def wfmorlet_fft(f0, sd, sampling_rate, ns=5, nt=None):
    """
    returns a complex morlet wavelet in the frequency domain

    Parameters
    ----------
        f0 : center frequency
        sd : standard deviation of center frequency
        sampling_rate : samplingrate
        ns : window length in number of standard deviations
        nt : window length in number of sample points
    """
    if nt == None:
        st = 1. / (2. * np.pi * sd)
        nt = 2 * int(ns * st * sampling_rate) + 1
    f = fftpack.fftfreq(nt, 1. / sampling_rate)
    wf = 2 * np.exp(-(f - f0) ** 2 / (2 * sd ** 2)) * np.sqrt(sampling_rate /
                                                    (np.sqrt(np.pi) * sd))
    wf[0 < f] = 0
    wf[f == 0] /= 2
    return wf
dataset/ETHPy150Open nipy/nitime/nitime/algorithms/wavelet.py/wfmorlet_fft/swapped operands of `<`