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ctgsna(3P)		    Sun Performance Library		    ctgsna(3P)

NAME
       ctgsna  - estimate reciprocal condition numbers for specified eigenval‐
       ues and/or eigenvectors of a matrix pair (A, B)

SYNOPSIS
       SUBROUTINE CTGSNA(JOB, HOWMNT, SELECT, N, A, LDA, B, LDB, VL, LDVL,
	     VR, LDVR, S, DIF, MM, M, WORK, LWORK, IWORK, INFO)

       CHARACTER * 1 JOB, HOWMNT
       COMPLEX A(LDA,*), B(LDB,*), VL(LDVL,*), VR(LDVR,*), WORK(*)
       INTEGER N, LDA, LDB, LDVL, LDVR, MM, M, LWORK, INFO
       INTEGER IWORK(*)
       LOGICAL SELECT(*)
       REAL S(*), DIF(*)

       SUBROUTINE CTGSNA_64(JOB, HOWMNT, SELECT, N, A, LDA, B, LDB, VL,
	     LDVL, VR, LDVR, S, DIF, MM, M, WORK, LWORK, IWORK, INFO)

       CHARACTER * 1 JOB, HOWMNT
       COMPLEX A(LDA,*), B(LDB,*), VL(LDVL,*), VR(LDVR,*), WORK(*)
       INTEGER*8 N, LDA, LDB, LDVL, LDVR, MM, M, LWORK, INFO
       INTEGER*8 IWORK(*)
       LOGICAL*8 SELECT(*)
       REAL S(*), DIF(*)

   F95 INTERFACE
       SUBROUTINE TGSNA(JOB, HOWMNT, SELECT, [N], A, [LDA], B, [LDB], VL,
	      [LDVL], VR, [LDVR], S, DIF, MM, M, [WORK], [LWORK], [IWORK],
	      [INFO])

       CHARACTER(LEN=1) :: JOB, HOWMNT
       COMPLEX, DIMENSION(:) :: WORK
       COMPLEX, DIMENSION(:,:) :: A, B, VL, VR
       INTEGER :: N, LDA, LDB, LDVL, LDVR, MM, M, LWORK, INFO
       INTEGER, DIMENSION(:) :: IWORK
       LOGICAL, DIMENSION(:) :: SELECT
       REAL, DIMENSION(:) :: S, DIF

       SUBROUTINE TGSNA_64(JOB, HOWMNT, SELECT, [N], A, [LDA], B, [LDB], VL,
	      [LDVL], VR, [LDVR], S, DIF, MM, M, [WORK], [LWORK], [IWORK],
	      [INFO])

       CHARACTER(LEN=1) :: JOB, HOWMNT
       COMPLEX, DIMENSION(:) :: WORK
       COMPLEX, DIMENSION(:,:) :: A, B, VL, VR
       INTEGER(8) :: N, LDA, LDB, LDVL, LDVR, MM, M, LWORK, INFO
       INTEGER(8), DIMENSION(:) :: IWORK
       LOGICAL(8), DIMENSION(:) :: SELECT
       REAL, DIMENSION(:) :: S, DIF

   C INTERFACE
       #include <sunperf.h>

       void ctgsna(char job, char howmnt, int *select, int n, complex *a,  int
		 lda, complex *b, int ldb, complex *vl, int ldvl, complex *vr,
		 int ldvr, float *s, float *dif, int mm, int *m, int *info);

       void ctgsna_64(char job, char howmnt, long *select, long n, complex *a,
		 long  lda, complex *b, long ldb, complex *vl, long ldvl, com‐
		 plex *vr, long ldvr, float *s, float *dif, long mm, long  *m,
		 long *info);

PURPOSE
       ctgsna estimates reciprocal condition numbers for specified eigenvalues
       and/or eigenvectors of a matrix pair (A, B).

       (A, B) must be in generalized Schur canonical form, that is,  A	and  B
       are both upper triangular.

ARGUMENTS
       JOB (input)
		 Specifies  whether  condition numbers are required for eigen‐
		 values (S) or eigenvectors (DIF):
		 = 'E': for eigenvalues only (S);
		 = 'V': for eigenvectors only (DIF);
		 = 'B': for both eigenvalues and eigenvectors (S and DIF).

       HOWMNT (input)
		 = 'A': compute condition numbers for all eigenpairs;
		 = 'S': compute	 condition  numbers  for  selected  eigenpairs
		 specified by the array SELECT.

       SELECT (input)
		 If  HOWMNT  =	'S', SELECT specifies the eigenpairs for which
		 condition numbers are required. To select  condition  numbers
		 for  the  corresponding  j-th	eigenvalue and/or eigenvector,
		 SELECT(j) must be set to .TRUE..  If HOWMNT = 'A', SELECT  is
		 not referenced.

       N (input) The order of the square matrix pair (A, B). N >= 0.

       A (input) The upper triangular matrix A in the pair (A,B).

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

       B (input) The upper triangular matrix B in the pair (A, B).

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

       VL (input)
		 If JOB = 'E' or 'B', VL must contain left eigenvectors of (A,
		 B), corresponding to the eigenpairs specified by  HOWMNT  and
		 SELECT.   The eigenvectors must be stored in consecutive col‐
		 umns of VL, as returned by CTGEVC.  If JOB = 'V', VL  is  not
		 referenced.

       LDVL (input)
		 The  leading dimension of the array VL. LDVL >= 1; and If JOB
		 = 'E' or 'B', LDVL >= N.

       VR (input)
		 If JOB = 'E' or 'B', VR must contain  right  eigenvectors  of
		 (A,  B),  corresponding to the eigenpairs specified by HOWMNT
		 and SELECT.  The eigenvectors must be stored  in  consecutive
		 columns  of  VR,  as returned by CTGEVC.  If JOB = 'V', VR is
		 not referenced.

       LDVR (input)
		 The leading dimension of the array VR. LDVR >= 1;  If	JOB  =
		 'E' or 'B', LDVR >= N.

       S (output)
		 If  JOB = 'E' or 'B', the reciprocal condition numbers of the
		 selected eigenvalues, stored in consecutive elements  of  the
		 array.	 If JOB = 'V', S is not referenced.

       DIF (output)
		 If  JOB = 'V' or 'B', the estimated reciprocal condition num‐
		 bers of the selected eigenvectors, stored in consecutive ele‐
		 ments	of  the array.	If the eigenvalues cannot be reordered
		 to compute DIF(j), DIF(j) is set to 0; this  can  only	 occur
		 when the true value would be very small anyway.  For each ei‐
		 genvalue/vector specified by SELECT, DIF stores  a  Frobenius
		 norm-based estimate of Difl.  If JOB = 'E', DIF is not refer‐
		 enced.

       MM (input)
		 The number of elements in the arrays S and DIF. MM >= M.

       M (output)
		 The number of elements of the arrays S and DIF used to	 store
		 the specified condition numbers; for each selected eigenvalue
		 one element is used. If HOWMNT = 'A', M is set to N.

       WORK (workspace)
		 If JOB = 'E', WORK is not referenced.	Otherwise, on exit, if
		 INFO = 0, WORK(1) returns the optimal LWORK.

       LWORK (input)
		 The  dimension of the array WORK. LWORK >= max(1, N).	If JOB
		 = 'V' or 'B', LWORK >= max(1, 2*N*N).

       IWORK (workspace)
		 dimension(N+2) If JOB = 'E', IWORK is not referenced.

       INFO (output)
		 = 0: Successful exit
		 < 0: If INFO = -i, the i-th argument had an illegal value

FURTHER DETAILS
       The reciprocal of the condition number of the i-th  generalized	eigen‐
       value w = (a, b) is defined as

	       S(I) = (|v'Au|**2 + |v'Bu|**2)**(1/2) / (norm(u)*norm(v))

       where u and v are the right and left eigenvectors of (A, B) correspond‐
       ing to w; |z| denotes the absolute value of  the	 complex  number,  and
       norm(u) denotes the 2-norm of the vector u. The pair (a, b) corresponds
       to an eigenvalue w = a/b (= v'Au/v'Bu) of the matrix pair  (A,  B).  If
       both  a	and  b	equal  zero,  then  (A,B) is singular and S(I) = -1 is
       returned.

       An approximate error bound on the chordal  distance  between  the  i-th
       computed generalized eigenvalue w and the corresponding exact eigenval‐
       ue lambda is

	       chord(w, lambda) <=   EPS * norm(A, B) / S(I),

       where EPS is the machine precision.

       The reciprocal of the condition number of the right eigenvector	u  and
       left  eigenvector  v  corresponding  to the generalized eigenvalue w is
       defined as follows. Suppose

			(A, B) = ( a   *  ) ( b	 *  )  1
				 ( 0  A22 ),( 0 B22 )  n-1
				   1  n-1     1 n-1

       Then the reciprocal condition number DIF(I) is

	       Difl[(a, b), (A22, B22)]	 = sigma-min( Zl )

       where sigma-min(Zl) denotes the smallest singular value of

	      Zl = [ kron(a, In-1) -kron(1, A22) ]
		   [ kron(b, In-1) -kron(1, B22) ].

       Here In-1 is the identity matrix of size n-1 and X'  is	the  conjugate
       transpose  of X. kron(X, Y) is the Kronecker product between the matri‐
       ces X and Y.

       We approximate the smallest singular value of Zl with an	 upper	bound.
       This is done by CLATDF.

       An approximate error bound for a computed eigenvector VL(i) or VR(i) is
       given by

			   EPS * norm(A, B) / DIF(i).

       See ref. [2-3] for more details and further references.

       Based on contributions by
	  Bo Kagstrom and Peter Poromaa, Department of Computing Science,
	  Umea University, S-901 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
	   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.

				  6 Mar 2009			    ctgsna(3P)
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