XYIntervalSeriesCollection seriesCollection = new XYIntervalSeriesCollection(); for (XYIntervalSeries series : moveTypeToSeriesMapList.get(scoreLevelIndex).values()) { seriesCollection.addSeries(series);
XYIntervalSeriesCollection seriesCollection = new XYIntervalSeriesCollection(); for (XYIntervalSeries series : moveTypeToSeriesMapList.get(scoreLevelIndex).values()) { seriesCollection.addSeries(series);
dataset.addSeries(series); plot.setDataset(seriesIndex, dataset);
dataset.addSeries(series);
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) { regressionDataset.addSeries(computeRegressionData(min, max)); computeCoefficientOfDetermination(); } } }
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(); } } } }
dataset.addSeries(pop);
scatterpointsDataset.addSeries(scatterValues);
scatterpointsDataset.addSeries(scatterValues);