Example usage for org.apache.commons.math.stat.clustering KMeansPlusPlusClusterer cluster

Introduction

In this page you can find the example usage for org.apache.commons.math.stat.clustering KMeansPlusPlusClusterer cluster.

Prototype

public List<Cluster<T>> cluster(final Collection<T> points, final int k, final int maxIterations) 

Source Link

Document

Runs the K-means++ clustering algorithm.

Usage

From source file:org.mart.crs.management.tempo.TempoExtractor.java

protected void extractTempo() {
    List<EuclideanFloatPoint> pointList = new ArrayList<EuclideanFloatPoint>();
    for (BeatSegment beatSegment : beatStructure.getBeatSegments()) {
        pointList.add(new EuclideanFloatPoint(new double[] { beatSegment.getDuration() }));
    }/*from  w  ww .  j  a va 2s  . com*/

    KMeansPlusPlusClusterer clusterer = new KMeansPlusPlusClusterer(new Random(2039091238l));
    List<Cluster<EuclideanFloatPoint>> cluster = clusterer.cluster(pointList, numberOfCluster, 100);

    int maxIndex = 0;
    int maxNumberOfPoints = 0;
    for (int i = 0; i < numberOfCluster; i++) {
        int numberOfPoints = cluster.get(i).getPoints().size();
        if (numberOfPoints > maxNumberOfPoints) {
            maxIndex = i;
            maxNumberOfPoints = numberOfPoints;
        }
    }

    float beatLength = (float) cluster.get(maxIndex).getCenter().getPoint()[0];
    this.tempo = 60 / beatLength;

}

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From source file:playground.christoph.evacuation.analysis.EvacuationTimeClusterer.java

Map<BasicLocation, List<Double>> buildCluster(int numClusters, int iterations) {

    createCostMap();/*from w  w w.  j  a  v a  2  s  . c  o  m*/

    KMeansPlusPlusClusterer<ClusterableLocation> clusterer = new KMeansPlusPlusClusterer<ClusterableLocation>(
            MatsimRandom.getLocalInstance());

    List<ClusterableLocation> points = getClusterableLocations();

    buildQuadTree(points);

    log.info("do clustering...");
    List<Cluster<ClusterableLocation>> list = clusterer.cluster(points, numClusters, iterations);

    Map<BasicLocation, List<Double>> map = new HashMap<BasicLocation, List<Double>>();

    for (Cluster<ClusterableLocation> cluster : list) {
        BasicLocation center = cluster.getCenter().getBasicLocation();

        List<Double> evacuationTimes = new ArrayList<Double>();
        for (ClusterableLocation location : cluster.getPoints()) {
            List<Double> pointTravelTimes = locationMap.get(location.getBasicLocation());
            evacuationTimes.addAll(pointTravelTimes);
        }

        map.put(center, evacuationTimes);
    }

    log.info("done.");

    return map;
}

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