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 <stdio.h>
#include <TMath.h>
#include <TCanvas.h>
#include <iostream>
#include <TROOT.h>
#include <TChain.h>
#include <TObject.h>
#include <TRandom.h>
#include <TFile.h>
#include <math.h>
#include <TF1Convolution.h>
#include <TF1.h>
#include <TH1F.h>
#include <TGraph.h>
#include <TStopwatch.h>
 
using namespace std;
 
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++)
   {
      Double_t x = gRandom->Exp(1./0.3);//gives a alpha of -0.3 in the exp
      x += gRandom->Gaus(0.,3.);
      h_ExpGauss->Fill(x);//probability density function of the addition of two variables is the convolution of 2 dens. functions
   }
 
   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.