PDF version (NAG web site
, 64-bit version, 64-bit version)
NAG Toolbox: nag_sum_fft_realherm_1d_multi_col (c06pq)
Purpose
nag_sum_fft_realherm_1d_multi_col (c06pq) computes the discrete Fourier transforms of sequences, each containing real data values or a Hermitian complex sequence stored column-wise in a complex storage format.
Syntax
Description
Given
sequences of
real data values
, for
and
,
nag_sum_fft_realherm_1d_multi_col (c06pq) simultaneously calculates the Fourier transforms of all the sequences defined by
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 (since is real, as is for even).
Alternatively, given
Hermitian sequences of
complex data values
, this function simultaneously calculates their inverse (
backward) discrete Fourier transforms defined by
The transformed values
are real.
(Note the scale factor in the above definition.)
A call of nag_sum_fft_realherm_1d_multi_col (c06pq) with followed by a call with 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
,
,
and
.
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:
– string (length ≥ 1)
-
If the forward transform as defined in
Description is to be computed, then
direct must be set equal to 'F'.
If the backward transform is to be computed then
direct must be set equal to 'B'.
Constraint:
or .
- 2:
– int64int32nag_int scalar
-
, the number of real or complex values in each sequence.
Constraint:
.
- 3:
– int64int32nag_int scalar
-
, the number of sequences to be transformed.
Constraint:
.
- 4:
– 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
column of the array. In other words, if the data values of the
th sequence to be transformed are denoted by
, for
, then:
- if ,
must contain , for and ;
-
if , and must contain the real and imaginary parts respectively of , for and . (Note that for the sequence to be Hermitian, the imaginary part of , and of for even, must be zero.)
Optional Input Parameters
None.
Output Parameters
- 1:
– double array
-
-
if and x is declared with bounds then and will contain the real and imaginary parts respectively of , for and ;
-
if and x is declared with bounds then will contain , for and .
- 2:
– 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 . |
-
-
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_realherm_1d_multi_col (c06pq) is approximately proportional to , but also depends on the factors of . nag_sum_fft_realherm_1d_multi_col (c06pq) 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_realherm_1d_multi_col (c06pq) with ), after expanding them from complex Hermitian form into a full complex sequences.
Inverse transforms are then calculated by calling nag_sum_fft_realherm_1d_multi_col (c06pq) with showing that the original sequences are restored.
Open in the MATLAB editor:
c06pq_example
function c06pq_example
fprintf('c06pq example results\n\n');
m = int64(3);
n = int64(6);
x = [0.3854 0.6772 0.1138 0.6751 0.6362 0.1424 0 0;
0.5417 0.2983 0.1181 0.7255 0.8638 0.8723 0 0;
0.9172 0.0644 0.6037 0.6430 0.0428 0.4815 0 0];
x = transpose(x);
disp('Original data values:');
disp(x(1:n,:));
direct = 'F';
[xt, ifail] = c06pq(direct, n, m, x);
zt = xt(1:2:n+1,:) + i*xt(2:2:n+2,:);
title = 'Discrete Fourier transforms in complex Hermitian format:';
[ifail] = x04da('General','Non-unit', zt, title);
for j = 1:m
zt(1:n,j) = nag_herm2complex(n,xt(:,j));
end
title = 'Discrete Fourier transforms in full complex format:';
disp(' ');
[ifail] = x04da('General','Non-unit', zt, title);
direct = 'B';
[xr, ifail] = c06pq(direct, n, m, xt);
disp(' ');
disp('Original data as restored by inverse transform:');
disp(xr(1:n,:));
function [z] = nag_herm2complex(n,x);
z(1) = complex(x(1));
for j = 2:floor(double(n)/2) + 1
z(j) = x(2*j-1) + i*x(2*j);
z(n-j+2) = x(2*j-1) - i*x(2*j);
end
c06pq example results
Original data values:
0.3854 0.5417 0.9172
0.6772 0.2983 0.0644
0.1138 0.1181 0.6037
0.6751 0.7255 0.6430
0.6362 0.8638 0.0428
0.1424 0.8723 0.4815
Discrete Fourier transforms in complex Hermitian format:
1 2 3
1 1.0737 1.3961 1.1237
0.0000 0.0000 0.0000
2 -0.1041 -0.0365 0.0914
-0.0044 0.4666 -0.0508
3 0.1126 0.0780 0.3936
-0.3738 -0.0607 0.3458
4 -0.1467 -0.1521 0.1530
0.0000 0.0000 0.0000
Discrete Fourier transforms in full complex format:
1 2 3
1 1.0737 1.3961 1.1237
0.0000 0.0000 0.0000
2 -0.1041 -0.0365 0.0914
-0.0044 0.4666 -0.0508
3 0.1126 0.0780 0.3936
-0.3738 -0.0607 0.3458
4 -0.1467 -0.1521 0.1530
0.0000 0.0000 0.0000
5 0.1126 0.0780 0.3936
0.3738 0.0607 -0.3458
6 -0.1041 -0.0365 0.0914
0.0044 -0.4666 0.0508
Original data as restored by inverse transform:
0.3854 0.5417 0.9172
0.6772 0.2983 0.0644
0.1138 0.1181 0.6037
0.6751 0.7255 0.6430
0.6362 0.8638 0.0428
0.1424 0.8723 0.4815
PDF version (NAG web site
, 64-bit version, 64-bit version)
© The Numerical Algorithms Group Ltd, Oxford, UK. 2009–2015