org.mcennis.graphrat.algorithm.machinelearning.ClassifyPerActor.java Source code

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/*
 * WekaClassifierMultiAttribute - created 7/02/2009 - 11:46:52 PM
 * Copyright Daniel McEnnis, see license.txt
 */
/*
 *   This file is part of GraphRAT.
 *
 *   GraphRAT 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 3 of the License, or
 *   (at your option) any later version.
 *
 *   GraphRAT is distributed in the hope that it will be useful,
 *   but WITHOUT ANY WARRANTY; without even the implied warranty of
 *   MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *   GNU General Public License for more details.
 *
 *   You should have received a copy of the GNU General Public License
 *   along with GraphRAT.  If not, see <http://www.gnu.org/licenses/>.
 */
package org.mcennis.graphrat.algorithm.machinelearning;

import java.util.*;
import java.util.logging.Level;
import java.util.logging.Logger;

import org.dynamicfactory.descriptors.Properties;
import org.mcennis.graphrat.graph.Graph;
import org.mcennis.graphrat.actor.Actor;
import org.mcennis.graphrat.algorithm.Algorithm;
import org.mcennis.graphrat.algorithm.AlgorithmMacros;
import org.mcennis.graphrat.descriptors.IODescriptor;
import org.mcennis.graphrat.descriptors.IODescriptor.Type;
import org.mcennis.graphrat.descriptors.IODescriptorFactory;
import org.dynamicfactory.descriptors.*;
import org.dynamicfactory.property.Property;
import org.mcennis.graphrat.link.Link;
import org.mcennis.graphrat.link.LinkFactory;
import org.dynamicfactory.model.ModelShell;
import org.mcennis.graphrat.query.ActorQuery;
import org.mcennis.graphrat.query.ActorQueryFactory;
import org.mcennis.graphrat.query.LinkQuery;
import org.mcennis.graphrat.query.LinkQuery.LinkEnd;
import org.mcennis.graphrat.query.actor.ActorByMode;
import weka.classifiers.Classifier;
import weka.core.Attribute;
import weka.core.FastVector;
import weka.core.Instance;
import weka.core.Instances;

/**
 *
 * @author Daniel McEnnis
 */
public class ClassifyPerActor extends ModelShell implements Algorithm {

    PropertiesInternal parameter = PropertiesFactory.newInstance().create();
    LinkedList<IODescriptor> input = new LinkedList<IODescriptor>();
    LinkedList<IODescriptor> output = new LinkedList<IODescriptor>();

    public ClassifyPerActor() {
        ParameterInternal name = ParameterFactory.newInstance().create("AlgorithmClass", String.class);
        SyntaxObject syntax = SyntaxCheckerFactory.newInstance().create(1, 1, null, String.class);
        name.setRestrictions(syntax);
        name.add("Weka Classifier Multi-Attribute");
        parameter.add(name);

        name = ParameterFactory.newInstance().create("Name", String.class);
        syntax = SyntaxCheckerFactory.newInstance().create(1, Integer.MAX_VALUE, null, String.class);
        name.setRestrictions(syntax);
        name.add("Weka Classifier Multi-Attribute");
        parameter.add(name);

        name = ParameterFactory.newInstance().create("Category", String.class);
        syntax = SyntaxCheckerFactory.newInstance().create(1, 1, null, String.class);
        name.setRestrictions(syntax);
        name.add("Machine Learning");
        parameter.add(name);

        name = ParameterFactory.newInstance().create("LinkFilter", LinkQuery.class);
        syntax = SyntaxCheckerFactory.newInstance().create(0, 1, null, LinkQuery.class);
        name.setRestrictions(syntax);
        parameter.add(name);

        name = ParameterFactory.newInstance().create("ActorFilter", ActorQuery.class);
        syntax = SyntaxCheckerFactory.newInstance().create(0, 1, null, ActorQuery.class);
        name.setRestrictions(syntax);
        parameter.add(name);

        name = ParameterFactory.newInstance().create("SourceAppendGraphID", Boolean.class);
        syntax = SyntaxCheckerFactory.newInstance().create(1, 1, null, Boolean.class);
        name.setRestrictions(syntax);
        name.add(false);
        parameter.add(name);

        name = ParameterFactory.newInstance().create("GroundMode", String.class);
        syntax = SyntaxCheckerFactory.newInstance().create(1, 1, null, String.class);
        name.setRestrictions(syntax);
        name.add("tag");
        parameter.add(name);

        name = ParameterFactory.newInstance().create("TargetMode", String.class);
        syntax = SyntaxCheckerFactory.newInstance().create(1, 1, null, String.class);
        name.setRestrictions(syntax);
        name.add("tag");
        parameter.add(name);

        name = ParameterFactory.newInstance().create("Relation", String.class);
        syntax = SyntaxCheckerFactory.newInstance().create(1, 1, null, String.class);
        name.setRestrictions(syntax);
        name.add("tag");
        parameter.add(name);

        name = ParameterFactory.newInstance().create("SourceProperty", String.class);
        syntax = SyntaxCheckerFactory.newInstance().create(1, 1, null, String.class);
        name.setRestrictions(syntax);
        name.add("Property");
        parameter.add(name);

        name = ParameterFactory.newInstance().create("ClassifierProperty", String.class);
        syntax = SyntaxCheckerFactory.newInstance().create(1, 1, null, String.class);
        name.setRestrictions(syntax);
        name.add("Property");
        parameter.add(name);

        name = ParameterFactory.newInstance().create("LinkEnd", LinkEnd.class);
        syntax = SyntaxCheckerFactory.newInstance().create(1, 1, null, LinkEnd.class);
        name.setRestrictions(syntax);
        name.add(LinkEnd.SOURCE);
        parameter.add(name);
    }

    public void execute(Graph g) {
        // construct the queries to be used

        ActorByMode groundMode = (ActorByMode) ActorQueryFactory.newInstance().create("ActorByMode");
        groundMode.buildQuery((String) parameter.get("GroundMode").get(), ".*", false);

        ActorByMode targetMode = (ActorByMode) ActorQueryFactory.newInstance().create("ActorByMode");
        targetMode.buildQuery((String) parameter.get("TargetMode").get(), ".*", false);

        // build a list of new artists
        TreeSet<Actor> artists = new TreeSet<Actor>();
        artists.addAll(AlgorithmMacros.filterActor(parameter, g, targetMode.execute(g, artists, null)));

        // collect the instance variables from the properties to be the 

        for (Actor i : artists) {
            Property classifierProperty = i.getProperty(
                    AlgorithmMacros.getSourceID(parameter, g, (String) parameter.get("ClassifierProperty").get()));
            if (!classifierProperty.getValue().isEmpty()) {
                Classifier classifier = (Classifier) classifierProperty.getValue().get(0);
                TreeSet<Actor> artist = new TreeSet<Actor>();
                artist.add(i);

                Iterator<Actor> users = AlgorithmMacros.filterActor(parameter, g, groundMode, null, null);
                Instances dataSet = null;
                boolean firstRun = true;
                while (users.hasNext()) {
                    TreeSet<Actor> user = new TreeSet<Actor>();
                    user.add(users.next());
                    Property property = user.first().getProperty(AlgorithmMacros.getSourceID(parameter, g,
                            (String) parameter.get("SourceProperty").get()));
                    if (property.getPropertyClass().getName().contentEquals(Instance.class.getName())) {
                        List values = property.getValue();
                        if (!values.isEmpty()) {
                            // get the existing instance
                            Instance object = (Instance) values.get(0);
                            if (firstRun) {
                                firstRun = false;
                                Instances current = object.dataset();
                                FastVector attributes = new FastVector();
                                for (int j = 0; j < current.numAttributes(); ++j) {
                                    attributes.addElement(current.attribute(j));
                                }
                                Attribute classValue = new Attribute(i.getID());
                                attributes.addElement(classValue);
                                dataSet = new Instances(i.getID(), attributes, 1000);
                                dataSet.setClassIndex(dataSet.numAttributes() - 1);
                            }

                            // for every artist, create a temporary artist classifer
                            double[] content = new double[object.numAttributes() + 1];
                            for (int j = 0; j < object.numAttributes() + 1; ++j) {
                                content[j] = object.value(j);
                            }

                            Instance base = new Instance(1.0, content);
                            try {
                                double strength = classifier.classifyInstance(base);
                                if ((!Double.isNaN(strength)) && (strength != 0.0)) {
                                    Link link = LinkFactory.newInstance()
                                            .create((String) parameter.get("Relation").get());
                                    if ((LinkEnd) parameter.get("LinkEnd").get() == LinkEnd.SOURCE) {
                                        link.set(user.first(), strength, artist.first());
                                    } else {
                                        link.set(artist.first(), strength, user.first());
                                    }
                                    g.add(link);
                                }
                            } catch (Exception ex) {
                                Logger.getLogger(ClassifyPerActor.class.getName()).log(Level.SEVERE, null, ex);
                            }
                        }
                    }
                }
            }
        }
    }

    public ClassifyPerActor prototype() {
        return new ClassifyPerActor();
    }

    public List<IODescriptor> getInputType() {
        return input;
    }

    public List<IODescriptor> getOutputType() {
        return output;
    }

    public Properties getParameter() {
        return parameter;
    }

    public Parameter getParameter(String param) {
        return parameter.get(param);
    }

    public void init(Properties map) {
        if (parameter.check(map)) {
            parameter.merge(map);

            IODescriptor desc = IODescriptorFactory.newInstance().create(Type.ACTOR,
                    (String) parameter.get("Name").get(), (String) parameter.get("GroundMode").get(), null, null,
                    "", false);
            input.add(desc);

            desc = IODescriptorFactory.newInstance().create(Type.ACTOR, (String) parameter.get("Name").get(),
                    (String) parameter.get("TargetMode").get(), null, null, "", false);
            input.add(desc);

            desc = IODescriptorFactory.newInstance().create(Type.LINK, (String) parameter.get("Name").get(),
                    (String) parameter.get("Relation").get(), null, null, "", false);
            output.add(desc);

            desc = IODescriptorFactory.newInstance().create(Type.ACTOR_PROPERTY,
                    (String) parameter.get("Name").get(), (String) parameter.get("GroundMode").get(), null,
                    (String) parameter.get("SourceProperty").get(), "",
                    (Boolean) parameter.get("SourceAppendGraphID").get());
            input.add(desc);

            desc = IODescriptorFactory.newInstance().create(Type.ACTOR_PROPERTY,
                    (String) parameter.get("Name").get(), (String) parameter.get("TargetMode").get(), null,
                    (String) parameter.get("ClassifierProperty").get(), "",
                    (Boolean) parameter.get("SourceAppendGraphID").get());
            input.add(desc);
        }
    }
}