nag_sum_fft_realherm_1d (c06pac) (PDF version)
c06 Chapter Contents
c06 Chapter Introduction
NAG Library Manual

NAG Library Function Document

nag_sum_fft_realherm_1d (c06pac)

 Contents

    1  Purpose
    7  Accuracy

1  Purpose

nag_sum_fft_realherm_1d (c06pac) calculates the discrete Fourier transform of a sequence of n real data values or of a Hermitian sequence of n complex data values stored in compact form in a double array.

2  Specification

#include <nag.h>
#include <nagc06.h>
void  nag_sum_fft_realherm_1d (Nag_TransformDirection direct, double x[], Integer n, NagError *fail)

3  Description

Given a sequence of n real data values xj , for j=0,1,,n-1, nag_sum_fft_realherm_1d (c06pac) calculates their discrete Fourier transform (in the forward direction) defined by
z^k = 1n j=0 n-1 xj × exp -i 2πjk n ,   k= 0, 1, , n-1 .  
The transformed values z^k  are complex, but they form a Hermitian sequence (i.e., z^ n-k  is the complex conjugate of z^k ), so they are completely determined by n real numbers (since z^0  is real, as is z^ n/2  for n even).
Alternatively, given a Hermitian sequence of n complex data values zj , this function calculates their inverse (backward) discrete Fourier transform defined by
x^k = 1n j=0 n-1 zj × exp i 2πjk n ,   k= 0, 1, , n-1 .  
The transformed values x^k  are real.
(Note the scale factor of 1n  in the above definitions.)
A call of nag_sum_fft_realherm_1d (c06pac) with direct=Nag_ForwardTransform followed by a call with direct=Nag_BackwardTransform will restore the original data.
nag_sum_fft_realherm_1d (c06pac) 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).
The same functionality is available using the forward and backward transform function pair: nag_sum_fft_real_2d (c06pvc) and nag_sum_fft_hermitian_2d (c06pwc) on setting n=1. This pair use a different storage solution; real data is stored in a double array, while Hermitian data (the first unconjugated half) is stored in a Complex array.

4  References

Brigham E O (1974) The Fast Fourier Transform Prentice–Hall
Temperton C (1983) Self-sorting mixed-radix fast Fourier transforms J. Comput. Phys. 52 1–23

5  Arguments

1:     direct Nag_TransformDirectionInput
On entry: if the forward transform as defined in Section 3 is to be computed, then direct must be set equal to Nag_ForwardTransform.
If the backward transform is to be computed then direct must be set equal to Nag_BackwardTransform.
Constraint: direct=Nag_ForwardTransform or Nag_BackwardTransform.
2:     x[ n+2 ] doubleInput/Output
On entry:
  • if direct=Nag_ForwardTransform, x[j] must contain xj, for j=0,1,,n-1;
  • if direct=Nag_BackwardTransform, x[2×k] and x[2×k+1] must contain the real and imaginary parts respectively of zk, for k=0,1,,n/2. (Note that for the sequence zk to be Hermitian, the imaginary part of z0, and of zn/2  for n even, must be zero.)
On exit:
  • if direct=Nag_ForwardTransform, x[2×k] and x[2×k+1] will contain the real and imaginary parts respectively of z^k, for k=0,1,,n/2;
  • if direct=Nag_BackwardTransform, x[j] will contain x^j, for j=0,1,,n-1.
3:     n IntegerInput
On entry: n, the number of data values.
Constraint: n1.
4:     fail NagError *Input/Output
The NAG error argument (see Section 2.7 in How to Use the NAG Library and its Documentation).

6  Error Indicators and Warnings

NE_ALLOC_FAIL
Dynamic memory allocation failed.
See Section 2.3.1.2 in How to Use the NAG Library and its Documentation for further information.
NE_BAD_PARAM
On entry, argument value had an illegal value.
value is an invalid value of direct.
NE_INT
On entry, n=value.
Constraint: n1.
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.
An unexpected error has been triggered by this function. Please contact NAG.
See Section 2.7.6 in How to Use the NAG Library and its Documentation for further information.
NE_NO_LICENCE
Your licence key may have expired or may not have been installed correctly.
See Section 2.7.5 in How to Use the NAG Library and its Documentation 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

nag_sum_fft_realherm_1d (c06pac) is threaded by NAG for parallel execution in multithreaded implementations of the NAG Library.
nag_sum_fft_realherm_1d (c06pac) 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

The time taken is approximately proportional to n × logn, but also depends on the factorization of n. nag_sum_fft_realherm_1d (c06pac) is faster if the only prime factors of n are 2, 3 or 5; and fastest of all if n is a power of 2. This function internally allocates a workspace of 3n+100 double values.

10  Example

This example reads in a sequence of real data values and prints their discrete Fourier transform (as computed by nag_sum_fft_realherm_1d (c06pac) with direct=Nag_ForwardTransform), after expanding it from complex Hermitian form into a full complex sequence. It then performs an inverse transform using nag_sum_fft_realherm_1d (c06pac) with direct=Nag_BackwardTransform, and prints the sequence so obtained alongside the original data values.

10.1  Program Text

Program Text (c06pace.c)

10.2  Program Data

Program Data (c06pace.d)

10.3  Program Results

Program Results (c06pace.r)


nag_sum_fft_realherm_1d (c06pac) (PDF version)
c06 Chapter Contents
c06 Chapter Introduction
NAG Library Manual

© The Numerical Algorithms Group Ltd, Oxford, UK. 2016