f08 Chapter Contents
f08 Chapter Introduction
NAG C Library Manual

# NAG Library Function Documentnag_ztgevc (f08yxc)

## 1  Purpose

nag_ztgevc (f08yxc) computes some or all of the right and/or left generalized eigenvectors of a pair of complex upper triangular matrices $\left(A,B\right)$.

## 2  Specification

 #include #include
 void nag_ztgevc (Nag_OrderType order, Nag_SideType side, Nag_HowManyType how_many, const Nag_Boolean select[], Integer n, const Complex a[], Integer pda, const Complex b[], Integer pdb, Complex vl[], Integer pdvl, Complex vr[], Integer pdvr, Integer mm, Integer *m, NagError *fail)

## 3  Description

nag_ztgevc (f08yxc) computes some or all of the right and/or left generalized eigenvectors of the matrix pair $\left(A,B\right)$ which is assumed to be in upper triangular form. If the matrix pair $\left(A,B\right)$ is not upper triangular then the function nag_zhgeqz (f08xsc) should be called before invoking nag_ztgevc (f08yxc).
The right generalized eigenvector $x$ and the left generalized eigenvector $y$ of $\left(A,B\right)$ corresponding to a generalized eigenvalue $\lambda$ are defined by
 $A-λBx=0$
and
 $yH A-λ B=0.$
If a generalized eigenvalue is determined as $0/0$, which is due to zero diagonal elements at the same locations in both $A$ and $B$, a unit vector is returned as the corresponding eigenvector.
Note that the generalized eigenvalues are computed using nag_zhgeqz (f08xsc) but nag_ztgevc (f08yxc) does not explicitly require the generalized eigenvalues to compute eigenvectors. The ordering of the eigenvectors is based on the ordering of the eigenvalues as computed by nag_ztgevc (f08yxc).
If all eigenvectors are requested, the function may either return the matrices $X$ and/or $Y$ of right or left eigenvectors of $\left(A,B\right)$, or the products $ZX$ and/or $QY$, where $Z$ and $Q$ are two matrices supplied by you. Usually, $Q$ and $Z$ are chosen as the unitary matrices returned by nag_zhgeqz (f08xsc). Equivalently, $Q$ and $Z$ are the left and right Schur vectors of the matrix pair supplied to nag_zhgeqz (f08xsc). In that case, $QY$ and $ZX$ are the left and right generalized eigenvectors, respectively, of the matrix pair supplied to nag_zhgeqz (f08xsc).

## 4  References

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
Golub G H and Van Loan C F (1996) Matrix Computations (3rd Edition) Johns Hopkins University Press, Baltimore
Moler C B and Stewart G W (1973) An algorithm for generalized matrix eigenproblems SIAM J. Numer. Anal. 10 241–256
Stewart G W and Sun J-G (1990) Matrix Perturbation Theory Academic Press, London

## 5  Arguments

1:     orderNag_OrderTypeInput
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 3.2.1.3 in the Essential Introduction for a more detailed explanation of the use of this argument.
Constraint: ${\mathbf{order}}=\mathrm{Nag_RowMajor}$ or Nag_ColMajor.
2:     sideNag_SideTypeInput
On entry: specifies the required sets of generalized eigenvectors.
${\mathbf{side}}=\mathrm{Nag_RightSide}$
Only right eigenvectors are computed.
${\mathbf{side}}=\mathrm{Nag_LeftSide}$
Only left eigenvectors are computed.
${\mathbf{side}}=\mathrm{Nag_BothSides}$
Both left and right eigenvectors are computed.
Constraint: ${\mathbf{side}}=\mathrm{Nag_BothSides}$, $\mathrm{Nag_LeftSide}$ or $\mathrm{Nag_RightSide}$.
3:     how_manyNag_HowManyTypeInput
On entry: specifies further details of the required generalized eigenvectors.
${\mathbf{how_many}}=\mathrm{Nag_ComputeAll}$
All right and/or left eigenvectors are computed.
${\mathbf{how_many}}=\mathrm{Nag_BackTransform}$
All right and/or left eigenvectors are computed; they are backtransformed using the input matrices supplied in arrays vr and/or vl.
${\mathbf{how_many}}=\mathrm{Nag_ComputeSelected}$
Selected right and/or left eigenvectors, defined by the array select, are computed.
Constraint: ${\mathbf{how_many}}=\mathrm{Nag_ComputeAll}$, $\mathrm{Nag_BackTransform}$ or $\mathrm{Nag_ComputeSelected}$.
4:     select[$\mathit{dim}$]const Nag_BooleanInput
Note: the dimension, dim, of the array select must be at least
• $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$ when ${\mathbf{how_many}}=\mathrm{Nag_ComputeSelected}$;
• $1$ otherwise.
On entry: specifies the eigenvectors to be computed if ${\mathbf{how_many}}=\mathrm{Nag_ComputeSelected}$. To select the generalized eigenvector corresponding to the $j$th generalized eigenvalue, the $j$th element of select should be set to Nag_TRUE.
Constraint: ${\mathbf{select}}\left[\mathit{j}\right]=\mathrm{Nag_TRUE}$, for $\mathit{j}=0,1,\dots ,n-1$.
5:     nIntegerInput
On entry: $n$, the order of the matrices $A$ and $B$.
Constraint: ${\mathbf{n}}\ge 0$.
6:     a[$\mathit{dim}$]const ComplexInput
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 matrix $A$ must be in upper triangular form. Usually, this is the matrix $A$ returned by nag_zhgeqz (f08xsc).
7:     pdaIntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array a.
Constraint: ${\mathbf{pda}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
8:     b[$\mathit{dim}$]const ComplexInput
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 matrix $B$ must be in upper triangular form with non-negative real diagonal elements. Usually, this is the matrix $B$ returned by nag_zhgeqz (f08xsc).
9:     pdbIntegerInput
On entry: the stride separating row or column elements (depending on the value of order) in the array b.
Constraint: ${\mathbf{pdb}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$.
10:   vl[$\mathit{dim}$]ComplexInput/Output
Note: the dimension, dim, of the array vl must be at least
• $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{pdvl}}×{\mathbf{mm}}\right)$ when ${\mathbf{side}}=\mathrm{Nag_LeftSide}$ or $\mathrm{Nag_BothSides}$ and ${\mathbf{order}}=\mathrm{Nag_ColMajor}$;
• $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}×{\mathbf{pdvl}}\right)$ when ${\mathbf{side}}=\mathrm{Nag_LeftSide}$ or $\mathrm{Nag_BothSides}$ and ${\mathbf{order}}=\mathrm{Nag_RowMajor}$;
• $1$ when ${\mathbf{side}}=\mathrm{Nag_RightSide}$.
The $i$th element of the $j$th vector is stored in
• ${\mathbf{vl}}\left[\left(j-1\right)×{\mathbf{pdvl}}+i-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_ColMajor}$;
• ${\mathbf{vl}}\left[\left(i-1\right)×{\mathbf{pdvl}}+j-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_RowMajor}$.
On entry: if ${\mathbf{how_many}}=\mathrm{Nag_BackTransform}$ and ${\mathbf{side}}=\mathrm{Nag_LeftSide}$ or $\mathrm{Nag_BothSides}$, vl must be initialized to an $n$ by $n$ matrix $Q$. Usually, this is the unitary matrix $Q$ of left Schur vectors returned by nag_zhgeqz (f08xsc).
On exit: if ${\mathbf{side}}=\mathrm{Nag_LeftSide}$ or $\mathrm{Nag_BothSides}$, vl contains:
• if ${\mathbf{how_many}}=\mathrm{Nag_ComputeAll}$, the matrix $Y$ of left eigenvectors of $\left(A,B\right)$;
• if ${\mathbf{how_many}}=\mathrm{Nag_BackTransform}$, the matrix $QY$;
• if ${\mathbf{how_many}}=\mathrm{Nag_ComputeSelected}$, the left eigenvectors of $\left(A,B\right)$ specified by select, stored consecutively in the rows or columns (depending on the value of order) of the array vl, in the same order as their corresponding eigenvalues.
11:   pdvlIntegerInput
On entry: the stride used in the array vl.
Constraints:
• if ${\mathbf{order}}=\mathrm{Nag_ColMajor}$,
• if ${\mathbf{side}}=\mathrm{Nag_LeftSide}$ or $\mathrm{Nag_BothSides}$, ${\mathbf{pdvl}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$;
• if ${\mathbf{side}}=\mathrm{Nag_RightSide}$, ${\mathbf{pdvl}}\ge 1$;
• if ${\mathbf{order}}=\mathrm{Nag_RowMajor}$,
• if ${\mathbf{side}}=\mathrm{Nag_LeftSide}$ or $\mathrm{Nag_BothSides}$, ${\mathbf{pdvl}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{mm}}\right)$;
• if ${\mathbf{side}}=\mathrm{Nag_RightSide}$, ${\mathbf{pdvl}}\ge 1$.
12:   vr[$\mathit{dim}$]ComplexInput/Output
Note: the dimension, dim, of the array vr must be at least
• $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{pdvr}}×{\mathbf{mm}}\right)$ when ${\mathbf{side}}=\mathrm{Nag_RightSide}$ or $\mathrm{Nag_BothSides}$ and ${\mathbf{order}}=\mathrm{Nag_ColMajor}$;
• $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}×{\mathbf{pdvr}}\right)$ when ${\mathbf{side}}=\mathrm{Nag_RightSide}$ or $\mathrm{Nag_BothSides}$ and ${\mathbf{order}}=\mathrm{Nag_RowMajor}$;
• $1$ when ${\mathbf{side}}=\mathrm{Nag_LeftSide}$.
The $i$th element of the $j$th vector is stored in
• ${\mathbf{vr}}\left[\left(j-1\right)×{\mathbf{pdvr}}+i-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_ColMajor}$;
• ${\mathbf{vr}}\left[\left(i-1\right)×{\mathbf{pdvr}}+j-1\right]$ when ${\mathbf{order}}=\mathrm{Nag_RowMajor}$.
On entry: if ${\mathbf{how_many}}=\mathrm{Nag_BackTransform}$ and ${\mathbf{side}}=\mathrm{Nag_RightSide}$ or $\mathrm{Nag_BothSides}$, vr must be initialized to an $n$ by $n$ matrix $Z$. Usually, this is the unitary matrix $Z$ of right Schur vectors returned by nag_dhgeqz (f08xec).
On exit: if ${\mathbf{side}}=\mathrm{Nag_RightSide}$ or $\mathrm{Nag_BothSides}$, vr contains:
• if ${\mathbf{how_many}}=\mathrm{Nag_ComputeAll}$, the matrix $X$ of right eigenvectors of $\left(A,B\right)$;
• if ${\mathbf{how_many}}=\mathrm{Nag_BackTransform}$, the matrix $ZX$;
• if ${\mathbf{how_many}}=\mathrm{Nag_ComputeSelected}$, the right eigenvectors of $\left(A,B\right)$ specified by select, stored consecutively in the rows or columns (depending on the value of order) of the array vr, in the same order as their corresponding eigenvalues.
13:   pdvrIntegerInput
On entry: the stride used in the array vr.
Constraints:
• if ${\mathbf{order}}=\mathrm{Nag_ColMajor}$,
• if ${\mathbf{side}}=\mathrm{Nag_RightSide}$ or $\mathrm{Nag_BothSides}$, ${\mathbf{pdvr}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$;
• if ${\mathbf{side}}=\mathrm{Nag_LeftSide}$, ${\mathbf{pdvr}}\ge 1$;
• if ${\mathbf{order}}=\mathrm{Nag_RowMajor}$,
• if ${\mathbf{side}}=\mathrm{Nag_RightSide}$ or $\mathrm{Nag_BothSides}$, ${\mathbf{pdvr}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{mm}}\right)$;
• if ${\mathbf{side}}=\mathrm{Nag_LeftSide}$, ${\mathbf{pdvr}}\ge 1$.
14:   mmIntegerInput
On entry: the number of columns in the arrays vl and/or vr.
Constraints:
• if ${\mathbf{how_many}}=\mathrm{Nag_ComputeAll}$ or $\mathrm{Nag_BackTransform}$, ${\mathbf{mm}}\ge {\mathbf{n}}$;
• if ${\mathbf{how_many}}=\mathrm{Nag_ComputeSelected}$, mm must not be less than the number of requested eigenvectors.
15:   mInteger *Output
On exit: the number of columns in the arrays vl and/or vr actually used to store the eigenvectors. If ${\mathbf{how_many}}=\mathrm{Nag_ComputeAll}$ or $\mathrm{Nag_BackTransform}$, m is set to n. Each selected eigenvector occupies one column.
16:   failNagError *Input/Output
The NAG error argument (see Section 3.6 in the Essential Introduction).

## 6  Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
On entry, argument $〈\mathit{\text{value}}〉$ had an illegal value.
NE_CONSTRAINT
On entry, ${\mathbf{select}}\left[\mathit{j}\right]=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{select}}\left[\mathit{j}\right]=\mathrm{Nag_TRUE}$, for $\mathit{j}=0,1,\dots ,n-1$
NE_ENUM_INT_2
On entry, ${\mathbf{how_many}}=〈\mathit{\text{value}}〉$, ${\mathbf{n}}=〈\mathit{\text{value}}〉$ and ${\mathbf{mm}}=〈\mathit{\text{value}}〉$.
Constraint: if ${\mathbf{how_many}}=\mathrm{Nag_ComputeAll}$ or $\mathrm{Nag_BackTransform}$, ${\mathbf{mm}}\ge {\mathbf{n}}$;
if ${\mathbf{how_many}}=\mathrm{Nag_ComputeSelected}$, mm must not be less than the number of requested eigenvectors.
On entry, ${\mathbf{side}}=〈\mathit{\text{value}}〉$, ${\mathbf{pdvl}}=〈\mathit{\text{value}}〉$, ${\mathbf{mm}}=〈\mathit{\text{value}}〉$.
Constraint: if ${\mathbf{side}}=\mathrm{Nag_LeftSide}$ or $\mathrm{Nag_BothSides}$, ${\mathbf{pdvl}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{mm}}\right)$;
if ${\mathbf{side}}=\mathrm{Nag_RightSide}$, ${\mathbf{pdvl}}\ge 1$.
On entry, ${\mathbf{side}}=〈\mathit{\text{value}}〉$, ${\mathbf{pdvl}}=〈\mathit{\text{value}}〉$ and ${\mathbf{n}}=〈\mathit{\text{value}}〉$.
Constraint: if ${\mathbf{side}}=\mathrm{Nag_LeftSide}$ or $\mathrm{Nag_BothSides}$, ${\mathbf{pdvl}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$;
if ${\mathbf{side}}=\mathrm{Nag_RightSide}$, ${\mathbf{pdvl}}\ge 1$.
On entry, ${\mathbf{side}}=〈\mathit{\text{value}}〉$, ${\mathbf{pdvr}}=〈\mathit{\text{value}}〉$, ${\mathbf{mm}}=〈\mathit{\text{value}}〉$.
Constraint: if ${\mathbf{side}}=\mathrm{Nag_RightSide}$ or $\mathrm{Nag_BothSides}$, ${\mathbf{pdvr}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{mm}}\right)$;
if ${\mathbf{side}}=\mathrm{Nag_LeftSide}$, ${\mathbf{pdvr}}\ge 1$.
On entry, ${\mathbf{side}}=〈\mathit{\text{value}}〉$, ${\mathbf{pdvr}}=〈\mathit{\text{value}}〉$ and ${\mathbf{n}}=〈\mathit{\text{value}}〉$.
Constraint: if ${\mathbf{side}}=\mathrm{Nag_RightSide}$ or $\mathrm{Nag_BothSides}$, ${\mathbf{pdvr}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$;
if ${\mathbf{side}}=\mathrm{Nag_LeftSide}$, ${\mathbf{pdvr}}\ge 1$.
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, ${\mathbf{pdvl}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{pdvl}}>0$.
On entry, ${\mathbf{pdvr}}=〈\mathit{\text{value}}〉$.
Constraint: ${\mathbf{pdvr}}>0$.
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.

## 7  Accuracy

It is beyond the scope of this manual to summarize the accuracy of the solution of the generalized eigenvalue problem. Interested readers should consult Section 4.11 of the LAPACK Users' Guide (see Anderson et al. (1999)) and Chapter 6 of Stewart and Sun (1990).

nag_ztgevc (f08yxc) is the sixth step in the solution of the complex generalized eigenvalue problem and is usually called after nag_zhgeqz (f08xsc).
The real analogue of this function is nag_dtgevc (f08ykc).

## 9  Example

This example computes the $\alpha$ and $\beta$ arguments, which defines the generalized eigenvalues and the corresponding left and right eigenvectors, of the matrix pair $\left(A,B\right)$ given by
 $A = 1.0+3.0i 1.0+4.0i 1.0+5.0i 1.0+6.0i 2.0+2.0i 4.0+3.0i 8.0+4.0i 16.0+5.0i 3.0+1.0i 9.0+2.0i 27.0+3.0i 81.0+4.0i 4.0+0.0i 16.0+1.0i 64.0+2.0i 256.0+3.0i$
and
 $B = 1.0+0.0i 2.0+1.0i 3.0+2.0i 4.0+3.0i 1.0+1.0i 4.0+2.0i 9.0+3.0i 16.0+4.0i 1.0+2.0i 8.0+3.0i 27.0+4.0i 64.0+5.0i 1.0+3.0i 16.0+4.0i 81.0+5.0i 256.0+6.0i .$
To compute generalized eigenvalues, it is required to call five functions: nag_zggbal (f08wvc) to balance the matrix, nag_zgeqrf (f08asc) to perform the $QR$ factorization of $B$, nag_zunmqr (f08auc) to apply $Q$ to $A$, nag_zgghrd (f08wsc) to reduce the matrix pair to the generalized Hessenberg form and nag_zhgeqz (f08xsc) to compute the eigenvalues via the $QZ$ algorithm.
The computation of generalized eigenvectors is done by calling nag_ztgevc (f08yxc) to compute the eigenvectors of the balanced matrix pair. The function nag_zggbak (f08wwc) is called to backward transform the eigenvectors to the user-supplied matrix pair. If both left and right eigenvectors are required then nag_zggbak (f08wwc) must be called twice.

### 9.1  Program Text

Program Text (f08yxce.c)

### 9.2  Program Data

Program Data (f08yxce.d)

### 9.3  Program Results

Program Results (f08yxce.r)