DTGEVC(l)		LAPACK routine (version	1.1)		    DTGEVC(l)

NAME
  DTGEVC - compute selected left and/or	right generalized eigenvectors of a
  pair of real upper triangular	matrices (A,B)

SYNOPSIS

  SUBROUTINE DTGEVC( JOB, SIDE,	SELECT,	N, A, LDA, B, LDB, VL, LDVL, VR,
		     LDVR, MM, M, WORK,	INFO )

      CHARACTER	     JOB, SIDE

      INTEGER	     INFO, LDA,	LDB, LDVL, LDVR, M, MM,	N

      LOGICAL	     SELECT( * )

      DOUBLE	     PRECISION A( LDA, * ), B( LDB, * ), VL( LDVL, * ),	VR(
		     LDVR, * ),	WORK( N, * )

PURPOSE
  DTGEVC computes selected left	and/or right generalized eigenvectors of a
  pair of real upper triangular	matrices (A,B).	 The j-th generalized left
  and right eigenvectors are  y	 and  x, resp.,	such that:
       H			   H
      y	 (A - wB) = 0  or  (A -	wB) y =	0   and	   (A -	wB)x = 0

								      H	Note:
  the left eigenvector is sometimes defined as the row vector  y
	but DTGEVC computes the	column vector y.
  Reminder: the	eigenvectors may be real or complex.  If complex, the
	eigenvector for	the eigenvalue w s.t. Im(w) > 0	is computed.

ARGUMENTS

  JOB	  (input) CHARACTER*1
	  = 'A': compute All (left/right/left+right) generalized eigenvectors
	  of (A,B); = 'S': compute Selected (left/right/left+right) general-
	  ized eigenvectors of (A,B) --	see the	description of the argument
	  SELECT; = 'B'	or 'T':	compute	all (left/right/left+right) general-
	  ized eigenvectors of (A,B), and Back Transform them using the	ini-
	  tial contents	of VL/VR -- see	the descriptions of the	arguments VL
	  and VR.

  SIDE	  (input) CHARACTER*1
	  Specifies for	which side eigenvectors	are to be computed:
	  = 'R': compute right eigenvectors only;
	  = 'L': compute left eigenvectors only;
	  = 'B': compute both right and	left eigenvectors.

  SELECT  (input) LOGICAL array, dimension (N)
	  If JOB='S', then SELECT specifies the	(generalized) eigenvectors to
	  be computed.	To get the eigenvector corresponding to	the j-th
	  eigenvalue, set SELECT(j) to conjugates, i.e., A(j+1,j) is nonzero,
	  then only the	eigenvector for	the first may be selected (the second
	  being	just the conjugate of the first); this may be done by setting
	  either SELECT(j) or SELECT(j+1) to .TRUE.

	  If JOB='A', 'B', or 'T', SELECT is not referenced, and all eigen-
	  vectors are selected.

  N	  (input) INTEGER
	  The order of the matrices A and B.  N	>= 0.

  A	  (input) DOUBLE PRECISION array, dimension (LDA,N)
	  One of the pair of matrices whose generalized	eigenvectors are to
	  be computed.	It must	be block upper triangular, with	1-by-1 or 2-
	  by-2 blocks on the diagonal, the 1-by-1 blocks corresponding to
	  real generalized eigenvalues and the 2-by-2 blocks corresponding to
	  complex generalized eigenvalues.  The	eigenvalues are	computed from
	  the diagonal blocks of A and corresponding entries of	B.

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

  B	  (input) DOUBLE PRECISION array, dimension (LDB,N)
	  The other of the pair	of matrices whose generalized eigenvectors
	  are to be computed.  It must be upper	triangular, and	if A has a
	  2-by-2 diagonal block	in rows/columns	j,j+1, then the	corresponding
	  2-by-2 block of B must be diagonal with positive entries.

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

  VL	  (input/output) DOUBLE	PRECISION array, dimension (LDVL,MM)
	  On exit, the left eigenvectors (column vectors -- see	the note in
	  "Purpose".)  Real eigenvectors take one column, complex take two
	  columns, the first for the real part and the second for the ima-
	  ginary part.	If JOB='A', then all left eigenvectors of (A,B)	will
	  be computed and stored in VL.	 If JOB='S', then only the eigenvec-
	  tors selected	by SELECT will be computed, and	they will be stored
	  one right after another in VL; the first selected eigenvector	will
	  go in	column 1 (and 2, if complex), the second in the	next
	  column(s), etc.  If JOB='B' or 'T', then all left eigenvectors of
	  (A,B)	will be	computed and multiplied	(on the	left) by the matrix
	  found	in VL on entry to DTGEVC.  Usually, this will be the Q matrix
	  computed by DGGHRD and DHGEQZ, so that on exit, VL will contain the
	  left eigenvectors of the original matrix pair.  In any case, each
	  eigenvector will be scaled so	the largest component of each vector
	  has abs(real part) + abs(imag. part)=1, *unless*  the	diagonal
	  blocks in A and B corresponding to the eigenvector are both zero
	  (hence, 1-by-1), in which case the eigenvector will be zero.	If
	  SIDE = 'R', VL is not	referenced.

  LDVL	  (input) INTEGER
	  The leading dimension	of array VL.  LDVL >= 1; if SIDE = 'B' or
	  'L', LDVL >= N.

  VR	  (input/output) COMPLEX*16 array, dimension (LDVR,MM)
	  On exit, the right eigenvectors.  Real eigenvectors take one
	  column, complex take two columns, the	first for the real part	and
	  the second for the imaginary part.  If JOB='A', then all right
	  eigenvectors of (A,B)	will be	computed and stored in VR.  If
	  JOB='S', then	only the eigenvectors selected by SELECT will be com-
	  puted, and they will be stored one right after another in VR;	the
	  first	selected eigenvector will go in	column 1 (and 2, if complex),
	  the second in	the next column(s), etc.  If JOB='B' or	'T', then all
	  right	eigenvectors of	(A,B) will be computed and multiplied (on the
	  left)	by the matrix found in VR on entry to DTGEVC.  Usually,	this
	  will be the Z	matrix computed	by DGGHRD and DHGEQZ, so that on
	  exit,	VR will	contain	the right eigenvectors of the original matrix
	  pair.	 In any	case, each eigenvector will be scaled so the largest
	  component of each vector has abs(real	part) +	abs(imag. part)=1,
	  *unless*  the	diagonal blocks	in A and B corresponding to the
	  eigenvector are both zero (hence, 1-by-1), in	which case the eigen-
	  vector will be zero.	If SIDE	= 'L', VR is not referenced.

  LDVR	  (input) INTEGER
	  The leading dimension	of array VR.  LDVR >= 1; if SIDE = 'B' or
	  'R', LDVR >= N.

  MM	  (input) INTEGER
	  The number of	columns	in VL and/or VR.  If JOB='A', 'B', or 'T',
	  then MM >= N.	 If JOB='S', then MM must be at	least the number of
	  columns required, as computed	from SELECT.  Each .TRUE. value	in
	  SELECT corresponding to a real eigenvalue (i.e., A(j+1,j) and
	  A(j,j-1) are zero) counts for	one column, and	each conjugate pair
	  (i.e., A(j+1,j) is not zero) counts for two columns.	(.TRUE.
	  values corresponding to the second of	a pair -- A(j,j-1) is not
	  zero -- are ignored.)

  M	  (output) INTEGER
	  The number of	columns	in VL and/or VR	actually used to store the
	  eigenvectors.

  WORK	  (workspace) DOUBLE PRECISION array, dimension	( N, 6 )

  INFO	  (output) INTEGER
	  = 0:	successful exit.
	  < 0:	if INFO	= -i, the i-th argument	had an illegal value.
	  > 0:	the 2-by-2 block (INFO:INFO+1) does not	have a complex eigen-
	  value.

FURTHER	DETAILS
  Allocation of	workspace:
  ---------- --	---------

     WORK( j, 1	) = 1-norm of j-th column of A,	above the diagonal
     WORK( j, 2	) = 1-norm of j-th column of B,	above the diagonal
     WORK( *, 3	) = real part of eigenvector
     WORK( *, 4	) = imaginary part of eigenvector
     WORK( *, 5	) = real part of back-transformed eigenvector
     WORK( *, 6	) = imaginary part of back-transformed eigenvector

  Rowwise vs. columnwise solution methods:
  ------- --  ---------- -------- -------

  Finding a generalized	eigenvector consists basically of solving the singu-
  lar triangular system
						    H
     (A	- w B) x = 0	 (for right) or:   (A -	w B) y = 0  (for left)

  Consider finding the i-th right eigenvector (assume all eigenvalues are
  real). The equation to be solved is:
       n		   i
  0 = sum  C(j,k) v(k)	= sum  C(j,k) v(k)     for j = i,. . .,1
      k=j		  k=j

  where	 C = (A	- w B)	(The components	v(i+1:n) are 0.)

  The "rowwise"	method is:

  (1)  v(i) := 1
  for j	= i-1,.	. .,1:
			  i
      (2) compute  s = - sum C(j,k) v(k)   and
			k=j+1

      (3) v(j) := s / C(j,j)

  Step 2 is sometimes called the "dot product" step, since it is an inner
  product between the j-th row and the portion of the eigenvector that has
  been computed	so far.

  The "columnwise" method consists basically in	doing the sums for all the
  rows in parallel.  As	each v(j) is computed, the contribution	of v(j)	times
  the j-th column of C is added	to the partial sums.  Since FORTRAN arrays
  are stored columnwise, this has the advantage	that at	each step, the
  entries of C that are	accessed are adjacent to one another, whereas with
  the rowwise method, the entries accessed at a	step are spaced	LDA (and LDB)
  words	apart.

  When finding left eigenvectors, the matrix in	question is the	transpose of
  the one in storage, so the rowwise method then actually accesses columns of
  A and	B at each step,	and so is the preferred	method.