This method adds a list of data points to the list of objects for clustering.

Note that to ensure optimal performance, it is best to invoke the method nokia.maps.clustering.ClusterProvider#cluster after all the data have been added. Otherwise, as in database systems, addition of new data points means that indices may have to be modified, which incurs a performance penalty.

This method starts the clustering process. Note that the process is asynchronous, therefore to receive notification of its completion, you need to attach an observer to the instance of this class, using the method nokia.maps.util.OObject#addObserver. The observer function must be triggered when the ClusterProvider state changes to nokia.maps.clustering.ClusterProvider.STATE_CLUSTERED.

 var ClusterProvider = nokia.maps.clustering.ClusterProvider; 
 clusterProvider = new ClusterProvider(map, {
	  dataPoints: [PASS YOUR DATA POINTS HERE]
 });
 clusterProvider.addObserver("state", function (obj, key, state, oldValue) {
	  if (state == ClusterProvider.STATE_CLUSTERED) {
		  console.log("Clustering is done!");
	  }
 });
 clusterProvider.cluster();

This method sets a new epsilon value (in pixels), which represents the area within which data points are considered for clustering. Depending from the clustering algorithm used, area might be a circle with epsilon radius, or a minimum bounding rectangle of that circle. (DBSCAN algorithm with RTree based index)

Note that clusters should be recalculated when the epsilon value changes. Please call the method nokia.maps.clustering.ClusterProvider#cluster explicitly to force a recalculation.

Note that clusters should be recalculated whenever this method has been called. Please call the method nokia.maps.clustering.ClusterProvider#cluster explicitly to force a recalculation.