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.. _ahelp_3dDFT:

*****
3dDFT
*****

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    Usage: 3dDFT [options] dataset
           where 'dataset' is complex- or float-valued.
     * Carries out the DFT along the time axis.
     * To do the DFT along the spatial axes, use program 3dFFT.
     * The input dataset can be complex-valued or float-valued.
       If it is any other data type, it will be converted to floats
       before processing.
     * [June 2018] The FFT length used is NOT rounded up to a convenient
       FFT radix; instead, the FFT size is actual value supplied in option
       '-nfft' or the number of time points (if '-nfft' isn't used).
     * However, if the FFT length has large prime factors (say > 97), the
       Fast Fourier Transform algorithm will be relatively slow. This slowdown
       is probably only noticeable for very long files, since reading and
       writing datasets seems to take most of the elapsed time in 'normal' cases.
    
    OPTIONS:
    --------
    
     -prefix PP  == use 'PP' as the prefix of the output file
    
     -abs     == output float dataset = abs(DFT)
                * Otherwise, the output file is complex-valued.
                  You can then use 3dcalc to extract the real part, the
                  imaginary part, the phase, etc.; see its '-cx2r' option:
                    3dcalc  -cx2r REAL -a cxset+orig-expr a -prefix rset+orig
                * Please note that if you view a complex dataset in AFNI,
                  the default operation is that you are looking at the
                  absolute value of the dataset.
                 ++ You can control the way a complex IMAGE appears via
                    the 'Disp' control panel (ABS, PHASE, REAL, IMAGE).
                 ++ You can control the way a complex TIME SERIES graph appears
                    via environment variable AFNI_GRAPH_CX2R (in 'EditEnv').
    
     -nfft N  == use 'N' for DFT length (must be >= #time points)
    
     -detrend == least-squares remove linear drift before DFT
                  [for more intricate detrending, use 3dDetrend first]
    
     -taper f == taper 'f' fraction of data at ends (0 <= f <= 1).
                  [Hamming 'raised cosine' taper of f/2 of the ]
                  [data length at each end; default is no taper]
                  [cf. 3dPeriodogam -help for tapering details!]
    
     -inverse == Do the inverse DFT:
                   SUM{ data[j] * exp(+2*PI*i*j/nfft) } * 1/nfft
                 instead of the forward transform
                   SUM{ data[j] * exp(-2*PI*i*j/nfft) }
    
    ++ Compile date = Apr 18 2024 {AFNI_24.1.03:linux_ubuntu_16_64}