com.cloudera.oryx.kmeans.computation.covariance.DistanceData.java Source code

Introduction

Here is the source code for com.cloudera.oryx.kmeans.computation.covariance.DistanceData.java

Source

/*
 * 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.computation.covariance;

import com.cloudera.oryx.common.iterator.FileLineIterable;
import com.cloudera.oryx.common.servcomp.Store;
import com.google.common.base.Function;
import com.google.common.collect.Maps;
import org.apache.commons.math3.linear.RealMatrix;
import org.apache.commons.math3.linear.RealVector;

import java.io.IOException;
import java.io.Serializable;
import java.util.Map;

public final class DistanceData implements Serializable {

    private final RealVector means;
    private final RealMatrix covInv;

    public static Map<ClusterKey, DistanceData> load(String prefix, int n) throws IOException {
        Map<ClusterKey, CovarianceDataBuilder> db = Maps.newHashMap();

        Store store = Store.get();
        for (String file : store.list(prefix, true)) {
            for (String line : new FileLineIterable(store.readFrom(file))) {
                CovarianceData cd = CovarianceData.parse(line);
                ClusterKey key = new ClusterKey(cd.getClusteringId(), cd.getCenterId());
                CovarianceDataBuilder cdb = db.get(key);
                if (cdb == null) {
                    cdb = new CovarianceDataBuilder(n);
                    db.put(key, cdb);
                }
                cdb.update(cd);
            }
        }

        return Maps.transformValues(db, new Function<CovarianceDataBuilder, DistanceData>() {
            @Override
            public DistanceData apply(CovarianceDataBuilder input) {
                return input.getDistanceData();
            }
        });
    }

    public DistanceData(RealVector means) {
        this(means, null);
    }

    public DistanceData(RealVector means, RealMatrix covInv) {
        this.means = means;
        this.covInv = covInv;
    }

    public boolean hasCovariance() {
        return covInv != null;
    }

    public double euclideanDistance(RealVector v) {
        return means.getDistance(v);
    }

    public double mahalanobisDistance(RealVector v) {
        RealVector d = v.subtract(means);
        return d.dotProduct(covInv.operate(d));
    }
}