lu.lippmann.cdb.ext.hydviga.cbr.GapFillingKnowledgeDBAnalyzer.java Source code

Introduction

Here is the source code for lu.lippmann.cdb.ext.hydviga.cbr.GapFillingKnowledgeDBAnalyzer.java

Source

/**
 * Copyright 2014-2016 LIST (Luxembourg Institute of Science and Technology), all right reserved.
 * Authorship : Olivier PARISOT, Yoanne DIDRY
 * Licensed under GNU General Public License version 3
 */
package lu.lippmann.cdb.ext.hydviga.cbr;

import java.io.File;
import java.util.*;

import weka.core.*;
import lu.lippmann.cdb.ext.hydviga.HydroRunner;
import lu.lippmann.cdb.weka.*;

/**
 * GapFillingKnowledgeDBAnalyzer.
 * 
 * @author the gapIt team
 */
public final class GapFillingKnowledgeDBAnalyzer {
    //
    // Static methods
    //

    private static int getCountOfFictiveGaps(final Instances newkdb) {
        final Set<String> set = new HashSet<String>();
        for (int i = 0; i < newkdb.numInstances(); i++) {
            final String key = newkdb.instance(i).stringValue(newkdb.attribute("serieName").index()) + "-"
                    + newkdb.instance(i).value(newkdb.attribute("gapSize").index()) + "-"
                    + newkdb.instance(i).value(newkdb.attribute("gapPosition").index());
            set.add(key);
        }
        return set.size();
    }

    //
    // Main method
    //

    /**
     * Main method.
     * @param args command line arguments
     */
    public static void main(final String[] args) {
        try {
            HydroRunner.init(false);

            Instances newkdb = new Instances(GapFillingKnowledgeDB.getKnowledgeDB());

            System.out.println("Considered fictive gaps -> " + getCountOfFictiveGaps(newkdb));

            System.out.println(newkdb.toSummaryString());

            newkdb = WekaDataProcessingUtil.filterDataSetOnNominalValue(newkdb,
                    newkdb.attribute("useDownstream").index(), "false");
            newkdb = WekaDataProcessingUtil.filterDataSetOnNominalValue(newkdb,
                    newkdb.attribute("useUpstream").index(), "false");
            //newkdb=WekaDataProcessingUtil.filterDataSetOnNominalValue(newkdb,newkdb.attribute("useNearest").index(),"false");
            //newkdb=WekaDataProcessingUtil.filterDataSetOnNominalValue(newkdb,newkdb.attribute("useMostSimilar").index(),"false");

            //System.out.println(newkdb.toSummaryString());

            Instances withGoodNashSutcliffe = new Instances(newkdb, 0);
            for (int i = 0; i < newkdb.numInstances(); i++) {
                if (newkdb.instance(i).value(newkdb.attribute("NashSutcliffe").index()) > 0.5d) {
                    withGoodNashSutcliffe.add(new DenseInstance(1d, newkdb.instance(i).toDoubleArray()));
                }
            }

            System.out.println(withGoodNashSutcliffe.numInstances() + " / " + newkdb.numInstances());

            final double perc = (double) getCountOfFictiveGaps(withGoodNashSutcliffe)
                    / getCountOfFictiveGaps(newkdb);
            System.out.println("Fictive gaps that are infilled with a good Nash-Sutcliffe -> "
                    + getCountOfFictiveGaps(withGoodNashSutcliffe) + " (" + perc + "%)");

            WekaDataAccessUtil.saveInstancesIntoARFFFile(withGoodNashSutcliffe,
                    new File("./withGoodNashSutcliffe.arff"));
        } catch (final Exception e) {
            e.printStackTrace();
        }
    }
}