/*
 *  RapidMiner
 *
 *  Copyright (C) 2001-2014 by RapidMiner and the contributors
 *
 *  Complete list of developers available at our web site:
 *
 *       http://rapidminer.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.tools.math.similarity.divergences;

import com.rapidminer.example.Attribute;
import com.rapidminer.example.Attributes;
import com.rapidminer.example.Example;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.example.Tools;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.tools.math.similarity.BregmanDivergence;

/**
 * The "Logarithmic loss ".
 * 
 * @author Regina Fritsch
 */
public class LogarithmicLoss extends BregmanDivergence {

	private static final long serialVersionUID = 871453359959645339L;

	@Override
	public void init(ExampleSet exampleSet) throws OperatorException {
	    super.init(exampleSet);
	    Tools.onlyNumericalAttributes(exampleSet, "value based similarities");
		Attributes attributes = exampleSet.getAttributes();
		if (attributes.size() != 1)
			throw new OperatorException("The bregman divergence you've choosen is not applicable for the dataset! Proceeding with the 'Squared Euclidean distance' bregman divergence.");
		for (Example example: exampleSet) {
			for (Attribute attribute: attributes) {
				if (example.getValue(attribute) <= 0) 
					throw new OperatorException("The bregman divergence you've choosen is not applicable for the dataset! Proceeding with the 'Squared Euclidean distance' bregman divergence.");;
			}
		}
	}

	@Override
	public double calculateDistance(double[] value1, double[] value2) {
		return (value1[0] * Math.log(value1[0] / value2[0])) - (value1[0] - value2[0]);
	}

	@Override
	public String toString() {
		return "Logarithmic loss";
	}
}