Loading [MathJax]/extensions/tex2jax.js
Logo ROOT   6.08/07
Reference Guide
All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Properties Friends Macros Modules Pages
TwoHistoFit2D.C File Reference

Detailed Description

View in nbviewer Open in SWAN Example to fit two histograms at the same time.

pict1_TwoHistoFit2D.C.png
Processing /mnt/build/workspace/root-makedoc-v608/rootspi/rdoc/src/v6-08-00-patches/tutorials/fit/TwoHistoFit2D.C...
Do global fit
PARAMETER DEFINITIONS:
NO. NAME VALUE STEP SIZE LIMITS
1 p0 1.00000e+02 1.00000e-02 no limits
2 p1 6.00000e+00 1.00000e-02 no limits
3 p2 2.00000e+00 1.00000e-02 no limits
4 p3 7.00000e+00 1.00000e-02 no limits
5 p4 3.00000e+00 1.00000e-02 no limits
6 p5 1.00000e+02 1.00000e-02 no limits
7 p6 1.20000e+01 1.00000e-02 no limits
8 p7 3.00000e+00 1.00000e-02 no limits
9 p8 1.10000e+01 1.00000e-02 no limits
10 p9 2.00000e+00 1.00000e-02 no limits
**********
** 1 **SET PRINT 0 1.008e-321
**********
**********
** 2 **MIGRAD 5000 0.01
**********
MIGRAD MINIMIZATION HAS CONVERGED.
FCN=4015.63 FROM MIGRAD STATUS=CONVERGED 525 CALLS 526 TOTAL
EDM=7.6486e-07 STRATEGY= 1 ERROR MATRIX UNCERTAINTY 4.8 per cent
EXT PARAMETER STEP FIRST
NO. NAME VALUE ERROR SIZE DERIVATIVE
1 p0 2.55114e+01 2.22488e-01 1.18177e-03 1.29664e-03
2 p1 6.03551e+00 1.56999e-02 1.78147e-04 5.19787e-02
3 p2 1.95953e+00 1.34972e-02 1.02338e-04 -2.33229e-02
4 p3 7.09821e+00 3.32869e-02 2.39025e-04 2.42668e-02
5 p4 2.94271e+00 2.42010e-02 -1.88552e-04 2.78492e-03
6 p5 2.63145e+01 2.69272e-01 -2.31447e-03 -2.60065e-03
7 p6 1.19850e+01 3.51596e-02 4.24095e-04 -3.93611e-02
8 p7 2.90086e+00 2.64547e-02 8.06256e-05 -5.19640e-03
9 p8 1.09762e+01 1.47334e-02 -6.74373e-05 -1.09628e-02
10 p9 1.95760e+00 1.14466e-02 2.85422e-05 -1.15592e-01
Chi2 Fit = 4015.63 ndf = 3921 3921
(int) 0
#include "TH2D.h"
#include "TF2.h"
#include "TCanvas.h"
#include "TStyle.h"
#include "TRandom3.h"
#include "TVirtualFitter.h"
#include "TList.h"
#include <vector>
#include <map>
#include <iostream>
double gauss2D(double *x, double *par) {
double z1 = double((x[0]-par[1])/par[2]);
double z2 = double((x[1]-par[3])/par[4]);
return par[0]*exp(-0.5*(z1*z1+z2*z2));
}
double my2Dfunc(double *x, double *par) {
double *p1 = &par[0];
double *p2 = &par[5];
return gauss2D(x,p1) + gauss2D(x,p2);
}
// data need to be globals to be visible by fcn
std::vector<std::pair<double, double> > coords;
std::vector<double > values;
std::vector<double > errors;
void myFcn(Int_t & /*nPar*/, Double_t * /*grad*/ , Double_t &fval, Double_t *p, Int_t /*iflag */ )
{
int n = coords.size();
double chi2 = 0;
double tmp,x[2];
for (int i = 0; i <n; ++i ) {
x[0] = coords[i].first;
x[1] = coords[i].second;
tmp = ( values[i] - my2Dfunc(x,p))/errors[i];
chi2 += tmp*tmp;
}
fval = chi2;
}
TRandom3 rndm;
void FillHisto(TH2D * h, int n, double * p) {
const double mx1 = p[1];
const double my1 = p[3];
const double sx1 = p[2];
const double sy1 = p[4];
const double mx2 = p[6];
const double my2 = p[8];
const double sx2 = p[7];
const double sy2 = p[9];
//const double w1 = p[0]*sx1*sy1/(p[5]*sx2*sy2);
const double w1 = 0.5;
double x, y;
for (int i = 0; i < n; ++i) {
// generate randoms with larger gaussians
rndm.Rannor(x,y);
double r = rndm.Rndm(1);
if (r < w1) {
x = x*sx1 + mx1;
y = y*sy1 + my1;
}
else {
x = x*sx2 + mx2;
y = y*sy2 + my2;
}
h->Fill(x,y);
}
}
int TwoHistoFit2D(bool global = true) {
// create two histograms
int nbx1 = 50;
int nby1 = 50;
int nbx2 = 50;
int nby2 = 50;
double xlow1 = 0.;
double ylow1 = 0.;
double xup1 = 10.;
double yup1 = 10.;
double xlow2 = 5.;
double ylow2 = 5.;
double xup2 = 20.;
double yup2 = 20.;
TH2D * h1 = new TH2D("h1","core",nbx1,xlow1,xup1,nby1,ylow1,yup1);
TH2D * h2 = new TH2D("h2","tails",nbx2,xlow2,xup2,nby2,ylow2,yup2);
double iniParams[10] = { 100, 6., 2., 7., 3, 100, 12., 3., 11., 2. };
// create fit function
TF2 * func = new TF2("func",my2Dfunc,xlow2,xup2,ylow2,yup2, 10);
func->SetParameters(iniParams);
// fill Histos
int n1 = 50000;
int n2 = 50000;
// h1->FillRandom("func", n1);
//h2->FillRandom("func",n2);
FillHisto(h1,n1,iniParams);
FillHisto(h2,n2,iniParams);
// scale histograms to same heights (for fitting)
double dx1 = (xup1-xlow1)/double(nbx1);
double dy1 = (yup1-ylow1)/double(nby1);
double dx2 = (xup2-xlow2)/double(nbx2);
double dy2 = (yup2-ylow2)/double(nby2);
// h1->Sumw2();
// h1->Scale( 1.0 / ( n1 * dx1 * dy1 ) );
// scale histo 2 to scale of 1
h2->Sumw2();
h2->Scale( ( double(n1) * dx1 * dy1 ) / ( double(n2) * dx2 * dy2 ) );
if (global) {
// fill data structure for fit (coordinates + values + errors)
std::cout << "Do global fit" << std::endl;
// fit now all the function together
// fill data structure for fit (coordinates + values + errors)
TAxis *xaxis1 = h1->GetXaxis();
TAxis *yaxis1 = h1->GetYaxis();
TAxis *xaxis2 = h2->GetXaxis();
TAxis *yaxis2 = h2->GetYaxis();
int nbinX1 = h1->GetNbinsX();
int nbinY1 = h1->GetNbinsY();
int nbinX2 = h2->GetNbinsX();
int nbinY2 = h2->GetNbinsY();
/// reset data structure
coords = std::vector<std::pair<double,double> >();
values = std::vector<double>();
errors = std::vector<double>();
for (int ix = 1; ix <= nbinX1; ++ix) {
for (int iy = 1; iy <= nbinY1; ++iy) {
if ( h1->GetBinContent(ix,iy) > 0 ) {
coords.push_back( std::make_pair(xaxis1->GetBinCenter(ix), yaxis1->GetBinCenter(iy) ) );
values.push_back( h1->GetBinContent(ix,iy) );
errors.push_back( h1->GetBinError(ix,iy) );
}
}
}
for (int ix = 1; ix <= nbinX2; ++ix) {
for (int iy = 1; iy <= nbinY2; ++iy) {
if ( h2->GetBinContent(ix,iy) > 0 ) {
coords.push_back( std::make_pair(xaxis2->GetBinCenter(ix), yaxis2->GetBinCenter(iy) ) );
values.push_back( h2->GetBinContent(ix,iy) );
errors.push_back( h2->GetBinError(ix,iy) );
}
}
}
for (int i = 0; i < 10; ++i) {
minuit->SetParameter(i, func->GetParName(i), func->GetParameter(i), 0.01, 0,0);
}
minuit->SetFCN(myFcn);
double arglist[100];
arglist[0] = 0;
// set print level
minuit->ExecuteCommand("SET PRINT",arglist,2);
// minimize
arglist[0] = 5000; // number of function calls
arglist[1] = 0.01; // tolerance
minuit->ExecuteCommand("MIGRAD",arglist,2);
//get result
double minParams[10];
double parErrors[10];
for (int i = 0; i < 10; ++i) {
minParams[i] = minuit->GetParameter(i);
parErrors[i] = minuit->GetParError(i);
}
double chi2, edm, errdef;
int nvpar, nparx;
minuit->GetStats(chi2,edm,errdef,nvpar,nparx);
func->SetParameters(minParams);
func->SetParErrors(parErrors);
func->SetChisquare(chi2);
int ndf = coords.size()-nvpar;
func->SetNDF(ndf);
std::cout << "Chi2 Fit = " << chi2 << " ndf = " << ndf << " " << func->GetNDF() << std::endl;
// add to list of functions
h1->GetListOfFunctions()->Add(func);
h2->GetListOfFunctions()->Add(func);
}
else {
// fit independently
h1->Fit(func);
h2->Fit(func);
}
// Create a new canvas.
TCanvas * c1 = new TCanvas("c1","Two HIstogram Fit example",100,10,900,800);
c1->Divide(2,2);
c1->cd(1);
h1->Draw();
func->SetRange(xlow1,ylow1,xup1,yup1);
func->DrawCopy("cont1 same");
c1->cd(2);
h1->Draw("lego");
func->DrawCopy("surf1 same");
c1->cd(3);
func->SetRange(xlow2,ylow2,xup2,yup2);
h2->Draw();
func->DrawCopy("cont1 same");
c1->cd(4);
h2->Draw("lego");
gPad->SetLogz();
func->Draw("surf1 same");
return 0;
}
Author
Rene Brun

Definition in file TwoHistoFit2D.C.