clustersDbscan
描述
¥Description
Takes a set of points and partition them into clusters according to DBSCAN 算法 data clustering algorithm.
¥Takes a set of points and partition them into clusters according to DBSCAN's data clustering algorithm.
参数
¥Parameters
名称 | 类型 | 描述 |
---|---|---|
points | FeatureCollection<点> | 待聚类 |
maxDistance | number | Maximum Distance between any point of the cluster to generate the clusters (kilometers by default, see options) |
options? | 对象 | 可选参数(默认 ) |
options.units? | string | in which maxDistance is expressed, can be degrees, radians, miles, or kilometers (default "kilometers") |
options.mutate? | boolean | Allows GeoJSON input to be mutated (default false) |
options.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'.(默认 3) |
返回
¥Returns
FeatureCollection<点, DbscanProps> Clustered Points with an additional two properties associated to each Feature:
¥FeatureCollection<Point, DbscanProps> 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
¥Examples
// 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);
安装
¥Installation
$ npm install @turf/clusters-dbscan
import { clustersDbscan } from "@turf/clusters-dbscan";
const result = clustersDbscan(...);
$ npm install @turf/turf
import * as turf from "@turf/turf";
const result = turf.clustersDbscan(...);