org.apache.mahout.clustering.display.DisplaySpectralKMeans.java Source code

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Here is the source code for org.apache.mahout.clustering.display.DisplaySpectralKMeans.java

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/*
 * Licensed to the Apache Software Foundation (ASF) under one or more
 * contributor license agreements.  See the NOTICE file distributed with
 * this work for additional information regarding copyright ownership.
 * The ASF 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
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License 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 org.apache.mahout.clustering.display;

import java.awt.Graphics;
import java.awt.Graphics2D;
import java.io.File;
import java.io.Writer;

import com.google.common.base.Charsets;
import com.google.common.io.Closeables;
import com.google.common.io.Files;
import org.apache.hadoop.conf.Configuration;
import org.apache.hadoop.fs.FileSystem;
import org.apache.hadoop.fs.Path;
import org.apache.hadoop.mapred.JobConf;
import org.apache.mahout.clustering.spectral.kmeans.SpectralKMeansDriver;
import org.apache.mahout.common.HadoopUtil;
import org.apache.mahout.common.RandomUtils;
import org.apache.mahout.common.distance.DistanceMeasure;
import org.apache.mahout.common.distance.ManhattanDistanceMeasure;

public class DisplaySpectralKMeans extends DisplayClustering {

    protected static final String SAMPLES = "samples";
    protected static final String OUTPUT = "output";
    protected static final String TEMP = "tmp";
    protected static final String AFFINITIES = "affinities";

    DisplaySpectralKMeans() {
        initialize();
        setTitle("Spectral k-Means Clusters (>" + (int) (significance * 100) + "% of population)");
    }

    public static void main(String[] args) throws Exception {
        System.out.println("hello");
        DistanceMeasure measure = new ManhattanDistanceMeasure();
        Path samples = new Path(SAMPLES);
        Path output = new Path(OUTPUT);
        Path tempDir = new Path(TEMP);
        Configuration conf = new Configuration();
        conf.set("mapred.job.tracker", "ajila-server-01:54311");
        conf.set("fs.default.name", "hdfs://ajila-server-01:54310");
        HadoopUtil.delete(conf, samples);
        HadoopUtil.delete(conf, output);

        RandomUtils.useTestSeed();
        DisplayClustering.generateSamples();
        writeSampleData(samples);
        Path affinities = new Path(output, AFFINITIES);
        FileSystem fs = FileSystem.get(output.toUri(), conf);
        if (!fs.exists(output)) {
            fs.mkdirs(output);
        }
        Writer writer = null;
        try {
            writer = Files.newWriter(new File(affinities.toString()), Charsets.UTF_8);
            for (int i = 0; i < SAMPLE_DATA.size(); i++) {
                for (int j = 0; j < SAMPLE_DATA.size(); j++) {
                    writer.write(i + "," + j + ','
                            + measure.distance(SAMPLE_DATA.get(i).get(), SAMPLE_DATA.get(j).get()) + '\n');
                }
            }
        } finally {
            Closeables.close(writer, false);
        }
        int maxIter = 10;
        double convergenceDelta = 0.001;
        SpectralKMeansDriver.run(new Configuration(), affinities, output, SAMPLE_DATA.size(), 3, measure,
                convergenceDelta, maxIter, tempDir, false);
        new DisplaySpectralKMeans();
    }

    @Override
    public void paint(Graphics g) {
        plotClusteredSampleData((Graphics2D) g, new Path(OUTPUT));
    }
}