NAG Library Manual, Mark 30

Interfaces: FL CL CPP AD PY MB

NAG CL Interface Introduction

F01 (Matop) Chapter Contents

F01 (Matop) Chapter Introduction

f01fm: FL CL CPP AD PY MB

NAG CL Interface
f01fmc (complex_gen_matrix_fun_usd)

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NAG Library Manual, Mark 30

Interfaces: FL CL CPP AD PY MB

NAG CL Interface Introduction

F01 (Matop) Chapter Contents

F01 (Matop) Chapter Introduction

f01fm: FL CL CPP AD PY MB

▸▿ Contents

2 Specification

3 Description

4 References

5 Arguments

6 Error Indicators and Warnings

8 Parallelism and Performance

9 Further Comments

▸▿ 10 Example

10.1 Program Text

10.2 Program Data

10.3 Program Results

© The Numerical Algorithms Group Ltd. 2024

CL Name Style:
Short (a00aac)
Long (impl_details)
Full (nag_info_impl_details)

1 Purpose

f01fmc computes the matrix function,

f (A)

, of a complex

n \times n

matrix

A

, using analytical derivatives of

f

you have supplied.

2 Specification

#include <nag.h>

void

f01fmc (Nag_OrderType order, Integer n, Complex a[], Integer pda,

void	(f)(Integer m, Integer iflag, Integer nz, const Complex z[], Complex fz[], Nag_Comm *comm),

Nag_Comm *comm, Integer *iflag, NagError *fail)

The function may be called by the names: f01fmc or nag_matop_complex_gen_matrix_fun_usd.

3 Description

f (A)

is computed using the Schur–Parlett algorithm described in Higham (2008) and Davies and Higham (2003).

The scalar function

f

, and the derivatives of

f

, are returned by the function f which, given an integer

m

, should evaluate

f^{(m)} (z_{i})

at a number of points

z_{i}

, for

i = 1, 2, \dots, n_{z}

, on the complex plane. f01fmc is, therefore, appropriate for functions that can be evaluated on the complex plane and whose derivatives, of arbitrary order, can also be evaluated on the complex plane.

4 References

Davies P I and Higham N J (2003) A Schur–Parlett algorithm for computing matrix functions SIAM J. Matrix Anal. Appl. 25(2) 464–485

Higham N J (2008) Functions of Matrices: Theory and Computation SIAM, Philadelphia, PA, USA

5 Arguments

1: $order$ – 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

order = 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:

order = Nag_RowMajor

or

Nag_ColMajor

.

2: $n$ – Integer Input

On entry:

n

, the order of the matrix

A

.

Constraint:

n \geq 0

.

3: $a [\dim]$ – Complex Input/Output

Note: the dimension, dim, of the array a must be at least

pda \times n

.

The

(i, j)

th element of the matrix

A

is stored in

$a [(j - 1) \times pda + i - 1]$ when $order = Nag_ColMajor$ ;
$a [(i - 1) \times pda + j - 1]$ when $order = Nag_RowMajor$ .

On entry: the

n \times n

matrix

A

.

On exit: the

n \times n

matrix,

f (A)

.

4: $pda$ – Integer Input

On entry: the stride separating row or column elements (depending on the value of order) in the array a.

Constraint:

pda \geq n

.

5: $f$ – function, supplied by the user External Function

Given an integer

m

, the function f evaluates

f^{(m)} (z_{i})

at a number of points

z_{i}

.

The specification of f is:

void	f (Integer m, Integer iflag, Integer nz, const Complex z[], Complex fz[], Nag_Comm comm)

1: $m$ – Integer Input

On entry: the order,

m

, of the derivative required.

If

m = 0

,

f (z_{i})

should be returned. For

m > 0

,

f^{(m)} (z_{i})

should be returned.

2: $iflag$ – Integer * Input/Output

On entry: iflag will be zero.

On exit: iflag should either be unchanged from its entry value of zero, or may be set nonzero to indicate that there is a problem in evaluating the function

f (z)

; for instance

f (z_{i})

may not be defined for a particular

z_{i}

. If iflag is returned as nonzero then f01fmc will terminate the computation, with

fail . code =

NE_INT, NE_INT_2 or NE_USER_STOP.

3: $nz$ – Integer Input

On entry:

n_{z}

, the number of function or derivative values required.

4: $z [\dim]$ – const Complex Input

On entry: the

n_{z}

points

z_{1}, z_{2}, \dots, z_{n_{z}}

at which the function

f

is to be evaluated.

5: $fz [\dim]$ – Complex Output

On exit: the

n_{z}

function or derivative values.

fz [i - 1]

should return the value

f^{(m)} (z_{i})

, for

i = 1, 2, \dots, n_{z}

.

6: $comm$ – Nag_Comm *

Pointer to structure of type Nag_Comm; the following members are relevant to f.

user – double *
iuser – Integer *
p – Pointer: The type Pointer will be void *. Before calling f01fmc you may allocate memory and initialize these pointers with various quantities for use by f when called from f01fmc (see Section 3.1.1 in the Introduction to the NAG Library CL Interface).

Note: f should not return floating-point NaN (Not a Number) or infinity values, since these are not handled by f01fmc. If your code inadvertently does return any NaNs or infinities, f01fmc is likely to produce unexpected results.

6: $comm$ – Nag_Comm *

The NAG communication argument (see Section 3.1.1 in the Introduction to the NAG Library CL Interface).

7: $iflag$ – Integer * Output

On exit:

iflag = 0

, unless iflag has been set nonzero inside f, in which case iflag will be the value set and fail will be set to

fail . code =

NE_INT, NE_INT_2 or NE_USER_STOP.

8: $fail$ – NagError * Input/Output

The NAG error argument (see Section 7 in the Introduction to the NAG Library CL Interface).

6 Error 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.
NE_BAD_PARAM: On entry, argument $⟨ value ⟩$ had an illegal value.
NE_CONVERGENCE: A Taylor series failed to converge.
NE_INT: On entry, $n = ⟨ value ⟩$ .
Constraint: $n \geq 0$ .
NE_INT_2: On entry, $pda = ⟨ value ⟩$ and $n = ⟨ value ⟩$ .
Constraint: $pda \geq n$ .
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.

An unexpected internal error occurred when ordering the eigenvalues of $A$ . Please contact NAG.

The function was unable to compute the Schur decomposition of $A$ .
Note: this failure should not occur and suggests that the function has been called incorrectly.

There was an error whilst reordering the Schur form of $A$ .
Note: this failure should not occur and suggests that the function has been called incorrectly.
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_USER_STOP: Termination requested in f.

7 Accuracy

For a normal matrix

A

(for which

A^{H} A = A A^{H}

), the Schur decomposition is diagonal and the algorithm reduces to evaluating

f

at the eigenvalues of

A

and then constructing

f (A)

using the Schur vectors. This should give a very accurate result. In general, however, no error bounds are available for the algorithm. See Section 9.4 of Higham (2008) for further discussion of the Schur–Parlett algorithm.

8 Parallelism and Performance

Background information to multithreading can be found in the Multithreading documentation.

f01fmc is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library. In these implementations, this function may make calls to the user-supplied functions from within an OpenMP parallel region. Thus OpenMP pragmas within the user functions can only be used if you are compiling the user-supplied function and linking the executable in accordance with the instructions in the Users' Note for your implementation. You must also ensure that you use the NAG communication argument comm in a thread safe manner, which is best achieved by only using it to supply read-only data to the user functions.

f01fmc 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.

9 Further Comments

Up to

6 n^{2}

of Complex allocatable memory is required.

The cost of the Schur–Parlett algorithm depends on the spectrum of

A

, but is roughly between

28 n^{3}

and

n^{4} / 3

floating-point operations. There is an additional cost in evaluating

f

and its derivatives. If the derivatives of

f

are not known analytically, then f01flc can be used to evaluate

f (A)

using numerical differentiation. If

A

is complex Hermitian then it is recommended that f01ffc be used as it is more efficient and, in general, more accurate than f01fmc.

Note that

f

must be analytic in the region of the complex plane containing the spectrum of

A

.

For further information on matrix functions, see Higham (2008).

If estimates of the condition number of the matrix function are required then f01kcc should be used.

f01emc can be used to find the matrix function

f (A)

for a real matrix

A

.

10 Example

This example finds the

e^{3 A}

where

A = (\begin{array}{r} 1.0 + 0.0 i & 0.0 + 0.0 i & 1.0 + 0.0 i & 0.0 + 2.0 i \\ 0.0 + 1.0 i & 1.0 + 0.0 i & - 1.0 + 0.0 i & 1.0 + 0.0 i \\ - 1.0 + 0.0 i & 0.0 + 1.0 i & 0.0 + 1.0 i & 0.0 + 1.0 i \\ 1.0 + 1.0 i & 0.0 + 2.0 i & - 1.0 + 0.0 i & 0.0 + 1.0 i \end{array}) .

10.1 Program Text

Program Text (f01fmce.c)

10.2 Program Data

Program Data (f01fmce.d)

10.3 Program Results

Program Results (f01fmce.r)

NAG Library Manual, Mark 30

Interfaces: FL CL CPP AD PY MB

NAG CL Interface Introduction

F01 (Matop) Chapter Contents

F01 (Matop) Chapter Introduction

f01fm: FL CL CPP AD PY MB

© The Numerical Algorithms Group Ltd. 2024