Description
HOI (Higher Order Interactions) is a Python package to go beyond pairwise interactions by quantifying the statistical dependencies between 2 or more units using information-theoretical metrics. The package is built on top of Jax allowing computations on CPU or GPU.
Installation
Dependencies
HOI requires :
Python (>= 3.8)
numpy(>=1.22)
scipy (>=1.9)
jax
pandas
scikit-learn
jax-tqdm
tqdm
User installation
To install Jax on GPU or CPU-only, please refer to Jax’s documentation : https://jax.readthedocs.io/en/latest/installation.html
If you already have a working installation of NumPy, SciPy and Jax, the easiest way to install hoi is using pip:
pip install -U hoi
You can also install the latest version of the software directly from Github :
pip install git+https://github.com/brainets/hoi.git
For developers
For developers, you can install it in develop mode with the following commands :
git clone https://github.com/brainets/hoi.git
cd hoi
pip install -e .['full']
The full installation of HOI includes additional packages to test the software and build the documentation :
pytest
pytest-cov
codecov
xarray
sphinx!=4.1.0
sphinx-gallery
pydata-sphinx-theme
sphinxcontrib-bibtex
numpydoc
matplotlib
flake8
pep8-naming
black
Help and Support
Documentation
Link to the documentation: https://brainets.github.io/hoi/
Overview of the mathematical background : https://brainets.github.io/hoi/theory.html
List of implemented HOI metrics : https://brainets.github.io/hoi/api/modules.html
Examples : https://brainets.github.io/hoi/auto_examples/index.html
Communication
For questions, please use the following link : https://github.com/brainets/hoi/discussions
Acknowledgments
HOI was mainly developed during the Google Summer of Code 2023 (https://summerofcode.withgoogle.com/archive/2023/projects/z6hGpvLS)
Metadata
Release files for hoi 0.0.7
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| hoi-0.0.7.tar.gz | 33.5 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| hoi-0.0.7-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 95.2 kB
Release files / hoi-0.0.7.tar.gz
| Download URL | hoi-0.0.7.tar.gz |
|---|---|
| Size | 33.5 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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Transparency logRelease files / hoi-0.0.7-py3-none-any.whl
| Download URL | hoi-0.0.7-py3-none-any.whl |
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| Size | 61.7 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Jan 30, 2026.
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