问题
I am writing some code with Python using the scipy.signal library to filter electromagnetic data that is mixed with various undesirable signatures that I want to filter out. For example, I have power line harmonics at various frequencies (i.e. 60, 120 Hz, etc....) with a width of only a few Hz that I would like to remove from the data using a notch filter. Is there already an existing function in python where I can merely inform the code how many data points i wish to use for the filter, the center-line frequency that I wish to remove and the width of the transition band or do I need to design a filter from scratch? If it is the latter I would greatly appreciate an example of notch filter design in Python to include window implementation to minimize aliasing.
回答1:
There are a few options for the solution on the scipy.signal website, but they introduce a lot of ringing, which will translate to artifacts in the convolved signal. After trying many things I found the following function worked the best for implementing an FIR notch filter.
# 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
来源：https://stackoverflow.com/questions/35565540/designing-an-fir-notch-filter-with-python