resultspanel.java

wekaUT是 university texas austin 开发的基于weka的半指导学习(semi supervised learning)的分类器

		 && (name.toLowerCase().equals("key_run"))) {
	m_RunCombo.setSelectedIndex(i);
	runCol = i;
      } else if (name.toLowerCase().equals("key_scheme") ||
		 name.toLowerCase().equals("key_scheme_options") ||
		 name.toLowerCase().equals("key_scheme_version_id")) {
	m_ResultKeyList.addSelectionInterval(i, i);
	selectedList += "," + (i + 1);
	//=============== BEGIN EDIT mbilenko ===============
      // automatic selection of the correct measure for clustering experiments 
      } else if (name.toLowerCase().indexOf("pairwise_f_measure") != -1) {
	  m_CompareCombo.setSelectedIndex(i);
	  m_ErrorCompareCol = i;
      }
      // automatic selection of the correct measure for deduping experiments 
       else if (name.toLowerCase().equals("precision")) {
	m_CompareCombo.setSelectedIndex(i);
      //=============== END EDIT mbilenko ===============	
       }else if (name.toLowerCase().indexOf("percent_correct") != -1) {
	  m_CompareCombo.setSelectedIndex(i);
	  classificationTask=true;
       }else if (!classificationTask && (name.toLowerCase().indexOf("root_mean_squared_error") != -1)) {
	   // automatic selection of the correct measure for regression experiments 
	   m_CompareCombo.setSelectedIndex(i);
       }else if (name.toLowerCase().indexOf("percent_incorrect") != -1) {
	   m_ErrorCompareCol = i;
	   //remember index of error for computing error reductions
      }
    }
      //=============== BEGIN EDIT melville ===============	
    if(learning){
	m_DatasetKeyList.addSelectionInterval(learning_key, learning_key);
	selectedListDataset += "," + (learning_key + 1);
	m_CompareModel.addElement("%Error_reduction");
	m_CompareModel.addElement("Top_20%_%Error_reduction");
    }
      //=============== END EDIT melville ===============	
    
    if (runCol == -1) {
      runCol = 0;
    }
    m_DatasetKeyBut.setEnabled(true);
    m_RunCombo.setEnabled(true);
    m_ResultKeyBut.setEnabled(true);
    m_CompareCombo.setEnabled(true);
    
    // Reconnect the configuration listener
    m_RunCombo.addActionListener(m_ConfigureListener);
    
    // Set up the TTester with the new data
    m_TTester.setRunColumn(runCol);
    Range generatorRange = new Range();
    if (selectedList.length() != 0) {
      try {
	generatorRange.setRanges(selectedList);
      } catch (Exception ex) {
	ex.printStackTrace();
	System.err.println(ex.getMessage());
      }
    }
    m_TTester.setResultsetKeyColumns(generatorRange);

    generatorRange = new Range();
    if (selectedListDataset.length() != 0) {
      try {
	generatorRange.setRanges(selectedListDataset);
      } catch (Exception ex) {
	ex.printStackTrace();
	System.err.println(ex.getMessage());
      }
    }
    m_TTester.setDatasetKeyColumns(generatorRange);
    //=============== BEGIN EDIT melville ===============
    m_TTester.setLearningCurve(learning);
    m_TTester.setFraction(fraction);
    if(learning){//get points on the learning curve
	Attribute attr;
	if(noise){//override fraction
	    attr = m_Instances.attribute("Key_Noise_levels");
	}else if(fraction){
	    attr = m_Instances.attribute("Key_Fraction_instances");
	}else {
	    attr = m_Instances.attribute("Key_Total_instances");
	}
	double []pts = new double [attr.numValues()];
	for(int k=0; k<attr.numValues(); k++){
	    pts[k] = Double.parseDouble(attr.value(k));
	}
	//sort points
	Arrays.sort(pts);
	m_TTester.setPoints(pts);
    }
    //=============== END EDIT melville ===============
    m_SigTex.setEnabled(true);
    m_PrecTex.setEnabled(true);

    setTTester();
  }

  /**
   * Updates the test chooser with possible tests
   */
  protected void setTTester() {
    
    String name = (new SimpleDateFormat("HH:mm:ss - "))
      .format(new Date())
      + "Available resultsets";
    StringBuffer outBuff = new StringBuffer();
    outBuff.append("Available resultsets\n"
		   + m_TTester.resultsetKey() + "\n\n");
    m_History.addResult(name, outBuff);
    m_History.setSingle(name);

    m_TestsModel.removeAllElements();
    for (int i = 0; i < m_TTester.getNumResultsets(); i++) {
      String tname = m_TTester.getResultsetName(i);
      /*      if (tname.length() > 20) {
	tname = tname.substring(0, 20);
	} */
      m_TestsModel.addElement(tname);
    }
    m_TestsModel.addElement("Summary");
    m_TestsModel.addElement("Ranking");
    //================ BEGIN EDIT melville ================
    m_TestsModel.addElement("Learning Curve Summary");
    //================ END EDIT melville ================
    m_TestsList.setSelectedIndex(0);
    m_TestsButton.setEnabled(true);

    m_PerformBut.setEnabled(true);
    
  }

  
  /**
   * Carries out a t-test using the current configuration.
   */
  protected void performTest() {

    String sigStr = m_SigTex.getText();
    if (sigStr.length() != 0) {
      m_TTester.setSignificanceLevel((new Double(sigStr)).doubleValue());
    } else {
      m_TTester.setSignificanceLevel(0.05);
    }

    String precStr = m_PrecTex.getText();
    if (precStr.length() != 0) {
	m_TTester.setPrecision((new Integer(precStr)).intValue());
    } else {
	m_TTester.setPrecision(2);
    }
    // Carry out the test chosen and biff the results to the output area
    m_TTester.setShowStdDevs(m_ShowStdDevs.isSelected());
    int compareCol = m_CompareCombo.getSelectedIndex();
    int tType = m_TestsList.getSelectedIndex();

    //=============== BEGIN EDIT melville ===============
    String test_selected = (String) m_TestsList.getSelectedValue();
    String name = (new SimpleDateFormat("HH:mm:ss - "))
      .format(new Date())
      + (String) m_CompareCombo.getSelectedItem() + " - "
      + test_selected;
    StringBuffer outBuff = new StringBuffer();
    if(((String) m_CompareCombo.getSelectedItem()).equalsIgnoreCase("%error_reduction"))
	outBuff.append(m_TTester.header("Percentage error reduction"));
    else if(((String) m_CompareCombo.getSelectedItem()).equalsIgnoreCase("top_20%_%error_reduction"))
	outBuff.append(m_TTester.header("Top 20% Percentage error reduction"));
    else outBuff.append(m_TTester.header(compareCol));
    outBuff.append("\n");
    m_History.addResult(name, outBuff);
    m_History.setSingle(name);
    try {
	if (tType < m_TTester.getNumResultsets()) {
	    if(((String) m_CompareCombo.getSelectedItem()).equalsIgnoreCase("%error_reduction")){
		outBuff.append(m_TTester.multiResultsetPercentErrorReduction(tType, m_ErrorCompareCol));
	    }else if(((String) m_CompareCombo.getSelectedItem()).equalsIgnoreCase("top_20%_%error_reduction")){
		outBuff.append(m_TTester.multiResultsetTopNPercentErrorReduction(tType, m_ErrorCompareCol, 0.20));
	    }else outBuff.append(m_TTester.multiResultsetFull(tType, compareCol));
	}
      
      else if (test_selected.equalsIgnoreCase("summary")) {
	  outBuff.append(m_TTester.multiResultsetSummary(compareCol));
      } else if (test_selected.equalsIgnoreCase("ranking")) {
	  outBuff.append(m_TTester.multiResultsetRanking(compareCol));
      }  
      //================ END EDIT melville ================
      
      outBuff.append("\n");
    } catch (Exception ex) {
      outBuff.append(ex.getMessage() + "\n");
    }
    m_History.updateResult(name);
  }

  
  public void setResultKeyFromDialog() {

    ListSelectorDialog jd = new ListSelectorDialog(null, m_ResultKeyList);

    // Open the dialog
    int result = jd.showDialog();
    
    // If accepted, update the ttester
    if (result == ListSelectorDialog.APPROVE_OPTION) {
      int [] selected = m_ResultKeyList.getSelectedIndices();
      String selectedList = "";
      for (int i = 0; i < selected.length; i++) {
	selectedList += "," + (selected[i] + 1);
      }
      Range generatorRange = new Range();
      if (selectedList.length() != 0) {
	try {
	  generatorRange.setRanges(selectedList);
	} catch (Exception ex) {
	  ex.printStackTrace();
	  System.err.println(ex.getMessage());
	}
      }
      m_TTester.setResultsetKeyColumns(generatorRange);
      setTTester();
    }
  }
  
  public void setDatasetKeyFromDialog() {

    ListSelectorDialog jd = new ListSelectorDialog(null, m_DatasetKeyList);

    // Open the dialog
    int result = jd.showDialog();
    //=============== BEGIN EDIT melville ===============
    //Check if learning curves should be generated
    boolean noise = false;
    boolean learning = false;
    boolean fraction = false;
    int learning_key = -1;
    
    // If accepted, update the ttester
    if (result == ListSelectorDialog.APPROVE_OPTION) {
      int [] selected = m_DatasetKeyList.getSelectedIndices();
      String selectedList = "";
      Object [] selected_string = m_DatasetKeyList.getSelectedValues();
      for (int i = 0; i < selected.length; i++) {
	  if(((String)selected_string[i]).toLowerCase().equals("key_noise_levels")){
	      learning_key = i;
	      learning = true;
	      //fraction = true;
	      noise = true;
	  }else	if(((String)selected_string[i]).toLowerCase().equals("key_fraction_instances")){
	      learning_key = i;
	      learning = true;
	      fraction = true;
	  }else if(((String)selected_string[i]).toLowerCase().equals("key_total_instances")  && !learning){ 
	      learning = true;
	      learning_key = i;
	  }else
	      selectedList += "," + (selected[i] + 1);
      }
      
      m_TTester.setLearningCurve(learning);
      m_TTester.setFraction(fraction);
      if(learning){//get points on the learning curve
	  selectedList += "," + (selected[learning_key] + 1);
	  Attribute attr;
	  if(noise){//override fraction
	      attr = m_Instances.attribute("Key_Noise_levels");
	  }else	if(fraction){
	      attr = m_Instances.attribute("Key_Fraction_instances");
	  }else {
	      attr = m_Instances.attribute("Key_Total_instances");
	  }
	  double []pts = new double [attr.numValues()];
	  for(int k=0; k<attr.numValues(); k++){
	      pts[k] = Double.parseDouble(attr.value(k));
	  }
	  Arrays.sort(pts);
	  m_TTester.setPoints(pts);
      }
      //================ END EDIT melville ================

      Range generatorRange = new Range();
      if (selectedList.length() != 0) {
	try {
	  generatorRange.setRanges(selectedList);
	} catch (Exception ex) {
	  ex.printStackTrace();
	  System.err.println(ex.getMessage());
	}
      }
      m_TTester.setDatasetKeyColumns(generatorRange);
      setTTester();
    }
  }

  public void setTestBaseFromDialog() {
    ListSelectorDialog jd = new ListSelectorDialog(null, m_TestsList);

    // Open the dialog
    jd.showDialog();
  }

  /**
   * Save the currently selected result buffer to a file.
   */
  protected void saveBuffer() {
    StringBuffer sb = m_History.getSelectedBuffer();
    if (sb != null) {
      if (m_SaveOut.save(sb)) {
	JOptionPane.showMessageDialog(this,
				      "File saved",
				      "Results",
				      JOptionPane.INFORMATION_MESSAGE);
      }
    } else {
      m_SaveOutBut.setEnabled(false);
    }
  }

  //=============== BEGIN EDIT mbilenko ===============
  /**
   * Plot the currently selected output buffer
   */
  protected void plotOutput() {
    try { 
      StringBuffer sb = m_History.getSelectedBuffer();
      if (sb != null) {
	// dump the output into a temporary file
	File tempDirFile = new File("/tmp");
	final File bufferFile = File.createTempFile("buffer", "", tempDirFile);
	bufferFile.deleteOnExit();

	PrintWriter writer = new PrintWriter(new BufferedOutputStream(new FileOutputStream(bufferFile)));
	writer.print(sb);
	writer.close();

	// launch the perl script to process the file
	
	//Process proc = Runtime.getRuntime().exec("perl weka/gui/experiment/plot.pl " + bufferFile.getPath());
	Process proc = Runtime.getRuntime().exec("perl /u/ml/software/weka-latest/weka/gui/experiment/plot.pl " + bufferFile.getPath());
	proc.waitFor();

	// get a list of generated gnuplot scripts
	String[] scriptList = tempDirFile.list(new FilenameFilter() {
	    public boolean accept(File f, String s) { return (s.endsWith(".gplot") && s.startsWith(bufferFile.getName())); }
	  });
	for (int i = 0; i < scriptList.length; i++) {
	  // launch gnuplot
	  scriptList[i] = tempDirFile.getPath() + "/" + scriptList[i];
	  System.out.println(scriptList[i]);
	  proc = Runtime.getRuntime().exec("gnuplot -persist " + scriptList[i]);
	  File plotFile = new File(scriptList[i]);
	  plotFile.deleteOnExit();
	  File dataFile = new File(scriptList[i].replaceAll(".gplot", ".dat"));
	  dataFile.deleteOnExit();
	} 
      } else {
	m_PlotBut.setEnabled(false);
      }
    } catch (Exception e) {
      System.out.println("Problems plotting: " + e);
      e.printStackTrace();
    } 
  } 


  //=============== END EDIT mbilenko ===============
  
  /**
   * Tests out the results panel from the command line.
   *
   * @param args ignored
   */
  public static void main(String [] args) {

    try {
      final JFrame jf = new JFrame("Weka Experiment: Results Analysis");
      jf.getContentPane().setLayout(new BorderLayout());
      final ResultsPanel sp = new ResultsPanel();
      //sp.setBorder(BorderFactory.createTitledBorder("Setup"));
      jf.getContentPane().add(sp, BorderLayout.CENTER);
      jf.addWindowListener(new WindowAdapter() {
	public void windowClosing(WindowEvent e) {
	  jf.dispose();
	  System.exit(0);
	}
      });
      jf.pack();
      jf.setSize(700, 550);
      jf.setVisible(true);
    } catch (Exception ex) {
      ex.printStackTrace();
      System.err.println(ex.getMessage());
    }
  }
}