Example usage for weka.gui.visualize PlotData2D setPlotName

List of usage examples for weka.gui.visualize PlotData2D setPlotName

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Introduction

In this page you can find the example usage for weka.gui.visualize PlotData2D setPlotName.

Prototype

public void setPlotName(String name)

Source Link

Document

Set the name of this plot

Usage

From source file:cyber009.main.UDALNeuralNetwork.java

public void showData() {
    //System.out.println(dataSet);
    PlotData2D p2D = new PlotData2D(dataSet);
    p2D.setPlotName("Syn data");
    VisualizePanel vp = new VisualizePanel();
    vp.setName("Show Data");
    try {/*from  www.j  a v a2s. c  o m*/
        vp.addPlot(p2D);

        JFrame frame = new JFrame("Show Data");
        frame.setSize(600, 600);
        frame.setVisible(true);
        frame.getContentPane().setLayout(new BorderLayout());
        frame.getContentPane().add(vp, BorderLayout.CENTER);
        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        frame.setVisible(true);
        func.showCoefficients();
    } catch (Exception ex) {
        Logger.getLogger(MainSyntacticData.class.getName()).log(Level.SEVERE, null, ex);
    }

}

From source file:cyber009.udal.mains.WekaUDAL.java

public void showPlot(Instances dataSet) {
    PlotData2D p2D = new PlotData2D(dataSet);
    p2D.setPlotName(dataSet.relationName());
    VisualizePanel vp = new VisualizePanel();
    vp.setName(dataSet.relationName());/*from  w  ww  . jav a2  s  . co m*/
    try {
        vp.addPlot(p2D);
        JFrame frame = new JFrame(dataSet.relationName());
        frame.setSize(600, 600);
        frame.setVisible(true);
        frame.getContentPane().setLayout(new BorderLayout());
        frame.getContentPane().add(vp, BorderLayout.CENTER);
        frame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        frame.setVisible(true);
    } catch (Exception ex) {
        Logger.getLogger(WekaUDAL.class.getName()).log(Level.SEVERE, null, ex);
    }
}

From source file:meka.gui.explorer.classify.AbstractShowThresholdCurve.java

License:Open Source License

/**
 * Creates a panel displaying the ROC data.
 *
 * @param data          the threshold curve data
 * @param title         the title of the plot
 * @return              the panel/*from  w ww . j a  v a2  s . c o m*/
 * @throws Exception    if plot generation fails
 */
protected ThresholdVisualizePanel createPanel(Instances data, String title) throws Exception {
    ThresholdVisualizePanel result = new ThresholdVisualizePanel();
    PlotData2D plot = new PlotData2D(data);
    plot.setPlotName(title);
    plot.m_displayAllPoints = true;
    boolean[] connectPoints = new boolean[data.numInstances()];
    for (int cp = 1; cp < connectPoints.length; cp++)
        connectPoints[cp] = true;
    plot.setConnectPoints(connectPoints);
    result.addPlot(plot);
    setComboBoxIndices(data, result);
    return result;
}

From source file:meka.gui.explorer.classify.IncrementalPerformance.java

License:Open Source License

/**
 * Creates a panel displaying the data.// w w  w.j a v a 2 s  .c o  m
 *
 * @param data          the plot data
 * @return              the panel
 * @throws Exception    if plot generation fails
 */
protected VisualizePanel createPanel(Instances data) throws Exception {
    VisualizePanel result = new ThresholdVisualizePanel();
    PlotData2D plot = new PlotData2D(data);
    plot.setPlotName("Incremental performance");
    plot.m_displayAllPoints = true;
    boolean[] connectPoints = new boolean[data.numInstances()];
    for (int cp = 1; cp < connectPoints.length; cp++)
        connectPoints[cp] = true;
    plot.setConnectPoints(connectPoints);
    result.addPlot(plot);
    if (data.attribute(SAMPLES) != null)
        result.setXIndex(data.attribute(SAMPLES).index());
    if (data.attribute(ACCURACY) != null)
        result.setYIndex(data.attribute(ACCURACY).index());
    return result;
}

From source file:meka.gui.explorer.classify.ShowMacroCurve.java

License:Open Source License

/**
 * Creates a panel displaying the data.// w  ww .ja  va2s .  c  om
 *
 * @param data          the plot data
 * @return              the panel
 * @throws Exception    if plot generation fails
 */
protected VisualizePanel createPanel(Instances data) throws Exception {
    VisualizePanel result = new ThresholdVisualizePanel();
    PlotData2D plot = new PlotData2D(data);
    plot.setPlotName("Macro-averaged Performance");
    plot.m_displayAllPoints = true;
    boolean[] connectPoints = new boolean[data.numInstances()];
    for (int cp = 1; cp < connectPoints.length; cp++)
        connectPoints[cp] = true;
    plot.setConnectPoints(connectPoints);
    result.addPlot(plot);
    if (data.attribute(SAMPLES) != null)
        result.setXIndex(data.attribute(SAMPLES).index());
    if (data.attribute(ACCURACY) != null)
        result.setYIndex(data.attribute(ACCURACY).index());
    return result;
}

From source file:meka.gui.explorer.classify.ShowMicroCurve.java

License:Open Source License

/**
 * Creates a panel displaying the data.//from w  w w  . jav  a  2  s .co  m
 *
 * @param data          the plot data
 * @return              the panel
 * @throws Exception    if plot generation fails
 */
protected VisualizePanel createPanel(Instances data) throws Exception {
    VisualizePanel result = new ThresholdVisualizePanel();
    PlotData2D plot = new PlotData2D(data);
    plot.setPlotName("Micro-averaged Performance");
    plot.m_displayAllPoints = true;
    boolean[] connectPoints = new boolean[data.numInstances()];
    for (int cp = 1; cp < connectPoints.length; cp++)
        connectPoints[cp] = true;
    plot.setConnectPoints(connectPoints);
    result.addPlot(plot);
    if (data.attribute(SAMPLES) != null)
        result.setXIndex(data.attribute(SAMPLES).index());
    if (data.attribute(ACCURACY) != null)
        result.setYIndex(data.attribute(ACCURACY).index());
    return result;
}

From source file:meka.gui.guichooser.PrecisionRecallCurve.java

License:Open Source License

/**
 * Called by the menu items action listener.
 *///from   w w w .  j  a va 2s.  c  om
@Override
protected void launch() {
    m_FileChooser = GUIHelper.newConverterFileChooser();
    // choose file
    int retVal = m_FileChooser.showOpenDialog(null);
    if (retVal != JFileChooser.APPROVE_OPTION)
        return;
    File file = m_FileChooser.getSelectedFile();

    // create plot
    Instances data;
    try {
        data = m_FileChooser.getLoader().getDataSet();
    } catch (Exception e) {
        JOptionPane.showMessageDialog(null, "Error loading file '" + file + "':\n" + e, "Error",
                JOptionPane.ERROR_MESSAGE);
        e.printStackTrace();
        return;
    }
    data.setClassIndex(data.numAttributes() - 1);
    ThresholdVisualizePanel vmc = new ThresholdVisualizePanel();
    vmc.setROCString("(Area under PRC = " + Utils.doubleToString(ThresholdCurve.getPRCArea(data), 4) + ")");
    vmc.setName(data.relationName());
    PlotData2D tempd = new PlotData2D(data);
    tempd.setPlotName(data.relationName());
    tempd.m_displayAllPoints = true;
    // specify which points are connected
    boolean[] cp = new boolean[data.numInstances()];
    for (int n = 1; n < cp.length; n++)
        cp[n] = true;
    try {
        tempd.setConnectPoints(cp);
        vmc.addPlot(tempd);
        if (data.attribute(ThresholdCurve.RECALL_NAME) != null)
            vmc.setXIndex(data.attribute(ThresholdCurve.RECALL_NAME).index());
        if (data.attribute(ThresholdCurve.PRECISION_NAME) != null)
            vmc.setYIndex(data.attribute(ThresholdCurve.PRECISION_NAME).index());
    } catch (Exception e) {
        JOptionPane.showMessageDialog(null, "Error adding plot:\n" + e, "Error", JOptionPane.ERROR_MESSAGE);
        e.printStackTrace();
        return;
    }

    MekaFrame frame = new MekaFrame();
    frame.setTitle(getName());
    frame.setDefaultCloseOperation(MekaFrame.DISPOSE_ON_CLOSE);
    frame.getContentPane().setLayout(new BorderLayout());
    frame.getContentPane().add(vmc);
    frame.setSize(800, 600);
    frame.setLocationRelativeTo(null);
    frame.setVisible(true);
}

From source file:meka.gui.guichooser.ROC.java

License:Open Source License

/**
 * Called by the menu items action listener.
 *///  w  w  w.  jav a2  s . c  o m
@Override
protected void launch() {
    m_FileChooser = GUIHelper.newConverterFileChooser();
    // choose file
    int retVal = m_FileChooser.showOpenDialog(null);
    if (retVal != JFileChooser.APPROVE_OPTION)
        return;
    File file = m_FileChooser.getSelectedFile();

    // create plot
    Instances data;
    try {
        data = m_FileChooser.getLoader().getDataSet();
    } catch (Exception e) {
        JOptionPane.showMessageDialog(null, "Error loading file '" + file + "':\n" + e, "Error",
                JOptionPane.ERROR_MESSAGE);
        e.printStackTrace();
        return;
    }
    data.setClassIndex(data.numAttributes() - 1);
    ThresholdVisualizePanel vmc = new ThresholdVisualizePanel();
    vmc.setROCString("(Area under ROC = " + Utils.doubleToString(ThresholdCurve.getROCArea(data), 4) + ")");
    vmc.setName(data.relationName());
    PlotData2D tempd = new PlotData2D(data);
    tempd.setPlotName(data.relationName());
    tempd.m_displayAllPoints = true;
    // specify which points are connected
    boolean[] cp = new boolean[data.numInstances()];
    for (int n = 1; n < cp.length; n++)
        cp[n] = true;
    try {
        tempd.setConnectPoints(cp);
        vmc.addPlot(tempd);
        if (data.attribute(ThresholdCurve.FP_RATE_NAME) != null)
            vmc.setXIndex(data.attribute(ThresholdCurve.FP_RATE_NAME).index());
        if (data.attribute(ThresholdCurve.TP_RATE_NAME) != null)
            vmc.setYIndex(data.attribute(ThresholdCurve.TP_RATE_NAME).index());
    } catch (Exception e) {
        JOptionPane.showMessageDialog(null, "Error adding plot:\n" + e, "Error", JOptionPane.ERROR_MESSAGE);
        e.printStackTrace();
        return;
    }

    MekaFrame frame = new MekaFrame();
    frame.setTitle(getName());
    frame.setDefaultCloseOperation(MekaFrame.DISPOSE_ON_CLOSE);
    frame.getContentPane().setLayout(new BorderLayout());
    frame.getContentPane().add(vmc);
    frame.setSize(800, 600);
    frame.setLocationRelativeTo(null);
    frame.setVisible(true);
}

From source file:milk.visualize.MIPlot2D.java

License:Open Source License

/**
 * Sets the plot vectors from a set of exemplars
 * @param added the exemplars//from   www  .java 2 s .c om
 * @exception exception Exception if plots could not be set
 */
public void setPlotExemplars(Exemplars added) throws Exception {
    super.removeAllPlots(); // Set xIndex, yIndex and cIndex to 0   
    if (added == null) {
        plotExemplars = null;
        setEnabled(false);
        return;
    }

    plotExemplars = new Exemplars(added);
    int cIndex = plotExemplars.classIndex();

    for (int i = 0; i < plotExemplars.numExemplars(); i++) {
        Exemplar ex = plotExemplars.exemplar(i);
        Instances insts = ex.getInstances();
        PlotData2D tmp = new PlotData2D(insts);
        int num = insts.numInstances();
        int[] shapes = new int[num];
        int[] sizes = new int[num];
        for (int j = 0; j < num; j++) {
            shapes[j] = Plot2D.X_SHAPE;
            sizes[j] = Plot2D.DEFAULT_SHAPE_SIZE;
        }

        tmp.setShapeType(shapes);
        tmp.setShapeSize(sizes);
        tmp.m_useCustomColour = false;
        tmp.setCindex(cIndex);
        tmp.setPlotName(Integer.toString((int) ex.idValue()));
        addPlot(tmp); // determineBound() involved
    }
    // Reset
    if (x != null)
        setXValue(x);
    if (y != null)
        setYValue(y);
    m_cIndex = cIndex;
    if (!Double.isNaN(maxC))
        m_maxC = maxC;
    if (!Double.isNaN(minC))
        m_minC = minC;
}

From source file:miRdup.WekaModule.java

License:Open Source License

public static void rocCurve(Evaluation eval) {
    try {/*from w  w  w .  ja v a 2  s.  c  om*/
        // generate curve
        ThresholdCurve tc = new ThresholdCurve();
        int classIndex = 0;
        Instances result = tc.getCurve(eval.predictions(), classIndex);
        result.toString();
        // plot curve
        ThresholdVisualizePanel vmc = new ThresholdVisualizePanel();
        vmc.setROCString("(Area under ROC = " + Utils.doubleToString(tc.getROCArea(result), 4) + ")");
        vmc.setName(result.relationName());
        PlotData2D tempd = new PlotData2D(result);
        tempd.setPlotName(result.relationName());
        tempd.addInstanceNumberAttribute();
        // specify which points are connected
        boolean[] cp = new boolean[result.numInstances()];
        for (int n = 1; n < cp.length; n++) {
            cp[n] = true;
        }
        tempd.setConnectPoints(cp);
        // add plot
        vmc.addPlot(tempd);

        //
        result.toString();

        // display curve
        String plotName = vmc.getName();
        final javax.swing.JFrame jf = new javax.swing.JFrame("Weka Classifier Visualize: " + plotName);
        jf.setSize(500, 400);
        jf.getContentPane().setLayout(new BorderLayout());
        jf.getContentPane().add(vmc, BorderLayout.CENTER);
        jf.addWindowListener(new java.awt.event.WindowAdapter() {
            public void windowClosing(java.awt.event.WindowEvent e) {
                jf.dispose();
            }
        });

        jf.setVisible(true);
        System.out.println("");
    } catch (Exception e) {
        e.printStackTrace();
    }

}