Logo ROOT   6.16/01
Reference Guide
fitNormSum.C File Reference

Detailed Description

View in nbviewer Open in SWAN Tutorial for normalized sum of two functions Here: a background exponential and a crystalball function Parameters can be set:

  1. with the TF1 object before adding the function (for 3) and 4))
  2. with the TF1NormSum object (first two are the coefficients, then the non constant parameters)
  3. with the TF1 object after adding the function

Sum can be constructed by:

  1. by a string containing the names of the functions and/or the coefficient in front
  2. by a string containg formulas like expo, gaus...
  3. by the list of functions and coefficients (which are 1 by default)
  4. by a std::vector for functions and coefficients
Time to generate 1050000 events: Real time 0:00:00, CP time 0.160
****************************************
Minimizer is Minuit2 / Migrad
Chi2 = 1021.04
NDf = 993
Edm = 8.20922e-06
NCalls = 233
NSignal = 50083 +/- 1235.87
NBackground = 998896 +/- 1573.51
Mean = 2.99897 +/- 0.00224467
Sigma = 0.297886 +/- 0.00230899
Alpha = 2.12449 +/- 0.140022
N = 1.15624 +/- 0.474843
Slope = -0.300343 +/- 0.000644416
Time to fit using ROOT TF1Normsum: Real time 0:00:00, CP time 0.160
#include <TMath.h>
#include <TCanvas.h>
#include <TF1NormSum.h>
#include <TF1.h>
#include <TH1.h>
using namespace std;
void fitNormSum()
{
const int nsig = 5.E4;
const int nbkg = 1.e6;
Int_t NEvents = nsig+nbkg;
Int_t NBins = 1e3;
double signal_mean = 3;
TF1 *f_cb = new TF1("MyCrystalBall","crystalball",-5.,5.);
TF1 *f_exp = new TF1("MyExponential","expo",-5.,5.);
// I.:
f_exp-> SetParameters(1.,-0.3);
f_cb -> SetParameters(1,signal_mean,0.3,2,1.5);
// CONSTRUCTION OF THE TF1NORMSUM OBJECT ........................................
// 1) :
TF1NormSum *fnorm_exp_cb = new TF1NormSum(f_cb,f_exp,nsig,nbkg);
// 4) :
TF1 * f_sum = new TF1("fsum", *fnorm_exp_cb, -5., 5., fnorm_exp_cb->GetNpar());
f_sum->Draw();
// III.:
f_sum->SetParameters( fnorm_exp_cb->GetParameters().data() );
f_sum->SetParName(1,"NBackground");
f_sum->SetParName(0,"NSignal");
for (int i = 2; i < f_sum->GetNpar(); ++i)
f_sum->SetParName(i,fnorm_exp_cb->GetParName(i) );
// GENERATE HISTOGRAM TO FIT ..............................................................
w.Start();
TH1D *h_sum = new TH1D("h_ExpCB", "Exponential Bkg + CrystalBall function", NBins, -5., 5.);
for (int i=0; i<NEvents; i++)
{
h_sum -> Fill(f_sum -> GetRandom());
}
printf("Time to generate %d events: ",NEvents);
w.Print();
//TH1F *h_orig = new TH1F(*h_sum);
// need to scale histogram with width since we are fitting a density
h_sum -> Sumw2();
h_sum -> Scale(1., "width");
//fit - use Minuit2 if available
new TCanvas("Fit","Fit",800,1000);
// do a least-square fit of the spectrum
auto result = h_sum -> Fit("fsum","SQ");
result->Print();
h_sum -> Draw();
printf("Time to fit using ROOT TF1Normsum: ");
w.Print();
// test if parameters are fine
std::vector<double> pref = {nsig, nbkg, signal_mean};
for (unsigned int i = 0; i< pref.size(); ++i) {
if (!TMath::AreEqualAbs(pref[i], f_sum->GetParameter(i), f_sum->GetParError(i)*10.) )
Error("testFitNormSum","Difference found in fitted %s - difference is %g sigma",f_sum->GetParName(i), (f_sum->GetParameter(i)-pref[i])/f_sum->GetParError(i));
}
// add parameters
auto t1 = new TLatex(-2.5, 300000, TString::Format("%s = %8.0f #pm %4.0f", "NSignal",f_sum->GetParameter(0), f_sum->GetParError(0) ) );
auto t2 = new TLatex(-2.5, 270000, TString::Format("%s = %8.0f #pm %4.0f", "Nbackgr",f_sum->GetParameter(1), f_sum->GetParError(1) ) );
t1->Draw();
t2->Draw();
}
int Int_t
Definition: RtypesCore.h:41
void Error(const char *location, const char *msgfmt,...)
void SetParameters(TFitEditor::FuncParams_t &pars, TF1 *func)
Restore the parameters from pars into the function.
Definition: TFitEditor.cxx:287
R__EXTERN TStyle * gStyle
Definition: TStyle.h:406
static void SetDefaultMinimizer(const char *type, const char *algo=0)
The Canvas class.
Definition: TCanvas.h:31
Class adding two functions: c1*f1+c2*f2.
Definition: TF1NormSum.h:19
const char * GetParName(Int_t ipar) const
Definition: TF1NormSum.h:66
std::vector< double > GetParameters() const
Return array of parameters.
Definition: TF1NormSum.cxx:288
Int_t GetNpar() const
Return the number of (non constant) parameters including the coefficients: for 2 functions: c1,...
Definition: TF1NormSum.cxx:360
1-Dim function class
Definition: TF1.h:211
virtual Double_t GetParError(Int_t ipar) const
Return value of parameter number ipar.
Definition: TF1.cxx:1904
virtual Int_t GetNpar() const
Definition: TF1.h:465
virtual const char * GetParName(Int_t ipar) const
Definition: TF1.h:513
virtual void SetParName(Int_t ipar, const char *name)
Set name of parameter number ipar.
Definition: TF1.cxx:3443
virtual void Draw(Option_t *option="")
Draw this function with its current attributes.
Definition: TF1.cxx:1312
virtual void SetParameters(const Double_t *params)
Definition: TF1.h:628
virtual Double_t GetParameter(Int_t ipar) const
Definition: TF1.h:496
1-D histogram with a double per channel (see TH1 documentation)}
Definition: TH1.h:614
To draw Mathematical Formula.
Definition: TLatex.h:18
Stopwatch class.
Definition: TStopwatch.h:28
void Start(Bool_t reset=kTRUE)
Start the stopwatch.
Definition: TStopwatch.cxx:58
void Print(Option_t *option="") const
Print the real and cpu time passed between the start and stop events.
Definition: TStopwatch.cxx:219
static TString Format(const char *fmt,...)
Static method which formats a string using a printf style format descriptor and return a TString.
Definition: TString.cxx:2286
void SetOptStat(Int_t stat=1)
The type of information printed in the histogram statistics box can be selected via the parameter mod...
Definition: TStyle.cxx:1444
TFitResultPtr Fit(FitObject *h1, TF1 *f1, Foption_t &option, const ROOT::Math::MinimizerOptions &moption, const char *goption, ROOT::Fit::DataRange &range)
Definition: HFitImpl.cxx:134
Bool_t AreEqualAbs(Double_t af, Double_t bf, Double_t epsilon)
Definition: TMath.h:412
STL namespace.
th1 Draw()
auto * t1
Definition: textangle.C:20
Author
Lorenzo Moneta

Definition in file fitNormSum.C.