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@turf/clusters-kmeans
Advanced tools
@turf/clusters-kmeans is a module from the Turf.js library that provides functionality for clustering geographical points using the K-means algorithm. This is particularly useful for spatial analysis and geographic data visualization.
Basic K-means Clustering
This feature allows you to perform K-means clustering on a set of geographical points. The code sample demonstrates how to cluster six points into two clusters.
const turf = require('@turf/turf');
const points = turf.featureCollection([
turf.point([0, 0]),
turf.point([2, 2]),
turf.point([3, 3]),
turf.point([8, 8]),
turf.point([8, 9]),
turf.point([7, 8])
]);
const clustered = turf.clustersKmeans(points, {numberOfClusters: 2});
console.log(clustered);
Custom Number of Clusters
This feature allows you to specify the number of clusters you want to create. The code sample demonstrates clustering the same six points into three clusters.
const turf = require('@turf/turf');
const points = turf.featureCollection([
turf.point([0, 0]),
turf.point([2, 2]),
turf.point([3, 3]),
turf.point([8, 8]),
turf.point([8, 9]),
turf.point([7, 8])
]);
const clustered = turf.clustersKmeans(points, {numberOfClusters: 3});
console.log(clustered);
Cluster Properties
This feature allows you to retain and inspect the properties of the original points after clustering. The code sample demonstrates how to cluster points and then log the properties of each clustered point.
const turf = require('@turf/turf');
const points = turf.featureCollection([
turf.point([0, 0], {name: 'A'}),
turf.point([2, 2], {name: 'B'}),
turf.point([3, 3], {name: 'C'}),
turf.point([8, 8], {name: 'D'}),
turf.point([8, 9], {name: 'E'}),
turf.point([7, 8], {name: 'F'})
]);
const clustered = turf.clustersKmeans(points, {numberOfClusters: 2});
console.log(clustered.features.map(f => f.properties));
kmeans-js is a simple JavaScript implementation of the K-means clustering algorithm. Unlike @turf/clusters-kmeans, it is not specifically designed for geographical data but can be used for general clustering tasks.
ml-kmeans is a machine learning library for Node.js that provides K-means clustering. It is more general-purpose compared to @turf/clusters-kmeans and can be used for a variety of data types, not just geographical points.
simple-statistics is a JavaScript library that provides a variety of statistical methods, including K-means clustering. It is a more comprehensive library for statistical analysis compared to @turf/clusters-kmeans, which is focused on geographical data.
Takes a set of points and partition them into clusters using the k-mean . It uses the k-means algorithm
Parameters
points
FeatureCollection<Point> to be clusteredoptions
Object Optional parameters (optional, default {}
)
Examples
// 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<Point> Clustered Points with an additional two properties associated to each Feature:- {number} cluster - the associated clusterId
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.
Install this module individually:
$ npm install @turf/clusters-kmeans
Or install the Turf module that includes it as a function:
$ npm install @turf/turf
6.5.0
@turf/points-with-polygon
Add MultiPoint support
(PR https://github.com/Turfjs/turf/pull/2137 - Author @twelch)@turf/dissolve
Complete rewrite of the dissolve module to resolve many bugs
(PR https://github.com/Turfjs/turf/pull/2110 - Author @rowanwins)
@turf/mask
Complete rewrite of the mask module to resolve many bugs
(PR https://github.com/Turfjs/turf/pull/2130 - Author @rowanwins)
@turf/boolean-valid
Add missing dependency to
(PR https://github.com/Turfjs/turf/pull/2094 - Author @rycgar)
@turf/boolean-overlap
Improve clarity
(PR https://github.com/Turfjs/turf/pull/2133 - Author @patrickbrett)FAQs
turf clusters-kmeans module
The npm package @turf/clusters-kmeans receives a total of 406,414 weekly downloads. As such, @turf/clusters-kmeans popularity was classified as popular.
We found that @turf/clusters-kmeans demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 9 open source maintainers collaborating on the project.
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