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Chapter Contents
Chapter Introduction
NAG Toolbox

# NAG Toolbox: nag_sparseig_real_band_solve (f12ag)

## Purpose

nag_sparseig_real_band_solve (f12ag) is the main solver function in a suite of functions consisting of nag_sparseig_real_option (f12ad), nag_sparseig_real_band_init (f12af) and nag_sparseig_real_band_solve (f12ag). It must be called following an initial call to nag_sparseig_real_band_init (f12af) and following any calls to nag_sparseig_real_option (f12ad).
nag_sparseig_real_band_solve (f12ag) returns approximations to selected eigenvalues, and (optionally) the corresponding eigenvectors, of a standard or generalized eigenvalue problem defined by real banded nonsymmetric matrices. The banded matrix must be stored using the LAPACK storage format for real banded nonsymmetric matrices.

## Syntax

[nconv, dr, di, z, resid, v, comm, icomm, ifail] = f12ag(kl, ku, ab, mb, sigmar, sigmai, resid, comm, icomm)
[nconv, dr, di, z, resid, v, comm, icomm, ifail] = nag_sparseig_real_band_solve(kl, ku, ab, mb, sigmar, sigmai, resid, comm, icomm)

## Description

The suite of functions is designed to calculate some of the eigenvalues, λ $\lambda$, (and optionally the corresponding eigenvectors, x $x$) of a standard eigenvalue problem Ax = λx $Ax=\lambda x$, or of a generalized eigenvalue problem Ax = λBx $Ax=\lambda Bx$ of order n $n$, where n $n$ is large and the coefficient matrices A $A$ and B $B$ are banded, real and nonsymmetric.
Following a call to the initialization function nag_sparseig_real_band_init (f12af), nag_sparseig_real_band_solve (f12ag) returns the converged approximations to eigenvalues and (optionally) the corresponding approximate eigenvectors and/or an orthonormal basis for the associated approximate invariant subspace. The eigenvalues (and eigenvectors) are selected from those of a standard or generalized eigenvalue problem defined by real banded nonsymmetric matrices. There is negligible additional computational cost to obtain eigenvectors; an orthonormal basis is always computed, but there is an additional storage cost if both are requested.
The banded matrices A $A$ and B$B$ must be stored using the LAPACK column ordered storage format for banded nonsymmetric matrices; please refer to Section [Packed storage] in the F07 Chapter Introduction for details on this storage format.
nag_sparseig_real_band_solve (f12ag) is based on the banded driver functions dnbdr1 to dnbdr6 from the ARPACK package, which uses the Implicitly Restarted Arnoldi iteration method. The method is described in Lehoucq and Sorensen (1996) and Lehoucq (2001) while its use within the ARPACK software is described in great detail in Lehoucq et al. (1998). An evaluation of software for computing eigenvalues of sparse nonsymmetric matrices is provided in Lehoucq and Scott (1996). This suite of functions offers the same functionality as the ARPACK banded driver software for real nonsymmetric problems, but the interface design is quite different in order to make the option setting clearer and to combine the different drivers into a general purpose function.
nag_sparseig_real_band_solve (f12ag), is a general purpose function that must be called following initialization by nag_sparseig_real_band_init (f12af). nag_sparseig_real_band_solve (f12ag) uses options, set either by default or explicitly by calling nag_sparseig_real_option (f12ad), to return the converged approximations to selected eigenvalues and (optionally):
 – the corresponding approximate eigenvectors; – an orthonormal basis for the associated approximate invariant subspace; – both.

## References

Lehoucq R B (2001) Implicitly restarted Arnoldi methods and subspace iteration SIAM Journal on Matrix Analysis and Applications 23 551–562
Lehoucq R B and Scott J A (1996) An evaluation of software for computing eigenvalues of sparse nonsymmetric matrices Preprint MCS-P547-1195 Argonne National Laboratory
Lehoucq R B and Sorensen D C (1996) Deflation techniques for an implicitly restarted Arnoldi iteration SIAM Journal on Matrix Analysis and Applications 17 789–821
Lehoucq R B, Sorensen D C and Yang C (1998) ARPACK Users' Guide: Solution of Large-scale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods SIAM, Philidelphia

## Parameters

### Compulsory Input Parameters

1:     kl – int64int32nag_int scalar
The number of subdiagonals of the matrices A $A$ and B$B$.
Constraint: kl0${\mathbf{kl}}\ge 0$.
2:     ku – int64int32nag_int scalar
The number of superdiagonals of the matrices A $A$ and B$B$.
Constraint: ku0${\mathbf{ku}}\ge 0$.
3:     ab(ldab, : $:$) – double array
The first dimension of the array ab must be at least 2 × kl + ku + 1$2×{\mathbf{kl}}+{\mathbf{ku}}+1$
The second dimension of the array must be at least max (1,n) $\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$
Must contain the matrix A$A$ in LAPACK banded storage format for nonsymmetric matrices (see Section [Band storage] in the F07 Chapter Introduction).
4:     mb(ldmb, : $:$) – double array
The first dimension of the array mb must be at least 2 × kl + ku + 1$2×{\mathbf{kl}}+{\mathbf{ku}}+1$
The second dimension of the array must be at least max (1,n)$\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$
Must contain the matrix B$B$ in LAPACK banded storage format for nonsymmetric matrices (see Section [Band storage] in the F07 Chapter Introduction).
5:     sigmar – double scalar
If one of the Shifted Inverse Real modes (see nag_sparseig_real_option (f12ad)) have been selected then sigmar must contain the real part of the shift used; otherwise sigmar is not referenced. Section [Computational modes for non-Hermitian problems] in the F12 Chapter Introduction describes the use of shift and inverse transformations.
6:     sigmai – double scalar
If one of the Shifted Inverse Real modes (see nag_sparseig_real_option (f12ad)) have been selected then sigmai must contain the imaginary part of the shift used; otherwise sigmai is not referenced. Section [Computational modes for non-Hermitian problems] in the F12 Chapter Introduction describes the use of shift and inverse transformations.
7:     resid( : $:$) – double array
Note: the dimension of the array resid must be at least n${\mathbf{n}}$ (see nag_sparseig_real_band_init (f12af)).
Need not be set unless the option Initial Residual has been set in a prior call to nag_sparseig_real_option (f12ad) in which case resid must contain an initial residual vector.
8:     comm( : $:$) – double array
Must remain unchanged from the prior call to nag_sparseig_real_option (f12ad) and nag_sparseig_real_band_init (f12af).
9:     icomm( : $:$) – int64int32nag_int array
Must remain unchanged from the prior call to nag_sparseig_real_option (f12ad) and nag_sparseig_real_band_init (f12af).

None.

### Input Parameters Omitted from the MATLAB Interface

ldab ldmb ldz ldv

### Output Parameters

1:     nconv – int64int32nag_int scalar
The number of converged eigenvalues.
2:     dr( : $:$) – double array
Note: the dimension of the array dr must be at least nev + 1 ${\mathbf{nev}}+1$ (see nag_sparseig_real_band_init (f12af)).
The first nconv locations of the array dr contain the real parts of the converged approximate eigenvalues. The number of eigenvalues returned may be one more than the number requested by nev since complex values occur as conjugate pairs and the second in the pair can be returned in position nev + 1${\mathbf{nev}}+1$ of the array.
3:     di( : $:$) – double array
Note: the dimension of the array di must be at least nev + 1 ${\mathbf{nev}}+1$ (see nag_sparseig_real_band_init (f12af)).
The first nconv locations of the array di contain the imaginary parts of the converged approximate eigenvalues. The number of eigenvalues returned may be one more than the number requested by nev since complex values occur as conjugate pairs and the second in the pair can be returned in position nev + 1${\mathbf{nev}}+1$ of the array.
4:     z(n × (nev + 1)${\mathbf{n}}×\left({\mathbf{nev}}+1\right)$) – double array
The second dimension of the array will be n × (nev + 1) ${\mathbf{n}}×\left({\mathbf{nev}}+1\right)$
If the default option Vectors = Ritz${\mathbf{Vectors}}=\text{Ritz}$ has been selected then z contains the final set of eigenvectors corresponding to the eigenvalues held in dr and di. The complex eigenvector associated with the eigenvalue with positive imaginary part is stored in two consecutive columns. The first column holds the real part of the eigenvector and the second column holds the imaginary part. The eigenvector associated with the eigenvalue with negative imaginary part is simply the complex conjugate of the eigenvector associated with the positive imaginary part.
5:     resid( : $:$) – double array
Note: the dimension of the array resid must be at least n${\mathbf{n}}$ (see nag_sparseig_real_band_init (f12af)).
Contains the final residual vector.
6:     v(n × ncv${\mathbf{n}}×{\mathbf{ncv}}$) – double array
If the option Vectors (see nag_sparseig_real_option (f12ad)) has been set to Schur or Ritz then the first nconv × n${\mathbf{nconv}}×n$ elements of v will contain approximate Schur vectors that span the desired invariant subspace.
The i$i$th Schur vector is stored in the i$i$th column of v.
7:     comm( : $:$) – double array
Contains no useful information.
8:     icomm( : $:$) – int64int32nag_int array
Contains no useful information.
9:     ifail – int64int32nag_int scalar
${\mathrm{ifail}}={\mathbf{0}}$ unless the function detects an error (see [Error Indicators and Warnings]).

## Error Indicators and Warnings

Errors or warnings detected by the function:
ifail = 1${\mathbf{ifail}}=1$
On entry, kl < 0 ${\mathbf{kl}}<0$.
ifail = 2${\mathbf{ifail}}=2$
On entry, ku < 0 ${\mathbf{ku}}<0$.
ifail = 3${\mathbf{ifail}}=3$
On entry, ldab < 2 × kl + ku + 1 $\mathit{ldab}<2×{\mathbf{kl}}+{\mathbf{ku}}+1$.
ifail = 4${\mathbf{ifail}}=4$
On entry, the option ${\mathbf{Shifted Inverse Imaginary}}$ was selected, and sigmai = zero${\mathbf{sigmai}}=\text{zero}$, but sigmai must be nonzero for this computational mode.
ifail = 5${\mathbf{ifail}}=5$
${\mathbf{Iteration Limit}}<0$.
ifail = 6${\mathbf{ifail}}=6$
The options Generalized and Regular are incompatible.
ifail = 7${\mathbf{ifail}}=7$
The Initial Residual was selected but the starting vector held in resid is zero.
ifail = 8${\mathbf{ifail}}=8$
Either the initialization function nag_sparseig_real_band_init (f12af) has not been called prior to the first call of this function or a communication array has become corrupted.
ifail = 9${\mathbf{ifail}}=9$
On entry, ldz < n$\mathit{ldz}<{\mathbf{n}}$ or ldz < 1 $\mathit{ldz}<1$ when no vectors are required.
ifail = 10${\mathbf{ifail}}=10$
On entry, the option Vectors = Select ${\mathbf{Vectors}}=\text{Select}$ was selected, but this is not yet implemented.
ifail = 11${\mathbf{ifail}}=11$
The number of eigenvalues found to sufficient accuracy is zero.
ifail = 12${\mathbf{ifail}}=12$
Could not build an Arnoldi factorization. Consider changing ncv or nev in the initialization function (see Section [Parameters] in (f12af) for details of these parameters).
ifail = 13${\mathbf{ifail}}=13$
Unexpected error in internal call to compute eigenvalues and corresponding error bounds of the current upper Hessenberg matrix. Please contact NAG.
ifail = 14${\mathbf{ifail}}=14$
Unexpected error during calculation of a real Schur form: there was a failure to compute all the converged eigenvalues. Please contact NAG.
ifail = 15${\mathbf{ifail}}=15$
Unexpected error: the computed Schur form could not be reordered by an internal call. Please contact NAG.
ifail = 16${\mathbf{ifail}}=16$
ifail = 17${\mathbf{ifail}}=17$
ifail = 18${\mathbf{ifail}}=18$
ifail = 19${\mathbf{ifail}}=19$
ifail = 20${\mathbf{ifail}}=20$
ifail = 21${\mathbf{ifail}}=21$
The maximum number of iterations has been reached. Some Ritz values may have converged; nconv returns the number of converged values.
ifail = 22${\mathbf{ifail}}=22$
No shifts could be applied during a cycle of the implicitly restarted Arnoldi iteration. One possibility is to increase the size of ncv relative to nev (see Section [Parameters] in (f12af) for details of these parameters).
ifail = 23${\mathbf{ifail}}=23$
Overflow occurred during transformation of Ritz values to those of the original problem.
ifail = 24${\mathbf{ifail}}=24$
ifail = 25${\mathbf{ifail}}=25$

## Accuracy

The relative accuracy of a Ritz value, λ $\lambda$, is considered acceptable if its Ritz estimate Tolerance × |λ| $\le {\mathbf{Tolerance}}×|\lambda |$. The default Tolerance used is the machine precision given by nag_machine_precision (x02aj).

None.

## Example

```function nag_sparseig_real_band_solve_example
nx = 10;
n = nx*nx;
nev = 4;
ncv = 10;
kl = 10;
ku = 10;

% Construct ab and mb
ab = zeros(2*kl+ku+1,n);
mb = zeros(2*kl+ku+1,n);

% Main diagonal of A.
idiag = kl + ku + 1;
for j=1:n
ab(idiag,j) = 4;
mb(idiag,j) = 4;
end

% First subdiagonal and superdiagonal of A.
isup = kl + ku;
isub = kl + ku + 2;
rho = 100;
h = 1/11;
for i=1:nx
lo = (i-1)*nx;
for j=lo+1:lo+nx-1
ab(isub,j+1) = -1 + 0.5*h*rho;
ab(isup,j) = -1 - 0.5*h*rho;
end
end
for j = 1:n - 1
mb(isub,j+1) = 1;
mb(isup,j) = 1;
end

% kl-th subdiagonal and ku-th super-diagonal.
isup = kl + 1;
isub = 2*kl + ku + 1;
for i = 1:nx - 1
lo = (i-1)*nx;
for j = lo + 1:lo + nx
ab(isup,nx+j) = -1;
ab(isub,j) = -1;
end
end

sigmar = 0;
sigmai = 0;
resid = zeros(100,1);

[icomm, comm, ifail] = nag_sparseig_real_band_init(int64(n), int64(nev), int64(ncv));
[icomm, comm, ifail] = nag_sparseig_real_option('REGULAR INVERSE', icomm, comm);
[icomm, comm, ifail] = nag_sparseig_real_option('GENERALIZED', icomm, comm);
[nconv, dr, di, z, residOut, v, comm, icomm, ifail] = ...
nag_sparseig_real_band_solve(int64(kl), int64(ku), ab, mb, sigmar, sigmai, resid, comm, icomm);
nconv, dr(1:double(nconv)), di(1:double(nconv)), ifail
```
```

nconv =

4

ans =

3.5094
3.5094
3.3702
3.3702

ans =

1.1197
-1.1197
1.1145
-1.1145

ifail =

0

```
```function f12ag_example
nx = 10;
n = nx*nx;
nev = 4;
ncv = 10;
kl = 10;
ku = 10;

% Construct ab and mb
ab = zeros(2*kl+ku+1,n);
mb = zeros(2*kl+ku+1,n);

% Main diagonal of A.
idiag = kl + ku + 1;
for j=1:n
ab(idiag,j) = 4;
mb(idiag,j) = 4;
end

% First subdiagonal and superdiagonal of A.
isup = kl + ku;
isub = kl + ku + 2;
rho = 100;
h = 1/11;
for i=1:nx
lo = (i-1)*nx;
for j=lo+1:lo+nx-1
ab(isub,j+1) = -1 + 0.5*h*rho;
ab(isup,j) = -1 - 0.5*h*rho;
end
end
for j = 1:n - 1
mb(isub,j+1) = 1;
mb(isup,j) = 1;
end

% kl-th subdiagonal and ku-th super-diagonal.
isup = kl + 1;
isub = 2*kl + ku + 1;
for i = 1:nx - 1
lo = (i-1)*nx;
for j = lo + 1:lo + nx
ab(isup,nx+j) = -1;
ab(isub,j) = -1;
end
end

sigmar = 0;
sigmai = 0;
resid = zeros(100,1);

[icomm, comm, ifail] = f12af(int64(n), int64(nev), int64(ncv));
[icomm, comm, ifail] = f12ad('REGULAR INVERSE', icomm, comm);
[icomm, comm, ifail] = f12ad('GENERALIZED', icomm, comm);
[nconv, dr, di, z, residOut, v, comm, icomm, ifail] = ...
f12ag(int64(kl), int64(ku), ab, mb, sigmar, sigmai, resid, comm, icomm);
nconv, dr(1:double(nconv)), di(1:double(nconv)), ifail
```
```

nconv =

4

ans =

3.5094
3.5094
3.3702
3.3702

ans =

1.1197
-1.1197
1.1145
-1.1145

ifail =

0

```