/*
 *  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.operator.learner.meta;

import com.rapidminer.example.Attribute;
import com.rapidminer.example.Example;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.operator.Model;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.operator.learner.PredictionModel;

/**
 * The model for the relative regression meta learner.
 * 
 * @author Ingo Mierswa
 */
public class RelativeRegressionModel extends PredictionModel implements DelegationModel {

	private static final long serialVersionUID = -8474869399613666453L;

	private String relativeAttributeName;

	private Model baseModel;

	protected RelativeRegressionModel(ExampleSet trainingExampleSet, Model baseModel, String relativeAttributeName) {
		super(trainingExampleSet);
		this.baseModel = baseModel;
		this.relativeAttributeName = relativeAttributeName;
	}

	@Override
	public ExampleSet performPrediction(ExampleSet exampleSet, Attribute predictedLabel) throws OperatorException {
		ExampleSet resultSet = baseModel.apply(exampleSet);
		Attribute relativeAttribute = resultSet.getAttributes().get(relativeAttributeName);
		Attribute predLabel = resultSet.getAttributes().getPredictedLabel();

		// checks
		if (relativeAttribute == null) {
			throw new UserError(null, 111, relativeAttributeName);
		}

		if (predLabel == null) {
			throw new UserError(null, 107);
		}

		// change predictions 
		for (Example e : resultSet) {
			double relativeValue = e.getValue(relativeAttribute);
			double predictedValue = e.getValue(predLabel);
			e.setValue(predLabel, relativeValue + predictedValue);
		}

		return resultSet;
	}

	@Override
	public String getName() {
		return "Relative Model for " + baseModel.getName();
	}

	@Override
	public Model getBaseModel() {
		return baseModel;
	}

	@Override
	public String getShortInfo() {
		return "Regression relative to attribute \"" + relativeAttributeName + "\"";
	}
}