LAPACK  3.10.0
LAPACK: Linear Algebra PACKage

◆ ctrsen()

subroutine ctrsen ( character  JOB,
character  COMPQ,
logical, dimension( * )  SELECT,
integer  N,
complex, dimension( ldt, * )  T,
integer  LDT,
complex, dimension( ldq, * )  Q,
integer  LDQ,
complex, dimension( * )  W,
integer  M,
real  S,
real  SEP,
complex, dimension( * )  WORK,
integer  LWORK,
integer  INFO 
)

CTRSEN

Download CTRSEN + dependencies [TGZ] [ZIP] [TXT]

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.
Parameters
[in]JOB
          JOB is 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).
[in]COMPQ
          COMPQ is CHARACTER*1
          = 'V': update the matrix Q of Schur vectors;
          = 'N': do not update Q.
[in]SELECT
          SELECT is 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..
[in]N
          N is INTEGER
          The order of the matrix T. N >= 0.
[in,out]T
          T is 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.
[in]LDT
          LDT is INTEGER
          The leading dimension of the array T. LDT >= max(1,N).
[in,out]Q
          Q is 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.
[in]LDQ
          LDQ is INTEGER
          The leading dimension of the array Q.
          LDQ >= 1; and if COMPQ = 'V', LDQ >= N.
[out]W
          W is COMPLEX array, dimension (N)
          The reordered eigenvalues of T, in the same order as they
          appear on the diagonal of T.
[out]M
          M is INTEGER
          The dimension of the specified invariant subspace.
          0 <= M <= N.
[out]S
          S is 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.
[out]SEP
          SEP is 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.
[out]WORK
          WORK is COMPLEX array, dimension (MAX(1,LWORK))
          On exit, if INFO = 0, WORK(1) returns the optimal LWORK.
[in]LWORK
          LWORK is INTEGER
          The dimension of the array WORK.
          If JOB = 'N', LWORK >= 1;
          if JOB = 'E', LWORK = max(1,M*(N-M));
          if JOB = 'V' or 'B', LWORK >= max(1,2*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.
[out]INFO
          INFO is INTEGER
          = 0:  successful exit
          < 0:  if INFO = -i, the i-th argument had an illegal value
Author
Univ. of Tennessee
Univ. of California Berkeley
Univ. of Colorado Denver
NAG Ltd.
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**H * T * Z = ( T11 T12 ) n1
                         (  0  T22 ) n2
                            n1  n2

  where N = n1+n2. 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**H, then the reordered Schur factorization of A is given by
  A = (Q*Z)*(Z**H*T*Z)*(Q*Z)**H, 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

Definition at line 262 of file ctrsen.f.

264 *
265 * -- LAPACK computational routine --
266 * -- LAPACK is a software package provided by Univ. of Tennessee, --
267 * -- Univ. of California Berkeley, Univ. of Colorado Denver and NAG Ltd..--
268 *
269 * .. Scalar Arguments ..
270  CHARACTER COMPQ, JOB
271  INTEGER INFO, LDQ, LDT, LWORK, M, N
272  REAL S, SEP
273 * ..
274 * .. Array Arguments ..
275  LOGICAL SELECT( * )
276  COMPLEX Q( LDQ, * ), T( LDT, * ), W( * ), WORK( * )
277 * ..
278 *
279 * =====================================================================
280 *
281 * .. Parameters ..
282  REAL ZERO, ONE
283  parameter( zero = 0.0e+0, one = 1.0e+0 )
284 * ..
285 * .. Local Scalars ..
286  LOGICAL LQUERY, WANTBH, WANTQ, WANTS, WANTSP
287  INTEGER IERR, K, KASE, KS, LWMIN, N1, N2, NN
288  REAL EST, RNORM, SCALE
289 * ..
290 * .. Local Arrays ..
291  INTEGER ISAVE( 3 )
292  REAL RWORK( 1 )
293 * ..
294 * .. External Functions ..
295  LOGICAL LSAME
296  REAL CLANGE
297  EXTERNAL lsame, clange
298 * ..
299 * .. External Subroutines ..
300  EXTERNAL clacn2, clacpy, ctrexc, ctrsyl, xerbla
301 * ..
302 * .. Intrinsic Functions ..
303  INTRINSIC max, sqrt
304 * ..
305 * .. Executable Statements ..
306 *
307 * Decode and test the input parameters.
308 *
309  wantbh = lsame( job, 'B' )
310  wants = lsame( job, 'E' ) .OR. wantbh
311  wantsp = lsame( job, 'V' ) .OR. wantbh
312  wantq = lsame( compq, 'V' )
313 *
314 * Set M to the number of selected eigenvalues.
315 *
316  m = 0
317  DO 10 k = 1, n
318  IF( SELECT( k ) )
319  $ m = m + 1
320  10 CONTINUE
321 *
322  n1 = m
323  n2 = n - m
324  nn = n1*n2
325 *
326  info = 0
327  lquery = ( lwork.EQ.-1 )
328 *
329  IF( wantsp ) THEN
330  lwmin = max( 1, 2*nn )
331  ELSE IF( lsame( job, 'N' ) ) THEN
332  lwmin = 1
333  ELSE IF( lsame( job, 'E' ) ) THEN
334  lwmin = max( 1, nn )
335  END IF
336 *
337  IF( .NOT.lsame( job, 'N' ) .AND. .NOT.wants .AND. .NOT.wantsp )
338  $ THEN
339  info = -1
340  ELSE IF( .NOT.lsame( compq, 'N' ) .AND. .NOT.wantq ) THEN
341  info = -2
342  ELSE IF( n.LT.0 ) THEN
343  info = -4
344  ELSE IF( ldt.LT.max( 1, n ) ) THEN
345  info = -6
346  ELSE IF( ldq.LT.1 .OR. ( wantq .AND. ldq.LT.n ) ) THEN
347  info = -8
348  ELSE IF( lwork.LT.lwmin .AND. .NOT.lquery ) THEN
349  info = -14
350  END IF
351 *
352  IF( info.EQ.0 ) THEN
353  work( 1 ) = lwmin
354  END IF
355 *
356  IF( info.NE.0 ) THEN
357  CALL xerbla( 'CTRSEN', -info )
358  RETURN
359  ELSE IF( lquery ) THEN
360  RETURN
361  END IF
362 *
363 * Quick return if possible
364 *
365  IF( m.EQ.n .OR. m.EQ.0 ) THEN
366  IF( wants )
367  $ s = one
368  IF( wantsp )
369  $ sep = clange( '1', n, n, t, ldt, rwork )
370  GO TO 40
371  END IF
372 *
373 * Collect the selected eigenvalues at the top left corner of T.
374 *
375  ks = 0
376  DO 20 k = 1, n
377  IF( SELECT( k ) ) THEN
378  ks = ks + 1
379 *
380 * Swap the K-th eigenvalue to position KS.
381 *
382  IF( k.NE.ks )
383  $ CALL ctrexc( compq, n, t, ldt, q, ldq, k, ks, ierr )
384  END IF
385  20 CONTINUE
386 *
387  IF( wants ) THEN
388 *
389 * Solve the Sylvester equation for R:
390 *
391 * T11*R - R*T22 = scale*T12
392 *
393  CALL clacpy( 'F', n1, n2, t( 1, n1+1 ), ldt, work, n1 )
394  CALL ctrsyl( 'N', 'N', -1, n1, n2, t, ldt, t( n1+1, n1+1 ),
395  $ ldt, work, n1, scale, ierr )
396 *
397 * Estimate the reciprocal of the condition number of the cluster
398 * of eigenvalues.
399 *
400  rnorm = clange( 'F', n1, n2, work, n1, rwork )
401  IF( rnorm.EQ.zero ) THEN
402  s = one
403  ELSE
404  s = scale / ( sqrt( scale*scale / rnorm+rnorm )*
405  $ sqrt( rnorm ) )
406  END IF
407  END IF
408 *
409  IF( wantsp ) THEN
410 *
411 * Estimate sep(T11,T22).
412 *
413  est = zero
414  kase = 0
415  30 CONTINUE
416  CALL clacn2( nn, work( nn+1 ), work, est, kase, isave )
417  IF( kase.NE.0 ) THEN
418  IF( kase.EQ.1 ) THEN
419 *
420 * Solve T11*R - R*T22 = scale*X.
421 *
422  CALL ctrsyl( 'N', 'N', -1, n1, n2, t, ldt,
423  $ t( n1+1, n1+1 ), ldt, work, n1, scale,
424  $ ierr )
425  ELSE
426 *
427 * Solve T11**H*R - R*T22**H = scale*X.
428 *
429  CALL ctrsyl( 'C', 'C', -1, n1, n2, t, ldt,
430  $ t( n1+1, n1+1 ), ldt, work, n1, scale,
431  $ ierr )
432  END IF
433  GO TO 30
434  END IF
435 *
436  sep = scale / est
437  END IF
438 *
439  40 CONTINUE
440 *
441 * Copy reordered eigenvalues to W.
442 *
443  DO 50 k = 1, n
444  w( k ) = t( k, k )
445  50 CONTINUE
446 *
447  work( 1 ) = lwmin
448 *
449  RETURN
450 *
451 * End of CTRSEN
452 *
subroutine xerbla(SRNAME, INFO)
XERBLA
Definition: xerbla.f:60
logical function lsame(CA, CB)
LSAME
Definition: lsame.f:53
real function clange(NORM, M, N, A, LDA, WORK)
CLANGE returns the value of the 1-norm, Frobenius norm, infinity-norm, or the largest absolute value ...
Definition: clange.f:115
subroutine clacn2(N, V, X, EST, KASE, ISAVE)
CLACN2 estimates the 1-norm of a square matrix, using reverse communication for evaluating matrix-vec...
Definition: clacn2.f:133
subroutine clacpy(UPLO, M, N, A, LDA, B, LDB)
CLACPY copies all or part of one two-dimensional array to another.
Definition: clacpy.f:103
subroutine ctrexc(COMPQ, N, T, LDT, Q, LDQ, IFST, ILST, INFO)
CTREXC
Definition: ctrexc.f:126
subroutine ctrsyl(TRANA, TRANB, ISGN, M, N, A, LDA, B, LDB, C, LDC, SCALE, INFO)
CTRSYL
Definition: ctrsyl.f:157
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