f12ac: FL CL CPP AD

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.

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NAG Library Manual, Mark 27

Interfaces: FL CL CPP AD

NAG FL Interface Introduction

F12 (Sparseig) Chapter Contents

F12 (Sparseig) Chapter Introduction

f12ac: FL CL CPP AD

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

▸▿ 10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

1 Purpose

f12acf is a post-processing 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)

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,

λ

, (and optionally the corresponding eigenvectors,

x

) of a standard eigenvalue problem

A x = λ x

, or of a generalized eigenvalue problem

A x = λ B x

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 post-processing 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 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

5 Arguments

1: $nconv$ – Integer Output

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

2: $dr (*)$ – Real (Kind=nag_wp) array Output

Note: the dimension of the array dr must be at least

nev + 1

(see f12aaf).

On exit: the first nconv locations of the array dr contain the real parts of the converged approximate eigenvalues.

3: $di (*)$ – Real (Kind=nag_wp) array Output

Note: the dimension of the array di must be at least

nev + 1

(see f12aaf).

On exit: the first nconv locations of the array di contain the imaginary parts of the converged approximate eigenvalues.

4: $z (ldz *)$ – Real (Kind=nag_wp) array Output

Note: the second dimension of the array z must be at least

nev + 1

if the default option

Vectors = RITZ

has been selected and at least

1

if the option

Vectors = NONE

SCHUR

has been selected (see f12aaf).

On exit: if the default option

Vectors = 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: $ldz$ – 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 $Vectors = Ritz$ has been selected, $ldz \geq n$ ;
if the option $Vectors = None or Schur$ has been selected, $ldz \geq 1$ .

6: $sigmar$ – 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: $sigmai$ – 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: $resid (*)$ – Real (Kind=nag_wp) array Input

Note: the dimension of the array resid must be at least

n

(see f12aaf).

On entry: must not be modified following a call to f12abf since it contains data required by f12acf.

9: $v (ldv *)$ – Real (Kind=nag_wp) array Input/Output

Note: the second dimension of the array v must be at least

\max (1, ncv)

(see f12aaf).

On entry: the ncv columns of v contain the Arnoldi basis vectors for

OP

as constructed by f12abf.

On exit: if the option

Vectors = SCHUR

has been set, or the option

Vectors = 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: $ldv$ – Integer Input

On entry: the first dimension of the array v as declared in the (sub)program from which f12acf is called.

Constraint:

ldv \geq n

11: $comm (*)$ – 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: $icomm (*)$ – 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: $ifail$ – Integer Input/Output

On entry: ifail must be set to

0

- 1

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

1

is recommended. If message printing is undesirable, then the value

1

is recommended. Otherwise, the value

0

is recommended. When the value $- 1$ or $1$ is used it is essential to test the value of ifail on exit.

On exit:

ifail = 0

unless the routine detects an error or a warning has been flagged (see Section 6).

6 Error Indicators and Warnings

If on entry

ifail = 0

- 1

, explanatory error messages are output on the current error message unit (as defined by x04aaf).

Errors or warnings detected by the routine:

$ifail = 1$: On entry, $ldz = 〈value〉$ , $n = 〈value〉$ in f12aaf, or $ldz < 1$ when no vectors required.
Constraint: $ldz \geq \max (1, n)$ (see n in f12aaf).

$ifail = 2$: On entry, $Vectors = SELECT$ , but this is not yet implemented.

$ifail = 3$: 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.

$ifail = 4$: Got a different count of the number of converged Ritz values than the value passed to it through the argument icomm: number counted $= 〈value〉$ , number expected $= 〈value〉$ . This usually indicates that a communication array has been altered or has become corrupted between calls to f12abf and f12acf.

$ifail = 5$: During calculation of a real Schur form, there was a failure to compute $〈value〉$ eigenvalues in a total of $〈value〉$ iterations.

$ifail = 6$: The computed Schur form could not be reordered by an internal call. This routine returned with $ifail = 〈value〉$ . Please contact NAG.

$ifail = 7$: In calculating eigenvectors, an internal call returned with an error. Please contact NAG.

$ifail = 8$: Either the solver routine has not been called prior to the call of this routine or a communication array has become corrupted.

$ifail = - 99$: 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.

$ifail = - 399$: 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.

$ifail = - 999$: 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,

λ

, is considered acceptable if its Ritz estimate

\leq Tolerance \times |λ|

. 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 implementation-specific information.

9 Further Comments

None.

10 Example

This example solves

A x = λ B x

in regular-invert mode, where

A

and

B

are obtained from the standard central difference discretization of the one-dimensional convection-diffusion operator

\frac{d^{2} u}{d x^{2}} + ρ \frac{d u}{d x}

[0, 1]

, with zero Dirichlet boundary conditions.

f12ac: FL CL CPP AD

NAG FL Interfacef12acf (real_​proc)

▸▿ Contents

1 Purpose

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

7 Accuracy

8 Parallelism and Performance

9 Further Comments

10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

NAG FL Interface
f12acf (real_proc)