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Copy pathHighMass-HggFitter_mgg_makePlots.cc
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HighMass-HggFitter_mgg_makePlots.cc
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/** \macro H2GGFitter.cc
*
* The analysis root trees produced in a simple format
*
* TFile file(filename,"RECREATE", "X->jj input tree for unbinned maximum-likelihood fit");
* TTree* outTree = new TTree("XTojj","X->jj input tree for unbinned maximum-likelihood fit");
* Float_t mass;
* Int_t CAT3;
* Float_t weight;
*
* outTree->Branch("mass",&mass,"mass/F");
* outTree->Branch("weight",&weight,"weight/F");
* outTree->Branch("CAT4",&CAT4,"CAT4/I");
* {
* .............
* outTree->Fill();
* }
*
* file.Write();
* file.Close();
* delete outTree;
*
* are used as input files. They have to be produced for
* data and Monte Carlo signal and background data sets
* after all analysis selections to be applied. *
*/
// Loading: .L HH2ggbbFitter.cc
// Running: runfits("hgg120-shapes-combined-Unbinned.root")
//
using namespace RooFit;
using namespace RooStats ;
static const Int_t NCAT = 4; // chiara
std::string filePOSTfix="";
double signalScaler=1.00;
void AddSigData(RooWorkspace*, Float_t);
void AddBkgData(RooWorkspace*, Float_t);
void MakeRooKeysPDFMCBkg(RooWorkspace*, Float_t);
void SigModelFitGauss(RooWorkspace*, Float_t);
void SigModelFitCBC(RooWorkspace*, Float_t);
RooFitResult* BkgModelFitBernstein(RooWorkspace*, Bool_t, Float_t, bool);
RooFitResult* BkgModelFitExpo(RooWorkspace*, Bool_t, Float_t, bool);
RooFitResult* BkgModelFitDiJetFunc(RooWorkspace*, Bool_t, Float_t, bool);
RooFitResult* BkgModelFitExpolFunc(RooWorkspace*, Bool_t, Float_t, bool);
void MakePlots(RooWorkspace*, Float_t, RooFitResult*, bool);
void MakeSigWS(RooWorkspace* w, const char* filename);
void MakeBkgWS(RooWorkspace* w, const char* filename);
void SetConstantParams(const RooArgSet* params);
void MakeParameterTrendvsMassGauss();
void MakeParameterTrendvsMassCBC();
void MakePlotMassDataMC(RooWorkspace*, Float_t);
void MakePlotNVTXDataMC(RooWorkspace*, Float_t);
TPaveText* get_labelCMS( int legendQuadrant = 0 , std::string year="2012", bool sim=false) {
if( legendQuadrant!=0 && legendQuadrant!=1 && legendQuadrant!=2 && legendQuadrant!=3 ) {
std::cout << "WARNING! Legend quadrant '" << legendQuadrant << "' not yet implemented for CMS label. Using 2." << std::endl;
legendQuadrant = 2;
}
float x1, y1, x2, y2;
if( legendQuadrant==1 ) {
x1 = 0.63;
y1 = 0.83;
x2 = 0.8;
y2 = 0.87;
} else if( legendQuadrant==2 ) {
x1 = 0.25;
y1 = 0.83;
x2 = 0.42;
y2 = 0.87;
} else if( legendQuadrant==3 ) {
x1 = 0.25;
y1 = 0.2;
x2 = 0.42;
y2 = 0.24;
} else if( legendQuadrant==0 ) {
x1 = 0.175;
y1 = 0.953;
x2 = 0.6;
y2 = 0.975;
}
TPaveText* cmslabel = new TPaveText( x1, y1, x2, y2, "brNDC" );
cmslabel->SetFillColor(kWhite);
cmslabel->SetTextSize(0.038);
if( legendQuadrant==0 ) cmslabel->SetTextAlign(11);
cmslabel->SetTextSize(0.038);
cmslabel->SetTextFont(42);
std::string leftText;
if (sim) leftText = "CMS Simulation"; //cwr ->remove 2011
else {
leftText = "CMS Preliminary, 19.5 fb^{-1}";
}
cmslabel->AddText(leftText.c_str());
return cmslabel;
}
TPaveText* get_labelSqrt( int legendQuadrant ) {
if( legendQuadrant!=0 && legendQuadrant!=1 && legendQuadrant!=2 && legendQuadrant!=3 ) {
std::cout << "WARNING! Legend quadrant '" << legendQuadrant << "' not yet implemented for Sqrt label. Using 2." << std::endl;
legendQuadrant = 2;
}
float x1, y1, x2, y2;
if( legendQuadrant==1 ) {
x1 = 0.63;
y1 = 0.78;
x2 = 0.8;
y2 = 0.82;
} else if( legendQuadrant==2 ) {
x1 = 0.25;
y1 = 0.78;
x2 = 0.42;
y2 = 0.82;
} else if( legendQuadrant==3 ) {
x1 = 0.25;
y1 = 0.16;
x2 = 0.42;
y2 = 0.2;
} else if( legendQuadrant==0 ) {
x1 = 0.65;
y1 = 0.953;
x2 = 0.87;
y2 = 0.975;
}
TPaveText* label_sqrt = new TPaveText(x1,y1,x2,y2, "brNDC");
label_sqrt->SetFillColor(kWhite);
label_sqrt->SetTextSize(0.038);
label_sqrt->SetTextFont(42);
label_sqrt->SetTextAlign(31); // align right
label_sqrt->AddText("#sqrt{s} = 8 TeV");
return label_sqrt;
}
RooArgSet* defineVariables() {
// define variables of the input ntuple //livia
RooRealVar* PhotonsMass = new RooRealVar("PhotonsMass", "M(gg)",100, 2000,"GeV");
RooRealVar* ph1_eta = new RooRealVar("ph1_eta", "eta(g1)",-10,10,"");
RooRealVar* ph2_eta = new RooRealVar("ph2_eta", "eta(g2)",-10,10,"");
RooRealVar* ph1_r9 = new RooRealVar("ph1_r9", "R9(g1)",-10,10,"");
RooRealVar* ph2_r9 = new RooRealVar("ph2_r9", "R9(g2)",-10,10,"");
RooRealVar* evweight = new RooRealVar("evweight","Reweightings",0,10,"");
RooRealVar* nvtx = new RooRealVar("nvtx", "nvtx", 0, 50, "");
// RooRealVar* btagCategory = new RooRealVar("btagCategory","event category",0.9,2.1,"") ;
RooArgSet* ntplVars = new RooArgSet(*PhotonsMass, *ph1_eta, *ph2_eta, *ph1_r9, *ph2_r9, *evweight, *nvtx);
return ntplVars;
}
void runfits(const Float_t mass=150, Bool_t dobands = false) {
//******************************************************************//
// Running mode corresponds to the following cases
// - full run set:
// - create signal and background data sets
// - make and fit signal and background models
// - write signal and background workspaces in root files
// - write data card
//***********************************ß********************************//
TString fileBaseName(TString::Format("HighMass-hgg.m%.1f", mass));
TString fileBkgName(TString::Format("HighMass-hgg.inputbkg_8TeV", mass));
TString card_name(TString::Format("HighMass-hgg_m%.0f_models_Bkg_8TeV_test.rs", mass));
HLFactory hlf("HLFactory", card_name, false);
RooWorkspace* w = hlf.GetWs();
Double_t MMIN = 100.; //130 //livia //100 //180 //270
Double_t MMAX = 800.; //450 //livia //200 // 300 //2000
w->var("PhotonsMass")->setMin(MMIN);
w->var("PhotonsMass")->setMax(MMAX);
cout << "Now plot Data vs MC bkg" << endl;
MakePlotMassDataMC(w, mass);
//MakePlotNVTXDataMC(w, mass);
//PlotVtxRecoEff();
// Make plots for data and fit results
cout << endl; cout << "Preparing final plots" << endl;
//MakePlots(w, mass, fitresults_bern, blind);
//PlotSigShape(w, 0);
//PlotSigShape(w, 1);
//PlotSigShape(w, 2);
//PlotSigShape(w, 3);
return;
}
void MakePlots(RooWorkspace* w, Float_t mass, RooFitResult* fitresults, bool blind) {
Int_t ncat = NCAT;
cout << endl; cout << "Retreive everything:" << endl;
w->Print();
// retrieve data sets from the workspace
RooDataSet* dataAll = (RooDataSet*) w->data("Data");
RooDataSet* signalAll = (RooDataSet*) w->data("SigWeight");
// maximum 9 cat...
RooDataSet* data[9];
RooDataSet* signal[9];
RooAbsPdf* PhotonsMassGaussSig[9];
RooAbsPdf* PhotonsMassGaussSig_bis[9];
RooAbsPdf* PhotonsMassSig[9];
RooExtendPdf* PhotonsMassBkg[9];
for (int c=0; c<ncat; ++c) {
data[c] = (RooDataSet*) w->data(TString::Format("Data_cat%d",c));
signal[c] = (RooDataSet*) w->data(TString::Format("SigWeight_cat%d",c));
PhotonsMassGaussSig[c] = (RooAbsPdf*) w->pdf(TString::Format("PhotonsMassGaussSig_cat%d",c));
PhotonsMassGaussSig_bis[c] = (RooAbsPdf*) w->pdf(TString::Format("PhotonsMassGaussSig_cat%d_bis",c));
PhotonsMassSig[c] = (RooAbsPdf*) w->pdf("PhotonsMassSig"+TString::Format("_cat%d",c));
PhotonsMassBkg[c] = (RooExtendPdf*) w->pdf(TString::Format("PhotonsMassBkg_cat%d",c));
}
// retrieve mass observable from the workspace
RooRealVar* PhotonsMass = w->var("PhotonsMass");
PhotonsMass->setUnit("GeV");
// retrieve pdfs after the fits
RooAbsPdf* PhotonsMassGaussSigAll = w->pdf("PhotonsMassGaussSig");
RooAbsPdf* PhotonsMassGaussSigAll_bis = w->pdf("PhotonsMassGaussSig_bis");
RooAbsPdf* PhotonsMassSigAll = w->pdf("PhotonsMassSig");
RooAbsPdf* PhotonsMassBkgAll = w->pdf("PhotonsMassBkgAll");
Float_t minMassFit, maxMassFit;
if(mass<200){ //m150
minMassFit = 100;
maxMassFit = 200;
} else if(mass>=200 && mass <500){//m200 and m250
minMassFit = 180;
maxMassFit = 500;
}else{//m300 m400
minMassFit = 280;
maxMassFit = 500;
}
Float_t MASS(mass);
int iMass = abs(mass);
Int_t nBinsMass(0.2*mass); // chiara
/* // ****************************SIG ALL
cout << endl; cout << "Progress plotting: signal" << endl;
RooPlot* plotPhotonsMassAll = PhotonsMass->frame(Range(minMassFit,maxMassFit),Bins(nBinsMass));
signalAll->plotOn(plotPhotonsMassAll);
gStyle->SetOptTitle(0);
PhotonsMassSigAll->plotOn(plotPhotonsMassAll);
PhotonsMassSigAll->plotOn(plotPhotonsMassAll,Components("PhotonsMassGaussSig"),LineStyle(kDashed),LineColor(kGreen));
PhotonsMassSigAll->plotOn(plotPhotonsMassAll,Components("PhotonsMassGaussSig_bis"),LineStyle(kDashed),LineColor(kRed));
//PhotonsMassSigAll->paramOn(plotPhotonsMassAll, ShowConstants(true), Layout(0.65,0.75,0.85), Format("NEU",AutoPrecision(2)));
//plotPhotonsMassAll->getAttText()->SetTextSize(0.03);
TCanvas* c1 = new TCanvas("c1","PhotonsMass",0,0,500,500);
c1->cd(1);
plotPhotonsMassAll->Draw();
c1->SaveAs("plots/sigmodel_"+TString::Format("%d.png", iMass));
c1->SaveAs("plots/sigmodel_"+TString::Format("%d.root", iMass));
*/
// ****************************SIG CAT
cout << endl; cout << "Progress plotting: signal per categories" << endl;
TLatex *text = new TLatex();
text->SetNDC();
text->SetTextSize(0.04);
RooPlot* plotPhotonsMass[9];
for (int c=0; c<ncat; ++c) {
plotPhotonsMass[c] = PhotonsMass->frame(Range(mass-30,mass+30),Bins(nBinsMass));
signal[c]->plotOn(plotPhotonsMass[c],LineColor(kWhite),MarkerColor(kWhite));
PhotonsMassSig[c] ->plotOn(plotPhotonsMass[c]);
PhotonsMassSig[c] ->plotOn(plotPhotonsMass[c],Components("PhotonsMassGaussSig"+TString::Format("_cat%d",c)),LineStyle(kDashed),LineColor(kGreen));
PhotonsMassSig[c] ->plotOn(plotPhotonsMass[c],Components("PhotonsMassGaussSig"+TString::Format("_cat%d_bis",c)),LineStyle(kDashed),LineColor(kRed));
//PhotonsMassSig[c] ->paramOn(plotPhotonsMass[c], ShowConstants(true), Layout(0.65,0.75,0.85), Format("NEU",AutoPrecision(2)));
signal[c] ->plotOn(plotPhotonsMass[c]);
// TCanvas* dummy = new TCanvas("dummy", "dummy",0, 0, 400, 400);
// TH1F *hist = new TH1F("hist", "hist", 400, minMassFit, maxMassFit);
plotPhotonsMass[c]->SetTitle("");
plotPhotonsMass[c]->SetMinimum(0.0);
plotPhotonsMass[c]->SetMaximum(1.40*plotPhotonsMass[c]->GetMaximum());
plotPhotonsMass[c]->GetXaxis()->SetTitle("m_{#gamma#gamma} (GeV)");
TCanvas* ctmp = new TCanvas("ctmp","PhotonsMass Background Categories",0,0,500,500);
plotPhotonsMass[c]->Draw();
plotPhotonsMass[c]->SetAxisRange(0.000001,plotPhotonsMass[c]->GetMaximum()*1.2,"Y");
plotPhotonsMass[c]->Draw("SAME");
TLegend *legmc = new TLegend(0.62,0.75,0.92,0.9);
legmc->AddEntry(plotPhotonsMass[c]->getObject(5),"Simulation","LPE");
legmc->AddEntry(plotPhotonsMass[c]->getObject(1),"Parametric Model","L");
legmc->AddEntry(plotPhotonsMass[c]->getObject(3),"Gaussian 2 component","L");
legmc->AddEntry(plotPhotonsMass[c]->getObject(2),"Gaussian 1 component","L");
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
TLatex *lat = new TLatex(mass-20.,0.91*plotPhotonsMass[c]->GetMaximum(),"#scale[1.0]{CMS Preliminary}");
lat->Draw();
ctmp->SaveAs("plots/sigmodel_"+TString::Format("%d_cat%d.root", iMass, c));
ctmp->SaveAs("plots/sigmodel_"+TString::Format("%d_cat%d.png", iMass, c));
ctmp->SetLogy();
ctmp->SaveAs("plots/sigmodel_"+TString::Format("%d_cat%d_LOG.png", iMass, c));
}
// ****************************BKG CAT LOG
cout << endl; cout << "Progress plotting: background" << endl;
TCanvas* c4 = new TCanvas("c4","PhotonsMass Background Categories",0,0,400,400);
RooPlot* plotPhotonsMassBkg[9];
for (int c=0; c<ncat; ++c) {
plotPhotonsMassBkg[c] = PhotonsMass->frame(Range(minMassFit, maxMassFit),nBinsMass);
data[c]->plotOn(plotPhotonsMassBkg[c],RooFit::Invisible());
PhotonsMassBkg[c]->plotOn(plotPhotonsMassBkg[c],LineColor(kBlue),Range("fitrange"),NormRange("fitrange"));
if( blind ) {
PhotonsMass->setRange("unblind_up",mass+10.,maxMassFit);
PhotonsMass->setRange("unblind_down",minMassFit,mass-10.);
data[c]->plotOn(plotPhotonsMassBkg[c], RooFit::CutRange("unblind_up"));
data[c]->plotOn(plotPhotonsMassBkg[c], RooFit::CutRange("unblind_down"));
} else {
data[c]->plotOn(plotPhotonsMassBkg[c], Range("fitrange"));
}
plotPhotonsMassBkg[c]->Draw();
gPad->SetLogy(1);
plotPhotonsMassBkg[c]->SetAxisRange(1.5,plotPhotonsMassBkg[c]->GetMaximum()*1.5,"Y");
c4->SaveAs("plots/backgrounds_log_"+TString::Format("cat%d.png", c));
c4->SaveAs("plots/backgrounds_log_"+TString::Format("cat%d.root", c));
}
// ****************************BKG LIN
TCanvas* c5 = new TCanvas("c5","PhotonsMass Background Categories",0,0,400,400);
RooPlot* plotPhotonsMassBkg[9];
for (int c=0; c<ncat; ++c) {
plotPhotonsMassBkg[c] = PhotonsMass->frame(Range(minMassFit, maxMassFit),nBinsMass);
data[c]->plotOn(plotPhotonsMassBkg[c],RooFit::Invisible());
PhotonsMassBkg[c]->plotOn(plotPhotonsMassBkg[c],LineColor(kBlue),Range("fitrange"),NormRange("fitrange"));
if( blind ) {
PhotonsMass->setRange("unblind_up",mass+10.,maxMassFit);
PhotonsMass->setRange("unblind_down",minMassFit,mass-10.);
data[c]->plotOn(plotPhotonsMassBkg[c], RooFit::CutRange("unblind_up"));
data[c]->plotOn(plotPhotonsMassBkg[c], RooFit::CutRange("unblind_down"));
} else {
data[c]->plotOn(plotPhotonsMassBkg[c], Range("fitrange"));
}
plotPhotonsMassBkg[c]->SetAxisRange(0.001,plotPhotonsMassBkg[c]->GetMaximum()*1.5,"Y");
plotPhotonsMassBkg[c]->Draw();
c5->SaveAs("plots/backgrounds_"+TString::Format("cat%d.png", c));
c5->SaveAs("plots/backgrounds_"+TString::Format("cat%d.root", c));
}
}
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;
}
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;
}
void R2JJFitter(double mass, std::string postfix="")
{
filePOSTfix=postfix;
if(postfix!="")
{
// for optimization studies
MMIN=1000;
if(mass==1000)
signalScaler=0.034246;
if((mass>1000)&&(mass<500))
signalScaler=0.02469;
if(mass==2000)
signalScaler=2.0;
};
runfits(mass, 1);
if(postfix!="")
{
// for optimization studies
MMIN=1000;
if(mass==1000)
signalScaler=0.033500;
if((mass>1000)&&(mass<2000))
signalScaler=0.02016;
if(mass==2000)
signalScaler=2.22222;
};
runfits(mass, 0);
runfits(mass, 2);
}
void MakeParameterTrendvsMassGauss(){
TString wsDir = "workspaces/"+filePOSTfix;
Int_t ncat = NCAT;
Float_t masses[5];
masses[0] = 150.0;
masses[1] = 200.0;
masses[2] = 250.0;
masses[3] = 300.0;
masses[4] = 400.0.;
Float_t masses_err[5];
masses_err[0] = 0.;
masses_err[1] = 0.;
masses_err[2] = 0.;
masses_err[3] = 0.;
masses_err[4] = 0.;
TFile* file[5];
for(imass = 0; imass<5;imass++) file[imass]= new TFile(wsDir+TString::Format("HighMass-hgg.m%.1f_8TeV.inputsig.root",masses[imass]));
RooWorkspace* ws[5];
for(imass = 0; imass<5;imass++) ws[imass] = (RooWorkspace*) file[imass]->Get("w_all");
Float_t m0[5];
Float_t m1[5];
Float_t sigma0[5];
Float_t sigma1[5];
Float_t frac[5];
Float_t sig[5];
Float_t m0_err[5];
Float_t m1_err[5];
Float_t sigma0_err[5];
Float_t sigma1_err[5];
Float_t frac_err[5];
Float_t sig_err[5];
TCanvas* c1 = new TCanvas("c1", "c1", 1);
c1->cd();
TPaveText* label_cat[5];
TPaveText* label_cms = get_labelCMS(0, "2012", true);
TPaveText* label_sqrt = get_labelSqrt(0);
for (int c=0; c<ncat; ++c) { //per ogni categoria
for(imass = 0; imass<5;imass++){//guardo tutte le masse
m0[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_m0_cat%d",c))->getVal()/masses[imass];
// m1[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_m1_cat%d",c))->getVal()/masses[imass];
sigma0[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_sigma0_cat%d",c))->getVal()/masses[imass];
sigma1[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_sigma1_cat%d",c))->getVal()/masses[imass];
frac[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_frac_cat%d",c))->getVal();
//sig[imass]= ws[imass]->var(TString::Format("nsig_cat%d",c))->getVal();
m0_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_m0_cat%d",c))->getError()/masses[imass];
// m1_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_m1_cat%d",c))->getError()/masses[imass];
sigma0_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_sigma0_cat%d",c))->getError()/masses[imass];
sigma1_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_sigma1_cat%d",c))->getError()/masses[imass];
frac_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_frac_cat%d",c))->getError();
é//sig_err[imass]= ws[imass]->var(TString::Format("nsig_cat%d",c))->getError();
std::cout<<masses[imass]<<" "<<m0[imass]<<" "<<m0_err[imass]<<std::endl;
}
label_cat[c] = new TPaveText(0.6, 0.8, 0.7, 0.9, "brNDC" );
label_cat[c]->SetFillColor(kWhite);
label_cat[c]->SetBorderSize(1.5);
label_cat[c]->SetTextSize(0.038);
label_cat[c]->SetTextAlign(11);
label_cat[c]->SetTextFont(42);
label_cat[c]->AddText(TString::Format("Cat %d", c));
TGraphErrors* m0Graph = new TGraphErrors(5,masses, m0, masses_err, m0_err);
m0Graph->Draw("APE");
m0Graph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
m0Graph->GetYaxis()->SetRangeUser(0.8, 1.2);
m0Graph->GetYaxis()->SetTitle("m0 / m_{#gamma#gamma}");
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/m0vsmasses_%d.png", c));
/* TGraphErrors* m1Graph = new TGraphErrors(5,masses, m1, masses_err, m1_err);
m1Graph->Draw("APE");
m1Graph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
m1Graph->GetYaxis()->SetTitle("m1 [GeV]");
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/m1vsmasses_%d.png", c));*/
TGraphErrors* sigma0Graph = new TGraphErrors(5,masses, sigma0, masses_err, sigma0_err);
sigma0Graph->Draw("APE");
sigma0Graph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
sigma0Graph->GetYaxis()->SetTitle("#sigma0 / m_{#gamma#gamma}");
sigma0Graph->GetYaxis()->SetRangeUser(0., 0.07);
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/sigma0vsmasses_%d.png", c));
TGraphErrors* sigma1Graph = new TGraphErrors(5,masses, sigma1, masses_err, sigma1_err);
sigma1Graph->Draw("APE");
sigma1Graph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
sigma1Graph->GetYaxis()->SetTitle("#sigma1 / m_{#gamma#gamma}");
sigma1Graph->GetYaxis()->SetRangeUser(0., 0.07);
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/sigma1vsmasses_%d.png", c));
TGraphErrors* fracGraph = new TGraphErrors(5,masses, frac, masses_err, frac_err);
fracGraph->Draw("APE");
fracGraph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
fracGraph->GetYaxis()->SetTitle("%Gauss0 ");
fracGraph->GetYaxis()->SetRangeUser(0., 2.);
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/fracvsmasses_%d.png", c));
/* TGraphErrors* sigGraph = new TGraphErrors(5,masses, sig, masses_err, sig_err);
sigGraph->Draw("APE");
sigGraph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
sigGraph->GetYaxis()->SetTitle("Signal yield ");
sigGraph->GetYaxis()->SetRangeUser(0.001, 100.);
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SetLogy();
c1->SaveAs(TString::Format("plots/sigYieldvsmasses_%d.png", c));*/
}
}
void MakeParameterTrendvsMassCBC(){
gSystem->SetIncludePath("-I/afs/cern.ch/cms/slc5_amd64_gcc462/lcg/roofit/5.32.00-cms5/include");
gSystem->Load("libRooFit");
gROOT->ProcessLine(".x /afs/cern.ch/work/s/soffi/CMSSW_5_2_3-globe/src/HiggsAnalysis/HiggsTo2photons/h2gglobe/ChiaraFitLimits/RooCBCrujffPdf.cxx+");
TString wsDir = "workspaces/"+filePOSTfix;
Int_t ncat = NCAT;
Float_t masses[5];
masses[0] = 150.0;
masses[1] = 200.0;
masses[2] = 250.0;
masses[3] = 300.0;
masses[4] = 400.0.;
Float_t masses_err[5];
masses_err[0] = 0.;
masses_err[1] = 0.;
masses_err[2] = 0.;
masses_err[3] = 0.;
masses_err[4] = 0.;
TFile* file[5];
for(imass = 0; imass<5;imass++) file[imass]= new TFile(wsDir+TString::Format("HighMass-hgg.m%.1f_8TeV.inputsig.root",masses[imass]));
RooWorkspace* ws[5];
for(imass = 0; imass<5;imass++) ws[imass] = (RooWorkspace*) file[imass]->Get("w_all");
Float_t mean[5];
Float_t sigma[5];
Float_t alphaC[5];
Float_t alphaCB[5];
Float_t n[5];
Float_t sig[5];
Float_t mean_err[5];
Float_t sigma_err[5];
Float_t alphaC_err[5];
Float_t alphaCB_err[5];
Float_t n_err[5];
Float_t sig_err[5];
TCanvas* c1 = new TCanvas("c1", "c1", 1);
c1->cd();
TPaveText* label_cat[5];
TPaveText* label_cms = get_labelCMS(0, "2012", true);
TPaveText* label_sqrt = get_labelSqrt(0);
for (int c=0; c<ncat; ++c) { //per ogni categoria
for(imass = 0; imass<5;imass++){//guardo tutte le masse
mean[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_mean_cat%d",c))->getVal()/masses[imass];
sigma[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_sigma_cat%d",c))->getVal()/masses[imass];
alphaC[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_alphaC_cat%d",c))->getVal();
alphaCB[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_alphaCB_cat%d",c))->getVal();
n[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_n_cat%d",c))->getVal();
// sig[imass]= ws[imass]->var(TString::Format("nsigCBC_cat%d",c))->getVal();
mean_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_mean_cat%d",c))->getError()/masses[imass];
sigma_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_sigma_cat%d",c))->getError()/masses[imass];
alphaC_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_alphaC_cat%d",c))->getError();
alphaCB_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_alphaCB_cat%d",c))->getError();
n_err[imass]= ws[imass]->var(TString::Format("PhotonsMass_sig_n_cat%d",c))->getError();
// sig_err[imass]= ws[imass]->var(TString::Format("nsigCBC_cat%d",c))->getError();
std::cout<<masses[imass]<<" "<<mean[imass]<<" "<<mean_err[imass]<<std::endl;
}
label_cat[c] = new TPaveText(0.6, 0.8, 0.7, 0.9, "brNDC" );
label_cat[c]->SetFillColor(kWhite);
label_cat[c]->SetBorderSize(1.5);
label_cat[c]->SetTextSize(0.038);
label_cat[c]->SetTextAlign(11);
label_cat[c]->SetTextFont(42);
label_cat[c]->AddText(TString::Format("Cat %d", c));
TGraphErrors* meanGraph = new TGraphErrors(5,masses, mean, masses_err, mean_err);
meanGraph->Draw("APE");
meanGraph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
meanGraph->GetYaxis()->SetRangeUser(0.8, 1.2);
meanGraph->GetYaxis()->SetTitle("mean / m_{#gamma#gamma}");
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/meanvsmasses_%d.png", c));
TGraphErrors* sigmaGraph = new TGraphErrors(5,masses, sigma, masses_err, sigma_err);
sigmaGraph->Draw("APE");
sigmaGraph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
sigmaGraph->GetYaxis()->SetTitle("sigma / m_{#gamma#gamma}");
sigmaGraph->GetYaxis()->SetRangeUser(0.,0.1);
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/sigmavsmasses_%d.png", c));
TGraphErrors* alphaCGraph = new TGraphErrors(5,masses, alphaC, masses_err, alphaC_err);
alphaCGraph->Draw("APE");
alphaCGraph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
alphaCGraph->GetYaxis()->SetTitle("#alpha_{C}");
alphaCGraph->GetYaxis()->SetRangeUser(0., 0.4);
//Graph->GetYaxis()->SetRangeUser(0., 12.);
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/alphaCvsmasses_%d.png", c));
TGraphErrors* alphaCBGraph = new TGraphErrors(5,masses, alphaCB, masses_err, alphaCB_err);
alphaCBGraph->Draw("APE");
alphaCBGraph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
alphaCBGraph->GetYaxis()->SetTitle("#alpha_{CB}");
alphaCBGraph->GetYaxis()->SetRangeUser(0., 3.);
//Graph->GetYaxis()->SetRangeUser(0., 20.);
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/alphaCBvsmasses_%d.png", c));
TGraphErrors* nGraph = new TGraphErrors(5,masses, n, masses_err, n_err);
nGraph->Draw("APE");
nGraph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
nGraph->GetYaxis()->SetTitle("n ");
nGraph->GetYaxis()->SetRangeUser(0., 100.);
//nGraph->GetYaxis()->SetRangeUser(0., 2.);
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SaveAs(TString::Format("plots/nvsmasses_%d.png", c));
/*
TGraphErrors* sigGraph = new TGraphErrors(5,masses, sig, masses_err, sig_err);
sigGraph->Draw("APE");
sigGraph->GetXaxis()->SetTitle("m_{#gamma#gamma} [GeV]");
sigGraph->GetYaxis()->SetTitle("Signal yield ");
sigGraph->GetYaxis()->SetRangeUser(0.001, 100.);
label_cms->Draw("same");
label_sqrt->Draw("same");
label_cat[c]->Draw("same");
c1->SetLogy();
c1->SaveAs(TString::Format("plots/sigYieldvsmasses_%d.png", c));
*/
}
}
void PlotSigShape(RooWorkspace* w, Int_t c) {
Int_t nmass = 5;
Int_t masses[5] = {150, 200, 250, 300, 400};
TString inDir = "";
// Variables
RooArgSet* ntplVars = defineVariables();
RooRealVar* PhotonsMass = w->var("PhotonsMass");
TFile sigFile1("histograms_CMS-HGG_19032013.root"); //ggh prod mode tree livia
TCanvas* c1 = new TCanvas("c1", "c1", 1);
c1->cd();
RooPlot* plot;
for(int iMass=0;iMass<5;iMass++){ //per ogni massa
//chain summing up all production modes
TChain* sigTree1 = new TChain();
sigTree1->Add(TString::Format("histograms_CMS-HGG_19032013.root/ggh_m%d_8TeV", masses[iMass]));
sigTree1->Add(TString::Format("histograms_CMS-HGG_19032013.root/vbf_m%d_8TeV", masses[iMass]));
sigTree1->Add(TString::Format("histograms_CMS-HGG_19032013.root/wzh_m%d_8TeV", masses[iMass]));
sigTree1->Add(TString::Format("histograms_CMS-HGG_19032013.root/tth_m%d_8TeV", masses[iMass]));
sigTree1->SetTitle("sigTree1");
sigTree1->SetName("sigTree1");
// common preselection cut
TString mainCut = TString::Format("PhotonsMass>=(%d*0.7) && PhotonsMass<=(%d*1.3)", masses[iMass], masses[iMass]); // livia
RooDataSet sigWeighted("sigWeighted","dataset",sigTree1,*ntplVars,mainCut,"evweight");
cout << endl;
cout << "sigWeighted" << endl;
sigWeighted.Print("v");
cout << "---- nX: " << sigWeighted.sumEntries() << endl;
// apply a common preselection cut; split in categories
cout << endl;
RooDataSet* signal;
RooFormulaVar *massReduced_formula = new RooFormulaVar("massReduced_formula","",TString::Format("@0/%d-1",masses[iMass]),*w->var("PhotonsMass"));
RooRealVar* massReduced = (RooRealVar*) sigWeighted.addColumn(*massReduced_formula);
massReduced->SetName("massReduced");
massReduced->SetTitle("massReduced");
w->import(*massReduced);
// 1) prime 4 cat livia
if (c==0) signal = (RooDataSet*) sigWeighted.reduce(*w->var("massReduced"),mainCut+TString::Format("&& (abs(ph1_eta)<1.5 && abs(ph2_eta)<1.5) && (ph1_r9>0.94 && ph2_r9>0.94 )"));
if (c==1) signal = (RooDataSet*) sigWeighted.reduce(*w->var("massReduced"),mainCut+TString::Format("&& (abs(ph1_eta)<1.5 && abs(ph2_eta)<1.5) && (ph1_r9<0.94 || ph2_r9<0.94 ) "));
if (c==2) signal = (RooDataSet*) sigWeighted.reduce(*w->var("massReduced"),mainCut+TString::Format("&& (abs(ph1_eta)>1.5 || abs(ph2_eta)>1.5) && (ph1_r9>0.94 && ph2_r9>0.94 )"));
if (c==3) signal = (RooDataSet*) sigWeighted.reduce(*w->var("massReduced"),mainCut+TString::Format("&& (abs(ph1_eta)>1.5 || abs(ph2_eta)>1.5) && (ph1_r9>0.94 || ph2_r9>0.94 ) "));
if(iMass==0) plot = massReduced->frame(Range(-0.12, 0.12), Bins(60), Title("Mass Reduced"));
if(iMass==0) signal->plotOn(plot, DrawOption("L"), MarkerSize(0), MarkerColor(kWhite), LineWidth(2),LineColor(kBlack), XErrorSize(0), DataError(RooAbsData::None), Rescale(1./signal->sumEntries()));
if(iMass==1) signal->plotOn(plot, DrawOption("L"), MarkerSize(0), MarkerColor(kWhite), LineWidth(2),LineColor(kPink-8), XErrorSize(0), DataError(RooAbsData::None), Rescale(1./signal->sumEntries()));
if(iMass==2) signal->plotOn(plot, DrawOption("L"), MarkerSize(0), MarkerColor(kWhite), LineWidth(2),LineColor(kBlue+3), XErrorSize(0), DataError(RooAbsData::None), Rescale(1./signal->sumEntries()));
if(iMass==3) signal->plotOn(plot, DrawOption("L"), MarkerSize(0), MarkerColor(kWhite), LineWidth(2),LineColor(kOrange-3), XErrorSize(0), DataError(RooAbsData::None), Rescale(1./signal->sumEntries()));
if(iMass==4) signal->plotOn(plot, DrawOption("L"), MarkerSize(0), MarkerColor(kWhite), LineWidth(2),LineColor(kSpring-8), XErrorSize(0), DataError(RooAbsData::None), Rescale(1./signal->sumEntries()));
if(iMass==0) plot->Draw();
else plot->Draw("same");
}
plot->SetAxisRange(0.0001,0.4,"Y");
plot->GetXaxis()->SetTitle("#Delta m ");
plot->GetXaxis()->SetTitleFont(42);
plot->GetXaxis()->SetTitleSize(0.05);
TLegend* legmc = new TLegend(0.62, 0.6, 0.87, 0.89, "", "brNDC");
legmc->AddEntry(plot->getObject(0),"m_{#gamma#gamma} = 150 GeV","L");
legmc->AddEntry(plot->getObject(1),"m_{#gamma#gamma} = 200 GeV","L");
legmc->AddEntry(plot->getObject(2),"m_{#gamma#gamma} = 250 GeV","L");
legmc->AddEntry(plot->getObject(3),"m_{#gamma#gamma} = 300 GeV","L");
legmc->AddEntry(plot->getObject(4),"m_{#gamma#gamma} = 400 GeV","L");
legmc->SetTextSize(0.0206044);
legmc->SetTextFont(42);
legmc->SetBorderSize(0);
legmc->SetFillStyle(0);
legmc->Draw();
TLatex *lat = new TLatex(0.65,0.9,TString::Format("Cat: %d", c));
lat->SetTextSize(0.038);
lat->SetTextAlign(11);
lat->SetTextFont(42);
lat->Draw("same");
lat->SetNDC();
TPaveText* label_cms = get_labelCMS(0, "2012", true);
TPaveText* label_sqrt = get_labelSqrt(0);
label_cms->Draw("same");
label_sqrt->Draw("same");