https://github.com/braindatalab/pybispectra

A Python signal analysis toolbox for computing spectral-domain interactions using the bispectrum.
https://github.com/braindatalab/pybispectra

amplitude-amplitude-coupling bicoherence bispectrum connectivity cross-frequency-coupling hpmax neuroscience non-sinusoidal phase-amplitude-coupling phase-phase-coupling python signal-processing spatiospectral spectral-analysis ssd time-delay-estimation waveform waveshape

Last synced: 2 months ago
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A Python signal analysis toolbox for computing spectral-domain interactions using the bispectrum.

• Host: GitHub
• URL: https://github.com/braindatalab/pybispectra
• Owner: braindatalab
• License: mit
• Created: 2023-02-27T14:34:00.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2024-12-03T20:38:09.000Z (10 months ago)
• Last Synced: 2024-12-04T20:18:46.546Z (10 months ago)
• Topics: amplitude-amplitude-coupling, bicoherence, bispectrum, connectivity, cross-frequency-coupling, hpmax, neuroscience, non-sinusoidal, phase-amplitude-coupling, phase-phase-coupling, python, signal-processing, spatiospectral, spectral-analysis, ssd, time-delay-estimation, waveform, waveshape
• Language: Python
• Homepage: https://pybispectra.readthedocs.io/en/main/
• Size: 26 MB
• Stars: 19
• Watchers: 2
• Forks: 4
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • Changelog: changelog.md
  • License: LICENSE.txt
  • Citation: CITATION.cff

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README

          
![PyBispectra logo](docs/source/_static/logo.gif)

A Python signal processing package for computing spectral- and time-domain interactions using the bispectrum.

This package provides the tools for computing phase-amplitude coupling, time delay estimation, and wave shape features using the bispectrum and bicoherence. Additional tools for computing amplitude-amplitude coupling, phase-phase coupling, and spatio-spectral filters are also provided.

Parallel processing and [Numba](https://numba.pydata.org/) optimisation are implemented to reduce computation times.

## Installation & Requirements:

Install the package into the desired environment using pip `pip install pybispectra`


More information on the [installation](https://pybispectra.readthedocs.io/en/main/installation.html) page.

## Use:

To get started with the toolbox, check out the [documentation](https://pybispectra.readthedocs.io/en/main/) and [examples](https://pybispectra.readthedocs.io/en/main/examples.html).

## Contributing & Development:

If you encounter issues with the package, want to suggest improvements, or have made any changes which you would like to see officially supported, please refer to the [development](https://pybispectra.readthedocs.io/en/main/development.html) page. A unit test suite is included and must be expanded where necessary to validate any changes.

## Citing:

If you use this toolbox in your work, please include the following citation:


Binns, T. S., Pellegrini, F., Jurhar, T., & Haufe, S. (2023). PyBispectra. DOI: [10.5281/zenodo.8377820](https://doi.org/10.5281/zenodo.8377820)