/* Subroutine */ int slatdf_(integer *ijob, integer *n, real *z__, integer *
ldz, real *rhs, real *rdsum, real *rdscal, integer *ipiv, integer *
jpiv)
{
/* -- LAPACK auxiliary routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
June 30, 1999
Purpose
=======
SLATDF uses the LU factorization of the n-by-n matrix Z computed by
SGETC2 and computes a contribution to the reciprocal Dif-estimate
by solving Z * x = b for x, and choosing the r.h.s. b such that
the norm of x is as large as possible. On entry RHS = b holds the
contribution from earlier solved sub-systems, and on return RHS = x.
The factorization of Z returned by SGETC2 has the form Z = P*L*U*Q,
where P and Q are permutation matrices. L is lower triangular with
unit diagonal elements and U is upper triangular.
Arguments
=========
IJOB (input) INTEGER
IJOB = 2: First compute an approximative null-vector e
of Z using SGECON, e is normalized and solve for
Zx = +-e - f with the sign giving the greater value
of 2-norm(x). About 5 times as expensive as Default.
IJOB .ne. 2: Local look ahead strategy where all entries of
the r.h.s. b is choosen as either +1 or -1 (Default).
N (input) INTEGER
The number of columns of the matrix Z.
Z (input) REAL array, dimension (LDZ, N)
On entry, the LU part of the factorization of the n-by-n
matrix Z computed by SGETC2: Z = P * L * U * Q
LDZ (input) INTEGER
The leading dimension of the array Z. LDA >= max(1, N).
RHS (input/output) REAL array, dimension N.
On entry, RHS contains contributions from other subsystems.
On exit, RHS contains the solution of the subsystem with
entries acoording to the value of IJOB (see above).
RDSUM (input/output) REAL
On entry, the sum of squares of computed contributions to
the Dif-estimate under computation by STGSYL, where the
scaling factor RDSCAL (see below) has been factored out.
On exit, the corresponding sum of squares updated with the
contributions from the current sub-system.
If TRANS = 'T' RDSUM is not touched.
NOTE: RDSUM only makes sense when STGSY2 is called by STGSYL.
RDSCAL (input/output) REAL
On entry, scaling factor used to prevent overflow in RDSUM.
On exit, RDSCAL is updated w.r.t. the current contributions
in RDSUM.
If TRANS = 'T', RDSCAL is not touched.
NOTE: RDSCAL only makes sense when STGSY2 is called by
STGSYL.
IPIV (input) INTEGER array, dimension (N).
The pivot indices; for 1 <= i <= N, row i of the
matrix has been interchanged with row IPIV(i).
JPIV (input) INTEGER array, dimension (N).
The pivot indices; for 1 <= j <= N, column j of the
matrix has been interchanged with column JPIV(j).
Further Details
===============
Based on contributions by
Bo Kagstrom and Peter Poromaa, Department of Computing Science,
Umea University, S-901 87 Umea, Sweden.
This routine is a further developed implementation of algorithm
BSOLVE in [1] using complete pivoting in the LU factorization.
[1] Bo Kagstrom and Lars Westin,
Generalized Schur Methods with Condition Estimators for
Solving the Generalized Sylvester Equation, IEEE Transactions
on Automatic Control, Vol. 34, No. 7, July 1989, pp 745-751.
[2] Peter Poromaa,
On Efficient and Robust Estimators for the Separation
between two Regular Matrix Pairs with Applications in
Condition Estimation. Report IMINF-95.05, Departement of
Computing Science, Umea University, S-901 87 Umea, Sweden, 1995.
=====================================================================
Parameter adjustments */
/* Table of constant values */
static integer c__1 = 1;
static integer c_n1 = -1;
static real c_b23 = 1.f;
static real c_b37 = -1.f;
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2;
real r__1;
/* Builtin functions */
double sqrt(doublereal);
/* Local variables */
static integer info;
static real temp;
extern doublereal sdot_(integer *, real *, integer *, real *, integer *);
static real work[32];
static integer i__, j, k;
extern /* Subroutine */ int sscal_(integer *, real *, real *, integer *);
static real pmone;
extern doublereal sasum_(integer *, real *, integer *);
static real sminu;
static integer iwork[8];
extern /* Subroutine */ int scopy_(integer *, real *, integer *, real *,
integer *), saxpy_(integer *, real *, real *, integer *, real *,
integer *);
static real splus;
extern /* Subroutine */ int sgesc2_(integer *, real *, integer *, real *,
integer *, integer *, real *);
static real bm, bp, xm[8], xp[8];
extern /* Subroutine */ int sgecon_(char *, integer *, real *, integer *,
real *, real *, real *, integer *, integer *), slassq_(
integer *, real *, integer *, real *, real *), slaswp_(integer *,
real *, integer *, integer *, integer *, integer *, integer *);
#define z___ref(a_1,a_2) z__[(a_2)*z_dim1 + a_1]
z_dim1 = *ldz;
z_offset = 1 + z_dim1 * 1;
z__ -= z_offset;
--rhs;
--ipiv;
--jpiv;
/* Function Body */
if (*ijob != 2) {
/* Apply permutations IPIV to RHS */
i__1 = *n - 1;
slaswp_(&c__1, &rhs[1], ldz, &c__1, &i__1, &ipiv[1], &c__1);
/* Solve for L-part choosing RHS either to +1 or -1. */
pmone = -1.f;
i__1 = *n - 1;
for (j = 1; j <= i__1; ++j) {
bp = rhs[j] + 1.f;
bm = rhs[j] - 1.f;
splus = 1.f;
/* Look-ahead for L-part RHS(1:N-1) = + or -1, SPLUS and
SMIN computed more efficiently than in BSOLVE [1]. */
i__2 = *n - j;
splus += sdot_(&i__2, &z___ref(j + 1, j), &c__1, &z___ref(j + 1,
j), &c__1);
i__2 = *n - j;
sminu = sdot_(&i__2, &z___ref(j + 1, j), &c__1, &rhs[j + 1], &
c__1);
splus *= rhs[j];
if (splus > sminu) {
rhs[j] = bp;
} else if (sminu > splus) {
rhs[j] = bm;
} else {
/* In this case the updating sums are equal and we can
choose RHS(J) +1 or -1. The first time this happens
we choose -1, thereafter +1. This is a simple way to
get good estimates of matrices like Byers well-known
example (see [1]). (Not done in BSOLVE.) */
rhs[j] += pmone;
pmone = 1.f;
}
/* Compute the remaining r.h.s. */
temp = -rhs[j];
i__2 = *n - j;
saxpy_(&i__2, &temp, &z___ref(j + 1, j), &c__1, &rhs[j + 1], &
c__1);
/* L10: */
}
/* Solve for U-part, look-ahead for RHS(N) = +-1. This is not done
in BSOLVE and will hopefully give us a better estimate because
any ill-conditioning of the original matrix is transfered to U
and not to L. U(N, N) is an approximation to sigma_min(LU). */
i__1 = *n - 1;
scopy_(&i__1, &rhs[1], &c__1, xp, &c__1);
xp[*n - 1] = rhs[*n] + 1.f;
rhs[*n] += -1.f;
splus = 0.f;
sminu = 0.f;
for (i__ = *n; i__ >= 1; --i__) {
temp = 1.f / z___ref(i__, i__);
xp[i__ - 1] *= temp;
rhs[i__] *= temp;
i__1 = *n;
for (k = i__ + 1; k <= i__1; ++k) {
xp[i__ - 1] -= xp[k - 1] * (z___ref(i__, k) * temp);
rhs[i__] -= rhs[k] * (z___ref(i__, k) * temp);
/* L20: */
}
splus += (r__1 = xp[i__ - 1], dabs(r__1));
sminu += (r__1 = rhs[i__], dabs(r__1));
/* L30: */
}
if (splus > sminu) {
scopy_(n, xp, &c__1, &rhs[1], &c__1);
}
/* Apply the permutations JPIV to the computed solution (RHS) */
i__1 = *n - 1;
slaswp_(&c__1, &rhs[1], ldz, &c__1, &i__1, &jpiv[1], &c_n1);
/* Compute the sum of squares */
slassq_(n, &rhs[1], &c__1, rdscal, rdsum);
} else {
/* IJOB = 2, Compute approximate nullvector XM of Z */
sgecon_("I", n, &z__[z_offset], ldz, &c_b23, &temp, work, iwork, &
info);
scopy_(n, &work[*n], &c__1, xm, &c__1);
/* Compute RHS */
i__1 = *n - 1;
slaswp_(&c__1, xm, ldz, &c__1, &i__1, &ipiv[1], &c_n1);
temp = 1.f / sqrt(sdot_(n, xm, &c__1, xm, &c__1));
sscal_(n, &temp, xm, &c__1);
scopy_(n, xm, &c__1, xp, &c__1);
saxpy_(n, &c_b23, &rhs[1], &c__1, xp, &c__1);
saxpy_(n, &c_b37, xm, &c__1, &rhs[1], &c__1);
sgesc2_(n, &z__[z_offset], ldz, &rhs[1], &ipiv[1], &jpiv[1], &temp);
sgesc2_(n, &z__[z_offset], ldz, xp, &ipiv[1], &jpiv[1], &temp);
if (sasum_(n, xp, &c__1) > sasum_(n, &rhs[1], &c__1)) {
scopy_(n, xp, &c__1, &rhs[1], &c__1);
}
/* Compute the sum of squares */
slassq_(n, &rhs[1], &c__1, rdscal, rdsum);
}
return 0;
/* End of SLATDF */
} /* slatdf_ */
/* Subroutine */
int slatdf_(integer *ijob, integer *n, real *z__, integer * ldz, real *rhs, real *rdsum, real *rdscal, integer *ipiv, integer * jpiv)
{
/* System generated locals */
integer z_dim1, z_offset, i__1, i__2;
real r__1;
/* Builtin functions */
double sqrt(doublereal);
/* Local variables */
integer i__, j, k;
real bm, bp, xm[8], xp[8];
integer info;
real temp;
extern real sdot_(integer *, real *, integer *, real *, integer *);
real work[32];
extern /* Subroutine */
int sscal_(integer *, real *, real *, integer *);
real pmone;
extern real sasum_(integer *, real *, integer *);
real sminu;
integer iwork[8];
extern /* Subroutine */
int scopy_(integer *, real *, integer *, real *, integer *), saxpy_(integer *, real *, real *, integer *, real *, integer *);
real splus;
extern /* Subroutine */
int sgesc2_(integer *, real *, integer *, real *, integer *, integer *, real *), sgecon_(char *, integer *, real *, integer *, real *, real *, real *, integer *, integer *), slassq_(integer *, real *, integer *, real *, real *), slaswp_( integer *, real *, integer *, integer *, integer *, integer *, integer *);
/* -- LAPACK auxiliary routine (version 3.4.2) -- */
/* -- LAPACK is a software package provided by Univ. of Tennessee, -- */
/* -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..-- */
/* September 2012 */
/* .. Scalar Arguments .. */
/* .. */
/* .. Array Arguments .. */
/* .. */
/* ===================================================================== */
/* .. Parameters .. */
/* .. */
/* .. Local Scalars .. */
/* .. */
/* .. Local Arrays .. */
/* .. */
/* .. External Subroutines .. */
/* .. */
/* .. External Functions .. */
/* .. */
/* .. Intrinsic Functions .. */
/* .. */
/* .. Executable Statements .. */
/* Parameter adjustments */
z_dim1 = *ldz;
z_offset = 1 + z_dim1;
z__ -= z_offset;
--rhs;
--ipiv;
--jpiv;
/* Function Body */
if (*ijob != 2)
{
/* Apply permutations IPIV to RHS */
i__1 = *n - 1;
slaswp_(&c__1, &rhs[1], ldz, &c__1, &i__1, &ipiv[1], &c__1);
/* Solve for L-part choosing RHS either to +1 or -1. */
pmone = -1.f;
i__1 = *n - 1;
for (j = 1;
j <= i__1;
++j)
{
bp = rhs[j] + 1.f;
bm = rhs[j] - 1.f;
splus = 1.f;
/* Look-ahead for L-part RHS(1:N-1) = + or -1, SPLUS and */
/* SMIN computed more efficiently than in BSOLVE [1]. */
i__2 = *n - j;
splus += sdot_(&i__2, &z__[j + 1 + j * z_dim1], &c__1, &z__[j + 1 + j * z_dim1], &c__1);
i__2 = *n - j;
sminu = sdot_(&i__2, &z__[j + 1 + j * z_dim1], &c__1, &rhs[j + 1], &c__1);
splus *= rhs[j];
if (splus > sminu)
{
rhs[j] = bp;
}
else if (sminu > splus)
{
rhs[j] = bm;
}
else
{
/* In this case the updating sums are equal and we can */
/* choose RHS(J) +1 or -1. The first time this happens */
/* we choose -1, thereafter +1. This is a simple way to */
/* get good estimates of matrices like Byers well-known */
/* example (see [1]). (Not done in BSOLVE.) */
rhs[j] += pmone;
pmone = 1.f;
}
/* Compute the remaining r.h.s. */
temp = -rhs[j];
i__2 = *n - j;
saxpy_(&i__2, &temp, &z__[j + 1 + j * z_dim1], &c__1, &rhs[j + 1], &c__1);
/* L10: */
}
/* Solve for U-part, look-ahead for RHS(N) = +-1. This is not done */
/* in BSOLVE and will hopefully give us a better estimate because */
/* any ill-conditioning of the original matrix is transfered to U */
/* and not to L. U(N, N) is an approximation to sigma_min(LU). */
i__1 = *n - 1;
scopy_(&i__1, &rhs[1], &c__1, xp, &c__1);
xp[*n - 1] = rhs[*n] + 1.f;
rhs[*n] += -1.f;
splus = 0.f;
sminu = 0.f;
for (i__ = *n;
i__ >= 1;
--i__)
{
temp = 1.f / z__[i__ + i__ * z_dim1];
xp[i__ - 1] *= temp;
rhs[i__] *= temp;
i__1 = *n;
for (k = i__ + 1;
k <= i__1;
++k)
{
xp[i__ - 1] -= xp[k - 1] * (z__[i__ + k * z_dim1] * temp);
rhs[i__] -= rhs[k] * (z__[i__ + k * z_dim1] * temp);
/* L20: */
}
splus += (r__1 = xp[i__ - 1], abs(r__1));
sminu += (r__1 = rhs[i__], abs(r__1));
/* L30: */
}
if (splus > sminu)
{
scopy_(n, xp, &c__1, &rhs[1], &c__1);
}
/* Apply the permutations JPIV to the computed solution (RHS) */
i__1 = *n - 1;
slaswp_(&c__1, &rhs[1], ldz, &c__1, &i__1, &jpiv[1], &c_n1);
/* Compute the sum of squares */
slassq_(n, &rhs[1], &c__1, rdscal, rdsum);
}
else
{
/* IJOB = 2, Compute approximate nullvector XM of Z */
sgecon_("I", n, &z__[z_offset], ldz, &c_b23, &temp, work, iwork, & info);
scopy_(n, &work[*n], &c__1, xm, &c__1);
/* Compute RHS */
i__1 = *n - 1;
slaswp_(&c__1, xm, ldz, &c__1, &i__1, &ipiv[1], &c_n1);
temp = 1.f / sqrt(sdot_(n, xm, &c__1, xm, &c__1));
sscal_(n, &temp, xm, &c__1);
scopy_(n, xm, &c__1, xp, &c__1);
saxpy_(n, &c_b23, &rhs[1], &c__1, xp, &c__1);
saxpy_(n, &c_b37, xm, &c__1, &rhs[1], &c__1);
sgesc2_(n, &z__[z_offset], ldz, &rhs[1], &ipiv[1], &jpiv[1], &temp);
sgesc2_(n, &z__[z_offset], ldz, xp, &ipiv[1], &jpiv[1], &temp);
if (sasum_(n, xp, &c__1) > sasum_(n, &rhs[1], &c__1))
{
scopy_(n, xp, &c__1, &rhs[1], &c__1);
}
/* Compute the sum of squares */
slassq_(n, &rhs[1], &c__1, rdscal, rdsum);
}
return 0;
/* End of SLATDF */
}
