content: /*
   *    This program is free software; you can redistribute it and/or modify
   *    it under the terms of the GNU General Public License as published by
   *    the Free Software Foundation; either version 2 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 General Public License for more details.
   *
   *    You should have received a copy of the GNU General Public License
   *    along with this program; if not, write to the Free Software
   *    Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
   */
  
  /*
   *    Clusterer.java
   *    Copyright (C) 2004 University of Waikato, Hamilton, New Zealand
   *
   */
  
  package weka.gui.beans;
  
  import weka.clusterers.EM;
  import weka.core.Instances;
  import weka.core.OptionHandler;
  import weka.core.Utils;
  import weka.filters.Filter;
  import weka.filters.unsupervised.attribute.Remove;
  import weka.gui.Logger;
  import weka.gui.ExtensionFileFilter;
  
  import java.awt.BorderLayout;
  import java.beans.EventSetDescriptor;
  import java.io.*;
  import java.util.Enumeration;
  import java.util.Hashtable;
  import java.util.Vector;
  
  import javax.swing.JPanel;
  import javax.swing.JOptionPane;
  import javax.swing.JFileChooser;
  
  import javax.swing.JPanel;
  
  /**
   * Bean that wraps around weka.clusterers
   *
   * @author <a href="mailto:mutter@cs.waikato.ac.nz">Stefan Mutter</a>
   * @version $Revision: 5247 $
   * @see JPanel
   * @see BeanCommon
   * @see Visible
   * @see WekaWrapper
   * @see Serializable
   * @see UserRequestAcceptor
   * @see TrainingSetListener
   * @see TestSetListener
   */
  public class Clusterer
    extends JPanel
    implements BeanCommon, Visible, WekaWrapper, EventConstraints, 
               UserRequestAcceptor, TrainingSetListener, 
               TestSetListener, ConfigurationProducer {
  
    /** for serialization */
    private static final long serialVersionUID = 7729795159836843810L;
  
    protected BeanVisual m_visual = 
      new BeanVisual("Clusterer",
  		   BeanVisual.ICON_PATH+"EM.gif",
  		   BeanVisual.ICON_PATH+"EM_animated.gif");
  
    private static int IDLE = 0;
    private static int BUILDING_MODEL = 1;
    private static int CLUSTERING = 2;
  
    private int m_state = IDLE;
  
    private Thread m_buildThread = null;
  
    /**
     * Global info for the wrapped classifier (if it exists).
     */
    protected String m_globalInfo;
  
    /**
     * Objects talking to us
     */
    private Hashtable m_listenees = new Hashtable();
  
    /**
     * Objects listening for batch clusterer events
     */
    private Vector m_batchClustererListeners = new Vector();
  
  
    /**
     * Objects listening for graph events
     */
    private Vector m_graphListeners = new Vector();
  
    /**
     * Objects listening for text events
     */
    private Vector m_textListeners = new Vector();
  
    /**
     * Holds training instances for batch training. 
     */
    private Instances m_trainingSet;
    private transient Instances m_testingSet;
    private weka.clusterers.Clusterer m_Clusterer = new EM();
    
  
    private transient Logger m_log = null;
  
    private Double m_dummy = new Double(0.0);
  
    private transient JFileChooser m_fileChooser = null;
  
    /**
     * Global info (if it exists) for the wrapped classifier
     *
     * @return the global info
     */
    public String globalInfo() {
      return m_globalInfo;
    }
  
    /**
     * Creates a new <code>Clusterer</code> instance.
     */
    public Clusterer() {
      setLayout(new BorderLayout());
      add(m_visual, BorderLayout.CENTER);
      setClusterer(m_Clusterer);
    }
  
    /**
     * Set a custom (descriptive) name for this bean
     * 
     * @param name the name to use
     */
    public void setCustomName(String name) {
      m_visual.setText(name);
    }
  
    /**
     * Get the custom (descriptive) name for this bean (if one has been set)
     * 
     * @return the custom name (or the default name)
     */
    public String getCustomName() {
      return m_visual.getText();
    }
  
    /**
     * Set the clusterer for this wrapper
     *
     * @param c a <code>weka.clusterers.Clusterer</code> value
     */
    public void setClusterer(weka.clusterers.Clusterer c) {
      boolean loadImages = true;
      if (c.getClass().getName().
  	compareTo(m_Clusterer.getClass().getName()) == 0) {
        loadImages = false;
      } else {
        // clusterer has changed so any batch training status is now
        // invalid
        m_trainingSet = null;
      }
      m_Clusterer = c;
      String clustererName = c.getClass().toString();
      clustererName = clustererName.substring(clustererName.
  					      lastIndexOf('.')+1, 
  					      clustererName.length());
      if (loadImages) {
        if (!m_visual.loadIcons(BeanVisual.ICON_PATH+clustererName+".gif",
  		       BeanVisual.ICON_PATH+clustererName+"_animated.gif")) {
  	useDefaultVisual();
        }
      }
      m_visual.setText(clustererName);
  
      // get global info
      m_globalInfo = KnowledgeFlowApp.getGlobalInfo(m_Clusterer);
    }
  
  
    /**
     * Returns true if this clusterer has an incoming connection that is
     * a batch set of instances
     *
     * @return a <code>boolean</code> value
     */
    public boolean hasIncomingBatchInstances() {
      if (m_listenees.size() == 0) {
        return false;
      }
      if (m_listenees.containsKey("trainingSet") ||
  	m_listenees.containsKey("testSet") ||
          m_listenees.containsKey("dataSet")) {
        return true;
      }
      return false;
    }
  
    /**
     * Get the clusterer currently set for this wrapper
     *
     * @return a <code>weka.clusterers.Clusterer</code> value
     */
    public weka.clusterers.Clusterer getClusterer() {
      return m_Clusterer;
    }
  
    /**
     * Sets the algorithm (clusterer) for this bean
     *
     * @param algorithm an <code>Object</code> value
     * @exception IllegalArgumentException if an error occurs
     */
    public void setWrappedAlgorithm(Object algorithm) 
      {
  
      if (!(algorithm instanceof weka.clusterers.Clusterer)) { 
        throw new IllegalArgumentException(algorithm.getClass()+" : incorrect "
  					 +"type of algorithm (Clusterer)");
      }
      setClusterer((weka.clusterers.Clusterer)algorithm);
    }
  
    /**
     * Returns the wrapped clusterer
     *
     * @return an <code>Object</code> value
     */
    public Object getWrappedAlgorithm() {
      return getClusterer();
    }
  
  
    /**
     * Accepts a training set and builds batch clusterer
     *
     * @param e a <code>TrainingSetEvent</code> value
     */
    public void acceptTrainingSet(final TrainingSetEvent e) {
      if (e.isStructureOnly()) {
        // no need to build a clusterer, instead just generate a dummy
        // BatchClustererEvent in order to pass on instance structure to
        // any listeners 
        BatchClustererEvent ce = 
  	new BatchClustererEvent(this, m_Clusterer, 
  				 new DataSetEvent(this, e.getTrainingSet()),
  				 e.getSetNumber(), e.getMaxSetNumber(),1);
  
        notifyBatchClustererListeners(ce);
        return;
      }
      if (m_buildThread == null) {
        try {
  	if (m_state == IDLE) {
  	  synchronized (this) {
  	    m_state = BUILDING_MODEL;
  	  }
  	  m_trainingSet = e.getTrainingSet();
  //	  final String oldText = m_visual.getText();
  	  m_buildThread = new Thread() {
  	      public void run() {
  		try {
  		  if (m_trainingSet != null) {  
  		    m_visual.setAnimated();
  //		    m_visual.setText("Building clusters...");
  		    if (m_log != null) {
  		      m_log.statusMessage(statusMessagePrefix() 
  		          + "Building clusters...");
  		    }
  		    buildClusterer();
                      if(m_batchClustererListeners.size() > 0){
                          BatchClustererEvent ce = 
                              new BatchClustererEvent(this, m_Clusterer, 
  				 new DataSetEvent(this, e.getTrainingSet()),
  				 e.getSetNumber(), e.getMaxSetNumber(),1);
                          notifyBatchClustererListeners(ce);
                      }
  		    if (m_Clusterer instanceof weka.core.Drawable && 
  			m_graphListeners.size() > 0) {
  		      String grphString = 
  			((weka.core.Drawable)m_Clusterer).graph();
                        int grphType = ((weka.core.Drawable)m_Clusterer).graphType();
  		      String grphTitle = m_Clusterer.getClass().getName();
  		      grphTitle = grphTitle.substring(grphTitle.
  						      lastIndexOf('.')+1, 
  						      grphTitle.length());
  		      grphTitle = "Set " + e.getSetNumber() + " ("
  			+e.getTrainingSet().relationName() + ") "
  			+grphTitle;
  		      
  		      GraphEvent ge = new GraphEvent(Clusterer.this, 
  						     grphString, 
  						     grphTitle,
                                                       grphType);
  		      notifyGraphListeners(ge);
  		    }
  
  		    if (m_textListeners.size() > 0) {
  		      String modelString = m_Clusterer.toString();
  		      String titleString = m_Clusterer.getClass().getName();
  		      
  		      titleString = titleString.
  			substring(titleString.lastIndexOf('.') + 1,
  				  titleString.length());
  		      modelString = "=== Clusterer model ===\n\n" +
  			"Scheme:   " +titleString+"\n" +
  			"Relation: "  + m_trainingSet.relationName() + 
  			((e.getMaxSetNumber() > 1) 
  			 ? "\nTraining Fold: "+e.getSetNumber()
  			 :"")
  			+ "\n\n"
  			+ modelString;
  		      titleString = "Model: " + titleString;
  
  		      TextEvent nt = new TextEvent(Clusterer.this,
  						   modelString,
  						   titleString);
  		      notifyTextListeners(nt);
  		    }
  		  }
  		} catch (Exception ex) {
  		  Clusterer.this.stop(); // stop processing
  		  if (m_log != null) {
  		    m_log.statusMessage(statusMessagePrefix()
  		        + "ERROR (See log for details");
  		    m_log.logMessage("[Clusterer] " + statusMessagePrefix()
  		        + " problem training clusterer. " + ex.getMessage());
  		  }
  		  ex.printStackTrace();
  		} finally {
  //		  m_visual.setText(oldText);
  		  m_visual.setStatic();
  		  m_state = IDLE;
  		  if (isInterrupted()) {
  		    // prevent any clusterer events from being fired
  		    m_trainingSet = null;
  		    if (m_log != null) {
  		      m_log.logMessage("[Clusterer]" + statusMessagePrefix() 
  		          + " Build clusterer interrupted!");
  		      m_log.statusMessage(statusMessagePrefix() 
  		          + "INTERRUPTED");
  		    }
  		  } else {
  		    // save header
  		    m_trainingSet = new Instances(m_trainingSet, 0);
  		    if (m_log != null) {
  		      m_log.statusMessage(statusMessagePrefix() + "Finished.");
  		    }
  		  }
  		  block(false);
  		}
  	      }	
  	    };
  	  m_buildThread.setPriority(Thread.MIN_PRIORITY);
  	  m_buildThread.start();
  	  // make sure the thread is still running before we block
  	  //	  if (m_buildThread.isAlive()) {
  	  block(true);
  	    //	  }
  	  m_buildThread = null;
  	  m_state = IDLE;
  	}
        } catch (Exception ex) {
  	ex.printStackTrace();
        }
      }
    }
  
    /**
     * Accepts a test set for a batch trained clusterer
     *
     * @param e a <code>TestSetEvent</code> value
     */
    public void acceptTestSet(TestSetEvent e) {
  
      if (m_trainingSet != null) {
        try {
  	if (m_state == IDLE) {
  	  synchronized(this) {
  	    m_state = CLUSTERING;
  	  }
            m_testingSet = e.getTestSet();
  	  if (m_trainingSet.equalHeaders(m_testingSet)) {
  	    BatchClustererEvent ce = 
  	      new BatchClustererEvent(this, m_Clusterer, 
  				       new DataSetEvent(this, e.getTestSet()),
  				  e.getSetNumber(), e.getMaxSetNumber(),0);
  
  	    notifyBatchClustererListeners(ce);
  	    
  	  }
  	  m_state = IDLE;
  	}
        } catch (Exception ex) {
          stop(); // stop any processing
          if (m_log != null) {
            m_log.statusMessage(statusMessagePrefix()
                + "ERROR (see log for details");
            m_log.logMessage("[Clusterer] " + statusMessagePrefix()
                + " problem during testing. " + ex.getMessage());
          }
  	ex.printStackTrace();
        }
      }
    }
  
  /**
     * Builds the clusters
     */
    private void buildClusterer() throws Exception {
        if(m_trainingSet.classIndex() < 0)  
          m_Clusterer.buildClusterer(m_trainingSet);
        else{ //class based evaluation if class attribute is set
          Remove removeClass = new Remove();
  	removeClass.setAttributeIndices(""+(m_trainingSet.classIndex()+1));
  	removeClass.setInvertSelection(false);
  	removeClass.setInputFormat(m_trainingSet);
  	Instances clusterTrain = Filter.useFilter(m_trainingSet, removeClass);
  	m_Clusterer.buildClusterer(clusterTrain);
        }
    }
  
    /**
     * Sets the visual appearance of this wrapper bean
     *
     * @param newVisual a <code>BeanVisual</code> value
     */
    public void setVisual(BeanVisual newVisual) {
      m_visual = newVisual;
    }
  
    /**
     * Gets the visual appearance of this wrapper bean
     */
    public BeanVisual getVisual() {
      return m_visual;
    }
  
    /**
     * Use the default visual appearance for this bean
     */
    public void useDefaultVisual() {
      m_visual.loadIcons(BeanVisual.ICON_PATH+"DefaultClusterer.gif",
  		       BeanVisual.ICON_PATH+"DefaultClusterer_animated.gif");
    }
  
    /**
     * Add a batch clusterer listener
     *
     * @param cl a <code>BatchClustererListener</code> value
     */
    public synchronized void 
      addBatchClustererListener(BatchClustererListener cl) {
      m_batchClustererListeners.addElement(cl);
    }
  
    /**
     * Remove a batch clusterer listener
     *
     * @param cl a <code>BatchClustererListener</code> value
     */
    public synchronized void 
      removeBatchClustererListener(BatchClustererListener cl) {
      m_batchClustererListeners.remove(cl);
    }
  
    /**
     * Notify all batch clusterer listeners of a batch clusterer event
     *
     * @param ce a <code>BatchClustererEvent</code> value
     */
    private void notifyBatchClustererListeners(BatchClustererEvent ce) {
      Vector l;
      synchronized (this) {
        l = (Vector)m_batchClustererListeners.clone();
      }
      if (l.size() > 0) {
        for(int i = 0; i < l.size(); i++) {
  	((BatchClustererListener)l.elementAt(i)).acceptClusterer(ce);
        }
      }
    }
  
    /**
     * Add a graph listener
     *
     * @param cl a <code>GraphListener</code> value
     */
    public synchronized void addGraphListener(GraphListener cl) {
      m_graphListeners.addElement(cl);
    }
  
    /**
     * Remove a graph listener
     *
     * @param cl a <code>GraphListener</code> value
     */
    public synchronized void removeGraphListener(GraphListener cl) {
      m_graphListeners.remove(cl);
    }
  
    /**
     * Notify all graph listeners of a graph event
     *
     * @param ge a <code>GraphEvent</code> value
     */
    private void notifyGraphListeners(GraphEvent ge) {
      Vector l;
      synchronized (this) {
        l = (Vector)m_graphListeners.clone();
      }
      if (l.size() > 0) {
        for(int i = 0; i < l.size(); i++) {
  	((GraphListener)l.elementAt(i)).acceptGraph(ge);
        }
      }
    }
  
    /**
     * Add a text listener
     *
     * @param cl a <code>TextListener</code> value
     */
    public synchronized void addTextListener(TextListener cl) {
      m_textListeners.addElement(cl);
    }
  
    /**
     * Remove a text listener
     *
     * @param cl a <code>TextListener</code> value
     */
    public synchronized void removeTextListener(TextListener cl) {
      m_textListeners.remove(cl);
    }
  
    /**
     * Notify all text listeners of a text event
     *
     * @param ge a <code>TextEvent</code> value
     */
    private void notifyTextListeners(TextEvent ge) {
      Vector l;
      synchronized (this) {
        l = (Vector)m_textListeners.clone();
      }
      if (l.size() > 0) {
        for(int i = 0; i < l.size(); i++) {
  	((TextListener)l.elementAt(i)).acceptText(ge);
        }
      }
    }
    
    /**
     * We don't have to keep track of configuration listeners (see the
     * documentation for ConfigurationListener/ConfigurationEvent).
     * 
     * @param cl a ConfigurationListener.
     */
    public synchronized void addConfigurationListener(ConfigurationListener cl) {
      
    }
    
    /**
     * We don't have to keep track of configuration listeners (see the
     * documentation for ConfigurationListener/ConfigurationEvent).
     * 
     * @param cl a ConfigurationListener.
     */
    public synchronized void removeConfigurationListener(ConfigurationListener cl) {
      
    }
  
  
    /**
     * Returns true if, at this time, 
     * the object will accept a connection with respect to the named event
     *
     * @param eventName the event
     * @return true if the object will accept a connection
     */
    public boolean connectionAllowed(String eventName) {
      /*    if (eventName.compareTo("instance") == 0) {
        if (!(m_Clusterer instanceof weka.classifiers.UpdateableClassifier)) {
  	return false;
        }
        } */
      if (m_listenees.containsKey(eventName)) {
        return false;
      }
      return true;
    }
  
    /**
     * Returns true if, at this time, 
     * the object will accept a connection according to the supplied
     * EventSetDescriptor
     *
     * @param esd the EventSetDescriptor
     * @return true if the object will accept a connection
     */
    public boolean connectionAllowed(EventSetDescriptor esd) {
      return connectionAllowed(esd.getName());
    }
  
    /**
     * Notify this object that it has been registered as a listener with
     * a source with respect to the named event
     *
     * @param eventName the event
     * @param source the source with which this object has been registered as
     * a listener
     */
    public synchronized void connectionNotification(String eventName,
  						  Object source) {
  
      if (connectionAllowed(eventName)) {
        m_listenees.put(eventName, source);
        /*      if (eventName.compareTo("instance") == 0) {
  	startIncrementalHandler();
  	} */
      }
    }
  
    /**
     * Notify this object that it has been deregistered as a listener with
     * a source with respect to the supplied event name
     *
     * @param eventName the event
     * @param source the source with which this object has been registered as
     * a listener
     */
    public synchronized void disconnectionNotification(String eventName,
  						     Object source) {
      m_listenees.remove(eventName);
    }
  
    /**
     * Function used to stop code that calls acceptTrainingSet. This is 
     * needed as clusterer construction is performed inside a separate
     * thread of execution.
     *
     * @param tf a <code>boolean</code> value
     */
    private synchronized void block(boolean tf) {
  
      if (tf) {
        try {
  	  // only block if thread is still doing something useful!
  	if (m_buildThread.isAlive() && m_state != IDLE) {
  	  wait();
  	  }
        } catch (InterruptedException ex) {
        }
      } else {
        notifyAll();
      }
    }
  
    /**
     * Returns true if. at this time, the bean is busy with some
     * (i.e. perhaps a worker thread is performing some calculation).
     * 
     * @return true if the bean is busy.
     */
    public boolean isBusy() {
      return (m_buildThread != null);
    }
    
    /**
     * Stop any clusterer action
     */
    public void stop() {
      // tell all listenees (upstream beans) to stop
      Enumeration en = m_listenees.keys();
      while (en.hasMoreElements()) {
        Object tempO = m_listenees.get(en.nextElement());
        if (tempO instanceof BeanCommon) {
  	((BeanCommon)tempO).stop();
        }
      }
  
      // stop the build thread
      if (m_buildThread != null) {
        m_buildThread.interrupt();
        m_buildThread.stop();
        m_buildThread = null;
        m_visual.setStatic();
      }
    }
  
    /**
     * Set a logger
     *
     * @param logger a <code>Logger</code> value
     */
    public void setLog(Logger logger) {
      m_log = logger;
    }
  
    public void saveModel() {
      try {
        if (m_fileChooser == null) {
          // i.e. after de-serialization
          m_fileChooser = 
            new JFileChooser(new File(System.getProperty("user.dir")));
          ExtensionFileFilter ef = new ExtensionFileFilter("model", "Serialized weka clusterer");
        m_fileChooser.setFileFilter(ef);
        }
        int returnVal = m_fileChooser.showSaveDialog(this);
        if (returnVal == JFileChooser.APPROVE_OPTION) {
          File saveTo = m_fileChooser.getSelectedFile();
          String fn = saveTo.getAbsolutePath();
          if (!fn.endsWith(".model")) {
            fn += ".model";
            saveTo = new File(fn);
          }
          ObjectOutputStream os = 
            new ObjectOutputStream(new BufferedOutputStream(
                                                            new FileOutputStream(saveTo)));
          os.writeObject(m_Clusterer);
          if (m_trainingSet != null) {
            Instances header = new Instances(m_trainingSet, 0);
            os.writeObject(header);
          }
          os.close();
          if (m_log != null) {
            m_log.logMessage("[Clusterer] Saved clusterer " + getCustomName());
          }
        }
      } catch (Exception ex) {
        JOptionPane.showMessageDialog(Clusterer.this,
                                      "Problem saving clusterer.\n",
                                      "Save Model",
                                      JOptionPane.ERROR_MESSAGE);
        if (m_log != null) {
          m_log.logMessage("[Clusterer] Problem saving clusterer. " 
              + getCustomName() + ex.getMessage());
        }
      }
    }
  
    public void loadModel() {
      try {
        if (m_fileChooser == null) {
          // i.e. after de-serialization
          m_fileChooser = 
            new JFileChooser(new File(System.getProperty("user.dir")));
          ExtensionFileFilter ef = new ExtensionFileFilter("model", "Serialized weka clusterer");
          m_fileChooser.setFileFilter(ef);
        }
        int returnVal = m_fileChooser.showOpenDialog(this);
        if (returnVal == JFileChooser.APPROVE_OPTION) {
          File loadFrom = m_fileChooser.getSelectedFile();
          ObjectInputStream is = 
            new ObjectInputStream(new BufferedInputStream(
                                  new FileInputStream(loadFrom)));
          // try and read the model
          weka.clusterers.Clusterer temp = (weka.clusterers.Clusterer)is.readObject();
  
          // Update name and icon
          setClusterer(temp);
          
          // try and read the header (if present)
          try {
            m_trainingSet = (Instances)is.readObject();
          } catch (Exception ex) {
            // quietly ignore
          }
          is.close();
          if (m_log != null) {
            m_log.logMessage("[Clusterer] Loaded clusterer: "
                             + m_Clusterer.getClass().toString());
          }
        }
      } catch (Exception ex) {
        JOptionPane.showMessageDialog(Clusterer.this,
                                      "Problem loading classifier.\n",
                                      "Load Model",
                                      JOptionPane.ERROR_MESSAGE);
        if (m_log != null) {
          m_log.logMessage("[Clusterer] Problem loading classifier. " 
              + ex.getMessage());
        }
      }
    }
  
    /**
     * Return an enumeration of requests that can be made by the user
     *
     * @return an <code>Enumeration</code> value
     */
    public Enumeration enumerateRequests() {
      Vector newVector = new Vector(0);
      if (m_buildThread != null) {
        newVector.addElement("Stop");
      }
  
      if (m_buildThread == null &&
          m_Clusterer != null) {
        newVector.addElement("Save model");
      }
  
      if (m_buildThread == null) {
        newVector.addElement("Load model");
      }
      
      return newVector.elements();
    }
  
    /**
     * Perform a particular request
     *
     * @param request the request to perform
     * @exception IllegalArgumentException if an error occurs
     */
    public void performRequest(String request) {
      if (request.compareTo("Stop") == 0) {
        stop();
      }  else if (request.compareTo("Save model") == 0) {
        saveModel();
      } else if (request.compareTo("Load model") == 0) {
        loadModel();
      } else {
        throw new IllegalArgumentException(request
  					 + " not supported (Clusterer)");
      }
    }
  
    /**
     * Returns true, if at the current time, the event described by the
     * supplied event descriptor could be generated.
     *
     * @param esd an <code>EventSetDescriptor</code> value
     * @return a <code>boolean</code> value
     */
    public boolean eventGeneratable(EventSetDescriptor esd) {
      String eventName = esd.getName();
      return eventGeneratable(eventName);
    }
  
    /**
     * Returns true, if at the current time, the named event could
     * be generated. Assumes that the supplied event name is
     * an event that could be generated by this bean
     *
     * @param eventName the name of the event in question
     * @return true if the named event could be generated at this point in
     * time
     */
    public boolean eventGeneratable(String eventName) {
      if (eventName.compareTo("graph") == 0) {
        // can't generate a GraphEvent if clusterer is not drawable
        if (!(m_Clusterer instanceof weka.core.Drawable)) {
  	return false;
        }
        // need to have a training set before the clusterer
        // can generate a graph!
        if (!m_listenees.containsKey("trainingSet")) {
  	return false;
        }
        // Source needs to be able to generate a trainingSet
        // before we can generate a graph
        Object source = m_listenees.get("trainingSet");
         if (source instanceof EventConstraints) {
  	if (!((EventConstraints)source).eventGeneratable("trainingSet")) {
  	  return false;
  	}
        }
      }
  
      if (eventName.compareTo("batchClusterer") == 0) {
        if (!m_listenees.containsKey("trainingSet")) {
  	return false;
        }
       
        Object source = m_listenees.get("trainingSet");
        if (source != null && source instanceof EventConstraints) {
  	if (!((EventConstraints)source).eventGeneratable("trainingSet")) {
  	  return false;
  	}
        }
      }
  
      if (eventName.compareTo("text") == 0) {
        if (!m_listenees.containsKey("trainingSet")){ 
  	return false;
        }
        Object source = m_listenees.get("trainingSet");
        if (source != null && source instanceof EventConstraints) {
  	if (!((EventConstraints)source).eventGeneratable("trainingSet")) {
  	  return false;
  	}
        }
      }
  
      if (eventName.compareTo("batchClassifier") == 0)
          return false;
      if (eventName.compareTo("incrementalClassifier") == 0)
          return false;
      
      return true;
    }
    
    private String statusMessagePrefix() {
      return getCustomName() + "$" + hashCode() + "|"
      + ((m_Clusterer instanceof OptionHandler &&
          Utils.joinOptions(((OptionHandler)m_Clusterer).getOptions()).length() > 0)
          ? Utils.joinOptions(((OptionHandler)m_Clusterer).getOptions()) + "|"
              : "");
    }
  }
  