com.cloudera.oryx.kmeans.common.LloydsUpdateStrategy.java Source code

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Here is the source code for com.cloudera.oryx.kmeans.common.LloydsUpdateStrategy.java

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/*
 * Copyright (c) 2013, Cloudera, Inc. All Rights Reserved.
 *
 * Cloudera, Inc. licenses this file to you under the Apache License,
 * Version 2.0 (the "License"). You may not use this file except in
 * compliance with the License. You may obtain a copy of the License at
 *
 *     http://www.apache.org/licenses/LICENSE-2.0
 *
 * This software is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR
 * CONDITIONS OF ANY KIND, either express or implied. See the License for
 * the specific language governing permissions and limitations under the
 * License.
 */

package com.cloudera.oryx.kmeans.common;

import java.util.List;
import java.util.Map;

import org.apache.commons.math3.linear.RealVector;

import com.google.common.collect.Lists;
import com.google.common.collect.Maps;

public final class LloydsUpdateStrategy implements KMeansUpdateStrategy {

    private final int numIterations;

    public LloydsUpdateStrategy(int numIterations) {
        this.numIterations = numIterations;
    }

    @Override
    public <W extends Weighted<RealVector>> Centers update(List<W> points, Centers centers) {
        for (int iter = 0; iter < numIterations; iter++) {
            Map<Integer, List<W>> assignments = Maps.newHashMap();
            for (int i = 0; i < centers.size(); i++) {
                assignments.put(i, Lists.<W>newArrayList());
            }
            for (W weightedVec : points) {
                assignments.get(centers.getDistance(weightedVec.thing()).getClosestCenterId()).add(weightedVec);
            }
            List<RealVector> centroids = Lists.newArrayList();
            for (Map.Entry<Integer, List<W>> e : assignments.entrySet()) {
                if (e.getValue().isEmpty()) {
                    centroids.add(centers.get(e.getKey())); // fix the no-op center
                } else {
                    centroids.add(centroid(e.getValue()));
                }
            }
            centers = new Centers(centroids);
        }
        return centers;
    }

    /**
     * Compute the {@code Vector} that is the centroid of the given weighted points.
     * 
     * @param points The weighted points
     * @return The centroid of the weighted points
     */
    public static <W extends Weighted<RealVector>> RealVector centroid(Iterable<W> points) {
        RealVector center = null;
        double sz = 0.0;
        for (W v : points) {
            RealVector weighted = v.thing().mapMultiply(v.weight());
            if (center == null) {
                center = weighted;
            } else {
                center = center.add(weighted);
            }
            sz += v.weight();
        }
        return center.mapDivide(sz);
    }
}