org.netlib.lapack
Class STGSEN
java.lang.Object
org.netlib.lapack.STGSEN
public class STGSEN
 extends java.lang.Object
STGSEN is a simplified interface to the JLAPACK routine stgsen.
This interface converts Javastyle 2D rowmajor arrays into
the 1D columnmajor linearized arrays expected by the lower
level JLAPACK routines. Using this interface also allows you
to omit offset and leading dimension arguments. However, because
of these conversions, these routines will be slower than the low
level ones. Following is the description from the original Fortran
source. Contact seymour@cs.utk.edu with any questions.
* ..
*
* Purpose
* =======
*
* STGSEN reorders the generalized real Schur decomposition of a real
* matrix pair (A, B) (in terms of an orthonormal equivalence trans
* formation Q' * (A, B) * Z), so that a selected cluster of eigenvalues
* appears in the leading diagonal blocks of the upper quasitriangular
* matrix A and the upper triangular B. The leading columns of Q and
* Z form orthonormal bases of the corresponding left and right eigen
* spaces (deflating subspaces). (A, B) must be in generalized real
* Schur canonical form (as returned by SGGES), i.e. A is block upper
* triangular with 1by1 and 2by2 diagonal blocks. B is upper
* triangular.
*
* STGSEN also computes the generalized eigenvalues
*
* w(j) = (ALPHAR(j) + i*ALPHAI(j))/BETA(j)
*
* of the reordered matrix pair (A, B).
*
* Optionally, STGSEN 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 "projections" onto left and right eigenspaces w.r.t.
* the selected cluster in the (1,1)block.
*
* Arguments
* =========
*
* IJOB (input) INTEGER
* Specifies whether condition numbers are required for the
* cluster of eigenvalues (PL and PR) or the deflating subspaces
* (Difu and Difl):
* =0: Only reorder w.r.t. SELECT. No extras.
* =1: Reciprocal of norms of "projections" onto left and right
* eigenspaces w.r.t. the selected cluster (PL and PR).
* =2: Upper bounds on Difu and Difl. Fnormbased estimate
* (DIF(1:2)).
* =3: Estimate of Difu and Difl. 1normbased estimate
* (DIF(1:2)).
* About 5 times as expensive as IJOB = 2.
* =4: Compute PL, PR and DIF (i.e. 0, 1 and 2 above): Economic
* version to get it all.
* =5: Compute PL, PR and DIF (i.e. 0, 1 and 3 above)
*
* WANTQ (input) LOGICAL
* .TRUE. : update the left transformation matrix Q;
* .FALSE.: do not update Q.
*
* WANTZ (input) LOGICAL
* .TRUE. : update the right transformation matrix Z;
* .FALSE.: do not update Z.
*
* SELECT (input) LOGICAL array, dimension (N)
* SELECT specifies the eigenvalues in the selected cluster.
* To select a real eigenvalue w(j), SELECT(j) must be set to
* .TRUE.. To select a complex conjugate pair of eigenvalues
* w(j) and w(j+1), corresponding to a 2by2 diagonal block,
* either SELECT(j) or SELECT(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.
*
* N (input) INTEGER
* The order of the matrices A and B. N >= 0.
*
* A (input/output) REAL array, dimension(LDA,N)
* On entry, the upper quasitriangular matrix A, with (A, B) in
* generalized real Schur canonical form.
* On exit, A is overwritten by the reordered matrix A.
*
* LDA (input) INTEGER
* The leading dimension of the array A. LDA >= max(1,N).
*
* B (input/output) REAL array, dimension(LDB,N)
* On entry, the upper triangular matrix B, with (A, B) in
* generalized real Schur canonical form.
* On exit, B is overwritten by the reordered matrix B.
*
* LDB (input) INTEGER
* The leading dimension of the array B. LDB >= max(1,N).
*
* ALPHAR (output) REAL array, dimension (N)
* ALPHAI (output) REAL array, dimension (N)
* BETA (output) REAL array, dimension (N)
* On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will
* be the generalized eigenvalues. ALPHAR(j) + ALPHAI(j)*i
* and BETA(j),j=1,...,N are the diagonals of the complex Schur
* form (S,T) that would result if the 2by2 diagonal blocks of
* the real generalized Schur form of (A,B) were further reduced
* to triangular form using complex unitary transformations.
* If ALPHAI(j) is zero, then the jth eigenvalue is real; if
* positive, then the jth and (j+1)st eigenvalues are a
* complex conjugate pair, with ALPHAI(j+1) negative.
*
* Q (input/output) REAL array, dimension (LDQ,N)
* On entry, if WANTQ = .TRUE., Q is an NbyN matrix.
* On exit, Q has been postmultiplied by the left orthogonal
* transformation matrix which reorder (A, B); The leading M
* columns of Q form orthonormal bases for the specified pair of
* left eigenspaces (deflating subspaces).
* If WANTQ = .FALSE., Q is not referenced.
*
* LDQ (input) INTEGER
* The leading dimension of the array Q. LDQ >= 1;
* and if WANTQ = .TRUE., LDQ >= N.
*
* Z (input/output) REAL array, dimension (LDZ,N)
* On entry, if WANTZ = .TRUE., Z is an NbyN matrix.
* On exit, Z has been postmultiplied by the left orthogonal
* transformation matrix which reorder (A, B); The leading M
* columns of Z form orthonormal bases for the specified pair of
* left eigenspaces (deflating subspaces).
* If WANTZ = .FALSE., Z is not referenced.
*
* LDZ (input) INTEGER
* The leading dimension of the array Z. LDZ >= 1;
* If WANTZ = .TRUE., LDZ >= N.
*
* M (output) INTEGER
* The dimension of the specified pair of left and right eigen
* spaces (deflating subspaces). 0 <= M <= N.
*
* PL, PR (output) REAL
* If IJOB = 1, 4 or 5, PL, PR are lower bounds on the
* reciprocal of the norm of "projections" 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.
*
* DIF (output) REAL array, dimension (2).
* If IJOB >= 2, DIF(1:2) store the estimates of Difu and Difl.
* If IJOB = 2 or 4, DIF(1:2) are Fnormbased upper bounds on
* Difu and Difl. If IJOB = 3 or 5, DIF(1:2) are 1normbased
* estimates of Difu and Difl.
* If M = 0 or N, DIF(1:2) = Fnorm([A, B]).
* If IJOB = 0 or 1, DIF is not referenced.
*
* WORK (workspace/output) REAL array, dimension (LWORK)
* IF IJOB = 0, 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. LWORK >= 4*N+16.
* If IJOB = 1, 2 or 4, LWORK >= MAX(4*N+16, 2*M*(NM)).
* If IJOB = 3 or 5, LWORK >= MAX(4*N+16, 4*M*(NM)).
*
* 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.
*
* IWORK (workspace/output) INTEGER array, dimension (LIWORK)
* IF IJOB = 0, IWORK is not referenced. Otherwise,
* on exit, if INFO = 0, IWORK(1) returns the optimal LIWORK.
*
* LIWORK (input) INTEGER
* The dimension of the array IWORK. LIWORK >= 1.
* If IJOB = 1, 2 or 4, LIWORK >= N+6.
* If IJOB = 3 or 5, LIWORK >= MAX(2*M*(NM), N+6).
*
* If LIWORK = 1, then a workspace query is assumed; the
* routine only calculates the optimal size of the IWORK array,
* returns this value as the first entry of the IWORK array, and
* no error message related to LIWORK is issued by XERBLA.
*
* INFO (output) INTEGER
* =0: Successful exit.
* <0: If INFO = i, the ith 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 illconditioned.
* (A, B) may have been partially reordered.
* If requested, 0 is returned in DIF(*), PL and PR.
*
* Further Details
* ===============
*
* STGSEN 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'*(A, B)*W = (A11 A12) (B11 B12) n1
* ( 0 A22),( 0 B22) n2
* n1 n2 n1 n2
*
* where N = n1+n2 and U' 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).
*
* If (A, B) has been obtained from the generalized real Schur
* decomposition of a matrix pair (C, D) = Q*(A, B)*Z', then the
* reordered generalized real Schur form of (C, D) is given by
*
* (C, D) = (Q*U)*(U'*(A, B)*W)*(Z*W)',
*
* 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 illconditioned,
* then its value may differ significantly from its value before
* reordering.
*
* 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)] = sigmamin( Zu )
* and
* Difl[(A11, B11), (A22, B22)] = Difu[(A22, B22), (A11, B11)],
*
* where sigmamin(Zu) is the smallest singular value of the
* (2*n1*n2)by(2*n1*n2) matrix
*
* Zu = [ kron(In2, A11) kron(A22', In1) ]
* [ kron(In2, B11) kron(B22', In1) ].
*
* Here, Inx is the identity matrix of size nx and A22' 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 = (Fnorm(L)**2+1)**(1/2) and PR = (Fnorm(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
* Fnorm(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 = ( Fnorm(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
*
* maxangle(L, L') <= arctan( y * PL / (1  y * (1  PL * PL)**(1/2))
* maxangle(R, R') <= arctan( y * PR / (1  y * (1  PR * PR)**(1/2))
*
* See LAPACK User's Guide section 4.11 or the following references
* for more information.
*
* Note that if the default method for computing the Frobeniusnorm
* based estimate DIF is not wanted (see SLATDF), then the parameter
* IDIFJB (see below) should be changed from 3 to 4 (routine SLATDF
* (IJOB = 2 will be used)). See STGSYL for more details.
*
* Based on contributions by
* Bo Kagstrom and Peter Poromaa, Department of Computing Science,
* Umea University, S901 87 Umea, Sweden.
*
* References
* ==========
*
* [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
* RealTime Applications, Kluwer Academic Publ. 1993, pp 195218.
*
* [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, S901 87 Umea, Sweden, 1994. Also as LAPACK Working
* Note 87. To appear in Numerical Algorithms, 1996.
*
* [3] B. Kagstrom and P. Poromaa, LAPACKStyle 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, S901 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.
*
* =====================================================================
*
* .. Parameters ..
Method Summary 
static void 
STGSEN(int ijob,
boolean wantq,
boolean wantz,
boolean[] select,
int n,
float[][] a,
float[][] b,
float[] alphar,
float[] alphai,
float[] beta,
float[][] q,
float[][] z,
intW m,
floatW pl,
floatW pr,
float[] dif,
float[] work,
int lwork,
int[] iwork,
int liwork,
intW info)

Methods inherited from class java.lang.Object 
clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait 
STGSEN
public STGSEN()
STGSEN
public static void STGSEN(int ijob,
boolean wantq,
boolean wantz,
boolean[] select,
int n,
float[][] a,
float[][] b,
float[] alphar,
float[] alphai,
float[] beta,
float[][] q,
float[][] z,
intW m,
floatW pl,
floatW pr,
float[] dif,
float[] work,
int lwork,
int[] iwork,
int liwork,
intW info)