Interfaces: FL CL AD

c06pq: FL CL AD

NAG CL Interface
c06pqc (fft_realherm_1d_multi_col)

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NAG Library Manual, Mark 27

Interfaces: FL CL AD

NAG CL Interface Introduction

C06 (Sum) Chapter Contents

C06 (Sum) Chapter Introduction

c06pq: FL CL 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

c06pqc computes the discrete Fourier transforms of

m

sequences, each containing

n

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

2 Specification

#include <nag.h>

void	c06pqc (Nag_TransformDirection direct, Integer n, Integer m, double x[], NagError *fail)

The function may be called by the names: c06pqc or nag_sum_fft_realherm_1d_multi_col.

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

, c06pqc 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 function 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 c06pqc with

direct = Nag_ForwardTransform

followed by a call with

direct = Nag_BackwardTransform

will restore the original data.

The function 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: $direct$ – Nag_TransformDirection Input

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

Nag_ForwardTransform

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

Nag_BackwardTransform

Constraint:

direct = Nag_ForwardTransform

Nag_BackwardTransform

2: $n$ – Integer Input

On entry:

n

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

Constraint:

n \geq 1

3: $m$ – Integer Input

On entry:

m

, the number of sequences to be transformed.

Constraint:

m \geq 1

4: $x [(n + 2) \times m]$ – double Input/Output

On entry: the

m

real or Hermitian data sequences to be transformed.

if $direct = Nag_ForwardTransform$ , the $m$ real data sequences, $x^{p} = (x_{1}^{p}, x_{2}^{p}, \dots, x_{n}^{p})$ , for $p = 1, 2, \dots, m$ , should be stored sequentially in x, with a stride of $n + 2$ between sequences.
if $direct = Nag_BackwardTransform$ , the $m$ Hermitian data sequences, ${\hat{z}}^{p} = ({\hat{z}}_{1}^{p}, {\hat{z}}_{2}^{p}, \dots, {\hat{z}}_{n / 2 + 1}^{p}) = ({\hat{z}}_{1}^{p} . re, {\hat{z}}_{1}^{p} . im, {\hat{z}}_{2}^{p} . re, {\hat{z}}_{2}^{p} . im, \dots, {\hat{z}}_{n / 2 + 1}^{p} . re, {\hat{z}}_{n / 2 + 1}^{p} . im)$ , for $p = 1, 2, \dots, m$ , should be stored sequentially in x, with a stride of $n + 2$ between sequences.

In other words:

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

On exit:

if $direct = Nag_ForwardTransform$ then the $m$ sequences, ${\hat{z}}^{p}$ , for $p = 1, 2, \dots, m$ stored as described on entry for $direct = Nag_BackwardTransform$
if $direct = Nag_BackwardTransform$ then the $m$ sequences, $x^{p}$ , for $p = 1, 2, \dots, m$ stored as described on entry for $direct = Nag_ForwardTransform$

5: $fail$ – 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_INT: On entry, $m = 〈value〉$ .
Constraint: $m \geq 1$ .

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

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

c06pqc is not threaded in any implementation.

9 Further Comments

The time taken by c06pqc is approximately proportional to

n m \log (n)

, but also depends on the factors of

n

. c06pqc 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 c06pqc with

direct = Nag_ForwardTransform

), after expanding them from complex Hermitian form into full complex sequences.

Inverse transforms are then calculated by calling c06pqc with

direct = Nag_BackwardTransform

showing that the original sequences are restored.

Interfaces: FL CL AD

NAG CL Interface Introduction

C06 (Sum) Chapter Contents

C06 (Sum) Chapter Introduction

c06pq: FL CL AD

NAG CL Interfacec06pqc (fft_​realherm_​1d_​multi_​col)

▸▿ 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 CL Interface
c06pqc (fft_realherm_1d_multi_col)