{"id":13515019,"url":"https://github.com/stephenhky/PyTDA","last_synced_at":"2025-03-31T04:36:19.386Z","repository":{"id":35683035,"uuid":"39958997","full_name":"stephenhky/PyTDA","owner":"stephenhky","description":"Topological Data Analysis in Python","archived":false,"fork":false,"pushed_at":"2019-02-20T19:00:36.000Z","size":19,"stargazers_count":170,"open_issues_count":0,"forks_count":34,"subscribers_count":18,"default_branch":"master","last_synced_at":"2025-03-14T20:53:01.491Z","etag":null,"topics":["demo-codes","numerical-methods","python","tda","topological-data-analysis","topology"],"latest_commit_sha":null,"homepage":"https://github.com/stephenhky/MoguTDA","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/stephenhky.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2015-07-30T15:52:55.000Z","updated_at":"2025-01-10T14:57:16.000Z","dependencies_parsed_at":"2022-09-07T05:13:42.855Z","dependency_job_id":null,"html_url":"https://github.com/stephenhky/PyTDA","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stephenhky%2FPyTDA","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stephenhky%2FPyTDA/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stephenhky%2FPyTDA/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/stephenhky%2FPyTDA/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/stephenhky","download_url":"https://codeload.github.com/stephenhky/PyTDA/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246418658,"owners_count":20773934,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["demo-codes","numerical-methods","python","tda","topological-data-analysis","topology"],"created_at":"2024-08-01T05:01:05.417Z","updated_at":"2025-03-31T04:36:19.104Z","avatar_url":"https://github.com/stephenhky.png","language":"Python","funding_links":[],"categories":["Libraries, frameworks, tools","Python"],"sub_categories":[],"readme":"# PyTDA - Topological Data Analysis (TDA) for Python\n\n## Important Notice\nThis repository is NOT a Python package. Codes in this\nrepository are for demonstration and described in the blog\nentries listed below. And the codes in this repository run\nin Python 2.7 only.\n\nHowever, there will be an optimized\ncode found in the package [`mogutda`](https://pypi.org/project/mogutda/), and\nyou can refer to the codes in my another repository: [MoguTDA](https://github.com/stephenhky/MoguTDA)\nYou can also install the package `mogutda` by typing\non the command prompt:\n\n```\npip install -U mogutda\n```\n\nThe package `mogutda` runs in Python 2.7, 3.5, and 3.6.\n\n\n## Introduction\nPyTDA contains Python codes that demonstrate the numerical calculation\nof algebraic topology in an application to topological data analysis \n(TDA).\n\nTopological data analysis aims at studying the shapes of the data, and\ndraw some insights from them. A lot of machine learning algorithms deal \nwith distances, which are extremely useful, but they miss the \ninformation the data may carry from their geometry.\n\n## Demo Codes and Blog Entries\nCodes in this repository are demo codes for a few entries of my blog,\n[Everything about Data Analytics](https://datawarrior.wordpress.com/),\nand the corresponding entries are:\n\n* [Starting the Journey of Topological Data Analysis (TDA)](https://datawarrior.wordpress.com/2015/08/03/tda-1-starting-the-journey-of-topological-data-analysis-tda/) (August 3, 2015)\n* [Constructing Connectivities](https://datawarrior.wordpress.com/2015/09/14/tda-2-constructing-connectivities/) (September 14, 2015)\n* [Homology and Betti Numbers](https://datawarrior.wordpress.com/2015/11/03/tda-3-homology-and-betti-numbers/) (November 3, 2015)\n* [Topology in Physics and Computing](https://datawarrior.wordpress.com/2015/11/10/mathanalytics-6-topology-in-physics-and-computing/) (November 10, 2015)\n* [Persistence](https://datawarrior.wordpress.com/2015/12/20/tda-4-persistence/) (December 20, 2015)\n* [Topological Phases](https://datawarrior.wordpress.com/2016/10/06/topological-phases/) (October 6, 2016)\n* [moguTDA: Python package for Simplicial Complex](https://datawarrior.wordpress.com/2018/07/02/mogutda-python-package-for-simplicial-complex/) (July 2, 2018)\n\n## Wolfram Demonstration\nRichard Hennigan put a nice Wolfram Demonstration online explaining what\nthe simplicial complexes are, and how homologies are defined:\n\n* [Simplicial Homology of the Alpha Complex](http://demonstrations.wolfram.com/SimplicialHomologyOfTheAlphaComplex/)\n\n## Other TDA Packages\nIt is recommended that for real application, you should use the following packages\nfor efficiency, because my codes serve the pedagogical purpose only.\n\n### C++\n* [Dionysus](http://www.mrzv.org/software/dionysus/)\n* [PHAT](https://bitbucket.org/phat-code/phat)\n\n### Python\n* [mogutda](https://pypi.org/project/mogutda/)\n* [Dionysus](http://www.mrzv.org/software/dionysus/python/overview.html)\n\n### R\n* [TDA](https://cran.r-project.org/web/packages/TDA/index.html) (article: [\\[arXiv\\]](http://arxiv.org/abs/1411.1830))\n\n## References\n* Afra J. Zomorodian. *Topology for Computing* (New York, NY: Cambridge University Press, 2009). [\\[Amazon\\]](https://www.amazon.com/Computing-Cambridge-Monographs-Computational-Mathematics/dp/0521136091)\n* Afra J. Zomorodian. \"Topological Data Analysis,\" *Proceedings of Symposia in Applied Mathematics* (2011). [\\[link\\]](http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.261.1298)\n* Afra Zomorodian, Gunnar Carlsson, “Computing Persistent Homology,” *Discrete Comput. Geom.* 33, 249-274 (2005). [\\[pdf\\]](http://geometry.stanford.edu/papers/zc-cph-05/zc-cph-05.pdf) \n* Gunnar Carlsson, “Topology and Data”, *Bull. Amer. Math. Soc.* 46, 255-308 (2009). [\\[link\\]](http://www.ams.org/journals/bull/2009-46-02/S0273-0979-09-01249-X/)\n* P. Y. Lum, G. Singh, A. Lehman, T. Ishkanov, M. Vejdemo-Johansson, M. Alagappan, J. Carlsson, G. Carlsson, “Extracting insights from the shape of complex data using topology”, *Sci. Rep.* 3, 1236 (2013). [\\[link\\]](http://www.nature.com/srep/2013/130207/srep01236/full/srep01236.html)\n* Robert Ghrist, “Barcodes: The persistent topology of data,” *Bull. Amer. Math. Soc.* 45, 1-15 (2008). [\\[pdf\\]](http://www.ams.org/journals/bull/2008-45-01/S0273-0979-07-01191-3/S0273-0979-07-01191-3.pdf)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstephenhky%2FPyTDA","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstephenhky%2FPyTDA","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstephenhky%2FPyTDA/lists"}