update:
A := A - v * w' - w * v'
*/
i__2 = *n - i__;
dsyr2_(uplo, &i__2, &c_b151, &a[i__ + 1 + i__ * a_dim1], &
c__1, &tau[i__], &c__1, &a[i__ + 1 + (i__ + 1) *
a_dim1], lda);
a[i__ + 1 + i__ * a_dim1] = e[i__];
}
d__[i__] = a[i__ + i__ * a_dim1];
tau[i__] = taui;
/* L20: */
}
d__[*n] = a[*n + *n * a_dim1];
}
return 0;
/* End of DSYTD2 */
} /* dsytd2_ */
/* Subroutine */ int dsytrd_(char *uplo, integer *n, doublereal *a, integer *
lda, doublereal *d__, doublereal *e, doublereal *tau, doublereal *
work, integer *lwork, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2, i__3;
/* Local variables */
static integer i__, j, nb, kk, nx, iws;
extern logical lsame_(char *, char *);
static integer nbmin, iinfo;
static logical upper;
extern /* Subroutine */ int dsytd2_(char *, integer *, doublereal *,
integer *, doublereal *, doublereal *, doublereal *, integer *), dsyr2k_(char *, char *, integer *, integer *, doublereal
*, doublereal *, integer *, doublereal *, integer *, doublereal *,
doublereal *, integer *), dlatrd_(char *,
integer *, integer *, doublereal *, integer *, doublereal *,
doublereal *, doublereal *, integer *), xerbla_(char *,
integer *);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static integer ldwork, lwkopt;
static logical lquery;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DSYTRD reduces a real symmetric matrix A to real symmetric
tridiagonal form T by an orthogonal similarity transformation:
Q**T * A * Q = T.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': Upper triangle of A is stored;
= 'L': Lower triangle of A is stored.
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the symmetric matrix A. If UPLO = 'U', the leading
N-by-N upper triangular part of A contains the upper
triangular part of the matrix A, and the strictly lower
triangular part of A is not referenced. If UPLO = 'L', the
leading N-by-N lower triangular part of A contains the lower
triangular part of the matrix A, and the strictly upper
triangular part of A is not referenced.
On exit, if UPLO = 'U', the diagonal and first superdiagonal
of A are overwritten by the corresponding elements of the
tridiagonal matrix T, and the elements above the first
superdiagonal, with the array TAU, represent the orthogonal
matrix Q as a product of elementary reflectors; if UPLO
= 'L', the diagonal and first subdiagonal of A are over-
written by the corresponding elements of the tridiagonal
matrix T, and the elements below the first subdiagonal, with
the array TAU, represent the orthogonal matrix Q as a product
of elementary reflectors. See Further Details.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
D (output) DOUBLE PRECISION array, dimension (N)
The diagonal elements of the tridiagonal matrix T:
D(i) = A(i,i).
E (output) DOUBLE PRECISION array, dimension (N-1)
The off-diagonal elements of the tridiagonal matrix T:
E(i) = A(i,i+1) if UPLO = 'U', E(i) = A(i+1,i) if UPLO = 'L'.
TAU (output) DOUBLE PRECISION array, dimension (N-1)
The scalar factors of the elementary reflectors (see Further
Details).
WORK (workspace/output) DOUBLE PRECISION array, dimension (MAX(1,LWORK))
On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK. LWORK >= 1.
For optimum performance LWORK >= N*NB, where NB is the
optimal blocksize.
If LWORK = -1, then a workspace query is assumed; the routine
only calculates the optimal size of the WORK array, returns
this value as the first entry of the WORK array, and no error
message related to LWORK is issued by XERBLA.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
Further Details
===============
If UPLO = 'U', the matrix Q is represented as a product of elementary
reflectors
Q = H(n-1) . . . H(2) H(1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(i+1:n) = 0 and v(i) = 1; v(1:i-1) is stored on exit in
A(1:i-1,i+1), and tau in TAU(i).
If UPLO = 'L', the matrix Q is represented as a product of elementary
reflectors
Q = H(1) H(2) . . . H(n-1).
Each H(i) has the form
H(i) = I - tau * v * v'
where tau is a real scalar, and v is a real vector with
v(1:i) = 0 and v(i+1) = 1; v(i+2:n) is stored on exit in A(i+2:n,i),
and tau in TAU(i).
The contents of A on exit are illustrated by the following examples
with n = 5:
if UPLO = 'U': if UPLO = 'L':
( d e v2 v3 v4 ) ( d )
( d e v3 v4 ) ( e d )
( d e v4 ) ( v1 e d )
( d e ) ( v1 v2 e d )
( d ) ( v1 v2 v3 e d )
where d and e denote diagonal and off-diagonal elements of T, and vi
denotes an element of the vector defining H(i).
=====================================================================
Test the input parameters
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
--d__;
--e;
--tau;
--work;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
lquery = *lwork == -1;
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*lda < max(1,*n)) {
*info = -4;
} else if (*lwork < 1 && ! lquery) {
*info = -9;
}
if (*info == 0) {
/* Determine the block size. */
nb = ilaenv_(&c__1, "DSYTRD", uplo, n, &c_n1, &c_n1, &c_n1, (ftnlen)6,
(ftnlen)1);
lwkopt = *n * nb;
work[1] = (doublereal) lwkopt;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DSYTRD", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*n == 0) {
work[1] = 1.;
return 0;
}
nx = *n;
iws = 1;
if (nb > 1 && nb < *n) {
/*
Determine when to cross over from blocked to unblocked code
(last block is always handled by unblocked code).
Computing MAX
*/
i__1 = nb, i__2 = ilaenv_(&c__3, "DSYTRD", uplo, n, &c_n1, &c_n1, &
c_n1, (ftnlen)6, (ftnlen)1);
nx = max(i__1,i__2);
if (nx < *n) {
/* Determine if workspace is large enough for blocked code. */
ldwork = *n;
iws = ldwork * nb;
if (*lwork < iws) {
/*
Not enough workspace to use optimal NB: determine the
minimum value of NB, and reduce NB or force use of
unblocked code by setting NX = N.
Computing MAX
*/
i__1 = *lwork / ldwork;
nb = max(i__1,1);
nbmin = ilaenv_(&c__2, "DSYTRD", uplo, n, &c_n1, &c_n1, &c_n1,
(ftnlen)6, (ftnlen)1);
if (nb < nbmin) {
nx = *n;
}
}
} else {
nx = *n;
}
} else {
nb = 1;
}
if (upper) {
/*
Reduce the upper triangle of A.
Columns 1:kk are handled by the unblocked method.
*/
kk = *n - (*n - nx + nb - 1) / nb * nb;
i__1 = kk + 1;
i__2 = -nb;
for (i__ = *n - nb + 1; i__2 < 0 ? i__ >= i__1 : i__ <= i__1; i__ +=
i__2) {
/*
Reduce columns i:i+nb-1 to tridiagonal form and form the
matrix W which is needed to update the unreduced part of
the matrix
*/
i__3 = i__ + nb - 1;
dlatrd_(uplo, &i__3, &nb, &a[a_offset], lda, &e[1], &tau[1], &
work[1], &ldwork);
/*
Update the unreduced submatrix A(1:i-1,1:i-1), using an
update of the form: A := A - V*W' - W*V'
*/
i__3 = i__ - 1;
dsyr2k_(uplo, "No transpose", &i__3, &nb, &c_b151, &a[i__ *
a_dim1 + 1], lda, &work[1], &ldwork, &c_b15, &a[a_offset],
lda);
/*
Copy superdiagonal elements back into A, and diagonal
elements into D
*/
i__3 = i__ + nb - 1;
for (j = i__; j <= i__3; ++j) {
a[j - 1 + j * a_dim1] = e[j - 1];
d__[j] = a[j + j * a_dim1];
/* L10: */
}
/* L20: */
}
/* Use unblocked code to reduce the last or only block */
dsytd2_(uplo, &kk, &a[a_offset], lda, &d__[1], &e[1], &tau[1], &iinfo);
} else {
/* Reduce the lower triangle of A */
i__2 = *n - nx;
i__1 = nb;
for (i__ = 1; i__1 < 0 ? i__ >= i__2 : i__ <= i__2; i__ += i__1) {
/*
Reduce columns i:i+nb-1 to tridiagonal form and form the
matrix W which is needed to update the unreduced part of
the matrix
*/
i__3 = *n - i__ + 1;
dlatrd_(uplo, &i__3, &nb, &a[i__ + i__ * a_dim1], lda, &e[i__], &
tau[i__], &work[1], &ldwork);
/*
Update the unreduced submatrix A(i+ib:n,i+ib:n), using
an update of the form: A := A - V*W' - W*V'
*/
i__3 = *n - i__ - nb + 1;
dsyr2k_(uplo, "No transpose", &i__3, &nb, &c_b151, &a[i__ + nb +
i__ * a_dim1], lda, &work[nb + 1], &ldwork, &c_b15, &a[
i__ + nb + (i__ + nb) * a_dim1], lda);
/*
Copy subdiagonal elements back into A, and diagonal
elements into D
*/
i__3 = i__ + nb - 1;
for (j = i__; j <= i__3; ++j) {
a[j + 1 + j * a_dim1] = e[j];
d__[j] = a[j + j * a_dim1];
/* L30: */
}
/* L40: */
}
/* Use unblocked code to reduce the last or only block */
i__1 = *n - i__ + 1;
dsytd2_(uplo, &i__1, &a[i__ + i__ * a_dim1], lda, &d__[i__], &e[i__],
&tau[i__], &iinfo);
}
work[1] = (doublereal) lwkopt;
return 0;
/* End of DSYTRD */
} /* dsytrd_ */
/* Subroutine */ int dtrevc_(char *side, char *howmny, logical *select,
integer *n, doublereal *t, integer *ldt, doublereal *vl, integer *
ldvl, doublereal *vr, integer *ldvr, integer *mm, integer *m,
doublereal *work, integer *info)
{
/* System generated locals */
integer t_dim1, t_offset, vl_dim1, vl_offset, vr_dim1, vr_offset, i__1,
i__2, i__3;
doublereal d__1, d__2, d__3, d__4;
/* Local variables */
static integer i__, j, k;
static doublereal x[4] /* was [2][2] */;
static integer j1, j2, n2, ii, ki, ip, is;
static doublereal wi, wr, rec, ulp, beta, emax;
static logical pair;
extern doublereal ddot_(integer *, doublereal *, integer *, doublereal *,
integer *);
static logical allv;
static integer ierr;
static doublereal unfl, ovfl, smin;
static logical over;
static doublereal vmax;
static integer jnxt;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
static doublereal scale;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dgemv_(char *, integer *, integer *,
doublereal *, doublereal *, integer *, doublereal *, integer *,
doublereal *, doublereal *, integer *);
static doublereal remax;
extern /* Subroutine */ int dcopy_(integer *, doublereal *, integer *,
doublereal *, integer *);
static logical leftv, bothv;
extern /* Subroutine */ int daxpy_(integer *, doublereal *, doublereal *,
integer *, doublereal *, integer *);
static doublereal vcrit;
static logical somev;
static doublereal xnorm;
extern /* Subroutine */ int dlaln2_(logical *, integer *, integer *,
doublereal *, doublereal *, doublereal *, integer *, doublereal *,
doublereal *, doublereal *, integer *, doublereal *, doublereal *
, doublereal *, integer *, doublereal *, doublereal *, integer *),
dlabad_(doublereal *, doublereal *);
extern integer idamax_(integer *, doublereal *, integer *);
extern /* Subroutine */ int xerbla_(char *, integer *);
static doublereal bignum;
static logical rightv;
static doublereal smlnum;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DTREVC computes some or all of the right and/or left eigenvectors of
a real upper quasi-triangular matrix T.
Matrices of this type are produced by the Schur factorization of
a real general matrix: A = Q*T*Q**T, as computed by DHSEQR.
The right eigenvector x and the left eigenvector y of T corresponding
to an eigenvalue w are defined by:
T*x = w*x, (y**H)*T = w*(y**H)
where y**H denotes the conjugate transpose of y.
The eigenvalues are not input to this routine, but are read directly
from the diagonal blocks of T.
This routine returns the matrices X and/or Y of right and left
eigenvectors of T, or the products Q*X and/or Q*Y, where Q is an
input matrix. If Q is the orthogonal factor that reduces a matrix
A to Schur form T, then Q*X and Q*Y are the matrices of right and
left eigenvectors of A.
Arguments
=========
SIDE (input) CHARACTER*1
= 'R': compute right eigenvectors only;
= 'L': compute left eigenvectors only;
= 'B': compute both right and left eigenvectors.
HOWMNY (input) CHARACTER*1
= 'A': compute all right and/or left eigenvectors;
= 'B': compute all right and/or left eigenvectors,
backtransformed by the matrices in VR and/or VL;
= 'S': compute selected right and/or left eigenvectors,
as indicated by the logical array SELECT.
SELECT (input/output) LOGICAL array, dimension (N)
If HOWMNY = 'S', SELECT specifies the eigenvectors to be
computed.
If w(j) is a real eigenvalue, the corresponding real
eigenvector is computed if SELECT(j) is .TRUE..
If w(j) and w(j+1) are the real and imaginary parts of a
complex eigenvalue, the corresponding complex eigenvector is
computed if either SELECT(j) or SELECT(j+1) is .TRUE., and
on exit SELECT(j) is set to .TRUE. and SELECT(j+1) is set to
.FALSE..
Not referenced if HOWMNY = 'A' or 'B'.
N (input) INTEGER
The order of the matrix T. N >= 0.
T (input) DOUBLE PRECISION array, dimension (LDT,N)
The upper quasi-triangular matrix T in Schur canonical form.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= max(1,N).
VL (input/output) DOUBLE PRECISION array, dimension (LDVL,MM)
On entry, if SIDE = 'L' or 'B' and HOWMNY = 'B', VL must
contain an N-by-N matrix Q (usually the orthogonal matrix Q
of Schur vectors returned by DHSEQR).
On exit, if SIDE = 'L' or 'B', VL contains:
if HOWMNY = 'A', the matrix Y of left eigenvectors of T;
if HOWMNY = 'B', the matrix Q*Y;
if HOWMNY = 'S', the left eigenvectors of T specified by
SELECT, stored consecutively in the columns
of VL, in the same order as their
eigenvalues.
A complex eigenvector corresponding to a complex eigenvalue
is stored in two consecutive columns, the first holding the
real part, and the second the imaginary part.
Not referenced if SIDE = 'R'.
LDVL (input) INTEGER
The leading dimension of the array VL. LDVL >= 1, and if
SIDE = 'L' or 'B', LDVL >= N.
VR (input/output) DOUBLE PRECISION array, dimension (LDVR,MM)
On entry, if SIDE = 'R' or 'B' and HOWMNY = 'B', VR must
contain an N-by-N matrix Q (usually the orthogonal matrix Q
of Schur vectors returned by DHSEQR).
On exit, if SIDE = 'R' or 'B', VR contains:
if HOWMNY = 'A', the matrix X of right eigenvectors of T;
if HOWMNY = 'B', the matrix Q*X;
if HOWMNY = 'S', the right eigenvectors of T specified by
SELECT, stored consecutively in the columns
of VR, in the same order as their
eigenvalues.
A complex eigenvector corresponding to a complex eigenvalue
is stored in two consecutive columns, the first holding the
real part and the second the imaginary part.
Not referenced if SIDE = 'L'.
LDVR (input) INTEGER
The leading dimension of the array VR. LDVR >= 1, and if
SIDE = 'R' or 'B', LDVR >= N.
MM (input) INTEGER
The number of columns in the arrays VL and/or VR. MM >= M.
M (output) INTEGER
The number of columns in the arrays VL and/or VR actually
used to store the eigenvectors.
If HOWMNY = 'A' or 'B', M is set to N.
Each selected real eigenvector occupies one column and each
selected complex eigenvector occupies two columns.
WORK (workspace) DOUBLE PRECISION array, dimension (3*N)
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
Further Details
===============
The algorithm used in this program is basically backward (forward)
substitution, with scaling to make the the code robust against
possible overflow.
Each eigenvector is normalized so that the element of largest
magnitude has magnitude 1; here the magnitude of a complex number
(x,y) is taken to be |x| + |y|.
=====================================================================
Decode and test the input parameters
*/
/* Parameter adjustments */
--select;
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
vl_dim1 = *ldvl;
vl_offset = 1 + vl_dim1;
vl -= vl_offset;
vr_dim1 = *ldvr;
vr_offset = 1 + vr_dim1;
vr -= vr_offset;
--work;
/* Function Body */
bothv = lsame_(side, "B");
rightv = lsame_(side, "R") || bothv;
leftv = lsame_(side, "L") || bothv;
allv = lsame_(howmny, "A");
over = lsame_(howmny, "B");
somev = lsame_(howmny, "S");
*info = 0;
if (! rightv && ! leftv) {
*info = -1;
} else if (! allv && ! over && ! somev) {
*info = -2;
} else if (*n < 0) {
*info = -4;
} else if (*ldt < max(1,*n)) {
*info = -6;
} else if (*ldvl < 1 || leftv && *ldvl < *n) {
*info = -8;
} else if (*ldvr < 1 || rightv && *ldvr < *n) {
*info = -10;
} else {
/*
Set M to the number of columns required to store the selected
eigenvectors, standardize the array SELECT if necessary, and
test MM.
*/
if (somev) {
*m = 0;
pair = FALSE_;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (pair) {
pair = FALSE_;
select[j] = FALSE_;
} else {
if (j < *n) {
if (t[j + 1 + j * t_dim1] == 0.) {
if (select[j]) {
++(*m);
}
} else {
pair = TRUE_;
if (select[j] || select[j + 1]) {
select[j] = TRUE_;
*m += 2;
}
}
} else {
if (select[*n]) {
++(*m);
}
}
}
/* L10: */
}
} else {
*m = *n;
}
if (*mm < *m) {
*info = -11;
}
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DTREVC", &i__1);
return 0;
}
/* Quick return if possible. */
if (*n == 0) {
return 0;
}
/* Set the constants to control overflow. */
unfl = SAFEMINIMUM;
ovfl = 1. / unfl;
dlabad_(&unfl, &ovfl);
ulp = PRECISION;
smlnum = unfl * (*n / ulp);
bignum = (1. - ulp) / smlnum;
/*
Compute 1-norm of each column of strictly upper triangular
part of T to control overflow in triangular solver.
*/
work[1] = 0.;
i__1 = *n;
for (j = 2; j <= i__1; ++j) {
work[j] = 0.;
i__2 = j - 1;
for (i__ = 1; i__ <= i__2; ++i__) {
work[j] += (d__1 = t[i__ + j * t_dim1], abs(d__1));
/* L20: */
}
/* L30: */
}
/*
Index IP is used to specify the real or complex eigenvalue:
IP = 0, real eigenvalue,
1, first of conjugate complex pair: (wr,wi)
-1, second of conjugate complex pair: (wr,wi)
*/
n2 = *n << 1;
if (rightv) {
/* Compute right eigenvectors. */
ip = 0;
is = *m;
for (ki = *n; ki >= 1; --ki) {
if (ip == 1) {
goto L130;
}
if (ki == 1) {
goto L40;
}
if (t[ki + (ki - 1) * t_dim1] == 0.) {
goto L40;
}
ip = -1;
L40:
if (somev) {
if (ip == 0) {
if (! select[ki]) {
goto L130;
}
} else {
if (! select[ki - 1]) {
goto L130;
}
}
}
/* Compute the KI-th eigenvalue (WR,WI). */
wr = t[ki + ki * t_dim1];
wi = 0.;
if (ip != 0) {
wi = sqrt((d__1 = t[ki + (ki - 1) * t_dim1], abs(d__1))) *
sqrt((d__2 = t[ki - 1 + ki * t_dim1], abs(d__2)));
}
/* Computing MAX */
d__1 = ulp * (abs(wr) + abs(wi));
smin = max(d__1,smlnum);
if (ip == 0) {
/* Real right eigenvector */
work[ki + *n] = 1.;
/* Form right-hand side */
i__1 = ki - 1;
for (k = 1; k <= i__1; ++k) {
work[k + *n] = -t[k + ki * t_dim1];
/* L50: */
}
/*
Solve the upper quasi-triangular system:
(T(1:KI-1,1:KI-1) - WR)*X = SCALE*WORK.
*/
jnxt = ki - 1;
for (j = ki - 1; j >= 1; --j) {
if (j > jnxt) {
goto L60;
}
j1 = j;
j2 = j;
jnxt = j - 1;
if (j > 1) {
if (t[j + (j - 1) * t_dim1] != 0.) {
j1 = j - 1;
jnxt = j - 2;
}
}
if (j1 == j2) {
/* 1-by-1 diagonal block */
dlaln2_(&c_false, &c__1, &c__1, &smin, &c_b15, &t[j +
j * t_dim1], ldt, &c_b15, &c_b15, &work[j + *
n], n, &wr, &c_b29, x, &c__2, &scale, &xnorm,
&ierr);
/*
Scale X(1,1) to avoid overflow when updating
the right-hand side.
*/
if (xnorm > 1.) {
if (work[j] > bignum / xnorm) {
x[0] /= xnorm;
scale /= xnorm;
}
}
/* Scale if necessary */
if (scale != 1.) {
dscal_(&ki, &scale, &work[*n + 1], &c__1);
}
work[j + *n] = x[0];
/* Update right-hand side */
i__1 = j - 1;
d__1 = -x[0];
daxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[
*n + 1], &c__1);
} else {
/* 2-by-2 diagonal block */
dlaln2_(&c_false, &c__2, &c__1, &smin, &c_b15, &t[j -
1 + (j - 1) * t_dim1], ldt, &c_b15, &c_b15, &
work[j - 1 + *n], n, &wr, &c_b29, x, &c__2, &
scale, &xnorm, &ierr);
/*
Scale X(1,1) and X(2,1) to avoid overflow when
updating the right-hand side.
*/
if (xnorm > 1.) {
/* Computing MAX */
d__1 = work[j - 1], d__2 = work[j];
beta = max(d__1,d__2);
if (beta > bignum / xnorm) {
x[0] /= xnorm;
x[1] /= xnorm;
scale /= xnorm;
}
}
/* Scale if necessary */
if (scale != 1.) {
dscal_(&ki, &scale, &work[*n + 1], &c__1);
}
work[j - 1 + *n] = x[0];
work[j + *n] = x[1];
/* Update right-hand side */
i__1 = j - 2;
d__1 = -x[0];
daxpy_(&i__1, &d__1, &t[(j - 1) * t_dim1 + 1], &c__1,
&work[*n + 1], &c__1);
i__1 = j - 2;
d__1 = -x[1];
daxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[
*n + 1], &c__1);
}
L60:
;
}
/* Copy the vector x or Q*x to VR and normalize. */
if (! over) {
dcopy_(&ki, &work[*n + 1], &c__1, &vr[is * vr_dim1 + 1], &
c__1);
ii = idamax_(&ki, &vr[is * vr_dim1 + 1], &c__1);
remax = 1. / (d__1 = vr[ii + is * vr_dim1], abs(d__1));
dscal_(&ki, &remax, &vr[is * vr_dim1 + 1], &c__1);
i__1 = *n;
for (k = ki + 1; k <= i__1; ++k) {
vr[k + is * vr_dim1] = 0.;
/* L70: */
}
} else {
if (ki > 1) {
i__1 = ki - 1;
dgemv_("N", n, &i__1, &c_b15, &vr[vr_offset], ldvr, &
work[*n + 1], &c__1, &work[ki + *n], &vr[ki *
vr_dim1 + 1], &c__1);
}
ii = idamax_(n, &vr[ki * vr_dim1 + 1], &c__1);
remax = 1. / (d__1 = vr[ii + ki * vr_dim1], abs(d__1));
dscal_(n, &remax, &vr[ki * vr_dim1 + 1], &c__1);
}
} else {
/*
Complex right eigenvector.
Initial solve
[ (T(KI-1,KI-1) T(KI-1,KI) ) - (WR + I* WI)]*X = 0.
[ (T(KI,KI-1) T(KI,KI) ) ]
*/
if ((d__1 = t[ki - 1 + ki * t_dim1], abs(d__1)) >= (d__2 = t[
ki + (ki - 1) * t_dim1], abs(d__2))) {
work[ki - 1 + *n] = 1.;
work[ki + n2] = wi / t[ki - 1 + ki * t_dim1];
} else {
work[ki - 1 + *n] = -wi / t[ki + (ki - 1) * t_dim1];
work[ki + n2] = 1.;
}
work[ki + *n] = 0.;
work[ki - 1 + n2] = 0.;
/* Form right-hand side */
i__1 = ki - 2;
for (k = 1; k <= i__1; ++k) {
work[k + *n] = -work[ki - 1 + *n] * t[k + (ki - 1) *
t_dim1];
work[k + n2] = -work[ki + n2] * t[k + ki * t_dim1];
/* L80: */
}
/*
Solve upper quasi-triangular system:
(T(1:KI-2,1:KI-2) - (WR+i*WI))*X = SCALE*(WORK+i*WORK2)
*/
jnxt = ki - 2;
for (j = ki - 2; j >= 1; --j) {
if (j > jnxt) {
goto L90;
}
j1 = j;
j2 = j;
jnxt = j - 1;
if (j > 1) {
if (t[j + (j - 1) * t_dim1] != 0.) {
j1 = j - 1;
jnxt = j - 2;
}
}
if (j1 == j2) {
/* 1-by-1 diagonal block */
dlaln2_(&c_false, &c__1, &c__2, &smin, &c_b15, &t[j +
j * t_dim1], ldt, &c_b15, &c_b15, &work[j + *
n], n, &wr, &wi, x, &c__2, &scale, &xnorm, &
ierr);
/*
Scale X(1,1) and X(1,2) to avoid overflow when
updating the right-hand side.
*/
if (xnorm > 1.) {
if (work[j] > bignum / xnorm) {
x[0] /= xnorm;
x[2] /= xnorm;
scale /= xnorm;
}
}
/* Scale if necessary */
if (scale != 1.) {
dscal_(&ki, &scale, &work[*n + 1], &c__1);
dscal_(&ki, &scale, &work[n2 + 1], &c__1);
}
work[j + *n] = x[0];
work[j + n2] = x[2];
/* Update the right-hand side */
i__1 = j - 1;
d__1 = -x[0];
daxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[
*n + 1], &c__1);
i__1 = j - 1;
d__1 = -x[2];
daxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[
n2 + 1], &c__1);
} else {
/* 2-by-2 diagonal block */
dlaln2_(&c_false, &c__2, &c__2, &smin, &c_b15, &t[j -
1 + (j - 1) * t_dim1], ldt, &c_b15, &c_b15, &
work[j - 1 + *n], n, &wr, &wi, x, &c__2, &
scale, &xnorm, &ierr);
/*
Scale X to avoid overflow when updating
the right-hand side.
*/
if (xnorm > 1.) {
/* Computing MAX */
d__1 = work[j - 1], d__2 = work[j];
beta = max(d__1,d__2);
if (beta > bignum / xnorm) {
rec = 1. / xnorm;
x[0] *= rec;
x[2] *= rec;
x[1] *= rec;
x[3] *= rec;
scale *= rec;
}
}
/* Scale if necessary */
if (scale != 1.) {
dscal_(&ki, &scale, &work[*n + 1], &c__1);
dscal_(&ki, &scale, &work[n2 + 1], &c__1);
}
work[j - 1 + *n] = x[0];
work[j + *n] = x[1];
work[j - 1 + n2] = x[2];
work[j + n2] = x[3];
/* Update the right-hand side */
i__1 = j - 2;
d__1 = -x[0];
daxpy_(&i__1, &d__1, &t[(j - 1) * t_dim1 + 1], &c__1,
&work[*n + 1], &c__1);
i__1 = j - 2;
d__1 = -x[1];
daxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[
*n + 1], &c__1);
i__1 = j - 2;
d__1 = -x[2];
daxpy_(&i__1, &d__1, &t[(j - 1) * t_dim1 + 1], &c__1,
&work[n2 + 1], &c__1);
i__1 = j - 2;
d__1 = -x[3];
daxpy_(&i__1, &d__1, &t[j * t_dim1 + 1], &c__1, &work[
n2 + 1], &c__1);
}
L90:
;
}
/* Copy the vector x or Q*x to VR and normalize. */
if (! over) {
dcopy_(&ki, &work[*n + 1], &c__1, &vr[(is - 1) * vr_dim1
+ 1], &c__1);
dcopy_(&ki, &work[n2 + 1], &c__1, &vr[is * vr_dim1 + 1], &
c__1);
emax = 0.;
i__1 = ki;
for (k = 1; k <= i__1; ++k) {
/* Computing MAX */
d__3 = emax, d__4 = (d__1 = vr[k + (is - 1) * vr_dim1]
, abs(d__1)) + (d__2 = vr[k + is * vr_dim1],
abs(d__2));
emax = max(d__3,d__4);
/* L100: */
}
remax = 1. / emax;
dscal_(&ki, &remax, &vr[(is - 1) * vr_dim1 + 1], &c__1);
dscal_(&ki, &remax, &vr[is * vr_dim1 + 1], &c__1);
i__1 = *n;
for (k = ki + 1; k <= i__1; ++k) {
vr[k + (is - 1) * vr_dim1] = 0.;
vr[k + is * vr_dim1] = 0.;
/* L110: */
}
} else {
if (ki > 2) {
i__1 = ki - 2;
dgemv_("N", n, &i__1, &c_b15, &vr[vr_offset], ldvr, &
work[*n + 1], &c__1, &work[ki - 1 + *n], &vr[(
ki - 1) * vr_dim1 + 1], &c__1);
i__1 = ki - 2;
dgemv_("N", n, &i__1, &c_b15, &vr[vr_offset], ldvr, &
work[n2 + 1], &c__1, &work[ki + n2], &vr[ki *
vr_dim1 + 1], &c__1);
} else {
dscal_(n, &work[ki - 1 + *n], &vr[(ki - 1) * vr_dim1
+ 1], &c__1);
dscal_(n, &work[ki + n2], &vr[ki * vr_dim1 + 1], &
c__1);
}
emax = 0.;
i__1 = *n;
for (k = 1; k <= i__1; ++k) {
/* Computing MAX */
d__3 = emax, d__4 = (d__1 = vr[k + (ki - 1) * vr_dim1]
, abs(d__1)) + (d__2 = vr[k + ki * vr_dim1],
abs(d__2));
emax = max(d__3,d__4);
/* L120: */
}
remax = 1. / emax;
dscal_(n, &remax, &vr[(ki - 1) * vr_dim1 + 1], &c__1);
dscal_(n, &remax, &vr[ki * vr_dim1 + 1], &c__1);
}
}
--is;
if (ip != 0) {
--is;
}
L130:
if (ip == 1) {
ip = 0;
}
if (ip == -1) {
ip = 1;
}
/* L140: */
}
}
if (leftv) {
/* Compute left eigenvectors. */
ip = 0;
is = 1;
i__1 = *n;
for (ki = 1; ki <= i__1; ++ki) {
if (ip == -1) {
goto L250;
}
if (ki == *n) {
goto L150;
}
if (t[ki + 1 + ki * t_dim1] == 0.) {
goto L150;
}
ip = 1;
L150:
if (somev) {
if (! select[ki]) {
goto L250;
}
}
/* Compute the KI-th eigenvalue (WR,WI). */
wr = t[ki + ki * t_dim1];
wi = 0.;
if (ip != 0) {
wi = sqrt((d__1 = t[ki + (ki + 1) * t_dim1], abs(d__1))) *
sqrt((d__2 = t[ki + 1 + ki * t_dim1], abs(d__2)));
}
/* Computing MAX */
d__1 = ulp * (abs(wr) + abs(wi));
smin = max(d__1,smlnum);
if (ip == 0) {
/* Real left eigenvector. */
work[ki + *n] = 1.;
/* Form right-hand side */
i__2 = *n;
for (k = ki + 1; k <= i__2; ++k) {
work[k + *n] = -t[ki + k * t_dim1];
/* L160: */
}
/*
Solve the quasi-triangular system:
(T(KI+1:N,KI+1:N) - WR)'*X = SCALE*WORK
*/
vmax = 1.;
vcrit = bignum;
jnxt = ki + 1;
i__2 = *n;
for (j = ki + 1; j <= i__2; ++j) {
if (j < jnxt) {
goto L170;
}
j1 = j;
j2 = j;
jnxt = j + 1;
if (j < *n) {
if (t[j + 1 + j * t_dim1] != 0.) {
j2 = j + 1;
jnxt = j + 2;
}
}
if (j1 == j2) {
/*
1-by-1 diagonal block
Scale if necessary to avoid overflow when forming
the right-hand side.
*/
if (work[j] > vcrit) {
rec = 1. / vmax;
i__3 = *n - ki + 1;
dscal_(&i__3, &rec, &work[ki + *n], &c__1);
vmax = 1.;
vcrit = bignum;
}
i__3 = j - ki - 1;
work[j + *n] -= ddot_(&i__3, &t[ki + 1 + j * t_dim1],
&c__1, &work[ki + 1 + *n], &c__1);
/* Solve (T(J,J)-WR)'*X = WORK */
dlaln2_(&c_false, &c__1, &c__1, &smin, &c_b15, &t[j +
j * t_dim1], ldt, &c_b15, &c_b15, &work[j + *
n], n, &wr, &c_b29, x, &c__2, &scale, &xnorm,
&ierr);
/* Scale if necessary */
if (scale != 1.) {
i__3 = *n - ki + 1;
dscal_(&i__3, &scale, &work[ki + *n], &c__1);
}
work[j + *n] = x[0];
/* Computing MAX */
d__2 = (d__1 = work[j + *n], abs(d__1));
vmax = max(d__2,vmax);
vcrit = bignum / vmax;
} else {
/*
2-by-2 diagonal block
Scale if necessary to avoid overflow when forming
the right-hand side.
Computing MAX
*/
d__1 = work[j], d__2 = work[j + 1];
beta = max(d__1,d__2);
if (beta > vcrit) {
rec = 1. / vmax;
i__3 = *n - ki + 1;
dscal_(&i__3, &rec, &work[ki + *n], &c__1);
vmax = 1.;
vcrit = bignum;
}
i__3 = j - ki - 1;
work[j + *n] -= ddot_(&i__3, &t[ki + 1 + j * t_dim1],
&c__1, &work[ki + 1 + *n], &c__1);
i__3 = j - ki - 1;
work[j + 1 + *n] -= ddot_(&i__3, &t[ki + 1 + (j + 1) *
t_dim1], &c__1, &work[ki + 1 + *n], &c__1);
/*
Solve
[T(J,J)-WR T(J,J+1) ]'* X = SCALE*( WORK1 )
[T(J+1,J) T(J+1,J+1)-WR] ( WORK2 )
*/
dlaln2_(&c_true, &c__2, &c__1, &smin, &c_b15, &t[j +
j * t_dim1], ldt, &c_b15, &c_b15, &work[j + *
n], n, &wr, &c_b29, x, &c__2, &scale, &xnorm,
&ierr);
/* Scale if necessary */
if (scale != 1.) {
i__3 = *n - ki + 1;
dscal_(&i__3, &scale, &work[ki + *n], &c__1);
}
work[j + *n] = x[0];
work[j + 1 + *n] = x[1];
/* Computing MAX */
d__3 = (d__1 = work[j + *n], abs(d__1)), d__4 = (d__2
= work[j + 1 + *n], abs(d__2)), d__3 = max(
d__3,d__4);
vmax = max(d__3,vmax);
vcrit = bignum / vmax;
}
L170:
;
}
/* Copy the vector x or Q*x to VL and normalize. */
if (! over) {
i__2 = *n - ki + 1;
dcopy_(&i__2, &work[ki + *n], &c__1, &vl[ki + is *
vl_dim1], &c__1);
i__2 = *n - ki + 1;
ii = idamax_(&i__2, &vl[ki + is * vl_dim1], &c__1) + ki -
1;
remax = 1. / (d__1 = vl[ii + is * vl_dim1], abs(d__1));
i__2 = *n - ki + 1;
dscal_(&i__2, &remax, &vl[ki + is * vl_dim1], &c__1);
i__2 = ki - 1;
for (k = 1; k <= i__2; ++k) {
vl[k + is * vl_dim1] = 0.;
/* L180: */
}
} else {
if (ki < *n) {
i__2 = *n - ki;
dgemv_("N", n, &i__2, &c_b15, &vl[(ki + 1) * vl_dim1
+ 1], ldvl, &work[ki + 1 + *n], &c__1, &work[
ki + *n], &vl[ki * vl_dim1 + 1], &c__1);
}
ii = idamax_(n, &vl[ki * vl_dim1 + 1], &c__1);
remax = 1. / (d__1 = vl[ii + ki * vl_dim1], abs(d__1));
dscal_(n, &remax, &vl[ki * vl_dim1 + 1], &c__1);
}
} else {
/*
Complex left eigenvector.
Initial solve:
((T(KI,KI) T(KI,KI+1) )' - (WR - I* WI))*X = 0.
((T(KI+1,KI) T(KI+1,KI+1)) )
*/
if ((d__1 = t[ki + (ki + 1) * t_dim1], abs(d__1)) >= (d__2 =
t[ki + 1 + ki * t_dim1], abs(d__2))) {
work[ki + *n] = wi / t[ki + (ki + 1) * t_dim1];
work[ki + 1 + n2] = 1.;
} else {
work[ki + *n] = 1.;
work[ki + 1 + n2] = -wi / t[ki + 1 + ki * t_dim1];
}
work[ki + 1 + *n] = 0.;
work[ki + n2] = 0.;
/* Form right-hand side */
i__2 = *n;
for (k = ki + 2; k <= i__2; ++k) {
work[k + *n] = -work[ki + *n] * t[ki + k * t_dim1];
work[k + n2] = -work[ki + 1 + n2] * t[ki + 1 + k * t_dim1]
;
/* L190: */
}
/*
Solve complex quasi-triangular system:
( T(KI+2,N:KI+2,N) - (WR-i*WI) )*X = WORK1+i*WORK2
*/
vmax = 1.;
vcrit = bignum;
jnxt = ki + 2;
i__2 = *n;
for (j = ki + 2; j <= i__2; ++j) {
if (j < jnxt) {
goto L200;
}
j1 = j;
j2 = j;
jnxt = j + 1;
if (j < *n) {
if (t[j + 1 + j * t_dim1] != 0.) {
j2 = j + 1;
jnxt = j + 2;
}
}
if (j1 == j2) {
/*
1-by-1 diagonal block
Scale if necessary to avoid overflow when
forming the right-hand side elements.
*/
if (work[j] > vcrit) {
rec = 1. / vmax;
i__3 = *n - ki + 1;
dscal_(&i__3, &rec, &work[ki + *n], &c__1);
i__3 = *n - ki + 1;
dscal_(&i__3, &rec, &work[ki + n2], &c__1);
vmax = 1.;
vcrit = bignum;
}
i__3 = j - ki - 2;
work[j + *n] -= ddot_(&i__3, &t[ki + 2 + j * t_dim1],
&c__1, &work[ki + 2 + *n], &c__1);
i__3 = j - ki - 2;
work[j + n2] -= ddot_(&i__3, &t[ki + 2 + j * t_dim1],
&c__1, &work[ki + 2 + n2], &c__1);
/* Solve (T(J,J)-(WR-i*WI))*(X11+i*X12)= WK+I*WK2 */
d__1 = -wi;
dlaln2_(&c_false, &c__1, &c__2, &smin, &c_b15, &t[j +
j * t_dim1], ldt, &c_b15, &c_b15, &work[j + *
n], n, &wr, &d__1, x, &c__2, &scale, &xnorm, &
ierr);
/* Scale if necessary */
if (scale != 1.) {
i__3 = *n - ki + 1;
dscal_(&i__3, &scale, &work[ki + *n], &c__1);
i__3 = *n - ki + 1;
dscal_(&i__3, &scale, &work[ki + n2], &c__1);
}
work[j + *n] = x[0];
work[j + n2] = x[2];
/* Computing MAX */
d__3 = (d__1 = work[j + *n], abs(d__1)), d__4 = (d__2
= work[j + n2], abs(d__2)), d__3 = max(d__3,
d__4);
vmax = max(d__3,vmax);
vcrit = bignum / vmax;
} else {
/*
2-by-2 diagonal block
Scale if necessary to avoid overflow when forming
the right-hand side elements.
Computing MAX
*/
d__1 = work[j], d__2 = work[j + 1];
beta = max(d__1,d__2);
if (beta > vcrit) {
rec = 1. / vmax;
i__3 = *n - ki + 1;
dscal_(&i__3, &rec, &work[ki + *n], &c__1);
i__3 = *n - ki + 1;
dscal_(&i__3, &rec, &work[ki + n2], &c__1);
vmax = 1.;
vcrit = bignum;
}
i__3 = j - ki - 2;
work[j + *n] -= ddot_(&i__3, &t[ki + 2 + j * t_dim1],
&c__1, &work[ki + 2 + *n], &c__1);
i__3 = j - ki - 2;
work[j + n2] -= ddot_(&i__3, &t[ki + 2 + j * t_dim1],
&c__1, &work[ki + 2 + n2], &c__1);
i__3 = j - ki - 2;
work[j + 1 + *n] -= ddot_(&i__3, &t[ki + 2 + (j + 1) *
t_dim1], &c__1, &work[ki + 2 + *n], &c__1);
i__3 = j - ki - 2;
work[j + 1 + n2] -= ddot_(&i__3, &t[ki + 2 + (j + 1) *
t_dim1], &c__1, &work[ki + 2 + n2], &c__1);
/*
Solve 2-by-2 complex linear equation
([T(j,j) T(j,j+1) ]'-(wr-i*wi)*I)*X = SCALE*B
([T(j+1,j) T(j+1,j+1)] )
*/
d__1 = -wi;
dlaln2_(&c_true, &c__2, &c__2, &smin, &c_b15, &t[j +
j * t_dim1], ldt, &c_b15, &c_b15, &work[j + *
n], n, &wr, &d__1, x, &c__2, &scale, &xnorm, &
ierr);
/* Scale if necessary */
if (scale != 1.) {
i__3 = *n - ki + 1;
dscal_(&i__3, &scale, &work[ki + *n], &c__1);
i__3 = *n - ki + 1;
dscal_(&i__3, &scale, &work[ki + n2], &c__1);
}
work[j + *n] = x[0];
work[j + n2] = x[2];
work[j + 1 + *n] = x[1];
work[j + 1 + n2] = x[3];
/* Computing MAX */
d__1 = abs(x[0]), d__2 = abs(x[2]), d__1 = max(d__1,
d__2), d__2 = abs(x[1]), d__1 = max(d__1,d__2)
, d__2 = abs(x[3]), d__1 = max(d__1,d__2);
vmax = max(d__1,vmax);
vcrit = bignum / vmax;
}
L200:
;
}
/* Copy the vector x or Q*x to VL and normalize. */
if (! over) {
i__2 = *n - ki + 1;
dcopy_(&i__2, &work[ki + *n], &c__1, &vl[ki + is *
vl_dim1], &c__1);
i__2 = *n - ki + 1;
dcopy_(&i__2, &work[ki + n2], &c__1, &vl[ki + (is + 1) *
vl_dim1], &c__1);
emax = 0.;
i__2 = *n;
for (k = ki; k <= i__2; ++k) {
/* Computing MAX */
d__3 = emax, d__4 = (d__1 = vl[k + is * vl_dim1], abs(
d__1)) + (d__2 = vl[k + (is + 1) * vl_dim1],
abs(d__2));
emax = max(d__3,d__4);
/* L220: */
}
remax = 1. / emax;
i__2 = *n - ki + 1;
dscal_(&i__2, &remax, &vl[ki + is * vl_dim1], &c__1);
i__2 = *n - ki + 1;
dscal_(&i__2, &remax, &vl[ki + (is + 1) * vl_dim1], &c__1)
;
i__2 = ki - 1;
for (k = 1; k <= i__2; ++k) {
vl[k + is * vl_dim1] = 0.;
vl[k + (is + 1) * vl_dim1] = 0.;
/* L230: */
}
} else {
if (ki < *n - 1) {
i__2 = *n - ki - 1;
dgemv_("N", n, &i__2, &c_b15, &vl[(ki + 2) * vl_dim1
+ 1], ldvl, &work[ki + 2 + *n], &c__1, &work[
ki + *n], &vl[ki * vl_dim1 + 1], &c__1);
i__2 = *n - ki - 1;
dgemv_("N", n, &i__2, &c_b15, &vl[(ki + 2) * vl_dim1
+ 1], ldvl, &work[ki + 2 + n2], &c__1, &work[
ki + 1 + n2], &vl[(ki + 1) * vl_dim1 + 1], &
c__1);
} else {
dscal_(n, &work[ki + *n], &vl[ki * vl_dim1 + 1], &
c__1);
dscal_(n, &work[ki + 1 + n2], &vl[(ki + 1) * vl_dim1
+ 1], &c__1);
}
emax = 0.;
i__2 = *n;
for (k = 1; k <= i__2; ++k) {
/* Computing MAX */
d__3 = emax, d__4 = (d__1 = vl[k + ki * vl_dim1], abs(
d__1)) + (d__2 = vl[k + (ki + 1) * vl_dim1],
abs(d__2));
emax = max(d__3,d__4);
/* L240: */
}
remax = 1. / emax;
dscal_(n, &remax, &vl[ki * vl_dim1 + 1], &c__1);
dscal_(n, &remax, &vl[(ki + 1) * vl_dim1 + 1], &c__1);
}
}
++is;
if (ip != 0) {
++is;
}
L250:
if (ip == -1) {
ip = 0;
}
if (ip == 1) {
ip = -1;
}
/* L260: */
}
}
return 0;
/* End of DTREVC */
} /* dtrevc_ */
/* Subroutine */ int dtrexc_(char *compq, integer *n, doublereal *t, integer *
ldt, doublereal *q, integer *ldq, integer *ifst, integer *ilst,
doublereal *work, integer *info)
{
/* System generated locals */
integer q_dim1, q_offset, t_dim1, t_offset, i__1;
/* Local variables */
static integer nbf, nbl, here;
extern logical lsame_(char *, char *);
static logical wantq;
extern /* Subroutine */ int dlaexc_(logical *, integer *, doublereal *,
integer *, doublereal *, integer *, integer *, integer *, integer
*, doublereal *, integer *), xerbla_(char *, integer *);
static integer nbnext;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DTREXC reorders the real Schur factorization of a real matrix
A = Q*T*Q**T, so that the diagonal block of T with row index IFST is
moved to row ILST.
The real Schur form T is reordered by an orthogonal similarity
transformation Z**T*T*Z, and optionally the matrix Q of Schur vectors
is updated by postmultiplying it with Z.
T must be in Schur canonical form (as returned by DHSEQR), that is,
block upper triangular with 1-by-1 and 2-by-2 diagonal blocks; each
2-by-2 diagonal block has its diagonal elements equal and its
off-diagonal elements of opposite sign.
Arguments
=========
COMPQ (input) CHARACTER*1
= 'V': update the matrix Q of Schur vectors;
= 'N': do not update Q.
N (input) INTEGER
The order of the matrix T. N >= 0.
T (input/output) DOUBLE PRECISION array, dimension (LDT,N)
On entry, the upper quasi-triangular matrix T, in Schur
Schur canonical form.
On exit, the reordered upper quasi-triangular matrix, again
in Schur canonical form.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= max(1,N).
Q (input/output) DOUBLE PRECISION array, dimension (LDQ,N)
On entry, if COMPQ = 'V', the matrix Q of Schur vectors.
On exit, if COMPQ = 'V', Q has been postmultiplied by the
orthogonal transformation matrix Z which reorders T.
If COMPQ = 'N', Q is not referenced.
LDQ (input) INTEGER
The leading dimension of the array Q. LDQ >= max(1,N).
IFST (input/output) INTEGER
ILST (input/output) INTEGER
Specify the reordering of the diagonal blocks of T.
The block with row index IFST is moved to row ILST, by a
sequence of transpositions between adjacent blocks.
On exit, if IFST pointed on entry to the second row of a
2-by-2 block, it is changed to point to the first row; ILST
always points to the first row of the block in its final
position (which may differ from its input value by +1 or -1).
1 <= IFST <= N; 1 <= ILST <= N.
WORK (workspace) DOUBLE PRECISION array, dimension (N)
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
= 1: two adjacent blocks were too close to swap (the problem
is very ill-conditioned); T may have been partially
reordered, and ILST points to the first row of the
current position of the block being moved.
=====================================================================
Decode and test the input arguments.
*/
/* Parameter adjustments */
t_dim1 = *ldt;
t_offset = 1 + t_dim1;
t -= t_offset;
q_dim1 = *ldq;
q_offset = 1 + q_dim1;
q -= q_offset;
--work;
/* Function Body */
*info = 0;
wantq = lsame_(compq, "V");
if (! wantq && ! lsame_(compq, "N")) {
*info = -1;
} else if (*n < 0) {
*info = -2;
} else if (*ldt < max(1,*n)) {
*info = -4;
} else if (*ldq < 1 || wantq && *ldq < max(1,*n)) {
*info = -6;
} else if (*ifst < 1 || *ifst > *n) {
*info = -7;
} else if (*ilst < 1 || *ilst > *n) {
*info = -8;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DTREXC", &i__1);
return 0;
}
/* Quick return if possible */
if (*n <= 1) {
return 0;
}
/*
Determine the first row of specified block
and find out it is 1 by 1 or 2 by 2.
*/
if (*ifst > 1) {
if (t[*ifst + (*ifst - 1) * t_dim1] != 0.) {
--(*ifst);
}
}
nbf = 1;
if (*ifst < *n) {
if (t[*ifst + 1 + *ifst * t_dim1] != 0.) {
nbf = 2;
}
}
/*
Determine the first row of the final block
and find out it is 1 by 1 or 2 by 2.
*/
if (*ilst > 1) {
if (t[*ilst + (*ilst - 1) * t_dim1] != 0.) {
--(*ilst);
}
}
nbl = 1;
if (*ilst < *n) {
if (t[*ilst + 1 + *ilst * t_dim1] != 0.) {
nbl = 2;
}
}
if (*ifst == *ilst) {
return 0;
}
if (*ifst < *ilst) {
/* Update ILST */
if (nbf == 2 && nbl == 1) {
--(*ilst);
}
if (nbf == 1 && nbl == 2) {
++(*ilst);
}
here = *ifst;
L10:
/* Swap block with next one below */
if (nbf == 1 || nbf == 2) {
/* Current block either 1 by 1 or 2 by 2 */
nbnext = 1;
if (here + nbf + 1 <= *n) {
if (t[here + nbf + 1 + (here + nbf) * t_dim1] != 0.) {
nbnext = 2;
}
}
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &here, &
nbf, &nbnext, &work[1], info);
if (*info != 0) {
*ilst = here;
return 0;
}
here += nbnext;
/* Test if 2 by 2 block breaks into two 1 by 1 blocks */
if (nbf == 2) {
if (t[here + 1 + here * t_dim1] == 0.) {
nbf = 3;
}
}
} else {
/*
Current block consists of two 1 by 1 blocks each of which
must be swapped individually
*/
nbnext = 1;
if (here + 3 <= *n) {
if (t[here + 3 + (here + 2) * t_dim1] != 0.) {
nbnext = 2;
}
}
i__1 = here + 1;
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &i__1, &
c__1, &nbnext, &work[1], info);
if (*info != 0) {
*ilst = here;
return 0;
}
if (nbnext == 1) {
/* Swap two 1 by 1 blocks, no problems possible */
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &
here, &c__1, &nbnext, &work[1], info);
++here;
} else {
/* Recompute NBNEXT in case 2 by 2 split */
if (t[here + 2 + (here + 1) * t_dim1] == 0.) {
nbnext = 1;
}
if (nbnext == 2) {
/* 2 by 2 Block did not split */
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &
here, &c__1, &nbnext, &work[1], info);
if (*info != 0) {
*ilst = here;
return 0;
}
here += 2;
} else {
/* 2 by 2 Block did split */
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &
here, &c__1, &c__1, &work[1], info);
i__1 = here + 1;
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &
i__1, &c__1, &c__1, &work[1], info);
here += 2;
}
}
}
if (here < *ilst) {
goto L10;
}
} else {
here = *ifst;
L20:
/* Swap block with next one above */
if (nbf == 1 || nbf == 2) {
/* Current block either 1 by 1 or 2 by 2 */
nbnext = 1;
if (here >= 3) {
if (t[here - 1 + (here - 2) * t_dim1] != 0.) {
nbnext = 2;
}
}
i__1 = here - nbnext;
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &i__1, &
nbnext, &nbf, &work[1], info);
if (*info != 0) {
*ilst = here;
return 0;
}
here -= nbnext;
/* Test if 2 by 2 block breaks into two 1 by 1 blocks */
if (nbf == 2) {
if (t[here + 1 + here * t_dim1] == 0.) {
nbf = 3;
}
}
} else {
/*
Current block consists of two 1 by 1 blocks each of which
must be swapped individually
*/
nbnext = 1;
if (here >= 3) {
if (t[here - 1 + (here - 2) * t_dim1] != 0.) {
nbnext = 2;
}
}
i__1 = here - nbnext;
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &i__1, &
nbnext, &c__1, &work[1], info);
if (*info != 0) {
*ilst = here;
return 0;
}
if (nbnext == 1) {
/* Swap two 1 by 1 blocks, no problems possible */
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &
here, &nbnext, &c__1, &work[1], info);
--here;
} else {
/* Recompute NBNEXT in case 2 by 2 split */
if (t[here + (here - 1) * t_dim1] == 0.) {
nbnext = 1;
}
if (nbnext == 2) {
/* 2 by 2 Block did not split */
i__1 = here - 1;
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &
i__1, &c__2, &c__1, &work[1], info);
if (*info != 0) {
*ilst = here;
return 0;
}
here += -2;
} else {
/* 2 by 2 Block did split */
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &
here, &c__1, &c__1, &work[1], info);
i__1 = here - 1;
dlaexc_(&wantq, n, &t[t_offset], ldt, &q[q_offset], ldq, &
i__1, &c__1, &c__1, &work[1], info);
here += -2;
}
}
}
if (here > *ilst) {
goto L20;
}
}
*ilst = here;
return 0;
/* End of DTREXC */
} /* dtrexc_ */
/* Subroutine */ int dtrti2_(char *uplo, char *diag, integer *n, doublereal *
a, integer *lda, integer *info)
{
/* System generated locals */
integer a_dim1, a_offset, i__1, i__2;
/* Local variables */
static integer j;
static doublereal ajj;
extern /* Subroutine */ int dscal_(integer *, doublereal *, doublereal *,
integer *);
extern logical lsame_(char *, char *);
static logical upper;
extern /* Subroutine */ int dtrmv_(char *, char *, char *, integer *,
doublereal *, integer *, doublereal *, integer *), xerbla_(char *, integer *);
static logical nounit;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DTRTI2 computes the inverse of a real upper or lower triangular
matrix.
This is the Level 2 BLAS version of the algorithm.
Arguments
=========
UPLO (input) CHARACTER*1
Specifies whether the matrix A is upper or lower triangular.
= 'U': Upper triangular
= 'L': Lower triangular
DIAG (input) CHARACTER*1
Specifies whether or not the matrix A is unit triangular.
= 'N': Non-unit triangular
= 'U': Unit triangular
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the triangular matrix A. If UPLO = 'U', the
leading n by n upper triangular part of the array A contains
the upper triangular matrix, and the strictly lower
triangular part of A is not referenced. If UPLO = 'L', the
leading n by n lower triangular part of the array A contains
the lower triangular matrix, and the strictly upper
triangular part of A is not referenced. If DIAG = 'U', the
diagonal elements of A are also not referenced and are
assumed to be 1.
On exit, the (triangular) inverse of the original matrix, in
the same storage format.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -k, the k-th argument had an illegal value
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
nounit = lsame_(diag, "N");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (! nounit && ! lsame_(diag, "U")) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DTRTI2", &i__1);
return 0;
}
if (upper) {
/* Compute inverse of upper triangular matrix. */
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (nounit) {
a[j + j * a_dim1] = 1. / a[j + j * a_dim1];
ajj = -a[j + j * a_dim1];
} else {
ajj = -1.;
}
/* Compute elements 1:j-1 of j-th column. */
i__2 = j - 1;
dtrmv_("Upper", "No transpose", diag, &i__2, &a[a_offset], lda, &
a[j * a_dim1 + 1], &c__1);
i__2 = j - 1;
dscal_(&i__2, &ajj, &a[j * a_dim1 + 1], &c__1);
/* L10: */
}
} else {
/* Compute inverse of lower triangular matrix. */
for (j = *n; j >= 1; --j) {
if (nounit) {
a[j + j * a_dim1] = 1. / a[j + j * a_dim1];
ajj = -a[j + j * a_dim1];
} else {
ajj = -1.;
}
if (j < *n) {
/* Compute elements j+1:n of j-th column. */
i__1 = *n - j;
dtrmv_("Lower", "No transpose", diag, &i__1, &a[j + 1 + (j +
1) * a_dim1], lda, &a[j + 1 + j * a_dim1], &c__1);
i__1 = *n - j;
dscal_(&i__1, &ajj, &a[j + 1 + j * a_dim1], &c__1);
}
/* L20: */
}
}
return 0;
/* End of DTRTI2 */
} /* dtrti2_ */
/* Subroutine */ int dtrtri_(char *uplo, char *diag, integer *n, doublereal *
a, integer *lda, integer *info)
{
/* System generated locals */
address a__1[2];
integer a_dim1, a_offset, i__1, i__2[2], i__3, i__4, i__5;
char ch__1[2];
/* Local variables */
static integer j, jb, nb, nn;
extern logical lsame_(char *, char *);
extern /* Subroutine */ int dtrmm_(char *, char *, char *, char *,
integer *, integer *, doublereal *, doublereal *, integer *,
doublereal *, integer *), dtrsm_(
char *, char *, char *, char *, integer *, integer *, doublereal *
, doublereal *, integer *, doublereal *, integer *);
static logical upper;
extern /* Subroutine */ int dtrti2_(char *, char *, integer *, doublereal
*, integer *, integer *), xerbla_(char *, integer
*);
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
static logical nounit;
/*
-- LAPACK routine (version 3.2) --
-- LAPACK is a software package provided by Univ. of Tennessee, --
-- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
November 2006
Purpose
=======
DTRTRI computes the inverse of a real upper or lower triangular
matrix A.
This is the Level 3 BLAS version of the algorithm.
Arguments
=========
UPLO (input) CHARACTER*1
= 'U': A is upper triangular;
= 'L': A is lower triangular.
DIAG (input) CHARACTER*1
= 'N': A is non-unit triangular;
= 'U': A is unit triangular.
N (input) INTEGER
The order of the matrix A. N >= 0.
A (input/output) DOUBLE PRECISION array, dimension (LDA,N)
On entry, the triangular matrix A. If UPLO = 'U', the
leading N-by-N upper triangular part of the array A contains
the upper triangular matrix, and the strictly lower
triangular part of A is not referenced. If UPLO = 'L', the
leading N-by-N lower triangular part of the array A contains
the lower triangular matrix, and the strictly upper
triangular part of A is not referenced. If DIAG = 'U', the
diagonal elements of A are also not referenced and are
assumed to be 1.
On exit, the (triangular) inverse of the original matrix, in
the same storage format.
LDA (input) INTEGER
The leading dimension of the array A. LDA >= max(1,N).
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value
> 0: if INFO = i, A(i,i) is exactly zero. The triangular
matrix is singular and its inverse can not be computed.
=====================================================================
Test the input parameters.
*/
/* Parameter adjustments */
a_dim1 = *lda;
a_offset = 1 + a_dim1;
a -= a_offset;
/* Function Body */
*info = 0;
upper = lsame_(uplo, "U");
nounit = lsame_(diag, "N");
if (! upper && ! lsame_(uplo, "L")) {
*info = -1;
} else if (! nounit && ! lsame_(diag, "U")) {
*info = -2;
} else if (*n < 0) {
*info = -3;
} else if (*lda < max(1,*n)) {
*info = -5;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("DTRTRI", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 0) {
return 0;
}
/* Check for singularity if non-unit. */
if (nounit) {
i__1 = *n;
for (*info = 1; *info <= i__1; ++(*info)) {
if (a[*info + *info * a_dim1] == 0.) {
return 0;
}
/* L10: */
}
*info = 0;
}
/*
Determine the block size for this environment.
Writing concatenation
*/
i__2[0] = 1, a__1[0] = uplo;
i__2[1] = 1, a__1[1] = diag;
s_cat(ch__1, a__1, i__2, &c__2, (ftnlen)2);
nb = ilaenv_(&c__1, "DTRTRI", ch__1, n, &c_n1, &c_n1, &c_n1, (ftnlen)6, (
ftnlen)2);
if (nb <= 1 || nb >= *n) {
/* Use unblocked code */
dtrti2_(uplo, diag, n, &a[a_offset], lda, info);
} else {
/* Use blocked code */
if (upper) {
/* Compute inverse of upper triangular matrix */
i__1 = *n;
i__3 = nb;
for (j = 1; i__3 < 0 ? j >= i__1 : j <= i__1; j += i__3) {
/* Computing MIN */
i__4 = nb, i__5 = *n - j + 1;
jb = min(i__4,i__5);
/* Compute rows 1:j-1 of current block column */
i__4 = j - 1;
dtrmm_("Left", "Upper", "No transpose", diag, &i__4, &jb, &
c_b15, &a[a_offset], lda, &a[j * a_dim1 + 1], lda);
i__4 = j - 1;
dtrsm_("Right", "Upper", "No transpose", diag, &i__4, &jb, &
c_b151, &a[j + j * a_dim1], lda, &a[j * a_dim1 + 1],
lda);
/* Compute inverse of current diagonal block */
dtrti2_("Upper", diag, &jb, &a[j + j * a_dim1], lda, info);
/* L20: */
}
} else {
/* Compute inverse of lower triangular matrix */
nn = (*n - 1) / nb * nb + 1;
i__3 = -nb;
for (j = nn; i__3 < 0 ? j >= 1 : j <= 1; j += i__3) {
/* Computing MIN */
i__1 = nb, i__4 = *n - j + 1;
jb = min(i__1,i__4);
if (j + jb <= *n) {
/* Compute rows j+jb:n of current block column */
i__1 = *n - j - jb + 1;
dtrmm_("Left", "Lower", "No transpose", diag, &i__1, &jb,
&c_b15, &a[j + jb + (j + jb) * a_dim1], lda, &a[j
+ jb + j * a_dim1], lda);
i__1 = *n - j - jb + 1;
dtrsm_("Right", "Lower", "No transpose", diag, &i__1, &jb,
&c_b151, &a[j + j * a_dim1], lda, &a[j + jb + j *
a_dim1], lda);
}
/* Compute inverse of current diagonal block */
dtrti2_("Lower", diag, &jb, &a[j + j * a_dim1], lda, info);
/* L30: */
}
}
}
return 0;
/* End of DTRTRI */
} /* dtrtri_ */