/* Subroutine */ int ztrevc_(char *side, char *howmny, logical *select,
integer *n, doublecomplex *t, integer *ldt, doublecomplex *vl,
integer *ldvl, doublecomplex *vr, integer *ldvr, integer *mm, integer
*m, doublecomplex *work, doublereal *rwork, integer *info)
{
/* -- LAPACK 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
=======
ZTREVC computes some or all of the right and/or left eigenvectors of
a complex upper triangular matrix T.
The right eigenvector x and the left eigenvector y of T corresponding
to an eigenvalue w are defined by:
T*x = w*x, y'*T = w*y'
where y' denotes the conjugate transpose of the vector y.
If all eigenvectors are requested, the routine may either return the
matrices X and/or Y of right or left eigenvectors of T, or the
products Q*X and/or Q*Y, where Q is an input unitary
matrix. If T was obtained from the Schur factorization of an
original matrix A = Q*T*Q', then Q*X and Q*Y are the matrices of
right or 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,
and backtransform them using the input matrices
supplied in VR and/or VL;
= 'S': compute selected right and/or left eigenvectors,
specified by the logical array SELECT.
SELECT (input) LOGICAL array, dimension (N)
If HOWMNY = 'S', SELECT specifies the eigenvectors to be
computed.
If HOWMNY = 'A' or 'B', SELECT is not referenced.
To select the eigenvector corresponding to the j-th
eigenvalue, SELECT(j) must be set to .TRUE..
N (input) INTEGER
The order of the matrix T. N >= 0.
T (input/output) COMPLEX*16 array, dimension (LDT,N)
The upper triangular matrix T. T is modified, but restored
on exit.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= max(1,N).
VL (input/output) COMPLEX*16 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 unitary matrix Q of
Schur vectors returned by ZHSEQR).
On exit, if SIDE = 'L' or 'B', VL contains:
if HOWMNY = 'A', the matrix Y of left eigenvectors of T;
VL is lower triangular. The i-th column
VL(i) of VL is the eigenvector corresponding
to T(i,i).
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.
If SIDE = 'R', VL is not referenced.
LDVL (input) INTEGER
The leading dimension of the array VL. LDVL >= max(1,N) if
SIDE = 'L' or 'B'; LDVL >= 1 otherwise.
VR (input/output) COMPLEX*16 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 unitary matrix Q of
Schur vectors returned by ZHSEQR).
On exit, if SIDE = 'R' or 'B', VR contains:
if HOWMNY = 'A', the matrix X of right eigenvectors of T;
VR is upper triangular. The i-th column
VR(i) of VR is the eigenvector corresponding
to T(i,i).
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.
If SIDE = 'L', VR is not referenced.
LDVR (input) INTEGER
The leading dimension of the array VR. LDVR >= max(1,N) if
SIDE = 'R' or 'B'; LDVR >= 1 otherwise.
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 eigenvector occupies one
column.
WORK (workspace) COMPLEX*16 array, dimension (2*N)
RWORK (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 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 */
/* Table of constant values */
static doublecomplex c_b2 = {1.,0.};
static integer c__1 = 1;
/* System generated locals */
integer t_dim1, t_offset, vl_dim1, vl_offset, vr_dim1, vr_offset, i__1,
i__2, i__3, i__4, i__5;
doublereal d__1, d__2, d__3;
doublecomplex z__1, z__2;
/* Builtin functions */
double d_imag(doublecomplex *);
void d_cnjg(doublecomplex *, doublecomplex *);
/* Local variables */
static logical allv;
static doublereal unfl, ovfl, smin;
static logical over;
static integer i__, j, k;
static doublereal scale;
extern logical lsame_(char *, char *);
static doublereal remax;
static logical leftv, bothv;
extern /* Subroutine */ int zgemv_(char *, integer *, integer *,
doublecomplex *, doublecomplex *, integer *, doublecomplex *,
integer *, doublecomplex *, doublecomplex *, integer *);
static logical somev;
extern /* Subroutine */ int zcopy_(integer *, doublecomplex *, integer *,
doublecomplex *, integer *), dlabad_(doublereal *, doublereal *);
static integer ii, ki;
extern doublereal dlamch_(char *);
static integer is;
extern /* Subroutine */ int xerbla_(char *, integer *), zdscal_(
integer *, doublereal *, doublecomplex *, integer *);
extern integer izamax_(integer *, doublecomplex *, integer *);
static logical rightv;
extern doublereal dzasum_(integer *, doublecomplex *, integer *);
static doublereal smlnum;
extern /* Subroutine */ int zlatrs_(char *, char *, char *, char *,
integer *, doublecomplex *, integer *, doublecomplex *,
doublereal *, doublereal *, integer *);
static doublereal ulp;
#define t_subscr(a_1,a_2) (a_2)*t_dim1 + a_1
#define t_ref(a_1,a_2) t[t_subscr(a_1,a_2)]
#define vl_subscr(a_1,a_2) (a_2)*vl_dim1 + a_1
#define vl_ref(a_1,a_2) vl[vl_subscr(a_1,a_2)]
#define vr_subscr(a_1,a_2) (a_2)*vr_dim1 + a_1
#define vr_ref(a_1,a_2) vr[vr_subscr(a_1,a_2)]
--select;
t_dim1 = *ldt;
t_offset = 1 + t_dim1 * 1;
t -= t_offset;
vl_dim1 = *ldvl;
vl_offset = 1 + vl_dim1 * 1;
vl -= vl_offset;
vr_dim1 = *ldvr;
vr_offset = 1 + vr_dim1 * 1;
vr -= vr_offset;
--work;
--rwork;
/* 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");
/* Set M to the number of columns required to store the selected
eigenvectors. */
if (somev) {
*m = 0;
i__1 = *n;
for (j = 1; j <= i__1; ++j) {
if (select[j]) {
++(*m);
}
/* L10: */
}
} else {
*m = *n;
}
*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 if (*mm < *m) {
*info = -11;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("ZTREVC", &i__1);
return 0;
}
/* Quick return if possible. */
if (*n == 0) {
return 0;
}
/* Set the constants to control overflow. */
unfl = dlamch_("Safe minimum");
ovfl = 1. / unfl;
dlabad_(&unfl, &ovfl);
ulp = dlamch_("Precision");
smlnum = unfl * (*n / ulp);
/* Store the diagonal elements of T in working array WORK. */
i__1 = *n;
for (i__ = 1; i__ <= i__1; ++i__) {
i__2 = i__ + *n;
i__3 = t_subscr(i__, i__);
work[i__2].r = t[i__3].r, work[i__2].i = t[i__3].i;
/* L20: */
}
/* Compute 1-norm of each column of strictly upper triangular
part of T to control overflow in triangular solver. */
rwork[1] = 0.;
i__1 = *n;
for (j = 2; j <= i__1; ++j) {
i__2 = j - 1;
rwork[j] = dzasum_(&i__2, &t_ref(1, j), &c__1);
/* L30: */
}
if (rightv) {
/* Compute right eigenvectors. */
is = *m;
for (ki = *n; ki >= 1; --ki) {
if (somev) {
if (! select[ki]) {
goto L80;
}
}
/* Computing MAX */
i__1 = t_subscr(ki, ki);
d__3 = ulp * ((d__1 = t[i__1].r, abs(d__1)) + (d__2 = d_imag(&
t_ref(ki, ki)), abs(d__2)));
smin = max(d__3,smlnum);
work[1].r = 1., work[1].i = 0.;
/* Form right-hand side. */
i__1 = ki - 1;
for (k = 1; k <= i__1; ++k) {
i__2 = k;
i__3 = t_subscr(k, ki);
z__1.r = -t[i__3].r, z__1.i = -t[i__3].i;
work[i__2].r = z__1.r, work[i__2].i = z__1.i;
/* L40: */
}
/* Solve the triangular system:
(T(1:KI-1,1:KI-1) - T(KI,KI))*X = SCALE*WORK. */
i__1 = ki - 1;
for (k = 1; k <= i__1; ++k) {
i__2 = t_subscr(k, k);
i__3 = t_subscr(k, k);
i__4 = t_subscr(ki, ki);
z__1.r = t[i__3].r - t[i__4].r, z__1.i = t[i__3].i - t[i__4]
.i;
t[i__2].r = z__1.r, t[i__2].i = z__1.i;
i__2 = t_subscr(k, k);
if ((d__1 = t[i__2].r, abs(d__1)) + (d__2 = d_imag(&t_ref(k,
k)), abs(d__2)) < smin) {
i__3 = t_subscr(k, k);
t[i__3].r = smin, t[i__3].i = 0.;
}
/* L50: */
}
if (ki > 1) {
i__1 = ki - 1;
zlatrs_("Upper", "No transpose", "Non-unit", "Y", &i__1, &t[
t_offset], ldt, &work[1], &scale, &rwork[1], info);
i__1 = ki;
work[i__1].r = scale, work[i__1].i = 0.;
}
/* Copy the vector x or Q*x to VR and normalize. */
if (! over) {
zcopy_(&ki, &work[1], &c__1, &vr_ref(1, is), &c__1);
ii = izamax_(&ki, &vr_ref(1, is), &c__1);
i__1 = vr_subscr(ii, is);
remax = 1. / ((d__1 = vr[i__1].r, abs(d__1)) + (d__2 = d_imag(
&vr_ref(ii, is)), abs(d__2)));
zdscal_(&ki, &remax, &vr_ref(1, is), &c__1);
i__1 = *n;
for (k = ki + 1; k <= i__1; ++k) {
i__2 = vr_subscr(k, is);
vr[i__2].r = 0., vr[i__2].i = 0.;
/* L60: */
}
} else {
if (ki > 1) {
i__1 = ki - 1;
z__1.r = scale, z__1.i = 0.;
zgemv_("N", n, &i__1, &c_b2, &vr[vr_offset], ldvr, &work[
1], &c__1, &z__1, &vr_ref(1, ki), &c__1);
}
ii = izamax_(n, &vr_ref(1, ki), &c__1);
i__1 = vr_subscr(ii, ki);
remax = 1. / ((d__1 = vr[i__1].r, abs(d__1)) + (d__2 = d_imag(
&vr_ref(ii, ki)), abs(d__2)));
zdscal_(n, &remax, &vr_ref(1, ki), &c__1);
}
/* Set back the original diagonal elements of T. */
i__1 = ki - 1;
for (k = 1; k <= i__1; ++k) {
i__2 = t_subscr(k, k);
i__3 = k + *n;
t[i__2].r = work[i__3].r, t[i__2].i = work[i__3].i;
/* L70: */
}
--is;
L80:
;
}
}
if (leftv) {
/* Compute left eigenvectors. */
is = 1;
i__1 = *n;
for (ki = 1; ki <= i__1; ++ki) {
if (somev) {
if (! select[ki]) {
goto L130;
}
}
/* Computing MAX */
i__2 = t_subscr(ki, ki);
d__3 = ulp * ((d__1 = t[i__2].r, abs(d__1)) + (d__2 = d_imag(&
t_ref(ki, ki)), abs(d__2)));
smin = max(d__3,smlnum);
i__2 = *n;
work[i__2].r = 1., work[i__2].i = 0.;
/* Form right-hand side. */
i__2 = *n;
for (k = ki + 1; k <= i__2; ++k) {
i__3 = k;
d_cnjg(&z__2, &t_ref(ki, k));
z__1.r = -z__2.r, z__1.i = -z__2.i;
work[i__3].r = z__1.r, work[i__3].i = z__1.i;
/* L90: */
}
/* Solve the triangular system:
(T(KI+1:N,KI+1:N) - T(KI,KI))'*X = SCALE*WORK. */
i__2 = *n;
for (k = ki + 1; k <= i__2; ++k) {
i__3 = t_subscr(k, k);
i__4 = t_subscr(k, k);
i__5 = t_subscr(ki, ki);
z__1.r = t[i__4].r - t[i__5].r, z__1.i = t[i__4].i - t[i__5]
.i;
t[i__3].r = z__1.r, t[i__3].i = z__1.i;
i__3 = t_subscr(k, k);
if ((d__1 = t[i__3].r, abs(d__1)) + (d__2 = d_imag(&t_ref(k,
k)), abs(d__2)) < smin) {
i__4 = t_subscr(k, k);
t[i__4].r = smin, t[i__4].i = 0.;
}
/* L100: */
}
if (ki < *n) {
i__2 = *n - ki;
zlatrs_("Upper", "Conjugate transpose", "Non-unit", "Y", &
i__2, &t_ref(ki + 1, ki + 1), ldt, &work[ki + 1], &
scale, &rwork[1], info);
i__2 = ki;
work[i__2].r = scale, work[i__2].i = 0.;
}
/* Copy the vector x or Q*x to VL and normalize. */
if (! over) {
i__2 = *n - ki + 1;
zcopy_(&i__2, &work[ki], &c__1, &vl_ref(ki, is), &c__1);
i__2 = *n - ki + 1;
ii = izamax_(&i__2, &vl_ref(ki, is), &c__1) + ki - 1;
i__2 = vl_subscr(ii, is);
remax = 1. / ((d__1 = vl[i__2].r, abs(d__1)) + (d__2 = d_imag(
&vl_ref(ii, is)), abs(d__2)));
i__2 = *n - ki + 1;
zdscal_(&i__2, &remax, &vl_ref(ki, is), &c__1);
i__2 = ki - 1;
for (k = 1; k <= i__2; ++k) {
i__3 = vl_subscr(k, is);
vl[i__3].r = 0., vl[i__3].i = 0.;
/* L110: */
}
} else {
if (ki < *n) {
i__2 = *n - ki;
z__1.r = scale, z__1.i = 0.;
zgemv_("N", n, &i__2, &c_b2, &vl_ref(1, ki + 1), ldvl, &
work[ki + 1], &c__1, &z__1, &vl_ref(1, ki), &c__1);
}
ii = izamax_(n, &vl_ref(1, ki), &c__1);
i__2 = vl_subscr(ii, ki);
remax = 1. / ((d__1 = vl[i__2].r, abs(d__1)) + (d__2 = d_imag(
&vl_ref(ii, ki)), abs(d__2)));
zdscal_(n, &remax, &vl_ref(1, ki), &c__1);
}
/* Set back the original diagonal elements of T. */
i__2 = *n;
for (k = ki + 1; k <= i__2; ++k) {
i__3 = t_subscr(k, k);
i__4 = k + *n;
t[i__3].r = work[i__4].r, t[i__3].i = work[i__4].i;
/* L120: */
}
++is;
L130:
;
}
}
return 0;
/* End of ZTREVC */
} /* ztrevc_ */
/* Subroutine */ int ctrsen_(char *job, char *compq, logical *select, integer
*n, complex *t, integer *ldt, complex *q, integer *ldq, complex *w,
integer *m, real *s, real *sep, complex *work, integer *lwork,
integer *info)
{
/* -- LAPACK 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
=======
CTRSEN reorders the Schur factorization of a complex matrix
A = Q*T*Q**H, so that a selected cluster of eigenvalues appears in
the leading positions on the diagonal of the upper triangular matrix
T, and the leading columns of Q form an orthonormal basis of the
corresponding right invariant subspace.
Optionally the routine computes the reciprocal condition numbers of
the cluster of eigenvalues and/or the invariant subspace.
Arguments
=========
JOB (input) CHARACTER*1
Specifies whether condition numbers are required for the
cluster of eigenvalues (S) or the invariant subspace (SEP):
= 'N': none;
= 'E': for eigenvalues only (S);
= 'V': for invariant subspace only (SEP);
= 'B': for both eigenvalues and invariant subspace (S and
SEP).
COMPQ (input) CHARACTER*1
= 'V': update the matrix Q of Schur vectors;
= 'N': do not update Q.
SELECT (input) LOGICAL array, dimension (N)
SELECT specifies the eigenvalues in the selected cluster. To
select the j-th eigenvalue, SELECT(j) must be set to .TRUE..
N (input) INTEGER
The order of the matrix T. N >= 0.
T (input/output) COMPLEX array, dimension (LDT,N)
On entry, the upper triangular matrix T.
On exit, T is overwritten by the reordered matrix T, with the
selected eigenvalues as the leading diagonal elements.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= max(1,N).
Q (input/output) COMPLEX 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
unitary transformation matrix which reorders T; the leading M
columns of Q form an orthonormal basis for the specified
invariant subspace.
If COMPQ = 'N', Q is not referenced.
LDQ (input) INTEGER
The leading dimension of the array Q.
LDQ >= 1; and if COMPQ = 'V', LDQ >= N.
W (output) COMPLEX array, dimension (N)
The reordered eigenvalues of T, in the same order as they
appear on the diagonal of T.
M (output) INTEGER
The dimension of the specified invariant subspace.
0 <= M <= N.
S (output) REAL
If JOB = 'E' or 'B', S is a lower bound on the reciprocal
condition number for the selected cluster of eigenvalues.
S cannot underestimate the true reciprocal condition number
by more than a factor of sqrt(N). If M = 0 or N, S = 1.
If JOB = 'N' or 'V', S is not referenced.
SEP (output) REAL
If JOB = 'V' or 'B', SEP is the estimated reciprocal
condition number of the specified invariant subspace. If
M = 0 or N, SEP = norm(T).
If JOB = 'N' or 'E', SEP is not referenced.
WORK (workspace/output) COMPLEX array, dimension (LWORK)
If JOB = 'N', WORK is not referenced. Otherwise,
on exit, if INFO = 0, WORK(1) returns the optimal LWORK.
LWORK (input) INTEGER
The dimension of the array WORK.
If JOB = 'N', LWORK >= 1;
if JOB = 'E', LWORK = M*(N-M);
if JOB = 'V' or 'B', LWORK >= 2*M*(N-M).
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
===============
CTRSEN first collects the selected eigenvalues by computing a unitary
transformation Z to move them to the top left corner of T. In other
words, the selected eigenvalues are the eigenvalues of T11 in:
Z'*T*Z = ( T11 T12 ) n1
( 0 T22 ) n2
n1 n2
where N = n1+n2 and Z' means the conjugate transpose of Z. The first
n1 columns of Z span the specified invariant subspace of T.
If T has been obtained from the Schur factorization of a matrix
A = Q*T*Q', then the reordered Schur factorization of A is given by
A = (Q*Z)*(Z'*T*Z)*(Q*Z)', and the first n1 columns of Q*Z span the
corresponding invariant subspace of A.
The reciprocal condition number of the average of the eigenvalues of
T11 may be returned in S. S lies between 0 (very badly conditioned)
and 1 (very well conditioned). It is computed as follows. First we
compute R so that
P = ( I R ) n1
( 0 0 ) n2
n1 n2
is the projector on the invariant subspace associated with T11.
R is the solution of the Sylvester equation:
T11*R - R*T22 = T12.
Let F-norm(M) denote the Frobenius-norm of M and 2-norm(M) denote
the two-norm of M. Then S is computed as the lower bound
(1 + F-norm(R)**2)**(-1/2)
on the reciprocal of 2-norm(P), the true reciprocal condition number.
S cannot underestimate 1 / 2-norm(P) by more than a factor of
sqrt(N).
An approximate error bound for the computed average of the
eigenvalues of T11 is
EPS * norm(T) / S
where EPS is the machine precision.
The reciprocal condition number of the right invariant subspace
spanned by the first n1 columns of Z (or of Q*Z) is returned in SEP.
SEP is defined as the separation of T11 and T22:
sep( T11, T22 ) = sigma-min( C )
where sigma-min(C) is the smallest singular value of the
n1*n2-by-n1*n2 matrix
C = kprod( I(n2), T11 ) - kprod( transpose(T22), I(n1) )
I(m) is an m by m identity matrix, and kprod denotes the Kronecker
product. We estimate sigma-min(C) by the reciprocal of an estimate of
the 1-norm of inverse(C). The true reciprocal 1-norm of inverse(C)
cannot differ from sigma-min(C) by more than a factor of sqrt(n1*n2).
When SEP is small, small changes in T can cause large changes in
the invariant subspace. An approximate bound on the maximum angular
error in the computed right invariant subspace is
EPS * norm(T) / SEP
=====================================================================
Decode and test the input parameters.
Parameter adjustments */
/* Table of constant values */
static integer c_n1 = -1;
/* System generated locals */
integer q_dim1, q_offset, t_dim1, t_offset, i__1, i__2, i__3;
/* Builtin functions */
double sqrt(doublereal);
/* Local variables */
static integer kase, ierr, k;
static real scale;
extern logical lsame_(char *, char *);
static integer lwmin;
static logical wantq, wants;
static real rnorm;
static integer n1, n2;
static real rwork[1];
extern doublereal clange_(char *, integer *, integer *, complex *,
integer *, real *);
static integer nn, ks;
extern /* Subroutine */ int clacon_(integer *, complex *, complex *, real
*, integer *), clacpy_(char *, integer *, integer *, complex *,
integer *, complex *, integer *), xerbla_(char *, integer
*);
static logical wantbh;
extern /* Subroutine */ int ctrexc_(char *, integer *, complex *, integer
*, complex *, integer *, integer *, integer *, integer *);
static logical wantsp;
extern /* Subroutine */ int ctrsyl_(char *, char *, integer *, integer *,
integer *, complex *, integer *, complex *, integer *, complex *,
integer *, real *, integer *);
static logical lquery;
static real est;
#define t_subscr(a_1,a_2) (a_2)*t_dim1 + a_1
#define t_ref(a_1,a_2) t[t_subscr(a_1,a_2)]
--select;
t_dim1 = *ldt;
t_offset = 1 + t_dim1 * 1;
t -= t_offset;
q_dim1 = *ldq;
q_offset = 1 + q_dim1 * 1;
q -= q_offset;
--w;
--work;
/* Function Body */
wantbh = lsame_(job, "B");
wants = lsame_(job, "E") || wantbh;
wantsp = lsame_(job, "V") || wantbh;
wantq = lsame_(compq, "V");
/* Set M to the number of selected eigenvalues. */
*m = 0;
i__1 = *n;
for (k = 1; k <= i__1; ++k) {
if (select[k]) {
++(*m);
}
/* L10: */
}
n1 = *m;
n2 = *n - *m;
nn = n1 * n2;
*info = 0;
lquery = *lwork == -1;
if (wantsp) {
/* Computing MAX */
i__1 = 1, i__2 = nn << 1;
lwmin = max(i__1,i__2);
} else if (lsame_(job, "N")) {
lwmin = 1;
} else if (lsame_(job, "E")) {
lwmin = max(1,nn);
}
if (! lsame_(job, "N") && ! wants && ! wantsp) {
*info = -1;
} else if (! lsame_(compq, "N") && ! wantq) {
*info = -2;
} else if (*n < 0) {
*info = -4;
} else if (*ldt < max(1,*n)) {
*info = -6;
} else if (*ldq < 1 || wantq && *ldq < *n) {
*info = -8;
} else if (*lwork < lwmin && ! lquery) {
*info = -14;
}
if (*info == 0) {
work[1].r = (real) lwmin, work[1].i = 0.f;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("CTRSEN", &i__1);
return 0;
} else if (lquery) {
return 0;
}
/* Quick return if possible */
if (*m == *n || *m == 0) {
if (wants) {
*s = 1.f;
}
if (wantsp) {
*sep = clange_("1", n, n, &t[t_offset], ldt, rwork);
}
goto L40;
}
/* Collect the selected eigenvalues at the top left corner of T. */
ks = 0;
i__1 = *n;
for (k = 1; k <= i__1; ++k) {
if (select[k]) {
++ks;
/* Swap the K-th eigenvalue to position KS. */
if (k != ks) {
ctrexc_(compq, n, &t[t_offset], ldt, &q[q_offset], ldq, &k, &
ks, &ierr);
}
}
/* L20: */
}
if (wants) {
/* Solve the Sylvester equation for R:
T11*R - R*T22 = scale*T12 */
clacpy_("F", &n1, &n2, &t_ref(1, n1 + 1), ldt, &work[1], &n1);
ctrsyl_("N", "N", &c_n1, &n1, &n2, &t[t_offset], ldt, &t_ref(n1 + 1,
n1 + 1), ldt, &work[1], &n1, &scale, &ierr);
/* Estimate the reciprocal of the condition number of the cluster
of eigenvalues. */
rnorm = clange_("F", &n1, &n2, &work[1], &n1, rwork);
if (rnorm == 0.f) {
*s = 1.f;
} else {
*s = scale / (sqrt(scale * scale / rnorm + rnorm) * sqrt(rnorm));
}
}
if (wantsp) {
/* Estimate sep(T11,T22). */
est = 0.f;
kase = 0;
L30:
clacon_(&nn, &work[nn + 1], &work[1], &est, &kase);
if (kase != 0) {
if (kase == 1) {
/* Solve T11*R - R*T22 = scale*X. */
ctrsyl_("N", "N", &c_n1, &n1, &n2, &t[t_offset], ldt, &t_ref(
n1 + 1, n1 + 1), ldt, &work[1], &n1, &scale, &ierr);
} else {
/* Solve T11'*R - R*T22' = scale*X. */
ctrsyl_("C", "C", &c_n1, &n1, &n2, &t[t_offset], ldt, &t_ref(
n1 + 1, n1 + 1), ldt, &work[1], &n1, &scale, &ierr);
}
goto L30;
}
*sep = scale / est;
}
L40:
/* Copy reordered eigenvalues to W. */
i__1 = *n;
for (k = 1; k <= i__1; ++k) {
i__2 = k;
i__3 = t_subscr(k, k);
w[i__2].r = t[i__3].r, w[i__2].i = t[i__3].i;
/* L50: */
}
work[1].r = (real) lwmin, work[1].i = 0.f;
return 0;
/* End of CTRSEN */
} /* ctrsen_ */
/* Subroutine */ int clahrd_(integer *n, integer *k, integer *nb, complex *a,
integer *lda, complex *tau, complex *t, integer *ldt, complex *y,
integer *ldy)
{
/* -- 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
=======
CLAHRD reduces the first NB columns of a complex general n-by-(n-k+1)
matrix A so that elements below the k-th subdiagonal are zero. The
reduction is performed by a unitary 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 CGEHRD.
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.
NB (input) INTEGER
The number of columns to be reduced.
A (input/output) COMPLEX 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) COMPLEX array, dimension (NB)
The scalar factors of the elementary reflectors. See Further
Details.
T (output) COMPLEX array, dimension (LDT,NB)
The upper triangular matrix T.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= NB.
Y (output) COMPLEX array, dimension (LDY,NB)
The n-by-nb matrix Y.
LDY (input) INTEGER
The leading dimension of the array Y. LDY >= max(1,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 complex scalar, and v is a complex 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 h a a a )
( a h a a a )
( a h 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).
=====================================================================
Quick return if possible
Parameter adjustments */
/* Table of constant values */
static complex c_b1 = {0.f,0.f};
static complex c_b2 = {1.f,0.f};
static integer c__1 = 1;
/* System generated locals */
integer a_dim1, a_offset, t_dim1, t_offset, y_dim1, y_offset, i__1, i__2,
i__3;
complex q__1;
/* Local variables */
static integer i__;
extern /* Subroutine */ int cscal_(integer *, complex *, complex *,
integer *), cgemv_(char *, integer *, integer *, complex *,
complex *, integer *, complex *, integer *, complex *, complex *,
integer *), ccopy_(integer *, complex *, integer *,
complex *, integer *), caxpy_(integer *, complex *, complex *,
integer *, complex *, integer *), ctrmv_(char *, char *, char *,
integer *, complex *, integer *, complex *, integer *);
static complex ei;
extern /* Subroutine */ int clarfg_(integer *, complex *, complex *,
integer *, complex *), clacgv_(integer *, complex *, integer *);
#define a_subscr(a_1,a_2) (a_2)*a_dim1 + a_1
#define a_ref(a_1,a_2) a[a_subscr(a_1,a_2)]
#define t_subscr(a_1,a_2) (a_2)*t_dim1 + a_1
#define t_ref(a_1,a_2) t[t_subscr(a_1,a_2)]
#define y_subscr(a_1,a_2) (a_2)*y_dim1 + a_1
#define y_ref(a_1,a_2) y[y_subscr(a_1,a_2)]
--tau;
a_dim1 = *lda;
a_offset = 1 + a_dim1 * 1;
a -= a_offset;
t_dim1 = *ldt;
t_offset = 1 + t_dim1 * 1;
t -= t_offset;
y_dim1 = *ldy;
y_offset = 1 + y_dim1 * 1;
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(1:n,i)
Compute i-th column of A - Y * V' */
i__2 = i__ - 1;
clacgv_(&i__2, &a_ref(*k + i__ - 1, 1), lda);
i__2 = i__ - 1;
q__1.r = -1.f, q__1.i = 0.f;
cgemv_("No transpose", n, &i__2, &q__1, &y[y_offset], ldy, &a_ref(
*k + i__ - 1, 1), lda, &c_b2, &a_ref(1, i__), &c__1);
i__2 = i__ - 1;
clacgv_(&i__2, &a_ref(*k + i__ - 1, 1), lda);
/* 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;
ccopy_(&i__2, &a_ref(*k + 1, i__), &c__1, &t_ref(1, *nb), &c__1);
i__2 = i__ - 1;
ctrmv_("Lower", "Conjugate transpose", "Unit", &i__2, &a_ref(*k +
1, 1), lda, &t_ref(1, *nb), &c__1);
/* w := w + V2'*b2 */
i__2 = *n - *k - i__ + 1;
i__3 = i__ - 1;
cgemv_("Conjugate transpose", &i__2, &i__3, &c_b2, &a_ref(*k +
i__, 1), lda, &a_ref(*k + i__, i__), &c__1, &c_b2, &t_ref(
1, *nb), &c__1);
/* w := T'*w */
i__2 = i__ - 1;
ctrmv_("Upper", "Conjugate transpose", "Non-unit", &i__2, &t[
t_offset], ldt, &t_ref(1, *nb), &c__1);
/* b2 := b2 - V2*w */
i__2 = *n - *k - i__ + 1;
i__3 = i__ - 1;
q__1.r = -1.f, q__1.i = 0.f;
cgemv_("No transpose", &i__2, &i__3, &q__1, &a_ref(*k + i__, 1),
lda, &t_ref(1, *nb), &c__1, &c_b2, &a_ref(*k + i__, i__),
&c__1);
/* b1 := b1 - V1*w */
i__2 = i__ - 1;
ctrmv_("Lower", "No transpose", "Unit", &i__2, &a_ref(*k + 1, 1),
lda, &t_ref(1, *nb), &c__1);
i__2 = i__ - 1;
q__1.r = -1.f, q__1.i = 0.f;
caxpy_(&i__2, &q__1, &t_ref(1, *nb), &c__1, &a_ref(*k + 1, i__), &
c__1);
i__2 = a_subscr(*k + i__ - 1, i__ - 1);
a[i__2].r = ei.r, a[i__2].i = ei.i;
}
/* Generate the elementary reflector H(i) to annihilate
A(k+i+1:n,i) */
i__2 = a_subscr(*k + i__, i__);
ei.r = a[i__2].r, ei.i = a[i__2].i;
/* Computing MIN */
i__2 = *k + i__ + 1;
i__3 = *n - *k - i__ + 1;
clarfg_(&i__3, &ei, &a_ref(min(i__2,*n), i__), &c__1, &tau[i__]);
i__2 = a_subscr(*k + i__, i__);
a[i__2].r = 1.f, a[i__2].i = 0.f;
/* Compute Y(1:n,i) */
i__2 = *n - *k - i__ + 1;
cgemv_("No transpose", n, &i__2, &c_b2, &a_ref(1, i__ + 1), lda, &
a_ref(*k + i__, i__), &c__1, &c_b1, &y_ref(1, i__), &c__1);
i__2 = *n - *k - i__ + 1;
i__3 = i__ - 1;
cgemv_("Conjugate transpose", &i__2, &i__3, &c_b2, &a_ref(*k + i__, 1)
, lda, &a_ref(*k + i__, i__), &c__1, &c_b1, &t_ref(1, i__), &
c__1);
i__2 = i__ - 1;
q__1.r = -1.f, q__1.i = 0.f;
cgemv_("No transpose", n, &i__2, &q__1, &y[y_offset], ldy, &t_ref(1,
i__), &c__1, &c_b2, &y_ref(1, i__), &c__1);
cscal_(n, &tau[i__], &y_ref(1, i__), &c__1);
/* Compute T(1:i,i) */
i__2 = i__ - 1;
i__3 = i__;
q__1.r = -tau[i__3].r, q__1.i = -tau[i__3].i;
cscal_(&i__2, &q__1, &t_ref(1, i__), &c__1);
i__2 = i__ - 1;
ctrmv_("Upper", "No transpose", "Non-unit", &i__2, &t[t_offset], ldt,
&t_ref(1, i__), &c__1);
i__2 = t_subscr(i__, i__);
i__3 = i__;
t[i__2].r = tau[i__3].r, t[i__2].i = tau[i__3].i;
/* L10: */
}
i__1 = a_subscr(*k + *nb, *nb);
a[i__1].r = ei.r, a[i__1].i = ei.i;
return 0;
/* End of CLAHRD */
} /* clahrd_ */
/* Subroutine */ int clarft_(char *direct, char *storev, integer *n, integer *
k, complex *v, integer *ldv, complex *tau, complex *t, integer *ldt)
{
/* -- LAPACK auxiliary routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
September 30, 1994
Purpose
=======
CLARFT forms the triangular factor T of a complex 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) COMPLEX 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) COMPLEX array, dimension (K)
TAU(i) must contain the scalar factor of the elementary
reflector H(i).
T (output) COMPLEX 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 */
/* Table of constant values */
static complex c_b2 = {0.f,0.f};
static integer c__1 = 1;
/* System generated locals */
integer t_dim1, t_offset, v_dim1, v_offset, i__1, i__2, i__3, i__4;
complex q__1;
/* Local variables */
static integer i__, j;
extern /* Subroutine */ int cgemv_(char *, integer *, integer *, complex *
, complex *, integer *, complex *, integer *, complex *, complex *
, integer *);
extern logical lsame_(char *, char *);
extern /* Subroutine */ int ctrmv_(char *, char *, char *, integer *,
complex *, integer *, complex *, integer *), clacgv_(integer *, complex *, integer *);
static complex vii;
#define t_subscr(a_1,a_2) (a_2)*t_dim1 + a_1
#define t_ref(a_1,a_2) t[t_subscr(a_1,a_2)]
#define v_subscr(a_1,a_2) (a_2)*v_dim1 + a_1
#define v_ref(a_1,a_2) v[v_subscr(a_1,a_2)]
v_dim1 = *ldv;
v_offset = 1 + v_dim1 * 1;
v -= v_offset;
--tau;
t_dim1 = *ldt;
t_offset = 1 + t_dim1 * 1;
t -= t_offset;
/* Function Body */
if (*n == 0) {
return 0;
}
if (lsame_(direct, "F")) {
i__1 = *k;
for (i__ = 1; i__ <= i__1; ++i__) {
i__2 = i__;
if (tau[i__2].r == 0.f && tau[i__2].i == 0.f) {
/* H(i) = I */
i__2 = i__;
for (j = 1; j <= i__2; ++j) {
i__3 = t_subscr(j, i__);
t[i__3].r = 0.f, t[i__3].i = 0.f;
/* L10: */
}
} else {
/* general case */
i__2 = v_subscr(i__, i__);
vii.r = v[i__2].r, vii.i = v[i__2].i;
i__2 = v_subscr(i__, i__);
v[i__2].r = 1.f, v[i__2].i = 0.f;
if (lsame_(storev, "C")) {
/* T(1:i-1,i) := - tau(i) * V(i:n,1:i-1)' * V(i:n,i) */
i__2 = *n - i__ + 1;
i__3 = i__ - 1;
i__4 = i__;
q__1.r = -tau[i__4].r, q__1.i = -tau[i__4].i;
cgemv_("Conjugate transpose", &i__2, &i__3, &q__1, &v_ref(
i__, 1), ldv, &v_ref(i__, i__), &c__1, &c_b2, &
t_ref(1, i__), &c__1);
} else {
/* T(1:i-1,i) := - tau(i) * V(1:i-1,i:n) * V(i,i:n)' */
if (i__ < *n) {
i__2 = *n - i__;
clacgv_(&i__2, &v_ref(i__, i__ + 1), ldv);
}
i__2 = i__ - 1;
i__3 = *n - i__ + 1;
i__4 = i__;
q__1.r = -tau[i__4].r, q__1.i = -tau[i__4].i;
cgemv_("No transpose", &i__2, &i__3, &q__1, &v_ref(1, i__)
, ldv, &v_ref(i__, i__), ldv, &c_b2, &t_ref(1,
i__), &c__1);
if (i__ < *n) {
i__2 = *n - i__;
clacgv_(&i__2, &v_ref(i__, i__ + 1), ldv);
}
}
i__2 = v_subscr(i__, i__);
v[i__2].r = vii.r, v[i__2].i = vii.i;
/* T(1:i-1,i) := T(1:i-1,1:i-1) * T(1:i-1,i) */
i__2 = i__ - 1;
ctrmv_("Upper", "No transpose", "Non-unit", &i__2, &t[
t_offset], ldt, &t_ref(1, i__), &c__1);
i__2 = t_subscr(i__, i__);
i__3 = i__;
t[i__2].r = tau[i__3].r, t[i__2].i = tau[i__3].i;
}
/* L20: */
}
} else {
for (i__ = *k; i__ >= 1; --i__) {
i__1 = i__;
if (tau[i__1].r == 0.f && tau[i__1].i == 0.f) {
/* H(i) = I */
i__1 = *k;
for (j = i__; j <= i__1; ++j) {
i__2 = t_subscr(j, i__);
t[i__2].r = 0.f, t[i__2].i = 0.f;
/* L30: */
}
} else {
/* general case */
if (i__ < *k) {
if (lsame_(storev, "C")) {
i__1 = v_subscr(*n - *k + i__, i__);
vii.r = v[i__1].r, vii.i = v[i__1].i;
i__1 = v_subscr(*n - *k + i__, i__);
v[i__1].r = 1.f, v[i__1].i = 0.f;
/* T(i+1:k,i) :=
- tau(i) * V(1:n-k+i,i+1:k)' * V(1:n-k+i,i) */
i__1 = *n - *k + i__;
i__2 = *k - i__;
i__3 = i__;
q__1.r = -tau[i__3].r, q__1.i = -tau[i__3].i;
cgemv_("Conjugate transpose", &i__1, &i__2, &q__1, &
v_ref(1, i__ + 1), ldv, &v_ref(1, i__), &c__1,
&c_b2, &t_ref(i__ + 1, i__), &c__1);
i__1 = v_subscr(*n - *k + i__, i__);
v[i__1].r = vii.r, v[i__1].i = vii.i;
} else {
i__1 = v_subscr(i__, *n - *k + i__);
vii.r = v[i__1].r, vii.i = v[i__1].i;
i__1 = v_subscr(i__, *n - *k + i__);
v[i__1].r = 1.f, v[i__1].i = 0.f;
/* T(i+1:k,i) :=
- tau(i) * V(i+1:k,1:n-k+i) * V(i,1:n-k+i)' */
i__1 = *n - *k + i__ - 1;
clacgv_(&i__1, &v_ref(i__, 1), ldv);
i__1 = *k - i__;
i__2 = *n - *k + i__;
i__3 = i__;
q__1.r = -tau[i__3].r, q__1.i = -tau[i__3].i;
cgemv_("No transpose", &i__1, &i__2, &q__1, &v_ref(
i__ + 1, 1), ldv, &v_ref(i__, 1), ldv, &c_b2,
&t_ref(i__ + 1, i__), &c__1);
i__1 = *n - *k + i__ - 1;
clacgv_(&i__1, &v_ref(i__, 1), ldv);
i__1 = v_subscr(i__, *n - *k + i__);
v[i__1].r = vii.r, v[i__1].i = vii.i;
}
/* T(i+1:k,i) := T(i+1:k,i+1:k) * T(i+1:k,i) */
i__1 = *k - i__;
ctrmv_("Lower", "No transpose", "Non-unit", &i__1, &t_ref(
i__ + 1, i__ + 1), ldt, &t_ref(i__ + 1, i__), &
c__1);
}
i__1 = t_subscr(i__, i__);
i__2 = i__;
t[i__1].r = tau[i__2].r, t[i__1].i = tau[i__2].i;
}
/* L40: */
}
}
return 0;
/* End of CLARFT */
} /* clarft_ */
/* Subroutine */ int cdrvgg_(integer *nsizes, integer *nn, integer *ntypes,
logical *dotype, integer *iseed, real *thresh, real *thrshn, integer *
nounit, complex *a, integer *lda, complex *b, complex *s, complex *t,
complex *s2, complex *t2, complex *q, integer *ldq, complex *z__,
complex *alpha1, complex *beta1, complex *alpha2, complex *beta2,
complex *vl, complex *vr, complex *work, integer *lwork, real *rwork,
real *result, integer *info)
{
/* Initialized data */
static integer kclass[26] = { 1,1,1,1,1,1,1,1,1,1,1,1,1,1,1,2,2,2,2,2,2,2,
2,2,2,3 };
static integer kbmagn[26] = { 1,1,1,1,1,1,1,1,3,2,3,2,2,3,1,1,1,1,1,1,1,3,
2,3,2,1 };
static integer ktrian[26] = { 0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,1,1,1,1,1,
1,1,1,1 };
static logical lasign[26] = { FALSE_,FALSE_,FALSE_,FALSE_,FALSE_,FALSE_,
TRUE_,FALSE_,TRUE_,TRUE_,FALSE_,FALSE_,TRUE_,TRUE_,TRUE_,FALSE_,
TRUE_,FALSE_,FALSE_,FALSE_,TRUE_,TRUE_,TRUE_,TRUE_,TRUE_,FALSE_ };
static logical lbsign[26] = { FALSE_,FALSE_,FALSE_,FALSE_,FALSE_,FALSE_,
FALSE_,TRUE_,FALSE_,FALSE_,TRUE_,TRUE_,FALSE_,FALSE_,TRUE_,FALSE_,
TRUE_,FALSE_,FALSE_,FALSE_,FALSE_,FALSE_,FALSE_,FALSE_,FALSE_,
FALSE_ };
static integer kz1[6] = { 0,1,2,1,3,3 };
static integer kz2[6] = { 0,0,1,2,1,1 };
static integer kadd[6] = { 0,0,0,0,3,2 };
static integer katype[26] = { 0,1,0,1,2,3,4,1,4,4,1,1,4,4,4,2,4,5,8,7,9,4,
4,4,4,0 };
static integer kbtype[26] = { 0,0,1,1,2,-3,1,4,1,1,4,4,1,1,-4,2,-4,8,8,8,
8,8,8,8,8,0 };
static integer kazero[26] = { 1,1,1,1,1,1,2,1,2,2,1,1,2,2,3,1,3,5,5,5,5,3,
3,3,3,1 };
static integer kbzero[26] = { 1,1,1,1,1,1,1,2,1,1,2,2,1,1,4,1,4,6,6,6,6,4,
4,4,4,1 };
static integer kamagn[26] = { 1,1,1,1,1,1,1,1,2,3,2,3,2,3,1,1,1,1,1,1,1,2,
3,3,2,1 };
/* Format strings */
static char fmt_9999[] = "(\002 CDRVGG: \002,a,\002 returned INFO=\002,i"
"6,\002.\002,/9x,\002N=\002,i6,\002, JTYPE=\002,i6,\002, ISEED="
"(\002,3(i5,\002,\002),i5,\002)\002)";
static char fmt_9998[] = "(\002 CDRVGG: \002,a,\002 Eigenvectors from"
" \002,a,\002 incorrectly \002,\002normalized.\002,/\002 Bits of "
"error=\002,0p,g10.3,\002,\002,9x,\002N=\002,i6,\002, JTYPE=\002,"
"i6,\002, ISEED=(\002,3(i5,\002,\002),i5,\002)\002)";
static char fmt_9997[] = "(/1x,a3,\002 -- Complex Generalized eigenvalue"
" problem driver\002)";
static char fmt_9996[] = "(\002 Matrix types (see CDRVGG for details):"
" \002)";
static char fmt_9995[] = "(\002 Special Matrices:\002,23x,\002(J'=transp"
"osed Jordan block)\002,/\002 1=(0,0) 2=(I,0) 3=(0,I) 4=(I,I"
") 5=(J',J') \002,\0026=(diag(J',I), diag(I,J'))\002,/\002 Diag"
"onal Matrices: ( \002,\002D=diag(0,1,2,...) )\002,/\002 7=(D,"
"I) 9=(large*D, small*I\002,\002) 11=(large*I, small*D) 13=(l"
"arge*D, large*I)\002,/\002 8=(I,D) 10=(small*D, large*I) 12="
"(small*I, large*D) \002,\002 14=(small*D, small*I)\002,/\002 15"
"=(D, reversed D)\002)";
static char fmt_9994[] = "(\002 Matrices Rotated by Random \002,a,\002 M"
"atrices U, V:\002,/\002 16=Transposed Jordan Blocks "
" 19=geometric \002,\002alpha, beta=0,1\002,/\002 17=arithm. alp"
"ha&beta \002,\002 20=arithmetic alpha, beta=0,"
"1\002,/\002 18=clustered \002,\002alpha, beta=0,1 21"
"=random alpha, beta=0,1\002,/\002 Large & Small Matrices:\002,"
"/\002 22=(large, small) \002,\00223=(small,large) 24=(smal"
"l,small) 25=(large,large)\002,/\002 26=random O(1) matrices"
".\002)";
static char fmt_9993[] = "(/\002 Tests performed: (S is Schur, T is tri"
"angular, \002,\002Q and Z are \002,a,\002,\002,/20x,\002l and r "
"are the appropriate left and right\002,/19x,\002eigenvectors, re"
"sp., a is alpha, b is beta, and\002,/19x,a,\002 means \002,a,"
"\002.)\002,/\002 1 = | A - Q S Z\002,a,\002 | / ( |A| n ulp ) "
" 2 = | B - Q T Z\002,a,\002 | / ( |B| n ulp )\002,/\002 3 = | "
"I - QQ\002,a,\002 | / ( n ulp ) 4 = | I - ZZ\002,a"
",\002 | / ( n ulp )\002,/\002 5 = difference between (alpha,beta"
") and diagonals of\002,\002 (S,T)\002,/\002 6 = max | ( b A - a "
"B )\002,a,\002 l | / const. 7 = max | ( b A - a B ) r | / cons"
"t.\002,/1x)";
static char fmt_9992[] = "(\002 Matrix order=\002,i5,\002, type=\002,i2"
",\002, seed=\002,4(i4,\002,\002),\002 result \002,i3,\002 is\002"
",0p,f8.2)";
static char fmt_9991[] = "(\002 Matrix order=\002,i5,\002, type=\002,i2"
",\002, seed=\002,4(i4,\002,\002),\002 result \002,i3,\002 is\002"
",1p,e10.3)";
/* System generated locals */
integer a_dim1, a_offset, b_dim1, b_offset, q_dim1, q_offset, s_dim1,
s_offset, s2_dim1, s2_offset, t_dim1, t_offset, t2_dim1,
t2_offset, vl_dim1, vl_offset, vr_dim1, vr_offset, z_dim1,
z_offset, i__1, i__2, i__3, i__4, i__5, i__6, i__7, i__8, i__9,
i__10, i__11;
real r__1, r__2, r__3, r__4, r__5, r__6, r__7, r__8, r__9, r__10, r__11,
r__12, r__13, r__14, r__15, r__16;
complex q__1, q__2, q__3, q__4;
/* Builtin functions */
double r_sign(real *, real *), c_abs(complex *);
void r_cnjg(complex *, complex *);
integer s_wsfe(cilist *), do_fio(integer *, char *, ftnlen), e_wsfe(void);
double r_imag(complex *);
/* Local variables */
static integer iadd, nmax;
static real temp1, temp2;
static integer j, n;
static logical badnn;
extern /* Subroutine */ int cgegs_(char *, char *, integer *, complex *,
integer *, complex *, integer *, complex *, complex *, complex *,
integer *, complex *, integer *, complex *, integer *, real *,
integer *), cgegv_(char *, char *, integer *,
complex *, integer *, complex *, integer *, complex *, complex *,
complex *, integer *, complex *, integer *, complex *, integer *,
real *, integer *), cget51_(integer *, integer *,
complex *, integer *, complex *, integer *, complex *, integer *,
complex *, integer *, complex *, real *, real *), cget52_(logical
*, integer *, complex *, integer *, complex *, integer *, complex
*, integer *, complex *, complex *, complex *, real *, real *);
static real dumma[4];
static integer iinfo;
static real rmagn[4];
static complex ctemp;
static integer nmats, jsize, nerrs, i1, jtype, ntest, n1;
extern /* Subroutine */ int clatm4_(integer *, integer *, integer *,
integer *, logical *, real *, real *, real *, integer *, integer *
, complex *, integer *), cunm2r_(char *, char *, integer *,
integer *, integer *, complex *, integer *, complex *, complex *,
integer *, complex *, integer *);
static integer jc, nb;
extern /* Subroutine */ int slabad_(real *, real *);
static integer in, jr;
extern /* Subroutine */ int clarfg_(integer *, complex *, complex *,
integer *, complex *);
static integer ns;
extern /* Complex */ VOID clarnd_(complex *, integer *, integer *);
extern doublereal slamch_(char *);
extern /* Subroutine */ int clacpy_(char *, integer *, integer *, complex
*, integer *, complex *, integer *);
static real safmin, safmax;
static integer ioldsd[4];
extern integer ilaenv_(integer *, char *, char *, integer *, integer *,
integer *, integer *, ftnlen, ftnlen);
extern /* Subroutine */ int alasvm_(char *, integer *, integer *, integer
*, integer *), claset_(char *, integer *, integer *,
complex *, complex *, complex *, integer *), xerbla_(char
*, integer *);
static real ulpinv;
static integer lwkopt, mtypes, ntestt, nbz;
static real ulp;
/* Fortran I/O blocks */
static cilist io___43 = { 0, 0, 0, fmt_9999, 0 };
static cilist io___44 = { 0, 0, 0, fmt_9999, 0 };
static cilist io___47 = { 0, 0, 0, fmt_9999, 0 };
static cilist io___49 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___50 = { 0, 0, 0, fmt_9998, 0 };
static cilist io___51 = { 0, 0, 0, fmt_9997, 0 };
static cilist io___52 = { 0, 0, 0, fmt_9996, 0 };
static cilist io___53 = { 0, 0, 0, fmt_9995, 0 };
static cilist io___54 = { 0, 0, 0, fmt_9994, 0 };
static cilist io___55 = { 0, 0, 0, fmt_9993, 0 };
static cilist io___56 = { 0, 0, 0, fmt_9992, 0 };
static cilist io___57 = { 0, 0, 0, fmt_9991, 0 };
#define a_subscr(a_1,a_2) (a_2)*a_dim1 + a_1
#define a_ref(a_1,a_2) a[a_subscr(a_1,a_2)]
#define b_subscr(a_1,a_2) (a_2)*b_dim1 + a_1
#define b_ref(a_1,a_2) b[b_subscr(a_1,a_2)]
#define q_subscr(a_1,a_2) (a_2)*q_dim1 + a_1
#define q_ref(a_1,a_2) q[q_subscr(a_1,a_2)]
#define s_subscr(a_1,a_2) (a_2)*s_dim1 + a_1
#define s_ref(a_1,a_2) s[s_subscr(a_1,a_2)]
#define t_subscr(a_1,a_2) (a_2)*t_dim1 + a_1
#define t_ref(a_1,a_2) t[t_subscr(a_1,a_2)]
#define z___subscr(a_1,a_2) (a_2)*z_dim1 + a_1
#define z___ref(a_1,a_2) z__[z___subscr(a_1,a_2)]
/* -- LAPACK test routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
September 30, 1994
Purpose
=======
CDRVGG checks the nonsymmetric generalized eigenvalue driver
routines.
T T T
CGEGS factors A and B as Q S Z and Q T Z , where means
transpose, T is upper triangular, S is in generalized Schur form
(upper triangular), and Q and Z are unitary. It also
computes the generalized eigenvalues (alpha(1),beta(1)), ...,
(alpha(n),beta(n)), where alpha(j)=S(j,j) and beta(j)=T(j,j) --
thus, w(j) = alpha(j)/beta(j) is a root of the generalized
eigenvalue problem
det( A - w(j) B ) = 0
and m(j) = beta(j)/alpha(j) is a root of the essentially equivalent
problem
det( m(j) A - B ) = 0
CGEGV computes the generalized eigenvalues (alpha(1),beta(1)), ...,
(alpha(n),beta(n)), the matrix L whose columns contain the
generalized left eigenvectors l, and the matrix R whose columns
contain the generalized right eigenvectors r for the pair (A,B).
When CDRVGG is called, a number of matrix "sizes" ("n's") and a
number of matrix "types" are specified. For each size ("n")
and each type of matrix, one matrix will be generated and used
to test the nonsymmetric eigenroutines. For each matrix, 7
tests will be performed and compared with the threshhold THRESH:
Results from CGEGS:
H
(1) | A - Q S Z | / ( |A| n ulp )
H
(2) | B - Q T Z | / ( |B| n ulp )
H
(3) | I - QQ | / ( n ulp )
H
(4) | I - ZZ | / ( n ulp )
(5) maximum over j of D(j) where:
|alpha(j) - S(j,j)| |beta(j) - T(j,j)|
D(j) = ------------------------ + -----------------------
max(|alpha(j)|,|S(j,j)|) max(|beta(j)|,|T(j,j)|)
Results from CGEGV:
(6) max over all left eigenvalue/-vector pairs (beta/alpha,l) of
| l**H * (beta A - alpha B) | / ( ulp max( |beta A|, |alpha B| ) )
where l**H is the conjugate tranpose of l.
(7) max over all right eigenvalue/-vector pairs (beta/alpha,r) of
| (beta A - alpha B) r | / ( ulp max( |beta A|, |alpha B| ) )
Test Matrices
---- --------
The sizes of the test matrices are specified by an array
NN(1:NSIZES); the value of each element NN(j) specifies one size.
The "types" are specified by a logical array DOTYPE( 1:NTYPES ); if
DOTYPE(j) is .TRUE., then matrix type "j" will be generated.
Currently, the list of possible types is:
(1) ( 0, 0 ) (a pair of zero matrices)
(2) ( I, 0 ) (an identity and a zero matrix)
(3) ( 0, I ) (an identity and a zero matrix)
(4) ( I, I ) (a pair of identity matrices)
t t
(5) ( J , J ) (a pair of transposed Jordan blocks)
t ( I 0 )
(6) ( X, Y ) where X = ( J 0 ) and Y = ( t )
( 0 I ) ( 0 J )
and I is a k x k identity and J a (k+1)x(k+1)
Jordan block; k=(N-1)/2
(7) ( D, I ) where D is diag( 0, 1,..., N-1 ) (a diagonal
matrix with those diagonal entries.)
(8) ( I, D )
(9) ( big*D, small*I ) where "big" is near overflow and small=1/big
(10) ( small*D, big*I )
(11) ( big*I, small*D )
(12) ( small*I, big*D )
(13) ( big*D, big*I )
(14) ( small*D, small*I )
(15) ( D1, D2 ) where D1 is diag( 0, 0, 1, ..., N-3, 0 ) and
D2 is diag( 0, N-3, N-4,..., 1, 0, 0 )
t t
(16) Q ( J , J ) Z where Q and Z are random unitary matrices.
(17) Q ( T1, T2 ) Z where T1 and T2 are upper triangular matrices
with random O(1) entries above the diagonal
and diagonal entries diag(T1) =
( 0, 0, 1, ..., N-3, 0 ) and diag(T2) =
( 0, N-3, N-4,..., 1, 0, 0 )
(18) Q ( T1, T2 ) Z diag(T1) = ( 0, 0, 1, 1, s, ..., s, 0 )
diag(T2) = ( 0, 1, 0, 1,..., 1, 0 )
s = machine precision.
(19) Q ( T1, T2 ) Z diag(T1)=( 0,0,1,1, 1-d, ..., 1-(N-5)*d=s, 0 )
diag(T2) = ( 0, 1, 0, 1, ..., 1, 0 )
N-5
(20) Q ( T1, T2 ) Z diag(T1)=( 0, 0, 1, 1, a, ..., a =s, 0 )
diag(T2) = ( 0, 1, 0, 1, ..., 1, 0, 0 )
(21) Q ( T1, T2 ) Z diag(T1)=( 0, 0, 1, r1, r2, ..., r(N-4), 0 )
diag(T2) = ( 0, 1, 0, 1, ..., 1, 0, 0 )
where r1,..., r(N-4) are random.
(22) Q ( big*T1, small*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
diag(T2) = ( 0, 1, ..., 1, 0, 0 )
(23) Q ( small*T1, big*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
diag(T2) = ( 0, 1, ..., 1, 0, 0 )
(24) Q ( small*T1, small*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
diag(T2) = ( 0, 1, ..., 1, 0, 0 )
(25) Q ( big*T1, big*T2 ) Z diag(T1) = ( 0, 0, 1, ..., N-3, 0 )
diag(T2) = ( 0, 1, ..., 1, 0, 0 )
(26) Q ( T1, T2 ) Z where T1 and T2 are random upper-triangular
matrices.
Arguments
=========
NSIZES (input) INTEGER
The number of sizes of matrices to use. If it is zero,
CDRVGG does nothing. It must be at least zero.
NN (input) INTEGER array, dimension (NSIZES)
An array containing the sizes to be used for the matrices.
Zero values will be skipped. The values must be at least
zero.
NTYPES (input) INTEGER
The number of elements in DOTYPE. If it is zero, CDRVGG
does nothing. It must be at least zero. If it is MAXTYP+1
and NSIZES is 1, then an additional type, MAXTYP+1 is
defined, which is to use whatever matrix is in A. This
is only useful if DOTYPE(1:MAXTYP) is .FALSE. and
DOTYPE(MAXTYP+1) is .TRUE. .
DOTYPE (input) LOGICAL array, dimension (NTYPES)
If DOTYPE(j) is .TRUE., then for each size in NN a
matrix of that size and of type j will be generated.
If NTYPES is smaller than the maximum number of types
defined (PARAMETER MAXTYP), then types NTYPES+1 through
MAXTYP will not be generated. If NTYPES is larger
than MAXTYP, DOTYPE(MAXTYP+1) through DOTYPE(NTYPES)
will be ignored.
ISEED (input/output) INTEGER array, dimension (4)
On entry ISEED specifies the seed of the random number
generator. The array elements should be between 0 and 4095;
if not they will be reduced mod 4096. Also, ISEED(4) must
be odd. The random number generator uses a linear
congruential sequence limited to small integers, and so
should produce machine independent random numbers. The
values of ISEED are changed on exit, and can be used in the
next call to CDRVGG to continue the same random number
sequence.
THRESH (input) REAL
A test will count as "failed" if the "error", computed as
described above, exceeds THRESH. Note that the error is
scaled to be O(1), so THRESH should be a reasonably small
multiple of 1, e.g., 10 or 100. In particular, it should
not depend on the precision (single vs. double) or the size
of the matrix. It must be at least zero.
THRSHN (input) REAL
Threshhold for reporting eigenvector normalization error.
If the normalization of any eigenvector differs from 1 by
more than THRSHN*ulp, then a special error message will be
printed. (This is handled separately from the other tests,
since only a compiler or programming error should cause an
error message, at least if THRSHN is at least 5--10.)
NOUNIT (input) INTEGER
The FORTRAN unit number for printing out error messages
(e.g., if a routine returns IINFO not equal to 0.)
A (input/workspace) COMPLEX array, dimension (LDA, max(NN))
Used to hold the original A matrix. Used as input only
if NTYPES=MAXTYP+1, DOTYPE(1:MAXTYP)=.FALSE., and
DOTYPE(MAXTYP+1)=.TRUE.
LDA (input) INTEGER
The leading dimension of A, B, S, T, S2, and T2.
It must be at least 1 and at least max( NN ).
B (input/workspace) COMPLEX array, dimension (LDA, max(NN))
Used to hold the original B matrix. Used as input only
if NTYPES=MAXTYP+1, DOTYPE(1:MAXTYP)=.FALSE., and
DOTYPE(MAXTYP+1)=.TRUE.
S (workspace) COMPLEX array, dimension (LDA, max(NN))
The upper triangular matrix computed from A by CGEGS.
T (workspace) COMPLEX array, dimension (LDA, max(NN))
The upper triangular matrix computed from B by CGEGS.
S2 (workspace) COMPLEX array, dimension (LDA, max(NN))
The matrix computed from A by CGEGV. This will be the
Schur (upper triangular) form of some matrix related to A,
but will not, in general, be the same as S.
T2 (workspace) COMPLEX array, dimension (LDA, max(NN))
The matrix computed from B by CGEGV. This will be the
Schur form of some matrix related to B, but will not, in
general, be the same as T.
Q (workspace) COMPLEX array, dimension (LDQ, max(NN))
The (left) unitary matrix computed by CGEGS.
LDQ (input) INTEGER
The leading dimension of Q, Z, VL, and VR. It must
be at least 1 and at least max( NN ).
Z (workspace) COMPLEX array, dimension (LDQ, max(NN))
The (right) unitary matrix computed by CGEGS.
ALPHA1 (workspace) COMPLEX array, dimension (max(NN))
BETA1 (workspace) COMPLEX array, dimension (max(NN))
The generalized eigenvalues of (A,B) computed by CGEGS.
ALPHA1(k) / BETA1(k) is the k-th generalized eigenvalue of
the matrices in A and B.
ALPHA2 (workspace) COMPLEX array, dimension (max(NN))
BETA2 (workspace) COMPLEX array, dimension (max(NN))
The generalized eigenvalues of (A,B) computed by CGEGV.
ALPHA2(k) / BETA2(k) is the k-th generalized eigenvalue of
the matrices in A and B.
VL (workspace) COMPLEX array, dimension (LDQ, max(NN))
The (lower triangular) left eigenvector matrix for the
matrices in A and B.
VR (workspace) COMPLEX array, dimension (LDQ, max(NN))
The (upper triangular) right eigenvector matrix for the
matrices in A and B.
WORK (workspace) COMPLEX array, dimension (LWORK)
LWORK (input) INTEGER
The number of entries in WORK. This must be at least
MAX( 2*N, N*(NB+1), (k+1)*(2*k+N+1) ), where "k" is the
sum of the blocksize and number-of-shifts for CHGEQZ, and
NB is the greatest of the blocksizes for CGEQRF, CUNMQR,
and CUNGQR. (The blocksizes and the number-of-shifts are
retrieved through calls to ILAENV.)
RWORK (workspace) REAL array, dimension (8*N)
RESULT (output) REAL array, dimension (7)
The values computed by the tests described above.
The values are currently limited to 1/ulp, to avoid
overflow.
INFO (output) INTEGER
= 0: successful exit
< 0: if INFO = -i, the i-th argument had an illegal value.
> 0: A routine returned an error code. INFO is the
absolute value of the INFO value returned.
=====================================================================
Parameter adjustments */
--nn;
--dotype;
--iseed;
t2_dim1 = *lda;
t2_offset = 1 + t2_dim1 * 1;
t2 -= t2_offset;
s2_dim1 = *lda;
s2_offset = 1 + s2_dim1 * 1;
s2 -= s2_offset;
t_dim1 = *lda;
t_offset = 1 + t_dim1 * 1;
t -= t_offset;
s_dim1 = *lda;
s_offset = 1 + s_dim1 * 1;
s -= s_offset;
b_dim1 = *lda;
b_offset = 1 + b_dim1 * 1;
b -= b_offset;
a_dim1 = *lda;
a_offset = 1 + a_dim1 * 1;
a -= a_offset;
vr_dim1 = *ldq;
vr_offset = 1 + vr_dim1 * 1;
vr -= vr_offset;
vl_dim1 = *ldq;
vl_offset = 1 + vl_dim1 * 1;
vl -= vl_offset;
z_dim1 = *ldq;
z_offset = 1 + z_dim1 * 1;
z__ -= z_offset;
q_dim1 = *ldq;
q_offset = 1 + q_dim1 * 1;
q -= q_offset;
--alpha1;
--beta1;
--alpha2;
--beta2;
--work;
--rwork;
--result;
/* Function Body
Check for errors */
*info = 0;
badnn = FALSE_;
nmax = 1;
i__1 = *nsizes;
for (j = 1; j <= i__1; ++j) {
/* Computing MAX */
i__2 = nmax, i__3 = nn[j];
nmax = max(i__2,i__3);
if (nn[j] < 0) {
badnn = TRUE_;
}
/* L10: */
}
/* Maximum blocksize and shift -- we assume that blocksize and number
of shifts are monotone increasing functions of N.
Computing MAX */
i__1 = 1, i__2 = ilaenv_(&c__1, "CGEQRF", " ", &nmax, &nmax, &c_n1, &c_n1,
(ftnlen)6, (ftnlen)1), i__1 = max(i__1,i__2), i__2 = ilaenv_(&
c__1, "CUNMQR", "LC", &nmax, &nmax, &nmax, &c_n1, (ftnlen)6, (
ftnlen)2), i__1 = max(i__1,i__2), i__2 = ilaenv_(&c__1, "CUNGQR",
" ", &nmax, &nmax, &nmax, &c_n1, (ftnlen)6, (ftnlen)1);
nb = max(i__1,i__2);
nbz = ilaenv_(&c__1, "CHGEQZ", "SII", &nmax, &c__1, &nmax, &c__0, (ftnlen)
6, (ftnlen)3);
ns = ilaenv_(&c__4, "CHGEQZ", "SII", &nmax, &c__1, &nmax, &c__0, (ftnlen)
6, (ftnlen)3);
i1 = nbz + ns;
/* Computing MAX */
i__1 = nmax << 1, i__2 = nmax * (nb + 1), i__1 = max(i__1,i__2), i__2 = ((
i1 << 1) + nmax + 1) * (i1 + 1);
lwkopt = max(i__1,i__2);
/* Check for errors */
if (*nsizes < 0) {
*info = -1;
} else if (badnn) {
*info = -2;
} else if (*ntypes < 0) {
*info = -3;
} else if (*thresh < 0.f) {
*info = -6;
} else if (*lda <= 1 || *lda < nmax) {
*info = -10;
} else if (*ldq <= 1 || *ldq < nmax) {
*info = -19;
} else if (lwkopt > *lwork) {
*info = -30;
}
if (*info != 0) {
i__1 = -(*info);
xerbla_("CDRVGG", &i__1);
return 0;
}
/* Quick return if possible */
if (*nsizes == 0 || *ntypes == 0) {
return 0;
}
ulp = slamch_("Precision");
safmin = slamch_("Safe minimum");
safmin /= ulp;
safmax = 1.f / safmin;
slabad_(&safmin, &safmax);
ulpinv = 1.f / ulp;
/* The values RMAGN(2:3) depend on N, see below. */
rmagn[0] = 0.f;
rmagn[1] = 1.f;
/* Loop over sizes, types */
ntestt = 0;
nerrs = 0;
nmats = 0;
i__1 = *nsizes;
for (jsize = 1; jsize <= i__1; ++jsize) {
n = nn[jsize];
n1 = max(1,n);
rmagn[2] = safmax * ulp / (real) n1;
rmagn[3] = safmin * ulpinv * n1;
if (*nsizes != 1) {
mtypes = min(26,*ntypes);
} else {
mtypes = min(27,*ntypes);
}
i__2 = mtypes;
for (jtype = 1; jtype <= i__2; ++jtype) {
if (! dotype[jtype]) {
goto L150;
}
++nmats;
ntest = 0;
/* Save ISEED in case of an error. */
for (j = 1; j <= 4; ++j) {
ioldsd[j - 1] = iseed[j];
/* L20: */
}
/* Initialize RESULT */
for (j = 1; j <= 7; ++j) {
result[j] = 0.f;
/* L30: */
}
/* Compute A and B
Description of control parameters:
KCLASS: =1 means w/o rotation, =2 means w/ rotation,
=3 means random.
KATYPE: the "type" to be passed to CLATM4 for computing A.
KAZERO: the pattern of zeros on the diagonal for A:
=1: ( xxx ), =2: (0, xxx ) =3: ( 0, 0, xxx, 0 ),
=4: ( 0, xxx, 0, 0 ), =5: ( 0, 0, 1, xxx, 0 ),
=6: ( 0, 1, 0, xxx, 0 ). (xxx means a string of
non-zero entries.)
KAMAGN: the magnitude of the matrix: =0: zero, =1: O(1),
=2: large, =3: small.
LASIGN: .TRUE. if the diagonal elements of A are to be
multiplied by a random magnitude 1 number.
KBTYPE, KBZERO, KBMAGN, IBSIGN: the same, but for B.
KTRIAN: =0: don't fill in the upper triangle, =1: do.
KZ1, KZ2, KADD: used to implement KAZERO and KBZERO.
RMAGN: used to implement KAMAGN and KBMAGN. */
if (mtypes > 26) {
goto L110;
}
iinfo = 0;
if (kclass[jtype - 1] < 3) {
/* Generate A (w/o rotation) */
if ((i__3 = katype[jtype - 1], abs(i__3)) == 3) {
in = ((n - 1) / 2 << 1) + 1;
if (in != n) {
claset_("Full", &n, &n, &c_b1, &c_b1, &a[a_offset],
lda);
}
} else {
in = n;
}
clatm4_(&katype[jtype - 1], &in, &kz1[kazero[jtype - 1] - 1],
&kz2[kazero[jtype - 1] - 1], &lasign[jtype - 1], &
rmagn[kamagn[jtype - 1]], &ulp, &rmagn[ktrian[jtype -
1] * kamagn[jtype - 1]], &c__2, &iseed[1], &a[
a_offset], lda);
iadd = kadd[kazero[jtype - 1] - 1];
if (iadd > 0 && iadd <= n) {
i__3 = a_subscr(iadd, iadd);
i__4 = kamagn[jtype - 1];
a[i__3].r = rmagn[i__4], a[i__3].i = 0.f;
}
/* Generate B (w/o rotation) */
if ((i__3 = kbtype[jtype - 1], abs(i__3)) == 3) {
in = ((n - 1) / 2 << 1) + 1;
if (in != n) {
claset_("Full", &n, &n, &c_b1, &c_b1, &b[b_offset],
lda);
}
} else {
in = n;
}
clatm4_(&kbtype[jtype - 1], &in, &kz1[kbzero[jtype - 1] - 1],
&kz2[kbzero[jtype - 1] - 1], &lbsign[jtype - 1], &
rmagn[kbmagn[jtype - 1]], &c_b39, &rmagn[ktrian[jtype
- 1] * kbmagn[jtype - 1]], &c__2, &iseed[1], &b[
b_offset], lda);
iadd = kadd[kbzero[jtype - 1] - 1];
if (iadd != 0 && iadd <= n) {
i__3 = b_subscr(iadd, iadd);
i__4 = kbmagn[jtype - 1];
b[i__3].r = rmagn[i__4], b[i__3].i = 0.f;
}
if (kclass[jtype - 1] == 2 && n > 0) {
/* Include rotations
Generate Q, Z as Householder transformations times
a diagonal matrix. */
i__3 = n - 1;
for (jc = 1; jc <= i__3; ++jc) {
i__4 = n;
for (jr = jc; jr <= i__4; ++jr) {
i__5 = q_subscr(jr, jc);
clarnd_(&q__1, &c__3, &iseed[1]);
q[i__5].r = q__1.r, q[i__5].i = q__1.i;
i__5 = z___subscr(jr, jc);
clarnd_(&q__1, &c__3, &iseed[1]);
z__[i__5].r = q__1.r, z__[i__5].i = q__1.i;
/* L40: */
}
i__4 = n + 1 - jc;
clarfg_(&i__4, &q_ref(jc, jc), &q_ref(jc + 1, jc), &
c__1, &work[jc]);
i__4 = (n << 1) + jc;
i__5 = q_subscr(jc, jc);
r__2 = q[i__5].r;
r__1 = r_sign(&c_b39, &r__2);
work[i__4].r = r__1, work[i__4].i = 0.f;
i__4 = q_subscr(jc, jc);
q[i__4].r = 1.f, q[i__4].i = 0.f;
i__4 = n + 1 - jc;
clarfg_(&i__4, &z___ref(jc, jc), &z___ref(jc + 1, jc),
&c__1, &work[n + jc]);
i__4 = n * 3 + jc;
i__5 = z___subscr(jc, jc);
r__2 = z__[i__5].r;
r__1 = r_sign(&c_b39, &r__2);
work[i__4].r = r__1, work[i__4].i = 0.f;
i__4 = z___subscr(jc, jc);
z__[i__4].r = 1.f, z__[i__4].i = 0.f;
/* L50: */
}
clarnd_(&q__1, &c__3, &iseed[1]);
ctemp.r = q__1.r, ctemp.i = q__1.i;
i__3 = q_subscr(n, n);
q[i__3].r = 1.f, q[i__3].i = 0.f;
i__3 = n;
work[i__3].r = 0.f, work[i__3].i = 0.f;
i__3 = n * 3;
r__1 = c_abs(&ctemp);
q__1.r = ctemp.r / r__1, q__1.i = ctemp.i / r__1;
work[i__3].r = q__1.r, work[i__3].i = q__1.i;
clarnd_(&q__1, &c__3, &iseed[1]);
ctemp.r = q__1.r, ctemp.i = q__1.i;
i__3 = z___subscr(n, n);
z__[i__3].r = 1.f, z__[i__3].i = 0.f;
i__3 = n << 1;
work[i__3].r = 0.f, work[i__3].i = 0.f;
i__3 = n << 2;
r__1 = c_abs(&ctemp);
q__1.r = ctemp.r / r__1, q__1.i = ctemp.i / r__1;
work[i__3].r = q__1.r, work[i__3].i = q__1.i;
/* Apply the diagonal matrices */
i__3 = n;
for (jc = 1; jc <= i__3; ++jc) {
i__4 = n;
for (jr = 1; jr <= i__4; ++jr) {
i__5 = a_subscr(jr, jc);
i__6 = (n << 1) + jr;
r_cnjg(&q__3, &work[n * 3 + jc]);
q__2.r = work[i__6].r * q__3.r - work[i__6].i *
q__3.i, q__2.i = work[i__6].r * q__3.i +
work[i__6].i * q__3.r;
i__7 = a_subscr(jr, jc);
q__1.r = q__2.r * a[i__7].r - q__2.i * a[i__7].i,
q__1.i = q__2.r * a[i__7].i + q__2.i * a[
i__7].r;
a[i__5].r = q__1.r, a[i__5].i = q__1.i;
i__5 = b_subscr(jr, jc);
i__6 = (n << 1) + jr;
r_cnjg(&q__3, &work[n * 3 + jc]);
q__2.r = work[i__6].r * q__3.r - work[i__6].i *
q__3.i, q__2.i = work[i__6].r * q__3.i +
work[i__6].i * q__3.r;
i__7 = b_subscr(jr, jc);
q__1.r = q__2.r * b[i__7].r - q__2.i * b[i__7].i,
q__1.i = q__2.r * b[i__7].i + q__2.i * b[
i__7].r;
b[i__5].r = q__1.r, b[i__5].i = q__1.i;
/* L60: */
}
/* L70: */
}
i__3 = n - 1;
cunm2r_("L", "N", &n, &n, &i__3, &q[q_offset], ldq, &work[
1], &a[a_offset], lda, &work[(n << 1) + 1], &
iinfo);
if (iinfo != 0) {
goto L100;
}
i__3 = n - 1;
cunm2r_("R", "C", &n, &n, &i__3, &z__[z_offset], ldq, &
work[n + 1], &a[a_offset], lda, &work[(n << 1) +
1], &iinfo);
if (iinfo != 0) {
goto L100;
}
i__3 = n - 1;
cunm2r_("L", "N", &n, &n, &i__3, &q[q_offset], ldq, &work[
1], &b[b_offset], lda, &work[(n << 1) + 1], &
iinfo);
if (iinfo != 0) {
goto L100;
}
i__3 = n - 1;
cunm2r_("R", "C", &n, &n, &i__3, &z__[z_offset], ldq, &
work[n + 1], &b[b_offset], lda, &work[(n << 1) +
1], &iinfo);
if (iinfo != 0) {
goto L100;
}
}
} else {
/* Random matrices */
i__3 = n;
for (jc = 1; jc <= i__3; ++jc) {
i__4 = n;
for (jr = 1; jr <= i__4; ++jr) {
i__5 = a_subscr(jr, jc);
i__6 = kamagn[jtype - 1];
clarnd_(&q__2, &c__4, &iseed[1]);
q__1.r = rmagn[i__6] * q__2.r, q__1.i = rmagn[i__6] *
q__2.i;
a[i__5].r = q__1.r, a[i__5].i = q__1.i;
i__5 = b_subscr(jr, jc);
i__6 = kbmagn[jtype - 1];
clarnd_(&q__2, &c__4, &iseed[1]);
q__1.r = rmagn[i__6] * q__2.r, q__1.i = rmagn[i__6] *
q__2.i;
b[i__5].r = q__1.r, b[i__5].i = q__1.i;
/* L80: */
}
/* L90: */
}
}
L100:
if (iinfo != 0) {
io___43.ciunit = *nounit;
s_wsfe(&io___43);
do_fio(&c__1, "Generator", (ftnlen)9);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
*info = abs(iinfo);
return 0;
}
L110:
/* Call CGEGS to compute H, T, Q, Z, alpha, and beta. */
clacpy_(" ", &n, &n, &a[a_offset], lda, &s[s_offset], lda);
clacpy_(" ", &n, &n, &b[b_offset], lda, &t[t_offset], lda);
ntest = 1;
result[1] = ulpinv;
cgegs_("V", "V", &n, &s[s_offset], lda, &t[t_offset], lda, &
alpha1[1], &beta1[1], &q[q_offset], ldq, &z__[z_offset],
ldq, &work[1], lwork, &rwork[1], &iinfo);
if (iinfo != 0) {
io___44.ciunit = *nounit;
s_wsfe(&io___44);
do_fio(&c__1, "CGEGS", (ftnlen)5);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
*info = abs(iinfo);
goto L130;
}
ntest = 4;
/* Do tests 1--4 */
cget51_(&c__1, &n, &a[a_offset], lda, &s[s_offset], lda, &q[
q_offset], ldq, &z__[z_offset], ldq, &work[1], &rwork[1],
&result[1]);
cget51_(&c__1, &n, &b[b_offset], lda, &t[t_offset], lda, &q[
q_offset], ldq, &z__[z_offset], ldq, &work[1], &rwork[1],
&result[2]);
cget51_(&c__3, &n, &b[b_offset], lda, &t[t_offset], lda, &q[
q_offset], ldq, &q[q_offset], ldq, &work[1], &rwork[1], &
result[3]);
cget51_(&c__3, &n, &b[b_offset], lda, &t[t_offset], lda, &z__[
z_offset], ldq, &z__[z_offset], ldq, &work[1], &rwork[1],
&result[4]);
/* Do test 5: compare eigenvalues with diagonals. */
temp1 = 0.f;
i__3 = n;
for (j = 1; j <= i__3; ++j) {
i__4 = j;
i__5 = s_subscr(j, j);
q__2.r = alpha1[i__4].r - s[i__5].r, q__2.i = alpha1[i__4].i
- s[i__5].i;
q__1.r = q__2.r, q__1.i = q__2.i;
i__6 = j;
i__7 = t_subscr(j, j);
q__4.r = beta1[i__6].r - t[i__7].r, q__4.i = beta1[i__6].i -
t[i__7].i;
q__3.r = q__4.r, q__3.i = q__4.i;
/* Computing MAX */
i__8 = j;
i__9 = s_subscr(j, j);
r__13 = safmin, r__14 = (r__1 = alpha1[i__8].r, dabs(r__1)) +
(r__2 = r_imag(&alpha1[j]), dabs(r__2)), r__13 = max(
r__13,r__14), r__14 = (r__3 = s[i__9].r, dabs(r__3))
+ (r__4 = r_imag(&s_ref(j, j)), dabs(r__4));
/* Computing MAX */
i__10 = j;
i__11 = t_subscr(j, j);
r__15 = safmin, r__16 = (r__5 = beta1[i__10].r, dabs(r__5)) +
(r__6 = r_imag(&beta1[j]), dabs(r__6)), r__15 = max(
r__15,r__16), r__16 = (r__7 = t[i__11].r, dabs(r__7))
+ (r__8 = r_imag(&t_ref(j, j)), dabs(r__8));
temp2 = (((r__9 = q__1.r, dabs(r__9)) + (r__10 = r_imag(&q__1)
, dabs(r__10))) / dmax(r__13,r__14) + ((r__11 =
q__3.r, dabs(r__11)) + (r__12 = r_imag(&q__3), dabs(
r__12))) / dmax(r__15,r__16)) / ulp;
temp1 = dmax(temp1,temp2);
/* L120: */
}
result[5] = temp1;
/* Call CGEGV to compute S2, T2, VL, and VR, do tests.
Eigenvalues and Eigenvectors */
clacpy_(" ", &n, &n, &a[a_offset], lda, &s2[s2_offset], lda);
clacpy_(" ", &n, &n, &b[b_offset], lda, &t2[t2_offset], lda);
ntest = 6;
result[6] = ulpinv;
cgegv_("V", "V", &n, &s2[s2_offset], lda, &t2[t2_offset], lda, &
alpha2[1], &beta2[1], &vl[vl_offset], ldq, &vr[vr_offset],
ldq, &work[1], lwork, &rwork[1], &iinfo);
if (iinfo != 0) {
io___47.ciunit = *nounit;
s_wsfe(&io___47);
do_fio(&c__1, "CGEGV", (ftnlen)5);
do_fio(&c__1, (char *)&iinfo, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
*info = abs(iinfo);
goto L130;
}
ntest = 7;
/* Do Tests 6 and 7 */
cget52_(&c_true, &n, &a[a_offset], lda, &b[b_offset], lda, &vl[
vl_offset], ldq, &alpha2[1], &beta2[1], &work[1], &rwork[
1], dumma);
result[6] = dumma[0];
if (dumma[1] > *thrshn) {
io___49.ciunit = *nounit;
s_wsfe(&io___49);
do_fio(&c__1, "Left", (ftnlen)4);
do_fio(&c__1, "CGEGV", (ftnlen)5);
do_fio(&c__1, (char *)&dumma[1], (ftnlen)sizeof(real));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
}
cget52_(&c_false, &n, &a[a_offset], lda, &b[b_offset], lda, &vr[
vr_offset], ldq, &alpha2[1], &beta2[1], &work[1], &rwork[
1], dumma);
result[7] = dumma[0];
if (dumma[1] > *thresh) {
io___50.ciunit = *nounit;
s_wsfe(&io___50);
do_fio(&c__1, "Right", (ftnlen)5);
do_fio(&c__1, "CGEGV", (ftnlen)5);
do_fio(&c__1, (char *)&dumma[1], (ftnlen)sizeof(real));
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer));
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(integer));
e_wsfe();
}
/* End of Loop -- Check for RESULT(j) > THRESH */
L130:
ntestt += ntest;
/* Print out tests which fail. */
i__3 = ntest;
for (jr = 1; jr <= i__3; ++jr) {
if (result[jr] >= *thresh) {
/* If this is the first test to fail,
print a header to the data file. */
if (nerrs == 0) {
io___51.ciunit = *nounit;
s_wsfe(&io___51);
do_fio(&c__1, "CGG", (ftnlen)3);
e_wsfe();
/* Matrix types */
io___52.ciunit = *nounit;
s_wsfe(&io___52);
e_wsfe();
io___53.ciunit = *nounit;
s_wsfe(&io___53);
e_wsfe();
io___54.ciunit = *nounit;
s_wsfe(&io___54);
do_fio(&c__1, "Unitary", (ftnlen)7);
e_wsfe();
/* Tests performed */
io___55.ciunit = *nounit;
s_wsfe(&io___55);
do_fio(&c__1, "unitary", (ftnlen)7);
do_fio(&c__1, "*", (ftnlen)1);
do_fio(&c__1, "conjugate transpose", (ftnlen)19);
for (j = 1; j <= 5; ++j) {
do_fio(&c__1, "*", (ftnlen)1);
}
e_wsfe();
}
++nerrs;
if (result[jr] < 1e4f) {
io___56.ciunit = *nounit;
s_wsfe(&io___56);
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer))
;
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(
integer));
do_fio(&c__1, (char *)&jr, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&result[jr], (ftnlen)sizeof(
real));
e_wsfe();
} else {
io___57.ciunit = *nounit;
s_wsfe(&io___57);
do_fio(&c__1, (char *)&n, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&jtype, (ftnlen)sizeof(integer))
;
do_fio(&c__4, (char *)&ioldsd[0], (ftnlen)sizeof(
integer));
do_fio(&c__1, (char *)&jr, (ftnlen)sizeof(integer));
do_fio(&c__1, (char *)&result[jr], (ftnlen)sizeof(
real));
e_wsfe();
}
}
/* L140: */
}
L150:
;
}
/* L160: */
}
/* Summary */
alasvm_("CGG", nounit, &nerrs, &ntestt, &c__0);
return 0;
/* End of CDRVGG */
} /* cdrvgg_ */
/* Subroutine */ int ctrexc_(char *compq, integer *n, complex *t, integer *
ldt, complex *q, integer *ldq, integer *ifst, integer *ilst, integer *
info)
{
/* -- LAPACK routine (version 3.0) --
Univ. of Tennessee, Univ. of California Berkeley, NAG Ltd.,
Courant Institute, Argonne National Lab, and Rice University
March 31, 1993
Purpose
=======
CTREXC reorders the Schur factorization of a complex matrix
A = Q*T*Q**H, so that the diagonal element of T with row index IFST
is moved to row ILST.
The Schur form T is reordered by a unitary similarity transformation
Z**H*T*Z, and optionally the matrix Q of Schur vectors is updated by
postmultplying it with Z.
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) COMPLEX array, dimension (LDT,N)
On entry, the upper triangular matrix T.
On exit, the reordered upper triangular matrix.
LDT (input) INTEGER
The leading dimension of the array T. LDT >= max(1,N).
Q (input/output) COMPLEX 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
unitary 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) INTEGER
ILST (input) INTEGER
Specify the reordering of the diagonal elements of T:
The element with row index IFST is moved to row ILST by a
sequence of transpositions between adjacent elements.
1 <= IFST <= N; 1 <= ILST <= 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 */
/* Table of constant values */
static integer c__1 = 1;
/* System generated locals */
integer q_dim1, q_offset, t_dim1, t_offset, i__1, i__2, i__3;
complex q__1;
/* Builtin functions */
void r_cnjg(complex *, complex *);
/* Local variables */
static complex temp;
extern /* Subroutine */ int crot_(integer *, complex *, integer *,
complex *, integer *, real *, complex *);
static integer k;
extern logical lsame_(char *, char *);
static logical wantq;
static integer m1, m2, m3;
static real cs;
static complex t11, t22, sn;
extern /* Subroutine */ int clartg_(complex *, complex *, real *, complex
*, complex *), xerbla_(char *, integer *);
#define q_subscr(a_1,a_2) (a_2)*q_dim1 + a_1
#define q_ref(a_1,a_2) q[q_subscr(a_1,a_2)]
#define t_subscr(a_1,a_2) (a_2)*t_dim1 + a_1
#define t_ref(a_1,a_2) t[t_subscr(a_1,a_2)]
t_dim1 = *ldt;
t_offset = 1 + t_dim1 * 1;
t -= t_offset;
q_dim1 = *ldq;
q_offset = 1 + q_dim1 * 1;
q -= q_offset;
/* Function Body */
*info = 0;
wantq = lsame_(compq, "V");
if (! lsame_(compq, "N") && ! wantq) {
*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_("CTREXC", &i__1);
return 0;
}
/* Quick return if possible */
if (*n == 1 || *ifst == *ilst) {
return 0;
}
if (*ifst < *ilst) {
/* Move the IFST-th diagonal element forward down the diagonal. */
m1 = 0;
m2 = -1;
m3 = 1;
} else {
/* Move the IFST-th diagonal element backward up the diagonal. */
m1 = -1;
m2 = 0;
m3 = -1;
}
i__1 = *ilst + m2;
i__2 = m3;
for (k = *ifst + m1; i__2 < 0 ? k >= i__1 : k <= i__1; k += i__2) {
/* Interchange the k-th and (k+1)-th diagonal elements. */
i__3 = t_subscr(k, k);
t11.r = t[i__3].r, t11.i = t[i__3].i;
i__3 = t_subscr(k + 1, k + 1);
t22.r = t[i__3].r, t22.i = t[i__3].i;
/* Determine the transformation to perform the interchange. */
q__1.r = t22.r - t11.r, q__1.i = t22.i - t11.i;
clartg_(&t_ref(k, k + 1), &q__1, &cs, &sn, &temp);
/* Apply transformation to the matrix T. */
if (k + 2 <= *n) {
i__3 = *n - k - 1;
crot_(&i__3, &t_ref(k, k + 2), ldt, &t_ref(k + 1, k + 2), ldt, &
cs, &sn);
}
i__3 = k - 1;
r_cnjg(&q__1, &sn);
crot_(&i__3, &t_ref(1, k), &c__1, &t_ref(1, k + 1), &c__1, &cs, &q__1)
;
i__3 = t_subscr(k, k);
t[i__3].r = t22.r, t[i__3].i = t22.i;
i__3 = t_subscr(k + 1, k + 1);
t[i__3].r = t11.r, t[i__3].i = t11.i;
if (wantq) {
/* Accumulate transformation in the matrix Q. */
r_cnjg(&q__1, &sn);
crot_(n, &q_ref(1, k), &c__1, &q_ref(1, k + 1), &c__1, &cs, &q__1)
;
}
/* L10: */
}
return 0;
/* End of CTREXC */
} /* ctrexc_ */
