fitConvolution.C File Reference

Detailed Description

Tutorial for convolution of two functions

 
 FCN=298.12 FROM MIGRAD    STATUS=CONVERGED     457 CALLS         458 TOTAL
                     EDM=1.08093e-08    STRATEGY= 1      ERROR MATRIX ACCURATE 
  EXT PARAMETER                                   STEP         FIRST   
  NO.   NAME      VALUE            ERROR          SIZE      DERIVATIVE 
   1  p0           7.32859e+00   3.70795e-02   1.23437e-05  -3.46193e-02
   2  p1           7.33040e-02   2.44083e-03   3.62176e-06  -7.16223e-02
   3  p2          -2.26420e+00   4.91803e-02   5.24021e-05  -1.27917e-02
   4  p3           1.12811e+00   6.28810e-02   1.94847e-05  -2.72591e-02

 
#include <TCanvas.h>
#include <TRandom.h>
#include <TF1Convolution.h>
#include <TF1.h>
#include <TH1F.h>
 
void fitConvolution()
{
   // Construction of histogram to fit.
   TH1F *h_ExpGauss = new TH1F("h_ExpGauss", "Exponential convoluted by Gaussian", 100, 0., 5.);
   for (int i = 0; i < 1e6; i++) {
      // Gives a alpha of -0.3 in the exp.
      double x = gRandom->Exp(1. / 0.3);
      x += gRandom->Gaus(0., 3.);
      // Probability density function of the addition of two variables is the
      // convolution of two density functions.
      h_ExpGauss->Fill(x);
   }
 
   TF1Convolution *f_conv = new TF1Convolution("expo", "gaus", -1, 6, true);
   f_conv->SetRange(-1., 6.);
   f_conv->SetNofPointsFFT(1000);
   TF1 *f = new TF1("f", *f_conv, 0., 5., f_conv->GetNpar());
   f->SetParameters(1., -0.3, 0., 1.);
 
   // Fit.
   new TCanvas("c", "c", 800, 1000);
   h_ExpGauss->Fit("f");
   h_ExpGauss->Draw();
}

Author

Aurelie Flandi

Definition in file fitConvolution.C.