SignalFilters

Filtering digital signals using a front end to scipy filters


License
MIT
Install
pip install SignalFilters==0.0.8

Documentation

SignalFilters

A collection of digital signal filter front end for SciPy

A collection of signal processing tools, utilities and class for signal processing

Description

The signal processing tool box has the following topics

  1. filters: Definition of three digital signal filters (all with low, high, -band-pass mode)
    • Ideal block filter
    • Butterworth filter
    • Kaiser filter
    • Phase shift removal
  2. utils: Classes and function to support signal processing
    • SignalGenerator: class to generated signal with multiple harmonic components and noise for testing purposes
    • get_peaks: Extract the peaks from a power spectral density

Installation

SignalFilters can be installed via pip from PyPi

pip install SignalFilters

Examples

Using digital filters is easy. In two steps we do:

  1. Define a noisy sine wave
  1. Filter the noisy sine wave with a band pass filter with low and high cut-off frequency at 0.08 Hz and 0.12 Hz, respectively:

More examples can be found at example_filtering and example_filtering_rtd.

Notes

  • The SciPy packages provides most signal processing tool, such as as a Power Spectral Density (PSF) estimator.
  • The filters defined in this package are a front end to the Scipy filters, making it easier to use digital filters in your code.
  • For peak finding either the PeakUtils or the PyWafo package is recommended.
  • The function get_peaks is a front end to the peakutils.peaks function
  • This project has been set up using PyScaffold 4.5.0. For details and usage information on PyScaffold see http://pyscaffold.readthedocs.org/.