public void TestBinChi2()
{
int npiece = 1000;
double bw = 1.0 / npiece;
double nsig = 10000;
double[] edges = NP.Linspace(0,1, npiece);
double[] x = NP.MidPoints(edges);
double[] y = NP.Broadcast(
(xx) => nsig*bw*GenericPDF.gaussian_flat(xx, 0.5, 0.1),
x);
PDF pdf = (v) => {
double xx = v[0];
double mu = v[1];
double sigma = v[2];
double N = v[3];
return N*GenericPDF.gaussian_flat(xx, mu, sigma);
};
double[] arg = { 0.5, 0.1, nsig };
BinChi2 x2 = new BinChi2(pdf, edges, y);
double chi2 = x2.Compute(arg);
Assert.IsTrue(chi2 < 1.0);
}
/// <summary>
/// Construct PeakFitter from initialpeakguess, histogam edges+values,
/// </summary>
/// <param name="guess">Initial peak guess.</param>
/// <param name="edges">edges of the truncated histogram</param>
/// <param name="y">histogram value</param>
/// <param name="sigma">Uncertainty on Y</param>
/// <returns>PeakFitter</returns>
public static PeakFitter FromGuess(InitialPeakGuess guess, double[] edges, double[] y, double[] sigma = null)
{
PeakingPDF pdf = PeakingPDF.OfInitialPeakGuess(guess);
BinChi2 x2 = new BinChi2(pdf.Compute, edges, y, sigma);
string[] paramnames = pdf.ParamNames(); //full paramname with x
string[] pname = new string[paramnames.Length - 1]; //Dock off x
for (int i = 0; i < pname.Length; i++)
{
pname[i] = paramnames[i + 1];
}
Minuit minuit = new Minuit((FCN)(x2.Compute), pname);
minuit.SetInitialValue("mu", guess.mu);
minuit.SetInitialValue("sigma", guess.sigma);
minuit.SetInitialValue("nsig", guess.nsig);
minuit.SetInitialValue("m", guess.m);
minuit.SetInitialValue("c", guess.c);
minuit.SetInitialValue("nbkg", guess.nbkg);
PeakFitter ret = new PeakFitter() { pdf = pdf, minuit = minuit, edges=edges};
return ret;
}
