protected void plotScatterDiagram() {
// plot sample as one dimensional scatter plot and Gaussian
double xmax = 5.;
double xmin = -5.;
DatanGraphics.openWorkstation(getClass().getName(), "E3Min_1.ps");
DatanGraphics.setFormat(0., 0.);
DatanGraphics.setWindowInComputingCoordinates(xmin, xmax, 0., .5);
DatanGraphics.setViewportInWorldCoordinates(-.15, .9, .16, .86);
DatanGraphics.setWindowInWorldCoordinates(-.414, 1., 0., 1.);
DatanGraphics.setBigClippingWindow();
DatanGraphics.chooseColor(2);
DatanGraphics.drawFrame();
DatanGraphics.drawScaleX("y");
DatanGraphics.drawScaleY("f(y)");
DatanGraphics.drawBoundary();
double xpl[] = new double[2];
double ypl[] = new double[2];
// plot scatter diagram
DatanGraphics.chooseColor(1);
for (int i = 0; i < y.length; i++) {
xpl[0] = y[i];
xpl[1] = y[i];
ypl[0] = 0.;
ypl[0] = .1;
DatanGraphics.drawPolyline(xpl, ypl);
}
// draw Gaussian corresponding to solution
int npl = 100;
xpl = new double[npl];
ypl = new double[npl];
double fact = 1. / (Math.sqrt(2. * Math.PI) * x.getElement(1));
double dpl = (xmax - xmin) / (double) (npl - 1);
for (int i = 0; i < npl; i++) {
xpl[i] = xmin + (double) i * dpl;
ypl[i] = fact * Math.exp(-.5 * Math.pow((xpl[i] - x.getElement(0)) / x.getElement(1), 2.));
}
DatanGraphics.chooseColor(5);
DatanGraphics.drawPolyline(xpl, ypl);
// draw caption
String sn = "N = " + nny;
numForm.setMaximumFractionDigits(3);
numForm.setMinimumFractionDigits(3);
String sx1 = ", x_1# = " + numForm.format(x.getElement(0));
String sx2 = ", x_2# = " + numForm.format(x.getElement(1));
String sdx1 = ", &D@x_1# = " + numForm.format(Math.sqrt(cx.getElement(0, 0)));
String sdx2 = ", &D@x_2# = " + numForm.format(Math.sqrt(cx.getElement(1, 1)));
caption = sn + sx1 + sx2 + sdx1 + sdx2;
DatanGraphics.setBigClippingWindow();
DatanGraphics.chooseColor(2);
DatanGraphics.drawCaption(1., caption);
DatanGraphics.closeWorkstation();
}
public E3Min() {
numForm = NumberFormat.getNumberInstance(Locale.US);
numForm.setMaximumFractionDigits(12);
numForm.setMinimumFractionDigits(12);
String s =
"Example demonstrating the use of class MinAsy by fitting a Gaussian to small sample"
+ " and determining the asymmetric errors of parameters by MinAsy";
df = new DatanFrame(getClass().getName(), s);
AuxJInputGroup ig = new AuxJInputGroup("Enter number N of events (>= 2, <= 10000)", "");
JLabel errorLabel = new JLabel();
ni[0] = new AuxJNumberInput("N", "number of events", errorLabel);
ig.add(ni[0]);
ni[0].setProperties("N", true);
ni[0].setMinimum(2);
ni[0].setMaximum(10000);
ni[0].setNumberInTextField(10);
df.add(ig);
df.add(errorLabel);
JButton goButton = new JButton("Go");
GoButtonListener gl = new GoButtonListener();
goButton.addActionListener(gl);
df.add(goButton);
df.repaint();
}