| 1 |
//////////////////////////////////////////////////////////////////////////
|
| 2 |
//Geng-yuan Jeng/UC Riverside
|
| 3 |
//2009/04/20 14:41:01
|
| 4 |
/////////////////////////////////////////////////////////////////////////
|
| 5 |
|
| 6 |
#ifndef __CINT__
|
| 7 |
#include "RooGlobalFunc.h"
|
| 8 |
#endif
|
| 9 |
#include "RooRealVar.h"
|
| 10 |
#include "RooDataSet.h"
|
| 11 |
#include "RooGaussian.h"
|
| 12 |
#include "TCanvas.h"
|
| 13 |
#include "RooPlot.h"
|
| 14 |
#include "TH1D.h"
|
| 15 |
#include "TTree.h"
|
| 16 |
using namespace RooFit;
|
| 17 |
// .493/.2114 j1
|
| 18 |
//.773/.3257 j2
|
| 19 |
// .863/.353 j3
|
| 20 |
//.808/.294 j4
|
| 21 |
void fitNewRelIso()
|
| 22 |
{
|
| 23 |
// TString fileName = "skimmed/QCDbinall_NewRelIso.root";
|
| 24 |
// TString fileName = "skimmed/QCDbin4_NewRelIso_CD30_rebin2.root";
|
| 25 |
// TString fileName = "skimmed/QCDbin3_NewRelIso_CD.root";
|
| 26 |
// TString fileName = "skimmed/QCDbin4_rebin.root";
|
| 27 |
// TString fileName = "skimmed/QCDbin4_NewRelIso_FastSim.root";
|
| 28 |
// TString fileName = "skimmed226/QCDbin4_005.root";
|
| 29 |
// TString fileName = "skimmed226/QCDbin4_005.root";
|
| 30 |
TString fileName = "skimmed226/QCDbin123_NewRelIso_FastSim_005.root";
|
| 31 |
|
| 32 |
// Dynamic(true) or static(false) range
|
| 33 |
bool dynamic = true;
|
| 34 |
int np = 100;
|
| 35 |
double epslon = 1.e-5;
|
| 36 |
double epslon1 = 1.e-6;
|
| 37 |
// Dynamic fit region weight
|
| 38 |
double itune1 = .25; // 0.15 for 1-3; 0.25 for 4
|
| 39 |
double itune2 = 1.65; //1.65
|
| 40 |
double itune3 = 1.25; //1.1 full 1.25 fast to limit upper fit range
|
| 41 |
double wxmin = 0.; // 1.81 1.7 (1.85 for fastsim 1.825 for full
|
| 42 |
double wxmax = 0.; // 0.9 .95 (/1.65 fast /2. full)
|
| 43 |
// Select fitting function:
|
| 44 |
// TString s0 = "landau";
|
| 45 |
// Select New or Old reliso:
|
| 46 |
// TString isoname = "New";
|
| 47 |
|
| 48 |
Double_t ax0=0.;
|
| 49 |
Double_t axf=0.05;
|
| 50 |
Double_t axF=0.1;
|
| 51 |
Double_t bx0=0.2; // 0.4 for 4 0.2 for 123
|
| 52 |
Double_t bxf=2.; // 2.0 for 4 1.0 for 123
|
| 53 |
int niter = 1;
|
| 54 |
int nsiter = 0;
|
| 55 |
Double_t temp = 0.;
|
| 56 |
Double_t tempb = 0.;
|
| 57 |
Double_t para[3] = {0.,0.,0.};
|
| 58 |
Double_t bound[3] = {10e6.,0.,0.};
|
| 59 |
int bmin;
|
| 60 |
int bmax;
|
| 61 |
int ndof;
|
| 62 |
|
| 63 |
gStyle->SetOptStat(1);
|
| 64 |
gStyle->SetPalette(1);
|
| 65 |
// Import histos
|
| 66 |
|
| 67 |
TFile *file = TFile::Open(fileName);
|
| 68 |
TTree *tree = (TTree*)file->Get("myTree");
|
| 69 |
TH1D *h0 = (TH1D*)file->Get("histos/h_RelIso_all");
|
| 70 |
TH1D *h1 = (TH1D*)file->Get("histos/h_RelIso_qcd");
|
| 71 |
Int_t jbin;
|
| 72 |
Double_t na;
|
| 73 |
tree->SetBranchAddress("jbin",&jbin);
|
| 74 |
tree->SetBranchAddress("na",&na);
|
| 75 |
tree->GetEntry(0);
|
| 76 |
// if(jbin != 0)
|
| 77 |
// itune1 *= jbin;
|
| 78 |
|
| 79 |
TH1D *h_all = (TH1D*)h0->Clone();
|
| 80 |
TH1D *h_qcd = (TH1D*)h1->Clone();
|
| 81 |
Int_t nbxMax = h_all->GetXaxis()->FindBin(2.0);
|
| 82 |
h_all->GetXaxis()->SetRange(2,h_all->GetXaxis()->FindBin(bxf));
|
| 83 |
Int_t nbMax = h_all->GetMaximumBin();
|
| 84 |
cout << "=========> Bin number at peak= " << nbMax << endl;
|
| 85 |
h_all->GetXaxis()->SetRange(1,nbxMax);
|
| 86 |
TAxis *axis0 = h_all->GetXaxis();
|
| 87 |
double bwidth = axis0->GetBinWidth(nbMax);
|
| 88 |
cout << "=========> bwidth = " << bwidth << endl;
|
| 89 |
|
| 90 |
cout << "\n>>>>> Iteration step: "<< niter << endl;
|
| 91 |
|
| 92 |
RooRealVar x("x","x",0.,2.);
|
| 93 |
RooRealVar y("y","y",0.,2.);
|
| 94 |
RooDataHist *dh0 = new RooDataHist("dh0","dh0",x,Import(*h0));
|
| 95 |
RooDataHist *dh1 = new RooDataHist("dh1","dh1",x,Import(*h1));
|
| 96 |
RooDataHist *dhy0 = new RooDataHist("dhy0","dhy0",y,Import(*h0));
|
| 97 |
RooDataHist *dhy1 = new RooDataHist("dhy1","dhy1",y,Import(*h1));
|
| 98 |
// Choose signal region:
|
| 99 |
x.setRange("signalregion",ax0,axf);
|
| 100 |
// x.setRange("signalregion",ax0,axF);
|
| 101 |
x.setRange("ctrlregion",bx0,bxf);
|
| 102 |
|
| 103 |
// S e t u p m o d e l
|
| 104 |
// ---------------------
|
| 105 |
|
| 106 |
// Declare variables x,mean,sigma with associated name, title, initial value and allowed range
|
| 107 |
// Exponential parameters
|
| 108 |
RooRealVar lamda("lamda","decay constant of exponential",1,-100.,100.);
|
| 109 |
// Gaussian parameters
|
| 110 |
RooRealVar mean("mean","mean of gaussian",1.5,0.,2.);
|
| 111 |
RooRealVar sigma("sigma","width of gaussian",1,0.,100.);
|
| 112 |
// Landau parameters
|
| 113 |
RooRealVar MPV("MPV","mean of landau",1,0,2);
|
| 114 |
RooRealVar Sig("Sig","sigma of landau",1,0,2);
|
| 115 |
// Build gaussian p.d.f in terms of x,mean and sigma
|
| 116 |
RooExponential expo("expo","exponential PDF",x,lamda);
|
| 117 |
RooGaussian gauss("gauss","gaussian PDF",x,mean,sigma);
|
| 118 |
RooLandau landau("landau","landau PDF",x,MPV,Sig);
|
| 119 |
// Build model
|
| 120 |
// RooRealVar elfrac("elfrac","fraction of Exponential and Landau",0.05,0.,1.);
|
| 121 |
// RooRealVar glfrac("glfrac","fraction of Gaussian and Landau",0.,0.,1.);
|
| 122 |
// RooAddPdf model("model","g+l",RooArgList(gauss,landau),glfrac);
|
| 123 |
|
| 124 |
// Construct plot frame in 'x'
|
| 125 |
RooPlot* xframe = x.frame(Title("Landau p.d.f. with data"));
|
| 126 |
RooPlot* yframe = y.frame(Title("Landau p.d.f. with data"));
|
| 127 |
|
| 128 |
// P l o t m o d e l a n d c h a n g e p a r a m e t e r v a l u e s
|
| 129 |
// ---------------------------------------------------------------------------
|
| 130 |
// Change the value of Parameters
|
| 131 |
// sigma.setVal(2.);
|
| 132 |
// MPV.setVal(0.8412);
|
| 133 |
// Sig.setVal(0.314);
|
| 134 |
// Plot gauss in frame (i.e. in x) and draw frame on canvas
|
| 135 |
// gauss.plotOn(xframe);
|
| 136 |
// landau.plotOn(xframe,LineColor(kRed));
|
| 137 |
|
| 138 |
// Make a second plot frame in x and draw both the
|
| 139 |
// data and the p.d.f in the frame
|
| 140 |
dh0->plotOn(xframe,MarkerStyle(23),MarkerColor(2),LineColor(2),XErrorSize(0));
|
| 141 |
dh1->plotOn(xframe,MarkerStyle(22),MarkerColor(9),LineColor(9),XErrorSize(0));
|
| 142 |
dhy0->plotOn(yframe,MarkerStyle(23),MarkerColor(2),LineColor(2),XErrorSize(0));
|
| 143 |
dhy1->plotOn(yframe,MarkerStyle(22),MarkerColor(9),LineColor(9),XErrorSize(0));
|
| 144 |
|
| 145 |
// F i t m o d e l t o d a t a
|
| 146 |
// -----------------------------
|
| 147 |
|
| 148 |
// Fit pdf to data
|
| 149 |
RooFitResult*rest = landau.fitTo(*dh0,Range("ctrlregion"),PrintLevel(-1),Save());
|
| 150 |
rest->Print("v");
|
| 151 |
niter++;
|
| 152 |
RooAbsReal* nQCDsigw = landau.createIntegral(x,NormSet(x),Range("signalregion"));
|
| 153 |
RooAbsReal* nQCDbkgw = landau.createIntegral(x,NormSet(x),Range("ctrlregion"));
|
| 154 |
nQCDsigw->Print();
|
| 155 |
nQCDbkgw->Print();
|
| 156 |
// Draw all frames on a canvas
|
| 157 |
Double_t xb0 = bx0;
|
| 158 |
Double_t xbf = bxf;
|
| 159 |
wxmin = (MPV.getVal() - itune1)/Sig.getVal();
|
| 160 |
wxmax = wxmin/itune2;
|
| 161 |
|
| 162 |
TAxis *axis = h0->GetXaxis();
|
| 163 |
if (dynamic) {
|
| 164 |
TCanvas* c = new TCanvas("fitNewRelIso","fitNewRelIso",1000,600);
|
| 165 |
c->Divide(2,1);
|
| 166 |
c->cd(1);
|
| 167 |
|
| 168 |
xb0 = MPV.getVal()-wxmin*Sig.getVal();
|
| 169 |
xbf = MPV.getVal()+wxmax*Sig.getVal();
|
| 170 |
if (xb0 < 2.*axf )
|
| 171 |
xb0 = 2.*axf;
|
| 172 |
if (xbf > itune3)
|
| 173 |
xbf = itune3;
|
| 174 |
|
| 175 |
for (;niter <= np && nsiter < 2; niter++){
|
| 176 |
xb0 = MPV.getVal()-wxmin*Sig.getVal();
|
| 177 |
xbf = MPV.getVal()+wxmax*Sig.getVal();
|
| 178 |
if (xb0 < 2.*axf )
|
| 179 |
xb0 = 2.*axf;
|
| 180 |
if (xbf > itune3)
|
| 181 |
xbf = itune3;
|
| 182 |
|
| 183 |
bmin = axis->FindBin(xb0);
|
| 184 |
bmax = axis->FindBin(xbf);
|
| 185 |
// number of bins of non-empty entries (>5) - (num params. of Landau+1)
|
| 186 |
ndof = bmax-bmin+1-4;
|
| 187 |
|
| 188 |
cout << "\n>>>>> Iteration step: "<< niter << endl;
|
| 189 |
cout << "=========> xb0, xbf = " << xb0 << ", " << xbf << endl;
|
| 190 |
// x.setRange("ctrlregion",xb0.getVal(),xbf.getVal());
|
| 191 |
x.setRange("ctrlregion",xb0,xbf);
|
| 192 |
x.setRange("intregion",0.,xbf);
|
| 193 |
x.setRange("centregion",axf,xb0);
|
| 194 |
|
| 195 |
// Construct a chi^2 of the data and the model,
|
| 196 |
// which is the input probability density scaled
|
| 197 |
// by the number of events in the dataset
|
| 198 |
// RooChi2Var chi2("chi2","chi2",landau,*dh0,Range(xb0.getVal(),xbf.getVal()));
|
| 199 |
RooChi2Var chi2("chi2","chi2",landau,*dh0,Range("ctrlregion"));
|
| 200 |
// Use RooMinuit interface to minimize chi^2
|
| 201 |
RooMinuit m(chi2);
|
| 202 |
m.migrad();
|
| 203 |
m.hesse();
|
| 204 |
|
| 205 |
if ((fabs(chi2.getVal()/ndof - bound[0]) <= epslon) ||
|
| 206 |
(fabs(chi2.getVal()/ndof - temp) <= epslon) ||
|
| 207 |
(fabs(xb0 - tempb) < = epslon1 )
|
| 208 |
){
|
| 209 |
nsiter++;
|
| 210 |
cout << "=========> Conditions converge for " << nsiter << " time(s)" << endl;
|
| 211 |
}
|
| 212 |
if (chi2.getVal()/ndof < bound[0]){
|
| 213 |
bound[0] = chi2.getVal()/ndof;
|
| 214 |
bound[1] = xb0;
|
| 215 |
bound[2] = xbf;
|
| 216 |
para[1] = MPV.getVal();
|
| 217 |
para[2] = Sig.getVal();
|
| 218 |
nQCDsigw = landau.createIntegral(x,NormSet(x),Range("signalregion"));
|
| 219 |
nQCDbkgw = landau.createIntegral(x,NormSet(x),Range("ctrlregion"));
|
| 220 |
cout << "=========> New Min Norm. chi2 = " << chi2.getVal()/ndof <<endl;
|
| 221 |
cout << "=========> Fitting range = " << bound[1] << " to " << bound[2] << endl;
|
| 222 |
landau.plotOn(xframe,NormRange("intregion"),Range("ctrlregion"),LineColor(niter+1));
|
| 223 |
landau.paramOn(xframe,Layout(0.28,0.75,0.42));
|
| 224 |
landau.plotOn(xframe,NormRange("intregion"),Range("signalregion"),LineColor(niter+1));
|
| 225 |
landau.plotOn(xframe,NormRange("intregion"),Range("centregion"),
|
| 226 |
LineColor(niter+1),LineStyle(4));
|
| 227 |
xframe->Draw();
|
| 228 |
nQCDsigw->Print();
|
| 229 |
nQCDbkgw->Print();
|
| 230 |
}
|
| 231 |
temp = chi2.getVal()/ndof;
|
| 232 |
tempb = xb0;
|
| 233 |
}
|
| 234 |
cout << "=========> Norm. chi2 of the last iteration = " << chi2.getVal()/ndof << endl;
|
| 235 |
cout << "=========> Fit range of the last iteration = " << xb0 << " to " << xbf << endl;
|
| 236 |
cout << "=========> MPV = " << MPV.getVal() << "; Sig = " << Sig.getVal() << endl;
|
| 237 |
cout << "================================================================" << endl;
|
| 238 |
|
| 239 |
// plot
|
| 240 |
Double_t mpv1 = para[1];
|
| 241 |
Double_t sig1 = para[2];
|
| 242 |
RooRealVar MPV1("MPV1","MPV1",mpv1);
|
| 243 |
RooRealVar Sig1("Sig1","Sig1",sig1);
|
| 244 |
RooLandau landau1("landau1","landau1",y,MPV1,Sig1);
|
| 245 |
cout << "=========> Minimum Norm. chi2 = " << bound[0] << endl;
|
| 246 |
cout << "=========> Final fit range = " << bound[1] << " to " << bound[2] << endl;
|
| 247 |
cout << "=========> Calculate nQCDsigw and nQCDbkgw: " << endl;
|
| 248 |
cout << "=========> Final MPV = para[1] = " << para[1] << endl;
|
| 249 |
cout << "=========> Final SIG = para[2] = " << para[2] << endl;
|
| 250 |
|
| 251 |
y.setRange("signalregion",ax0,axf);
|
| 252 |
y.setRange("centralregion",axf,bound[1]);
|
| 253 |
y.setRange("ctrlregion",bound[1],bound[2]);
|
| 254 |
nQCDsigw = landau1.createIntegral(y,NormSet(y),Range("signalregion"));
|
| 255 |
nQCDbkgw = landau1.createIntegral(y,NormSet(y),Range("ctrlregion"));
|
| 256 |
nQCDsigw->Print();
|
| 257 |
nQCDbkgw->Print();
|
| 258 |
|
| 259 |
landau1.plotOn(yframe,NormRange("ctrlregion"),Range("ctrlregion"));
|
| 260 |
landau1.plotOn(yframe,NormRange("ctrlregion"),Range("centralregion"),
|
| 261 |
LineColor(3),LineStyle(kDashed));
|
| 262 |
landau1.plotOn(yframe,NormRange("ctrlregion"),Range("signalregion"),LineColor(2));
|
| 263 |
c->cd(2);
|
| 264 |
yframe->Draw();
|
| 265 |
|
| 266 |
}
|
| 267 |
else { // Fixed range
|
| 268 |
|
| 269 |
TCanvas* c = new TCanvas("fitNewRelIso","fitNewRelIso",800,600);
|
| 270 |
para[1] = MPV.getVal();
|
| 271 |
para[2] = Sig.getVal();
|
| 272 |
bound[1] = bx0;
|
| 273 |
bound[2] = bxf;
|
| 274 |
bmin = axis->FindBin(bound[1]);
|
| 275 |
bmax = axis->FindBin(bound[2]);
|
| 276 |
// number of bins of non-empty entries (>5) - (num params. of Landau+1)
|
| 277 |
bound[0] = rest->minNll();
|
| 278 |
cout << "=========> Final fit range = " << bound[1] << " to " << bound[2] << endl;
|
| 279 |
// Print values of mean and sigma (that now reflect fitted values and errors)
|
| 280 |
cout << "=========> Final MPV = para[1] = " << para[1] << endl;
|
| 281 |
cout << "=========> Final SIG = para[2] = " << para[2] << endl;
|
| 282 |
|
| 283 |
x.setRange("signalregion",ax0,axf);
|
| 284 |
x.setRange("centralregion",axf,bound[1]);
|
| 285 |
x.setRange("ctrlregion",bound[1],bound[2]);
|
| 286 |
|
| 287 |
landau.plotOn(xframe,NormRange("ctrlregion"),Range("ctrlregion"));
|
| 288 |
landau.plotOn(xframe,NormRange("ctrlregion"),Range("centralregion"),
|
| 289 |
LineColor(3),LineStyle(kDashed));
|
| 290 |
landau.plotOn(xframe,NormRange("ctrlregion"),Range("signalregion"),LineColor(2));
|
| 291 |
xframe->Draw();
|
| 292 |
|
| 293 |
}
|
| 294 |
// h0->SetLineColor(9);
|
| 295 |
// h0->SetLineStyle(2);
|
| 296 |
// h0->SetLineWidth(2);
|
| 297 |
h0->Draw("same");
|
| 298 |
// h1->SetLineStyle(3);
|
| 299 |
// h1->SetLineWidth(2);
|
| 300 |
h1->SetLineColor(9); //40
|
| 301 |
// h1->SetFillStyle(3020); // 3018
|
| 302 |
// h1->SetFillColor(41); //38
|
| 303 |
h1->Draw("same");
|
| 304 |
|
| 305 |
// Get number of events within fitted region ==> cross check
|
| 306 |
TAxis *axis = h0->GetXaxis();
|
| 307 |
bmin = axis->FindBin(xb0);
|
| 308 |
bmax = axis->FindBin(xbf);
|
| 309 |
if ( !dynamic )
|
| 310 |
cout << "=========> Minimized FCN = " << bound[0] << endl;
|
| 311 |
double nfac = h0->Integral(bmin,bmax);
|
| 312 |
nfac -= (h0->GetBinContent(bmin))*(xb0-axis->GetBinLowEdge(bmin))/axis->GetBinWidth(bmin);
|
| 313 |
nfac -= (h0->GetBinContent(bmax))*(axis->GetBinUpEdge(bmax)-xbf)/axis->GetBinWidth(bmax);
|
| 314 |
cout << "=========> Final Nfac = " << nfac << endl;
|
| 315 |
// nQCDsigw->Print();
|
| 316 |
// nQCDbkgw->Print();
|
| 317 |
Double_t nQCDsig = nfac * nQCDsigw->getVal()/nQCDbkgw->getVal();
|
| 318 |
cout << "=========> Number of observed QCD evts = " << nQCDsig << endl;
|
| 319 |
// Print results
|
| 320 |
cout << "\n";
|
| 321 |
cout << ">>>>> Jet bin " << jbin << ":" << endl;
|
| 322 |
if ( dynamic ){
|
| 323 |
cout << ">>>>> itune1 = " << itune1 << "; ";
|
| 324 |
cout << "itune2 = " << itune2 << endl;
|
| 325 |
cout << ">>>>> wxmin = " << wxmin << "; ";
|
| 326 |
cout << "wxmax = " << wxmax << endl;
|
| 327 |
}
|
| 328 |
cout << ">>>>> Observed Ns = " << nQCDsig << endl;
|
| 329 |
cout << ">>>>> Expected Na = " << na << endl;
|
| 330 |
cout << "Deviation = " << (nQCDsig-na)/na*100.0 << " %" <<endl;
|
| 331 |
|
| 332 |
}
|
