Question

我正在使用scipy.signal库编写一些Python代码，以过滤与我想要过滤掉的各种不需要的签名混合的电磁数据。例如，我有各种频率（即60,120 Hz等）的电力线谐波，宽度只有几Hz，我想用陷波滤波器从数据中去掉。在python中是否已经有一个现有的函数，我只能告诉代码我希望用于滤波器的数据点数，我希望删除的中心线频率和过渡带的宽度，还是我需要设计从头开始过滤？如果是后者，我将非常感谢Python中的陷波滤波器设计示例，其中包括窗口实现以最小化混叠。

Answer 1

scipy.signal网站上的解决方案有几个选项，但它们会引入分配振铃，这将转换为卷积信号中的伪像。经过多次尝试后，我发现以下功能最适合实现FIR陷波滤波器。

# Required input defintions are as follows;
# time:   Time between samples
# band:   The bandwidth around the centerline freqency that you wish to filter
# freq:   The centerline frequency to be filtered
# ripple: The maximum passband ripple that is allowed in db
# order:  The filter order.  For FIR notch filters this is best set to 2 or 3,
#         IIR filters are best suited for high values of order.  This algorithm
#         is hard coded to FIR filters
# filter_type: 'butter', 'bessel', 'cheby1', 'cheby2', 'ellip'
# data:         the data to be filtered
def Implement_Notch_Filter(time, band, freq, ripple, order, filter_type, data):
    from scipy.signal import iirfilter
    fs   = 1/time
    nyq  = fs/2.0
    low  = freq - band/2.0
    high = freq + band/2.0
    low  = low/nyq
    high = high/nyq
    b, a = iirfilter(order, [low, high], rp=ripple, btype='bandstop',
                     analog=False, ftype=filter_type)
    filtered_data = lfilter(b, a, data)
    return filtered_data

使用python

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