Logo Search packages:      
Sourcecode: weka version File versions

ClustererPanel.java

/*
 *    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.
 */

/*
 *    ClustererPanel.java
 *    Copyright (C) 1999 University of Waikato, Hamilton, New Zealand
 *
 */

package weka.gui.explorer;

import weka.clusterers.ClusterEvaluation;
import weka.clusterers.Clusterer;
import weka.core.Attribute;
import weka.core.Capabilities;
import weka.core.Drawable;
import weka.core.FastVector;
import weka.core.Instance;
import weka.core.Instances;
import weka.core.OptionHandler;
import weka.core.SerializedObject;
import weka.core.Utils;
import weka.filters.Filter;
import weka.filters.unsupervised.attribute.Remove;
import weka.gui.ExtensionFileFilter;
import weka.gui.GenericObjectEditor;
import weka.gui.InstancesSummaryPanel;
import weka.gui.ListSelectorDialog;
import weka.gui.Logger;
import weka.gui.PropertyPanel;
import weka.gui.ResultHistoryPanel;
import weka.gui.SaveBuffer;
import weka.gui.SetInstancesPanel;
import weka.gui.SysErrLog;
import weka.gui.TaskLogger;
import weka.gui.explorer.Explorer.CapabilitiesFilterChangeEvent;
import weka.gui.explorer.Explorer.CapabilitiesFilterChangeListener;
import weka.gui.explorer.Explorer.ExplorerPanel;
import weka.gui.explorer.Explorer.LogHandler;
import weka.gui.treevisualizer.PlaceNode2;
import weka.gui.treevisualizer.TreeVisualizer;
import weka.gui.visualize.Plot2D;
import weka.gui.visualize.PlotData2D;
import weka.gui.visualize.VisualizePanel;

import java.awt.BorderLayout;
import java.awt.Dimension;
import java.awt.Font;
import java.awt.GridBagConstraints;
import java.awt.GridBagLayout;
import java.awt.GridLayout;
import java.awt.Insets;
import java.awt.Point;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;
import java.awt.event.InputEvent;
import java.awt.event.MouseAdapter;
import java.awt.event.MouseEvent;
import java.beans.PropertyChangeEvent;
import java.beans.PropertyChangeListener;
import java.io.File;
import java.io.FileInputStream;
import java.io.FileOutputStream;
import java.io.InputStream;
import java.io.ObjectInputStream;
import java.io.ObjectOutputStream;
import java.io.OutputStream;
import java.text.SimpleDateFormat;
import java.util.Date;
import java.util.Random;
import java.util.zip.GZIPInputStream;
import java.util.zip.GZIPOutputStream;

import javax.swing.BorderFactory;
import javax.swing.ButtonGroup;
import javax.swing.DefaultComboBoxModel;
import javax.swing.DefaultListModel;
import javax.swing.JButton;
import javax.swing.JCheckBox;
import javax.swing.JComboBox;
import javax.swing.JFileChooser;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JList;
import javax.swing.JMenuItem;
import javax.swing.JOptionPane;
import javax.swing.JPanel;
import javax.swing.JPopupMenu;
import javax.swing.JRadioButton;
import javax.swing.JScrollPane;
import javax.swing.JTextArea;
import javax.swing.JTextField;
import javax.swing.JViewport;
import javax.swing.SwingConstants;
import javax.swing.event.ChangeEvent;
import javax.swing.event.ChangeListener;
import javax.swing.filechooser.FileFilter;

/** 
 * This panel allows the user to select and configure a clusterer, and evaluate
 * the clusterer using a number of testing modes (test on the training data,
 * train/test on a percentage split, test on a
 * separate split). The results of clustering runs are stored in a result
 * history so that previous results are accessible.
 *
 * @author Mark Hall (mhall@cs.waikato.ac.nz)
 * @author Richard Kirkby (rkirkby@cs.waikato.ac.nz)
 * @version $Revision: 1.60 $
 */
00123 public class ClustererPanel
  extends JPanel
  implements CapabilitiesFilterChangeListener, ExplorerPanel, LogHandler {

  /** for serialization */
00128   static final long serialVersionUID = -2474932792950820990L;

  /** the parent frame */
00131   protected Explorer m_Explorer = null;
  
  /** The filename extension that should be used for model files */
00134   public static String MODEL_FILE_EXTENSION = ".model";

  /** Lets the user configure the clusterer */
00137   protected GenericObjectEditor m_ClustererEditor =
    new GenericObjectEditor();

  /** The panel showing the current clusterer selection */
00141   protected PropertyPanel m_CLPanel = new PropertyPanel(m_ClustererEditor);
  
  /** The output area for classification results */
00144   protected JTextArea m_OutText = new JTextArea(20, 40);

  /** The destination for log/status messages */
00147   protected Logger m_Log = new SysErrLog();

  /** The buffer saving object for saving output */
00150   SaveBuffer m_SaveOut = new SaveBuffer(m_Log, this);

  /** A panel controlling results viewing */
00153   protected ResultHistoryPanel m_History = new ResultHistoryPanel(m_OutText);

  /** Click to set test mode to generate a % split */
00156   protected JRadioButton m_PercentBut = new JRadioButton("Percentage split");

  /** Click to set test mode to test on training data */
00159   protected JRadioButton m_TrainBut = new JRadioButton("Use training set");

  /** Click to set test mode to a user-specified test set */
00162   protected JRadioButton m_TestSplitBut =
    new JRadioButton("Supplied test set");

  /** Click to set test mode to classes to clusters based evaluation */
00166   protected JRadioButton m_ClassesToClustersBut = 
    new JRadioButton("Classes to clusters evaluation");

  /** Lets the user select the class column for classes to clusters based
      evaluation */
00171   protected JComboBox m_ClassCombo = new JComboBox();

  /** Label by where the % split is entered */
00174   protected JLabel m_PercentLab = new JLabel("%", SwingConstants.RIGHT);

  /** The field where the % split is entered */
00177   protected JTextField m_PercentText = new JTextField("66");

  /** The button used to open a separate test dataset */
00180   protected JButton m_SetTestBut = new JButton("Set...");

  /** The frame used to show the test set selection panel */
00183   protected JFrame m_SetTestFrame;

  /** The button used to popup a list for choosing attributes to ignore while
      clustering */
00187   protected JButton m_ignoreBut = new JButton("Ignore attributes");

  protected DefaultListModel m_ignoreKeyModel = new DefaultListModel();
  protected JList m_ignoreKeyList = new JList(m_ignoreKeyModel);

  //  protected Remove m_ignoreFilter = null;
  
  /**
   * Alters the enabled/disabled status of elements associated with each
   * radio button
   */
00198   ActionListener m_RadioListener = new ActionListener() {
    public void actionPerformed(ActionEvent e) {
      updateRadioLinks();
    }
  };

  /** Click to start running the clusterer */
00205   protected JButton m_StartBut = new JButton("Start");

  /** Stop the class combo from taking up to much space */
00208   private Dimension COMBO_SIZE = new Dimension(250, m_StartBut
                                     .getPreferredSize().height);

  /** Click to stop a running clusterer */
00212   protected JButton m_StopBut = new JButton("Stop");

  /** The main set of instances we're playing with */
00215   protected Instances m_Instances;

  /** The user-supplied test set (if any) */
00218   protected Instances m_TestInstances;

  /** The current visualization object */
00221   protected VisualizePanel m_CurrentVis = null;

  /** Check to save the predictions in the results list for visualizing
      later on */
00225   protected JCheckBox m_StorePredictionsBut = 
    new JCheckBox("Store clusters for visualization");
  
  /** A thread that clustering runs in */
00229   protected Thread m_RunThread;
  
  /** The instances summary panel displayed by m_SetTestFrame */
00232   protected InstancesSummaryPanel m_Summary;

  /** Filter to ensure only model files are selected */  
00235   protected FileFilter m_ModelFilter =
    new ExtensionFileFilter(MODEL_FILE_EXTENSION, "Model object files");

  /** The file chooser for selecting model files */
  protected JFileChooser m_FileChooser 
00240     = new JFileChooser(new File(System.getProperty("user.dir")));

  /* Register the property editors we need */
  static {
     GenericObjectEditor.registerEditors();
  }
  
  /**
   * Creates the clusterer panel
   */
00250   public ClustererPanel() {

    // Connect / configure the components
    m_OutText.setEditable(false);
    m_OutText.setFont(new Font("Monospaced", Font.PLAIN, 12));
    m_OutText.setBorder(BorderFactory.createEmptyBorder(5, 5, 5, 5));
    m_OutText.addMouseListener(new MouseAdapter() {
      public void mouseClicked(MouseEvent e) {
      if ((e.getModifiers() & InputEvent.BUTTON1_MASK)
          != InputEvent.BUTTON1_MASK) {
        m_OutText.selectAll();
      }
      }
    });
    m_History.setBorder(BorderFactory.createTitledBorder("Result list (right-click for options)"));
    m_ClustererEditor.setClassType(Clusterer.class);
    m_ClustererEditor.setValue(ExplorerDefaults.getClusterer());
    m_ClustererEditor.addPropertyChangeListener(new PropertyChangeListener() {
      public void propertyChange(PropertyChangeEvent e) {
      repaint();
      }
    });

    m_TrainBut.setToolTipText("Cluster the same set that the clusterer"
                        + " is trained on");
    m_PercentBut.setToolTipText("Train on a percentage of the data and"
                        + " cluster the remainder");
    m_TestSplitBut.setToolTipText("Cluster a user-specified dataset");
    m_ClassesToClustersBut.setToolTipText("Evaluate clusters with respect to a"
                                +" class");
    m_ClassCombo.setToolTipText("Select the class attribute for class based"
                        +" evaluation");
    m_StartBut.setToolTipText("Starts the clustering");
    m_StopBut.setToolTipText("Stops a running clusterer");
    m_StorePredictionsBut.
      setToolTipText("Store predictions in the result list for later "
                 +"visualization");
    m_ignoreBut.setToolTipText("Ignore attributes during clustering");

    m_FileChooser.setFileFilter(m_ModelFilter);
    m_FileChooser.setFileSelectionMode(JFileChooser.FILES_ONLY);

    m_ClassCombo.setPreferredSize(COMBO_SIZE);
    m_ClassCombo.setMaximumSize(COMBO_SIZE);
    m_ClassCombo.setMinimumSize(COMBO_SIZE);
    m_ClassCombo.setEnabled(false);

    m_PercentBut.setSelected(ExplorerDefaults.getClustererTestMode() == 2);
    m_TrainBut.setSelected(ExplorerDefaults.getClustererTestMode() == 3);
    m_TestSplitBut.setSelected(ExplorerDefaults.getClustererTestMode() == 4);
    m_ClassesToClustersBut.setSelected(ExplorerDefaults.getClustererTestMode() == 5);
    m_StorePredictionsBut.setSelected(ExplorerDefaults.getClustererStoreClustersForVis());
    updateRadioLinks();
    ButtonGroup bg = new ButtonGroup();
    bg.add(m_TrainBut);
    bg.add(m_PercentBut);
    bg.add(m_TestSplitBut);
    bg.add(m_ClassesToClustersBut);
    m_TrainBut.addActionListener(m_RadioListener);
    m_PercentBut.addActionListener(m_RadioListener);
    m_TestSplitBut.addActionListener(m_RadioListener);
    m_ClassesToClustersBut.addActionListener(m_RadioListener);
    m_SetTestBut.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
      setTestSet();
      }
    });

    m_StartBut.setEnabled(false);
    m_StopBut.setEnabled(false);
    m_ignoreBut.setEnabled(false);
    m_StartBut.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
      startClusterer();
      }
    });
    m_StopBut.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
      stopClusterer();
      }
    });

    m_ignoreBut.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
        setIgnoreColumns();
      }
      });
   
    m_History.setHandleRightClicks(false);
    // see if we can popup a menu for the selected result
    m_History.getList().addMouseListener(new MouseAdapter() {
      public void mouseClicked(MouseEvent e) {
        if (((e.getModifiers() & InputEvent.BUTTON1_MASK)
             != InputEvent.BUTTON1_MASK) || e.isAltDown()) {
          int index = m_History.getList().locationToIndex(e.getPoint());
          if (index != -1) {
            String name = m_History.getNameAtIndex(index);
            visualizeClusterer(name, e.getX(), e.getY());
          } else {
            visualizeClusterer(null, e.getX(), e.getY());
          }
        }
      }
      });
    
    m_ClassCombo.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
      updateCapabilitiesFilter(m_ClustererEditor.getCapabilitiesFilter());
      }
    });

    // Layout the GUI
    JPanel p1 = new JPanel();
    p1.setBorder(BorderFactory.createCompoundBorder(
             BorderFactory.createTitledBorder("Clusterer"),
             BorderFactory.createEmptyBorder(0, 5, 5, 5)
             ));
    p1.setLayout(new BorderLayout());
    p1.add(m_CLPanel, BorderLayout.NORTH);

    JPanel p2 = new JPanel();
    GridBagLayout gbL = new GridBagLayout();
    p2.setLayout(gbL);
    p2.setBorder(BorderFactory.createCompoundBorder(
             BorderFactory.createTitledBorder("Cluster mode"),
             BorderFactory.createEmptyBorder(0, 5, 5, 5)
             ));
    GridBagConstraints gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.WEST;
    gbC.gridy = 0;     gbC.gridx = 0;
    gbL.setConstraints(m_TrainBut, gbC);
    p2.add(m_TrainBut);

    gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.WEST;
    gbC.gridy = 1;     gbC.gridx = 0;
    gbL.setConstraints(m_TestSplitBut, gbC);
    p2.add(m_TestSplitBut);

    gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.EAST;
    gbC.fill = GridBagConstraints.HORIZONTAL;
    gbC.gridy = 1;     gbC.gridx = 1;    gbC.gridwidth = 2;
    gbC.insets = new Insets(2, 10, 2, 0);
    gbL.setConstraints(m_SetTestBut, gbC);
    p2.add(m_SetTestBut);

    gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.WEST;
    gbC.gridy = 2;     gbC.gridx = 0;
    gbL.setConstraints(m_PercentBut, gbC);
    p2.add(m_PercentBut);

    gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.EAST;
    gbC.fill = GridBagConstraints.HORIZONTAL;
    gbC.gridy = 2;     gbC.gridx = 1;
    gbC.insets = new Insets(2, 10, 2, 10);
    gbL.setConstraints(m_PercentLab, gbC);
    p2.add(m_PercentLab);

    gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.EAST;
    gbC.fill = GridBagConstraints.HORIZONTAL;
    gbC.gridy = 2;     gbC.gridx = 2;  gbC.weightx = 100;
    gbC.ipadx = 20;
    gbL.setConstraints(m_PercentText, gbC);
    p2.add(m_PercentText);

    gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.WEST;
    gbC.gridy = 3;     gbC.gridx = 0;  gbC.gridwidth = 2;
    gbL.setConstraints(m_ClassesToClustersBut, gbC);
    p2.add(m_ClassesToClustersBut);

    m_ClassCombo.setBorder(BorderFactory.createEmptyBorder(0, 20, 0, 0));
    gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.WEST;
    gbC.gridy = 4;     gbC.gridx = 0;  gbC.gridwidth = 2;
    gbL.setConstraints(m_ClassCombo, gbC);
    p2.add(m_ClassCombo);

    gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.WEST;
    gbC.gridy = 5;     gbC.gridx = 0;  gbC.gridwidth = 2;
    gbL.setConstraints(m_StorePredictionsBut, gbC);
    p2.add(m_StorePredictionsBut);

    JPanel buttons = new JPanel();
    buttons.setLayout(new GridLayout(2, 1));
    JPanel ssButs = new JPanel();
    ssButs.setBorder(BorderFactory.createEmptyBorder(5, 5, 5, 5));
    ssButs.setLayout(new GridLayout(1, 2, 5, 5));
    ssButs.add(m_StartBut);
    ssButs.add(m_StopBut);

    JPanel ib = new JPanel();
    ib.setBorder(BorderFactory.createEmptyBorder(5, 5, 5, 5));
    ib.setLayout(new GridLayout(1, 1, 5, 5));
    ib.add(m_ignoreBut);
    buttons.add(ib);
    buttons.add(ssButs);
    
    JPanel p3 = new JPanel();
    p3.setBorder(BorderFactory.createTitledBorder("Clusterer output"));
    p3.setLayout(new BorderLayout());
    final JScrollPane js = new JScrollPane(m_OutText);
    p3.add(js, BorderLayout.CENTER);
    js.getViewport().addChangeListener(new ChangeListener() {
      private int lastHeight;
      public void stateChanged(ChangeEvent e) {
      JViewport vp = (JViewport)e.getSource();
      int h = vp.getViewSize().height; 
      if (h != lastHeight) { // i.e. an addition not just a user scrolling
        lastHeight = h;
        int x = h - vp.getExtentSize().height;
        vp.setViewPosition(new Point(0, x));
      }
      }
    });    

    JPanel mondo = new JPanel();
    gbL = new GridBagLayout();
    mondo.setLayout(gbL);
    gbC = new GridBagConstraints();
    //    gbC.anchor = GridBagConstraints.WEST;
    gbC.fill = GridBagConstraints.HORIZONTAL;
    gbC.gridy = 0;     gbC.gridx = 0;
    gbL.setConstraints(p2, gbC);
    mondo.add(p2);
    gbC = new GridBagConstraints();
    gbC.anchor = GridBagConstraints.NORTH;
    gbC.fill = GridBagConstraints.HORIZONTAL;
    gbC.gridy = 1;     gbC.gridx = 0;
    gbL.setConstraints(buttons, gbC);
    mondo.add(buttons);
    gbC = new GridBagConstraints();
    //gbC.anchor = GridBagConstraints.NORTH;
    gbC.fill = GridBagConstraints.BOTH;
    gbC.gridy = 2;     gbC.gridx = 0; gbC.weightx = 0;
    gbL.setConstraints(m_History, gbC);
    mondo.add(m_History);
    gbC = new GridBagConstraints();
    gbC.fill = GridBagConstraints.BOTH;
    gbC.gridy = 0;     gbC.gridx = 1;
    gbC.gridheight = 3;
    gbC.weightx = 100; gbC.weighty = 100;
    gbL.setConstraints(p3, gbC);
    mondo.add(p3);

    setLayout(new BorderLayout());
    add(p1, BorderLayout.NORTH);
    add(mondo, BorderLayout.CENTER);
  }
  
  /**
   * Updates the enabled status of the input fields and labels.
   */
00508   protected void updateRadioLinks() {
    
    m_SetTestBut.setEnabled(m_TestSplitBut.isSelected());
    if ((m_SetTestFrame != null) && (!m_TestSplitBut.isSelected())) {
      m_SetTestFrame.setVisible(false);
    }
    m_PercentText.setEnabled(m_PercentBut.isSelected());
    m_PercentLab.setEnabled(m_PercentBut.isSelected());
    m_ClassCombo.setEnabled(m_ClassesToClustersBut.isSelected());
  }

  /**
   * Sets the Logger to receive informational messages
   *
   * @param newLog the Logger that will now get info messages
   */
00524   public void setLog(Logger newLog) {

    m_Log = newLog;
  }

  /**
   * Tells the panel to use a new set of instances.
   *
   * @param inst a set of Instances
   */
00534   public void setInstances(Instances inst) {

    m_Instances = inst;
   
    m_ignoreKeyModel.removeAllElements();
    
    String [] attribNames = new String [m_Instances.numAttributes()];
    for (int i = 0; i < m_Instances.numAttributes(); i++) {
      String name = m_Instances.attribute(i).name();
      m_ignoreKeyModel.addElement(name);

       String type = "";
      switch (m_Instances.attribute(i).type()) {
      case Attribute.NOMINAL:
      type = "(Nom) ";
      break;
      case Attribute.NUMERIC:
      type = "(Num) ";
      break;
      case Attribute.STRING:
      type = "(Str) ";
      break;
      case Attribute.DATE:
      type = "(Dat) ";
      break;
      case Attribute.RELATIONAL:
      type = "(Rel) ";
      break;
      default:
      type = "(???) ";
      }
      String attnm = m_Instances.attribute(i).name();
     
      attribNames[i] = type + attnm;
    }

    
    m_StartBut.setEnabled(m_RunThread == null);
    m_StopBut.setEnabled(m_RunThread != null);
    m_ignoreBut.setEnabled(true);
    m_ClassCombo.setModel(new DefaultComboBoxModel(attribNames));
    if (inst.classIndex() == -1)
      m_ClassCombo.setSelectedIndex(attribNames.length - 1);
    else
      m_ClassCombo.setSelectedIndex(inst.classIndex());
    updateRadioLinks();
  }

  /**
   * Sets the user test set. Information about the current test set
   * is displayed in an InstanceSummaryPanel and the user is given the
   * ability to load another set from a file or url.
   *
   */
00588   protected void setTestSet() {

    if (m_SetTestFrame == null) {
      final SetInstancesPanel sp = new SetInstancesPanel();
      sp.setReadIncrementally(false);
      m_Summary = sp.getSummary();
      if (m_TestInstances != null) {
      sp.setInstances(m_TestInstances);
      }
      sp.addPropertyChangeListener(new PropertyChangeListener() {
      public void propertyChange(PropertyChangeEvent e) {
        m_TestInstances = sp.getInstances();
        m_TestInstances.setClassIndex(-1);  // make sure that no class attribute is set!
      }
      });
      // Add propertychangelistener to update m_TestInstances whenever
      // it changes in the settestframe
      m_SetTestFrame = new JFrame("Test Instances");
      sp.setParentFrame(m_SetTestFrame);   // enable Close-Button
      m_SetTestFrame.getContentPane().setLayout(new BorderLayout());
      m_SetTestFrame.getContentPane().add(sp, BorderLayout.CENTER);
      m_SetTestFrame.pack();
    }
    m_SetTestFrame.setVisible(true);
  }

  /**
   * Sets up the structure for the visualizable instances. This dataset
   * contains the original attributes plus the clusterer's cluster assignments
   * @param testInstances the instances that the clusterer has clustered
   * @param eval the evaluation to use
   * @return a PlotData2D object encapsulating the visualizable instances. The    
   * instances contain one more attribute (predicted
   * cluster) than the testInstances
   */
00623   public static PlotData2D setUpVisualizableInstances(Instances testInstances,
                                          ClusterEvaluation eval) 
    throws Exception {

    int numClusters = eval.getNumClusters();
    double [] clusterAssignments = eval.getClusterAssignments();

    FastVector hv = new FastVector();
    Instances newInsts;

    Attribute predictedCluster;
    FastVector clustVals = new FastVector();

    for (int i = 0; i < numClusters; i++) {
      clustVals.addElement("cluster"+i);
    }
    predictedCluster = new Attribute("Cluster", clustVals);
    for (int i = 0; i < testInstances.numAttributes(); i++) {
      hv.addElement(testInstances.attribute(i).copy());
    }
    hv.addElement(predictedCluster);
    
    newInsts = new Instances(testInstances.relationName()+"_clustered", hv, 
                       testInstances.numInstances());

    double [] values;
    int j;
    int [] pointShapes = null;
    int [] classAssignments = null;
    if (testInstances.classIndex() >= 0) {
      classAssignments = eval.getClassesToClusters();
      pointShapes = new int[testInstances.numInstances()];
      for (int i = 0; i < testInstances.numInstances(); i++) {
      pointShapes[i] = Plot2D.CONST_AUTOMATIC_SHAPE;
      }
    }

    for (int i = 0; i < testInstances.numInstances(); i++) {
      values = new double[newInsts.numAttributes()];
      for (j = 0; j < testInstances.numAttributes(); j++) {
      values[j] = testInstances.instance(i).value(j);
      }
      values[j] = clusterAssignments[i];
      newInsts.add(new Instance(1.0, values));
      if (pointShapes != null) {
      if ((int)testInstances.instance(i).classValue() != 
          classAssignments[(int)clusterAssignments[i]]) {
        pointShapes[i] = Plot2D.ERROR_SHAPE;
      }
      }
    }
    PlotData2D plotData = new PlotData2D(newInsts);
    if (pointShapes != null) {
      plotData.setShapeType(pointShapes);
    }
    plotData.addInstanceNumberAttribute();
    return plotData;
  }
  
  /**
   * Starts running the currently configured clusterer with the current
   * settings. This is run in a separate thread, and will only start if
   * there is no clusterer already running. The clusterer output is sent
   * to the results history panel.
   */
00688   protected void startClusterer() {

    if (m_RunThread == null) {
      m_StartBut.setEnabled(false);
      m_StopBut.setEnabled(true);
      m_ignoreBut.setEnabled(false);
      m_RunThread = new Thread() {
      public void run() {
        // Copy the current state of things
        m_Log.statusMessage("Setting up...");
        Instances inst = new Instances(m_Instances);
        inst.setClassIndex(-1);
        Instances userTest = null;
        PlotData2D predData = null;
        if (m_TestInstances != null) {
          userTest = new Instances(m_TestInstances);
        }
        
        boolean saveVis = m_StorePredictionsBut.isSelected();
        String grph = null;
        int[] ignoredAtts = null;

        int testMode = 0;
        int percent = 66;
        Clusterer clusterer = (Clusterer) m_ClustererEditor.getValue();
        Clusterer fullClusterer = null;
        StringBuffer outBuff = new StringBuffer();
        String name = (new SimpleDateFormat("HH:mm:ss - "))
        .format(new Date());
        String cname = clusterer.getClass().getName();
        if (cname.startsWith("weka.clusterers.")) {
          name += cname.substring("weka.clusterers.".length());
        } else {
          name += cname;
        }
          String cmd = m_ClustererEditor.getValue().getClass().getName();
          if (m_ClustererEditor.getValue() instanceof OptionHandler)
            cmd += " " + Utils.joinOptions(((OptionHandler) m_ClustererEditor.getValue()).getOptions());
        try {
          m_Log.logMessage("Started " + cname);
          m_Log.logMessage("Command: " + cmd);
          if (m_Log instanceof TaskLogger) {
            ((TaskLogger)m_Log).taskStarted();
          }
          if (m_PercentBut.isSelected()) {
            testMode = 2;
            percent = Integer.parseInt(m_PercentText.getText());
            if ((percent <= 0) || (percent >= 100)) {
            throw new Exception("Percentage must be between 0 and 100");
            }
          } else if (m_TrainBut.isSelected()) {
            testMode = 3;
          } else if (m_TestSplitBut.isSelected()) {
            testMode = 4;
            // Check the test instance compatibility
            if (userTest == null) {
            throw new Exception("No user test set has been opened");
            }
            if (!inst.equalHeaders(userTest)) {
            throw new Exception("Train and test set are not compatible");
            }
          } else if (m_ClassesToClustersBut.isSelected()) {
            testMode = 5;
          } else {
            throw new Exception("Unknown test mode");
          }

          Instances trainInst = new Instances(inst);
          if (m_ClassesToClustersBut.isSelected()) {
            trainInst.setClassIndex(m_ClassCombo.getSelectedIndex());
            inst.setClassIndex(m_ClassCombo.getSelectedIndex());
            if (inst.classAttribute().isNumeric()) {
            throw new Exception("Class must be nominal for class based "
                            +"evaluation!");
            }
          }
          if (!m_ignoreKeyList.isSelectionEmpty()) {
            trainInst = removeIgnoreCols(trainInst);
          }

          // Output some header information
          outBuff.append("=== Run information ===\n\n");
          outBuff.append("Scheme:       " + cname);
          if (clusterer instanceof OptionHandler) {
            String [] o = ((OptionHandler) clusterer).getOptions();
            outBuff.append(" " + Utils.joinOptions(o));
          }
          outBuff.append("\n");
          outBuff.append("Relation:     " + inst.relationName() + '\n');
          outBuff.append("Instances:    " + inst.numInstances() + '\n');
          outBuff.append("Attributes:   " + inst.numAttributes() + '\n');
          if (inst.numAttributes() < 100) {
            boolean [] selected = new boolean [inst.numAttributes()];
            for (int i = 0; i < inst.numAttributes(); i++) {
            selected[i] = true;
            }
            if (!m_ignoreKeyList.isSelectionEmpty()) {
            int [] indices = m_ignoreKeyList.getSelectedIndices();
            for (int i = 0; i < indices.length; i++) {
              selected[indices[i]] = false;
            }
            }
            if (m_ClassesToClustersBut.isSelected()) {
            selected[m_ClassCombo.getSelectedIndex()] = false;
            }
            for (int i = 0; i < inst.numAttributes(); i++) {
            if (selected[i]) {
              outBuff.append("              " + inst.attribute(i).name()
                         + '\n');
            }
            }
            if (!m_ignoreKeyList.isSelectionEmpty() 
              || m_ClassesToClustersBut.isSelected()) {
            outBuff.append("Ignored:\n");
            for (int i = 0; i < inst.numAttributes(); i++) {
              if (!selected[i]) {
                outBuff.append("              " + inst.attribute(i).name()
                           + '\n');
              }
            }
            }
          } else {
            outBuff.append("              [list of attributes omitted]\n");
          }

          if (!m_ignoreKeyList.isSelectionEmpty()) {
            ignoredAtts = m_ignoreKeyList.getSelectedIndices();
          }

          if (m_ClassesToClustersBut.isSelected()) {
            // add class to ignored list
            if (ignoredAtts == null) {
            ignoredAtts = new int[1];
            ignoredAtts[0] = m_ClassCombo.getSelectedIndex();
            } else {
            int[] newIgnoredAtts = new int[ignoredAtts.length+1];
            System.arraycopy(ignoredAtts, 0, newIgnoredAtts, 0, ignoredAtts.length);
            newIgnoredAtts[ignoredAtts.length] = m_ClassCombo.getSelectedIndex();
            ignoredAtts = newIgnoredAtts;
            }
          }


          outBuff.append("Test mode:    ");
          switch (testMode) {
            case 3: // Test on training
            outBuff.append("evaluate on training data\n");
            break;
            case 2: // Percent split
            outBuff.append("split " + percent
                         + "% train, remainder test\n");
            break;
            case 4: // Test on user split
            outBuff.append("user supplied test set: "
                       + userTest.numInstances() + " instances\n");
            break;
          case 5: // Classes to clusters evaluation on training
            outBuff.append("Classes to clusters evaluation on training data");
            
            break;
          }
          outBuff.append("\n");
          m_History.addResult(name, outBuff);
          m_History.setSingle(name);
          
          // Build the model and output it.
          m_Log.statusMessage("Building model on training data...");

          // remove the class attribute (if set) and build the clusterer
          clusterer.buildClusterer(removeClass(trainInst));
          
          if (testMode == 2) {
            outBuff.append("\n=== Clustering model (full training set) ===\n\n");
          
            outBuff.append(clusterer.toString() + '\n');
          }
          m_History.updateResult(name);
          if (clusterer instanceof Drawable) {
            try {
            grph = ((Drawable)clusterer).graph();
            } catch (Exception ex) {
            }
          }
          // copy full model for output
          SerializedObject so = new SerializedObject(clusterer);
          fullClusterer = (Clusterer) so.getObject();
          
          ClusterEvaluation eval = new ClusterEvaluation();
          eval.setClusterer(clusterer);
          switch (testMode) {
            case 3: case 5: // Test on training
            m_Log.statusMessage("Clustering training data...");
            eval.evaluateClusterer(trainInst);
            predData = setUpVisualizableInstances(inst,eval);
            outBuff.append("=== Model and evaluation on training set ===\n\n");
            break;

            case 2: // Percent split
            m_Log.statusMessage("Randomizing instances...");
            inst.randomize(new Random(1));
            trainInst.randomize(new Random(1));
            int trainSize = trainInst.numInstances() * percent / 100;
            int testSize = trainInst.numInstances() - trainSize;
            Instances train = new Instances(trainInst, 0, trainSize);
            Instances test = new Instances(trainInst, trainSize, testSize);
            Instances testVis = new Instances(inst, trainSize, testSize);
            m_Log.statusMessage("Building model on training split...");
            clusterer.buildClusterer(train);
            m_Log.statusMessage("Evaluating on test split...");
            eval.evaluateClusterer(test);
            predData = setUpVisualizableInstances(testVis, eval);
            outBuff.append("=== Model and evaluation on test split ===\n");
            break;
            
            case 4: // Test on user split
            m_Log.statusMessage("Evaluating on test data...");
            Instances userTestT = new Instances(userTest);
            if (!m_ignoreKeyList.isSelectionEmpty()) {
            userTestT = removeIgnoreCols(userTestT);
            }
            eval.evaluateClusterer(userTestT);
            predData = setUpVisualizableInstances(userTest, eval);
            outBuff.append("=== Model and evaluation on test set ===\n");
            break;

            default:
            throw new Exception("Test mode not implemented");
          }
          outBuff.append(eval.clusterResultsToString());
          outBuff.append("\n");
          m_History.updateResult(name);
          m_Log.logMessage("Finished " + cname);
          m_Log.statusMessage("OK");
        } catch (Exception ex) {
          ex.printStackTrace();
          m_Log.logMessage(ex.getMessage());
          JOptionPane.showMessageDialog(ClustererPanel.this,
                                "Problem evaluating clusterer:\n"
                                + ex.getMessage(),
                                "Evaluate clusterer",
                                JOptionPane.ERROR_MESSAGE);
          m_Log.statusMessage("Problem evaluating clusterer");
        } finally {
          if (predData != null) {
            m_CurrentVis = new VisualizePanel();
            m_CurrentVis.setName(name+" ("+inst.relationName()+")");
            m_CurrentVis.setLog(m_Log);
            predData.setPlotName(name+" ("+inst.relationName()+")");
            
            try {
            m_CurrentVis.addPlot(predData);
            } catch (Exception ex) {
            System.err.println(ex);
            }

            FastVector vv = new FastVector();
            vv.addElement(fullClusterer);
            Instances trainHeader = new Instances(m_Instances, 0);
            vv.addElement(trainHeader);
            if (ignoredAtts != null) vv.addElement(ignoredAtts);
            if (saveVis) {
            vv.addElement(m_CurrentVis);
            if (grph != null) {
              vv.addElement(grph);
            }
            
            }
            m_History.addObject(name, vv);
          }
          if (isInterrupted()) {
            m_Log.logMessage("Interrupted " + cname);
            m_Log.statusMessage("See error log");
          }
          m_RunThread = null;
          m_StartBut.setEnabled(true);
          m_StopBut.setEnabled(false);
          m_ignoreBut.setEnabled(true);
          if (m_Log instanceof TaskLogger) {
            ((TaskLogger)m_Log).taskFinished();
          }
        }
      }
      };
      m_RunThread.setPriority(Thread.MIN_PRIORITY);
      m_RunThread.start();
    }
  }

  private Instances removeClass(Instances inst) {
    Remove af = new Remove();
    Instances retI = null;
    
    try {
      if (inst.classIndex() < 0) {
      retI = inst;
      } else {
      af.setAttributeIndices(""+(inst.classIndex()+1));
      af.setInvertSelection(false);
      af.setInputFormat(inst);
      retI = Filter.useFilter(inst, af);
      }
    } catch (Exception e) {
      e.printStackTrace();
    }
    return retI;
  }

  private Instances removeIgnoreCols(Instances inst) {
    
    // If the user is doing classes to clusters evaluation and
    // they have opted to ignore the class, then unselect the class in
    // the ignore list
    if (m_ClassesToClustersBut.isSelected()) {
      int classIndex = m_ClassCombo.getSelectedIndex();
      if (m_ignoreKeyList.isSelectedIndex(classIndex)) {
      m_ignoreKeyList.removeSelectionInterval(classIndex, classIndex);
      }
    }
    int [] selected = m_ignoreKeyList.getSelectedIndices();
    Remove af = new Remove();
    Instances retI = null;

    try {
      af.setAttributeIndicesArray(selected);
      af.setInvertSelection(false);
      af.setInputFormat(inst);
      retI = Filter.useFilter(inst, af);
    } catch (Exception e) {
      e.printStackTrace();
    }
    
    return retI;
  }

  private Instances removeIgnoreCols(Instances inst, int[] toIgnore) {

    Remove af = new Remove();
    Instances retI = null;

    try {
      af.setAttributeIndicesArray(toIgnore);
      af.setInvertSelection(false);
      af.setInputFormat(inst);
      retI = Filter.useFilter(inst, af);
    } catch (Exception e) {
      e.printStackTrace();
    }
    
    return retI;
  }

  /**
   * Stops the currently running clusterer (if any).
   */
01042   protected void stopClusterer() {

    if (m_RunThread != null) {
      m_RunThread.interrupt();
      
      // This is deprecated (and theoretically the interrupt should do).
      m_RunThread.stop();
      
    }
  }

  /**
   * Pops up a TreeVisualizer for the clusterer from the currently
   * selected item in the results list
   * @param dottyString the description of the tree in dotty format
   * @param treeName the title to assign to the display
   */
01059   protected void visualizeTree(String dottyString, String treeName) {
    final javax.swing.JFrame jf = 
      new javax.swing.JFrame("Weka Classifier Tree Visualizer: "+treeName);
    jf.setSize(500,400);
    jf.getContentPane().setLayout(new BorderLayout());
    TreeVisualizer tv = new TreeVisualizer(null,
                                 dottyString,
                                 new PlaceNode2());
    jf.getContentPane().add(tv, BorderLayout.CENTER);
    jf.addWindowListener(new java.awt.event.WindowAdapter() {
      public void windowClosing(java.awt.event.WindowEvent e) {
        jf.dispose();
      }
      });
    
    jf.setVisible(true);
    tv.fitToScreen();
  }

  /**
   * Pops up a visualize panel to display cluster assignments
   * @param sp the visualize panel to display
   */
01082   protected void visualizeClusterAssignments(VisualizePanel sp) {
    if (sp != null) {
      String plotName = sp.getName();
      final javax.swing.JFrame jf = 
      new javax.swing.JFrame("Weka Clusterer Visualize: "+plotName);
      jf.setSize(500,400);
      jf.getContentPane().setLayout(new BorderLayout());
      jf.getContentPane().add(sp, BorderLayout.CENTER);
      jf.addWindowListener(new java.awt.event.WindowAdapter() {
        public void windowClosing(java.awt.event.WindowEvent e) {
          jf.dispose();
        }
      });

      jf.setVisible(true);
    }
  }

  /**
   * Handles constructing a popup menu with visualization options
   * @param name the name of the result history list entry clicked on by
   * the user
   * @param x the x coordinate for popping up the menu
   * @param y the y coordinate for popping up the menu
   */
01107   protected void visualizeClusterer(String name, int x, int y) {
    final String selectedName = name;
    JPopupMenu resultListMenu = new JPopupMenu();

    JMenuItem visMainBuffer = new JMenuItem("View in main window");
    if (selectedName != null) {
      visMainBuffer.addActionListener(new ActionListener() {
        public void actionPerformed(ActionEvent e) {
          m_History.setSingle(selectedName);
        }
      });
    } else {
      visMainBuffer.setEnabled(false);
    }
    resultListMenu.add(visMainBuffer);

    JMenuItem visSepBuffer = new JMenuItem("View in separate window");
    if (selectedName != null) {
    visSepBuffer.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
        m_History.openFrame(selectedName);
      }
      });
    } else {
      visSepBuffer.setEnabled(false);
    }
    resultListMenu.add(visSepBuffer);

    JMenuItem saveOutput = new JMenuItem("Save result buffer");
    if (selectedName != null) {
      saveOutput.addActionListener(new ActionListener() {
        public void actionPerformed(ActionEvent e) {
          saveBuffer(selectedName);
        }
      });
    } else {
      saveOutput.setEnabled(false);
    }
    resultListMenu.add(saveOutput);
    
    JMenuItem deleteOutput = new JMenuItem("Delete result buffer");
    if (selectedName != null) {
      deleteOutput.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
        m_History.removeResult(selectedName);
      }
      });
    } else {
      deleteOutput.setEnabled(false);
    }
    resultListMenu.add(deleteOutput);

    resultListMenu.addSeparator();

    JMenuItem loadModel = new JMenuItem("Load model");
    loadModel.addActionListener(new ActionListener() {
      public void actionPerformed(ActionEvent e) {
        loadClusterer();
      }
      });
    resultListMenu.add(loadModel);

    FastVector o = null;
    if (selectedName != null) {
      o = (FastVector)m_History.getNamedObject(selectedName);
    }

    VisualizePanel temp_vp = null;
    String temp_grph = null;
    Clusterer temp_clusterer = null;
    Instances temp_trainHeader = null;
    int[] temp_ignoreAtts = null;
    
    if (o != null) {
      for (int i = 0; i < o.size(); i++) {
      Object temp = o.elementAt(i);
      if (temp instanceof Clusterer) {
        temp_clusterer = (Clusterer)temp;
      } else if (temp instanceof Instances) { // training header
        temp_trainHeader = (Instances)temp;
      } else if (temp instanceof int[]) { // ignored attributes
        temp_ignoreAtts = (int[])temp;
      } else if (temp instanceof VisualizePanel) { // normal errors
        temp_vp = (VisualizePanel)temp;
      } else if (temp instanceof String) { // graphable output
        temp_grph = (String)temp;
      }
      } 
    }
      
    final VisualizePanel vp = temp_vp;
    final String grph = temp_grph;
    final Clusterer clusterer = temp_clusterer;
    final Instances trainHeader = temp_trainHeader;
    final int[] ignoreAtts = temp_ignoreAtts;
    
    JMenuItem saveModel = new JMenuItem("Save model");
    if (clusterer != null) {
      saveModel.addActionListener(new ActionListener() {
        public void actionPerformed(ActionEvent e) {
          saveClusterer(selectedName, clusterer, trainHeader, ignoreAtts);
        }
      });
    } else {
      saveModel.setEnabled(false);
    }
    resultListMenu.add(saveModel);
    
    JMenuItem reEvaluate =
      new JMenuItem("Re-evaluate model on current test set");
    if (clusterer != null && m_TestInstances != null) {
      reEvaluate.addActionListener(new ActionListener() {
        public void actionPerformed(ActionEvent e) {
          reevaluateModel(selectedName, clusterer, trainHeader, ignoreAtts);
        }
      }); 
    } else {
      reEvaluate.setEnabled(false);
    }
    resultListMenu.add(reEvaluate);
    
    resultListMenu.addSeparator();
    
    JMenuItem visClusts = new JMenuItem("Visualize cluster assignments");
    if (vp != null) {
      visClusts.addActionListener(new ActionListener() {
          public void actionPerformed(ActionEvent e) {
            visualizeClusterAssignments(vp);
          }
        });
      
    } else {
      visClusts.setEnabled(false);
    }
    resultListMenu.add(visClusts);

    JMenuItem visTree = new JMenuItem("Visualize tree");
    if (grph != null) {
      visTree.addActionListener(new ActionListener() {
        public void actionPerformed(ActionEvent e) {
          String title;
          if (vp != null) title = vp.getName();
          else title = selectedName;
          visualizeTree(grph, title);
        }
      });
    } else {
      visTree.setEnabled(false);
    }
    resultListMenu.add(visTree);

    resultListMenu.show(m_History.getList(), x, y);
  }
  
  /**
   * Save the currently selected clusterer output to a file.
   * @param name the name of the buffer to save
   */
01265   protected void saveBuffer(String name) {
    StringBuffer sb = m_History.getNamedBuffer(name);
    if (sb != null) {
      if (m_SaveOut.save(sb)) {
      m_Log.logMessage("Save successful.");
      }
    }
  }

  private void setIgnoreColumns() {
    ListSelectorDialog jd = new ListSelectorDialog(null, m_ignoreKeyList);

    // Open the dialog
    int result = jd.showDialog();
    
    if (result != ListSelectorDialog.APPROVE_OPTION) {
      // clear selected indices
      m_ignoreKeyList.clearSelection();
    }
  }

  /**
   * Saves the currently selected clusterer
   */
01289   protected void saveClusterer(String name, Clusterer clusterer,
                         Instances trainHeader, int[] ignoredAtts) {

    File sFile = null;
    boolean saveOK = true;

    int returnVal = m_FileChooser.showSaveDialog(this);
    if (returnVal == JFileChooser.APPROVE_OPTION) {
      sFile = m_FileChooser.getSelectedFile();
      if (!sFile.getName().toLowerCase().endsWith(MODEL_FILE_EXTENSION)) {
      sFile = new File(sFile.getParent(), sFile.getName() 
                   + MODEL_FILE_EXTENSION);
      }
      m_Log.statusMessage("Saving model to file...");
      
      try {
      OutputStream os = new FileOutputStream(sFile);
      if (sFile.getName().endsWith(".gz")) {
        os = new GZIPOutputStream(os);
      }
      ObjectOutputStream objectOutputStream = new ObjectOutputStream(os);
      objectOutputStream.writeObject(clusterer);
      if (trainHeader != null) objectOutputStream.writeObject(trainHeader);
      if (ignoredAtts != null) objectOutputStream.writeObject(ignoredAtts);
      objectOutputStream.flush();
      objectOutputStream.close();
      } catch (Exception e) {
      
      JOptionPane.showMessageDialog(null, e, "Save Failed",
                              JOptionPane.ERROR_MESSAGE);
      saveOK = false;
      }
      if (saveOK)
      m_Log.logMessage("Saved model (" + name
                   + ") to file '" + sFile.getName() + "'");
      m_Log.statusMessage("OK");
    }
  }

  /**
   * Loads a clusterer
   */
01331   protected void loadClusterer() {

    int returnVal = m_FileChooser.showOpenDialog(this);
    if (returnVal == JFileChooser.APPROVE_OPTION) {
      File selected = m_FileChooser.getSelectedFile();
      Clusterer clusterer = null;
      Instances trainHeader = null;
      int[] ignoredAtts = null;

      m_Log.statusMessage("Loading model from file...");

      try {
      InputStream is = new FileInputStream(selected);
      if (selected.getName().endsWith(".gz")) {
        is = new GZIPInputStream(is);
      }
      ObjectInputStream objectInputStream = new ObjectInputStream(is);
      clusterer = (Clusterer) objectInputStream.readObject();
      try { // see if we can load the header & ignored attribute info
        trainHeader = (Instances) objectInputStream.readObject();
        ignoredAtts = (int[]) objectInputStream.readObject();
      } catch (Exception e) {} // don't fuss if we can't
      objectInputStream.close();
      } catch (Exception e) {
      
      JOptionPane.showMessageDialog(null, e, "Load Failed",
                              JOptionPane.ERROR_MESSAGE);
      }     

      m_Log.statusMessage("OK");
      
      if (clusterer != null) {
      m_Log.logMessage("Loaded model from file '" + selected.getName()+ "'");
      String name = (new SimpleDateFormat("HH:mm:ss - ")).format(new Date());
      String cname = clusterer.getClass().getName();
      if (cname.startsWith("weka.clusterers."))
        cname = cname.substring("weka.clusterers.".length());
      name += cname + " from file '" + selected.getName() + "'";
      StringBuffer outBuff = new StringBuffer();

      outBuff.append("=== Model information ===\n\n");
      outBuff.append("Filename:     " + selected.getName() + "\n");
      outBuff.append("Scheme:       " + clusterer.getClass().getName());
      if (clusterer instanceof OptionHandler) {
        String [] o = ((OptionHandler) clusterer).getOptions();
        outBuff.append(" " + Utils.joinOptions(o));
      }
      outBuff.append("\n");

      if (trainHeader != null) {

        outBuff.append("Relation:     " + trainHeader.relationName() + '\n');
        outBuff.append("Attributes:   " + trainHeader.numAttributes() + '\n');
        if (trainHeader.numAttributes() < 100) {
          boolean [] selectedAtts = new boolean [trainHeader.numAttributes()];
          for (int i = 0; i < trainHeader.numAttributes(); i++) {
            selectedAtts[i] = true;
          }
          
          if (ignoredAtts != null)
            for (int i=0; i<ignoredAtts.length; i++)
            selectedAtts[ignoredAtts[i]] = false;
         
          for (int i = 0; i < trainHeader.numAttributes(); i++) {
            if (selectedAtts[i]) {
            outBuff.append("              " + trainHeader.attribute(i).name()
                         + '\n');
            }
          }
          if (ignoredAtts != null) {
            outBuff.append("Ignored:\n");
            for (int i=0; i<ignoredAtts.length; i++)
            outBuff.append("              "
                         + trainHeader.attribute(ignoredAtts[i]).name()
                         + '\n');
          }
        } else {
          outBuff.append("              [list of attributes omitted]\n");
        }
      } else {
        outBuff.append("\nTraining data unknown\n");
      } 
      
      outBuff.append("\n=== Clustering model ===\n\n");
      outBuff.append(clusterer.toString() + "\n");

      m_History.addResult(name, outBuff);
      m_History.setSingle(name);
      FastVector vv = new FastVector();
      vv.addElement(clusterer);
      if (trainHeader != null) vv.addElement(trainHeader);
      if (ignoredAtts != null) vv.addElement(ignoredAtts);
      // allow visualization of graphable classifiers
      String grph = null;
      if (clusterer instanceof Drawable) {
        try {
          grph = ((Drawable)clusterer).graph();
        } catch (Exception ex) {
        }
      }
      if (grph != null) vv.addElement(grph);
      
      m_History.addObject(name, vv);
      
      }
    }
  }

  /**
   * Re-evaluates the named clusterer with the current test set. Unpredictable
   * things will happen if the data set is not compatible with the clusterer.
   *
   * @param name the name of the clusterer entry
   * @param clusterer the clusterer to evaluate
   * @param trainHeader the header of the training set
   * @param ignoredAtts ignored attributes
   */
01448   protected void reevaluateModel(final String name, 
                                 final Clusterer clusterer,
                         final Instances trainHeader, 
                                 final int[] ignoredAtts) {

    if (m_RunThread == null) {
      m_StartBut.setEnabled(false);
      m_StopBut.setEnabled(true);
      m_ignoreBut.setEnabled(false);
      m_RunThread = new Thread() {
          public void run() {
            // Copy the current state of things
            m_Log.statusMessage("Setting up...");

            StringBuffer outBuff = m_History.getNamedBuffer(name);
            Instances userTest = null;

            PlotData2D predData = null;
            if (m_TestInstances != null) {
              userTest = new Instances(m_TestInstances);
            }
    
            boolean saveVis = m_StorePredictionsBut.isSelected();
            String grph = null;

            try {
              if (userTest == null) {
                throw new Exception("No user test set has been opened");
              }
              if (trainHeader != null && !trainHeader.equalHeaders(userTest)) {
                throw new Exception("Train and test set are not compatible");
              }

              m_Log.statusMessage("Evaluating on test data...");
              m_Log.logMessage("Re-evaluating clusterer (" + name + ") on test set");

              m_Log.logMessage("Started reevaluate model");
              if (m_Log instanceof TaskLogger) {
                ((TaskLogger)m_Log).taskStarted();
              }
              ClusterEvaluation eval = new ClusterEvaluation();
              eval.setClusterer(clusterer);
    
              Instances userTestT = new Instances(userTest);
              if (ignoredAtts != null) {
                userTestT = removeIgnoreCols(userTestT, ignoredAtts);
              }

              eval.evaluateClusterer(userTestT);
      
              predData = setUpVisualizableInstances(userTest, eval);

              outBuff.append("\n=== Re-evaluation on test set ===\n\n");
              outBuff.append("User supplied test set\n");  
              outBuff.append("Relation:     " + userTest.relationName() + '\n');
              outBuff.append("Instances:    " + userTest.numInstances() + '\n');
              outBuff.append("Attributes:   " + userTest.numAttributes() + "\n\n");
              if (trainHeader == null)
                outBuff.append("NOTE - if test set is not compatible then results are "
                               + "unpredictable\n\n");
      
              outBuff.append(eval.clusterResultsToString());
              outBuff.append("\n");
              m_History.updateResult(name);
              m_Log.logMessage("Finished re-evaluation");
              m_Log.statusMessage("OK");
            } catch (Exception ex) {
              ex.printStackTrace();
              m_Log.logMessage(ex.getMessage());
              JOptionPane.showMessageDialog(ClustererPanel.this,
                                            "Problem evaluating clusterer:\n"
                                            + ex.getMessage(),
                                            "Evaluate clusterer",
                                            JOptionPane.ERROR_MESSAGE);
              m_Log.statusMessage("Problem evaluating clusterer");

            } finally {
              if (predData != null) {
                m_CurrentVis = new VisualizePanel();
                m_CurrentVis.setName(name+" ("+userTest.relationName()+")");
                m_CurrentVis.setLog(m_Log);
                predData.setPlotName(name+" ("+userTest.relationName()+")");
      
                try {
                  m_CurrentVis.addPlot(predData);
                } catch (Exception ex) {
                  System.err.println(ex);
                }
      
                FastVector vv = new FastVector();
                vv.addElement(clusterer);
                if (trainHeader != null) vv.addElement(trainHeader);
                if (ignoredAtts != null) vv.addElement(ignoredAtts);
                if (saveVis) {
                  vv.addElement(m_CurrentVis);
                  if (grph != null) {
                    vv.addElement(grph);
                  }
        
                }
                m_History.addObject(name, vv);

              }
              if (isInterrupted()) {
                m_Log.logMessage("Interrupted reevaluate model");
                m_Log.statusMessage("See error log");
              }
              m_RunThread = null;
              m_StartBut.setEnabled(true);
              m_StopBut.setEnabled(false);
              m_ignoreBut.setEnabled(true);
              if (m_Log instanceof TaskLogger) {
                ((TaskLogger)m_Log).taskFinished();
              }
            }
          }
      
        };
      m_RunThread.setPriority(Thread.MIN_PRIORITY);
      m_RunThread.start();
    }
  }
  
  /**
   * updates the capabilities filter of the GOE
   * 
   * @param filter      the new filter to use
   */
01576   protected void updateCapabilitiesFilter(Capabilities filter) {
    Instances           tempInst;
    Capabilities  filterClass;

    if (filter == null) {
      m_ClustererEditor.setCapabilitiesFilter(new Capabilities(null));
      return;
    }
    
    if (!ExplorerDefaults.getInitGenericObjectEditorFilter())
      tempInst = new Instances(m_Instances, 0);
    else
      tempInst = new Instances(m_Instances);
    tempInst.setClassIndex(-1);

    try {
      filterClass = Capabilities.forInstances(tempInst);
    }
    catch (Exception e) {
      filterClass = new Capabilities(null);
    }
    
    m_ClustererEditor.setCapabilitiesFilter(filterClass);
  }
  
  /**
   * method gets called in case of a change event
   * 
   * @param e           the associated change event
   */
01606   public void capabilitiesFilterChanged(CapabilitiesFilterChangeEvent e) {
    if (e.getFilter() == null)
      updateCapabilitiesFilter(null);
    else
      updateCapabilitiesFilter((Capabilities) e.getFilter().clone());
  }

  /**
   * Sets the Explorer to use as parent frame (used for sending notifications
   * about changes in the data)
   * 
   * @param parent      the parent frame
   */
01619   public void setExplorer(Explorer parent) {
    m_Explorer = parent;
  }
  
  /**
   * returns the parent Explorer frame
   * 
   * @return            the parent
   */
01628   public Explorer getExplorer() {
    return m_Explorer;
  }
  
  /**
   * Returns the title for the tab in the Explorer
   * 
   * @return            the title of this tab
   */
01637   public String getTabTitle() {
    return "Cluster";
  }
  
  /**
   * Returns the tooltip for the tab in the Explorer
   * 
   * @return            the tooltip of this tab
   */
01646   public String getTabTitleToolTip() {
    return "Identify instance clusters";
  }

  /**
   * Tests out the clusterer panel from the command line.
   *
   * @param args may optionally contain the name of a dataset to load.
   */
01655   public static void main(String [] args) {

    try {
      final javax.swing.JFrame jf =
      new javax.swing.JFrame("Weka Explorer: Cluster");
      jf.getContentPane().setLayout(new BorderLayout());
      final ClustererPanel sp = new ClustererPanel();
      jf.getContentPane().add(sp, BorderLayout.CENTER);
      weka.gui.LogPanel lp = new weka.gui.LogPanel();
      sp.setLog(lp);
      jf.getContentPane().add(lp, BorderLayout.SOUTH);
      jf.addWindowListener(new java.awt.event.WindowAdapter() {
      public void windowClosing(java.awt.event.WindowEvent e) {
        jf.dispose();
        System.exit(0);
      }
      });
      jf.pack();
      jf.setSize(800, 600);
      jf.setVisible(true);
      if (args.length == 1) {
      System.err.println("Loading instances from " + args[0]);
      java.io.Reader r = new java.io.BufferedReader(
                     new java.io.FileReader(args[0]));
      Instances i = new Instances(r);
      sp.setInstances(i);
      }
    } catch (Exception ex) {
      ex.printStackTrace();
      System.err.println(ex.getMessage());
    }
  }
}

Generated by  Doxygen 1.6.0   Back to index