private XYIntervalSeries computeAcceptableDeviationData(double lowerBound, double upperBound) {
final XYSeries identity =
DatasetUtilities.sampleFunction2DToSeries(x -> x, lowerBound, upperBound, 100, "1:1 line");
final XYIntervalSeries xyIntervalSeries = new XYIntervalSeries(identity.getKey());
for (int i = 0; i < identity.getItemCount(); i++) {
XYDataItem item = identity.getDataItem(i);
final double x = item.getXValue();
final double y = item.getYValue();
if (scatterPlotModel.showAcceptableDeviation) {
final double acceptableDeviation = scatterPlotModel.acceptableDeviationInterval;
final double xOff = acceptableDeviation * x / 100;
final double yOff = acceptableDeviation * y / 100;
xyIntervalSeries.add(x, x - xOff, x + xOff, y, y - yOff, y + yOff);
} else {
xyIntervalSeries.add(x, x, x, y, y, y);
}
}
return xyIntervalSeries;
}
public void addData(DataChannel c) {
try {
int col = 1;
addLabel(lineOffset, 0, c.toString() + " Time (ms)");
addLabel(lineOffset + 1, 0, c.toString() + " Value");
for (Object o : c.getSeries().getItems()) {
XYDataItem i = (XYDataItem) o;
addNumber(lineOffset, col, i.getXValue());
addNumber(lineOffset + 1, col, i.getYValue());
col++;
}
} catch (RowsExceededException e) {
// TODO Auto-generated catch block
e.printStackTrace();
} catch (WriteException e) {
// TODO Auto-generated catch block
e.printStackTrace();
}
lineOffset += 2;
}
private XYIntervalSeries computeRegressionData(double xStart, double xEnd) {
if (scatterpointsDataset.getItemCount(0) > 1) {
final double[] coefficients = Regression.getOLSRegression(scatterpointsDataset, 0);
final Function2D curve = new LineFunction2D(coefficients[0], coefficients[1]);
final XYSeries regressionData =
DatasetUtilities.sampleFunction2DToSeries(curve, xStart, xEnd, 100, "regression line");
final XYIntervalSeries xyIntervalRegression = new XYIntervalSeries(regressionData.getKey());
for (int i = 0; i < regressionData.getItemCount(); i++) {
XYDataItem item = regressionData.getDataItem(i);
final double x = item.getXValue();
final double y = item.getYValue();
xyIntervalRegression.add(x, x, x, y, y, y);
}
return xyIntervalRegression;
} else {
JOptionPane.showMessageDialog(
this,
"Unable to compute regression line.\n"
+ "At least 2 values are needed to compute regression coefficients.");
return null;
}
}
