dsyevd_2stage function
void
dsyevd_2stage()
Implementation
void dsyevd_2stage(
final String JOBZ,
final String UPLO,
final int N,
final Matrix<double> A_,
final int LDA,
final Array<double> W_,
final Array<double> WORK_,
final int LWORK,
final Array<int> IWORK_,
final int LIWORK,
final Box<int> INFO,
) {
final A = A_.having(ld: LDA);
final W = W_.having();
final WORK = WORK_.having();
final IWORK = IWORK_.having();
const ZERO = 0.0, ONE = 1.0;
bool LOWER, LQUERY, WANTZ;
int INDE,
INDTAU,
// INDWK2,
INDWRK,
ISCALE,
LIWMIN = 0,
LLWORK,
// LLWRK2,
LWMIN = 0,
LHTRD = 0,
LWTRD,
KD,
IB,
INDHOUS;
double ANRM, BIGNUM, EPS, RMAX, RMIN, SAFMIN, SIGMA = 0, SMLNUM;
final IINFO = Box(0);
// Test the input parameters.
WANTZ = lsame(JOBZ, 'V');
LOWER = lsame(UPLO, 'L');
LQUERY = (LWORK == -1 || LIWORK == -1);
INFO.value = 0;
if (!(lsame(JOBZ, 'N'))) {
INFO.value = -1;
} else if (!(LOWER || lsame(UPLO, 'U'))) {
INFO.value = -2;
} else if (N < 0) {
INFO.value = -3;
} else if (LDA < max(1, N)) {
INFO.value = -5;
}
if (INFO.value == 0) {
if (N <= 1) {
LIWMIN = 1;
LWMIN = 1;
} else {
KD = ilaenv2stage(1, 'DSYTRD_2STAGE', JOBZ, N, -1, -1, -1);
IB = ilaenv2stage(2, 'DSYTRD_2STAGE', JOBZ, N, KD, -1, -1);
LHTRD = ilaenv2stage(3, 'DSYTRD_2STAGE', JOBZ, N, KD, IB, -1);
LWTRD = ilaenv2stage(4, 'DSYTRD_2STAGE', JOBZ, N, KD, IB, -1);
if (WANTZ) {
LIWMIN = 3 + 5 * N;
LWMIN = 1 + 6 * N + 2 * pow(N, 2).toInt();
} else {
LIWMIN = 1;
LWMIN = 2 * N + 1 + LHTRD + LWTRD;
}
}
WORK[1] = LWMIN.toDouble();
IWORK[1] = LIWMIN;
if (LWORK < LWMIN && !LQUERY) {
INFO.value = -8;
} else if (LIWORK < LIWMIN && !LQUERY) {
INFO.value = -10;
}
}
if (INFO.value != 0) {
xerbla('DSYEVD_2STAGE', -INFO.value);
return;
} else if (LQUERY) {
return;
}
// Quick return if possible
if (N == 0) return;
if (N == 1) {
W[1] = A[1][1];
if (WANTZ) A[1][1] = ONE;
return;
}
// Get machine constants.
SAFMIN = dlamch('Safe minimum');
EPS = dlamch('Precision');
SMLNUM = SAFMIN / EPS;
BIGNUM = ONE / SMLNUM;
RMIN = sqrt(SMLNUM);
RMAX = sqrt(BIGNUM);
// Scale matrix to allowable range, if necessary.
ANRM = dlansy('M', UPLO, N, A, LDA, WORK);
ISCALE = 0;
if (ANRM > ZERO && ANRM < RMIN) {
ISCALE = 1;
SIGMA = RMIN / ANRM;
} else if (ANRM > RMAX) {
ISCALE = 1;
SIGMA = RMAX / ANRM;
}
if (ISCALE == 1) dlascl(UPLO, 0, 0, ONE, SIGMA, N, N, A, LDA, INFO);
// Call DSYTRD_2STAGE to reduce symmetric matrix to tridiagonal form.
INDE = 1;
INDTAU = INDE + N;
INDHOUS = INDTAU + N;
INDWRK = INDHOUS + LHTRD;
LLWORK = LWORK - INDWRK + 1;
// INDWK2 = INDWRK + N * N;
// LLWRK2 = LWORK - INDWK2 + 1;
dsytrd_2stage(JOBZ, UPLO, N, A, LDA, W, WORK(INDE), WORK(INDTAU),
WORK(INDHOUS), LHTRD, WORK(INDWRK), LLWORK, IINFO);
// 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, WORK(INDE), INFO);
} else {
// Not available in this release, and argument checking should not
// let it getting here
return;
// dstedc('I', N, W, WORK(INDE), WORK(INDWRK), N, WORK(INDWK2), LLWRK2, IWORK,
// LIWORK, INFO);
// dormtr('L', UPLO, 'N', N, N, A, LDA, WORK(INDTAU), WORK(INDWRK), N,
// WORK(INDWK2), LLWRK2, IINFO);
// dlacpy('A', N, N, WORK(INDWRK), N, A, LDA);
}
// If matrix was scaled, then rescale eigenvalues appropriately.
if (ISCALE == 1) dscal(N, ONE / SIGMA, W, 1);
WORK[1] = LWMIN.toDouble();
IWORK[1] = LIWMIN;
}