KBE3D / KBCore / turf / clustersKmeans

函数: clustersKmeans()

clustersKmeans(points: FeatureCollection<Point>, options?: { numberOfClusters?: number; mutate?: boolean; }): FeatureCollection<Point, {[name: string]: any; } & { cluster?: number; centroid?: [number, number]; }>

Function

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

参数

points

FeatureCollection<Point>

to be clustered

options?

Optional parameters

numberOfClusters?

number

numberOfClusters that will be generated

mutate?

boolean

allows GeoJSON input to be mutated (significant performance increase if true)

返回

FeatureCollection<Point, {[name: string]: any; } & { cluster?: number; centroid?: [number, number]; }>

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]

示例

// 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];