NAME

SYNOPSIS

  SUBROUTINE DGGEV( JOBVL, JOBVR, N, A, LDA, B, LDB, ALPHAR, ALPHAI, 
 *      BETA, VL, LDVL, VR, LDVR, WORK, LWORK, INFO)
  CHARACTER * 1 JOBVL, JOBVR
  INTEGER N, LDA, LDB, LDVL, LDVR, LWORK, INFO
  DOUBLE PRECISION A(LDA,*), B(LDB,*), ALPHAR(*), ALPHAI(*), BETA(*), VL(LDVL,*), VR(LDVR,*), WORK(*)
 
  SUBROUTINE DGGEV_64( JOBVL, JOBVR, N, A, LDA, B, LDB, ALPHAR, 
 *      ALPHAI, BETA, VL, LDVL, VR, LDVR, WORK, LWORK, INFO)
  CHARACTER * 1 JOBVL, JOBVR
  INTEGER*8 N, LDA, LDB, LDVL, LDVR, LWORK, INFO
  DOUBLE PRECISION A(LDA,*), B(LDB,*), ALPHAR(*), ALPHAI(*), BETA(*), VL(LDVL,*), VR(LDVR,*), WORK(*)
 

F95 INTERFACE

  SUBROUTINE GGEV( JOBVL, JOBVR, [N], A, [LDA], B, [LDB], ALPHAR, 
 *       ALPHAI, BETA, VL, [LDVL], VR, [LDVR], [WORK], [LWORK], [INFO])
  CHARACTER(LEN=1) :: JOBVL, JOBVR
  INTEGER :: N, LDA, LDB, LDVL, LDVR, LWORK, INFO
  REAL(8), DIMENSION(:) :: ALPHAR, ALPHAI, BETA, WORK
  REAL(8), DIMENSION(:,:) :: A, B, VL, VR
 
  SUBROUTINE GGEV_64( JOBVL, JOBVR, [N], A, [LDA], B, [LDB], ALPHAR, 
 *       ALPHAI, BETA, VL, [LDVL], VR, [LDVR], [WORK], [LWORK], [INFO])
  CHARACTER(LEN=1) :: JOBVL, JOBVR
  INTEGER(8) :: N, LDA, LDB, LDVL, LDVR, LWORK, INFO
  REAL(8), DIMENSION(:) :: ALPHAR, ALPHAI, BETA, WORK
  REAL(8), DIMENSION(:,:) :: A, B, VL, VR
 

C INTERFACE

void dggev(char jobvl, char jobvr, int n, double *a, int lda, double *b, int ldb, double *alphar, double *alphai, double *beta, double *vl, int ldvl, double *vr, int ldvr, int *info);

void dggev_64(char jobvl, char jobvr, long n, double *a, long lda, double *b, long ldb, double *alphar, double *alphai, double *beta, double *vl, long ldvl, double *vr, long ldvr, long *info);

PURPOSE

A generalized eigenvalue for a pair of matrices (A,B) is a scalar lambda or a ratio alpha/beta = lambda, such that A - lambda*B is singular. It is usually represented as the pair (alpha,beta), as there is a reasonable interpretation for beta=0, and even for both being zero.

The right eigenvector v(j) corresponding to the eigenvalue lambda(j) of (A,B) satisfies

                 A * v(j) = lambda(j) * B * v(j).

The left eigenvector u(j) corresponding to the eigenvalue lambda(j) of (A,B) satisfies

                 u(j)**H * A  = lambda(j) * u(j)**H * B .

where u(j)**H is the conjugate-transpose of u(j).

ARGUMENTS

* JOBVL (input)

* JOBVR (input)

* N (input)

The order of the matrices A, B, VL, and VR. N >= 0.

* A (input/output)

On entry, the matrix A in the pair (A,B). On exit, A has been overwritten.

* LDA (input)

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

* B (input/output)

On entry, the matrix B in the pair (A,B). On exit, B has been overwritten.

* LDB (input)

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

* ALPHAR (output)

On exit, (ALPHAR(j) + ALPHAI(j)*i)/BETA(j), j=1,...,N, will be the generalized eigenvalues. If ALPHAI(j) is zero, then the j-th eigenvalue is real; if positive, then the j-th and (j+1)-st eigenvalues are a complex conjugate pair, with ALPHAI(j+1) negative.

Note: the quotients ALPHAR(j)/BETA(j) and ALPHAI(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, ALPHAR and ALPHAI will be always less than and usually comparable with norm(A) in magnitude, and BETA always less than and usually comparable with norm(B).

* ALPHAI (output)

See the description for ALPHAR.

* BETA (output)

See the description for ALPHAR.

* VL (input)

If JOBVL = 'V', the left eigenvectors u(j) are stored one after another in the columns of VL, in the same order as their eigenvalues. If the j-th eigenvalue is real, then u(j) = VL(:,j), the j-th column of VL. If the j-th and (j+1)-th eigenvalues form a complex conjugate pair, then u(j) = VL(:,j)+i*VL(:,j+1) and u(j+1) = VL(:,j)-i*VL(:,j+1). Each eigenvector will be scaled so the largest component have abs(real part)+abs(imag. part)=1. Not referenced if JOBVL = 'N'.

* LDVL (input)

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

* VR (input)

If JOBVR = 'V', the right eigenvectors v(j) are stored one after another in the columns of VR, in the same order as their eigenvalues. If the j-th eigenvalue is real, then v(j) = VR(:,j), the j-th column of VR. If the j-th and (j+1)-th eigenvalues form a complex conjugate pair, then v(j) = VR(:,j)+i*VR(:,j+1) and v(j+1) = VR(:,j)-i*VR(:,j+1). Each eigenvector will be scaled so the largest component have abs(real part)+abs(imag. part)=1. Not referenced if JOBVR = 'N'.

* LDVR (input)

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

* WORK (workspace)

On exit, if INFO = 0, WORK(1) returns the optimal LWORK.

* LWORK (input)

The dimension of the array WORK. LWORK >= max(1,8*N). For good performance, LWORK must generally be larger.

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.

* INFO (output)