c06pp: FL CL CPP AD

NAG FL Interface
c06ppf (fft_realherm_1d_multi_row)

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NAG Library Manual, Mark 27

Interfaces: FL CL CPP AD

NAG FL Interface Introduction

C06 (Sum) Chapter Contents

C06 (Sum) Chapter Introduction

c06pp: 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

c06ppf computes the discrete Fourier transforms of

m

sequences, each containing

n

real data values or a Hermitian complex sequence stored in a complex storage format.

2 Specification

Fortran Interface

Subroutine c06ppf (

direct, m, n, x, work, ifail)

Integer, Intent (In)	::	m, n
Integer, Intent (Inout)	::	ifail
Real (Kind=nag_wp), Intent (Inout)	::	x(m(n+2)), work()
Character (1), Intent (In)	::	direct

C Header Interface

#include <nag.h>

void	c06ppf_ (const char direct, const Integer m, const Integer n, double x[], double work[], Integer ifail, const Charlen length_direct)

The routine may be called by the names c06ppf or nagf_sum_fft_realherm_1d_multi_row.

3 Description

Given

m

sequences of

n

real data values

x_{j}^{p}

, for

j = 0, 1, \dots, n - 1

and

p = 1, 2, \dots, m

, c06ppf simultaneously calculates the Fourier transforms of all the sequences defined by

{\hat{z}}_{k}^{p} = \frac{1}{\sqrt{n}} \sum_{j = 0}^{n - 1} x_{j}^{p} \times \exp (- i \frac{2 π j k}{n}), k = 0, 1, \dots, n - 1 ​ and ​ p = 1, 2, \dots, m .

The transformed values

{\hat{z}}_{k}^{p}

are complex, but for each value of

p

the

{\hat{z}}_{k}^{p}

form a Hermitian sequence (i.e.,

{\hat{z}}_{n - k}^{p}

is the complex conjugate of

{\hat{z}}_{k}^{p}

), so they are completely determined by

m n

real numbers (since

{\hat{z}}_{0}^{p}

is real, as is

{\hat{z}}_{n / 2}^{p}

for

n

even).

Alternatively, given

m

Hermitian sequences of

n

complex data values

z_{j}^{p}

, this routine simultaneously calculates their inverse (backward) discrete Fourier transforms defined by

{\hat{x}}_{k}^{p} = \frac{1}{\sqrt{n}} \sum_{j = 0}^{n - 1} z_{j}^{p} \times \exp (i \frac{2 π j k}{n}), k = 0, 1, \dots, n - 1 ​ and ​ p = 1, 2, \dots, m .

The transformed values

{\hat{x}}_{k}^{p}

are real.

(Note the scale factor

\frac{1}{\sqrt{n}}

in the above definition.)

A call of c06ppf with

direct ='F'

followed by a call with

direct ='B'

will restore the original data.

The routine uses a variant of the fast Fourier transform (FFT) algorithm (see Brigham (1974)) known as the Stockham self-sorting algorithm, which is described in Temperton (1983). Special coding is provided for the factors

2

3

4

and

5

4 References

Brigham E O (1974) The Fast Fourier Transform Prentice–Hall

Temperton C (1983) Fast mixed-radix real Fourier transforms J. Comput. Phys. 52 340–350

5 Arguments

1: $direct$ – Character(1) Input

On entry: if the forward transform as defined in Section 3 is to be computed, direct must be set equal to 'F'.

If the backward transform is to be computed, direct must be set equal to 'B'.

Constraint:

direct ='F'

'B'

2: $m$ – Integer Input

On entry:

m

, the number of sequences to be transformed.

Constraint:

m \geq 1

3: $n$ – Integer Input

On entry:

n

, the number of real or complex values in each sequence.

Constraint:

n \geq 1

4: $x (m \times (n + 2))$ – Real (Kind=nag_wp) array Input/Output

On entry: the data must be stored such that consecutive elements of the same sequence are stored with a stride of m and corresponding elements of different sequences are stored consecutively. An additional two spaces are reserved for each sequence to allow for the pairwise storage of real and imaginary parts in the transformed domain. In other words, if the data values of the

p

th sequence to be transformed are denoted by

x_{j}^{p}

, for

j = 0, 1, \dots, n - 1

if $direct ='F'$ , $x (j \times m + p)$ must contain $x_{j}^{p}$ , for $j = 0, 1, \dots, n - 1$ and $p = 1, 2, \dots, m$ ;
if $direct ='B'$ , $x (2 \times k \times m + p)$ and $x ((2 \times k + 1) \times m + p)$ must contain the real and imaginary parts respectively of ${\hat{z}}_{k}^{p}$ , for $k = 0, 1, \dots, n / 2$ and $p = 1, 2, \dots, m$ . (Note that for the sequence ${\hat{z}}_{k}^{p}$ to be Hermitian, the imaginary part of ${\hat{z}}_{0}^{p}$ , and of ${\hat{z}}_{n / 2}^{p}$ for $n$ even, must be zero.)

On exit:

if $direct ='F'$ then $x (2 \times k \times m + p)$ and $x ((2 \times k + 1) \times m + p)$ will contain the real and imaginary parts respectively of ${\hat{z}}_{k}^{p}$ , for $k = 0, 1, \dots, n / 2$ and $p = 1, 2, \dots, m$ ;
if $direct ='B'$ then $x (j \times m + p)$ will contain $x_{j}^{p}$ , for $j = 0, 1, \dots, n - 1$ and $p = 1, 2, \dots, m$ ;

5: $work (*)$ – Real (Kind=nag_wp) array Workspace

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

m \times n + 2 \times n + 2 \times m + 15

The workspace requirements as documented for c06ppf may be an overestimate in some implementations.

On exit:

work (1)

contains the minimum workspace required for the current values of m and n with this implementation.

6: $ifail$ – 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, $m = 〈value〉$ .
Constraint: $m \geq 1$ .

$ifail = 2$: On entry, $n = 〈value〉$ .
Constraint: $n \geq 1$ .

$ifail = 3$: On entry, $direct = 〈value〉$ .
Constraint: $direct ='F'$ or $'B'$ .

$ifail = 4$: An internal error has occurred in this routine. Check the routine call and any array sizes. If the call is correct then please contact NAG for assistance.

$ifail = - 99$: 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

Some indication of accuracy can be obtained by performing a subsequent inverse transform and comparing the results with the original sequence (in exact arithmetic they would be identical).

8 Parallelism and Performance

c06ppf is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.

c06ppf 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

The time taken by c06ppf is approximately proportional to

n m \log (n)

, but also depends on the factors of

n

. c06ppf is fastest if the only prime factors of

n

are

2

3

and

5

, and is particularly slow if

n

is a large prime, or has large prime factors.

10 Example

This example reads in sequences of real data values and prints their discrete Fourier transforms (as computed by c06ppf with

direct ='F'

), after expanding them from complex Hermitian form into a full complex sequences. Inverse transforms are then calculated by calling c06ppf with

direct ='B'

showing that the original sequences are restored.

c06pp: FL CL CPP AD

NAG FL Interfacec06ppf (fft_​realherm_​1d_​multi_​row)

▸▿ 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
c06ppf (fft_realherm_1d_multi_row)