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R2GGBBBiasStudy_mggjj.cc
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R2GGBBBiasStudy_mggjj.cc
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#include <cstring>
#include <cerrno>
#include <iostream>
#include <cstdlib>
#include <cmath>
#include <vector>
#include <string>
#include <stdexcept>
#include <algorithm>
#include <unistd.h>
#include <errno.h>
#include <iomanip>
// ROOT headers
#include "TCanvas.h"
#include "TAxis.h"
#include "TH1F.h"
#include "TF1.h"
#include "TFile.h"
#include "TTree.h"
#include "TIterator.h"
#include "TLatex.h"
#include "TString.h"
#include "TLegend.h"
#include "TGraphAsymmErrors.h"
#include "TFitResult.h"
// RooFit headers
#include "RooAbsPdf.h"
#include "RooDataHist.h"
#include "RooDataSet.h"
#include "RooHistPdf.h"
#include "RooMsgService.h"
#include "RooNLLVar.h"
#include "RooPlot.h"
#include "RooRandom.h"
#include "RooRealVar.h"
#include "RooWorkspace.h"
#include "TStyle.h"
// RooStats headers
#include "RooStats/HLFactory.h"
#include "RooStats/RooStatsUtils.h"
#include "RooAbsPdf.h"
#include "RooAddPdf.h"
#include "RooProdPdf.h"
#include "RooAbsData.h"
#include "RooPlot.h"
#include "RooGaussian.h"
#include "RooProduct.h"
#include "RooExtendPdf.h"
#include "RooBernstein.h"
#include "RooExponential.h"
#include "RooLandau.h"
#include "RooGenericPdf.h"
#include "RooMCStudy.h"
#include "RooFitResult.h"
#include "RooMinimizer.h"
#include "RooCmdArg.h"
#include "RooConstVar.h"
#include "RooRealVar.h"
#include "RooChi2MCSModule.h"
#include "GaussExp.h"
#include "ExpGaussExp.h"
#include "HiggsCSandWidth.h"
using namespace RooFit;
using namespace RooStats ;
Int_t NCAT = 3;
double mRadMin, mRadMax;
TString inDir = "./Trees/";
void AddBkgData(RooWorkspace*, int);
RooAbsPdf* BkgModelFit(RooWorkspace*, int, int);
void BkgModelBias(RooWorkspace*,int,RooAbsPdf*,FILE*);
void SetParamNames(RooWorkspace*);
void SetConstantParams(const RooArgSet* params);
Double_t effSigma(TH1 *hist);
RooArgSet* defineVariables()
{
// define variables of the input ntuple
RooRealVar* mJJ = new RooRealVar("mJJ","M(jj)",0,3000,"GeV");
RooRealVar* mGG = new RooRealVar("mGG","M(#gamma#gamma)",0,3000,"GeV");
RooRealVar* mRad = new RooRealVar("mRad","M(#gamma#gammajj)",mRadMin,mRadMax,"GeV");
RooRealVar* pt = new RooRealVar("pt","p_{T}(jj)",0,3000,"GeV");
RooRealVar* pt1 = new RooRealVar("pt1","p_{T}^{1}(jj)",0.0,3000,"GeV");
RooRealVar* pt2 = new RooRealVar("pt2","p_{T}^{2}(jj)",0.0,3000,"GeV");
RooRealVar* wei = new RooRealVar("wei","ptG1 x ptG2",0,1000,"");
RooRealVar* weiS = new RooRealVar("weiS","HqT x PUwei",0,1000,"");
RooCategory* bJetTagCategory = new RooCategory("bJetTagCategory","event category 4") ;
bJetTagCategory->defineType("cat4_0",0);
bJetTagCategory->defineType("cat4_1",1);
bJetTagCategory->defineType("cat4_2",2);
bJetTagCategory->defineType("cat4_3",3);
RooCategory* catMva = new RooCategory("catMva","MVA event category") ;
catMva->defineType("MVAcat_0",0);
catMva->defineType("MVAcat_1",1);
catMva->defineType("MVAcat_2",2);
catMva->defineType("MVAcat_3",3);
catMva->defineType("MVAcat_4",4);
catMva->defineType("MVAcat_5",5);
catMva->defineType("MVAcat_6",6);
catMva->defineType("MVAcat_7",7);
catMva->defineType("MVAcat_8",8);
RooCategory* catjet = new RooCategory("CATJET","event category par Njets") ;
catjet->defineType("catjet_0",0);
catjet->defineType("catjet_1",1);
RooCategory* vbftag = new RooCategory("vbfTag","Passed VBF selection") ;
vbftag->defineType("vbftag_0",0);
vbftag->defineType("vbftag_1",1);
RooCategory* vhtag = new RooCategory("metTag","Passed VH hadronic selection") ;
vhtag->defineType("vhtag_0",0);
vhtag->defineType("vhtag_1",1);
RooCategory* leptag = new RooCategory("lepTag","Passed lepton selection") ;
leptag->defineType("leptag_0",0);
leptag->defineType("leptag_1",1);
RooCategory* excltag = new RooCategory("NOEXCLTAG","Passed exclusive selection") ;
excltag->defineType("excltag_0",0);
excltag->defineType("excltag_1",1);
RooRealVar* MITBDTG = new RooRealVar("MITBDTG","MIT BDTG",0.05,1,"");
RooRealVar* phomvaid1 = new RooRealVar("phomvaid1","phomvaid 1",-0.3,1,"");
RooRealVar* phomvaid2 = new RooRealVar("phomvaid2","phomvaid 2",-0.3,1,"");
RooArgSet* ntplVars = new RooArgSet(*mJJ,*mRad,*pt,*pt1, *pt2, *bJetTagCategory, *wei, *weiS, *catjet);
ntplVars->add(*mGG);
ntplVars->add(*vbftag);
ntplVars->add(*vhtag);
ntplVars->add(*leptag);
ntplVars->add(*catMva);
ntplVars->add(*MITBDTG);
ntplVars->add(*phomvaid1);
ntplVars->add(*phomvaid2);
return ntplVars;
}
void runfits(int cat=0, int modelNum=-1, int inDirNum=0)
{
mRadMin=350; mRadMax=1200;
//create truth models
const int nTruthModels=9;
RooAbsPdf *MggjjBkgTruth[nTruthModels] = {0};
switch(inDirNum){
case 0: inDir=" /afs/cern.ch/work/h/hebda/HggHbb/ntuples/TreesCS_kinfit/"; break;
case 1: inDir=" /afs/cern.ch/work/h/hebda/HggHbb/ntuples/Trees_reg/"; break;
case 2: inDir=" /afs/cern.ch/work/h/hebda/HggHbb/ntuples/Trees_reg_kinfit/"; break;
case 3: inDir=" /afs/cern.ch/work/h/hebda/HggHbb/ntuples/Trees_kinfit/"; break;
}
TString card_name("hggjjSM_models_Pol_8TeV.rs");
HLFactory hlf("HLFactory", card_name, false);
RooWorkspace* w = hlf.GetWs();
AddBkgData(w,cat);
FILE *fout = fopen("resultsBiasMggjj.txt","a");
if(modelNum<=0) fprintf(fout,"%s\n",inDir.Data());
for(int m=0; m<nTruthModels; ++m) {
if(modelNum>=0 && m!=modelNum) continue;
MggjjBkgTruth[m] = BkgModelFit(w,cat,m); //Ber, Exp, Lan, Lau, Pow
BkgModelBias(w,cat,MggjjBkgTruth[m],fout);
}
if(modelNum<0 || modelNum==5) fprintf(fout,"\n\n");
fclose(fout);
return;
}
void AddBkgData(RooWorkspace* w, int cat) {
Int_t ncat = NCAT;
// common preselection cut
TString mainCut("1");
if(cat==0) mainCut = "90<mJJ && mJJ<160";
else if(cat==1) mainCut = "90<mJJ && mJJ<165";
else if(cat==2) mainCut = "90<mJJ && mJJ<165";
//****************************//
// Signal Data Set
//****************************//
// Variables
RooArgSet* ntplVars = defineVariables();
RooRealVar weightVar("weightVar","",1,0,1000);
//****************************//
// CMS Data Set
//****************************//
// retrieve the data tree;
// no common preselection cut applied yet;
TFile dataFile(inDir+"tree_data_weiMggjj.root");
TTree* dataTree = (TTree*) dataFile.Get("Events");
weightVar.setVal(1.);
ntplVars->add(RooArgList(weightVar));
RooDataSet Data("Data","dataset",dataTree,*ntplVars,"","wei");
// apply a common preselection cut;
// split into NCAT categories;
RooDataSet* dataToFit[9];
for (int c = 0; c < ncat; ++c) {
// Real data
dataToFit[c] = (RooDataSet*) Data.reduce(*w->var("mRad"),mainCut+TString::Format(" && bJetTagCategory==%d",c));
w->import(*dataToFit[c],Rename(TString::Format("Data_cat%d",c)));
}
// Create full data set without categorization
RooDataSet* data = (RooDataSet*) Data.reduce(*w->var("mRad"),mainCut);
w->import(*data, Rename("Data"));
data->Print("v");
}
RooAbsPdf *BkgModelFit(RooWorkspace* w, int c, int modelNum) {
std::vector<TString> catdesc;
catdesc.push_back("#scale[0.8]{Untagged}");
catdesc.push_back("#scale[0.8]{1-bjet tagged}");
catdesc.push_back("#scale[0.8]{2-bjet tagged}");
RooDataSet* data[9];
RooFitResult* fitresult[9];;
RooPlot* plotMggjjBkg[9];
Float_t minMassFit(mRadMin),maxMassFit(mRadMax);
RooRealVar* mGGJJ = w->var("mRad");
mGGJJ->setUnit("GeV");
TLatex *text = new TLatex();
text->SetNDC();
text->SetTextSize(0.04);
data[c] = (RooDataSet*) w->data(TString::Format("Data_cat%d",c));
RooFormulaVar *p1mod = new RooFormulaVar(TString::Format("p1mod_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_slope1_cat%d",c)));
RooFormulaVar *p2mod = new RooFormulaVar(TString::Format("p2mod_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_slope2_cat%d",c)));
RooFormulaVar *p3mod = new RooFormulaVar(TString::Format("p3mod_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_slope3_cat%d",c)));
RooFormulaVar *p4mod = new RooFormulaVar(TString::Format("p4mod_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_slope4_cat%d",c)));
RooFormulaVar *p5mod = new RooFormulaVar(TString::Format("p5mod_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_slope5_cat%d",c)));
RooFormulaVar *p1arg = new RooFormulaVar(TString::Format("p1arg_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_arg1_cat%d",c)));
RooFormulaVar *p2arg = new RooFormulaVar(TString::Format("p2arg_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_arg2_cat%d",c)));
RooFormulaVar *p3arg = new RooFormulaVar(TString::Format("p3arg_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_arg3_cat%d",c)));
RooFormulaVar *p4arg = new RooFormulaVar(TString::Format("p4arg_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_arg4_cat%d",c)));
RooFormulaVar *p5arg = new RooFormulaVar(TString::Format("p5arg_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_arg5_cat%d",c)));
RooFormulaVar *p1wid = new RooFormulaVar(TString::Format("p1wid_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_wid1_cat%d",c)));
RooFormulaVar *p2wid = new RooFormulaVar(TString::Format("p2wid_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_wid2_cat%d",c)));
RooFormulaVar *p3wid = new RooFormulaVar(TString::Format("p3wid_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_wid3_cat%d",c)));
RooFormulaVar *p4wid = new RooFormulaVar(TString::Format("p4wid_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_wid4_cat%d",c)));
RooFormulaVar *p5wid = new RooFormulaVar(TString::Format("p5wid_cat%d",c),"","@0",*w->var(TString::Format("mggjj_bkg_8TeV_wid5_cat%d",c)));
RooExponential* expo1 = new RooExponential("exp1","",*mGGJJ,*p1arg);
RooExponential* expo2 = new RooExponential("exp2","",*mGGJJ,*p2arg);
RooExponential* expo3 = new RooExponential("exp3","",*mGGJJ,*p3arg);
RooExponential* expo4 = new RooExponential("exp4","",*mGGJJ,*p4arg);
RooExponential* expo5 = new RooExponential("exp5","",*mGGJJ,*p5arg);
RooRealVar *p1mean = new RooRealVar("p1mean","",250,0,mRadMin);
RooRealVar *p2mean = new RooRealVar("p1mean","",250,0,mRadMin);
RooRealVar *p3mean = new RooRealVar("p1mean","",250,0,mRadMin);
RooRealVar *p4mean = new RooRealVar("p1mean","",250,0,mRadMin);
RooRealVar *p5mean = new RooRealVar("p1mean","",250,0,mRadMin);
RooLandau* lan1 = new RooLandau("lan1","",*mGGJJ,*p1mean,*p1wid);
RooLandau* lan2 = new RooLandau("lan2","",*mGGJJ,*p2mean,*p2wid);
RooLandau* lan3 = new RooLandau("lan3","",*mGGJJ,*p3mean,*p3wid);
RooLandau* lan4 = new RooLandau("lan4","",*mGGJJ,*p4mean,*p4wid);
RooLandau* lan5 = new RooLandau("lan5","",*mGGJJ,*p5mean,*p5wid);
const int totalNDOF=5;
int NDOF[totalNDOF]={0};
float minNLL[totalNDOF]={0.0}, chi2prob[totalNDOF]={-1.0};
int bestN = 0;
RooAbsPdf* MggjjBkgTmp[totalNDOF] = {0};
char fitName[10];
switch (modelNum){
case 0: {//Bernstein
RooRealVar* coeff[50];
RooArgList parlist;
//RooArgList parlist(*p1mod,*p2mod,*p3mod,*p4mod,*p5mod,*p1mod,*p2mod,*p3mod,*p4mod,"list");
for(int ii=0; ii<50; ++ii){
coeff[ii] = new RooRealVar(TString::Format("c_%d",ii),"coeff",1.0,-1000,1000);
parlist.add(*coeff[ii]);
}
MggjjBkgTmp[0] = new RooBernstein("BerN9", "", *mGGJJ, parlist);
parlist.add(*p5mod);
MggjjBkgTmp[1] = 0;//new RooBernstein("BerN10", "", *mGGJJ, parlist);
parlist.add(*p1arg);
MggjjBkgTmp[2] = new RooBernstein("BerN11", "", *mGGJJ, parlist);
parlist.add(*p2arg);
MggjjBkgTmp[3] = new RooBernstein("BerN12", "", *mGGJJ, parlist);
parlist.add(*p3arg);
MggjjBkgTmp[4] = new RooBernstein("BerN13", "", *mGGJJ, parlist);
sprintf(fitName,"Ber");
break;
}
case 1: //Exponential
w->factory(TString::Format("mggjj_bkg_8TeV_norm_cat%d[10.0,0.0,100000]",c));
MggjjBkgTmp[0] = new RooExtendPdf("ExpN1","",*expo1,*w->var(TString::Format("mggjj_bkg_8TeV_norm_cat%d",c)));
MggjjBkgTmp[1] = new RooAddPdf("ExpN2", "", RooArgList(*expo1,*expo2), RooArgList(*p1mod,*p2mod));
MggjjBkgTmp[2] = new RooAddPdf("ExpN3", "", RooArgList(*expo1,*expo2,*expo3), RooArgList(*p1mod,*p2mod,*p3mod));
MggjjBkgTmp[3] = new RooAddPdf("ExpN4", "", RooArgList(*expo1,*expo2,*expo3,*expo4), RooArgList(*p1mod,*p2mod,*p3mod,*p4mod));
MggjjBkgTmp[4] = new RooAddPdf("ExpN5", "", RooArgList(*expo1,*expo2,*expo3,*expo4,*expo5), RooArgList(*p1mod,*p2mod,*p3mod,*p4mod,*p5mod));
sprintf(fitName,"Exp");
break;
case 2: //Landau
w->factory(TString::Format("mggjj_bkg_8TeV_norm_cat%d[10.0,0.0,100000]",c));
MggjjBkgTmp[0] = new RooExtendPdf("LanN1","",*lan1,*w->var(TString::Format("mggjj_bkg_8TeV_norm_cat%d",c)));
MggjjBkgTmp[1] = new RooAddPdf("LanN2", "", RooArgList(*lan1,*lan2), RooArgList(*p1mod,*p2mod));
MggjjBkgTmp[2] = new RooAddPdf("LanN3", "", RooArgList(*lan1,*lan2,*lan3), RooArgList(*p1mod,*p2mod,*p3mod));
MggjjBkgTmp[3] = new RooAddPdf("LanN4", "", RooArgList(*lan1,*lan2,*lan3,*lan4), RooArgList(*p1mod,*p2mod,*p3mod,*p4mod));
MggjjBkgTmp[4] = new RooAddPdf("LanN5", "", RooArgList(*lan1,*lan2,*lan3,*lan4,*lan5), RooArgList(*p1mod,*p2mod,*p3mod,*p4mod,*p5mod));
sprintf(fitName,"Lan");
break;
case 3: //Laurent
MggjjBkgTmp[0] = new RooGenericPdf("LauN1","@1*pow(@0,-4)",RooArgList(*mGGJJ,*p1mod));
MggjjBkgTmp[1] = new RooGenericPdf("LauN2","@1*pow(@0,-4)+@2*pow(@0,-3)",RooArgList(*mGGJJ,*p1mod,*p2mod));
MggjjBkgTmp[2] = new RooGenericPdf("LauN3","@1*pow(@0,-4)+@2*pow(@0,-3)+@3*pow(@0,-5)",RooArgList(*mGGJJ,*p1mod,*p2mod,*p3mod));
MggjjBkgTmp[3] = new RooGenericPdf("LauN4","@1*pow(@0,-4)+@2*pow(@0,-3)+@3*pow(@0,-5)+@4*pow(@0,-2)",RooArgList(*mGGJJ,*p1mod,*p2mod,*p3mod,*p4mod));
MggjjBkgTmp[4] = new RooGenericPdf("LauN5","@1*pow(@0,-4)+@2*pow(@0,-3)+@3*pow(@0,-5)+@4*pow(@0,-2)+@5*pow(@0,-6)",RooArgList(*mGGJJ,*p1mod,*p2mod,*p3mod,*p4mod,*p5mod));
sprintf(fitName,"Lau");
break;
case 4: //Power
//MggjjBkgTmp[0] = new RooGenericPdf("PowN1","@1*pow(@0,@2)",RooArgList(*mGGJJ,*p1mod,*p1arg));
MggjjBkgTmp[0] = new RooGenericPdf("PowN1","@1*pow(@0,@2)",RooArgList(*mGGJJ,*p1mod,*p1arg));
MggjjBkgTmp[1] = new RooGenericPdf("PowN2","@1*pow(@0,@2)+@3*pow(@0,@4)",RooArgList(*mGGJJ,*p1mod,*p1arg,*p2mod,*p2arg));
MggjjBkgTmp[2] = new RooGenericPdf("PowN3","@1*pow(@0,@2)+@3*pow(@0,@4)+@5*pow(@0,@6)",RooArgList(*mGGJJ,*p1mod,*p1arg,*p2mod,*p2arg,*p3mod,*p3arg));
MggjjBkgTmp[3] = new RooGenericPdf("PowN4","@1*pow(@0,@2)+@3*pow(@0,@4)+@5*pow(@0,@6)+@7*pow(@0,@8)",RooArgList(*mGGJJ,*p1mod,*p1arg,*p2mod,*p2arg,*p3mod,*p3arg,*p4mod,*p4arg));
MggjjBkgTmp[4] = new RooGenericPdf("PowN5","@1*pow(@0,@2)+@3*pow(@0,@4)+@5*pow(@0,@6)+@7*pow(@0,@8)",RooArgList(*mGGJJ,*p1mod,*p1arg,*p2mod,*p2arg,*p3mod,*p3arg,*p4mod,*p4arg));
//MggjjBkgTmp[4] = new RooGenericPdf(TString::Format("MggjjBkg_cat%d",c),"@1*pow(@0,@2)+@3*pow(@0,@4)+@5*pow(@0,@6)+@7*pow(@0,@8)+@9*pow(@0,@10)",RooArgList(*mGGJJ,*p1mod,p*1arg,*p2mod,*p2arg,*p3mod,*p3arg,*p4mod,*p4arg,*p5mod,*p5arg));
sprintf(fitName,"Pow");
break;
case 5: //GaussExp
MggjjBkgTmp[0] = new GaussExp("GaussExp","GaussExp",*mGGJJ,*p1wid,*p2wid,*p3wid);
MggjjBkgTmp[1] = 0;
MggjjBkgTmp[2] = 0;
MggjjBkgTmp[3] = 0;
MggjjBkgTmp[4] = 0;
sprintf(fitName,"GaussExp");
break;
case 6: //ExpGaussExp
MggjjBkgTmp[0] = new ExpGaussExp("ExpGaussExp","ExpGaussExp",*mGGJJ,*p1wid,*p2wid,*p3wid,*p4wid);
MggjjBkgTmp[1] = 0;
MggjjBkgTmp[2] = 0;
MggjjBkgTmp[3] = 0;
MggjjBkgTmp[4] = 0;
sprintf(fitName,"ExpGaussExp");
break;
case 7:
MggjjBkgTmp[0] = new RooGenericPdf("LeveledExp","exp(@0/(@1-@0*@2))",RooArgList(*mGGJJ,*p1arg,*p2arg));
MggjjBkgTmp[1] = 0;
MggjjBkgTmp[2] = 0;
MggjjBkgTmp[3] = 0;
MggjjBkgTmp[4] = 0;
sprintf(fitName,"LeveledExp");
break;
case 8:
MggjjBkgTmp[0] = new RooGenericPdf("QCDFit","pow(1-@0/8000.0,@1)/pow(@0/8000.0,@2+@3*log(@0/8000.0))",RooArgList(*mGGJJ,*p1arg,*p2arg,*p3arg));
MggjjBkgTmp[1] = 0;
MggjjBkgTmp[2] = 0;
MggjjBkgTmp[3] = 0;
MggjjBkgTmp[4] = 0;
sprintf(fitName,"QCDFit");
break;
}
for(int i=0; i<totalNDOF; ++i){
fitresult[c] = MggjjBkgTmp[i]->fitTo(*data[c], Strategy(1),Minos(kFALSE), Range(minMassFit,maxMassFit),SumW2Error(kTRUE), Save(kTRUE));//strategy 1 or 2?
//w->import(*MggjjBkgTmp[i]);
minNLL[i] = fitresult[c]->minNll();
switch(modelNum){
case 0: NDOF[i] = i+1; break;
case 1: NDOF[i] = 2*(i+1); break;
case 2: NDOF[i] = 3*(i+1); break;
case 3: NDOF[i] = i+1; break;
case 4: NDOF[i] = 2*(i+1); break;
}
//************************************************//
// Plot Mggjj background fit results per categories
//************************************************//
// Plot Background Categories
//****************************//
TCanvas* ctmp = new TCanvas("ctmp","Mggjj Background Categories",0,0,500,500);
Int_t nBinsMass(80);
plotMggjjBkg[c] = mGGJJ->frame(nBinsMass);
data[c]->plotOn(plotMggjjBkg[c],LineColor(kWhite),MarkerColor(kWhite));
MggjjBkgTmp[i]->plotOn(plotMggjjBkg[c],LineColor(kBlue),Range("fit"),NormRange("fit"));
data[c]->plotOn(plotMggjjBkg[c]);
plotMggjjBkg[c]->SetTitle("");
plotMggjjBkg[c]->SetMinimum(0.0);
plotMggjjBkg[c]->SetMaximum(1.40*plotMggjjBkg[c]->GetMaximum());
plotMggjjBkg[c]->GetXaxis()->SetTitle("m_{#gamma#gammajj} (GeV)");
plotMggjjBkg[c]->Draw();
TLegend *legmc = new TLegend(0.62,0.75,0.92,0.9);
legmc->AddEntry(plotMggjjBkg[c]->getObject(2),"Weighted CS","LPE");
legmc->AddEntry(plotMggjjBkg[c]->getObject(1),"Bkg Model","L");
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
TLatex *lat = new TLatex(minMassFit+30.0,0.85*plotMggjjBkg[c]->GetMaximum(),"#splitline{#scale[1.0]{CMS Preliminary}}{#scale[0.8]{#sqrt{s} = 8 TeV}}");
lat->Draw();
TLatex *lat2 = new TLatex(minMassFit+30.0,0.7*plotMggjjBkg[c]->GetMaximum(),catdesc.at(c));
lat2->Draw();
//ctmp->SaveAs(TString::Format("databkgoversig_cat%d.pdf",c));
//ctmp->SaveAs(TString::Format("databkgoversig_cat%d.eps",c));
ctmp->SaveAs(TString::Format("plots/dataBkgMggjj_%sN%i_cat%d.png",fitName,i+(modelNum!=0),c));
//ctmp->SaveAs(TString::Format("databkgoversig_cat%d.C",c));
if(i>0){
float chi2 = 2*(minNLL[i-1]-minNLL[i]);
int chi2dof = NDOF[i]-NDOF[i-1];
chi2prob[i-1] = chi2<0 ? 1.0 : TMath::Prob(chi2,chi2dof);
if(chi2prob[i-1]>0.05 && (modelNum!=0 || i!=1) ) break;
}
if(data[c]->sumEntries()-1<=NDOF[i]) break;
bestN=i;
if(MggjjBkgTmp[i+1]==0) break;
}
FILE *results = fopen("resultsModelMggjj.txt","a");
fprintf(results,"### Mggjj spectrum, %s fit for cat%i. The best order is %i.\n",fitName,c,bestN+(modelNum!=0));//for Bernstein, N is the order of the polynomial fit.
for(int i=0; i<totalNDOF; ++i){
if(NDOF[i]==0) break;
fprintf(results,"N=%i NLL=%.3f NDOF=%i\n",i+(modelNum!=0),minNLL[i],NDOF[i]);
}
for(int i=1; i<totalNDOF; ++i){
if(NDOF[i]==0) break;
float chi2 = 2*(minNLL[i-1]-minNLL[i]);
int chi2dof = NDOF[i]-NDOF[i-1];
fprintf(results,"N=%i chi2=%.3f chi2dof=%i chi2prob=%.3f\n",i-1+(modelNum!=0),chi2,chi2dof,chi2prob[i-1]);
}
fprintf(results,"\n\n");
fclose(results);
MggjjBkgTmp[bestN]->fitTo(*data[c], Strategy(1),Minos(kFALSE), Range(minMassFit,maxMassFit),SumW2Error(kTRUE), Save(kTRUE));//strategy 1 or 2?
w->import(*MggjjBkgTmp[bestN]);
return MggjjBkgTmp[bestN];
}
void BkgModelBias(RooWorkspace* w,int c,RooAbsPdf* MggjjBkgTruth, FILE *fout){
std::vector<TString> catdesc;
catdesc.push_back("#scale[0.8]{Untagged}");
catdesc.push_back("#scale[0.8]{1-bjet tagged}");
catdesc.push_back("#scale[0.8]{2-bjet tagged}");
Float_t minMassFit(mRadMin),maxMassFit(mRadMax);
int sigMean[3]={500,750,1000};
float sigFWHM[3];//to be taken from signal model
if(c==1){ sigFWHM[0] = 44; sigFWHM[1]=55; sigFWHM[2]=61;}
else if(c==2){ sigFWHM[0] = 31; sigFWHM[1]=36; sigFWHM[2]=46;}
for(int i=0; i<sizeof(sigFWHM)/sizeof(float); ++i) sigFWHM[i]/=2.0;
TLatex *text = new TLatex();
text->SetNDC();
text->SetTextSize(0.04);
RooDataSet* data = (RooDataSet*) w->data(TString::Format("Data_cat%d",c));
RooRealVar* mGGJJ = w->var("mRad");
mGGJJ->setUnit("GeV");
mGGJJ->setRange(minMassFit,maxMassFit);
RooRealVar *p0 = new RooRealVar("p0","",-0.005,-1000,1000);
RooRealVar *p1 = new RooRealVar("p1","",250,-1000,1000);
RooRealVar *p2 = new RooRealVar("p2","",40,-100000,100000);
RooRealVar *p3 = new RooRealVar("p3","",-1.0,-100.0,0.0);
RooRealVar *p4 = new RooRealVar("p4","",1.00,-100.0,0.0);
const int totalNDOF=5;
RooAbsPdf* MggjjBkgTmp[totalNDOF] = {0};
MggjjBkgTmp[0] = new GaussExp("GaussExp","GaussExp",*mGGJJ,*p1,*p2,*p4);
MggjjBkgTmp[1] = new RooGenericPdf("Pow1","pow(@0,@1)",RooArgList(*mGGJJ,*p0));
//MggjjBkgTmp[1] = new RooGenericPdf("Pow1","pow(@0,@1)",RooArgList(*mGGJJ,*p0));
MggjjBkgTmp[2] = new RooGenericPdf("Func1","pow(@0+@1,@2)",RooArgList(*mGGJJ,*p0,*p4));
//MggjjBkgTmp[2] = new RooGenericPdf("Func1","exp(@0/(@1-@0*@2))",RooArgList(*mGGJJ,*p0,*p4));
MggjjBkgTmp[3] = new RooGenericPdf("Func2","1.0/pow(@0*@0+@0*@1+@2,@3)",RooArgList(*mGGJJ,*p1,*p2,*p4));
MggjjBkgTmp[4] = new RooGenericPdf("Func3","1.0/(pow(@0,@1)+@2)",RooArgList(*mGGJJ,*p1,*p4));
//MggjjBkgTmp[4] = new RooGenericPdf("Func3","pow(1-@0/8000.0,@1)/pow(@0/8000.0,@2+@3*log(@0/8000.0))",RooArgList(*mGGJJ,*p2,*p1,*p4));
if(MggjjBkgTruth->GetName()[0]=='E'){
fprintf(fout,"Mggjj spectrum, bias results for cat%d\n",c);
fprintf(fout,"Model\t %s %s %s %s %s\n",
// MggjjBkgTmp[0]->GetName(),MggjjBkgTmp[1]->GetName(),MggjjBkgTmp[2]->GetName(),MggjjBkgTmp[3]->GetName(),MggjjBkgTmp[4]->GetName());
"Candidate@500","Candidate@700","Candidate@1000","N/A","N/A");
}
const int Npse = 1000;
float results[totalNDOF] = {-9999};
//for(int k=0; k<totalNDOF; ++k){
for(int k=3; k<4; ++k){
if(k==0)
p0->setVal(-0.005);
else if(k==1)
p0->setVal(-2);
else if(k==2){
p0->setVal(-50);
p0->setRange(-1000,1000);
p4->setVal(0.01);
p4->setRange(-1000,1000);
}
else if(k==3){
p1->setVal(0);
p2->setVal(100000);
p4->setVal(3.0);
p1->setRange(000,000);
p2->setRange(-10000,100000000);
p4->setRange(-10,10);
}
else if(k==4){
p1->setVal(4);
p4->setVal(1000.0);
p1->setRange(-10,10);
p4->setRange(0,10000000);
}
RooRealVar *nbkg = new RooRealVar("nbkg","",1,0,100000);
RooExtendPdf *MggjjBkgFit = new RooExtendPdf(TString::Format("MggjjBkgFit_cat%d",c),"",*MggjjBkgTmp[k],*nbkg);
RooMCStudy * mcs = new RooMCStudy(*MggjjBkgTruth, *mGGJJ, FitModel(*MggjjBkgFit),Silence(), Extended(kTRUE), Binned(kFALSE),
FitOptions(Range(minMassFit,maxMassFit),Extended(kTRUE),PrintEvalErrors(0)));
RooChi2MCSModule chi2mod;
mcs->addModule(chi2mod);
if(c==2) mcs->generateAndFit(Npse*2,data->sumEntries(),kTRUE);
else mcs->generateAndFit(Npse,data->sumEntries(),kTRUE);
for(int iMean=0; iMean<sizeof(sigMean)/sizeof(int); ++iMean){
mGGJJ->setRange("sigRegion",sigMean[iMean]-sigFWHM[iMean],sigMean[iMean]+sigFWHM[iMean]);
std::vector<double> pulls;
//float genFraction = MggjjBkgTruth->createIntegral(*mGGJJ,*mGGJJ,"sigRegion")->getVal();
for(int i=0; i<Npse; ++i){
RooRealVar *q0 = new RooRealVar("q0","",mcs->fitParams(i)->getRealValue("p0"));
RooRealVar *q1 = new RooRealVar("q1","",mcs->fitParams(i)->getRealValue("p1"));
RooRealVar *q2 = new RooRealVar("q2","",mcs->fitParams(i)->getRealValue("p2"));
RooRealVar *q3 = new RooRealVar("q3","",mcs->fitParams(i)->getRealValue("p3"));
RooRealVar *q4 = new RooRealVar("q4","",mcs->fitParams(i)->getRealValue("p4"));
RooAbsPdf *fitFunc;
switch(k){
case 0: fitFunc = new GaussExp("GaussExpFit","GaussExp",*mGGJJ,*q1,*q2,*q4); break;
//case 0: fitFunc = new RooGenericPdf("Exp1","exp(@0*@1)",RooArgList(*mGGJJ,*q0)); break;
case 1: fitFunc = new RooGenericPdf("Pow1","pow(@0,@1)",RooArgList(*mGGJJ,*q0)); break;
//case 1: fitFunc = new RooGenericPdf("Exp1","exp(@0*@1)",RooArgList(*mGGJJ,*q0)); break;
case 2: fitFunc = new RooGenericPdf("Func1","pow(@0+@1,@2)",RooArgList(*mGGJJ,*q0,*q4)); break;
case 3: fitFunc = new RooGenericPdf("Func2","1.0/pow(@0*@0+@0*@1+@2,@3)",RooArgList(*mGGJJ,*q1,*q2,*q4)); break;
case 4: fitFunc = new RooGenericPdf("Func3","1.0/(pow(@0,@1)+@2)",RooArgList(*mGGJJ,*q1,*q4));break;
}
float fitFraction = fitFunc->createIntegral(*mGGJJ,*mGGJJ,"sigRegion")->getVal();
//float genN = mcs->fitParams(i)->getRealValue("ngen");
const RooAbsData* genDataset = mcs->genData(i);
char fitRangeString[80]; sprintf(fitRangeString,"mRad>%f && mRad<%f",sigMean[iMean]-sigFWHM[iMean],sigMean[iMean]+sigFWHM[iMean]);
float genN = genDataset->sumEntries(fitRangeString);
float fitN = mcs->fitParams(i)->getRealValue("nbkg");
float a=0.318/2.0, nl=fitN*fitFraction-0.5*TMath::ChisquareQuantile(a,2*fitN*fitFraction), nh=0.5*TMath::ChisquareQuantile(1-a,2*(fitN*fitFraction+1))-fitN*fitFraction;
float fitNerr = 0.5*(nl+nh);
if(fitNerr*fitFraction>0)// && mcs->fitParams(i)->getRealValue("chi2")/mcs->fitParams(i)->getRealValue("ndof")<10)
pulls.push_back((genN-fitN*fitFraction)/(fitNerr));
}
for(int i=0; i<pulls.size(); ++i){
for(int j=i; j<pulls.size(); ++j){
if(pulls[i]>pulls[j]){
float tmp=pulls[i];
pulls[i]=pulls[j];
pulls[j]=tmp;
}}}
if(pulls.size()==0)
results[iMean] = -9999;
else if(pulls.size()%2==0)
results[iMean] = 0.5*(pulls[pulls.size()/2]+pulls[pulls.size()/2-1]);
else
results[iMean] = pulls[pulls.size()/2];
if(pulls.size()==0){ pulls.push_back(-9999); pulls.push_back(-9998);}
//TH1F *h1 = new TH1F("h1","",50,pulls[0],pulls[pulls.size()-1]);
TH1F *h1 = new TH1F("h1","",25,-3,3);
h1->GetXaxis()->SetTitle("pull(N_{bgd}^{SR})");
for(int i=0; i<pulls.size(); i++) h1->Fill(pulls[i]);
TCanvas *c0 = new TCanvas("c0","c0",700,500);
h1->SetMaximum(h1->GetMaximum()*1.40);
h1->Draw();
TFitResultPtr pullFit;
if(h1->Integral()>4){
pullFit = h1->Fit("gaus","s");
TLatex *lat1 = new TLatex(-2.6,0.85*h1->GetMaximum(),"#splitline{#scale[1.0]{CMS Preliminary}}{#scale[0.8]{#sqrt{s} = 8 TeV}}");
lat1->Draw();
TLatex *lat12 = new TLatex(0.8,0.60*h1->GetMaximum(),TString::Format("#splitline{#scale[1.0]{#mu = %.2f #pm %.2f}}{#scale[1.0]{#sigma = %.2f #pm %.2f}}",pullFit->GetParams()[1],pullFit->GetErrors()[1],pullFit->GetParams()[2],pullFit->GetErrors()[2]));
lat12->SetTextColor(kRed);
lat12->Draw();
TLatex *lat13 = new TLatex();
lat13->DrawLatex(0.8,0.91*h1->GetMaximum(),TString::Format("Num PSE: %d",pulls.size()) );
lat13->DrawLatex(0.8,0.85*h1->GetMaximum(),TString::Format("Gen function: %s",MggjjBkgTruth->GetName()) );
lat13->DrawLatex(0.8,0.79*h1->GetMaximum(),TString::Format("Fit function: %s",MggjjBkgTmp[k]->GetName()) );
lat13->DrawLatex(0.8,0.73*h1->GetMaximum(),TString::Format("Median = %.2f ",results[iMean]) );
}
else{
TLatex *lat13 = new TLatex();
lat13->DrawLatex(0.0,0.5,"Not enough entries." );
lat13->DrawLatex(0.0,0.4,TString::Format("Median = %.2f ",results[iMean]) );
}
c0->SaveAs(TString::Format("plots/pullsMggjj_gen%s_fit%s_cat%d_M%d.png",MggjjBkgTruth->GetName(),MggjjBkgTmp[k]->GetName(),c,sigMean[iMean]));
}
TCanvas *c1 = new TCanvas("c1","c1",1200,1200);
c1->Divide(3,3);
for(int i=1;i<=9; ++i){
c1->cd(i);
RooPlot *frame = mGGJJ->frame();
if(i==1){
data->plotOn(frame);
MggjjBkgTruth->plotOn(frame,LineColor(kBlue),Range("fit"),NormRange("fit"));
frame->SetTitle("");
frame->SetMinimum(0.0);
frame->SetMaximum(1.40*frame->GetMaximum());
frame->GetXaxis()->SetTitle("m_{#gamma#gamma jj} (GeV)");
frame->Draw();
TLegend *legmc = new TLegend(0.62,0.75,0.92,0.9);
legmc->AddEntry(frame->getObject(0),"Weighted CS","LPE");
legmc->AddEntry(frame->getObject(1),"Bkg Model","L");
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
TLatex *lat = new TLatex(minMassFit+30.0,0.85*frame->GetMaximum(),"#splitline{#scale[1.0]{CMS Preliminary}}{#scale[0.8]{#sqrt{s} = 8 TeV}}");
lat->Draw();
TLatex *lat2 = new TLatex(minMassFit+30.0,0.7*frame->GetMaximum(),catdesc.at(c));
lat2->Draw();
continue;
}
mcs->genData(i)->plotOn(frame);
RooRealVar *q0 = new RooRealVar("q0","",mcs->fitParams(i)->getRealValue("p0"));
RooRealVar *q1 = new RooRealVar("q1","",mcs->fitParams(i)->getRealValue("p1"));
RooRealVar *q2 = new RooRealVar("q2","",mcs->fitParams(i)->getRealValue("p2"));
RooRealVar *q3 = new RooRealVar("q3","",mcs->fitParams(i)->getRealValue("p3"));
RooRealVar *q4 = new RooRealVar("q4","",mcs->fitParams(i)->getRealValue("p4"));//cout<<"\n\n\n\n\n!!!!!!\n\np1="<<q1->getVal()<<" p2="<<q2->getVal()<<" p4="<<q4->getVal()<<endl;//@@@
RooAbsPdf *fitFunc;
switch(k){
case 0: fitFunc = new GaussExp("GaussExpFit","GaussExp",*mGGJJ,*q1,*q2,*q4); break;
//case 0: fitFunc = new RooGenericPdf("Exp1","exp(@0*@1)",RooArgList(*mGGJJ,*q0)); break;
case 1: fitFunc = new RooGenericPdf("Pow1","pow(@0,@1)",RooArgList(*mGGJJ,*q0)); break;
case 2: fitFunc = new RooGenericPdf("Func1","pow(@0+@1,@2)",RooArgList(*mGGJJ,*q0,*q4)); break;
case 3: fitFunc = new RooGenericPdf("Func2","1.0/pow(@0*@0+@0*@1+@2,@3)",RooArgList(*mGGJJ,*q1,*q2,*q4)); break;
case 4: fitFunc = new RooGenericPdf("Func3","1.0/(pow(@0,@1)+@2)",RooArgList(*mGGJJ,*q1,*q4));break;
}
fitFunc->plotOn(frame,LineColor(kGreen),Range("fit"),NormRange("fit"));
frame->SetTitle("");
frame->SetMinimum(0.0);
frame->SetMaximum(1.40*frame->GetMaximum());
frame->GetXaxis()->SetTitle("m_{#gamma#gamma jj} (GeV)");
frame->Draw();
TLegend *legmc = new TLegend(0.62,0.75,0.92,0.9);
legmc->AddEntry(frame->getObject(0),TString::Format("Gen PSE #%i",i-1),"LPE");
legmc->AddEntry(frame->getObject(1),"Bkg Model","L");
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
TLatex *lat = new TLatex(minMassFit+30.0,0.85*frame->GetMaximum(),"#splitline{#scale[1.0]{CMS Preliminary}}{#scale[0.8]{#sqrt{s} = 8 TeV}}");
lat->Draw();
TLatex *lat2 = new TLatex(minMassFit+30.0,0.7*frame->GetMaximum(),catdesc.at(c));
lat2->Draw();
TLatex *lat3 = new TLatex();
lat3->SetNDC();
lat3->DrawLatex(0.62,0.68,TString::Format("#chi^{2}/N = %.2f",mcs->fitParams(i)->getRealValue("chi2")/mcs->fitParams(i)->getRealValue("ndof")));
lat3->DrawLatex(0.62,0.62,TString::Format("p(#chi^{2},N) = %.2f",mcs->fitParams(i)->getRealValue("prob")));
}
c1->SaveAs(TString::Format("plots/toymcMggjj_gen%s_fit%s_cat%d.png",MggjjBkgTruth->GetName(),MggjjBkgTmp[k]->GetName(),c));
delete mcs;
}
fprintf(fout,"%s\t%8.4f %8.4f %8.4f %8.4f %8.4f\n",MggjjBkgTruth->GetName(),results[0],results[1],results[2],results[3],results[4]);
return;
}
void SetConstantParams(const RooArgSet* params) {
TIterator* iter(params->createIterator());
for (TObject *a = iter->Next(); a != 0; a = iter->Next()) {
RooRealVar *rrv = dynamic_cast<RooRealVar *>(a);
if (rrv) { rrv->setConstant(true); std::cout << " " << rrv->GetName(); }
}
}
Double_t effSigma(TH1 *hist) {
TAxis *xaxis = hist->GetXaxis();
Int_t nb = xaxis->GetNbins();
if(nb < 10) {
std::cout << "effsigma: Not a valid histo. nbins = " << nb << std::endl;
return 0.;
}
Double_t bwid = xaxis->GetBinWidth(1);
if(bwid == 0) {
std::cout << "effsigma: Not a valid histo. bwid = " << bwid << std::endl;
return 0.;
}
Double_t xmax = xaxis->GetXmax();
Double_t xmin = xaxis->GetXmin();
Double_t ave = hist->GetMean();
Double_t rms = hist->GetRMS();
Double_t total=0.;
for(Int_t i=0; i<nb+2; i++) {
total+=hist->GetBinContent(i);
}
if(total < 100.) {
std::cout << "effsigma: Too few entries " << total << std::endl;
return 0.;
}
Int_t ierr=0;
Int_t ismin=999;
Double_t rlim=0.683*total;
Int_t nrms=rms/(bwid); // Set scan size to +/- rms
if(nrms > nb/10) nrms=nb/10; // Could be tuned...
Double_t widmin=9999999.;
for(Int_t iscan=-nrms;iscan<nrms+1;iscan++) { // Scan window centre
Int_t ibm=(ave-xmin)/bwid+1+iscan;
Double_t x=(ibm-0.5)*bwid+xmin;
Double_t xj=x;
Double_t xk=x;
Int_t jbm=ibm;
Int_t kbm=ibm;
Double_t bin=hist->GetBinContent(ibm);
total=bin;
for(Int_t j=1;j<nb;j++){
if(jbm < nb) {
jbm++;
xj+=bwid;
bin=hist->GetBinContent(jbm);
total+=bin;
if(total > rlim) break;
}
else ierr=1;
if(kbm > 0) {
kbm--;
xk-=bwid;
bin=hist->GetBinContent(kbm);
total+=bin;
if(total > rlim) break;
}
else ierr=1;
}
Double_t dxf=(total-rlim)*bwid/bin;
Double_t wid=(xj-xk+bwid-dxf)*0.5;
if(wid < widmin) {
widmin=wid;
ismin=iscan;
}
}
if(ismin == nrms || ismin == -nrms) ierr=3;
if(ierr != 0) std::cout << "effsigma: Error of type " << ierr << std::endl;
return widmin;
}