Next: , Previous: Overview of complex data FFTs, Up: Fast Fourier Transforms

16.3 Radix-2 FFT routines for complex data

The radix-2 algorithms described in this section are simple and compact, although not necessarily the most efficient. They use the Cooley-Tukey algorithm to compute in-place complex FFTs for lengths which are a power of 2—no additional storage is required. The corresponding self-sorting mixed-radix routines offer better performance at the expense of requiring additional working space.

All the functions described in this section are declared in the header file gsl_fft_complex.h.

— Function: int gsl_fft_complex_radix2_forward (gsl_complex_packed_array data, size_t stride, size_t n)
— Function: int gsl_fft_complex_radix2_transform (gsl_complex_packed_array data, size_t stride, size_t n, gsl_fft_direction sign)
— Function: int gsl_fft_complex_radix2_backward (gsl_complex_packed_array data, size_t stride, size_t n)
— Function: int gsl_fft_complex_radix2_inverse (gsl_complex_packed_array data, size_t stride, size_t n)

These functions compute forward, backward and inverse FFTs of length n with stride stride, on the packed complex array data using an in-place radix-2 decimation-in-time algorithm. The length of the transform n is restricted to powers of two. For the transform version of the function the sign argument can be either forward (-1) or backward (+1).

The functions return a value of GSL_SUCCESS if no errors were detected, or GSL_EDOM if the length of the data n is not a power of two.

— Function: int gsl_fft_complex_radix2_dif_forward (gsl_complex_packed_array data, size_t stride, size_t n)
— Function: int gsl_fft_complex_radix2_dif_transform (gsl_complex_packed_array data, size_t stride, size_t n, gsl_fft_direction sign)
— Function: int gsl_fft_complex_radix2_dif_backward (gsl_complex_packed_array data, size_t stride, size_t n)
— Function: int gsl_fft_complex_radix2_dif_inverse (gsl_complex_packed_array data, size_t stride, size_t n)

These are decimation-in-frequency versions of the radix-2 FFT functions.

Here is an example program which computes the FFT of a short pulse in a sample of length 128. To make the resulting Fourier transform real the pulse is defined for equal positive and negative times (-10 ... 10), where the negative times wrap around the end of the array. 

     #include <stdio.h>
     #include <math.h>
     #include <gsl/gsl_errno.h>
     #include <gsl/gsl_fft_complex.h>
     
     #define REAL(z,i) ((z)[2*(i)])
     #define IMAG(z,i) ((z)[2*(i)+1])
     
     int
     main (void)
     {
       int i; double data[2*128];
     
       for (i = 0; i < 128; i++)
         {
            REAL(data,i) = 0.0; IMAG(data,i) = 0.0;
         }
     
       REAL(data,0) = 1.0;
     
       for (i = 1; i <= 10; i++)
         {
            REAL(data,i) = REAL(data,128-i) = 1.0;
         }
     
       for (i = 0; i < 128; i++)
         {
           printf ("%d %e %e\n", i, 
                   REAL(data,i), IMAG(data,i));
         }
       printf ("\n");
     
       gsl_fft_complex_radix2_forward (data, 1, 128);
     
       for (i = 0; i < 128; i++)
         {
           printf ("%d %e %e\n", i, 
                   REAL(data,i)/sqrt(128), 
                   IMAG(data,i)/sqrt(128));
         }
     
       return 0;
     }

Note that we have assumed that the program is using the default error handler (which calls abort for any errors). If you are not using a safe error handler you would need to check the return status of gsl_fft_complex_radix2_forward.

The transformed data is rescaled by 1/\sqrt n so that it fits on the same plot as the input. Only the real part is shown, by the choice of the input data the imaginary part is zero. Allowing for the wrap-around of negative times at t=128, and working in units of k/n, the DFT approximates the continuum Fourier transform, giving a modulated sine function.