/*
 *  RapidMiner
 *
 *  Copyright (C) 2001-2008 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.learner.clustering.clusterer;

import java.util.Iterator;

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.AbstractModel;
import com.rapidminer.operator.OperatorException;
import com.rapidminer.operator.UserError;
import com.rapidminer.tools.Ontology;
import com.rapidminer.tools.WekaInstancesAdaptor;
import com.rapidminer.tools.WekaTools;

import weka.clusterers.Clusterer;
import weka.core.Instance;
import weka.core.Instances;

/**
 * A Weka clusterer which can be used to cluster examples. It is generated by a WekaClusterer.
 * 
 * @author Ingo Mierswa
 * @version $Id: WekaCluster.java,v 1.7 2008/09/12 10:31:40 tobiasmalbrecht Exp $
 */
public class WekaCluster extends AbstractModel {

	private static final long serialVersionUID = -8901173604075912094L;

	/** The used Weka clusterer. */
	private final Clusterer clusterer;

	public WekaCluster(ExampleSet exampleSet, Clusterer clusterer) {
		super(exampleSet);
		this.clusterer = clusterer;
	}

	public ExampleSet apply(ExampleSet exampleSet) throws OperatorException {
		log("Converting to Weka instances.");
		Instances instances = WekaTools.toWekaInstances(exampleSet, "ClusterInstances", WekaInstancesAdaptor.CLUSTERING);
		log("Applying Weka clusterer.");
		int i = 0;
		Attribute clusterAtt = exampleSet.getAttributes().getCluster();
		if (clusterAtt == null)
			clusterAtt = Tools.createSpecialAttribute(exampleSet, Attributes.CLUSTER_NAME, Ontology.NOMINAL);
		Iterator<Example> r = exampleSet.iterator();
		while (r.hasNext()) {
			Example e = r.next();
			Instance instance = instances.instance(i++);
			applyModelForInstance(instance, e, clusterAtt);
		}
        
        return exampleSet;
	}

	/**
	 * Clusters ervery weka instance and sets the result as cluster index of the current example.
	 */
	public void applyModelForInstance(Instance instance, Example e, Attribute clusterAtt) throws OperatorException {
		int cluster = -1;
		try {
			cluster = clusterer.clusterInstance(instance);
		} catch (Exception exc) {
			throw new UserError(null, exc, 905, new Object[] {
					clusterer, exc.toString()
			});
		}
		e.setValue(clusterAtt, "cluster" + cluster);
	}

	public String toString() {
		return clusterer.toString();
	}
}