playground.johannes.socialnetworks.survey.ivt2009.analysis.AcceptPropConst.java Source code

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Here is the source code for playground.johannes.socialnetworks.survey.ivt2009.analysis.AcceptPropConst.java

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/* *********************************************************************** *
 * project: org.matsim.*
 * AcceptPropConst.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.socialnetworks.survey.ivt2009.analysis;

import gnu.trove.TDoubleDoubleHashMap;
import gnu.trove.TDoubleDoubleIterator;
import gnu.trove.TDoubleIntHashMap;
import gnu.trove.TDoubleObjectHashMap;
import gnu.trove.TDoubleObjectIterator;
import gnu.trove.TObjectDoubleHashMap;

import java.util.Set;

import org.apache.commons.math.stat.descriptive.DescriptiveStatistics;
import org.apache.log4j.Logger;

import playground.johannes.sna.graph.Vertex;
import playground.johannes.sna.graph.analysis.AbstractVertexProperty;
import playground.johannes.sna.graph.spatial.SpatialVertex;
import playground.johannes.sna.math.Discretizer;
import playground.johannes.sna.math.FixedSampleSizeDiscretizer;
import playground.johannes.sna.math.Histogram;
import playground.johannes.socialnetworks.gis.CartesianDistanceCalculator;
import playground.johannes.socialnetworks.gis.DistanceCalculator;
import playground.johannes.socialnetworks.graph.analysis.AttributePartition;
import playground.johannes.socialnetworks.graph.spatial.analysis.Distance;

import com.vividsolutions.jts.geom.Point;

/**
 * @author illenberger
 *
 */
public class AcceptPropConst extends AbstractVertexProperty {

    private static final Logger logger = Logger.getLogger(AcceptPropConst.class);

    private Set<Point> destinations;

    private final double gamma = -1.6;

    private TObjectDoubleHashMap<Vertex> partitionAttributes;

    public void setDestinations(Set<Point> destinations) {
        this.destinations = destinations;
    }

    public void setPartitionAttributes(TObjectDoubleHashMap<Vertex> partitionAttributes) {
        this.partitionAttributes = partitionAttributes;
    }

    @Override
    public TObjectDoubleHashMap<Vertex> values(Set<? extends Vertex> vertices) {
        TObjectDoubleHashMap<Vertex> c_i = new TObjectDoubleHashMap<Vertex>();

        logger.info("Creating partitions...");

        AttributePartition partitioner = new AttributePartition(
                FixedSampleSizeDiscretizer.create(partitionAttributes.getValues(), 20, 100));
        //      AttributePartition partitioner = new AttributePartition(new LinearDiscretizer(values.getValues(), 20));
        TDoubleObjectHashMap<Set<Vertex>> partitions = partitioner.partition(partitionAttributes);
        logger.info(String.format("Created %1$s partitions.", partitions.size()));

        //      Discretizer discretizer = new LinearDiscretizer(1000.0);
        DistanceCalculator distanceCalculator = new CartesianDistanceCalculator();

        logger.info("Calculating prop const...");
        TDoubleObjectIterator<?> it = partitions.iterator();
        for (int i = 0; i < partitions.size(); i++) {

            it.advance();
            Set<? extends SpatialVertex> partition = (Set<? extends SpatialVertex>) it.value();

            DescriptiveStatistics stats = Distance.getInstance().statistics(partition);
            Discretizer discretizer = FixedSampleSizeDiscretizer.create(stats.getValues(), 20, 100);
            TDoubleDoubleHashMap m_d = Histogram.createHistogram(stats, discretizer, true);
            /*
             * count number of destinations at d
             */
            TDoubleIntHashMap M_d = new TDoubleIntHashMap();
            for (SpatialVertex vertex : partition) {
                Point p1 = vertex.getPoint();
                if (p1 != null) {
                    for (Point p2 : destinations) {
                        if (p2 != null) {
                            double d = distanceCalculator.distance(p1, p2);
                            d = discretizer.discretize(d);
                            M_d.adjustOrPutValue(d, 1, 1);
                        }
                    }
                }
            }
            /*
             * 
             */
            double c_sum = 0;
            int cnt = 0;
            TDoubleDoubleIterator mdIt = m_d.iterator();
            for (int k = 0; k < m_d.size(); k++) {
                mdIt.advance();
                double d = it.key();
                //            d = discretizer.discretize(d);
                d = Math.max(d, 1.0);
                int M = M_d.get(discretizer.discretize(d));
                if (M > 0) {
                    c_sum += mdIt.value() / (Math.pow(d, gamma) * M);

                    System.err.println(String.valueOf(mdIt.value() / (Math.pow(d, gamma) * M)));

                    cnt++;
                }
            }
            double c_mean = c_sum / (double) cnt;

            System.out.println(it.key() + "\t" + c_mean);
            /*
             * 
             */
            for (SpatialVertex vertex : partition) {
                c_i.put(vertex, c_mean);
            }
        }

        return c_i;
    }

}