/*
 *  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.postprocessing;

import java.util.ArrayList;
import java.util.Collections;
import java.util.HashMap;
import java.util.Iterator;
import java.util.List;
import java.util.Map;

import com.rapidminer.example.Attribute;
import com.rapidminer.example.AttributeRole;
import com.rapidminer.example.Attributes;
import com.rapidminer.example.Example;
import com.rapidminer.example.ExampleSet;
import com.rapidminer.example.table.AttributeFactory;
import com.rapidminer.operator.AbstractExampleSetProcessing;
import com.rapidminer.operator.OperatorDescription;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.ports.metadata.ExampleSetPrecondition;
import com.rapidminer.parameter.ParameterType;
import com.rapidminer.parameter.ParameterTypeString;
import com.rapidminer.tools.Ontology;
import com.rapidminer.tools.container.Tupel;

/**
 * Generates predictions from confidence attributes.
 * 
 * @author Tobias Malbrecht
 */
public class GeneratePredictionOperator extends AbstractExampleSetProcessing {
	public static final String PARAMETER_PREDICTION_NAME = "prediction_name";

	public GeneratePredictionOperator(OperatorDescription description) {
		super(description);
		getExampleSetInputPort().addPrecondition(new ExampleSetPrecondition(getExampleSetInputPort(), Attributes.CONFIDENCE_NAME, Ontology.NUMERICAL));
	}

	
	@Override
	public ExampleSet apply(ExampleSet exampleSet) throws OperatorException {
		// searching confidence attributes
		Map<Attribute, String> confidenceAttributes = new HashMap<Attribute, String>();
		for (Iterator<AttributeRole> iterator = exampleSet.getAttributes().specialAttributes(); iterator.hasNext(); ) {
			AttributeRole role = iterator.next();
			if (role.getSpecialName().matches(Attributes.CONFIDENCE_NAME + "_.*")) {
				confidenceAttributes.put(role.getAttribute(), role.getSpecialName().replaceAll("^" + Attributes.CONFIDENCE_NAME + "_(.*)$", "$1"));
			}
		}
		
		if (confidenceAttributes.size() > 0) {
			String predictionName = getParameterAsString(PARAMETER_PREDICTION_NAME);
			Attribute predictionAttribute = AttributeFactory.createAttribute("prediction(" + predictionName + ")", Ontology.NOMINAL);
			for (String value : confidenceAttributes.values()) {
				predictionAttribute.getMapping().mapString(value);
			}
			exampleSet.getExampleTable().addAttribute(predictionAttribute);
			exampleSet.getAttributes().addRegular(predictionAttribute);
			exampleSet.getAttributes().setSpecialAttribute(predictionAttribute, Attributes.PREDICTION_NAME);
			for (Example example: exampleSet) {
				ArrayList<Tupel<Double, String>> labelConfidences = new ArrayList<Tupel<Double,String>>(confidenceAttributes.size());
				for (Map.Entry<Attribute, String> entry : confidenceAttributes.entrySet()) {
					labelConfidences.add(new Tupel<Double, String>(example.getValue(entry.getKey()), entry.getValue()));
				}
				Collections.sort(labelConfidences);
				example.setValue(predictionAttribute, predictionAttribute.getMapping().mapString(labelConfidences.get(labelConfidences.size() - 1).getSecond()));
			}
		}
		
		return exampleSet;
	}

	@Override
	public boolean writesIntoExistingData() {
		return false;
	}
	
	@Override
	public List<ParameterType> getParameterTypes() {
		List<ParameterType> types = super.getParameterTypes();
		types.add(new ParameterTypeString(PARAMETER_PREDICTION_NAME, "The name of the label that should be predicted.", false, false));
		return types;
	}
}