DTGSEN(3)
π DTGSEN(3) β Library Functions Manual π
Okay bestie, welcome to the glow-up of DTGSEN π
. This is the page for dtgsen.f, and we are keeping every flag, number, and caveat exactly as it appears. No facts lost, just vibes added. β¨
πΈ NAME πΈ
/home/abuild/rpmbuild/BUILD/lapack-static-3.12.0-build/lapack-3.12.0/SRC/dtgsen.f
π¦ SYNOPSIS π¦
π§ Functions/Subroutines π§
subroutine DTGSEN (ijob, wantq, wantz, select, n, a, lda, b, ldb,
alphar, alphai, beta, q, ldq, z, ldz, m, pl, pr, dif, work, lwork,
iwork, liwork, info)
DTGSEN
π Function/Subroutine Documentation π
π subroutine DTGSEN π
subroutine DTGSEN (integer ijob, logical wantq, logical wantz, logical,
dimension( * ) select, integer n, double precision, dimension( lda, * )
a, integer lda, double precision, dimension( ldb, * ) b, integer ldb,
double precision, dimension( * ) alphar, double precision, dimension( *
) alphai, double precision, dimension( * ) beta, double precision,
dimension( ldq, * ) q, integer ldq, double precision, dimension( ldz, *
) z, integer ldz, integer m, double precision pl, double precision pr,
double precision, dimension( * ) dif, double precision, dimension( * )
work, integer lwork, integer, dimension( * ) iwork, integer liwork,
integer info)
DTGSEN
β¨ Purpose β¨
Bestie, here's the whole plot: DTGSEN reorders the generalized real Schur decomposition of a real matrix pair (A, B) (in terms of an orthonormal equivalence transformation Q**T * (A, B) * Z), so that a selected cluster of eigenvalues appears in the leading diagonal blocks of the upper quasi-triangular matrix A and the upper triangular B. The leading columns of Q and Z form orthonormal bases of the corresponding left and right eigenspaces (deflating subspaces). (A, B) must be in generalized real Schur canonical form (as returned by DGGES), i.e. A is block upper triangular with 1-by-1 and 2-by-2 diagonal blocks. B is upper triangular.
DTGSEN also computes the generalized eigenvalues
w(j) = (ALPHAR(j) + i*ALPHAI(j))/BETA(j)
of the reordered matrix pair (A, B).
Optionally, DTGSEN computes the estimates of reciprocal condition numbers for eigenvalues and eigenspaces. These are Difu[(A11,B11), (A22,B22)] and Difl[(A11,B11), (A22,B22)], i.e. the separation(s) between the matrix pairs (A11, B11) and (A22,B22) that correspond to the selected cluster and the eigenvalues outside the cluster, resp., and norms of onto left and right eigenspaces w.r.t. the selected cluster in the (1,1)-block. π«Ά
π Parameters π
IJOBβINTEGER. Specifies whether condition numbers are required for the cluster of eigenvalues (PLandPR) or the deflating subspaces (DifuandDifl):=0: Only reorder w.r.t.SELECT. No extras.=1: Reciprocal of norms of onto left and right eigenspaces w.r.t. the selected cluster (PLandPR).=2: Upper bounds onDifuandDifl. F-norm-based estimate (DIF(1:2)).=3: Estimate ofDifuandDifl. 1-norm-based estimate (DIF(1:2)). About 5 times as expensive asIJOB = 2.=4: ComputePL,PRandDIF(i.e. 0, 1 and 2 above): Economic version to get it all.=5: ComputePL,PRandDIF(i.e. 0, 1 and 3 above)
WANTQβLOGICAL..TRUE.: update the left transformation matrixQ;.FALSE.: do not updateQ.WANTZβLOGICAL..TRUE.: update the right transformation matrixZ;.FALSE.: do not updateZ.SELECTβLOGICALarray, dimension(N).SELECTspecifies the eigenvalues in the selected cluster. To select a real eigenvaluew(j),SELECT(j)must be set to.TRUE.. To select a complex conjugate pair of eigenvaluesw(j)andw(j+1), corresponding to a 2-by-2 diagonal block, eitherSELECT(j)orSELECT(j+1)or both must be set to.TRUE.; a complex conjugate pair of eigenvalues must be either both included in the cluster or both excluded. No half-picking, bestie.NβINTEGER. The order of the matricesAandB.N >= 0.AβDOUBLE PRECISIONarray, dimension(LDA,N). On entry, the upper quasi-triangular matrixA, with(A, B)in generalized real Schur canonical form. On exit,Ais overwritten by the reordered matrixA.LDAβINTEGER. The leading dimension of the arrayA.LDA >= max(1,N).BβDOUBLE PRECISIONarray, dimension(LDB,N). On entry, the upper triangular matrixB, with(A, B)in generalized real Schur canonical form. On exit,Bis overwritten by the reordered matrixB.LDBβINTEGER. The leading dimension of the arrayB.LDB >= max(1,N).ALPHARβDOUBLE PRECISIONarray, dimension(N).ALPHAIβDOUBLE PRECISIONarray, dimension(N).BETAβDOUBLE PRECISIONarray, dimension(N). On exit,(ALPHAR(j) + ALPHAI(j)*i)/BETA(j),j=1,...,N, will be the generalized eigenvalues.ALPHAR(j) + ALPHAI(j)*iandBETA(j),j=1,...,Nare the diagonals of the complex Schur form(S,T)that would result if the 2-by-2 diagonal blocks of the real generalized Schur form of(A,B)were further reduced to triangular form using complex unitary transformations. IfALPHAI(j)is zero, then thej-th eigenvalue is real; if positive, then thej-th and(j+1)-st eigenvalues are a complex conjugate pair, withALPHAI(j+1)negative.QβDOUBLE PRECISIONarray, dimension(LDQ,N). On entry, ifWANTQ = .TRUE.,Qis anN-by-Nmatrix. On exit,Qhas been postmultiplied by the left orthogonal transformation matrix which reorder(A, B); The leadingMcolumns ofQform orthonormal bases for the specified pair of left eigenspaces (deflating subspaces). IfWANTQ = .FALSE.,Qis not referenced.LDQβINTEGER. The leading dimension of the arrayQ.LDQ >= 1; and ifWANTQ = .TRUE.,LDQ >= N.ZβDOUBLE PRECISIONarray, dimension(LDZ,N). On entry, ifWANTZ = .TRUE.,Zis anN-by-Nmatrix. On exit,Zhas been postmultiplied by the left orthogonal transformation matrix which reorder(A, B); The leadingMcolumns ofZform orthonormal bases for the specified pair of left eigenspaces (deflating subspaces). IfWANTZ = .FALSE.,Zis not referenced.LDZβINTEGER. The leading dimension of the arrayZ.LDZ >= 1; IfWANTZ = .TRUE.,LDZ >= N.MβINTEGER. The dimension of the specified pair of left and right eigenspaces (deflating subspaces).0 <= M <= N.PLβDOUBLE PRECISION.PRβDOUBLE PRECISION.
Shared PL/PR details: If IJOB = 1, 4 or 5, PL, PR are lower bounds on the reciprocal of the norm of onto left and right eigenspaces with respect to the selected cluster. 0 < PL, PR <= 1. If M = 0 or M = N, PL = PR = 1. If IJOB = 0, 2 or 3, PL and PR are not referenced.
DIFβDOUBLE PRECISIONarray, dimension(2). IfIJOB >= 2,DIF(1:2)store the estimates ofDifuandDifl. IfIJOB = 2 or 4,DIF(1:2)are F-norm-based upper bounds onDifuandDifl. IfIJOB = 3 or 5,DIF(1:2)are 1-norm-based estimates ofDifuandDifl. IfM = 0 or N,DIF(1:2) = F-norm([A, B]). IfIJOB = 0 or 1,DIFis not referenced.WORKβDOUBLE PRECISIONarray, dimension(MAX(1,LWORK)). On exit, ifINFO = 0,WORK(1)returns the optimalLWORK.LWORKβINTEGER. The dimension of the arrayWORK.LWORK >= 4*N+16. IfIJOB = 1, 2 or 4,LWORK >= MAX(4*N+16, 2*M*(N-M)). IfIJOB = 3 or 5,LWORK >= MAX(4*N+16, 4*M*(N-M)).
IfLWORK = -1, then a workspace query is assumed; the routine only calculates the optimal size of theWORKarray, returns this value as the first entry of theWORKarray, and no error message related toLWORKis issued byXERBLA.
IWORKβINTEGERarray, dimension(MAX(1,LIWORK)). On exit, ifINFO = 0,IWORK(1)returns the optimalLIWORK.LIWORKβINTEGER. The dimension of the arrayIWORK.LIWORK >= 1. IfIJOB = 1, 2 or 4,LIWORK >= N+6. IfIJOB = 3 or 5,LIWORK >= MAX(2*M*(N-M), N+6).
IfLIWORK = -1, then a workspace query is assumed; the routine only calculates the optimal size of theIWORKarray, returns this value as the first entry of theIWORKarray, and no error message related toLIWORKis issued byXERBLA.
INFOβINTEGER.=0: Successful exit.<0: IfINFO = -i, thei-th argument had an illegal value.=1: Reordering of(A, B)failed because the transformed matrix pair(A, B)would be too far from generalized Schur form; the problem is very ill-conditioned.(A, B)may have been partially reordered. If requested,0is returned inDIF(*),PLandPR.
π Author π
Univ. of Tennessee β author credit, periodt. π
Shoutout to Univ. of California Berkeley, Univ. of Colorado Denver, and NAG Ltd. β absolute institutions, no cap π
β¨ Further Details β¨
Okay bestie, so hereβs the tea on what DTGSEN actually does under the hood: it first collects the selected eigenvalues by computing orthogonal U and W that move them to the top left corner of (A, B). In other words, the selected eigenvalues are the eigenvalues of (A11, B11) in:
U**T*(A, B)*W = (A11 A12) (B11 B12) n1
( 0 A22),( 0 B22) n2
n1 n2 n1 n2
where N = n1+n2 and U**T means the transpose of U. The first n1 columns of U and W span the specified pair of left and right eigenspaces (deflating subspaces) of (A, B). Iconic.
If (A, B) has been obtained from the generalized real Schur decomposition of a matrix pair (C, D) = Q*(A, B)*Z**T, then the reordered generalized real Schur form of (C, D) is given by
(C, D) = (Q*U)*(U**T*(A, B)*W)*(Z*W)**T,
and the first n1 columns of Q*U and Z*W span the corresponding deflating subspaces of (C, D) (Q and Z store Q*U and Z*W, resp.).
Note that if the selected eigenvalue is sufficiently ill-conditioned, then its value may differ significantly from its value before reordering. π
The reciprocal condition numbers of the left and right eigenspaces spanned by the first n1 columns of U and W (or Q*U and Z*W) may be returned in DIF(1:2), corresponding to Difu and Difl, resp.
The Difu and Difl are defined as:
Difu[(A11, B11), (A22, B22)] = sigma-min( Zu )
and
Difl[(A11, B11), (A22, B22)] = Difu[(A22, B22), (A11, B11)],
where sigma-min(Zu) is the smallest singular value of the (2*n1*n2)-by-(2*n1*n2) matrix
Zu = [ kron(In2, A11) -kron(A22**T, In1) ]
[ kron(In2, B11) -kron(B22**T, In1) ].
Here, Inx is the identity matrix of size nx and A22**T is the transpose of A22. kron(X, Y) is the Kronecker product between the matrices X and Y.
When DIF(2) is small, small changes in (A, B) can cause large changes in the deflating subspace. An approximate (asymptotic) bound on the maximum angular error in the computed deflating subspaces is
EPS * norm((A, B)) / DIF(2),
where EPS is the machine precision.
The reciprocal norm of the projectors on the left and right eigenspaces associated with (A11, B11) may be returned in PL and PR. They are computed as follows. First we compute L and R so that P*(A, B)*Q is block diagonal, where
P = ( I -L ) n1 Q = ( I R ) n1
( 0 I ) n2 and ( 0 I ) n2
n1 n2 n1 n2
and (L, R) is the solution to the generalized Sylvester equation
A11*R - L*A22 = -A12
B11*R - L*B22 = -B12
Then PL = (F-norm(L)**2+1)**(-1/2) and PR = (F-norm(R)**2+1)**(-1/2). An approximate (asymptotic) bound on the average absolute error of the selected eigenvalues is
EPS * norm((A, B)) / PL.
There are also global error bounds which valid for perturbations up to a certain restriction: A lower bound (x) on the smallest F-norm(E,F) for which an eigenvalue of (A11, B11) may move and coalesce with an eigenvalue of (A22, B22) under perturbation (E,F), (i.e. (A + E, B + F), is
x = min(Difu,Difl)/((1/(PL*PL)+1/(PR*PR))**(1/2)+2*max(1/PL,1/PR)).
An approximate bound on x can be computed from DIF(1:2), PL and PR.
If y = ( F-norm(E,F) / x) <= 1, the angles between the perturbed (L', R') and unperturbed (L, R) left and right deflating subspaces associated with the selected cluster in the (1,1)-blocks can be bounded as
max-angle(L, L') <= arctan( y * PL / (1 - y * (1 - PL * PL)**(1/2))
max-angle(R, R') <= arctan( y * PR / (1 - y * (1 - PR * PR)**(1/2))
See LAPACK Userβs Guide section 4.11 or the following references for more information.
Note that if the default method for computing the Frobenius-norm-based estimate DIF is not wanted (see DLATDF), then the parameter IDIFJB (see below) should be changed from 3 to 4 (routine DLATDF (IJOB = 2 will be used)). See DTGSYL for more details.
π«Ά Contributors π«Ά
Bo Kagstrom and Peter Poromaa, Department of Computing Science, Umea University, S-901 87 Umea, Sweden. Legends fr fr π
π References π
[1] B. Kagstrom; A Direct Method for Reordering Eigenvalues in the Generalized Real Schur Form of a Regular Matrix Pair (A, B), in M.S. Moonen et al (eds), Linear Algebra for Large Scale and Real-Time Applications, Kluwer Academic Publ. 1993, pp 195-218.[2] B. Kagstrom and P. Poromaa; Computing Eigenspaces with Specified Eigenvalues of a Regular Matrix Pair (A, B) and Condition Estimation: Theory, Algorithms and Software, Report UMINF - 94.04, Department of Computing Science, Umea University, S-901 87 Umea, Sweden, 1994. Also as LAPACK Working Note 87. To appear in Numerical Algorithms, 1996.[3] B. Kagstrom and P. Poromaa, LAPACK-Style Algorithms and Software for Solving the Generalized Sylvester Equation and Estimating the Separation between Regular Matrix Pairs, Report UMINF - 93.23, Department of Computing Science, Umea University, S-901 87 Umea, Sweden, December 1993, Revised April 1994, Also as LAPACK Working Note 75. To appear in ACM Trans. on Math. Software, Vol 22, No 1, 1996.
Definition at line 448 of file dtgsen.f.
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