NAG FL Interface
f12acf (real_proc)
Note: this routine uses optional parameters to define choices in the problem specification. If you wish to use default
settings for all of the optional parameters, then the option setting routine f12adf need not be called.
If, however, you wish to reset some or all of the settings please refer to Section 11 in f12adf for a detailed description of the specification of the optional parameters.
1
Purpose
f12acf is a postprocessing routine that must be called following a final exit from
f12abf. These are part of a suite of routines for the solution of real sparse eigensystems. The suite also includes
f12aaf,
f12adf and
f12aef.
2
Specification
Fortran Interface
Subroutine f12acf ( 
nconv, dr, di, z, ldz, sigmar, sigmai, resid, v, ldv, comm, icomm, ifail) 
Integer, Intent (In) 
:: 
ldz, ldv 
Integer, Intent (Inout) 
:: 
icomm(*), ifail 
Integer, Intent (Out) 
:: 
nconv 
Real (Kind=nag_wp), Intent (In) 
:: 
sigmar, sigmai, resid(*) 
Real (Kind=nag_wp), Intent (Inout) 
:: 
dr(*), di(*), z(ldz,*), v(ldv,*), comm(*) 

C Header Interface
#include <nag.h>
void 
f12acf_ (Integer *nconv, double dr[], double di[], double z[], const Integer *ldz, const double *sigmar, const double *sigmai, const double resid[], double v[], const Integer *ldv, double comm[], Integer icomm[], Integer *ifail) 

C++ Header Interface
#include <nag.h> extern "C" {
void 
f12acf_ (Integer &nconv, double dr[], double di[], double z[], const Integer &ldz, const double &sigmar, const double &sigmai, const double resid[], double v[], const Integer &ldv, double comm[], Integer icomm[], Integer &ifail) 
}

The routine may be called by the names f12acf or nagf_sparseig_real_proc.
3
Description
The suite of routines is designed to calculate some of the eigenvalues, $\lambda $, (and optionally the corresponding eigenvectors, $x$) of a standard eigenvalue problem $Ax=\lambda x$, or of a generalized eigenvalue problem $Ax=\lambda Bx$ of order $n$, where $n$ is large and the coefficient matrices $A$ and $B$ are sparse, real and nonsymmetric. The suite can also be used to find selected eigenvalues/eigenvectors of smaller scale dense, real and nonsymmetric problems.
Following a call to
f12abf,
f12acf 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 nonsymmetric matrices. There is negligible additional cost to obtain eigenvectors; an orthonormal basis is always computed, but there is an additional storage cost if both are requested.
f12acf is based on the routine
dneupd 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 routines offers the same functionality as the ARPACK software for real nonsymmetric problems, but the interface design is quite different in order to make the option setting clearer and to simplify some of the interfaces.
f12acf, is a postprocessing routine that must be called following a successful final exit from
f12abf.
f12acf uses data returned from
f12abf and options, set either by default or explicitly by calling
f12adf, to return the converged approximations to selected eigenvalues and (optionally):

–the corresponding approximate eigenvectors;

–an orthonormal basis for the associated approximate invariant subspace;

–both.
4
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 MCSP5471195 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 Largescale Eigenvalue Problems with Implicitly Restarted Arnoldi Methods SIAM, Philidelphia
5
Arguments

1:
$\mathbf{nconv}$ – Integer
Output

On exit: the number of converged eigenvalues as found by
f12abf.

2:
$\mathbf{dr}\left(*\right)$ – Real (Kind=nag_wp) array
Output

Note: the dimension of the array
dr
must be at least
${\mathbf{nev}}+1$ (see
f12aaf).
On exit: the first
nconv locations of the array
dr contain the real parts of the converged approximate eigenvalues.

3:
$\mathbf{di}\left(*\right)$ – Real (Kind=nag_wp) array
Output

Note: the dimension of the array
di
must be at least
${\mathbf{nev}}+1$ (see
f12aaf).
On exit: the first
nconv locations of the array
di contain the imaginary parts of the converged approximate eigenvalues.

4:
$\mathbf{z}\left({\mathbf{ldz}},*\right)$ – Real (Kind=nag_wp) array
Output

Note: the second dimension of the array
z
must be at least
${\mathbf{nev}}+1$ if the default option
${\mathbf{Vectors}}=\mathrm{RITZ}$
has been selected and at least
$1$ if the option
${\mathbf{Vectors}}=\mathrm{NONE}$ or
$\mathrm{SCHUR}$
has been selected (see
f12aaf).
On exit: if the default option
${\mathbf{Vectors}}=\mathrm{RITZ}$ (see
f12adf) 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:
$\mathbf{ldz}$ – Integer
Input

On entry: the first dimension of the array
z as declared in the (sub)program from which
f12acf is called.
Constraints:
 if the default option ${\mathbf{Vectors}}=\text{Ritz}$ has been selected, ${\mathbf{ldz}}\ge {\mathbf{n}}$;
 if the option ${\mathbf{Vectors}}=\text{None or Schur}$ has been selected, ${\mathbf{ldz}}\ge 1$.

6:
$\mathbf{sigmar}$ – Real (Kind=nag_wp)
Input

On entry: if one of the
Shifted Inverse Real modes have been selected then
sigmar contains the real part of the shift used; otherwise
sigmar is not referenced.

7:
$\mathbf{sigmai}$ – Real (Kind=nag_wp)
Input

On entry: if one of the
Shifted Inverse Real modes have been selected then
sigmai contains the imaginary part of the shift used; otherwise
sigmai is not referenced.

8:
$\mathbf{resid}\left(*\right)$ – Real (Kind=nag_wp) array
Input

Note: the dimension of the array
resid
must be at least
${\mathbf{n}}$ (see
f12aaf).
On entry: must not be modified following a call to
f12abf since it contains data required by
f12acf.

9:
$\mathbf{v}\left({\mathbf{ldv}},*\right)$ – Real (Kind=nag_wp) array
Input/Output

Note: the second dimension of the array
v
must be at least
$\mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{ncv}}\right)$ (see
f12aaf).
On entry: the
ncv columns of
v contain the Arnoldi basis vectors for
$\mathrm{OP}$ as constructed by
f12abf.
On exit: if the option
${\mathbf{Vectors}}=\mathrm{SCHUR}$ has been set, or the option
${\mathbf{Vectors}}=\mathrm{RITZ}$ has been set and a separate array
z has been passed (i.e.,
z does not equal
v), then the first
nconv columns of
v will contain approximate Schur vectors that span the desired invariant subspace.

10:
$\mathbf{ldv}$ – Integer
Input

On entry: the first dimension of the array
v as declared in the (sub)program from which
f12acf is called.
Constraint:
${\mathbf{ldv}}\ge {\mathbf{n}}$.

11:
$\mathbf{comm}\left(*\right)$ – Real (Kind=nag_wp) array
Communication Array

Note: the actual argument supplied
must be the array
comm supplied to the initialization routine
f12aaf.
On initial entry: must remain unchanged from the prior call to
f12abf.
On exit: contains data on the current state of the solution.

12:
$\mathbf{icomm}\left(*\right)$ – Integer array
Communication Array

Note: the actual argument supplied
must be the array
icomm supplied to the initialization routine
f12aaf.
On initial entry: must remain unchanged from the prior call to
f12abf.
On exit: contains data on the current state of the solution.

13:
$\mathbf{ifail}$ – Integer
Input/Output

On entry:
ifail must be set to
$0$,
$1$ or
$1$ to set behaviour on detection of an error; these values have no effect when no error is detected.
A value of $0$ causes the printing of an error message and program execution will be halted; otherwise program execution continues. A value of $1$ means that an error message is printed while a value of $1$ means that it is not.
If halting is not appropriate, the value
$1$ or
$1$ is recommended. If message printing is undesirable, then the value
$1$ is recommended. Otherwise, the value
$0$ is recommended.
When the value $\mathbf{1}$ or $\mathbf{1}$ is used it is essential to test the value of ifail on exit.
On exit:
${\mathbf{ifail}}={\mathbf{0}}$ unless the routine detects an error or a warning has been flagged (see
Section 6).
6
Error Indicators and Warnings
If on entry
${\mathbf{ifail}}=0$ or
$1$, explanatory error messages are output on the current error message unit (as defined by
x04aaf).
Errors or warnings detected by the routine:
 ${\mathbf{ifail}}=1$

On entry,
${\mathbf{ldz}}=\u2329\mathit{\text{value}}\u232a$,
${\mathbf{n}}=\u2329\mathit{\text{value}}\u232a$ in
f12aaf, or
${\mathbf{ldz}}<1$ when no vectors required.
Constraint:
${\mathbf{ldz}}\ge \mathrm{max}\phantom{\rule{0.125em}{0ex}}\left(1,{\mathbf{n}}\right)$ (see
n in
f12aaf).
 ${\mathbf{ifail}}=2$

On entry, ${\mathbf{Vectors}}=\mathrm{SELECT}$, but this is not yet implemented.
 ${\mathbf{ifail}}=3$

The number of eigenvalues found to sufficient accuracy, as communicated through the argument
icomm, is zero. You should experiment with different values of
nev and
ncv, or select a different computational mode or increase the maximum number of iterations prior to calling
f12abf.
 ${\mathbf{ifail}}=4$

Got a different count of the number of converged Ritz values than the value passed to it through the argument
icomm: number counted
$=\u2329\mathit{\text{value}}\u232a$, number expected
$=\u2329\mathit{\text{value}}\u232a$. This usually indicates that a communication array has been altered or has become corrupted between calls to
f12abf and
f12acf.
 ${\mathbf{ifail}}=5$

During calculation of a real Schur form, there was a failure to compute $\u2329\mathit{\text{value}}\u232a$ eigenvalues in a total of $\u2329\mathit{\text{value}}\u232a$ iterations.
 ${\mathbf{ifail}}=6$

The computed Schur form could not be reordered by an internal call. This routine returned with
${\mathbf{ifail}}=\u2329\mathit{\text{value}}\u232a$. Please contact
NAG.
 ${\mathbf{ifail}}=7$

In calculating eigenvectors, an internal call returned with an error. Please contact
NAG.
 ${\mathbf{ifail}}=8$

Either the solver routine has not been called prior to the call of this routine or a communication array has become corrupted.
 ${\mathbf{ifail}}=99$
An unexpected error has been triggered by this routine. Please
contact
NAG.
See
Section 7 in the Introduction to the NAG Library FL Interface for further information.
 ${\mathbf{ifail}}=399$
Your licence key may have expired or may not have been installed correctly.
See
Section 8 in the Introduction to the NAG Library FL Interface for further information.
 ${\mathbf{ifail}}=999$
Dynamic memory allocation failed.
See
Section 9 in the Introduction to the NAG Library FL Interface for further information.
7
Accuracy
The relative accuracy of a Ritz value,
$\lambda $, is considered acceptable if its Ritz estimate
$\le {\mathbf{Tolerance}}\times \left\lambda \right$. The default
Tolerance used is the
machine precision given by
x02ajf.
8
Parallelism and Performance
f12acf 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 routine. Please also consult the
Users' Note for your implementation for any additional implementationspecific information.
None.
10
Example
This example solves $Ax=\lambda Bx$ in regularinvert mode, where $A$ and $B$ are obtained from the standard central difference discretization of the onedimensional convectiondiffusion operator $\frac{{d}^{2}u}{d{x}^{2}}+\rho \frac{du}{dx}$
on $\left[0,1\right]$, with zero Dirichlet boundary conditions.
10.1
Program Text
10.2
Program Data
10.3
Program Results