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NAG Toolbox: nag_sum_fft_complex_multid_sep (c06fj)

 Contents

    1  Purpose
    2  Syntax
    7  Accuracy
    9  Example

Purpose

nag_sum_fft_complex_multid_sep (c06fj) computes the multidimensional discrete Fourier transform of a multivariate sequence of complex data values.

Syntax

[x, y, ifail] = c06fj(nd, x, y, 'ndim', ndim, 'n', n)
[x, y, ifail] = nag_sum_fft_complex_multid_sep(nd, x, y, 'ndim', ndim, 'n', n)

Description

nag_sum_fft_complex_multid_sep (c06fj) computes the multidimensional discrete Fourier transform of a multidimensional sequence of complex data values z j1 j2 jm , where j1 = 0 , 1 ,, n1-1 ,   j2 = 0 , 1 ,, n2-1 , and so on. Thus the individual dimensions are n1 , n2 ,, nm , and the total number of data values is n = n1 × n2 ×× nm .
The discrete Fourier transform is here defined (e.g., for m=2 ) by:
z^ k1 , k2 = 1n j1=0 n1-1 j2=0 n2-1 z j1j2 × exp -2πi j1k1 n1 + j2k2 n2 ,  
where k1 = 0 , 1 ,, n1-1 , k2 = 0 , 1 ,, n2-1 .
The extension to higher dimensions is obvious. (Note the scale factor of 1n  in this definition.)
To compute the inverse discrete Fourier transform, defined with exp + 2 π i  in the above formula instead of exp - 2 π i , this function should be preceded and followed by the complex conjugation of the data values and the transform (by negating the imaginary parts stored in y).
The data values must be supplied in a pair of one-dimensional arrays (real and imaginary parts separately), in accordance with the Fortran convention for storing multidimensional data (i.e., with the first subscript j1  varying most rapidly).
This function calls nag_sum_fft_complex_1d_sep (c06fc) to perform one-dimensional discrete Fourier transforms by the fast Fourier transform (FFT) algorithm in Brigham (1974), and hence there are some restrictions on the values of the ni  (see Arguments).

References

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

Parameters

Compulsory Input Parameters

1:     ndndim int64int32nag_int array
ndi must contain ni (the dimension of the ith variable) , for i=1,2,,m. The largest prime factor of each ndi must not exceed 19, and the total number of prime factors of ndi, counting repetitions, must not exceed 20.
Constraint: ndi1, for i=1,2,,ndim.
2:     xn – double array
x 1 + j1 + n1 j2 + n1 n2 j3 +  must contain the real part of the complex data value z j1 j2 jm , for 0 j1 n1 -1 , 0 j2 n2-1 , ; i.e., the values are stored in consecutive elements of the array according to the Fortran convention for storing multidimensional arrays.
3:     yn – double array
The imaginary parts of the complex data values, stored in the same way as the real parts in the array x.

Optional Input Parameters

1:     ndim int64int32nag_int scalar
Default: the dimension of the array nd.
m, the number of dimensions (or variables) in the multivariate data.
Constraint: ndim1.
2:     n int64int32nag_int scalar
Default: the dimension of the arrays x, y. (An error is raised if these dimensions are not equal.)
n, the total number of data values.
Constraint: n = nd1 × nd2 ×× ndndim.

Output Parameters

1:     xn – double array
The real parts of the corresponding elements of the computed transform.
2:     yn – double array
The imaginary parts of the corresponding elements of the computed transform.
3:     ifail int64int32nag_int scalar
ifail=0 unless the function detects an error (see Error Indicators and Warnings).

Error Indicators and Warnings

Errors or warnings detected by the function:
   ifail=1
On entry,ndim<1.
   ifail=2
On entry,n nd1× nd2×× ndndim.
   ifail=10×l+1
At least one of the prime factors of ndl is greater than 19.
   ifail=10×l+2
ndl has more than 20 prime factors.
   ifail=10×l+3
On entry,ndl<1.
   ifail=10×l+4
On entry,lwork<3×ndl.
   ifail=-99
An unexpected error has been triggered by this routine. Please contact NAG.
   ifail=-399
Your licence key may have expired or may not have been installed correctly.
   ifail=-999
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 is approximately proportional to n×logn , but also depends on the factorization of the individual dimensions ndi . nag_sum_fft_complex_multid_sep (c06fj) is faster if the only prime factors are 2, 3 or 5; and fastest of all if they are powers of 2.

Example

This example reads in a bivariate sequence of complex data values and prints the two-dimensional Fourier transform. It then performs an inverse transform and prints the sequence so obtained, which may be compared to the original data values.
function c06fj_example


fprintf('c06fj example results\n\n');

x = [ 1.000     0.999     0.987     0.936     0.802;
      0.994     0.989     0.963     0.891     0.731;
      0.903     0.885     0.823     0.694     0.467];
y = [ 0.000    -0.040    -0.159    -0.352    -0.597;
     -0.111    -0.151    -0.268    -0.454    -0.682
     -0.430    -0.466    -0.568    -0.720    -0.884];
nd = int64(size(x));
l  = int64(2);

% transform, then inverse transform to restore data
[xt, yt, ifail] = c06fj(nd, x, y);
[xr, yr, ifail] = c06fj(nd, xt, -yt);

% Display as complex matrices
z = x + i*y;
zt = reshape(xt+i*yt,nd);
zr = reshape(xr-i*yr,nd);

matrix = 'general';
diag = ' ';
usefrm = 'Above';
format = 'F9.3';
labrow = 'None';
labcol = 'None';
ncols  = int64(80);
indent = int64(0);

title  = 'Original data:';
[ifail] = x04db(...
    matrix, diag, z, usefrm, format, title, labrow, labcol, ncols, indent);
disp(' ');
title = 'Discrete Fourier transform of data:';
[ifail] = x04db(...
    matrix, diag, zt, usefrm, format, title, labrow, labcol, ncols, indent);
disp(' ');
title = 'Original sequence as restored by inverse transform:';
[ifail] = x04db(...
    matrix, diag, zr, usefrm, format, title, labrow, labcol, ncols, indent);


c06fj example results

 Original data:
      1.000    0.999    0.987    0.936    0.802
      0.000   -0.040   -0.159   -0.352   -0.597

      0.994    0.989    0.963    0.891    0.731
     -0.111   -0.151   -0.268   -0.454   -0.682

      0.903    0.885    0.823    0.694    0.467
     -0.430   -0.466   -0.568   -0.720   -0.884
 
 Discrete Fourier transform of data:
      3.373    0.481    0.251    0.054   -0.419
     -1.519   -0.091    0.178    0.319    0.415

      0.457    0.055    0.009   -0.022   -0.076
      0.137    0.032    0.039    0.036    0.004

     -0.170   -0.037   -0.042   -0.038   -0.002
      0.493    0.058    0.008   -0.025   -0.083
 
 Original sequence as restored by inverse transform:
      1.000    0.999    0.987    0.936    0.802
      0.000   -0.040   -0.159   -0.352   -0.597

      0.994    0.989    0.963    0.891    0.731
     -0.111   -0.151   -0.268   -0.454   -0.682

      0.903    0.885    0.823    0.694    0.467
     -0.430   -0.466   -0.568   -0.720   -0.884

PDF version (NAG web site, 64-bit version, 64-bit version)
Chapter Contents
Chapter Introduction
NAG Toolbox

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