# NAG CL Interfacef08xac (dgges)

Note: this function is deprecated. Replaced by f08xcc.

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## 1Purpose

f08xac computes the generalized eigenvalues, the generalized real Schur form $\left(S,T\right)$ and, optionally, the left and/or right generalized Schur vectors for a pair of $n×n$ real nonsymmetric matrices $\left(A,B\right)$. f08xac is marked as deprecated by LAPACK; the replacement routine is f08xcc which makes better use of Level 3 BLAS.

## 2Specification

 #include
void  f08xac (Nag_OrderType order, Nag_LeftVecsType jobvsl, Nag_RightVecsType jobvsr, Nag_SortEigValsType sort,
 Nag_Boolean (*selctg)(double ar, double ai, double b),
Integer n, double a[], Integer pda, double b[], Integer pdb, Integer *sdim, double alphar[], double alphai[], double beta[], double vsl[], Integer pdvsl, double vsr[], Integer pdvsr, NagError *fail)
The function may be called by the names: f08xac, nag_lapackeig_dgges or nag_dgges.

## 3Description

The generalized Schur factorization for a pair of real matrices $\left(A,B\right)$ is given by
 $A = QSZT , B = QTZT ,$
where $Q$ and $Z$ are orthogonal, $T$ is upper triangular and $S$ is upper quasi-triangular with $1×1$ and $2×2$ diagonal blocks. The generalized eigenvalues, $\lambda$, of $\left(A,B\right)$ are computed from the diagonals of $S$ and $T$ and satisfy
 $Az = λBz ,$
where $z$ is the corresponding generalized eigenvector. $\lambda$ is actually returned as the pair $\left(\alpha ,\beta \right)$ such that
 $λ = α/β$
since $\beta$, or even both $\alpha$ and $\beta$ can be zero. The columns of $Q$ and $Z$ are the left and right generalized Schur vectors of $\left(A,B\right)$.
Optionally, f08xac can order the generalized eigenvalues on the diagonals of $\left(S,T\right)$ so that selected eigenvalues are at the top left. The leading columns of $Q$ and $Z$ then form an orthonormal basis for the corresponding eigenspaces, the deflating subspaces.
f08xac computes $T$ to have non-negative diagonal elements, and the $2×2$ blocks of $S$ correspond to complex conjugate pairs of generalized eigenvalues. The generalized Schur factorization, before reordering, is computed by the $QZ$ algorithm.

## 4References

Anderson E, Bai Z, Bischof C, Blackford S, Demmel J, Dongarra J J, Du Croz J J, Greenbaum A, Hammarling S, McKenney A and Sorensen D (1999) LAPACK Users' Guide (3rd Edition) SIAM, Philadelphia https://www.netlib.org/lapack/lug
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore

## 5Arguments

1: $\mathbf{order}$Nag_OrderType Input
On entry: the order argument specifies the two-dimensional storage scheme being used, i.e., row-major ordering or column-major ordering. C language defined storage is specified by ${\mathbf{order}}=\mathrm{Nag_RowMajor}$. See Section 3.1.3 in the Introduction to the NAG Library CL Interface for a more detailed explanation of the use of this argument.
Constraint: ${\mathbf{order}}=\mathrm{Nag_RowMajor}$ or $\mathrm{Nag_ColMajor}$.
2: $\mathbf{jobvsl}$Nag_LeftVecsType Input
On entry: if ${\mathbf{jobvsl}}=\mathrm{Nag_NotLeftVecs}$, do not compute the left Schur vectors.
If ${\mathbf{jobvsl}}=\mathrm{Nag_LeftVecs}$, compute the left Schur vectors.
Constraint: ${\mathbf{jobvsl}}=\mathrm{Nag_NotLeftVecs}$ or $\mathrm{Nag_LeftVecs}$.
3: $\mathbf{jobvsr}$Nag_RightVecsType Input
On entry: if ${\mathbf{jobvsr}}=\mathrm{Nag_NotRightVecs}$, do not compute the right Schur vectors.
If ${\mathbf{jobvsr}}=\mathrm{Nag_RightVecs}$, compute the right Schur vectors.
Constraint: ${\mathbf{jobvsr}}=\mathrm{Nag_NotRightVecs}$ or $\mathrm{Nag_RightVecs}$.
4: $\mathbf{sort}$Nag_SortEigValsType Input
On entry: specifies whether or not to order the eigenvalues on the diagonal of the generalized Schur form.
${\mathbf{sort}}=\mathrm{Nag_NoSortEigVals}$
Eigenvalues are not ordered.
${\mathbf{sort}}=\mathrm{Nag_SortEigVals}$
Eigenvalues are ordered (see selctg).
Constraint: ${\mathbf{sort}}=\mathrm{Nag_NoSortEigVals}$ or $\mathrm{Nag_SortEigVals}$.
5: $\mathbf{selctg}$function, supplied by the user External Function
If ${\mathbf{sort}}=\mathrm{Nag_SortEigVals}$, selctg is used to select generalized eigenvalues to be moved to the top left of the generalized Schur form.
If ${\mathbf{sort}}=\mathrm{Nag_NoSortEigVals}$, selctg is not referenced by f08xac, and may be specified as NULLFN.
The specification of selctg is:
 Nag_Boolean selctg (double ar, double ai, double b)
1: $\mathbf{ar}$double Input
2: $\mathbf{ai}$double Input
3: $\mathbf{b}$double Input
On entry: an eigenvalue $\left({\mathbf{ar}}\left[j-1\right]+\sqrt{-1}×{\mathbf{ai}}\left[j-1\right]\right)/{\mathbf{b}}\left[j-1\right]$ is selected if ${\mathbf{selctg}}\left({\mathbf{ar}}\left[j-1\right],{\mathbf{ai}}\left[j-1\right],{\mathbf{b}}\left[j-1\right]\right)=\mathrm{Nag_TRUE}$. If either one of a complex conjugate pair is selected, then both complex generalized eigenvalues are selected.
Note that in the ill-conditioned case, a selected complex generalized eigenvalue may no longer satisfy ${\mathbf{selctg}}\left({\mathbf{ar}}\left[j-1\right],{\mathbf{ai}}\left[j-1\right],{\mathbf{b}}\left[j-1\right]\right)=\mathrm{Nag_TRUE}$ after ordering. ${\mathbf{fail}}\mathbf{.}\mathbf{code}=$ NE_SCHUR_REORDER_SELECT in this case.
6: $\mathbf{n}$Integer Input
On entry: $n$, the order of the matrices $A$ and $B$.
Constraint: ${\mathbf{n}}\ge 0$.
7: $\mathbf{a}\left[\mathit{dim}\right]$double Input/Output
Note: the dimension, dim, of the array a must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{pda}}×{\mathbf{n}}\right)$.
The $\left(i,j\right)$th element of the matrix $A$ is stored in
• ${\mathbf{a}}\left[\left(j-1\right)×{\mathbf{pda}}+i-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_ColMajor}$;
• ${\mathbf{a}}\left[\left(i-1\right)×{\mathbf{pda}}+j-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_RowMajor}$.
On entry: the first of the pair of matrices, $A$.
On exit: a has been overwritten by its generalized Schur form $S$.
8: $\mathbf{pda}$Integer Input
On entry: the stride separating row or column elements (depending on the value of order) in the array a.
Constraint: ${\mathbf{pda}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
9: $\mathbf{b}\left[\mathit{dim}\right]$double Input/Output
Note: the dimension, dim, of the array b must be at least $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{pdb}}×{\mathbf{n}}\right)$.
The $\left(i,j\right)$th element of the matrix $B$ is stored in
• ${\mathbf{b}}\left[\left(j-1\right)×{\mathbf{pdb}}+i-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_ColMajor}$;
• ${\mathbf{b}}\left[\left(i-1\right)×{\mathbf{pdb}}+j-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_RowMajor}$.
On entry: the second of the pair of matrices, $B$.
On exit: b has been overwritten by its generalized Schur form $T$.
10: $\mathbf{pdb}$Integer Input
On entry: the stride separating row or column elements (depending on the value of order) in the array b.
Constraint: ${\mathbf{pdb}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
11: $\mathbf{sdim}$Integer * Output
On exit: if ${\mathbf{sort}}=\mathrm{Nag_NoSortEigVals}$, ${\mathbf{sdim}}=0$.
If ${\mathbf{sort}}=\mathrm{Nag_SortEigVals}$, ${\mathbf{sdim}}=\text{}$ number of eigenvalues (after sorting) for which selctg is Nag_TRUE. (Complex conjugate pairs for which selctg is Nag_TRUE for either eigenvalue count as $2$.)
12: $\mathbf{alphar}\left[{\mathbf{n}}\right]$double Output
On exit: see the description of beta.
13: $\mathbf{alphai}\left[{\mathbf{n}}\right]$double Output
On exit: see the description of beta.
14: $\mathbf{beta}\left[{\mathbf{n}}\right]$double Output
On exit: $\left({\mathbf{alphar}}\left[\mathit{j}-1\right]+{\mathbf{alphai}}\left[\mathit{j}-1\right]×i\right)/{\mathbf{beta}}\left[\mathit{j}-1\right]$, for $\mathit{j}=1,2,\dots ,{\mathbf{n}}$, will be the generalized eigenvalues. ${\mathbf{alphar}}\left[\mathit{j}-1\right]+{\mathbf{alphai}}\left[\mathit{j}-1\right]×i$, and ${\mathbf{beta}}\left[\mathit{j}-1\right]$, for $\mathit{j}=1,2,\dots ,{\mathbf{n}}$, are the diagonals of the complex Schur form $\left(S,T\right)$ that would result if the $2×2$ diagonal blocks of the real Schur form of $\left(A,B\right)$ were further reduced to triangular form using $2×2$ complex unitary transformations.
If ${\mathbf{alphai}}\left[j-1\right]$ is zero, then the $j$th eigenvalue is real; if positive, then the $j$th and $\left(j+1\right)$st eigenvalues are a complex conjugate pair, with ${\mathbf{alphai}}\left[j\right]$ negative.
Note:  the quotients ${\mathbf{alphar}}\left[j-1\right]/{\mathbf{beta}}\left[j-1\right]$ and ${\mathbf{alphai}}\left[j-1\right]/{\mathbf{beta}}\left[j-1\right]$ may easily overflow or underflow, and ${\mathbf{beta}}\left[j-1\right]$ may even be zero. Thus, you should avoid naively computing the ratio $\alpha /\beta$. However, alphar and alphai will always be less than and usually comparable with ${‖A‖}_{2}$ in magnitude, and beta will always be less than and usually comparable with ${‖B‖}_{2}$.
15: $\mathbf{vsl}\left[\mathit{dim}\right]$double Output
Note: the dimension, dim, of the array vsl must be at least
• $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{pdvsl}}×{\mathbf{n}}\right)$ when ${\mathbf{jobvsl}}=\mathrm{Nag_LeftVecs}$;
• $1$ otherwise.
The $\left(i,j\right)$th element of the matrix is stored in
• ${\mathbf{vsl}}\left[\left(j-1\right)×{\mathbf{pdvsl}}+i-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_ColMajor}$;
• ${\mathbf{vsl}}\left[\left(i-1\right)×{\mathbf{pdvsl}}+j-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_RowMajor}$.
On exit: if ${\mathbf{jobvsl}}=\mathrm{Nag_LeftVecs}$, vsl will contain the left Schur vectors, $Q$.
If ${\mathbf{jobvsl}}=\mathrm{Nag_NotLeftVecs}$, vsl is not referenced.
16: $\mathbf{pdvsl}$Integer Input
On entry: the stride separating row or column elements (depending on the value of order) in the array vsl.
Constraints:
• if ${\mathbf{jobvsl}}=\mathrm{Nag_LeftVecs}$, ${\mathbf{pdvsl}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$;
• otherwise ${\mathbf{pdvsl}}\ge 1$.
17: $\mathbf{vsr}\left[\mathit{dim}\right]$double Output
Note: the dimension, dim, of the array vsr must be at least
• $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{pdvsr}}×{\mathbf{n}}\right)$ when ${\mathbf{jobvsr}}=\mathrm{Nag_RightVecs}$;
• $1$ otherwise.
The $\left(i,j\right)$th element of the matrix is stored in
• ${\mathbf{vsr}}\left[\left(j-1\right)×{\mathbf{pdvsr}}+i-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_ColMajor}$;
• ${\mathbf{vsr}}\left[\left(i-1\right)×{\mathbf{pdvsr}}+j-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_RowMajor}$.
On exit: if ${\mathbf{jobvsr}}=\mathrm{Nag_RightVecs}$, vsr will contain the right Schur vectors, $Z$.
If ${\mathbf{jobvsr}}=\mathrm{Nag_NotRightVecs}$, vsr is not referenced.
18: $\mathbf{pdvsr}$Integer Input
On entry: the stride separating row or column elements (depending on the value of order) in the array vsr.
Constraints:
• if ${\mathbf{jobvsr}}=\mathrm{Nag_RightVecs}$, ${\mathbf{pdvsr}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$;
• otherwise ${\mathbf{pdvsr}}\ge 1$.
19: $\mathbf{fail}$NagError * Input/Output
The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

## 6Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 3.1.2 in the Introduction to the NAG Library CL Interface for further information.
On entry, argument $⟨\mathit{\text{value}}⟩$ had an illegal value.
NE_ENUM_INT_2
On entry, ${\mathbf{jobvsl}}=⟨\mathit{\text{value}}⟩$, ${\mathbf{pdvsl}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: if ${\mathbf{jobvsl}}=\mathrm{Nag_LeftVecs}$, ${\mathbf{pdvsl}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$;
otherwise ${\mathbf{pdvsl}}\ge 1$.
On entry, ${\mathbf{jobvsr}}=⟨\mathit{\text{value}}⟩$, ${\mathbf{pdvsr}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: if ${\mathbf{jobvsr}}=\mathrm{Nag_RightVecs}$, ${\mathbf{pdvsr}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$;
otherwise ${\mathbf{pdvsr}}\ge 1$.
NE_INT
On entry, ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{n}}\ge 0$.
On entry, ${\mathbf{pda}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{pda}}>0$.
On entry, ${\mathbf{pdb}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{pdb}}>0$.
On entry, ${\mathbf{pdvsl}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{pdvsl}}>0$.
On entry, ${\mathbf{pdvsr}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{pdvsr}}>0$.
NE_INT_2
On entry, ${\mathbf{pda}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{pda}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
On entry, ${\mathbf{pdb}}=⟨\mathit{\text{value}}⟩$ and ${\mathbf{n}}=⟨\mathit{\text{value}}⟩$.
Constraint: ${\mathbf{pdb}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
NE_INTERNAL_ERROR
An internal error has occurred in this function. Check the function call and any array sizes. If the call is correct then please contact NAG for assistance.
See Section 7.5 in the Introduction to the NAG Library CL Interface for further information.
NE_ITERATION_QZ
The $QZ$ iteration failed. No eigenvectors have been calculated but ${\mathbf{alphar}}\left[j\right]$, ${\mathbf{alphai}}\left[j\right]$ and ${\mathbf{beta}}\left[j\right]$ should be correct from element $⟨\mathit{\text{value}}⟩$.
The $QZ$ iteration failed with an unexpected error, please contact NAG.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 8 in the Introduction to the NAG Library CL Interface for further information.
NE_SCHUR_REORDER
The eigenvalues could not be reordered because some eigenvalues were too close to separate (the problem is very ill-conditioned).
NE_SCHUR_REORDER_SELECT
After reordering, roundoff changed values of some complex eigenvalues so that leading eigenvalues in the generalized Schur form no longer satisfy ${\mathbf{selctg}}=\mathrm{Nag_TRUE}$. This could also be caused by underflow due to scaling.

## 7Accuracy

The computed generalized Schur factorization satisfies
 $A+E = QS ZT , B+F = QT ZT ,$
where
 $‖(E,F)‖ F = O(ε) ‖(A,B)‖ F$
and $\epsilon$ is the machine precision. See Section 4.11 of Anderson et al. (1999) for further details.

## 8Parallelism and Performance

f08xac is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
f08xac makes calls to BLAS and/or LAPACK routines, which may be threaded within the vendor library used by this implementation. Consult the documentation for the vendor library for further information.
Please consult the X06 Chapter Introduction for information on how to control and interrogate the OpenMP environment used within this function. Please also consult the Users' Note for your implementation for any additional implementation-specific information.

The total number of floating-point operations is proportional to ${n}^{3}$.
The complex analogue of this function is f08xnc.

## 10Example

This example finds the generalized Schur factorization of the matrix pair $\left(A,B\right)$, where
 $A = ( 3.9 12.5 -34.5 -0.5 4.3 21.5 -47.5 7.5 4.3 21.5 -43.5 3.5 4.4 26.0 -46.0 6.0 ) and B= ( 1.0 2.0 -3.0 1.0 1.0 3.0 -5.0 4.0 1.0 3.0 -4.0 3.0 1.0 3.0 -4.0 4.0 ) ,$
such that the real positive eigenvalues of $\left(A,B\right)$ correspond to the top left diagonal elements of the generalized Schur form, $\left(S,T\right)$.

### 10.1Program Text

Program Text (f08xace.c)

### 10.2Program Data

Program Data (f08xace.d)

### 10.3Program Results

Program Results (f08xace.r)