Example usage for org.jfree.data.statistics HistogramDataset HistogramDataset

List of usage examples for org.jfree.data.statistics HistogramDataset HistogramDataset

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Introduction

In this page you can find the example usage for org.jfree.data.statistics HistogramDataset HistogramDataset.

Prototype

public HistogramDataset()

Source Link

Document

Creates a new (empty) dataset with a default type of HistogramType .FREQUENCY.

Usage

From source file:OAT.trading.thread.BacktestThread.java

private void showHistogram(String title, double[] data) {
    if (data == null || data.length == 0) {
        return;/*from ww  w .ja  va  2 s.c om*/
    }

    HistogramDataset histogramDataset = new HistogramDataset();
    histogramDataset.addSeries(title, data, 15);

    JFreeChart chart = ChartFactory.createHistogram("", "", "", histogramDataset, PlotOrientation.VERTICAL,
            false, false, false);

    new BasicChartFrame(title, chart).setVisible(true);
}

From source file:org.fhcrc.cpl.viewer.amt.commandline.AmtDatabaseDiagnosticCommandLineModule.java

/**
 *
 * @return/*from  w  w w.j ava 2 s  . c o  m*/
 */
protected JFreeChart histogramIDProbs() {
    HistogramDataset dataset = new HistogramDataset();

    List<Double> histDataList = new ArrayList<Double>();

    AmtPeptideEntry[] entries = amtDB.getEntries();
    for (AmtPeptideEntry entry : entries) {
        if (entry.getNumObservations() > 1)
            histDataList.add((double) entry.calculateIDProbability());
    }
    double[] histData = new double[histDataList.size()];

    for (int i = 0; i < histData.length; i++)
        histData[i] = histDataList.get(i);

    ApplicationContext.setMessage("Mean ID probability: " + BasicStatistics.mean(histData));

    dataset.addSeries("ID probablity", histData, 200);

    JFreeChart chart = ChartFactory.createHistogram("id_probability", "id_probability", "id_probability",
            dataset, PlotOrientation.VERTICAL, false, false, false);
    PanelWithChart pwc = new PanelWithChart(chart);
    pwc.setName("id probs");

    if (showCharts)
        pwc.displayInTab();
    return pwc.getChart();
}

From source file:v800_trainer.JHistogram.java

public JPanel StartHistoSchrittlnge(JCicloTronic JTronicHandle) {

    boolean Summenhisto;
    int von = 0;//from   ww  w .  j a v  a2 s.  c o  m
    int bis = 0;
    int num = 0;
    int selected;
    int single;
    int Gruppen = 0;
    int i = 100;
    int j = 10;
    int m = 0;
    int n = 0;
    int Linecount = 0;
    int Anzahl = 1;

    JFreeChart chart;

    double DummyData[] = new double[1];

    selected = JTronicHandle.Auswahl_Histogramm.getSelectedIndex();
    Summenhisto = JTronicHandle.Summenhistogramm_Check.isSelected();

    chart = ChartFactory.createHistogram("", "Schrittlnge [cm]", "Hufigkeit", new HistogramDataset(),
            PlotOrientation.HORIZONTAL, true, true, true);

    chart.setBackgroundPaint(Color.white);

    JTronicHandle.applyChartTheme(chart);

    XYPlot plot = chart.getXYPlot();
    plot.setOrientation(PlotOrientation.VERTICAL);
    plot.setBackgroundPaint(Color.lightGray);
    plot.setDomainGridlinePaint(Color.white);
    plot.setRangeGridlinePaint(Color.white);

    plot.setAxisOffset(new RectangleInsets(5.0, 5.0, 5.0, 5.0));
    plot.getRangeAxis().setFixedDimension(15.0);

    ArrayList Bufferarray = new ArrayList();
    double Buffer;

    if (selected == 0) {
        single = 1;
    } else {
        single = 0;
        Summenhisto = false;
    }

    try {
        von = Integer.parseInt(JTronicHandle.Properties.getProperty("HistovonSchrittlnge", "100"));
        bis = Integer.parseInt(JTronicHandle.Properties.getProperty("HistobisSchrittlnge", "200"));
        Gruppen = Integer.parseInt(JTronicHandle.Properties.getProperty("HistostepSchrittlnge", "10"));
        Anzahl = (JTronicHandle.Auswahl_Histogramm.getItemCount() - 2) * single + 1;
        for (j = 0; j < Anzahl; j++) {
            if (single == 1) {
                selected = j + 1;
            }
            if (!Summenhisto) {
                num = JTronicHandle.Statistikhandle.TourData[selected].Datenpunkte;
            } else {
                num += JTronicHandle.Statistikhandle.TourData[selected].Datenpunkte;
            }

            n = 0;
            if (!Summenhisto) {
                create_Start_Stop(JTronicHandle, selected); //die limits einer gezoomten Graphik ermitteln

                for (i = start; i < stop; i++) {
                    Buffer = (double) JTronicHandle.Statistikhandle.TourData[selected].Schritt_lnge[i];
                    if (Buffer >= von && Buffer <= bis) {
                        Bufferarray.add(Buffer);
                    }
                }
            } else {
                for (i = 0; i < j + 1; i++) {
                    create_Start_Stop(JTronicHandle, i + 1);
                    for (m = start; m < stop; m++) {
                        Buffer = (double) JTronicHandle.Statistikhandle.TourData[i + 1].Schritt_lnge[m];
                        if (Buffer >= von && Buffer <= bis) {
                            Bufferarray.add(Buffer);
                        }

                    }

                }
            }

            DummyData = new double[Bufferarray.size()];

            for (i = 0; i < Bufferarray.size(); i++) {
                DummyData[i] = new Double(Bufferarray.get(i).toString());
            }

            if (!Summenhisto) {
                HistogramDataset histoHM = new HistogramDataset();
                histoHM.addSeries(
                        "" + JTronicHandle.Statistikhandle.TourData[selected].Tag + "."
                                + JTronicHandle.Statistikhandle.TourData[selected].Monat + "."
                                + JTronicHandle.Statistikhandle.TourData[selected].Jahr,
                        DummyData, Gruppen, (double) von, (double) bis);
                histoHM.setType(HistogramType.RELATIVE_FREQUENCY);
                plot.setDataset(Linecount, histoHM);
                plot.mapDatasetToRangeAxis(Linecount, 0);
                XYBarRenderer renderer = new XYBarRenderer();
                renderer.setDrawBarOutline(true);

                renderer.setSeriesPaint(0, getColour(Linecount, (int) 255 / Anzahl));

                renderer.setBaseToolTipGenerator(new StandardXYToolTipGenerator());
                plot.setRenderer(Linecount, renderer);

            }
            Linecount++;
        }
    } catch (Exception e) {
        JOptionPane.showMessageDialog(null, "StartHistoSchrittlnge\nFehler: Hm " + e + " " + i + " " + j,
                "Achtung!", JOptionPane.ERROR_MESSAGE);
    }

    if (Summenhisto) {
        HistogramDataset histoHM = new HistogramDataset();
        histoHM.addSeries("Summenhistogram", DummyData, Gruppen, (double) von, (double) bis);
        histoHM.setType(HistogramType.RELATIVE_FREQUENCY);

        plot.setDataset(0, histoHM);
        plot.mapDatasetToRangeAxis(0, 0);
        XYItemRenderer renderer = new XYBarRenderer();
        renderer.setSeriesPaint(0, Color.blue);
        renderer.setBaseToolTipGenerator(new StandardXYToolTipGenerator());

        plot.setRenderer(0, renderer);
    }
    chart.setPadding(padding);
    ChartPanel Panel = new ChartPanel(chart);

    return Panel;
}

From source file:playground.christoph.evacuation.analysis.EvacuationTimePictureWriter.java

private JFreeChart createHistogramChart(String transportMode, double[] travelTimes) {

    HistogramDataset dataset = new HistogramDataset();
    dataset.setType(HistogramType.RELATIVE_FREQUENCY);
    dataset.addSeries("evacuation travel time " + transportMode, travelTimes, 20);

    JFreeChart chart = ChartFactory.createHistogram(null, null, "frequency", dataset, PlotOrientation.VERTICAL,
            true, false, false);// ww  w . j ava2 s .  com
    chart.getXYPlot().setForegroundAlpha(0.75f);

    /*
     * set x-axis range 
     */
    double min = 0.0;
    double max = maxEvacuationTime;
    if (limitMaxEvacuationTime) {
        double cutOffValue = meanEvacuationTime + standardDeviation * evacuationTimeCutOffFactor;
        max = cutOffValue;
    }
    chart.getXYPlot().getDomainAxis().setLowerBound(min);
    chart.getXYPlot().getDomainAxis().setUpperBound(max);

    return chart;
}

From source file:org.fhcrc.cpl.viewer.amt.commandline.AmtDatabaseDiagnosticCommandLineModule.java

/**
 * Show a histogram of the standard deviations of hydrophobicity observations per peptide
 * @return/* w  w w.j a  va2s .  c  o m*/
 */
protected JFreeChart histogramHydroStdDev() {
    HistogramDataset dataset = new HistogramDataset();

    List<Double> histDataList = new ArrayList<Double>();

    AmtPeptideEntry[] entries = amtDB.getEntries();
    for (int i = 0; i < amtDB.numEntries(); i++) {
        if (entries[i].getNumObservations() > 1)
            histDataList.add(entries[i].getHydrophobicityStandardDeviation());
    }
    double[] histData = new double[histDataList.size()];

    for (int i = 0; i < histData.length; i++)
        histData[i] = histDataList.get(i);

    ApplicationContext.setMessage("Mean H standard deviation: " + BasicStatistics.mean(histData));

    dataset.addSeries("hyd_std_dev", histData, 100);

    JFreeChart chart = ChartFactory.createHistogram("hydstddev", "hydstddev", "hydstddev", dataset,
            PlotOrientation.VERTICAL, false, false, false);
    PanelWithChart pwc = new PanelWithChart(chart);
    pwc.setName("mean h std devs");

    if (showCharts)
        pwc.displayInTab();
    return pwc.getChart();
}

From source file:be.ugent.maf.cellmissy.gui.controller.analysis.singlecell.SingleCellAnalysisController.java

/**
 * For a single well, generate an histogram dataset.
 *
 * @param data//from w  w  w .ja  v a  2 s.  com
 * @param seriesKey
 * @param mapTo360
 * @return an HistogramDataset
 */
private HistogramDataset getHistogramDatasetForACondition(
        SingleCellConditionDataHolder singleCellConditionDataHolder, String seriesKey, int bins) {
    HistogramDataset dataset = new HistogramDataset();
    dataset.setType(HistogramType.RELATIVE_FREQUENCY);
    double[] toPrimitive = ArrayUtils.toPrimitive(
            AnalysisUtils.excludeNullValues(singleCellConditionDataHolder.getTurningAnglesVector()));

    double[] mappedData = new double[toPrimitive.length];
    for (int i = 0; i < toPrimitive.length; i++) {
        if (toPrimitive[i] > 0) {
            mappedData[i] = toPrimitive[i];
        } else {
            mappedData[i] = toPrimitive[i] + 360;
        }
    }
    double[] toAdd = mappedData;

    dataset.addSeries(seriesKey, toAdd, bins);
    return dataset;
}

From source file:org.fhcrc.cpl.viewer.amt.commandline.AmtDatabaseDiagnosticCommandLineModule.java

/**
 * Histogram all masses in the database/*from w  w  w  .ja  v a2s.c o  m*/
 * @return
 */
protected JFreeChart histogramMasses() {
    HistogramDataset dataset = new HistogramDataset();

    double[] histData = new double[amtDB.numEntries()];

    AmtPeptideEntry[] entries = amtDB.getEntries();
    for (int i = 0; i < amtDB.numEntries(); i++) {
        histData[i] = entries[i].getMass();

    }
    dataset.addSeries("masses", histData, 500);

    JFreeChart chart = ChartFactory.createHistogram("masses", "masses", "masses", dataset,
            PlotOrientation.VERTICAL, false, false, false);
    ChartDialog cd2 = new ChartDialog(chart);
    cd2.setSize(800, 600);
    PanelWithChart pwc = new PanelWithChart(chart);

    pwc.setName("masses");

    if (showCharts)
        pwc.displayInTab();
    return pwc.getChart();
}

From source file:simulation.AureoZauleckAnsLab2.java

public static JFreeChart createHistogram(ArrayList doubleMatrix, int width, String title, String label) {

    // Generate a one dimensional array of the size w*h of the double matrix
    ArrayList<Double> dataArrayList = new ArrayList<Double>();

    for (int i = 0; i < doubleMatrix.size(); i++) {

        double value = Double.parseDouble(doubleMatrix.get(i).toString());
        if (Double.isNaN(value))
            continue;
        else//w ww  . ja v  a  2  s .  co  m
            dataArrayList.add(value);
        System.out.println(value);
    }

    double[] data = new double[dataArrayList.size()];

    for (int p = 0; p < dataArrayList.size(); p++)
        data[p] = dataArrayList.get(p);

    // int number = data.length;
    HistogramDataset dataset = new HistogramDataset();

    dataset.setType(HistogramType.FREQUENCY);
    dataset.addSeries("Hist", data, width);
    String plotTitle = title;
    String yAxis = "Frequency";
    String xAxis = label;
    PlotOrientation orientation = PlotOrientation.VERTICAL;

    boolean show = false;
    boolean toolTips = false;
    boolean urls = false;
    JFreeChart chart = ChartFactory.createHistogram(plotTitle, xAxis, yAxis, dataset, orientation, show,
            toolTips, urls);

    chart.setBackgroundPaint(Color.white);
    ChartPanel chartPanel = new ChartPanel(chart);
    chartPanel.setPreferredSize(new java.awt.Dimension(500, 300));
    JFrame l = new JFrame();
    l.setContentPane(chartPanel);
    l.setSize(400, 400);
    l.setVisible(true);

    return chart;
}

From source file:net.bioclipse.chembl.moss.ui.wizard.ChemblMossWizardPage1.java

public void helpToHistogram(IStringMatrix matrix) {
    //Adds activity to histogram series
    series = new XYSeries("Activity for compounds");
    histogramSeries = new HistogramDataset();
    histogramSeries.setType(HistogramType.FREQUENCY);
    ArrayList<Double> activites = new ArrayList<Double>();
    double value;
    int cnt = 1;//w w  w  .j  a  v  a 2 s  . c  o  m
    double[] histact = new double[matrix.getRowCount() + 1];
    for (int i = 1; i < matrix.getRowCount() + 1; i++) {
        if (matrix.get(i, "actval").equals("")) {
            value = 0;
        } else {
            value = Double.parseDouble(matrix.get(i, "actval"));
        }
        activites.add(value);
    }
    //Sort list to increasing order of activities and adds them to histogram
    Collections.sort(activites);
    for (int i = 0; i < activites.size(); i++) {
        double d = activites.get(i);
        histact[i] = d;
        int t = activites.size() - 1;
        if (i == t) {
            series.add(d, cnt);
        } else {
            double dd = activites.get(i + 1);

            if (d == dd) {
                cnt++;
            } else {
                histact[i] = d;
                series.add(d, cnt);
                cnt = 1;
            }
        }
    }
    histogramSeries.addSeries("Histogram", histact, matrix.getRowCount());
}

From source file:MSUmpire.DIA.TargetMatchScoring.java

public void MixtureModeling() throws IOException {
    if (libTargetMatches.isEmpty()) {
        return;// ww  w .j a  v a2  s  .  c o m
    }
    int IDNo = 0;
    int decoyNo = 0;
    int modelNo = 0;
    double IDmean = 0d;
    double Decoymean = 0d;

    for (UmpireSpecLibMatch match : libIDMatches) {
        if (match.BestHit != null) {
            IDNo++;
            IDmean += match.BestHit.UmpireScore;
        }
    }

    decoyNo = decoyModelingList.size();
    for (PeakGroupScore peakGroupScore : decoyModelingList) {
        Decoymean += peakGroupScore.UmpireScore;
    }

    for (UmpireSpecLibMatch match : libTargetMatches) {
        //modelNo+= match.TargetHits.size();
        if (match.BestMS1Hit != null) {
            modelNo++;
        }
        if (match.BestMS2Hit != null) {
            modelNo++;
        }
    }

    Decoymean /= decoyNo;
    IDmean /= IDNo;

    PVector[] points = new PVector[modelNo];
    PVector[] centroids = new PVector[2];

    int idx = 0;
    for (UmpireSpecLibMatch match : libTargetMatches) {
        if (match.BestMS1Hit != null) {
            points[idx] = new PVector(1);
            points[idx].array[0] = match.BestMS1Hit.UmpireScore;
            idx++;
        }
        if (match.BestMS2Hit != null) {
            points[idx] = new PVector(1);
            points[idx].array[0] = match.BestMS2Hit.UmpireScore;
            idx++;
        }
        //            for(PeakGroupScore peakGroupScore : match.TargetHits){
        //                points[idx] = new PVector(1);
        //                points[idx].array[0] = match.BestMS2Hit.UmpireScore;
        //                idx++;
        //            }
    }

    MixtureModel mmc;
    centroids[0] = new PVector(1);
    centroids[0].array[0] = Decoymean;
    centroids[1] = new PVector(1);
    centroids[1].array[0] = IDmean;
    Vector<PVector>[] clusters = KMeans.run(points, 2, centroids);
    MixtureModel mm = ExpectationMaximization1D.initialize(clusters);
    mmc = ExpectationMaximization1D.run(points, mm);
    DecimalFormat df = new DecimalFormat("#.####");
    Logger.getRootLogger()
            .debug("----------------------------------------------------------------------------------------");
    Logger.getRootLogger().debug("No. of modeling points=" + modelNo);
    Logger.getRootLogger().debug("ID hits mean=" + df.format(IDmean));
    Logger.getRootLogger().debug("Decoy hits mean=" + df.format(Decoymean));
    //System.out.print("T-test: p-value=" + df.format(model.ttest.pValue).toString() + "\n");
    Logger.getRootLogger()
            .debug("Incorrect hits model mean=" + df.format(((PVector) mmc.param[0]).array[0]) + " variance="
                    + df.format(((PVector) mmc.param[0]).array[1]) + " weight=" + df.format(mmc.weight[0]));
    Logger.getRootLogger()
            .debug("Correct hits model mean=" + df.format(((PVector) mmc.param[1]).array[0]) + " variance="
                    + df.format(((PVector) mmc.param[1]).array[1]) + " weight=" + df.format(mmc.weight[1]));

    if (((PVector) mmc.param[0]).array[0] > ((PVector) mmc.param[1]).array[0]) {
        return;
    }

    float max = (float) (((PVector) mmc.param[1]).array[0] + 4 * Math.sqrt(((PVector) mmc.param[1]).array[1]));
    float min = (float) (((PVector) mmc.param[0]).array[0] - 4 * Math.sqrt(((PVector) mmc.param[0]).array[1]));

    IDNo = 0;
    decoyNo = 0;
    modelNo = 0;

    for (PeakGroupScore peakGroupScore : decoyModelingList) {
        if (peakGroupScore.UmpireScore > min && peakGroupScore.UmpireScore < max) {
            decoyNo++;
        }
    }

    for (UmpireSpecLibMatch match : libIDMatches) {
        if (match.BestHit != null && match.BestHit.UmpireScore > min && match.BestHit.UmpireScore < max) {
            IDNo++;
        }
    }

    for (UmpireSpecLibMatch match : libTargetMatches) {
        //targetNo += match.TargetHits.size();
        //decoyNo += match.DecoyHits.size();
        if (match.BestMS1Hit != null && match.BestMS1Hit.UmpireScore > min
                && match.BestMS1Hit.UmpireScore < max) {
            modelNo++;
        }
        if (match.BestMS2Hit != null && match.BestMS2Hit.UmpireScore > min
                && match.BestMS2Hit.UmpireScore < max) {
            modelNo++;
        }
        //modelNo += match.TargetHits.size();            
    }

    double[] IDObs = new double[IDNo];
    double[] DecoyObs = new double[decoyNo];
    double[] ModelObs = new double[modelNo];
    idx = 0;
    int didx = 0;
    int midx = 0;
    for (UmpireSpecLibMatch match : libIDMatches) {
        if (match.BestHit != null && match.BestHit.UmpireScore > min && match.BestHit.UmpireScore < max) {
            IDObs[idx++] = match.BestHit.UmpireScore;
        }
    }
    for (PeakGroupScore peakGroupScore : decoyModelingList) {
        if (peakGroupScore.UmpireScore > min && peakGroupScore.UmpireScore < max) {
            DecoyObs[didx++] = peakGroupScore.UmpireScore;
        }
    }

    for (UmpireSpecLibMatch match : libTargetMatches) {
        //            for(PeakGroupScore peak : match.TargetHits){
        //                ModelObs[midx++]=peak.UmpireScore;
        //            }
        if (match.BestMS1Hit != null && match.BestMS1Hit.UmpireScore > min
                && match.BestMS1Hit.UmpireScore < max) {
            ModelObs[midx++] = match.BestMS1Hit.UmpireScore;
        }
        if (match.BestMS2Hit != null && match.BestMS2Hit.UmpireScore > min
                && match.BestMS2Hit.UmpireScore < max) {
            ModelObs[midx++] = match.BestMS2Hit.UmpireScore;
        }
    }

    String pngfile = FilenameUtils.getFullPath(Filename) + "/" + FilenameUtils.getBaseName(Filename) + "_"
            + LibID + "_LibMatchModel.png";
    XYSeries model1 = new XYSeries("Incorrect matches");
    XYSeries model2 = new XYSeries("Correct matches");
    XYSeries model3 = new XYSeries("All target hits");

    String modelfile = FilenameUtils.getFullPath(pngfile) + "/" + FilenameUtils.getBaseName(pngfile)
            + "_ModelPoints.txt";
    FileWriter writer = new FileWriter(modelfile);
    writer.write("UScore\tModel\tCorrect\tDecoy\n");

    int NoPoints = 1000;
    double[] model_kde_x = new double[NoPoints];
    float intv = (max - min) / NoPoints;
    PVector point = new PVector(2);
    for (int i = 0; i < NoPoints; i++) {
        point.array[0] = max - i * intv;
        model_kde_x[i] = point.array[0];
        point.array[1] = mmc.EF.density(point, mmc.param[0]) * mmc.weight[0];
        model1.add(point.array[0], point.array[1]);
        point.array[1] = mmc.EF.density(point, mmc.param[1]) * mmc.weight[1];
        model2.add(point.array[0], point.array[1]);

    }

    KernelDensityEstimator kde = new KernelDensityEstimator();
    kde.SetData(ModelObs);
    double[] model_kde_y = kde.Density(model_kde_x);

    for (int i = 0; i < NoPoints; i++) {
        if (model_kde_x[i] > min && model_kde_x[i] < max) {
            point.array[0] = max - i * intv;
            model_kde_x[i] = point.array[0];
            model3.add(model_kde_x[i], model_kde_y[i]);
            writer.write(point.array[0] + "\t" + mmc.EF.density(point, mmc.param[0]) * mmc.weight[0] + "\t"
                    + mmc.EF.density(point, mmc.param[1]) * mmc.weight[1] + "\t" + model_kde_y[i] + "\n");
        }
    }
    writer.close();
    MixtureModelProb = new float[NoPoints + 1][3];
    float positiveaccu = 0f;
    float negativeaccu = 0f;

    MixtureModelProb[0][0] = (float) model2.getMaxX() + Float.MIN_VALUE;
    MixtureModelProb[0][1] = 1f;
    MixtureModelProb[0][2] = 1f;

    for (int i = 1; i < NoPoints + 1; i++) {
        float positiveNumber = model2.getY(NoPoints - i).floatValue();
        float negativeNumber = model1.getY(NoPoints - i).floatValue();
        MixtureModelProb[i][0] = model2.getX(NoPoints - i).floatValue();
        positiveaccu += positiveNumber;
        negativeaccu += negativeNumber;
        MixtureModelProb[i][2] = positiveNumber / (negativeNumber + positiveNumber);
        MixtureModelProb[i][1] = positiveaccu / (negativeaccu + positiveaccu);
    }

    XYSeriesCollection dataset = new XYSeriesCollection();
    dataset.addSeries(model1);
    dataset.addSeries(model2);
    dataset.addSeries(model3);

    HistogramDataset histogramDataset = new HistogramDataset();
    histogramDataset.setType(HistogramType.SCALE_AREA_TO_1);
    histogramDataset.addSeries("ID hits", IDObs, 100);
    histogramDataset.addSeries("Decoy hits", DecoyObs, 100);
    //histogramDataset.addSeries("Model hits", ModelObs, 100);

    JFreeChart chart = ChartFactory.createHistogram(FilenameUtils.getBaseName(pngfile), "Score", "Hits",
            histogramDataset, PlotOrientation.VERTICAL, true, false, false);
    XYPlot plot = chart.getXYPlot();

    NumberAxis domain = (NumberAxis) plot.getDomainAxis();
    domain.setRange(min, max);
    plot.setBackgroundPaint(Color.white);
    plot.setDomainGridlinePaint(Color.white);
    plot.setRangeGridlinePaint(Color.white);
    plot.setForegroundAlpha(0.8f);
    chart.setBackgroundPaint(Color.white);

    XYLineAndShapeRenderer render = new XYLineAndShapeRenderer();
    //        render.setSeriesPaint(0, Color.DARK_GRAY);
    //        render.setSeriesPaint(1, Color.DARK_GRAY); 
    //        render.setSeriesPaint(2, Color.GREEN); 
    //        render.setSeriesShape(0, new Ellipse2D.Double(0, 0, 2, 2));
    //        render.setSeriesShape(1, new Ellipse2D.Double(0, 0, 2, 2));
    //        render.setSeriesShape(2, new Ellipse2D.Double(0, 0, 2.5f, 2.5f));
    //        render.setSeriesStroke(1, new BasicStroke(1.0f));
    //        render.setSeriesStroke(0, new BasicStroke(1.0f));
    //        render.setSeriesStroke(2, new BasicStroke(2.0f));
    plot.setDataset(1, dataset);
    plot.setRenderer(1, render);
    plot.setDatasetRenderingOrder(DatasetRenderingOrder.FORWARD);
    try {
        ChartUtilities.saveChartAsPNG(new File(pngfile), chart, 1000, 600);
    } catch (IOException e) {
    }
}