{"id":32390787,"url":"https://github.com/e-/optics.js","last_synced_at":"2026-02-25T14:33:21.859Z","repository":{"id":13473943,"uuid":"16164007","full_name":"e-/optics.js","owner":"e-","description":"OPTICS density based clustering algorithm written in javascript","archived":false,"fork":false,"pushed_at":"2014-01-23T09:35:53.000Z","size":164,"stargazers_count":2,"open_issues_count":0,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2023-03-13T05:31:11.646Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":null,"has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":"deeplearning4j/deeplearning4j","license":"bsd-2-clause","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/e-.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}},"created_at":"2014-01-23T06:09:51.000Z","updated_at":"2020-06-30T14:18:37.000Z","dependencies_parsed_at":"2022-09-10T14:10:49.445Z","dependency_job_id":null,"html_url":"https://github.com/e-/optics.js","commit_stats":null,"previous_names":[],"tags_count":0,"template":null,"template_full_name":null,"purl":"pkg:github/e-/optics.js","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/e-%2Foptics.js","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/e-%2Foptics.js/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/e-%2Foptics.js/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/e-%2Foptics.js/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/e-","download_url":"https://codeload.github.com/e-/optics.js/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/e-%2Foptics.js/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":280906445,"owners_count":26411413,"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","status":"online","status_checked_at":"2025-10-25T02:00:06.499Z","response_time":81,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"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":[],"created_at":"2025-10-25T04:51:30.270Z","updated_at":"2025-10-25T04:52:24.039Z","avatar_url":"https://github.com/e-.png","language":null,"funding_links":[],"categories":[],"sub_categories":[],"readme":"# optics.js\n\noptics.js is an open source JavaScript library which implements OPTICS clustering algorithm for *browsers* and *node.js*. For more detailed information about OPTICS clustering algorithm , refer to the below paper.\n\u003e Ankerst, Mihael, et al. \"OPTICS: ordering points to identify the clustering structure.\" ACM SIGMOD Record 28.2 (1999): 49-60.\n\n## Demo\n[Demo](http://e-.github.io/optics.js/demo/)\n\n## Usage\n`optics(data, minPts, epsilon, getter, dist)` returns an array of class `Point`.\n  \n* `data`: An array of data to be clustered.\n* `minPts`: Defined in the forementioned paper.\n* `epsilon` Defined in the forementioned paper.\n* `getter`: *Optional.* If `data` contains other data structures (e.g. Object) rather than vectors (an array of numbers), you should specify how to get a vector from each element of `data`. The default value is an identity function (e.g. `function(d){return d;}`) which means each element of `data` is used as a vector.\n* `dist`: *Optional.* A distance function which computes the distance between two vectors. If not specified, the Euclidan distance function is used.\n\nClass `Point` contains the result of OPTICS clustering for one element of `data`\n\n* `point.datum` \n* `point.isProcessed` \n* `point.coreDistance` \n* `point.reachability` \n* `point.index` \n   \n## LICENSE\n\u0026copy; 2014, Jaemin Jo. Released under BSD license.\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fe-%2Foptics.js","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fe-%2Foptics.js","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fe-%2Foptics.js/lists"}