{"id":30219120,"url":"https://github.com/andrei-ng/minmaxlttb-rs","last_synced_at":"2025-08-14T07:47:51.744Z","repository":{"id":309432499,"uuid":"1036275961","full_name":"andrei-ng/minmaxlttb-rs","owner":"andrei-ng","description":"MinMaxLTTB and clasical LTTB algorithms for downsampling of timeseries for visualization","archived":false,"fork":false,"pushed_at":"2025-08-11T21:05:02.000Z","size":70,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":0,"default_branch":"main","last_synced_at":"2025-08-11T22:18:54.463Z","etag":null,"topics":["downsampling","lttb","plotly-rs","plotting","visualization"],"latest_commit_sha":null,"homepage":"","language":"Rust","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/andrei-ng.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,"zenodo":null}},"created_at":"2025-08-11T20:37:14.000Z","updated_at":"2025-08-11T21:05:05.000Z","dependencies_parsed_at":"2025-08-11T22:18:58.234Z","dependency_job_id":"2014f27e-1184-4a5f-8f22-0d99c591a104","html_url":"https://github.com/andrei-ng/minmaxlttb-rs","commit_stats":null,"previous_names":["andrei-ng/minmaxlttb-rs"],"tags_count":null,"template":false,"template_full_name":null,"purl":"pkg:github/andrei-ng/minmaxlttb-rs","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrei-ng%2Fminmaxlttb-rs","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrei-ng%2Fminmaxlttb-rs/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrei-ng%2Fminmaxlttb-rs/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrei-ng%2Fminmaxlttb-rs/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/andrei-ng","download_url":"https://codeload.github.com/andrei-ng/minmaxlttb-rs/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/andrei-ng%2Fminmaxlttb-rs/sbom","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":270385318,"owners_count":24574544,"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":"2025-08-14T02:00:10.309Z","response_time":75,"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":["downsampling","lttb","plotly-rs","plotting","visualization"],"created_at":"2025-08-14T07:47:48.872Z","updated_at":"2025-08-14T07:47:51.715Z","avatar_url":"https://github.com/andrei-ng.png","language":"Rust","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MinMaxLTTB\n\nA Rust crate for downsampling timeseries data using the LTTB (Largest Triangle Three Buckets) and MinMaxLTTB algorithms.\n\nThe standard LTTB algorithm is implemented as described in the original paper [Downsampling Time Series for Visual Representation](https://skemman.is/bitstream/1946/15343/3/SS_MSthesis.pdf). \nThe MinMaxLTTB algorithm follows [MinMaxLTTB: Leveraging MinMax-Preselection to Scale LTTB](https://arxiv.org/abs/2305.00332).\n\nThe crate draws inspiration from other implementations of LTTB and its variants \n - https://github.com/jeromefroe/lttb-rs\n - https://github.com/predict-idlab/MinMaxLTTB\n - https://github.com/cpbotha/lttb-bench/\n\n## Variants\n\n- **Standard LTTB**: Classic implementation of LTTB downsampling\n- **MinMax LTTB**: MinMax variant that better preserves local minima and maxima\n\n## Usage\n\nAdd to your `Cargo.toml`:\n\n```toml\n[dependencies]\nminmaxlttb = \"0.1.0\"\n```\n\n```rust\nuse minmaxlttb::{Point, LttbBuilder, LttbMethod};\n\n// Simple usage with convenience functions\nlet points = vec![Point::new(0.0, 1.0), Point::new(1.0, 2.0), Point::new(2.0, 3.0)];\nlet downsampled = minmaxlttb::lttb(\u0026points, 2);\n\n// Advanced usage with builder pattern\nlet lttb = LttbBuilder::new()\n    .threshold(2)\n    .method(LttbMethod::MinMax)\n    .ratio(3)\n    .build();\n\nlet result = lttb.downsample(\u0026points);\n```\n\n## Examples\n\nCheck the `examples` directory for a few examples that generate plots using the `plotly-rs` crate and are rendered in your system's default browser:\n - power: example of downsampling a real-world power consumption dataset with MinMaxLTTB\n - timeseries: example of downsampling a synthetic dataset with standard LTTB\n - minmax_vs_standard: comparison of LTTB and MinMaxLTTB downsampling\n - lttb_analysis: a visual analysis of the point selections and bucket/partition division for the MinMaxLTTB algorithm\n\n## License\n\nMIT ","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrei-ng%2Fminmaxlttb-rs","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fandrei-ng%2Fminmaxlttb-rs","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fandrei-ng%2Fminmaxlttb-rs/lists"}