code: /**
   * Copyright (c) 2012-2013, Daniele Codecasa <codecasa.job@gmail.com>,
   * Models and Algorithms for Data & Text Mining (MAD) laboratory of
   * Milano-Bicocca University, and all the CTBNCToolkit contributors
   * that will follow.
   * All rights reserved.
   *
   * @author Daniele Codecasa and all the CTBNCToolkit contributors that will follow.
   * @copyright 2012-2013 Daniele Codecasa, MAD laboratory, and all the CTBNCToolkit contributors that will follow
   */
  package CTBNCToolkit.clustering;
  
  import java.util.*;
  
  import CTBNCToolkit.GenericLearningResults;
  import CTBNCToolkit.IClassificationResult;
  import CTBNCToolkit.SufficientStatistics;
  
  /**
   * @author Daniele Codecasa <codecasa.job@gmail.com>
   *
   * Class used to hide the result of clustering algorithms.
   * It contain sufficient statistics and the classified
   * training set. 
   * 
   * @param <TimeType> type of the time interval (Integer = discrete time, Double = continuous time)
   */
  public class ClusteringResults<TimeType extends Number> extends GenericLearningResults {
  	
  	private List<IClassificationResult<TimeType>> clusterizedTrajectories;
  	
  	/**
  	 * Constructor.
  	 * 
  	 * @param sStats calculated sufficient statistics
  	 * @param clusterizedTrajectories clusterized trajectories
  	 */
  	ClusteringResults(SufficientStatistics[] sStats, List<IClassificationResult<TimeType>> clusterizedTrajectories) {
  		
  		super(sStats);
  		this.clusterizedTrajectories = clusterizedTrajectories;
  	}
  	
  	
  	/**
  	 * Return the clusterized trajectories.
  	 * 
  	 * @return clusterized trajectories
  	 */
  	public List<IClassificationResult<TimeType>> getClusterizedTrajectories() {
  		
  		return this.clusterizedTrajectories;
  	}
  	
  }
  