Metadata-Version: 2.1
Name: scikit-tda
Version: 1.1.1
Summary: Topological Data Analysis for humans
Home-page: https://github.com/scikit-tda/scikit-tda
Author: Nathaniel Saul, Chris Tralie
Author-email: nathaniel.saul@wsu.edu, chris.tralie@gmail.com
License: MIT
Keywords: topology data analysis,algebraic topology,unsupervised learning,persistent homology,persistence images,persistence diagrams,uniform manifold approximation and projection,sheaf theory,mapper,data visualization
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Financial and Insurance Industry
Classifier: Intended Audience :: Healthcare Industry
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Requires-Python: >3.3
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy
Requires-Dist: scipy
Requires-Dist: scikit-learn
Requires-Dist: matplotlib
Requires-Dist: Cython
Requires-Dist: ripser
Requires-Dist: persim
Requires-Dist: pillow
Requires-Dist: kmapper
Requires-Dist: tadasets
Provides-Extra: docs
Requires-Dist: sktda-docs-config ; extra == 'docs'
Requires-Dist: pyyaml ; extra == 'docs'
Provides-Extra: testing
Requires-Dist: pytest ; extra == 'testing'

[![DOI](https://zenodo.org/badge/129452930.svg)](https://zenodo.org/badge/latestdoi/129452930)
![PyPI - Version](https://img.shields.io/pypi/v/scikit-tda)
![PyPI - Downloads](https://img.shields.io/pypi/dm/scikit-tda)

Scikit-TDA is a home for Topological Data Analysis Python libraries intended for non-topologists.

This project aims to provide a curated library of TDA Python tools that are widely usable and easily approachable. It is structured so that each package can stand alone or be used as part of the `scikit-tda` bundle.

# Documentation

For complete documentation please checkout [docs.scikit-tda.org](https://docs.scikit-tda.org/en/latest/).

# Contact

If you would like to contribute, please reach out to us on
[github](https://github.com/scikit-tda) by starting a [discussion
topic](https://github.com/orgs/scikit-tda/discussions), [creating an
issue](https://github.com/scikit-tda/scikit-tda/issues), or reaching out on
[twitter](https://twitter.com/scikit_tda).

# Setup

To install all these libraries

```
    pip install scikit-tda
```

# Citations

If you would like to cite Scikit-TDA, please use the following citation/bibtex

> Saul, Nathaniel and Tralie, Chris. (2019). Scikit-TDA: Topological Data Analysis for Python. Zenodo. http://doi.org/10.5281/zenodo.2533369

```
@misc{scikittda2019,
  author       = {Nathaniel Saul, Chris Tralie},
  title        = {Scikit-TDA: Topological Data Analysis for Python},
  year         = 2019,
  doi          = {10.5281/zenodo.2533369},
  url          = {https://doi.org/10.5281/zenodo.2533369}
}
```

# License

This package is licensed with the MIT license.

# Contributing

Contributions are more than welcome! There are lots of opportunities for potential projects, so please get in touch if you would like to help out. Everything from code to notebooks to examples and documentation are all equally valuable so please don't feel you can't contribute. To contribute please fork the project make your changes and submit a pull request. We will do our best to work through any issues with you and get your code merged into the main branch.
