public TOFFitResults FitTOF(TOF t)
{
TOFFitResults results = new TOFFitResults();
double[] coefficients = new double[4];
// guess some reasonable values
coefficients[0] = t.Data[0];
coefficients[1] = ArrayOperation.GetMax(t.Data) - coefficients[0];
double lastT = t.Times[t.Times.Length - 1];
coefficients[2] = (t.Times[0] + lastT) / 2;
coefficients[3] = (lastT - t.Times[0]) / 5;
double mse = 0;
// this is totally tedious!
double[] times = new double[t.Times.Length];
for (int i = 0; i < t.Times.Length; i++)
{
times[i] = (double)t.Times[i];
}
CurveFit.NonLinearFit(times, t.Data, new ModelFunctionCallback(gaussian), coefficients, out mse, 1000000);
results.Background = coefficients[0];
results.Amplitude = coefficients[1];
results.Centre = coefficients[2];
results.Width = Math.Abs(coefficients[3]);
return(results);
}
public static double[] FitLorenzianToSlaveData(CavityScanData data, double limitLow, double limitHigh)
{
double mse = 0;
double[] voltages = data.parameters.CalculateRampVoltages();
double[] coefficients = new double[] { (data.parameters.High - data.parameters.Low) / 10, voltages[ArrayOperation.GetIndexOfMax(data.SlavePhotodiodeData)],
ArrayOperation.GetMax(data.SlavePhotodiodeData) - ArrayOperation.GetMin(data.SlavePhotodiodeData), 0 };
CurveFit.NonLinearFit(voltages, data.SlavePhotodiodeData, new ModelFunctionCallback(lorentzianNarrow),
coefficients, out mse, 4000);
fitFailSafe(coefficients, limitLow, limitHigh);
return(coefficients);
}