001/*
002 * Licensed to the Apache Software Foundation (ASF) under one or more
003 * contributor license agreements.  See the NOTICE file distributed with
004 * this work for additional information regarding copyright ownership.
005 * The ASF licenses this file to You under the Apache License, Version 2.0
006 * (the "License"); you may not use this file except in compliance with
007 * the License.  You may obtain a copy of the License at
008 *
009 *      http://www.apache.org/licenses/LICENSE-2.0
010 *
011 * Unless required by applicable law or agreed to in writing, software
012 * distributed under the License is distributed on an "AS IS" BASIS,
013 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
014 * See the License for the specific language governing permissions and
015 * limitations under the License.
016 */
017
018package org.apache.commons.math4.ml.clustering;
019
020import java.io.Serializable;
021import java.util.ArrayList;
022import java.util.List;
023
024/**
025 * Cluster holding a set of {@link Clusterable} points.
026 * @param <T> the type of points that can be clustered
027 * @since 3.2
028 */
029public class Cluster<T extends Clusterable> implements Serializable {
030
031    /** Serializable version identifier. */
032    private static final long serialVersionUID = -3442297081515880464L;
033
034    /** The points contained in this cluster. */
035    private final List<T> points;
036
037    /**
038     * Build a cluster centered at a specified point.
039     */
040    public Cluster() {
041        points = new ArrayList<>();
042    }
043
044    /**
045     * Add a point to this cluster.
046     * @param point point to add
047     */
048    public void addPoint(final T point) {
049        points.add(point);
050    }
051
052    /**
053     * Get the points contained in the cluster.
054     * @return points contained in the cluster
055     */
056    public List<T> getPoints() {
057        return points;
058    }
059
060    /**
061     * Computes the centroid of the cluster.
062     *
063     * @return the centroid for the cluster, or {@code null} if the
064     * cluster does not contain any points.
065     */
066    public Clusterable centroid() {
067        if (points.isEmpty()) {
068            return null;
069        } else {
070            final int dimension = points.get(0).getPoint().length;
071            final double[] centroid = new double[dimension];
072            for (final T p : points) {
073                final double[] point = p.getPoint();
074                for (int i = 0; i < centroid.length; i++) {
075                    centroid[i] += point[i];
076                }
077            }
078            for (int i = 0; i < centroid.length; i++) {
079                centroid[i] /= points.size();
080            }
081            return new DoublePoint(centroid);
082        }
083    }
084}