[![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.
Raw data
{
"_id": null,
"home_page": "https://github.com/scikit-tda/scikit-tda",
"name": "scikit-tda",
"maintainer": null,
"docs_url": null,
"requires_python": ">3.3",
"maintainer_email": null,
"keywords": "topology data analysis, algebraic topology, unsupervised learning, persistent homology, persistence images, persistence diagrams, uniform manifold approximation and projection, sheaf theory, mapper, data visualization",
"author": "Nathaniel Saul, Chris Tralie",
"author_email": "nathaniel.saul@wsu.edu, chris.tralie@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/1e/12/f13612a33e4e5d3c29a0ca1c4994d2f44b85c4c0005ece42606228c916fa/scikit_tda-1.1.1.tar.gz",
"platform": null,
"description": "[![DOI](https://zenodo.org/badge/129452930.svg)](https://zenodo.org/badge/latestdoi/129452930)\n![PyPI - Version](https://img.shields.io/pypi/v/scikit-tda)\n![PyPI - Downloads](https://img.shields.io/pypi/dm/scikit-tda)\n\nScikit-TDA is a home for Topological Data Analysis Python libraries intended for non-topologists.\n\nThis 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.\n\n# Documentation\n\nFor complete documentation please checkout [docs.scikit-tda.org](https://docs.scikit-tda.org/en/latest/).\n\n# Contact\n\nIf you would like to contribute, please reach out to us on\n[github](https://github.com/scikit-tda) by starting a [discussion\ntopic](https://github.com/orgs/scikit-tda/discussions), [creating an\nissue](https://github.com/scikit-tda/scikit-tda/issues), or reaching out on\n[twitter](https://twitter.com/scikit_tda).\n\n# Setup\n\nTo install all these libraries\n\n```\n pip install scikit-tda\n```\n\n# Citations\n\nIf you would like to cite Scikit-TDA, please use the following citation/bibtex\n\n> Saul, Nathaniel and Tralie, Chris. (2019). Scikit-TDA: Topological Data Analysis for Python. Zenodo. http://doi.org/10.5281/zenodo.2533369\n\n```\n@misc{scikittda2019,\n author = {Nathaniel Saul, Chris Tralie},\n title = {Scikit-TDA: Topological Data Analysis for Python},\n year = 2019,\n doi = {10.5281/zenodo.2533369},\n url = {https://doi.org/10.5281/zenodo.2533369}\n}\n```\n\n# License\n\nThis package is licensed with the MIT license.\n\n# Contributing\n\nContributions 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.\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "Topological Data Analysis for humans",
"version": "1.1.1",
"project_urls": {
"Homepage": "https://github.com/scikit-tda/scikit-tda"
},
"split_keywords": [
"topology data analysis",
" algebraic topology",
" unsupervised learning",
" persistent homology",
" persistence images",
" persistence diagrams",
" uniform manifold approximation and projection",
" sheaf theory",
" mapper",
" data visualization"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "61096cd7fd52c0cca80d409b60de5d5e99d494fe4005cc8a8fedb31b96f22af5",
"md5": "69d41a93a23f244dccd8f1a10d50f999",
"sha256": "5f035174d54090d2360d8acb1f1387f59b9a52c65822278a8af5aab237693674"
},
"downloads": -1,
"filename": "scikit_tda-1.1.1-py3-none-any.whl",
"has_sig": false,
"md5_digest": "69d41a93a23f244dccd8f1a10d50f999",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">3.3",
"size": 3781,
"upload_time": "2024-07-19T18:49:00",
"upload_time_iso_8601": "2024-07-19T18:49:00.003164Z",
"url": "https://files.pythonhosted.org/packages/61/09/6cd7fd52c0cca80d409b60de5d5e99d494fe4005cc8a8fedb31b96f22af5/scikit_tda-1.1.1-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "1e12f13612a33e4e5d3c29a0ca1c4994d2f44b85c4c0005ece42606228c916fa",
"md5": "66e0b96c851e2255304587a1dbf534b5",
"sha256": "530b8dd7391c37ca12a585e7c1e585adeb24779fc66ea612221f6273e654d086"
},
"downloads": -1,
"filename": "scikit_tda-1.1.1.tar.gz",
"has_sig": false,
"md5_digest": "66e0b96c851e2255304587a1dbf534b5",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">3.3",
"size": 4218,
"upload_time": "2024-07-19T18:49:01",
"upload_time_iso_8601": "2024-07-19T18:49:01.095424Z",
"url": "https://files.pythonhosted.org/packages/1e/12/f13612a33e4e5d3c29a0ca1c4994d2f44b85c4c0005ece42606228c916fa/scikit_tda-1.1.1.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2024-07-19 18:49:01",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "scikit-tda",
"github_project": "scikit-tda",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "scikit-tda"
}