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Schmidt","url":"https://thi.ng"},"license":"Apache-2.0","homepage":"https://thi.ng/k-means","keywords":["centroid","cluster","distance","eucledian","haversine","k-means","k-means++","k-medians","mean","median","nd","partition","self-organizing","typescript"],"repository":{"type":"git","url":"git+https://codeberg.org/thi.ng/umbrella.git","directory":"packages/k-means"},"description":"k-means & k-medians with customizable distance functions and centroid initializations for n-D vectors","maintainers":[{"name":"thi.ng","email":"k+npm@thi.ng"}],"readme":"<!-- This file is generated - DO NOT EDIT! -->\n<!-- Please see: https://codeberg.org/thi.ng/umbrella/src/branch/develop/CONTRIBUTING.md#changes-to-readme-files -->\n# ![@thi.ng/k-means](https://codeberg.org/thi.ng/umbrella/media/branch/develop/assets/banners/thing-k-means.svg?d8d57f39)\n\n[![npm version](https://img.shields.io/npm/v/@thi.ng/k-means.svg)](https://www.npmjs.com/package/@thi.ng/k-means)\n![npm downloads](https://img.shields.io/npm/dm/@thi.ng/k-means.svg)\n[![Mastodon Follow](https://img.shields.io/mastodon/follow/109331703950160316?domain=https%3A%2F%2Fmastodon.thi.ng&style=social)](https://mastodon.thi.ng/@toxi)\n\n> [!NOTE]\n\n> This is one of 217 standalone projects. LLM-free, human-made and\n> cared for software, maintained as part of the\n> [@thi.ng/umbrella](https://codeberg.org/thi.ng/umbrella/) ecosystem and\n> anti-framework.\n>\n> 🚀 Please help me to work full-time on these projects by [sponsoring\n> me](https://codeberg.org/thi.ng/umbrella/src/branch/develop/CONTRIBUTING.md#donations).\n> Thank you! ❤️\n\n- [About](#about)\n- [Status](#status)\n- [Installation](#installation)\n- [Dependencies](#dependencies)\n- [Usage examples](#usage-examples)\n- [API](#api)\n- [Authors](#authors)\n- [License](#license)\n\n## About\n\nk-means & k-medians with customizable distance functions and centroid initializations for n-D vectors.\n\nIn addition to the main\n[`kmeans()`](https://docs.thi.ng/umbrella/k-means/functions/kmeans.html)\nimplementation, the following k-means centroid initialization functions are\nprovided (can also be used in isolation to extract cluster centroids):\n\n- [`kmeansPlusPlus()`](https://docs.thi.ng/umbrella/k-means/functions/kmeansPlusPlus.html)\n- [`meanCut()`](https://docs.thi.ng/umbrella/k-means/functions/meanCut.html)\n- [`medianCut()`](https://docs.thi.ng/umbrella/k-means/functions/medianCut.html)\n\n## Status\n\n**BETA** - possibly breaking changes forthcoming\n\n[Search or submit any issues for this package](https://codeberg.org/thi.ng/umbrella/issues?q=%5Bk-means%5D)\n\n## Installation\n\n```bash\nyarn add @thi.ng/k-means\n```\n\nESM import:\n\n```ts\nimport * as kmeans from \"@thi.ng/k-means\";\n```\n\nBrowser ESM import:\n\n```html\n<script type=\"module\" src=\"https://esm.run/@thi.ng/k-means\"></script>\n```\n\n[JSDelivr documentation](https://www.jsdelivr.com/)\n\nFor Node.js REPL:\n\n```js\nconst kmeans = await import(\"@thi.ng/k-means\");\n```\n\nPackage sizes (brotli'd, pre-treeshake): ESM: 1.10 KB\n\n## Dependencies\n\n- [@thi.ng/api](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/api)\n- [@thi.ng/distance](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/distance)\n- [@thi.ng/errors](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/errors)\n- [@thi.ng/random](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/random)\n- [@thi.ng/vectors](https://codeberg.org/thi.ng/umbrella/src/branch/develop/packages/vectors)\n\nNote: @thi.ng/api is in _most_ cases a type-only import (not used at runtime)\n\n## Usage examples\n\nTwo projects in this repo's\n[/examples](https://codeberg.org/thi.ng/umbrella/src/branch/develop/examples)\ndirectory are using this package:\n\n| Screenshot                                                                                                             | Description                                                                 | Live demo                                             | Source                                                                                     |\n|:-----------------------------------------------------------------------------------------------------------------------|:----------------------------------------------------------------------------|:------------------------------------------------------|:-------------------------------------------------------------------------------------------|\n| <img src=\"https://codeberg.org/thi.ng/umbrella/media/branch/develop/assets/examples/dominant-colors.png\" width=\"240\"/> | Color palette generation via dominant color extraction from uploaded images | [Demo](https://demo.thi.ng/umbrella/dominant-colors/) | [Source](https://codeberg.org/thi.ng/umbrella/src/branch/develop/examples/dominant-colors) |\n| <img src=\"https://codeberg.org/thi.ng/umbrella/media/branch/develop/assets/examples/kmeans-viz.jpg\" width=\"240\"/>      | k-means clustering visualization                                            | [Demo](https://demo.thi.ng/umbrella/kmeans-viz/)      | [Source](https://codeberg.org/thi.ng/umbrella/src/branch/develop/examples/kmeans-viz)      |\n\n## API\n\n[Generated API docs](https://docs.thi.ng/umbrella/k-means/)\n\nExample usage: Clustering cities by lat/lon location\n\n```ts tangle:export/readme.ts\nimport { HAVERSINE_LATLON } from \"@thi.ng/distance\";\nimport { kmeans, meansLatLon } from \"@thi.ng/k-means\";\n\n// data sourced from:\n// https://github.com/OpenDataFormats/worldcities/blob/master/src/data/cities.json\nconst cities = [\n    { id: \"anchorage\", latlon: [61.21806, -149.90028] },\n    { id: \"berlin\", latlon: [52.52437, 13.41053] },\n    { id: \"boston\", latlon: [42.35843, -71.05977] },\n    { id: \"calgary\", latlon: [51.05011, -114.08529] },\n    { id: \"cape town\", latlon: [-33.92584, 18.42322] },\n    { id: \"detroit\", latlon: [42.33143, -83.04575] },\n    { id: \"harare\", latlon: [-17.82772, 31.05337] },\n    { id: \"london\", latlon: [51.50853, -0.12574] },\n    { id: \"manila\", latlon: [14.6042, 120.9822] },\n    { id: \"nairobi\", latlon: [-1.28333, 36.81667] },\n    { id: \"new york\", latlon: [40.71427, -74.00597] },\n    { id: \"paris\", latlon: [48.85341, 2.3488] },\n    { id: \"philadelphia\", latlon: [39.95233, -75.16379] },\n    { id: \"portland\", latlon: [45.52345, -122.67621] },\n    { id: \"seoul\", latlon: [37.566, 126.9784] },\n    { id: \"shanghai\", latlon: [31.22222, 121.45806] },\n    { id: \"tokyo\", latlon: [35.6895, 139.69171] },\n    { id: \"vancouver\", latlon: [49.24966, -123.11934] },\n    { id: \"vienna\", latlon: [48.20849, 16.37208] },\n    { id: \"windhoek\", latlon: [-22.55941, 17.08323] },\n];\n\n// cluster based on lat/lon\nconst clusters = kmeans(\n    5,\n    cities.map((x) => x.latlon),\n    {\n        // custom centroid calc for geo locations\n        // https://docs.thi.ng/umbrella/k-means/functions/meansLatLon.html\n        strategy: meansLatLon,\n        // custom distance function for geo location (default: DIST_SQ)\n        dist: HAVERSINE_LATLON,\n    }\n);\n\n// print each cluster\nfor (let c of clusters) {\n    console.log(c.items.map((i) => cities[i].id));\n}\n\n// [ 'manila', 'seoul', 'shanghai', 'tokyo' ]\n// [ 'berlin', 'london', 'paris', 'vienna' ]\n// [ 'boston', 'detroit', 'new york', 'philadelphia' ]\n// [ 'cape town', 'harare', 'nairobi', 'windhoek' ]\n// [ 'anchorage', 'calgary', 'portland', 'vancouver' ]\n```\n\n## Authors\n\n- [Karsten Schmidt](https://thi.ng)\n\nIf this project contributes to an academic publication, please cite it as:\n\n```bibtex\n@misc{thing-k-means,\n  title = \"@thi.ng/k-means\",\n  author = \"Karsten Schmidt\",\n  note = \"https://thi.ng/k-means\",\n  year = 2021\n}\n```\n\n## License\n\n&copy; 2021 - 2026 Karsten Schmidt // Apache License 2.0\n","readmeFilename":"README.md"}