{"id":19109467,"url":"https://github.com/boniolp/graphit","last_synced_at":"2025-09-15T18:25:42.631Z","repository":{"id":226227043,"uuid":"768106252","full_name":"boniolp/graphit","owner":"boniolp","description":"Graph-based Time Series Clustering Visualisation Tools","archived":false,"fork":false,"pushed_at":"2025-05-11T17:13:39.000Z","size":6033,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":3,"default_branch":"main","last_synced_at":"2025-06-05T04:39:34.067Z","etag":null,"topics":["clustering","graph","graph-analysis","graph-embedding","interpretability","python","python3","streamlit","time-series","time-series-analysis","time-series-clustering","visualization"],"latest_commit_sha":null,"homepage":"https://graphint.streamlit.app/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/boniolp.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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":"2024-03-06T13:34:48.000Z","updated_at":"2025-05-11T17:13:42.000Z","dependencies_parsed_at":"2025-01-03T03:42:02.449Z","dependency_job_id":"ff830c65-49de-49b8-9456-3fe926d3d519","html_url":"https://github.com/boniolp/graphit","commit_stats":null,"previous_names":["boniolp/graphit","boniolp/graphint"],"tags_count":0,"template":false,"template_full_name":"streamlit/streamlit-hello","purl":"pkg:github/boniolp/graphit","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/boniolp%2Fgraphit","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/boniolp%2Fgraphit/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/boniolp%2Fgraphit/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/boniolp%2Fgraphit/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/boniolp","download_url":"https://codeload.github.com/boniolp/graphit/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/boniolp%2Fgraphit/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":260562518,"owners_count":23028397,"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":["clustering","graph","graph-analysis","graph-embedding","interpretability","python","python3","streamlit","time-series","time-series-analysis","time-series-clustering","visualization"],"created_at":"2024-11-09T04:20:59.907Z","updated_at":"2025-09-15T18:25:42.616Z","avatar_url":"https://github.com/boniolp.png","language":"Python","readme":"\u003cp align=\"center\"\u003e\n\u003cimg width=\"230\" src=\"./figures/graphit_logo.png\"/\u003e\n\u003c/p\u003e\n\n\u003ch1 align=\"center\"\u003eGraphint\u003c/h1\u003e\n\u003ch2 align=\"center\"\u003eGraph-based Time Series Clustering Visualisation Tools\u003c/h2\u003e\n\n\u003cdiv align=\"center\"\u003e\n\u003cp\u003e\n\u003cimg alt=\"GitHub\" src=\"https://img.shields.io/github/license/boniolp/graphit\"\u003e \u003cimg alt=\"GitHub issues\" src=\"https://img.shields.io/github/issues/boniolp/graphit\"\u003e\n\u003c/p\u003e\n\u003c/div\u003e\n\n\u003cp align=\"center\"\u003e\u003ca href=\"https://graphit.streamlit.app/\"\u003eTry our demo\u003c/a\u003e\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n\u003cimg width=\"400\" src=\"./figures/demo_graphit.gif\"/\u003e\n\u003c/p\u003e\n\nGraphint is a Python-based web interactive tool to interpet and\ncompare time series clustering on several datasets of the [UCR-Archive](https://www.cs.ucr.edu/%7Eeamonn/time_series_data_2018/).\nIt is based on a novel graph-based time series clustering, called $k$-Graph.\n$k$-Graph is divided into three steps: (i) Graph embedding, (ii) Graph clustering, \nand (iii) Consensus Clustering.  Moreover, we provide a way to select the most interpretable \ngraph for the resulting clustering partition and allow the user to visualize the subsequences \ncontained in the most representative and exclusive nodes. Graphit allows the user the interact with\nthe graphs and identifies the important subsequences that helps creating the clusters. You may find more information [here](https://github.com/boniolp/kGraph).\n\n\n## Contributors\n\n* [Paul Boniol](https://boniolp.github.io/), Inria, ENS, PSL University, CNRS\n* [Donato Tiano](https://liris.cnrs.fr/en/member-page/donato-tiano), Università degli Studi di Modena e Reggio Emilia\n* [Angela Bonifati](https://perso.liris.cnrs.fr/angela.bonifati/), Lyon 1 University, IUF, Liris CNRS\n* [Themis Palpanas](https://helios2.mi.parisdescartes.fr/~themisp/), Université Paris Cité, IUF\n\n## Usage\n\n**Step 1:** Clone this repository using `git` and change into its root directory.\n\n```(bash)\ngit clone https://github.com/boniolp/graphit.git\ncd dsymb-playground/\n```\n\n**Step 2:** Create and activate a `conda` environment and install the dependencies.\n\n```(bash)\nconda create -n graphit python=3.9\nconda activate graphit\npip install -r requirements.txt\n```\n\n**Step 3:** install Graphviz and pyGraphviz: \n\n* For Mac:\n\n```(bash) \nbrew install graphviz\n```\n\n* For Linux (Ubuntu):\n\n```(bash) \nsudo apt install graphviz\n```\n\n* For Windows:\n\nStable Windows install packages are listed [here](https://graphviz.org/download/)\n\nOnce Graphviz is installed, you can install pygraphviz as follows:\n\n```(bash) \npip install pygraphviz\n```\n\n**Step 4:** You can use our tool in two different ways: \n\n- Access online: https://graphit.streamlit.app/\n- Run locally (preferable for faster interaction). To do so, run the following command:\n\n```(bash)\nstreamlit run Hello.py\n```\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fboniolp%2Fgraphit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fboniolp%2Fgraphit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fboniolp%2Fgraphit/lists"}