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; } }