Efficient FIR realtime filter
An efficient finite impulse response (FIR) filter class written in C++ with python wrapper.
The class offers also adaptive filtering using the least mean square (LMS) or normalised least mean square (NLMS) algorithm.
If you want to install it via pip you first need to install the fir1 filter package:
sudo add-apt-repository ppa:berndporr/usbdux sudo apt-get update sudo apt install fir1 sudo apt install fir1-dev
- Then install the python package with pip::
- pip3 install fir1
Note that this will install from source so you need to have swig installed.
You can also install from source:
git clone https://github.com/berndporr/fir1 cd fir1 cmake . make make install python3 setup.py install
The setup.py is alpha and needs to be tested.
The filter is a realtime filter which always receives the values one by one so can process data as it comes in from an ADC converter. This is simulated here with the for loop:
import fir1 b = signal.firwin(999,0.1) f = fir1.Fir1(b) for i in range(len(noisy_signal)): clean_signal[i] = f.filter(noisy_signal[i])
The constructor Fir1(b) receives the coefficients and then filtering is performed with the method filter().
LMS adaptive filter
Please check the C++ code for examples and the main github page. The functions are identical.
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