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@turf/clusters-dbscan

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@turf/clusters-dbscan

turf clusters-dbscan module

  • 7.1.0
  • latest
  • Source
  • npm
  • Socket score

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645K
decreased by-21.37%
Maintainers
9
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What is @turf/clusters-dbscan?

@turf/clusters-dbscan is a module from the Turf.js library that provides functionality for clustering geographical points using the DBSCAN (Density-Based Spatial Clustering of Applications with Noise) algorithm. This is useful for identifying clusters of points in spatial data, which can be applied in various fields such as geographic information systems (GIS), urban planning, and environmental monitoring.

What are @turf/clusters-dbscan's main functionalities?

Cluster Points

This feature allows you to cluster geographical points based on their proximity to each other. The code sample demonstrates how to create a collection of points and then apply the DBSCAN algorithm to identify clusters within a specified distance (0.3 units) and a minimum number of points (2) to form a cluster.

const turf = require('@turf/turf');

const points = turf.featureCollection([
  turf.point([0, 0]),
  turf.point([0.1, 0.1]),
  turf.point([0.2, 0.2]),
  turf.point([10, 10]),
  turf.point([10.1, 10.1])
]);

const clustered = turf.clustersDbscan(points, 0.3, { minPoints: 2 });

console.log(clustered);

Identify Noise Points

This feature helps in identifying noise points, which are points that do not belong to any cluster. The code sample shows how to filter out noise points from the clustered result.

const turf = require('@turf/turf');

const points = turf.featureCollection([
  turf.point([0, 0]),
  turf.point([0.1, 0.1]),
  turf.point([0.2, 0.2]),
  turf.point([10, 10]),
  turf.point([10.1, 10.1])
]);

const clustered = turf.clustersDbscan(points, 0.3, { minPoints: 2 });

const noisePoints = clustered.features.filter(feature => feature.properties.cluster === 'noise');

console.log(noisePoints);

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Package last updated on 09 Aug 2024

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