.Modelica_LinearSystems2.Math.Matrices.LAPACK.dggevx

Information

Lapack documentation:

   Purpose
   =======

   DGGEVX computes for a pair of N-by-N real nonsymmetric matrices (A,B)
   the generalized eigenvalues, and optionally, the left and/or right
   generalized eigenvectors.

   Optionally also, it computes a balancing transformation to improve
   the conditioning of the eigenvalues and eigenvectors (ILO, IHI,
   LSCALE, RSCALE, ABNRM, and BBNRM), reciprocal condition numbers for
   the eigenvalues (RCONDE), and reciprocal condition numbers for the
   right eigenvectors (RCONDV).

   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
   =========

   BALANC  (input) CHARACTER*1
           Specifies the balance option to be performed.
           = 'N':  do not diagonally scale or permute;
           = 'P':  permute only;
           = 'S':  scale only;
           = 'B':  both permute and scale.
           Computed reciprocal condition numbers will be for the
           matrices after permuting and/or balancing. Permuting does
           not change condition numbers (in exact arithmetic), but
           balancing does.

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

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

   SENSE   (input) CHARACTER*1
           Determines which reciprocal condition numbers are computed.
           = 'N': none are computed;
           = 'E': computed for eigenvalues only;
           = 'V': computed for eigenvectors only;
           = 'B': computed for eigenvalues and eigenvectors.

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

   A       (input/output) DOUBLE PRECISION array, dimension (LDA, N)
           On entry, the matrix A in the pair (A,B).
           On exit, A has been overwritten. If JOBVL='V' or JOBVR='V'
           or both, then A contains the first part of the real Schur
           form of the "balanced" versions of the input A and B.

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

   B       (input/output) DOUBLE PRECISION array, dimension (LDB, N)
           On entry, the matrix B in the pair (A,B).
           On exit, B has been overwritten. If JOBVL='V' or JOBVR='V'
           or both, then B contains the second part of the real Schur
           form of the "balanced" versions of the input A and B.

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

   ALPHAR  (output) DOUBLE PRECISION array, dimension (N)
   ALPHAI  (output) DOUBLE PRECISION array, dimension (N)
   BETA    (output) DOUBLE PRECISION array, dimension (N)
           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).

   VL      (output) DOUBLE PRECISION array, dimension (LDVL,N)
           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) INTEGER
           The leading dimension of the matrix VL. LDVL >= 1, and
           if JOBVL = 'V', LDVL >= N.

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

   ILO,IHI (output) INTEGER
           ILO and IHI are integer values such that on exit
           A(i,j) = 0 and B(i,j) = 0 if i > j and
           j = 1,...,ILO-1 or i = IHI+1,...,N.
           If BALANC = 'N' or 'S', ILO = 1 and IHI = N.

   LSCALE  (output) DOUBLE PRECISION array, dimension (N)
           Details of the permutations and scaling factors applied
           to the left side of A and B.  If PL(j) is the index of the
           row interchanged with row j, and DL(j) is the scaling
           factor applied to row j, then
             LSCALE(j) = PL(j)  for j = 1,...,ILO-1
                       = DL(j)  for j = ILO,...,IHI
                       = PL(j)  for j = IHI+1,...,N.
           The order in which the interchanges are made is N to IHI+1,
           then 1 to ILO-1.

   RSCALE  (output) DOUBLE PRECISION array, dimension (N)
           Details of the permutations and scaling factors applied
           to the right side of A and B.  If PR(j) is the index of the
           column interchanged with column j, and DR(j) is the scaling
           factor applied to column j, then
             RSCALE(j) = PR(j)  for j = 1,...,ILO-1
                       = DR(j)  for j = ILO,...,IHI
                       = PR(j)  for j = IHI+1,...,N
           The order in which the interchanges are made is N to IHI+1,
           then 1 to ILO-1.

   ABNRM   (output) DOUBLE PRECISION
           The one-norm of the balanced matrix A.

   BBNRM   (output) DOUBLE PRECISION
           The one-norm of the balanced matrix B.

   RCONDE  (output) DOUBLE PRECISION array, dimension (N)
           If SENSE = 'E' or 'B', the reciprocal condition numbers of
           the selected eigenvalues, stored in consecutive elements of
           the array. For a complex conjugate pair of eigenvalues two
           consecutive elements of RCONDE are set to the same value.
           Thus RCONDE(j), RCONDV(j), and the j-th columns of VL and VR
           all correspond to the same eigenpair (but not in general the
           j-th eigenpair, unless all eigenpairs are selected).
           If SENSE = 'V', RCONDE is not referenced.

   RCONDV  (output) DOUBLE PRECISION array, dimension (N)
           If SENSE = 'V' or 'B', the estimated reciprocal condition
           numbers of the selected eigenvectors, stored in consecutive
           elements of the array. For a complex eigenvector two
           consecutive elements of RCONDV are set to the same value. If
           the eigenvalues cannot be reordered to compute RCONDV(j),
           RCONDV(j) is set to 0; this can only occur when the true
           value would be very small anyway.
           If SENSE = 'E', RCONDV is not referenced.

   WORK    (workspace/output) DOUBLE PRECISION 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(1,6*N).
           If SENSE = 'E', LWORK >= 12*N.
           If SENSE = 'V' or 'B', LWORK >= 2*N*N+12*N+16.

           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.

   IWORK   (workspace) INTEGER array, dimension (N+6)
           If SENSE = 'E', IWORK is not referenced.

   BWORK   (workspace) LOGICAL array, dimension (N)
           If SENSE = 'N', BWORK is not referenced.

   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 ALPHAR(j), ALPHAI(j), and BETA(j)
                 should be correct for j=INFO+1,...,N.
           > N:  =N+1: other than QZ iteration failed in DHGEQZ.
                 =N+2: error return from DTGEVC.

   Further Details
   ===============

   Balancing a matrix pair (A,B) includes, first, permuting rows and
   columns to isolate eigenvalues, second, applying diagonal similarity
   transformation to the rows and columns to make the rows and columns
   as close in norm as possible. The computed reciprocal condition
   numbers correspond to the balanced matrix. Permuting rows and columns
   will not change the condition numbers (in exact arithmetic) but
   diagonal scaling will.  For further explanation of balancing, see
   section 4.11.1.2 of LAPACK Users' Guide.

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

        chord(w, lambda) <= EPS * norm(ABNRM, BBNRM) / RCONDE(I)

   An approximate error bound for the angle between the i-th computed
   eigenvector VL(i) or VR(i) is given by

        EPS * norm(ABNRM, BBNRM) / DIF(i).

   For further explanation of the reciprocal condition numbers RCONDE
   and RCONDV, see section 4.11 of LAPACK User's Guide.

   =====================================================================

Interface

function dggevx
  input Real A[:, size(A, 1)];
  input Real B[size(A, 1), size(A, 1)];
  output Real alphaReal[size(A, 1)] "Real part of alpha (eigenvalue=(alphaReal+i*alphaImag)/beta)";
  output Real alphaImag[size(A, 1)] "Imaginary part of alpha";
  output Real beta[size(A, 1)] "Denominator of eigenvalue";
  output Real lEigenVectors[size(A, 1), size(A, 1)] "left eigenvectors of matrix A";
  output Real rEigenVectors[size(A, 1), size(A, 1)] "right eigenvectors of matrix A";
  output Integer info;
end dggevx;

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