/*
* 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.flink.examples.java.clustering.util;
import java.io.BufferedWriter;
import java.io.File;
import java.io.FileWriter;
import java.io.IOException;
import java.text.DecimalFormat;
import java.util.Locale;
import java.util.Random;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.examples.java.clustering.KMeans;
/**
* Generates data for the {@link KMeans} example program.
*/
public class KMeansDataGenerator {
static {
Locale.setDefault(Locale.US);
}
private static final String CENTERS_FILE = "centers";
private static final String POINTS_FILE = "points";
private static final long DEFAULT_SEED = 4650285087650871364L;
private static final double DEFAULT_VALUE_RANGE = 100.0;
private static final double RELATIVE_STDDEV = 0.08;
private static final int DIMENSIONALITY = 2;
private static final DecimalFormat FORMAT = new DecimalFormat("#0.00");
private static final char DELIMITER = ' ';
/**
* Main method to generate data for the {@link KMeans} example program.
* <p>
* The generator creates to files:
* <ul>
* <li><code>< output-path >/points</code> for the data points
* <li><code>< output-path >/centers</code> for the cluster centers
* </ul>
*
* @param args
* <ol>
* <li>Int: Number of data points
* <li>Int: Number of cluster centers
* <li><b>Optional</b> String: Output path, default value is {tmp.dir}
* <li><b>Optional</b> Double: Standard deviation of data points
* <li><b>Optional</b> Double: Value range of cluster centers
* <li><b>Optional</b> Long: Random seed
* </ol>
*
* @throws IOException
*/
public static void main(String[] args) throws IOException {
// check parameter count
if (args.length < 2) {
System.out.println("KMeansDataGenerator -points <num> -k <num clusters> [-output <output-path>] [-stddev <relative stddev>] [-range <centroid range>] [-seed <seed>]");
System.exit(1);
}
// parse parameters
final ParameterTool params = ParameterTool.fromArgs(args);
final int numDataPoints = params.getInt("points");
final int k = params.getInt("k");
final String outDir = params.get("output", System.getProperty("java.io.tmpdir"));
final double stddev = params.getDouble("stddev", RELATIVE_STDDEV);
final double range = params.getDouble("range", DEFAULT_VALUE_RANGE);
final long firstSeed = params.getLong("seed", DEFAULT_SEED);
final double absoluteStdDev = stddev * range;
final Random random = new Random(firstSeed);
// the means around which data points are distributed
final double[][] means = uniformRandomCenters(random, k, DIMENSIONALITY, range);
// write the points out
BufferedWriter pointsOut = null;
try {
pointsOut = new BufferedWriter(new FileWriter(new File(outDir+"/"+POINTS_FILE)));
StringBuilder buffer = new StringBuilder();
double[] point = new double[DIMENSIONALITY];
int nextCentroid = 0;
for (int i = 1; i <= numDataPoints; i++) {
// generate a point for the current centroid
double[] centroid = means[nextCentroid];
for (int d = 0; d < DIMENSIONALITY; d++) {
point[d] = (random.nextGaussian() * absoluteStdDev) + centroid[d];
}
writePoint(point, buffer, pointsOut);
nextCentroid = (nextCentroid + 1) % k;
}
}
finally {
if (pointsOut != null) {
pointsOut.close();
}
}
// write the uniformly distributed centers to a file
BufferedWriter centersOut = null;
try {
centersOut = new BufferedWriter(new FileWriter(new File(outDir+"/"+CENTERS_FILE)));
StringBuilder buffer = new StringBuilder();
double[][] centers = uniformRandomCenters(random, k, DIMENSIONALITY, range);
for (int i = 0; i < k; i++) {
writeCenter(i + 1, centers[i], buffer, centersOut);
}
}
finally {
if (centersOut != null) {
centersOut.close();
}
}
System.out.println("Wrote "+numDataPoints+" data points to "+outDir+"/"+POINTS_FILE);
System.out.println("Wrote "+k+" cluster centers to "+outDir+"/"+CENTERS_FILE);
}
private static double[][] uniformRandomCenters(Random rnd, int num, int dimensionality, double range) {
final double halfRange = range / 2;
final double[][] points = new double[num][dimensionality];
for (int i = 0; i < num; i++) {
for (int dim = 0; dim < dimensionality; dim ++) {
points[i][dim] = (rnd.nextDouble() * range) - halfRange;
}
}
return points;
}
private static void writePoint(double[] coordinates, StringBuilder buffer, BufferedWriter out) throws IOException {
buffer.setLength(0);
// write coordinates
for (int j = 0; j < coordinates.length; j++) {
buffer.append(FORMAT.format(coordinates[j]));
if(j < coordinates.length - 1) {
buffer.append(DELIMITER);
}
}
out.write(buffer.toString());
out.newLine();
}
private static void writeCenter(long id, double[] coordinates, StringBuilder buffer, BufferedWriter out) throws IOException {
buffer.setLength(0);
// write id
buffer.append(id);
buffer.append(DELIMITER);
// write coordinates
for (int j = 0; j < coordinates.length; j++) {
buffer.append(FORMAT.format(coordinates[j]));
if(j < coordinates.length - 1) {
buffer.append(DELIMITER);
}
}
out.write(buffer.toString());
out.newLine();
}
}