/*
 *  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.cost;

import java.util.Map;

import com.rapidminer.example.Attribute;
import com.rapidminer.example.Example;
import com.rapidminer.operator.performance.MeasuredPerformance;
import com.rapidminer.tools.math.Averagable;

/**
 * This performance Criterion works with a given cost matrix. Every
 * classification result creates costs. Costs should be minimized since
 * that the fitness is - cost.
 * 
 * @author Sebastian Land
 */
public class ClassificationCostCriterion extends MeasuredPerformance {

    private static final long serialVersionUID = -7466139591781285005L;

    private double[][] costMatrix;
    private double exampleCount;
    private double costs;
    Attribute label;
    Attribute predictedLabel;
    private Map<String, Integer> classOrderMap = null;
    
    /**
     * Clone constructor
     * @param other the object to be cloned from
     */
    public ClassificationCostCriterion(ClassificationCostCriterion other ) {
    	this.exampleCount = other.exampleCount;
    	this.costs = other.costs;
    	if (other.label != null) {
    		this.label = (Attribute)other.label.clone();
    	} else {
    		this.label = null;
    	}

    	if (other.predictedLabel != null) {
    		this.predictedLabel = (Attribute)other.predictedLabel.clone();
    	} else {
    		this.predictedLabel = null;
    	}
    	
    	this.classOrderMap.putAll(other.classOrderMap);
    	
    	if (other.costMatrix != null) {
    		this.costMatrix = new double[other.costMatrix.length][];
    		for (int i = 0; i < other.costMatrix.length; ++i) {
    			if (other.costMatrix[i] != null) {
    				this.costMatrix[i] = new double[other.costMatrix[i].length];
    				for (int j = 0; j < other.costMatrix[i].length; ++j) {
    					this.costMatrix[i][j] = other.costMatrix[i][j];
    				}
    			} else {
    				this.costMatrix[i] = null;
    			}
    		}
    	} else {
    		this.costMatrix = null;
    	}
    }

    /**
     * This constructor is for counting with the order respective to the internal nominal mapping.
     * It is recommended to explicitly define the classOrder and use the {@link #ClassificationCostCriterion(double[][], Map, Attribute, Attribute)}
     * constructor instead.
     */
    public ClassificationCostCriterion(double[][] costMatrix, Attribute label, Attribute predictedLabel) {
        this(costMatrix, null, label, predictedLabel);
    }

    /**
     * Constructor to explicitly define the order of class names. Please take into account that the cost matrix
     * must have the same dimensions as the classorderMap has size and each interger between 0 and size-1 must
     * occur once in the classOrderMap.
     */
    public ClassificationCostCriterion(double[][] costMatrix, Map<String, Integer> classOrderMap, Attribute label, Attribute predictedLabel) {
        assert costMatrix.length == classOrderMap.size();
        this.classOrderMap = classOrderMap;
        this.costMatrix = costMatrix;
        this.label = label;
        this.predictedLabel = predictedLabel;
        exampleCount = 0;
        costs = 0;
    }

    @Override
    public String getDescription() {
        return "This Criterion delievers the misclassificationCosts";
    }

    @Override
    public String getName() {
        return "Misclassificationcosts";
    }

    @Override
    public void countExample(Example example) {
        exampleCount ++;
        if (classOrderMap == null) {
            costs += costMatrix[(int)example.getValue(predictedLabel)][(int)example.getValue(label)];
        } else {
            int predictedLabelIndex = classOrderMap.get(example.getNominalValue(predictedLabel));
            int labelIndex = classOrderMap.get(example.getNominalValue(label));
            costs += costMatrix[predictedLabelIndex][labelIndex];
        }
    }

    @Override
    public double getExampleCount() {
        return exampleCount;
    }

    @Override
    public double getFitness() {
        return -costs;
    }

    @Override
    protected void buildSingleAverage(Averagable averagable) {
    }

    @Override
    public double getMikroAverage() {
        return costs / exampleCount;
    }

    @Override
    public double getMikroVariance() {
        return 0;
    }


}