Welcome to Hypergraphx's docs!
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.. image:: ../assets/logo/logo.png
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Hypergraphx (HGX) is a Python library for higher-order network analysis.
.. toctree::
:maxdepth: 2
:caption: π Get Started
:class: index-toc
installation
quickstart
tutorials
.. toctree::
:maxdepth: 2
:caption: π API Reference
:class: index-toc
api/hypergraphx
Project links
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.. |fa-arxiv| raw:: html
.. |fa-github| raw:: html
.. |fa-pypi| raw:: html
.. |fa-docs| raw:: html
.. |fa-data| raw:: html
.. rst-class:: project-links
- |fa-arxiv| `Arxiv `_
- |fa-github| `GitHub `_
- |fa-pypi| `PyPI `_
- |fa-docs| `Documentation `_
- |fa-data| Data: To appear soon
Get started
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.. list-table::
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:header-rows: 0
:class: get-started
* - :doc:`βοΈ Installation `
- Install HGX from PyPI or source, then verify it works.
* - :doc:`π Quickstart `
- Create your first hypergraph and compute basic measures.
* - :doc:`π Tutorials `
- Notebook-driven examples for workflows and models.
Higher-order data repository
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To appear soon
Reference
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* Lotito, Quintino Francesco, et al. "Hypergraphx: a library for higher-order network analysis." Journal of Complex Networks 11.3 (2023): cnad019.
Contributing
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HGX is a collaborative project and we welcome suggestions and contributions.
If you are interested in contributing to HGX or have any questions about our project, please do not hesitate to reach out to us.
We look forward to hearing from you!
HGX Team
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Project coordinators:
* Quintino Francesco Lotito
* Federico Battiston
Core members:
* Martina Contisciani
* Caterina De Bacco
* Leonardo Di Gaetano
* Luca Gallo
* Alberto Montresor
* Federico Musciotto
* NicolΓ² Ruggeri
License
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This project is licensed under the `BSD 3-Clause License
`_.
Copyright |copyright|