private void computeChartDataIfPossible() {
// need to do this later: all GUI events must be processed first in order to get the correct
// state
SwingUtilities.invokeLater(
() -> {
if (scatterPlotModel.pointDataSource != null
&& scatterPlotModel.dataField != null
&& scatterPlotModel.pointDataSource.getFeatureCollection() != null
&& scatterPlotModel.pointDataSource.getFeatureCollection().features() != null
&& scatterPlotModel.pointDataSource.getFeatureCollection().features().hasNext()
&& scatterPlotModel.pointDataSource.getFeatureCollection().features().next() != null
&& scatterPlotModel
.pointDataSource
.getFeatureCollection()
.features()
.next()
.getAttribute(scatterPlotModel.dataField.getLocalName())
!= null
&& getRaster() != null) {
compute(scatterPlotModel.useRoiMask ? scatterPlotModel.roiMask : null);
} else {
scatterpointsDataset.removeAllSeries();
acceptableDeviationDataset.removeAllSeries();
regressionDataset.removeAllSeries();
getPlot().removeAnnotation(r2Annotation);
computedDatas = null;
}
});
}
private void finishScalingUpdate(
AxisRangeControl axisRangeControl, ValueAxis newAxis, ValueAxis oldAxis) {
if (axisRangeControl.isAutoMinMax()) {
newAxis.setAutoRange(false);
acceptableDeviationDataset.removeAllSeries();
regressionDataset.removeAllSeries();
getPlot().removeAnnotation(r2Annotation);
newAxis.setAutoRange(true);
axisRangeControl.adjustComponents(newAxis, 3);
newAxis.setAutoRange(false);
computeRegressionAndAcceptableDeviationData();
} else {
newAxis.setAutoRange(false);
newAxis.setRange(oldAxis.getRange());
}
}
private void computeRegressionAndAcceptableDeviationData() {
acceptableDeviationDataset.removeAllSeries();
regressionDataset.removeAllSeries();
getPlot().removeAnnotation(r2Annotation);
if (computedDatas != null) {
final ValueAxis domainAxis = getPlot().getDomainAxis();
final double min = domainAxis.getLowerBound();
final double max = domainAxis.getUpperBound();
acceptableDeviationDataset.addSeries(computeAcceptableDeviationData(min, max));
if (scatterPlotModel.showRegressionLine) {
final XYIntervalSeries series = computeRegressionData(min, max);
if (series != null) {
regressionDataset.addSeries(series);
computeCoefficientOfDetermination();
}
}
}
}
@Override
public void populate(XYPlot plot, AROTraceData analysis) {
if (analysis != null) {
gpsData.removeAllSeries();
// create the GPS dataset...
Map<GpsState, XYIntervalSeries> seriesMap =
new EnumMap<GpsState, XYIntervalSeries>(GpsState.class);
for (GpsState eventType : GpsState.values()) {
XYIntervalSeries series = new XYIntervalSeries(eventType);
seriesMap.put(eventType, series);
gpsData.addSeries(series);
}
Iterator<GpsInfo> iter =
analysis.getAnalyzerResult().getTraceresult().getGpsInfos().iterator();
if (iter.hasNext()) {
while (iter.hasNext()) {
GpsInfo gpsEvent = iter.next();
if (gpsEvent.getGpsState() != GpsState.GPS_DISABLED) {
seriesMap
.get(gpsEvent.getGpsState())
.add(
gpsEvent.getBeginTimeStamp(),
gpsEvent.getBeginTimeStamp(),
gpsEvent.getEndTimeStamp(),
0.5,
0,
1);
}
}
}
XYItemRenderer renderer = plot.getRenderer();
renderer.setSeriesPaint(gpsData.indexOf(GpsState.GPS_STANDBY), Color.YELLOW);
renderer.setSeriesPaint(gpsData.indexOf(GpsState.GPS_ACTIVE), new Color(34, 177, 76));
// Assign ToolTip to renderer
renderer.setBaseToolTipGenerator(
new XYToolTipGenerator() {
@Override
public String generateToolTip(XYDataset dataset, int series, int item) {
GpsState eventType = (GpsState) gpsData.getSeries(series).getKey();
return MessageFormat.format(
ResourceBundleHelper.getMessageString("gps.tooltip"),
dataset.getX(series, item),
ResourceBundleHelper.getEnumString(eventType));
}
});
}
plot.setDataset(gpsData);
}
private void updateDataSet() {
if (!isInitialized) {
return;
}
dataset.removeAllSeries();
double dx = 0.5 * dataSourceConfig.boxSize;
if (profileData != null) {
final float[] sampleValues = profileData.getSampleValues();
final float[] sampleSigmas = profileData.getSampleSigmas();
XYIntervalSeries series =
new XYIntervalSeries(
getRaster() != null ? getRaster().getName() : DEFAULT_SAMPLE_DATASET_NAME);
for (int x = 0; x < sampleValues.length; x++) {
final float y = sampleValues[x];
final float dy = sampleSigmas[x];
series.add(x, x - dx, x + dx, y, y - dy, y + dy);
}
dataset.addSeries(series);
if (dataSourceConfig.useCorrelativeData
&& dataSourceConfig.pointDataSource != null
&& dataSourceConfig.dataField != null) {
XYIntervalSeries corrSeries =
new XYIntervalSeries(
getCorrelativeDataLabel(
dataSourceConfig.pointDataSource, dataSourceConfig.dataField));
int[] shapeVertexIndexes = profileData.getShapeVertexIndexes();
SimpleFeature[] simpleFeatures =
dataSourceConfig.pointDataSource.getFeatureCollection().toArray(new SimpleFeature[0]);
if (shapeVertexIndexes.length == simpleFeatures.length) {
int fieldIndex =
getAttributeIndex(dataSourceConfig.pointDataSource, dataSourceConfig.dataField);
if (fieldIndex != -1) {
for (int i = 0; i < simpleFeatures.length; i++) {
Number attribute = (Number) simpleFeatures[i].getAttribute(fieldIndex);
if (attribute != null) {
final double x = shapeVertexIndexes[i];
final double y = attribute.doubleValue();
corrSeries.add(x, x, x, y, y, y);
}
}
dataset.addSeries(corrSeries);
}
} else {
System.out.println("Weird things happened:");
System.out.println(" shapeVertexIndexes.length = " + shapeVertexIndexes.length);
System.out.println(" simpleFeatures.length = " + simpleFeatures.length);
}
}
profilePlotDisplay.restoreAutoBounds();
xAxisRangeControl
.getBindingContext()
.setComponentsEnabled(
PROPERTY_NAME_MARK_SEGMENTS, profileData.getShapeVertices().length > 2);
}
}
