public static double[] FitLorenzianToSlaveData(CavityScanData data, double limitLow, double limitHigh)
{
double[] voltages = data.parameters.CalculateRampVoltages();
LorentzianFitter lorentzianFitter = new LorentzianFitter();
// takes the parameters (in this order, in the double[])
// N: background
// Q: signal
// c: centre
// w: width
dataPoint max = getMax(data.SlavePhotodiodeData);
dataPoint min = getMin(data.SlavePhotodiodeData);
lorentzianFitter.Fit(voltages, data.SlavePhotodiodeData,
new double[] { min.value, max.value - min.value,
voltages[max.index], (data.parameters.High - data.parameters.Low) / 10, });
double[] coefficients = lorentzianFitter.Parameters;
fitFailSafe(coefficients, limitLow, limitHigh);
return(new double[] { coefficients[3], coefficients[2], coefficients[1], coefficients[0] }); //to be consistent with old convention.
}
public static double[] FitLorenzianToData(double[] voltages, double[] signal)
{
double high = getMax(voltages).value;
double low = getMin(voltages).value;
System.Diagnostics.Debug.WriteLine(" " + low.ToString() + " " + high.ToString());
LorentzianFitter lorentzianFitter = new LorentzianFitter();
// takes the parameters (in this order, in the double[])
// N: background
// Q: signal
// c: centre
// w: width
dataPoint max = getMax(signal);
dataPoint min = getMin(signal);
lorentzianFitter.Fit(voltages, signal,
new double[] { min.value, max.value - min.value,
voltages[max.index], (high - low) / 10, });
double[] coefficients = lorentzianFitter.Parameters;
fitFailSafe(coefficients, low, high);
return(new double[] { coefficients[3], coefficients[2], coefficients[1], coefficients[0] }); //to be consistent with old convention.
}
public static LorentzianFit FitLorentzianToData(double[] voltages, double[] signal, LorentzianFit bestGuess)
{
LorentzianFitter lorentzianFitter = new LorentzianFitter();
lorentzianFitter.Fit(voltages, signal, new double[] { bestGuess.Background, bestGuess.Amplitude, bestGuess.Centre, bestGuess.Width });
double[] coefficients = lorentzianFitter.Parameters;
LorentzianFit fit = new LorentzianFit(coefficients[0], coefficients[1], coefficients[2], coefficients[3]);
double minCentrePosition = voltages.Min();
double maxCentrePosition = voltages.Max();
fit = fitFailSafe(fit, minCentrePosition, maxCentrePosition);
return(fit);
}
//This function speeds up the fitting process by passing the last fitted parameters as a guess,
// and by restricting the fit to only those points near to the peak
public static double[] FitLorenzianToData(double[] voltages, double[] signal, double[] parameters, double pointsToConsiderEitherSideOfPeakInFWHMs, int maximumNLMFSteps)
{
double high = getMax(voltages).value;
double low = getMin(voltages).value;
double pointsToConsider = 0;
System.Diagnostics.Debug.WriteLine(" " + low.ToString() + " " + high.ToString());
LorentzianFitter lorentzianFitter = new LorentzianFitter();
double[][] allxypairs = new double[voltages.Length][];
int j = 0;
for (int i = 0; i < voltages.Length; i++)
{
allxypairs[i] = new double[2];
allxypairs[i][0] = voltages[i];
allxypairs[i][1] = signal[i];
}
if (pointsToConsiderEitherSideOfPeakInFWHMs * parameters[0] < 10)
{
pointsToConsider = 10;
}
else
{
pointsToConsider = pointsToConsiderEitherSideOfPeakInFWHMs * parameters[0];
}
for (int i = 0; i < voltages.Length; i++)
{
if ((allxypairs[i][0] > (parameters[1] - pointsToConsider)) && (allxypairs[i][0] < (parameters[1] + pointsToConsider)))
{
j++;
}
}
double[] selectedvoltages = new double[j];
double[] selectedsignal = new double[j];
for (int i = 0, k = 0; i < voltages.Length; i++)
{
if ((allxypairs[i][0] > (parameters[1] - pointsToConsider)) && (allxypairs[i][0] < (parameters[1] + pointsToConsider)))
{
selectedvoltages[k] = allxypairs[i][0];
selectedsignal[k] = allxypairs[i][1];
k++;
}
}
// takes the parameters (in this order, in the double[])
// N: background
// Q: signal
// c: centre
// w: width
dataPoint max = getMax(signal);
dataPoint min = getMin(signal);
lorentzianFitter.Fit(selectedvoltages, selectedsignal,
new double[] { parameters[3], parameters[2], parameters[1], parameters[0] }, 0, 0, maximumNLMFSteps);
double[] coefficients = lorentzianFitter.Parameters;
fitFailSafe(coefficients, low, high);
return(new double[] { coefficients[3], coefficients[2], coefficients[1], coefficients[0] }); //to be consistent with old convention.
}
