Some months ago, I recovered a signal processing plugin that I did in the past. During this time I have been update it to make it compatible with Python 3.10.

I would like share a trial version with all of you 🙂 

The plugin-has a detailed documentation about the plugin, theory and examples of usage (which I believe are very interesting). The operators currently implemented are:

• Base line correction to remove the signal trend.

• Numerical derivative by difference approximation. This does the derivative in time domain and in frequency domain.
• Discrete Fourier Transform analysis to obtain the frequency content of the signal. Also, if the number of data is power of two, Cooley-Tukey algorith is used to do a FFT (much more efficient).
• Filter to filter out frenquency contribution by using a rectangular filter (Band pass, High pass and Low pass filters).

• Numerical integration with: Left hand, Right hand, Trapezoidal and Simpson methods. As numerical derivative, it integrate in both time and frequency domains.
• Inverse Discrete Fourier Transform to recover the data in time domain.
• Power Spectral Density to calculate the PSD based on DFT or by using Welch's method.
• Scale to scale the data, and

• Windowing to correct the data by window functions e.g. Hanning, Hamming, Gauss, ...

  

  Different normalization factors of the windows are available to mantain the Energy of the signal or the Peak amplitude.

   

The phylosophy of the plugin is that the user can create a processing flow with the desired operators to evaluate the signal.

I hope you find it of interest ;)