{"id":13528562,"url":"https://github.com/benfulcher/hctsa","last_synced_at":"2025-05-14T21:09:03.031Z","repository":{"id":9030406,"uuid":"10790340","full_name":"benfulcher/hctsa","owner":"benfulcher","description":"Highly comparative time-series analysis","archived":false,"fork":false,"pushed_at":"2025-04-10T23:04:33.000Z","size":192961,"stargazers_count":756,"open_issues_count":11,"forks_count":329,"subscribers_count":48,"default_branch":"main","last_synced_at":"2025-04-11T00:19:09.345Z","etag":null,"topics":["feature-extraction","matlab","time-series","time-series-analysis"],"latest_commit_sha":null,"homepage":"https://time-series-features.gitbook.io/hctsa-manual/","language":"MATLAB","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/benfulcher.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE.txt","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2013-06-19T11:41:59.000Z","updated_at":"2025-03-14T03:09:08.000Z","dependencies_parsed_at":"2023-10-20T18:21:49.929Z","dependency_job_id":"1f0cbe66-e766-4702-81b0-68698820dfde","html_url":"https://github.com/benfulcher/hctsa","commit_stats":{"total_commits":965,"total_committers":16,"mean_commits":60.3125,"dds":"0.22901554404145075","last_synced_commit":"3e76975eef0380060385e8379ffe988fb89d44ab"},"previous_names":[],"tags_count":22,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benfulcher%2Fhctsa","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benfulcher%2Fhctsa/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benfulcher%2Fhctsa/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/benfulcher%2Fhctsa/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/benfulcher","download_url":"https://codeload.github.com/benfulcher/hctsa/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248760207,"owners_count":21157309,"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":["feature-extraction","matlab","time-series","time-series-analysis"],"created_at":"2024-08-01T07:00:21.218Z","updated_at":"2025-04-13T18:30:41.781Z","avatar_url":"https://github.com/benfulcher.png","language":"MATLAB","funding_links":[],"categories":["Libraries","📦 Packages"],"sub_categories":["MATLAB"],"readme":"\u003cp align=\"center\"\u003e\u003cimg src=\"img/hctsa_logo_banner.png\" alt=\"hctsa logo\" height=\"180\"/\u003e\u003c/p\u003e\n\n\u003ch1 align=\"center\"\u003e\u003cem\u003ehctsa\u003c/em\u003e\u003c/h1\u003e\n\n\u003cp align=\"center\"\u003e\n \t\u003ca href=\"https://zenodo.org/badge/latestdoi/10790340\"\u003e\u003cimg src=\"https://zenodo.org/badge/10790340.svg\" height=\"20\"/\u003e\u003c/a\u003e\n \t\u003ca href=\"https://twitter.com/compTimeSeries\"\u003e\u003cimg src=\"https://img.shields.io/twitter/url/https/twitter.com/compTimeSeries.svg?style=social\u0026label=Follow%20%40compTimeSeries\" height=\"20\"/\u003e\u003c/a\u003e\n    \u003ca href=\"https://creativecommons.org/licenses/by-nc-sa/4.0/\"\u003e\u003cimg src=\"https://img.shields.io/badge/License-CC_BY--NC--SA_4.0-lightgrey.svg\" height=\"20\"/\u003e\u003c/a\u003e\n    \u003ca href=\"https://www.gnu.org/licenses/gpl-3.0\"\u003e\u003cimg src=\"https://img.shields.io/badge/License-GPLv3-blue.svg\" height=\"20\"/\u003e\u003c/a\u003e\n\u003c/p\u003e\n\n_hctsa_ is a Matlab software package for running highly comparative time-series analysis.\nIt extracts thousands of time-series features from a collection of univariate time series and includes a range of tools for visualizing and analyzing the resulting time-series feature matrix, including:\n\n1. Normalizing and clustering time-series data;\n2. Producing low-dimensional representations of time-series data;\n3. Identifying and interpreting discriminating features between different classes of time series; and\n4. Fitting and evaluating multivariate classification models.\n\n__Feel free to [email me](mailto:ben.d.fulcher@gmail.com) for advice on applications__ of _hctsa_ :nerd_face:\n\n## Installation :arrow_down:\n\nFor users _familiar with git_ (recommended), please [make a fork](https://help.github.com/articles/fork-a-repo/) of the repo and then clone it to your local machine.\nTo update, after setting an upstream remote (`git remote add upstream git://github.com/benfulcher/hctsa.git`) you can use `git pull upstream main`.\nTo obtain the latest toolboxes (like the optimized _catch22_ faeture set) you should then run `git submodule update --init`.\n\nUsers _unfamiliar with git_ can instead download the repository by clicking the green \"Code\" button then \"Download ZIP\".\n\nOnce downloaded, you can install _hctsa_ by running the `install.m` script (see [docs](https://time-series-features.gitbook.io/hctsa-manual/) for details).\n\n\u003c!-- We recommend working outside of the repository so that incremental updates can be pulled from the upstream repository. --\u003e\n\n## Documentation \u0026#x1F4D6;\n\n__Comprehensive documentation__ for _hctsa_, from getting started through to more advanced analyses is on [GitBook](https://time-series-features.gitbook.io/hctsa-manual/).\n\nThere is also alot of additional information in these docs, including:\n\n- :point_right: Information about alternative feature sets (including the much faster [catch22](https://github.com/DynamicsAndNeuralSystems/catch22)), and information about other time-series packages available in R, python, and Julia.\n- :wavy_dash: The accompanying time-series data archive for this project, [_CompEngine_](http://www.comp-engine.org).\n- :floppy_disk: Downloadable _hctsa_ feature matrices from time-series datasets with example workflows.\n- :computer: Resources for [distributing an _hctsa_ computation](https://github.com/benfulcher/distributed_hctsa) on a computing cluster.\n- :closed_book: A list of publications that have used _hctsa_ to address different research questions.\n- :information_desk_person: Frequently asked questions about _hctsa_ and related feature-based time-series analyses.\n\n## Acknowledgement :+1:\n\nIf you use this software, please read and cite these open-access articles:\n\n- \u0026#x1F4D7; B.D. Fulcher and N.S. Jones. [_hctsa_: A computational framework for automated time-series phenotyping using massive feature extraction](http://www.cell.com/cell-systems/fulltext/S2405-4712\\(17\\)30438-6). _Cell Systems_: __5__, 527 (2017).\n- \u0026#x1F4D7; B.D. Fulcher, M.A. Little, N.S. Jones. [Highly comparative time-series analysis: the empirical structure of time series and their methods](http://rsif.royalsocietypublishing.org/content/10/83/20130048.full). _J. Roy. Soc. Interface_: __10__, 83 (2013).\n\nFeedback, as [email](mailto:ben.d.fulcher@gmail.com), [GitHub issues](https://github.com/benfulcher/hctsa/issues) or [pull requests](https://help.github.com/articles/using-pull-requests/), is much appreciated.\n\n__For commercial use of _hctsa_, including licensing and consulting, contact [Engine Analytics](http://www.engineanalytics.org/).__\n\n## Licenses\n\n### Internal licenses\n\nThere are two licenses applied to the core parts of the repository:\n\n1. The framework for running _hctsa_ analyses and visualizations is licensed as the [Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License](http://creativecommons.org/licenses/by-nc-sa/4.0/).\nA license for commercial use is available from [Engine Analytics](http://www.engineanalytics.org/).\n\n2. Code for computing features from time-series data is licensed as [GNU General Public License version 3](http://www.gnu.org/licenses/gpl-3.0.en.html).\n\nA range of external code packages are provided in the `Toolboxes` directory of the repository, and each have their own associated license (as outlined below).\n\n### External packages and dependencies\n\nMany features in _hctsa_ rely on external packages and Matlab toolboxes.\nIn the case that some of them are unavailable, _hctsa_ can still be used, but only a reduced set of time-series features will be computed.\n\n_hctsa_ uses the following [Matlab Add-On Toolboxes](https://au.mathworks.com/products.html): Statistics and Machine Learning, Signal Processing, Curve Fitting, System Identification, Wavelet, and Econometrics.\n\nThe following external time-series analysis code packages are provided with the software (in the `Toolboxes` directory), and are used by our main feature-extraction algorithms to compute meaningful structural features from time series:\n\n- [_TISEAN_ package for nonlinear time-series analysis, version 3.0.1](http://www.mpipks-dresden.mpg.de/~tisean/Tisean_3.0.1/index.html) (GPL license).\n- [_TSTOOL_ package for nonlinear time-series analysis, version 1.2](http://www.dpi.physik.uni-goettingen.de/tstool/) (GPL license).\n- Joseph T. Lizier's [Java Information Dynamics Toolkit (JIDT)](https://github.com/jlizier/jidt) for studying information-theoretic measures of computation in complex systems, version 1.3 (GPL license).\n- Time-series analysis code developed by [Michael Small](http://staffhome.ecm.uwa.edu.au/~00027830/code.html) (unlicensed).\n- Max Little's [Time-series analysis code](http://www.maxlittle.net/software/index.php) (GPL license).\n- Sample Entropy code from [Physionet](https://archive.physionet.org/faq.shtml#license) (GPL license).\n- [_ARFIT_ Toolbox for AR model estimation](http://climate-dynamics.org/software/#arfit) (unlicensed).\n- [_gpml_ Toolbox for Gaussian Process regression model estimation, version 3.5](http://www.gaussianprocess.org/gpml/code/matlab/doc/) (FreeBSD license).\n- Danilo P. Mandic's [delay vector variance code](http://www.commsp.ee.ic.ac.uk/~mandic/dvv.htm) (GPL license).\n- [Cross Recurrence Plot Toolbox](http://tocsy.pik-potsdam.de/CRPtoolbox/) (GPL license)\n- Zoubin Ghahramani's [Hidden Markov Model (HMM) code](http://mlg.eng.cam.ac.uk/zoubin/software.html) (MIT license).\n- Danny Kaplan's Code for embedding statistics (GPL license).\n- Two-dimensional histogram code from Matlab Central (BSD license).\n- Various histogram and entropy code by Rudy Moddemeijer (unlicensed).\n\n## Acknowledgements :wave:\n\nMany thanks go to [Romesh Abeysuriya](https://github.com/RomeshA) for helping with the mySQL database set-up and install scripts, and [Santi Villalba](https://github.com/sdvillal) for lots of helpful feedback and advice on the software.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenfulcher%2Fhctsa","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fbenfulcher%2Fhctsa","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fbenfulcher%2Fhctsa/lists"}