KBE3D / KBCore / turf / clustersDbscan

函数: clustersDbscan()

clustersDbscan(points: FeatureCollection<Point>, maxDistance: number, options?: { units?: Units; minPoints?: number; mutate?: boolean; }): FeatureCollection<Point, {[name: string]: any; } & { dbscan?: Dbscan; cluster?: number; }>

Function

Takes a set of points and partition them into clusters according to https://en.wikipedia.org/wiki/DBSCAN|DBSCAN's

data clustering algorithm.

参数

points

FeatureCollection<Point>

to be clustered

maxDistance

number

Maximum Distance between any point of the cluster to generate the clusters (kilometers by default, see options)

options?

Optional parameters

units?

Units

in which maxDistance is expressed, Supports all valid Turf Units

minPoints?

number

Minimum number of points to generate a single cluster, points which do not meet this requirement will be classified as an 'edge' or 'noise'.

mutate?

boolean

Allows GeoJSON input to be mutated

返回

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

Clustered Points with an additional two properties associated to each Feature:

• {number} cluster - the associated clusterId
• {string} dbscan - type of point it has been classified as ('core'|'edge'|'noise')

示例

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

//addToMap
var addToMap = [clustered];