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.
The preferred way to install is with pip:
pip3 install fir1
You can also install from source with python3 setup.py install:
git clone https://github.com/berndporr/fir1 cd fir1 python3 setup.py install
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.
Release history Release notifications
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
|Filename, size||File type||Python version||Upload date||Hashes|
|Filename, size fir1-220.127.116.11-py3.6-linux-x86_64.egg (77.4 kB)||File type Egg||Python version 3.6||Upload date||Hashes View hashes|
Hashes for fir1-18.104.22.168-py3.6-linux-x86_64.egg