void plot( TString var, TString data, TString pdf, double low=-1, double high=-1 ) {
TFile *tf = TFile::Open( "root/FitOut.root" );
RooWorkspace *w = (RooWorkspace*)tf->Get("w");
TCanvas *canv = new TCanvas("c","c",800,800);
TPad *upperPad = new TPad(Form("%s_upper",canv->GetName()),"",0.,0.33,1.,1.);
TPad *lowerPad = new TPad(Form("%s_lower",canv->GetName()),"",0.,0.,1.,0.33);
canv->cd();
upperPad->Draw();
lowerPad->Draw();
if ( low < 0 ) low = w->var(var)->getMin();
if ( high < 0 ) high = w->var(var)->getMax();
RooPlot *plot = w->var(var)->frame(Range(low,high));
w->data(data)->plotOn(plot);
w->pdf(pdf)->plotOn(plot);
RooHist *underHist = plot->pullHist();
underHist->GetXaxis()->SetRangeUser(plot->GetXaxis()->GetXmin(), plot->GetXaxis()->GetXmax());
underHist->GetXaxis()->SetTitle(plot->GetXaxis()->GetTitle());
underHist->GetYaxis()->SetTitle("Pull");
underHist->GetXaxis()->SetLabelSize(0.12);
underHist->GetYaxis()->SetLabelSize(0.12);
underHist->GetXaxis()->SetTitleSize(0.2);
underHist->GetXaxis()->SetTitleOffset(0.7);
underHist->GetYaxis()->SetTitleSize(0.18);
underHist->GetYaxis()->SetTitleOffset(0.38);
plot->GetXaxis()->SetTitle("");
upperPad->SetBottomMargin(0.1);
upperPad->cd();
plot->Draw();
canv->cd();
lowerPad->SetTopMargin(0.05);
lowerPad->SetBottomMargin(0.35);
lowerPad->cd();
underHist->Draw("AP");
double ymin = underHist->GetYaxis()->GetXmin();
double ymax = underHist->GetYaxis()->GetXmax();
double yrange = Max( Abs( ymin ), Abs( ymax ) );
underHist->GetYaxis()->SetRangeUser( -1.*yrange, 1.*yrange );
double xmin = plot->GetXaxis()->GetXmin();
double xmax = plot->GetXaxis()->GetXmax();
TColor *mycol3sig = gROOT->GetColor( kGray );
mycol3sig->SetAlpha(0.5);
TColor *mycol2sig = gROOT->GetColor( kGray+1 );
mycol2sig->SetAlpha(0.5);
TColor *mycol1sig = gROOT->GetColor( kGray+2 );
mycol1sig->SetAlpha(0.5);
TBox box3sig;
box3sig.SetFillColor( mycol3sig->GetNumber() );
//box3sig.SetFillColorAlpha( kGray, 0.5 );
box3sig.SetFillStyle(1001);
box3sig.DrawBox( xmin, -3., xmax, 3.);
TBox box2sig;
box2sig.SetFillColor( mycol2sig->GetNumber() );
//box2sig.SetFillColorAlpha( kGray+1, 0.5 );
box2sig.SetFillStyle(1001);
box2sig.DrawBox( xmin, -2., xmax, 2.);
TBox box1sig;
box1sig.SetFillColor( mycol1sig->GetNumber() );
//box1sig.SetFillColorAlpha( kGray+2, 0.5 );
box1sig.SetFillStyle(1001);
box1sig.DrawBox( xmin, -1., xmax, 1.);
TLine lineErr;
lineErr.SetLineWidth(1);
lineErr.SetLineColor(kBlue-9);
lineErr.SetLineStyle(2);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),1.,plot->GetXaxis()->GetXmax(),1.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),-1.,plot->GetXaxis()->GetXmax(),-1.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),2.,plot->GetXaxis()->GetXmax(),2.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),-2.,plot->GetXaxis()->GetXmax(),-2.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),3.,plot->GetXaxis()->GetXmax(),3.);
lineErr.DrawLine(plot->GetXaxis()->GetXmin(),-3.,plot->GetXaxis()->GetXmax(),-3.);
TLine line;
line.SetLineWidth(3);
line.SetLineColor(kBlue);
line.DrawLine(plot->GetXaxis()->GetXmin(),0.,plot->GetXaxis()->GetXmax(),0.);
underHist->Draw("Psame");
RooHist *redPull = new RooHist();
int newp=0;
for (int p=0; p<underHist->GetN(); p++) {
double x,y;
underHist->GetPoint(p,x,y);
if ( TMath::Abs(y)>3 ) {
redPull->SetPoint(newp,x,y);
redPull->SetPointError(newp,0.,0.,underHist->GetErrorYlow(p),underHist->GetErrorYhigh(p));
newp++;
}
}
redPull->SetLineWidth(underHist->GetLineWidth());
redPull->SetMarkerStyle(underHist->GetMarkerStyle());
redPull->SetMarkerSize(underHist->GetMarkerSize());
redPull->SetLineColor(kRed);
redPull->SetMarkerColor(kRed);
redPull->Draw("Psame");
canv->Print(Form("tmp/%s.pdf",var.Data()));
tf->Close();
}
void BackgroundPrediction(std::string pname,int rebin_factor,int model_number = 0,int imass=750, bool plotBands = false)
{
rebin = rebin_factor;
std::string fname = std::string("../fitFilesMETPT34/") + pname + std::string("/histos_bkg.root");
stringstream iimass ;
iimass << imass;
std::string dirName = "info_"+iimass.str()+"_"+pname;
gStyle->SetOptStat(000000000);
gStyle->SetPadGridX(0);
gStyle->SetPadGridY(0);
setTDRStyle();
gStyle->SetPadGridX(0);
gStyle->SetPadGridY(0);
gStyle->SetOptStat(0000);
writeExtraText = true; // if extra text
extraText = "Preliminary"; // default extra text is "Preliminary"
lumi_13TeV = "2.7 fb^{-1}"; // default is "19.7 fb^{-1}"
lumi_7TeV = "4.9 fb^{-1}"; // default is "5.1 fb^{-1}"
double ratio_tau=-1;
TFile *f=new TFile(fname.c_str());
TH1F *h_mX_CR_tau=(TH1F*)f->Get("distribs_18_10_1")->Clone("CR_tau");
TH1F *h_mX_SR=(TH1F*)f->Get("distribs_18_10_0")->Clone("The_SR");
double maxdata = h_mX_SR->GetMaximum();
double nEventsSR = h_mX_SR->Integral(600,4000);
ratio_tau=(h_mX_SR->GetSumOfWeights()/(h_mX_CR_tau->GetSumOfWeights()));
//double nEventsSR = h_mX_SR->Integral(600,4000);
std::cout<<"ratio tau "<<ratio_tau<<std::endl;
TH1F *h_SR_Prediction;
TH1F *h_SR_Prediction2;
if(blind) {
h_SR_Prediction2 = (TH1F*)h_mX_CR_tau->Clone("h_SR_Prediction2");
h_mX_CR_tau->Rebin(rebin);
h_mX_CR_tau->SetLineColor(kBlack);
h_SR_Prediction=(TH1F*)h_mX_CR_tau->Clone("h_SR_Prediction");
} else {
h_SR_Prediction2=(TH1F*)h_mX_SR->Clone("h_SR_Prediction2");
h_mX_SR->Rebin(rebin);
h_mX_SR->SetLineColor(kBlack);
h_SR_Prediction=(TH1F*)h_mX_SR->Clone("h_SR_Prediction");
}
h_SR_Prediction->SetMarkerSize(0.7);
h_SR_Prediction->GetYaxis()->SetTitleOffset(1.2);
h_SR_Prediction->Sumw2();
/*TFile *f_sig = new TFile((dirName+"/w_signal_"+iimass.str()+".root").c_str());
RooWorkspace* xf_sig = (RooWorkspace*)f_sig->Get("Vg");
RooAbsPdf *xf_sig_pdf = (RooAbsPdf *)xf_sig->pdf((std::string("signal_fixed_")+pname).c_str());
RooWorkspace w_sig("w");
w_sig.import(*xf_sig_pdf,RooFit::RenameVariable((std::string("signal_fixed_")+pname).c_str(),(std::string("signal_fixed_")+pname+std::string("low")).c_str()),RooFit::RenameAllVariablesExcept("low","x"));
xf_sig_pdf = w_sig.pdf((std::string("signal_fixed_")+pname+std::string("low")).c_str());
RooArgSet* biasVars = xf_sig_pdf->getVariables();
TIterator *it = biasVars->createIterator();
RooRealVar* var = (RooRealVar*)it->Next();
while (var) {
var->setConstant(kTRUE);
var = (RooRealVar*)it->Next();
}
*/
RooRealVar x("x", "m_{X} (GeV)", SR_lo, SR_hi);
RooRealVar nBackground((std::string("bg_")+pname+std::string("_norm")).c_str(),"nbkg",h_mX_SR->GetSumOfWeights());
RooRealVar nBackground2((std::string("alt_bg_")+pname+std::string("_norm")).c_str(),"nbkg",h_mX_SR->GetSumOfWeights());
std::string blah = pname;
//pname=""; //Antibtag=tag to constrain b-tag to the anti-btag shape
/* RooRealVar bg_p0((std::string("bg_p0_")+pname).c_str(), "bg_p0", 4.2, 0, 200.);
RooRealVar bg_p1((std::string("bg_p1_")+pname).c_str(), "bg_p1", 4.5, 0, 300.);
RooRealVar bg_p2((std::string("bg_p2_")+pname).c_str(), "bg_p2", 0.000047, 0, 10.1);
RooGenericPdf bg_pure = RooGenericPdf((std::string("bg_pure_")+blah).c_str(),"(pow(1-@0/13000,@1)/pow(@0/13000,@2+@3*log(@0/13000)))",RooArgList(x,bg_p0,bg_p1,bg_p2));
*/
RooRealVar bg_p0((std::string("bg_p0_")+pname).c_str(), "bg_p0", 0., -1000, 200.);
RooRealVar bg_p1((std::string("bg_p1_")+pname).c_str(), "bg_p1", -13, -1000, 1000.);
RooRealVar bg_p2((std::string("bg_p2_")+pname).c_str(), "bg_p2", -1.4, -1000, 1000.);
bg_p0.setConstant(kTRUE);
//RooGenericPdf bg_pure = RooGenericPdf((std::string("bg_pure_")+blah).c_str(),"(pow(@0/13000,@1+@2*log(@0/13000)))",RooArgList(x,bg_p1,bg_p2));
RooGenericPdf bg = RooGenericPdf((std::string("bg_")+blah).c_str(),"(pow(@0/13000,@1+@2*log(@0/13000)))",RooArgList(x,bg_p1,bg_p2));
/*TF1* biasFunc = new TF1("biasFunc","(0.63*x/1000-1.45)",1350,3600);
TF1* biasFunc2 = new TF1("biasFunc2","TMath::Min(2.,2.3*x/1000-3.8)",1350,3600);
double bias_term_s = 0;
if ((imass > 2450 && blah == "antibtag") || (imass > 1640 && blah == "btag")) {
if (blah == "antibtag") {
bias_term_s = 2.7*biasFunc->Eval(imass);
} else {
bias_term_s = 2.7*biasFunc2->Eval(imass);
}
bias_term_s/=nEventsSR;
}
RooRealVar bias_term((std::string("bias_term_")+blah).c_str(), "bias_term", 0., -bias_term_s, bias_term_s);
//bias_term.setConstant(kTRUE);
RooAddPdf bg((std::string("bg_")+blah).c_str(), "bg_all", RooArgList(*xf_sig_pdf, bg_pure), bias_term);
*/
string name_output = "CR_RooFit_Exp";
std::cout<<"Nevents "<<nEventsSR<<std::endl;
RooDataHist pred("pred", "Prediction from SB", RooArgList(x), h_SR_Prediction);
RooFitResult *r_bg=bg.fitTo(pred, RooFit::Minimizer("Minuit2"), RooFit::Range(SR_lo, SR_hi), RooFit::SumW2Error(kTRUE), RooFit::Save());
//RooFitResult *r_bg=bg.fitTo(pred, RooFit::Range(SR_lo, SR_hi), RooFit::Save());
//RooFitResult *r_bg=bg.fitTo(pred, RooFit::Range(SR_lo, SR_hi), RooFit::Save(),RooFit::SumW2Error(kTRUE));
std::cout<<" --------------------- Building Envelope --------------------- "<<std::endl;
//std::cout<< "bg_p0_"<< pname << " param "<<bg_p0.getVal() << " "<<bg_p0.getError()<<std::endl;
std::cout<< "bg_p1_"<< pname << " param "<<bg_p1.getVal() << " "<<100*bg_p1.getError()<<std::endl;
std::cout<< "bg_p2_"<< pname << " param "<<bg_p2.getVal() << " "<<100*bg_p2.getError()<<std::endl;
//std::cout<< "bias_term_"<< blah << " param 0 "<<bias_term_s<<std::endl;
RooPlot *aC_plot=x.frame();
pred.plotOn(aC_plot, RooFit::MarkerColor(kPink+2));
if (!plotBands) {
bg.plotOn(aC_plot, RooFit::VisualizeError(*r_bg, 2), RooFit::FillColor(kYellow));
bg.plotOn(aC_plot, RooFit::VisualizeError(*r_bg, 1), RooFit::FillColor(kGreen));
}
bg.plotOn(aC_plot, RooFit::LineColor(kBlue));
//pred.plotOn(aC_plot, RooFit::LineColor(kBlack), RooFit::MarkerColor(kBlack));
TGraph* error_curve[5]; //correct error bands
TGraphAsymmErrors* dataGr = new TGraphAsymmErrors(h_SR_Prediction->GetNbinsX()); //data w/o 0 entries
for (int i=2; i!=5; ++i) {
error_curve[i] = new TGraph();
}
error_curve[2] = (TGraph*)aC_plot->getObject(1)->Clone("errs");
int nPoints = error_curve[2]->GetN();
error_curve[0] = new TGraph(2*nPoints);
error_curve[1] = new TGraph(2*nPoints);
error_curve[0]->SetFillStyle(1001);
error_curve[1]->SetFillStyle(1001);
error_curve[0]->SetFillColor(kGreen);
error_curve[1]->SetFillColor(kYellow);
error_curve[0]->SetLineColor(kGreen);
error_curve[1]->SetLineColor(kYellow);
if (plotBands) {
RooDataHist pred2("pred2", "Prediction from SB", RooArgList(x), h_SR_Prediction2);
error_curve[3]->SetFillStyle(1001);
error_curve[4]->SetFillStyle(1001);
error_curve[3]->SetFillColor(kGreen);
error_curve[4]->SetFillColor(kYellow);
error_curve[3]->SetLineColor(kGreen);
error_curve[4]->SetLineColor(kYellow);
error_curve[2]->SetLineColor(kBlue);
error_curve[2]->SetLineWidth(3);
double binSize = rebin;
for (int i=0; i!=nPoints; ++i) {
double x0,y0, x1,y1;
error_curve[2]->GetPoint(i,x0,y0);
RooAbsReal* nlim = new RooRealVar("nlim","y0",y0,-100000,100000);
//double lowedge = x0 - (SR_hi - SR_lo)/double(2*nPoints);
//double upedge = x0 + (SR_hi - SR_lo)/double(2*nPoints);
double lowedge = x0 - binSize/2.;
double upedge = x0 + binSize/2.;
x.setRange("errRange",lowedge,upedge);
RooExtendPdf* epdf = new RooExtendPdf("epdf","extpdf",bg, *nlim,"errRange");
// Construct unbinned likelihood
RooAbsReal* nll = epdf->createNLL(pred2,NumCPU(2));
// Minimize likelihood w.r.t all parameters before making plots
RooMinimizer* minim = new RooMinimizer(*nll);
minim->setMinimizerType("Minuit2");
minim->setStrategy(2);
minim->setPrintLevel(-1);
minim->migrad();
minim->hesse();
RooFitResult* result = minim->lastMinuitFit();
double errm = nlim->getPropagatedError(*result);
//std::cout<<x0<<" "<<lowedge<<" "<<upedge<<" "<<y0<<" "<<nlim->getVal()<<" "<<errm<<std::endl;
error_curve[0]->SetPoint(i,x0,(y0-errm));
error_curve[0]->SetPoint(2*nPoints-i-1,x0,y0+errm);
error_curve[1]->SetPoint(i,x0,(y0-2*errm));
error_curve[1]->SetPoint(2*nPoints-i-1,x0,(y0+2*errm));
error_curve[3]->SetPoint(i,x0,-errm/sqrt(y0));
error_curve[3]->SetPoint(2*nPoints-i-1,x0,errm/sqrt(y0));
error_curve[4]->SetPoint(i,x0,-2*errm/sqrt(y0));
error_curve[4]->SetPoint(2*nPoints-i-1,x0,2*errm/sqrt(y0));
}
int npois = 0;
dataGr->SetMarkerSize(1.0);
dataGr->SetMarkerStyle (20);
const double alpha = 1 - 0.6827;
for (int i=0; i!=h_SR_Prediction->GetNbinsX(); ++i){
if (h_SR_Prediction->GetBinContent(i+1) > 0) {
int N = h_SR_Prediction->GetBinContent(i+1);
double L = (N==0) ? 0 : (ROOT::Math::gamma_quantile(alpha/2,N,1.));
double U = ROOT::Math::gamma_quantile_c(alpha/2,N+1,1) ;
dataGr->SetPoint(npois,h_SR_Prediction->GetBinCenter(i+1),h_SR_Prediction->GetBinContent(i+1));
dataGr->SetPointEYlow(npois, N-L);
dataGr->SetPointEYhigh(npois, U-N);
npois++;
}
}
}
double xG[2] = {-10,4000};
double yG[2] = {0.0,0.0};
TGraph* unityG = new TGraph(2, xG, yG);
unityG->SetLineColor(kBlue);
unityG->SetLineWidth(1);
double xPad = 0.3;
TCanvas *c_rooFit=new TCanvas("c_rooFit", "c_rooFit", 800*(1.-xPad), 600);
c_rooFit->SetFillStyle(4000);
c_rooFit->SetFrameFillColor(0);
TPad *p_1=new TPad("p_1", "p_1", 0, xPad, 1, 1);
p_1->SetFillStyle(4000);
p_1->SetFrameFillColor(0);
p_1->SetBottomMargin(0.02);
TPad* p_2 = new TPad("p_2", "p_2",0,0,1,xPad);
p_2->SetBottomMargin((1.-xPad)/xPad*0.13);
p_2->SetTopMargin(0.03);
p_2->SetFillColor(0);
p_2->SetBorderMode(0);
p_2->SetBorderSize(2);
p_2->SetFrameBorderMode(0);
p_2->SetFrameBorderMode(0);
p_1->Draw();
p_2->Draw();
p_1->cd();
int nbins = (int) (SR_hi- SR_lo)/rebin;
x.setBins(nbins);
std::cout << "chi2(data) " << aC_plot->chiSquare()<<std::endl;
//std::cout << "p-value: data under hypothesis H0: " << TMath::Prob(chi2_data->getVal(), nbins - 1) << std::endl;
aC_plot->GetXaxis()->SetRangeUser(SR_lo, SR_hi);
aC_plot->GetXaxis()->SetLabelOffset(0.02);
aC_plot->GetYaxis()->SetRangeUser(0.1, 1000.);
h_SR_Prediction->GetXaxis()->SetRangeUser(SR_lo, SR_hi);
string rebin_ = itoa(rebin);
aC_plot->GetXaxis()->SetTitle("M_{Z#gamma} [GeV] ");
aC_plot->GetYaxis()->SetTitle(("Events / "+rebin_+" GeV ").c_str());
aC_plot->SetMarkerSize(0.7);
aC_plot->GetYaxis()->SetTitleOffset(1.2);
aC_plot->Draw();
if (plotBands) {
error_curve[1]->Draw("Fsame");
error_curve[0]->Draw("Fsame");
error_curve[2]->Draw("Lsame");
dataGr->Draw("p e1 same");
}
aC_plot->SetTitle("");
TPaveText *pave = new TPaveText(0.85,0.4,0.67,0.5,"NDC");
pave->SetBorderSize(0);
pave->SetTextSize(0.05);
pave->SetTextFont(42);
pave->SetLineColor(1);
pave->SetLineStyle(1);
pave->SetLineWidth(2);
pave->SetFillColor(0);
pave->SetFillStyle(0);
char name[1000];
sprintf(name,"#chi^{2}/n = %.2f",aC_plot->chiSquare());
pave->AddText(name);
//pave->Draw();
TLegend *leg = new TLegend(0.88,0.65,0.55,0.90,NULL,"brNDC");
leg->SetBorderSize(0);
leg->SetTextSize(0.05);
leg->SetTextFont(42);
leg->SetLineColor(1);
leg->SetLineStyle(1);
leg->SetLineWidth(2);
leg->SetFillColor(0);
leg->SetFillStyle(0);
h_SR_Prediction->SetMarkerColor(kBlack);
h_SR_Prediction->SetLineColor(kBlack);
h_SR_Prediction->SetMarkerStyle(20);
h_SR_Prediction->SetMarkerSize(1.0);
//h_mMMMMa_3Tag_SR->GetXaxis()->SetTitleSize(0.09);
if (blind)
leg->AddEntry(h_SR_Prediction, "Data: sideband", "ep");
else {
if (blah == "antibtag" )
leg->AddEntry(h_SR_Prediction, "Data: anti-b-tag SR", "ep");
else
leg->AddEntry(h_SR_Prediction, "Data: b-tag SR", "ep");
}
leg->AddEntry(error_curve[2], "Fit model", "l");
leg->AddEntry(error_curve[0], "Fit #pm1#sigma", "f");
leg->AddEntry(error_curve[1], "Fit #pm2#sigma", "f");
leg->Draw();
aC_plot->Draw("axis same");
CMS_lumi( p_1, iPeriod, iPos );
p_2->cd();
RooHist* hpull;
hpull = aC_plot->pullHist();
RooPlot* frameP = x.frame() ;
frameP->SetTitle("");
frameP->GetXaxis()->SetRangeUser(SR_lo, SR_hi);
frameP->addPlotable(hpull,"P");
frameP->GetYaxis()->SetRangeUser(-7,7);
frameP->GetYaxis()->SetNdivisions(505);
frameP->GetYaxis()->SetTitle("#frac{(data-fit)}{#sigma_{stat}}");
frameP->GetYaxis()->SetTitleSize((1.-xPad)/xPad*0.06);
frameP->GetYaxis()->SetTitleOffset(1.0/((1.-xPad)/xPad));
frameP->GetXaxis()->SetTitleSize((1.-xPad)/xPad*0.06);
//frameP->GetXaxis()->SetTitleOffset(1.0);
frameP->GetXaxis()->SetLabelSize((1.-xPad)/xPad*0.05);
frameP->GetYaxis()->SetLabelSize((1.-xPad)/xPad*0.05);
frameP->Draw();
if (plotBands) {
error_curve[4]->Draw("Fsame");
error_curve[3]->Draw("Fsame");
unityG->Draw("same");
hpull->Draw("psame");
frameP->Draw("axis same");
}
c_rooFit->SaveAs((dirName+"/"+name_output+".pdf").c_str());
const int nModels = 9;
TString models[nModels] = {
"env_pdf_0_13TeV_dijet2", //0
"env_pdf_0_13TeV_exp1", //1
"env_pdf_0_13TeV_expow1", //2
"env_pdf_0_13TeV_expow2", //3 => skip
"env_pdf_0_13TeV_pow1", //4
"env_pdf_0_13TeV_lau1", //5
"env_pdf_0_13TeV_atlas1", //6
"env_pdf_0_13TeV_atlas2", //7 => skip
"env_pdf_0_13TeV_vvdijet1" //8
};
int nPars[nModels] = {
2, 1, 2, 3, 1, 1, 2, 3, 2
};
TString parNames[nModels][3] = {
"env_pdf_0_13TeV_dijet2_log1","env_pdf_0_13TeV_dijet2_log2","",
"env_pdf_0_13TeV_exp1_p1","","",
"env_pdf_0_13TeV_expow1_exp1","env_pdf_0_13TeV_expow1_pow1","",
"env_pdf_0_13TeV_expow2_exp1","env_pdf_0_13TeV_expow2_pow1","env_pdf_0_13TeV_expow2_exp2",
"env_pdf_0_13TeV_pow1_p1","","",
"env_pdf_0_13TeV_lau1_l1","","",
"env_pdf_0_13TeV_atlas1_coeff1","env_pdf_0_13TeV_atlas1_log1","",
"env_pdf_0_13TeV_atlas2_coeff1","env_pdf_0_13TeV_atlas2_log1","env_pdf_0_13TeV_atlas2_log2",
"env_pdf_0_13TeV_vvdijet1_coeff1","env_pdf_0_13TeV_vvdijet1_log1",""
}
if(bias){
//alternative model
gSystem->Load("libHiggsAnalysisCombinedLimit");
gSystem->Load("libdiphotonsUtils");
TFile *f = new TFile("antibtag_multipdf.root");
RooWorkspace* xf = (RooWorkspace*)f->Get("wtemplates");
RooWorkspace *w_alt=new RooWorkspace("Vg");
for(int i=model_number; i<=model_number; i++){
RooMultiPdf *alternative = (RooMultiPdf *)xf->pdf("model_bkg_AntiBtag");
std::cout<<"Number of pdfs "<<alternative->getNumPdfs()<<std::endl;
for (int j=0; j!=alternative->getNumPdfs(); ++j){
std::cout<<alternative->getPdf(j)->GetName()<<std::endl;
}
RooAbsPdf *alt_bg = alternative->getPdf(alternative->getCurrentIndex()+i);//->clone();
w_alt->import(*alt_bg, RooFit::RenameVariable(alt_bg->GetName(),("alt_bg_"+blah).c_str()));
w_alt->Print("V");
std::cerr<<w_alt->var("x")<<std::endl;
RooRealVar * range_ = w_alt->var("x");
range_->setRange(SR_lo,SR_hi);
char* asd = ("alt_bg_"+blah).c_str() ;
w_alt->import(nBackground2);
std::cout<<alt_bg->getVal() <<std::endl;
w_alt->pdf(asd)->fitTo(pred, RooFit::Minimizer("Minuit2"), RooFit::Range(SR_lo, SR_hi), RooFit::SumW2Error(kTRUE), RooFit::Save());
RooArgSet* altVars = w_alt->pdf(asd)->getVariables();
TIterator *it2 = altVars->createIterator();
RooRealVar* varAlt = (RooRealVar*)it2->Next();
while (varAlt) {
varAlt->setConstant(kTRUE);
varAlt = (RooRealVar*)it2->Next();
}
alt_bg->plotOn(aC_plot, RooFit::LineColor(i+1), RooFit::LineStyle(i+2));
p_1->cd();
aC_plot->GetYaxis()->SetRangeUser(0.01, maxdata*50.);
aC_plot->Draw("same");
TH1F *h=new TH1F();
h->SetLineColor(1+i);
h->SetLineStyle(i+2);
leg->AddEntry(h, alt_bg->GetName(), "l");
w_alt->SaveAs((dirName+"/w_background_alternative.root").c_str());
}
leg->Draw();
p_1->SetLogy();
c_rooFit->Update();
c_rooFit->SaveAs((dirName+"/"+name_output+blah+"_multipdf.pdf").c_str());
for (int i=0; i!=nPars[model_number]; ++i) {
std::cout<<parNames[model_number][i]<<" param "<< w_alt->var(parNames[model_number][i])->getVal()<<" "<<w_alt->var(parNames[model_number][i])->getError()<<std::endl;
}
} else {
p_1->SetLogy();
c_rooFit->Update();
c_rooFit->SaveAs((dirName+"/"+name_output+"_log.pdf").c_str());
}
RooWorkspace *w=new RooWorkspace("Vg");
w->import(bg);
w->import(nBackground);
w->SaveAs((dirName+"/w_background_GaussExp.root").c_str());
TH1F *h_mX_SR_fakeData=(TH1F*)h_mX_SR->Clone("h_mX_SR_fakeData");
h_mX_SR_fakeData->Scale(nEventsSR/h_mX_SR_fakeData->GetSumOfWeights());
RooDataHist data_obs("data_obs", "Data", RooArgList(x), h_mX_SR_fakeData);
std::cout<<" Background number of events = "<<nEventsSR<<std::endl;
RooWorkspace *w_data=new RooWorkspace("Vg");
w_data->import(data_obs);
w_data->SaveAs((dirName+"/w_data.root").c_str());
}
void checkGoodness(TString scenario, TH1D* dummyThis,TString varType, TString shapeComb, TString INPUTDIR_PREFIX, TString SCEN_TRIG) {
cout << "Inside the checkGoodness we have " << scenario << " histo " << dummyThis->GetName() << " " << varType << " " << shapeComb << " " << INPUTDIR_PREFIX << " " << SCEN_TRIG << endl;
//for each bin, for each type get 3 histos
TH1D* hpulls_sig_pass = (TH1D*)dummyThis->Clone();
hpulls_sig_pass->SetName("hpulls_sig_pass");
TH1D* hpulls_sig_fail = (TH1D*)dummyThis->Clone();
hpulls_sig_fail->SetName("hpulls_sig_fail");
//TH1D* hpulls_bkg_pass = (TH1D*)dummyThis->Clone();
//hpulls_bkg_pass->SetName("hpulls_bkg_pass");
//TH1D* hpulls_bkg_fail = (TH1D*)dummyThis->Clone();
//hpulls_bkg_fail->SetName("hpulls_bkg_fail");
for (int ibin = 0; ibin < getNbin(varType)-1; ibin++) {
//int to string
std::ostringstream pprint;
pprint.str("");
pprint<<ibin;
string bin = pprint.str();
//for each bin for each type
cout << "get data from canvas" << endl;
RooHist* thisDataPass = getFitHist(INPUTDIR_PREFIX, scenario, "datalike_mc", varType, SCEN_TRIG,shapeComb, "1",TString(bin), "data");
RooCurve* thisSignalPass = getFitCurve(INPUTDIR_PREFIX,scenario, "datalike_mc", varType, SCEN_TRIG,shapeComb, "1",TString(bin), "sig");
RooCurve* thisBackgroundPass = getFitCurve(INPUTDIR_PREFIX,scenario, "datalike_mc", varType, SCEN_TRIG,shapeComb,"1",TString(bin), "bkg");
RooHist* thisDataFail = getFitHist(INPUTDIR_PREFIX, scenario, "datalike_mc", varType, SCEN_TRIG,shapeComb,"2",TString(bin), "data");
RooCurve* thisSignalFail = getFitCurve(INPUTDIR_PREFIX,scenario, "datalike_mc", varType, SCEN_TRIG,shapeComb,"2",TString(bin), "sig");
RooCurve* thisBackgroundFail = getFitCurve(INPUTDIR_PREFIX,scenario, "datalike_mc", varType, SCEN_TRIG,shapeComb,"2",TString(bin), "bkg");
// RooCurve* thisBackgroundFail = getFitCurve(INPUTDIR_PREFIX,scenario, "datalike_mc", varType, SCEN_TRIG,getShapeUtility(shapeComb, ibin,"datalike_mc"),"2",TString(bin), "bkg");
//Plot and save
//RooPlot* ctmp_pass = getFitPlot(INPUTDIR_PREFIX, scenario, "datalike_mc", varType, SCEN_TRIG,getShapeUtility(shapeComb, ibin,"datalike_mc"),"1",TString(bin), "data");
//new RooPlot();
TCanvas* ctmp_pass = new TCanvas("PASS"+TString(bin)+"_view_"+getShapeUtility(shapeComb, ibin,"datalike_mc"),"PASS"+TString(bin)+"_view_"+getShapeUtility(shapeComb, ibin,"datalike_mc"));
ctmp_pass->cd();
//ctmp_pass->Draw();
thisDataPass->Draw("ap");
thisSignalPass->Draw("same");
thisBackgroundPass->Draw("same");
ctmp_pass->SaveAs(INPUTDIR_PREFIX+"/PASS"+TString(bin)+"_view_"+getShapeUtility(shapeComb, ibin,"datalike_mc")+".png");
TCanvas* ctmp_fail = new TCanvas("FAIL"+TString(bin)+"_view_"+getShapeUtility(shapeComb, ibin,"datalike_mc"),"FAIL"+TString(bin)+"_view_"+getShapeUtility(shapeComb, ibin,"datalike_mc"));
//RooPlot* ctmp_fail = getFitPlot(INPUTDIR_PREFIX, scenario, "datalike_mc", varType, SCEN_TRIG,getShapeUtility(shapeComb, ibin,"datalike_mc"),"1",TString(bin), "data");
ctmp_fail->cd();
thisDataFail->Draw("ap");
thisSignalFail->Draw("same");
thisBackgroundFail->Draw("same");
ctmp_fail->SaveAs(INPUTDIR_PREFIX+"/FAIL"+TString(bin)+"_view_"+getShapeUtility(shapeComb, ibin,"datalike_mc")+".png");
//calculate and draw pulls
//PASS
TCanvas* cpull_pass_sig_tmp = new TCanvas("pulls_"+TString(bin)+"_PASS_SIG_"+getShapeUtility(shapeComb, ibin,"datalike_mc"),"pulls_"+TString(bin)+"_PASS_SIG_"+getShapeUtility(shapeComb, ibin,"datalike_mc"));
cpull_pass_sig_tmp->cd();
thisDataPass->makeResidHist(*thisSignalPass,kTRUE)->Draw("ap");
cpull_pass_sig_tmp->SaveAs(INPUTDIR_PREFIX+"/SIG"+TString(bin)+"_PULL_PASS_"+getShapeUtility(shapeComb, ibin,"datalike_mc")+".png");
//get mean pulls for a given canvas
hpulls_sig_pass->SetBinContent(ibin+1,fabs(getRooMean(thisDataPass->makeResidHist(*thisSignalPass,kTRUE))));
hpulls_sig_pass->SetBinError(ibin+1,0.000001);
/* TCanvas* cpull_pass_bkg_tmp = new TCanvas("pulls_"+TString(bin)+"_PASS_BKG_"+getShapeUtility(shapeComb, ibin,"datalike_mc","pulls_"+TString(bin)+"_PASS_BKG_"+getShapeUtility(shapeComb, ibin,"datalike_mc");
cpull_pass_bkg_tmp->cd();
thisDataPass->makeResidHist(*thisBackgroundPass,kTRUE)->Draw("ap");
cpull_pass_bkg_tmp->SaveAs("BKG"+TString(bin)+"_PULL_PASS_"+getShapeUtility(shapeComb, ibin,"datalike_mc"+".png");
//get mean pulls for a given canvas
hpulls_bkg_pass->SetBinContent(ibin+1,getRooMean(thisDataPass->makeResidHist(*thisBackgroundPass,kTRUE)));
hpulls_bkg_pass->SetBinError(ibin+1,0.000001);
*/
//FAIL
TCanvas* cpull_fail_sig_tmp = new TCanvas("pulls_"+TString(bin)+"_FAIL_SIG_"+getShapeUtility(shapeComb, ibin,"datalike_mc"),"pulls_"+TString(bin)+"_FAIL_SIG_"+getShapeUtility(shapeComb, ibin,"datalike_mc"));
cpull_fail_sig_tmp->cd();
thisDataFail->makeResidHist(*thisSignalFail,kTRUE)->Draw("ap");
cpull_fail_sig_tmp->SaveAs( INPUTDIR_PREFIX+"/SIG"+TString(bin)+"_PULL_FAIL_"+getShapeUtility(shapeComb, ibin,"datalike_mc")+".png");
cout << "get mean pulls for a given canvas" << endl;
hpulls_sig_fail->SetBinContent(ibin+1,fabs(getRooMean(thisDataFail->makeResidHist(*thisSignalFail,kTRUE))));
hpulls_sig_fail->SetBinError(ibin+1,0.000001);
/* TCanvas* cpull_fail_bkg_tmp = new TCanvas("pulls_"+TString(bin)+"_FAIL_BKG_"+getShapeUtility(shapeComb, ibin,"datalike_mc","pulls_"+TString(bin)+"_FAIL_BKG_"+getShapeUtility(shapeComb,
ibin));
cpull_fail_bkg_tmp->cd();
thisDataFail->makeResidHist(*thisBackgroundFail,kTRUE)->Draw("ap");
cpull_fail_bkg_tmp->SaveAs("BKG"+TString(bin)+"_PULL_FAIL_"+getShapeUtility(shapeComb, ibin,"datalike_mc"+".png");
cout << "get mean pulls for a given canvas" << endl;
hpulls_bkg_fail->SetBinContent(ibin+1,getRooMean(thisDataFail->makeResidHist(*thisBackgroundFail,kTRUE)));
hpulls_bkg_fail->SetBinError(ibin+1,0.000001);
*/
}
cout << "OUT PULLS FILL LOOP XXX" << endl;
//PLOT pull means distributions
TCanvas* cpullf_sig = new TCanvas("SIG"+scenario+varType,"SIG"+scenario+varType);
cpullf_sig->cd();
cpullf_sig->SetLogx();
cpullf_sig->SetLogy();
hpulls_sig_pass->SetMarkerStyle(22);
hpulls_sig_pass->SetMarkerSize(1.1);
hpulls_sig_pass->SetMarkerColor(kBlack);
hpulls_sig_pass->Draw("P");
hpulls_sig_fail->SetMarkerStyle(24);
hpulls_sig_fail->SetMarkerSize(1.1);
hpulls_sig_fail->SetMarkerColor(kRed);
hpulls_sig_fail->Draw("Psame");
cpullf_sig->SaveAs(INPUTDIR_PREFIX+"/SIG"+scenario+varType+".png");
/*
TCanvas* cpullf_bkg = new TCanvas("BKG"+scenario+varType,"BKG"+scenario+varType);
cpullf_bkg->cd();
hpulls_bkg_pass->SetMarkerStyle(22);
hpulls_bkg_pass->SetMarkerSize(1.1);
hpulls_bkg_pass->SetMarkerColor(kBlack);
hpulls_bkg_pass->Draw("P");
hpulls_bkg_fail->SetMarkerStyle(24);
hpulls_bkg_fail->SetMarkerSize(1.1);
hpulls_bkg_fail->SetMarkerColor(kRed);
hpulls_bkg_fail->Draw("Psame");
cpullf_bkg->SaveAs("BKG"+scenario+varType+".png");
*/
}