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

Introduction

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

Prototype

public DefaultBoxAndWhiskerCategoryDataset() 

Source Link

Document

Creates a new dataset.

Usage

From source file:FaceRatios.java

@SuppressWarnings("serial")
public static void main(String[] args) {
    int r = FSDK.ActivateLibrary(FACE_SDK_LICENSE);
    if (r == FSDK.FSDKE_OK) {
        FSDK.Initialize();/*  w w  w .j  a v  a  2  s. c  o m*/
        FSDK.SetFaceDetectionParameters(true, true, 384);

        Map<String, Map<String, ArrayList<Double>>> faceProperties = new HashMap<>();

        for (String directory : new File(FACE_DIRECTORY).list()) {
            if (new File(FACE_DIRECTORY + directory).isDirectory()) {
                Map<String, ArrayList<Double>> properties = new HashMap<String, ArrayList<Double>>() {
                    {
                        for (String property : propertyNames)
                            put(property, new ArrayList<Double>());
                    }
                };

                File[] files = new File(FACE_DIRECTORY + directory).listFiles();
                System.out.println("Analyzing " + directory + " with " + files.length + " files\n");
                for (File file : files) {
                    if (file.isFile()) {
                        HImage imageHandle = new HImage();
                        FSDK.LoadImageFromFileW(imageHandle, file.getAbsolutePath());

                        FSDK.TFacePosition.ByReference facePosition = new FSDK.TFacePosition.ByReference();
                        if (FSDK.DetectFace(imageHandle, facePosition) == FSDK.FSDKE_OK) {
                            FSDK_Features.ByReference facialFeatures = new FSDK_Features.ByReference();
                            FSDK.DetectFacialFeaturesInRegion(imageHandle, (FSDK.TFacePosition) facePosition,
                                    facialFeatures);

                            Point[] featurePoints = new Point[FSDK.FSDK_FACIAL_FEATURE_COUNT];
                            for (int i = 0; i < FSDK.FSDK_FACIAL_FEATURE_COUNT; i++) {
                                featurePoints[i] = new Point(0, 0);
                                featurePoints[i].x = facialFeatures.features[i].x;
                                featurePoints[i].y = facialFeatures.features[i].y;
                            }

                            double eyeDistance = featureDistance(featurePoints, FeatureID.LEFT_EYE,
                                    FeatureID.RIGHT_EYE);
                            double rightEyeSize = featureDistance(featurePoints,
                                    FeatureID.RIGHT_EYE_INNER_CORNER, FeatureID.RIGHT_EYE_OUTER_CORNER);
                            double leftEyeSize = featureDistance(featurePoints, FeatureID.LEFT_EYE_INNER_CORNER,
                                    FeatureID.LEFT_EYE_OUTER_CORNER);
                            double averageEyeSize = (rightEyeSize + leftEyeSize) / 2;

                            double mouthLength = featureDistance(featurePoints, FeatureID.MOUTH_RIGHT_CORNER,
                                    FeatureID.MOUTH_LEFT_CORNER);
                            double mouthHeight = featureDistance(featurePoints, FeatureID.MOUTH_BOTTOM,
                                    FeatureID.MOUTH_TOP);
                            double noseHeight = featureDistance(featurePoints, FeatureID.NOSE_BOTTOM,
                                    FeatureID.NOSE_BRIDGE);
                            double chinHeight = featureDistance(featurePoints, FeatureID.CHIN_BOTTOM,
                                    FeatureID.MOUTH_BOTTOM);

                            double chinToBridgeHeight = featureDistance(featurePoints, FeatureID.CHIN_BOTTOM,
                                    FeatureID.NOSE_BRIDGE);

                            double faceContourLeft = (featurePoints[FeatureID.CHIN_BOTTOM.getIndex()].getY()
                                    - featurePoints[FeatureID.FACE_CONTOUR2.getIndex()].getY())
                                    / (featurePoints[FeatureID.CHIN_BOTTOM.getIndex()].getX()
                                            - featurePoints[FeatureID.FACE_CONTOUR2.getIndex()].getX());
                            double faceContourRight = (featurePoints[FeatureID.CHIN_BOTTOM.getIndex()].getY()
                                    - featurePoints[FeatureID.FACE_CONTOUR12.getIndex()].getY())
                                    / (featurePoints[FeatureID.CHIN_BOTTOM.getIndex()].getX()
                                            - featurePoints[FeatureID.FACE_CONTOUR12.getIndex()].getX());

                            double bridgeLeftEyeDistance = featureDistance(featurePoints,
                                    FeatureID.LEFT_EYE_INNER_CORNER, FeatureID.NOSE_BRIDGE);
                            double bridgeRightEyeDistance = featureDistance(featurePoints,
                                    FeatureID.RIGHT_EYE_INNER_CORNER, FeatureID.NOSE_BRIDGE);

                            properties.get("eyeSize/eyeDistance").add(averageEyeSize / eyeDistance);
                            properties.get("eyeSizeDisparity")
                                    .add(Math.abs(leftEyeSize - rightEyeSize) / averageEyeSize);
                            properties.get("bridgeToEyeDisparity")
                                    .add(Math.abs(bridgeLeftEyeDistance - bridgeRightEyeDistance)
                                            / ((bridgeLeftEyeDistance + bridgeRightEyeDistance) / 2));
                            properties.get("eyeDistance/mouthLength").add(eyeDistance / mouthLength);
                            properties.get("eyeDistance/noseHeight").add(eyeDistance / noseHeight);
                            properties.get("eyeSize/mouthLength").add(eyeDistance / mouthLength);
                            properties.get("eyeSize/noseHeight").add(eyeDistance / noseHeight);
                            properties.get("mouthLength/mouthHeight").add(mouthLength / mouthHeight);
                            properties.get("chinHeight/noseHeight").add(chinHeight / noseHeight);
                            properties.get("chinHeight/chinToBridgeHeight")
                                    .add(chinHeight / chinToBridgeHeight);
                            properties.get("noseHeight/chinToBridgeHeight")
                                    .add(noseHeight / chinToBridgeHeight);
                            properties.get("mouthHeight/chinToBridgeHeight")
                                    .add(mouthHeight / chinToBridgeHeight);
                            properties.get("faceCountourAngle")
                                    .add(Math.toDegrees(Math.atan((faceContourLeft - faceContourRight)
                                            / (1 + faceContourLeft * faceContourRight))));
                        }

                        FSDK.FreeImage(imageHandle);
                    }
                }

                System.out.format("%32s\t%8s\t%8s\t%3s%n", "Property", "", "", "c");
                System.out.println(new String(new char[76]).replace("\0", "-"));

                ArrayList<Entry<String, ArrayList<Double>>> propertyList = new ArrayList<>(
                        properties.entrySet());
                Collections.sort(propertyList, new Comparator<Entry<String, ArrayList<Double>>>() {
                    @Override
                    public int compare(Entry<String, ArrayList<Double>> arg0,
                            Entry<String, ArrayList<Double>> arg1) {
                        DescriptiveStatistics dStats0 = new DescriptiveStatistics(listToArray(arg0.getValue()));
                        DescriptiveStatistics dStats1 = new DescriptiveStatistics(listToArray(arg1.getValue()));
                        return new Double(dStats0.getStandardDeviation() / dStats0.getMean())
                                .compareTo(dStats1.getStandardDeviation() / dStats1.getMean());
                    }
                });

                for (Entry<String, ArrayList<Double>> property : propertyList) {
                    DescriptiveStatistics dStats = new DescriptiveStatistics(listToArray(property.getValue()));
                    System.out.format("%32s\t%4f\t%4f\t%3s%n", property.getKey(), dStats.getMean(),
                            dStats.getStandardDeviation(),
                            Math.round(dStats.getStandardDeviation() / dStats.getMean() * 100) + "%");
                }

                System.out.println("\n");
                faceProperties.put(directory, properties);
            }
        }

        for (String propertyName : propertyNames) {
            DefaultBoxAndWhiskerCategoryDataset dataset = new DefaultBoxAndWhiskerCategoryDataset();
            for (Entry<String, Map<String, ArrayList<Double>>> face : faceProperties.entrySet()) {
                dataset.add(face.getValue().get(propertyName), "Default Series", face.getKey());
            }

            PropertyBoxWhisker plot = new PropertyBoxWhisker(propertyName, dataset);
            plot.pack();
            plot.setVisible(true);
        }
    }
}

---

From source file:org.jfree.chart.demo.BoxAndWhiskerChartDemo1.java

private static BoxAndWhiskerCategoryDataset createDataset() {
    byte byte0 = 3;
    byte byte1 = 5;
    byte byte2 = 20;
    DefaultBoxAndWhiskerCategoryDataset defaultboxandwhiskercategorydataset = new DefaultBoxAndWhiskerCategoryDataset();
    for (int i = 0; i < byte0; i++) {
        for (int j = 0; j < byte1; j++) {
            @SuppressWarnings("rawtypes")
            List list = createValueList(0.0D, 20D, byte2);
            defaultboxandwhiskercategorydataset.add(list, "Series " + i, "Category " + j);
        }/*from w ww . j a v a2s .  c o  m*/

    }

    return defaultboxandwhiskercategorydataset;
}

---

From source file:edu.msu.cme.rdp.classifier.train.validation.distance.BoxPlotUtils.java

public static void readData(String inFile, File outdir, String xAxisLabel, String yAxisLabel)
        throws IOException {
    XYSeriesCollection dataset = new XYSeriesCollection();
    DefaultBoxAndWhiskerCategoryDataset scatterDataset = new DefaultBoxAndWhiskerCategoryDataset();

    BufferedReader reader = new BufferedReader(new FileReader(inFile));
    String line = reader.readLine();

    while ((line = reader.readLine()) != null) {
        String[] values = line.split("\\t");
        XYSeries series = new XYSeries(values[2]);
        dataset.addSeries(series);/*from  ww  w .  ja v a 2  s  .  c o m*/

        double average = Double.parseDouble(values[4]);
        int Q1 = Integer.parseInt(values[6]);
        ;
        int median = Integer.parseInt(values[7]);
        int Q3 = Integer.parseInt(values[8]);
        int pct_98 = Integer.parseInt(values[9]);
        int pct_2 = Integer.parseInt(values[10]);
        int minOutlier = 0; // we don't care about the outliers
        int maxOutlier = 0; //

        BoxAndWhiskerItem item = new BoxAndWhiskerItem(average, median, Q1, Q3, pct_2, pct_98, minOutlier,
                maxOutlier, new ArrayList());
        scatterDataset.add(item, values[2], "");
    }

    String title = new File(inFile).getName();
    int index = title.indexOf(".");
    if (index != -1) {
        title = title.substring(0, index);
    }

    Font lableFont = new Font("Helvetica", Font.BOLD, 28);
    createBoxplot(scatterDataset, new PrintStream(new File(outdir, title + ".boxchart.png")), title, xAxisLabel,
            yAxisLabel, lableFont);

}

---

From source file:wsattacker.plugin.intelligentdos.ui.helper.ChartHelper.java

public static JFreeChart createDumyChart() {
    final BoxAndWhiskerCategoryDataset dataset = new DefaultBoxAndWhiskerCategoryDataset();

    final CategoryAxis xAxis = new CategoryAxis("Type");
    final NumberAxis yAxis = new NumberAxis("Value");
    yAxis.setAutoRangeIncludesZero(false);
    final BoxAndWhiskerRenderer renderer = new BoxAndWhiskerRenderer();
    renderer.setFillBox(true);/*  ww  w. j a  va  2  s  .c  o m*/
    renderer.setMeanVisible(false);
    renderer.setMedianVisible(false);
    // renderer.setToolTipGenerator(new BoxAndWhiskerToolTipGenerator());
    final CategoryPlot plot = new CategoryPlot(dataset, xAxis, yAxis, renderer);

    return new JFreeChart(plot);
}

---

From source file:org.fhcrc.cpl.toolbox.gui.chart.PanelWithBoxAndWhiskerChart.java

protected void init() {
    dataset = new DefaultBoxAndWhiskerCategoryDataset();

    final BoxAndWhiskerRenderer renderer = new BoxAndWhiskerRenderer();
    renderer.setFillBox(false);/*from   ww  w. ja v  a  2s.co  m*/
    renderer.setToolTipGenerator(new BoxAndWhiskerToolTipGenerator());
    final CategoryAxis xAxis = new CategoryAxis("Type");
    final NumberAxis yAxis = new NumberAxis("Value");
    final CategoryPlot plot = new CategoryPlot(dataset, xAxis, yAxis, renderer);

    final JFreeChart chart = new JFreeChart(getName(), new Font("SansSerif", Font.BOLD, 14), plot, true);

    init(chart.getPlot());
}

---

From source file:playground.anhorni.PLOC.analysis.RunsEnsembleBoxPlot.java

public RunsEnsembleBoxPlot(final String chartTitle) {
    dataset = new DefaultBoxAndWhiskerCategoryDataset();
    this.chartTitle = chartTitle;
}

---

From source file:playground.anhorni.PLOC.analysis.MultipleEnsemblesBoxPlot.java

public MultipleEnsemblesBoxPlot(final String chartTitle) {
    dataset = new DefaultBoxAndWhiskerCategoryDataset();
    this.chartTitle = chartTitle;
}

---

From source file:umontreal.iro.lecuyer.charts.BoxSeriesCollection.java

/**
 * Creates a new <TT>BoxSeriesCollection</TT> instance with an empty dataset.
 * //from  ww w . j  a v  a  2 s  . co m
 */
public BoxSeriesCollection() {
    renderer = new BoxAndWhiskerRenderer();
    seriesCollection = new DefaultBoxAndWhiskerCategoryDataset();
    ((BoxAndWhiskerRenderer) renderer).setMaximumBarWidth(BARWIDTH);
}

---

From source file:org.jgrasstools.gears.utils.chart.CategoryBoxplot.java

private void createDataset() {
    dataset = new DefaultBoxAndWhiskerCategoryDataset();

    for (int i = 0; i < categories.length; i++) {
        final List<Double> list = new ArrayList<Double>();
        double[] catValues = values.get(i);
        for (int j = 0; j < catValues.length; j++) {
            list.add(catValues[j]);//from   w  w w .j  av  a 2s .  c  o  m
        }
        dataset.add(list, "", categories[i]);
    }

}

---

From source file:playground.wrashid.tryouts.mess.Boxplot.java

private static BoxAndWhiskerCategoryDataset createSampleDataset() {

    final int seriesCount = 3;
    final int categoryCount = 4;
    final int entityCount = 22;

    final DefaultBoxAndWhiskerCategoryDataset dataset = new DefaultBoxAndWhiskerCategoryDataset();
    for (int i = 0; i < seriesCount; i++) {
        for (int j = 0; j < categoryCount; j++) {
            final List list = new ArrayList();
            // add some values...
            for (int k = 0; k < entityCount; k++) {
                final double value1 = 10.0 + Math.random() * 3;
                list.add(new Double(value1));
                final double value2 = 11.25 + Math.random(); // concentrate values in the middle
                list.add(new Double(value2));
            }/* ww  w .  j a v a2s.c  om*/
            dataset.add(list, "Series " + i, " Type " + j);
        }

    }

    return dataset;
}

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