functions.py 文件源码

def removePeriodic(data, f0=60.0, dt=None, harmonics=10, samples=4):
    if (hasattr(data, 'implements') and data.implements('MetaArray')):
        data1 = data.asarray()
        if dt is None:
            times = data.xvals('Time')
            dt = times[1]-times[0]
    else:
        data1 = data
        if dt is None:
            raise Exception('Must specify dt for this data')

    ft = np.fft.fft(data1)

    ## determine frequencies in fft data
    df = 1.0 / (len(data1) * dt)
    freqs = np.linspace(0.0, (len(ft)-1) * df, len(ft))

    ## flatten spikes at f0 and harmonics
    for i in xrange(1, harmonics + 2):
        f = f0 * i # target frequency

        ## determine index range to check for this frequency
        ind1 = int(np.floor(f / df))
        ind2 = int(np.ceil(f / df)) + (samples-1)
        if ind1 > len(ft)/2.:
            break
        mag = (abs(ft[ind1-1]) + abs(ft[ind2+1])) * 0.5
        for j in range(ind1, ind2+1):
            phase = np.angle(ft[j])   ## Must preserve the phase of each point, otherwise any transients in the trace might lead to large artifacts.
            re = mag * np.cos(phase)
            im = mag * np.sin(phase)
            ft[j] = re + im*1j
            ft[len(ft)-j] = re - im*1j

    data2 = np.fft.ifft(ft).real

    if (hasattr(data, 'implements') and data.implements('MetaArray')):
        return metaarray.MetaArray(data2, info=data.infoCopy())
    else:
        return data2