{"id":22371312,"url":"https://github.com/braindatalab/pybispectra","last_synced_at":"2025-07-30T20:32:03.907Z","repository":{"id":142679797,"uuid":"607207088","full_name":"braindatalab/PyBispectra","owner":"braindatalab","description":"A Python signal analysis toolbox for computing spectral-domain interactions using the bispectrum.","archived":false,"fork":false,"pushed_at":"2024-12-03T20:38:09.000Z","size":27232,"stargazers_count":19,"open_issues_count":1,"forks_count":4,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-12-04T20:18:46.546Z","etag":null,"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"],"latest_commit_sha":null,"homepage":"https://pybispectra.readthedocs.io/en/main/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/braindatalab.png","metadata":{"files":{"readme":"README.md","changelog":"changelog.md","contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":"CITATION.cff","codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2023-02-27T14:34:00.000Z","updated_at":"2024-12-03T20:38:11.000Z","dependencies_parsed_at":"2024-11-19T00:29:35.044Z","dependency_job_id":null,"html_url":"https://github.com/braindatalab/PyBispectra","commit_stats":null,"previous_names":[],"tags_count":3,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/braindatalab%2FPyBispectra","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/braindatalab%2FPyBispectra/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/braindatalab%2FPyBispectra/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/braindatalab%2FPyBispectra/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/braindatalab","download_url":"https://codeload.github.com/braindatalab/PyBispectra/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":228183286,"owners_count":17881597,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["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"],"created_at":"2024-12-04T20:18:50.707Z","updated_at":"2025-07-30T20:32:03.896Z","avatar_url":"https://github.com/braindatalab.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"![PyBispectra logo](docs/source/_static/logo.gif)\n\nA Python signal processing package for computing spectral- and time-domain interactions using the bispectrum.\n\nThis 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.\n\nParallel processing and [Numba](https://numba.pydata.org/) optimisation are implemented to reduce computation times.\n\n## Installation \u0026 Requirements:\nInstall the package into the desired environment using pip `pip install pybispectra`\u003cbr/\u003e\nMore information on the [installation](https://pybispectra.readthedocs.io/en/main/installation.html) page.\n\n## Use:\nTo 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).\n\n## Contributing \u0026 Development:\nIf 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.\n\n## Citing:\nIf you use this toolbox in your work, please include the following citation:\u003cbr/\u003e\nBinns, T. S., Pellegrini, F., Jurhar, T., \u0026 Haufe, S. (2023). PyBispectra. DOI: [10.5281/zenodo.8377820](https://doi.org/10.5281/zenodo.8377820)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbraindatalab%2Fpybispectra","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbraindatalab%2Fpybispectra","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbraindatalab%2Fpybispectra/lists"}