filters.py 文件源码

def sp_filter_butterworth_bandpass(input_data, passband, stopband, max_passband_loss, min_stopband_attenuation):
    # The SciPy signal processing module uses normalised frequencies, so we need to normalise the input values
    norm_passband = input_data.timebase.normalise_freq(passband)
    norm_stopband = input_data.timebase.normalise_freq(stopband)
    ord,wn = sp_signal.filter_design.buttord(norm_passband, norm_stopband, max_passband_loss, min_stopband_attenuation)
    b, a = sp_signal.filter_design.butter(ord, wn, btype = 'bandpass')

    output_data = input_data

    for i,s in enumerate(output_data.signal):
        output_data.signal[i] = sp_signal.lfilter(b,a,s)

    return output_data


#########################################
## wrappers to numpy signal processing ##
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