Provided by: liblapack-doc-man_3.5.0-2ubuntu1_all 
NAME
dlaqr4.f -
SYNOPSIS
Functions/Subroutines
subroutine dlaqr4 (WANTT, WANTZ, N, ILO, IHI, H, LDH, WR, WI, ILOZ, IHIZ, Z, LDZ, WORK,
LWORK, INFO)
DLAQR4 computes the eigenvalues of a Hessenberg matrix, and optionally the matrices
from the Schur decomposition.
Function/Subroutine Documentation
subroutine dlaqr4 (logicalWANTT, logicalWANTZ, integerN, integerILO, integerIHI, double
precision, dimension( ldh, * )H, integerLDH, double precision, dimension( * )WR, double
precision, dimension( * )WI, integerILOZ, integerIHIZ, double precision, dimension( ldz, *
)Z, integerLDZ, double precision, dimension( * )WORK, integerLWORK, integerINFO)
DLAQR4 computes the eigenvalues of a Hessenberg matrix, and optionally the matrices from
the Schur decomposition.
Purpose:
DLAQR4 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.
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.
Parameters:
WANTT
WANTT is LOGICAL
= .TRUE. : the full Schur form T is required;
= .FALSE.: only eigenvalues are required.
WANTZ
WANTZ is LOGICAL
= .TRUE. : the matrix of Schur vectors Z is required;
= .FALSE.: Schur vectors are not required.
N
N is INTEGER
The order of the matrix H. N .GE. 0.
ILO
ILO is INTEGER
IHI
IHI is 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
H is 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
LDH is INTEGER
The leading dimension of the array H. LDH .GE. max(1,N).
WR
WR is DOUBLE PRECISION array, dimension (IHI)
WI
WI is 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
ILOZ is INTEGER
IHIZ
IHIZ is 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
Z is 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
LDZ is INTEGER
The leading dimension of the array Z. if WANTZ is .TRUE.
then LDZ.GE.MAX(1,IHIZ). Otherwize, LDZ.GE.1.
WORK
WORK is DOUBLE PRECISION array, dimension LWORK
On exit, if LWORK = -1, WORK(1) returns an estimate of
the optimal value for LWORK.
LWORK
LWORK is 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
INFO is 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 a orthogonal 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(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.
Author:
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
Date:
September 2012
Contributors:
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.
Definition at line 263 of file dlaqr4.f.
Author
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