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cgegv


 NAME
      CGEGV - a pair of N-by-N complex nonsymmetric matrices A, B

 SYNOPSIS
      SUBROUTINE CGEGV( JOBVL, JOBVR, N, A, LDA, B, LDB, ALPHA,
                        BETA, VL, LDVL, VR, LDVR, WORK, LWORK,
                        RWORK, INFO )

          CHARACTER     JOBVL, JOBVR

          INTEGER       INFO, LDA, LDB, LDVL, LDVR, LWORK, N

          REAL          RWORK( * )

          COMPLEX       A( LDA, * ), ALPHA( * ), B( LDB, * ),
                        BETA( * ), VL( LDVL, * ), VR( LDVR, * ),
                        WORK( * )

 PURPOSE
      For a pair of N-by-N complex nonsymmetric matrices A, B:

         compute the generalized eigenvalues (alpha, beta)
         compute the left and/or right generalized eigenvectors
                 (VL and VR)

      The second action is optional -- see the description of
      JOBVL and JOBVR below.

      A generalized eigenvalue for a pair of matrices (A,B) is,
      roughly speaking, a scalar w or a ratio  alpha/beta = w,
      such that  A - w*B is singular.  It is usually represented
      as the pair (alpha,beta), as there is a reasonable interpre-
      tation for beta=0, and even for both being zero.  A good
      beginning reference is the book, "Matrix Computations", by
      G. Golub & C. van Loan (Johns Hopkins U. Press)

      A right generalized eigenvector corresponding to a general-
      ized eigenvalue  w  for a pair of matrices (A,B) is a vector
      r  such that  (A - w B) r = 0 .  A left generalized eigen-
      vector is a vector l  such that  (A - w B)**H l = 0 .

      Note: this routine performs "full balancing" on A and B --
      see "Further Details", below.

 ARGUMENTS
      JOBVL   (input) CHARACTER*1
              = 'N':  do not compute the left generalized eigen-
              vectors;
              = 'V':  compute the left generalized eigenvectors.

      JOBVR   (input) CHARACTER*1
              = 'N':  do not compute the right generalized

              eigenvectors;
              = 'V':  compute the right generalized eigenvectors.

      N       (input) INTEGER
              The number of rows and columns in the matrices A, B,
              VL, and VR.  N >= 0.

      A       (input/workspace) COMPLEX array, dimension (LDA, N)
              On entry, the first of the pair of matrices whose
              generalized eigenvalues and (optionally) generalized
              eigenvectors are to be computed.  On exit, the con-
              tents will have been destroyed.  (For a description
              of the contents of A on exit, see "Further Details",
              below.)

      LDA     (input) INTEGER
              The leading dimension of A.  LDA >= max(1,N).

      B       (input/workspace) COMPLEX array, dimension (LDB, N)
              On entry, the second of the pair of matrices whose
              generalized eigenvalues and (optionally) generalized
              eigenvectors are to be computed.  On exit, the con-
              tents will have been destroyed.  (For a description
              of the contents of B on exit, see "Further Details",
              below.)

      LDB     (input) INTEGER
              The leading dimension of B.  LDB >= max(1,N).

      ALPHA   (output) COMPLEX array, dimension (N)
              BETA    (output) COMPLEX array, dimension (N) On
              exit, ALPHA(j)/BETA(j), j=1,...,N, will be the gen-
              eralized eigenvalues.

              Note: the quotients ALPHA(j)/BETA(j) may easily
              over- or underflow, and BETA(j) may even be zero.
              Thus, the user should avoid naively computing the
              ratio alpha/beta.  However, ALPHA will be always
              less than and usually comparable with norm(A) in
              magnitude, and BETA always less than and usually
              comparable with norm(B).

      VL      (output) COMPLEX array, dimension (LDVL,N)
              If JOBVL = 'V', the left generalized eigenvectors.
              (See "Purpose", above.) Each eigenvector will be
              scaled so the largest component will have abs(real
              part) + abs(imag. part) = 1, *except* that for
              eigenvalues with alpha=beta=0, a zero vector will be
              returned as the corresponding eigenvector.  Not
              referenced if JOBVL = 'N'.

      LDVL    (input) INTEGER

              The leading dimension of the matrix VL. LDVL >= 1,
              and if JOBVL = 'V', LDVL >= N.

      VR      (output) COMPLEX array, dimension (LDVR,N)
              If JOBVL = 'V', the right generalized eigenvectors.
              (See "Purpose", above.) Each eigenvector will be
              scaled so the largest component will have abs(real
              part) + abs(imag. part) = 1, *except* that for
              eigenvalues with alpha=beta=0, a zero vector will be
              returned as the corresponding eigenvector.  Not
              referenced if JOBVR = 'N'.

      LDVR    (input) INTEGER
              The leading dimension of the matrix VR. LDVR >= 1,
              and if JOBVR = 'V', LDVR >= N.

      WORK    (workspace/output) COMPLEX array, dimension (LWORK)
              On exit, if INFO = 0, WORK(1) returns the optimal
              LWORK.

      LWORK   (input) INTEGER
              The dimension of the array WORK.  LWORK >=
              max(1,2*N).  For good performance, LWORK must gen-
              erally be larger.  To compute the optimal value of
              LWORK, call ILAENV to get blocksizes (for CGEQRF,
              CUNMQR, and CUNGQR.)  Then compute: NB  -- MAX of
              the blocksizes for CGEQRF, CUNMQR, and CUNGQR; The
              optimal LWORK is  MAX( 2*N, N*(NB+1) ).

      RWORK   (workspace/output) REAL array, dimension (8*N)

      INFO    (output) INTEGER
              = 0:  successful exit
              < 0:  if INFO = -i, the i-th argument had an illegal
              value.
              =1,...,N: The QZ iteration failed.  No eigenvectors
              have been calculated, but ALPHA(j) and BETA(j)
              should be correct for j=INFO+1,...,N.  > N:  errors
              that usually indicate LAPACK problems:
              =N+1: error return from CGGBAL
              =N+2: error return from CGEQRF
              =N+3: error return from CUNMQR
              =N+4: error return from CUNGQR
              =N+5: error return from CGGHRD
              =N+6: error return from CHGEQZ (other than failed
              iteration) =N+7: error return from CTGEVC
              =N+8: error return from CGGBAK (computing VL)
              =N+9: error return from CGGBAK (computing VR)
              =N+10: error return from CLASCL (various calls)

 FURTHER DETAILS
      Balancing

      ---------

      This driver calls CGGBAL to both permute and scale rows and
      columns of A and B.  The permutations PL and PR are chosen
      so that PL*A*PR and PL*B*R will be upper triangular except
      for the diagonal blocks A(i:j,i:j) and B(i:j,i:j), with i
      and j as close together as possible.  The diagonal scaling
      matrices DL and DR are chosen so that the pair
      DL*PL*A*PR*DR, DL*PL*B*PR*DR have entries close to one
      (except for the entries that start out zero.)

      After the eigenvalues and eigenvectors of the balanced
      matrices have been computed, CGGBAK transforms the eigenvec-
      tors back to what they would have been (in perfect arith-
      metic) if they had not been balanced.

      Contents of A and B on Exit
      -------- -- - --- - -- ----

      If any eigenvectors are computed (either JOBVL='V' or
      JOBVR='V' or both), then on exit the arrays A and B will
      contain the complex Schur form[*] of the "balanced" versions
      of A and B.  If no eigenvectors are computed, then only the
      diagonal blocks will be correct.

      [*] In other words, upper triangular form.