love_gannon.py 文件源码

def series_nfft(series,
                oversample=4):
    """
    note that output period units are [days] (so is frequency)
    """
    M = len(series)
    if not is_power_of_2(M):
        raise ValueError('series length {} is not a power of 2'.format(len(series)))
    N = M
    if N % 2 == 1:
        # number of frequency samples must be even
        N += 1
    N *= oversample
    # re-grid time the interval [-1/2, 1/2) as required by nfft
    time = series.index.astype(NP.int64) / 1e9
    time -= time[0]
    b = -0.5
    a = (M - 1) / (M * time[-1])
    x = a * time + b
    # setup for nfft computation
    plan = NFFT(N, M)
    plan.x = x
    plan.f = series.values
    plan.precompute()
    # compute nfft (note that conjugation is necessary because of the
    # difference in transform sign convention)
    x_nfft = NP.conj(plan.adjoint())
    # calculate frequencies and periods
    dt = ((series.index[-1] - series.index[0]) / M).total_seconds() / DAYS_TO_SECONDS
    f_range = NP.fft.fftshift(NP.fft.fftfreq(N, dt))
    T_range = 1 / f_range
    return x_nfft, f_range, T_range