playground.johannes.studies.coopsim.TimeSamplerTest.java Source code

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Here is the source code for playground.johannes.studies.coopsim.TimeSamplerTest.java

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/* *********************************************************************** *
 * project: org.matsim.*
 * TimeSamplerTest.java
 *                                                                         *
 * *********************************************************************** *
 *                                                                         *
 * copyright       : (C) 2011 by the members listed in the COPYING,        *
 *                   LICENSE and WARRANTY file.                            *
 * email           : info at matsim dot org                                *
 *                                                                         *
 * *********************************************************************** *
 *                                                                         *
 *   This program is free software; you can redistribute it and/or modify  *
 *   it under the terms of the GNU General Public License as published by  *
 *   the Free Software Foundation; either version 2 of the License, or     *
 *   (at your option) any later version.                                   *
 *   See also COPYING, LICENSE and WARRANTY file                           *
 *                                                                         *
 * *********************************************************************** */
package playground.johannes.studies.coopsim;

import gnu.trove.TDoubleDoubleHashMap;

import java.io.IOException;
import java.util.Random;

import org.apache.commons.math.FunctionEvaluationException;
import org.apache.commons.math.stat.descriptive.DescriptiveStatistics;

import playground.johannes.sna.math.FixedSampleSizeDiscretizer;
import playground.johannes.sna.math.Histogram;
import playground.johannes.sna.math.LinearDiscretizer;
import playground.johannes.sna.util.ProgressLogger;
import playground.johannes.sna.util.TXTWriter;
import playground.johannes.socialnetworks.statistics.Correlations;
import playground.johannes.socialnetworks.statistics.GaussDistribution;
import playground.johannes.socialnetworks.statistics.LogNormalDistribution;

/**
 * @author illenberger
 *
 */
public class TimeSamplerTest {

    /**
     * @param args
     * @throws FunctionEvaluationException 
     * @throws IOException 
     */
    public static void main(String[] args) throws FunctionEvaluationException, IOException {
        Random random = new Random();

        AdditiveDistribution arrTimePDF = new AdditiveDistribution();
        arrTimePDF.addComponent(new GaussDistribution(2151, 43030, 267));
        arrTimePDF.addComponent(new GaussDistribution(14227, 58036, 1382));

        TimeSampler arrivalSampler = new TimeSampler(arrTimePDF, 86400, random);

        AdditiveDistribution arrDurPDF = new AdditiveDistribution();
        arrDurPDF.addComponent(new GaussDistribution(7210, 41513, 133759479));
        arrDurPDF.addComponent(new GaussDistribution(15660, 73033, 277912890));

        //      TimeSampler arrDurSampler = new TimeSampler(arrDurPDF, 86400, random);
        //      
        //      LogNormalDistribution durPDF = new LogNormalDistribution(0.6883, 8.4954, 522.9869);
        //      TimeSampler durSampler = new TimeSampler(durPDF, 86400, random);
        DescriptiveStatistics durations = new DescriptiveStatistics();
        DescriptiveStatistics arrivals = new DescriptiveStatistics();

        ProgressLogger.init(10000, 1, 5);
        double sigma = 0.6883;
        for (int i = 0; i < 10000; i++) {
            int t_arr = arrivalSampler.nextSample();
            int dur_mean = (int) arrDurPDF.value(t_arr);
            if (dur_mean > 0) {
                double mu = Math.log(dur_mean) - Math.pow(sigma, 2) / 2.0;

                TimeSampler sampler = new TimeSampler(new LogNormalDistribution(sigma, mu, 522), 86400, random);
                double dur = sampler.nextSample();
                durations.addValue(dur);
                arrivals.addValue(t_arr);
                ProgressLogger.step();
            }
        }

        TDoubleDoubleHashMap hist = Histogram.createHistogram(durations,
                FixedSampleSizeDiscretizer.create(durations.getValues(), 1, 30), true);
        Histogram.normalize(hist);
        TXTWriter.writeMap(hist, "t", "n",
                "/Users/jillenberger/Work/socialnets/locationChoice/output/durations.txt");

        TDoubleDoubleHashMap correl = Correlations.mean(arrivals.getValues(), durations.getValues(),
                FixedSampleSizeDiscretizer.create(arrivals.getValues(), 1, 24));
        TXTWriter.writeMap(correl, "arr", "dur",
                "/Users/jillenberger/Work/socialnets/locationChoice/output/dur_arr.txt");
    }

}