/*
 *  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;

import java.util.List;

import com.rapidminer.operator.ports.InputPort;
import com.rapidminer.operator.ports.InputPortExtender;
import com.rapidminer.operator.ports.OutputPort;
import com.rapidminer.operator.ports.metadata.ExampleSetMetaData;
import com.rapidminer.operator.ports.metadata.MDTransformationRule;
import com.rapidminer.operator.ports.metadata.MetaData;
import com.rapidminer.operator.ports.metadata.ModelMetaData;
import com.rapidminer.operator.ports.metadata.Precondition;
import com.rapidminer.operator.ports.metadata.SimplePrecondition;

/**
 * <p>
 * This operator groups all input models together into a grouped (combined) model. This model can be completely applied
 * on new data or written into a file as once. This might become useful in cases where preprocessing and prediction
 * models should be applied together on new and unseen data.
 * </p>
 * 
 * <p>
 * This operator replaces the automatic model grouping known from previous versions of RapidMiner. The explicit usage of
 * this grouping operator gives the user more control about the grouping procedure. A grouped model can be ungrouped
 * with the {@link ModelUngrouper} operator.
 * </p>
 * 
 * <p>
 * Please note that the input models will be added in reverse order, i.e. the last created model, which is usually the
 * first one at the start of the io object, queue will be added as the last model to the combined group model.
 * </p>
 * 
 * @author Ingo Mierswa, Sebastian Land
 */
public class ModelGrouper extends Operator {

	private final InputPortExtender modelInputExtender = new InputPortExtender("models in", getInputPorts()) {
		@Override
		protected Precondition makePrecondition(InputPort port) {
			int index = modelInputExtender.getManagedPorts().size();
			return new SimplePrecondition(port, new MetaData(Model.class), index < 2);
		};
	};
	private final OutputPort modelOutput = getOutputPorts().createPort("model out");

	public ModelGrouper(OperatorDescription description) {
		super(description);

		modelInputExtender.ensureMinimumNumberOfPorts(2);
		
		getTransformer().addRule(new MDTransformationRule() {
			@Override
			public void transformMD() {
				List<MetaData> metaDatas = modelInputExtender.getMetaData(true);
				if (!metaDatas.isEmpty()) {
					MetaData input = metaDatas.iterator().next();
					if (input != null && input instanceof ModelMetaData) {
						ExampleSetMetaData trainMD = ((ModelMetaData) input).getTrainingSetMetaData();
						if (trainMD != null) {
							ModelMetaData mmd = new ModelMetaData(GroupedModel.class, trainMD);
							mmd.addToHistory(modelOutput);
							modelOutput.deliverMD(mmd);
							return;
						}
						modelOutput.deliverMD(null);
						return;
					}
				}
			}
		});
		modelInputExtender.start();
	}

	@Override
	public void doWork() throws OperatorException {
		GroupedModel groupedModel = new GroupedModel();
		List<Model> modelList = modelInputExtender.getData(true);
		for (Model model : modelList) {
			groupedModel.addModel(model);
		}

		modelOutput.deliver(groupedModel);
	}
}