@turf/clusters-kmeans

clustersKmeans

Takes a set of [points][1] and partition them into clusters using the k-mean .
It uses the [k-means algorithm][2]

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* points [FeatureCollection][3]<[Point][1]> to be clustered
* options [Object][4] Optional parameters (optional, default {})

* options.numberOfClusters [number][5] numberOfClusters that will be generated (optional, default Math.sqrt(numberOfPoints/2))
* options.mutate [boolean][6] allows GeoJSON input to be mutated (significant performance increase if true) (optional, default false)

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``javascript
// create random points with random z-values in their properties
var points = turf.randomPoint(100, {bbox: [0, 30, 20, 50]});
var options = {numberOfClusters: 7};
var clustered = turf.clustersKmeans(points, options);

//addToMap
var addToMap = [clustered];
`

Returns [FeatureCollection][3]<[Point][1]> Clustered Points with an additional two properties associated to each Feature:* {number} cluster - the associated clusterId
* {\[number, number]} centroid - Centroid of the cluster \[Longitude, Latitude]

[1]: https://tools.ietf.org/html/rfc7946#section-3.1.2

[2]: https://en.wikipedia.org/wiki/K-means_clustering

[3]: https://tools.ietf.org/html/rfc7946#section-3.3

[4]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Object

[5]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Number

[6]: https://developer.mozilla.org/docs/Web/JavaScript/Reference/Global_Objects/Boolean

---

This module is part of the Turfjs project, an open source module collection dedicated to geographic algorithms. It is maintained in the Turfjs/turf repository, where you can create PRs and issues.

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Install this single module individually:

`sh
$ npm install @turf/clusters-kmeans
`

Or install the all-encompassing @turf/turf module that includes all modules as functions:

`sh
$ npm install @turf/turf
``