/*
 *  RapidMiner
 *
 *  Copyright (C) 2001-2011 by Rapid-I and the contributors
 *
 *  Complete list of developers available at our web site:
 *
 *       http://rapid-i.com
 *
 *  This program is free software: you can redistribute it and/or modify
 *  it under the terms of the GNU Affero General Public License as published by
 *  the Free Software Foundation, either version 3 of the License, or
 *  (at your option) any later version.
 *
 *  This program 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 Affero General Public License for more details.
 *
 *  You should have received a copy of the GNU Affero General Public License
 *  along with this program.  If not, see http://www.gnu.org/licenses/.
 */
package com.rapidminer.operator.performance;

import java.io.ObjectStreamException;
import java.util.LinkedList;
import java.util.List;

import com.rapidminer.example.Example;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.tools.math.Averagable;
import com.rapidminer.tools.math.ROCBias;
import com.rapidminer.tools.math.ROCData;
import com.rapidminer.tools.math.ROCDataGenerator;


/**
 * This criterion calculates the area under the ROC curve.
 * 
 * @author Ingo Mierswa, Martin Scholz
 */
public class AreaUnderCurve extends MeasuredPerformance {

    private static final long serialVersionUID = 6877715214974493828L;

    public static class Optimistic extends AreaUnderCurve {
        private static final long serialVersionUID = 1L;
        public Optimistic() {
            super(ROCBias.OPTIMISTIC);
        }
    }

    public static class Pessimistic extends AreaUnderCurve {
        private static final long serialVersionUID = 1L;
        public Pessimistic() {
            super(ROCBias.PESSIMISTIC);
        }
    }

    public static class Neutral extends AreaUnderCurve {
        private static final long serialVersionUID = 1L;
        public Neutral() {
            super(ROCBias.NEUTRAL);
        }
    }

    /** The value of the AUC. */
    private double auc = Double.NaN;

    /** The data generator for this ROC curve. */
    private transient ROCDataGenerator rocDataGenerator = new ROCDataGenerator(1.0d, 1.0d);

    /** The data for the ROC curve. */
    private LinkedList<ROCData> rocData = new LinkedList<ROCData>();

    /** A counter for average building. */
    private int counter = 1;

    /** The positive class name. */
    private String positiveClass;

    private ROCBias method;

    /** Clone constructor. */
    public AreaUnderCurve() {
        method = ROCBias.OPTIMISTIC;
    }

    public AreaUnderCurve(ROCBias method) {
        this.method = method;
    }

    public AreaUnderCurve(AreaUnderCurve aucObject) {
        super(aucObject);
        this.auc = aucObject.auc;
        this.counter = aucObject.counter;
        this.positiveClass = aucObject.positiveClass;
        this.method = aucObject.method;
    }

    /** Calculates the AUC. */
    @Override
    public void startCounting(ExampleSet exampleSet, boolean useExampleWeights) throws OperatorException {
        super.startCounting(exampleSet, useExampleWeights);
        // create ROC data
        this.rocData.add(rocDataGenerator.createROCData(exampleSet, useExampleWeights, method));
        this.auc = rocDataGenerator.calculateAUC(this.rocData.getLast());
        this.positiveClass = exampleSet.getAttributes().getPredictedLabel().getMapping().getPositiveString();
    }

    /** Does nothing. Everything is done in {@link #startCounting(ExampleSet, boolean)}. */
    @Override
    public void countExample(Example example) {}

    @Override
    public double getExampleCount() {
        return 1.0d;
    }

    @Override
    public double getMikroVariance() {
        return Double.NaN;
    }

    @Override
    public double getMikroAverage() {
        return auc / counter;
    }

    /** Returns the fitness. */
    @Override
    public double getFitness() {
        return getAverage();
    }

    @Override
    public String getName() {
        if (method == ROCBias.NEUTRAL) {
            return "AUC";
        } else {
            return "AUC ("+method.toString().toLowerCase()+")";
        }
    }

    @Override
    public String getDescription() {
        return "The area under a ROC curve. Given example weights are also considered. Please note that the second class is considered to be positive.";
    }

    @Override
    public void buildSingleAverage(Averagable performance) {
        AreaUnderCurve other = (AreaUnderCurve) performance;
        this.counter += other.counter;
        this.auc += other.auc;
        this.rocData.addAll(other.rocData);
    }

    @Override
    public String toString() {
        return super.toString() + " (positive class: " + positiveClass + ")";
    }

    public List<ROCData> getRocData() {
        return rocData;
    }

    public ROCDataGenerator getRocDataGenerator() {
        return rocDataGenerator;
    }

    public void readResolve() throws ObjectStreamException {
        rocDataGenerator = new ROCDataGenerator(1.0d, 1.0d);
    }
}