com.venky.clustering.Clusterer Maven / Gradle / Ivy

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Commonly used programming tasks in java
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package com.venky.clustering;

import java.util.ArrayList;
import java.util.Collection;
import java.util.HashMap;
import java.util.List;
import java.util.Map;

public class Clusterer {
	private Metric metric;
	private CenterFinder centerFinder;

	public Clusterer(CenterFinder cf, Metric m){
		this.metric = m;
		this.centerFinder = cf;
	}

	public CenterFinder getCenterFinder(){
		return centerFinder;
	}
	
	public Metric getMetric(){
		return metric;
	}
	
	public List> cluster(Collection points, List centroids){
		List> clusters = new ArrayList>();
		for (T centroid: centroids){
			Cluster init = new Cluster(this);
			init.addPoint(centroid);
			clusters.add(init);
		}
		
		for (T p : points){
			int closestCentroidIndex = -1;
			double distanceToClosestCentroid = Double.POSITIVE_INFINITY;
			
			for (int i = 0; i < centroids.size() ; i ++ ){
				double distanceToCentroid = metric.distance(centroids.get(i),p);
				if (distanceToClosestCentroid > distanceToCentroid){
					distanceToClosestCentroid = distanceToCentroid; 
					closestCentroidIndex = i ;
				}
			}
			if (closestCentroidIndex >= 0 ){
				clusters.get(closestCentroidIndex).addPoint(p);
			}
		}
		return clusters;
	}
	
	public List> cluster(Collection points, int maxClusters){
		return cluster(points,new MaxClustersCreated(maxClusters)); 
	}
	
	public List> cluster(Collection points,StopCriteria stopCritieria){
		List> clusters = new ArrayList>();
		for (T point: points){
			Cluster init = new Cluster(this);
			init.addPoint(point);
			clusters.add(init);
		}
		
		Map,Map,Double>> distances = new HashMap, Map,Double>>();
		while (!stopCritieria.canStop(clusters)){

			int indexGrown = 0; 
			int indexDestroyed = 0; 
			double minDistance = Double.POSITIVE_INFINITY;
			for (int i = 0 ; i < clusters.size() ; i ++ ){
				Cluster inspected = clusters.get(i);
				Map,Double> inspectedDistances = distances.get(inspected);
				if (inspectedDistances == null){ 
					inspectedDistances = new HashMap, Double>();
					distances.put(inspected, inspectedDistances);
				}
				for (int j = i +1 ; j < clusters.size() ; j ++){
					Cluster other = clusters.get(j);
					Double distance = inspectedDistances.get(other); 
					if (distance == null){
						if (centerFinder != null){
							distance = inspected.centroidDistance(other);
						}else {
							distance = inspected.distance(other).getMaxDistance();
						}
						inspectedDistances.put(other, distance);
					}
					
					if (minDistance >  distance){
						minDistance = distance;
						indexGrown = i ;
						indexDestroyed = j ;
					}
				}
			}
			
			Cluster clusterGrown = clusters.get(indexGrown);
			Cluster clusterDestroyed = clusters.remove(indexDestroyed); //Note index Destroyed >= indexGrown.
			for (T p : clusterDestroyed.getPoints()){
				clusterGrown.addPoint(p);
			}
			distances.remove(clusterGrown);
			for (Cluster remaining: distances.keySet()){
				distances.get(remaining).remove(clusterGrown);
			}

		}
		return clusters;
	}
}