PDF version (NAG web site
, 64-bit version, 64-bit version)
NAG Toolbox: nag_sum_withdraw_fft_real_1d_multi_rfmt (c06fp)
Purpose
nag_sum_fft_real_1d_multi_rfmt (c06fp) computes the discrete Fourier transforms of sequences, each containing real data values. This function is designed to be particularly efficient on vector processors.
Syntax
Description
Given
sequences of
real data values
, for
and
,
nag_sum_fft_real_1d_multi_rfmt (c06fp) simultaneously calculates the Fourier transforms of all the sequences defined by
(Note the scale factor
in this definition.)
The transformed values
are complex, but for each value of
the
form a Hermitian sequence (i.e.,
is the complex conjugate of
), so they are completely determined by
real numbers (see also the
C06 Chapter Introduction).
The discrete Fourier transform is sometimes defined using a positive sign in the exponential term:
To compute this form, this function should be followed by forming the complex conjugates of the
; that is
, for
.
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
,
,
,
and
. This function is designed to be particularly efficient on vector processors, and it becomes especially fast as
, the number of transforms to be computed in parallel, increases.
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
Parameters
Compulsory Input Parameters
- 1:
– int64int32nag_int scalar
-
, the number of sequences to be transformed.
Constraint:
.
- 2:
– int64int32nag_int scalar
-
, the number of real values in each sequence.
Constraint:
.
- 3:
– double array
-
The data must be stored in
x as if in a two-dimensional array of dimension
; each of the
sequences is stored in a
row of the array. In other words, if the data values of the
th sequence to be transformed are denoted by
, for
, then the
elements of the array
x must contain the values
- 4:
– string (length ≥ 1)
-
Indicates whether trigonometric coefficients are to be calculated.
- Calculate the required trigonometric coefficients for the given value of , and store in the array trig.
- or
- The required trigonometric coefficients are assumed to have been calculated and stored in the array trig in a prior call to one of nag_sum_fft_real_1d_multi_rfmt (c06fp), nag_sum_fft_hermitian_1d_multi_rfmt (c06fq) or nag_sum_fft_complex_1d_multi_rfmt (c06fr). The function performs a simple check that the current value of is consistent with the values stored in trig.
Constraint:
, or .
- 5:
– double array
-
If
or
,
trig must contain the required trigonometric coefficients that have been previously calculated. Otherwise
trig need not be set.
Optional Input Parameters
None.
Output Parameters
- 1:
– double array
-
The
discrete Fourier transforms stored as if in a two-dimensional array of dimension
. Each of the
transforms is stored in a
row of the array in Hermitian form, overwriting the corresponding original sequence. If the
components of the discrete Fourier transform
are written as
, then for
,
is contained in
, and for
,
is contained in
. (See also
Real transforms in the C06 Chapter Introduction.)
- 2:
– double array
-
Contains the required coefficients (computed by the function if ).
- 3:
– int64int32nag_int scalar
unless the function detects an error (see
Error Indicators and Warnings).
Error Indicators and Warnings
Errors or warnings detected by the function:
-
-
-
-
-
-
On entry, | , or . |
-
-
Not used at this Mark.
-
-
On entry, | or , but the array trig and the current value of n are inconsistent. |
-
-
An unexpected error has occurred in an internal call. Check all function calls and array dimensions. Seek expert help.
-
An unexpected error has been triggered by this routine. Please
contact
NAG.
-
Your licence key may have expired or may not have been installed correctly.
-
Dynamic memory allocation failed.
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).
Further Comments
The time taken by nag_sum_fft_real_1d_multi_rfmt (c06fp) is approximately proportional to , but also depends on the factors of . nag_sum_fft_real_1d_multi_rfmt (c06fp) is fastest if the only prime factors of are , and , and is particularly slow if is a large prime, or has large prime factors.
Example
This example reads in sequences of real data values and prints their discrete Fourier transforms (as computed by
nag_sum_fft_real_1d_multi_rfmt (c06fp)). The Fourier transforms are expanded into full complex form using and printed. Inverse transforms are then calculated by conjugating and calling
nag_sum_fft_hermitian_1d_multi_rfmt (c06fq) showing that the original sequences are restored.
Open in the MATLAB editor:
c06fp_example
function c06fp_example
fprintf('c06fp example results\n\n');
m = int64(3);
n = int64(6);
x = [0.3854 0.6772 0.1138 0.6751 0.6362 0.1424;
0.5417 0.2983 0.1181 0.7255 0.8638 0.8723;
0.9172 0.0644 0.6037 0.6430 0.0428 0.4815];
init = 'Initial';
trig = zeros(2*n,1);
[xt, trig, ifail] = c06fp(m, n, x, init, trig);
disp('Discrete Fourier transforms in Hermitian format:');
disp(xt);
for j = 1:m
zt(j,:) = nag_herm2complex(xt(j,:));
end
title = 'Discrete Fourier transforms in full complex format:';
[ifail] = x04da('General','Non-unit', zt, title);
init = 'Subsequent';
nd = double(n);
xt(1:m,floor(nd/2)+2:n) = -xt(1:m,floor(nd/2)+2:n);
[xr, trig, ifail] = c06fq(m, n, xt, init, trig);
fprintf('\n');
disp('Original data as restored by inverse transform:');
disp(xr);
function [z] = nag_herm2complex(x);
n = size(x,2);
z(1) = complex(x(1));
for j = 2:floor((n-1)/2) + 1
z(j) = x(j) + i*x(n-j+2);
z(n-j+2) = x(j) - i*x(n-j+2);
end
if (mod(n,2)==0)
z(n/2+1) = complex(x(n/2+1));
end
c06fp example results
Discrete Fourier transforms in Hermitian format:
1.0737 -0.1041 0.1126 -0.1467 -0.3738 -0.0044
1.3961 -0.0365 0.0780 -0.1521 -0.0607 0.4666
1.1237 0.0914 0.3936 0.1530 0.3458 -0.0508
Discrete Fourier transforms in full complex format:
1 2 3 4 5 6
1 1.0737 -0.1041 0.1126 -0.1467 0.1126 -0.1041
0.0000 -0.0044 -0.3738 0.0000 0.3738 0.0044
2 1.3961 -0.0365 0.0780 -0.1521 0.0780 -0.0365
0.0000 0.4666 -0.0607 0.0000 0.0607 -0.4666
3 1.1237 0.0914 0.3936 0.1530 0.3936 0.0914
0.0000 -0.0508 0.3458 0.0000 -0.3458 0.0508
Original data as restored by inverse transform:
0.3854 0.6772 0.1138 0.6751 0.6362 0.1424
0.5417 0.2983 0.1181 0.7255 0.8638 0.8723
0.9172 0.0644 0.6037 0.6430 0.0428 0.4815
PDF version (NAG web site
, 64-bit version, 64-bit version)
© The Numerical Algorithms Group Ltd, Oxford, UK. 2009–2015