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https://github.com/giotto-ai/giotto-tda

A high-performance topological machine learning toolbox in Python
https://github.com/giotto-ai/giotto-tda

computational-topology machine-learning mapper scikit-learn tda topological-data-analysis topological-machine-learning topology

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A high-performance topological machine learning toolbox in Python

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README 

        
.. image:: https://raw.githubusercontent.com/giotto-ai/giotto-tda/master/doc/images/tda_logo.svg

   :width: 850



|Version|_ |Azure-build|_ |Azure-cov|_ |Azure-test|_ |Twitter-follow|_ |Slack-join|_



.. |Version| image:: https://img.shields.io/pypi/v/giotto-tda

.. _Version:



.. |Azure-build| image:: https://dev.azure.com/maintainers/Giotto/_apis/build/status/giotto-ai.giotto-tda?branchName=master

.. _Azure-build: https://dev.azure.com/maintainers/Giotto/_build?definitionId=6&_a=summary&repositoryFilter=6&branchFilter=141&requestedForFilter=ae4334d8-48e3-4663-af95-cb6c654474ea



.. |Azure-cov| image:: https://img.shields.io/azure-devops/coverage/maintainers/Giotto/6/master

.. _Azure-cov:



.. |Azure-test| image:: https://img.shields.io/azure-devops/tests/maintainers/Giotto/6/master

.. _Azure-test:



.. |Twitter-follow| image:: https://img.shields.io/twitter/follow/giotto_ai?label=Follow%20%40giotto_ai&style=social

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.. _Slack-join: https://slack.giotto.ai/



==========

giotto-tda

==========



``giotto-tda`` is a high-performance topological machine learning toolbox in Python built on top of

``scikit-learn`` and is distributed under the GNU AGPLv3 license. It is part of the `Giotto `_

family of open-source projects.



Project genesis

===============



``giotto-tda`` is the result of a collaborative effort between `L2F SA `_,

the `Laboratory for Topology and Neuroscience `_ at EPFL,

and the `Institute of Reconfigurable & Embedded Digital Systems (REDS) `_ of HEIG-VD.



License

=======



.. _L2F team: [email protected]



``giotto-tda`` is distributed under the AGPLv3 `license `_.

If you need a different distribution license, please contact the `L2F team`_.



Documentation

=============



Please visit `https://giotto-ai.github.io/gtda-docs `_ and navigate to the version you are interested in.



Installation

============



Dependencies

------------



The latest stable version of ``giotto-tda`` requires:



- Python (>= 3.7)

- NumPy (>= 1.19.1)

- SciPy (>= 1.5.0)

- joblib (>= 0.16.0)

- scikit-learn (>= 0.23.1)

- pyflagser (>= 0.4.3)

- python-igraph (>= 0.8.2)

- plotly (>= 4.8.2)

- ipywidgets (>= 7.5.1)



To run the examples, jupyter is required.



User installation

-----------------



The simplest way to install ``giotto-tda`` is using ``pip``   ::



    python -m pip install -U giotto-tda



If necessary, this will also automatically install all the above dependencies. Note: we recommend

upgrading ``pip`` to a recent version as the above may fail on very old versions.



Pre-release, experimental builds containing recently added features, and/or

bug fixes can be installed by running   ::



    python -m pip install -U giotto-tda-nightly



The main difference between ``giotto-tda-nightly`` and the developer installation (see the section

on contributing, below) is that the former is shipped with pre-compiled wheels (similarly to the stable

release) and hence does not require any C++ dependencies. As the main library module is called ``gtda`` in

both the stable and nightly versions, ``giotto-tda`` and ``giotto-tda-nightly`` should not be installed in

the same environment.



Developer installation

----------------------



Please consult the `dedicated page `_

for detailed instructions on how to build ``giotto-tda`` from sources across different platforms.



.. _contributing-section:



Contributing

============



We welcome new contributors of all experience levels. The Giotto

community goals are to be helpful, welcoming, and effective. To learn more about

making a contribution to ``giotto-tda``, please consult `the relevant page

`_.



Testing

-------



After developer installation, you can launch the test suite from outside the

source directory   ::



    pytest gtda



Important links

===============



- Official source code repo: https://github.com/giotto-ai/giotto-tda

- Download releases: https://pypi.org/project/giotto-tda/

- Issue tracker: https://github.com/giotto-ai/giotto-tda/issues



Citing giotto-tda

=================



If you use ``giotto-tda`` in a scientific publication, we would appreciate citations to the following paper:



   `giotto-tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration `_, Tauzin *et al*, J. Mach. Learn. Res. 22.39 (2021): 1-6.



You can use the following BibTeX entry:



.. code:: bibtex



    @article{giotto-tda,

      author  = {Guillaume Tauzin and Umberto Lupo and Lewis Tunstall and Julian Burella P\'{e}rez and Matteo Caorsi and Anibal M. Medina-Mardones and Alberto Dassatti and Kathryn Hess},

      title   = {giotto-tda: A Topological Data Analysis Toolkit for Machine Learning and Data Exploration},

      journal = {Journal of Machine Learning Research},

      year    = {2021},

      volume  = {22},

      number  = {39},

      pages   = {1-6},

      url     = {http://jmlr.org/papers/v22/20-325.html}

    }



Community

=========



giotto-ai Slack workspace: https://slack.giotto.ai/



Contacts

========



[email protected]