//____________________________________
void DoSPlot(RooWorkspace* ws){
std::cout << "Calculate sWeights" << std::endl;
// get what we need out of the workspace to do the fit
RooAbsPdf* model = ws->pdf("model");
RooRealVar* zYield = ws->var("zYield");
RooRealVar* qcdYield = ws->var("qcdYield");
RooDataSet* data = (RooDataSet*) ws->data("data");
// fit the model to the data.
model->fitTo(*data, Extended() );
// The sPlot technique requires that we fix the parameters
// of the model that are not yields after doing the fit.
RooRealVar* sigmaZ = ws->var("sigmaZ");
RooRealVar* qcdMassDecayConst = ws->var("qcdMassDecayConst");
sigmaZ->setConstant();
qcdMassDecayConst->setConstant();
RooMsgService::instance().setSilentMode(true);
// Now we use the SPlot class to add SWeights to our data set
// based on our model and our yield variables
RooStats::SPlot* sData = new RooStats::SPlot("sData","An SPlot",
*data, model, RooArgList(*zYield,*qcdYield) );
// Check that our weights have the desired properties
std::cout << "Check SWeights:" << std::endl;
std::cout << std::endl << "Yield of Z is "
<< zYield->getVal() << ". From sWeights it is "
<< sData->GetYieldFromSWeight("zYield") << std::endl;
std::cout << "Yield of QCD is "
<< qcdYield->getVal() << ". From sWeights it is "
<< sData->GetYieldFromSWeight("qcdYield") << std::endl
<< std::endl;
for(Int_t i=0; i < 10; i++)
{
std::cout << "z Weight " << sData->GetSWeight(i,"zYield")
<< " qcd Weight " << sData->GetSWeight(i,"qcdYield")
<< " Total Weight " << sData->GetSumOfEventSWeight(i)
<< std::endl;
}
std::cout << std::endl;
// import this new dataset with sWeights
std::cout << "import new dataset with sWeights" << std::endl;
ws->import(*data, Rename("dataWithSWeights"));
}
//____________________________________
void DoSPlot(RooWorkspace* ws){
std::cout << "Calculate sWeights" << std::endl;
RooAbsPdf* model = ws->pdf("model");
RooRealVar* nsig = ws->var("nsig");
RooRealVar* nBbkg = ws->var("nBbkg");
RooRealVar* nbkg = ws->var("nbkg");
RooRealVar* nbkg2 = ws->var("nbkg2");
RooDataSet* data = (RooDataSet*) ws->data("data");
// fit the model to the data.
model->fitTo(*data, Extended() );
RooMsgService::instance().setSilentMode(true);
// Now we use the SPlot class to add SWeights to our data set
// based on our model and our yield variables
RooStats::SPlot* sData = new RooStats::SPlot("sData","An SPlot",
*data, model, RooArgList(*nsig,*nBbkg,*nbkg,*nbkg2) );
// Check that our weights have the desired properties
std::cout << "Check SWeights:" << std::endl;
std::cout << std::endl << "Yield of sig is "
<< nsig->getVal() << ". From sWeights it is "
<< sData->GetYieldFromSWeight("nsig") << std::endl;
std::cout << std::endl << "Yield of Bbkg is "
<< nBbkg->getVal() << ". From sWeights it is "
<< sData->GetYieldFromSWeight("nBbkg") << std::endl;
std::cout << std::endl << "Yield of bkg is "
<< nbkg->getVal() << ". From sWeights it is "
<< sData->GetYieldFromSWeight("nbkg") << std::endl;
std::cout << std::endl << "Yield of bkg2 is "
<< nbkg2->getVal() << ". From sWeights it is "
<< sData->GetYieldFromSWeight("nbkg2") << std::endl;
cout << endl; cout << endl; cout << endl;
float sum20=0;
float sum50=0;
float sum100=0;
float sum200=0;
float sum300=0;
float sum600=0;
float sum900=0;
float sum1200=0;
float total=0;
// saving weights into a file
ofstream myfile;
myfile.open ("weights.txt");
// plot the weight event by event with the Sum of events values as cross-check
for(Int_t i=0; i < data->numEntries(); i++) {
//myfile << sData->GetSWeight(i,"nsig") << " " << sData->GetSWeight(i,"nBbkg") << " " << sData->GetSWeight(i,"nbkg") << " " << sData->GetSWeight(i,"nbkg2") << endl;
//myfile << sData->GetSWeight(i,"nsig") <<endl;
myfile << (unsigned int) data->get(i)->getRealValue("run")
<< " " << (unsigned int) data->get(i)->getRealValue("event")
<< " " << (float) data->get(i)->getRealValue("FourMu_Mass")
<< " " << sData->GetSWeight(i,"nsig")
<< endl;
// std::cout << "nsig Weight " << sData->GetSWeight(i,"nsig")
// << " nBbkg Weight " << sData->GetSWeight(i,"nBbkg")
// << " nbkg Weight " << sData->GetSWeight(i,"nbkg")
// << " nbkg2 Weight " << sData->GetSWeight(i,"nbkg2")
// << " Total Weight " << sData->GetSumOfEventSWeight(i)
// << std::endl;
total+=sData->GetSWeight(i,"nsig");
if(i<20) sum20+=sData->GetSWeight(i,"nsig");
if(i<50) sum50+=sData->GetSWeight(i,"nsig");
if(i<100) sum100+=sData->GetSWeight(i,"nsig");
if(i<200) sum200+=sData->GetSWeight(i,"nsig");
if(i<300) sum300+=sData->GetSWeight(i,"nsig");
if(i<600) sum600+=sData->GetSWeight(i,"nsig");
if(i<900) sum900+=sData->GetSWeight(i,"nsig");
if(i<1200) sum1200+=sData->GetSWeight(i,"nsig");
}
myfile.close();
std::cout << std::endl;
std::cout<<"Sum of the sWeights is: "<<total<<std::endl;
std::cout<<"Sum of the first 20 sWeights is: "<<sum20<<std::endl;
std::cout<<"Sum of the first 50 sWeights is: "<<sum50<<std::endl;
std::cout<<"Sum of the first 100 sWeights is: "<<sum100<<std::endl;
std::cout<<"Sum of the first 200 sWeights is: "<<sum200<<std::endl;
std::cout<<"Sum of the first 300 sWeights is: "<<sum300<<std::endl;
std::cout<<"Sum of the first 600 sWeights is: "<<sum600<<std::endl;
std::cout<<"Sum of the first 900 sWeights is: "<<sum900<<std::endl;
std::cout<<"Sum of the first 1200 sWeights is: "<<sum1200<<std::endl;
std::cout<<"Total # of events: "<<data->numEntries()<<std::endl;
// import this new dataset with sWeights
std::cout << "import new dataset with sWeights" << std::endl;
ws->import(*data, Rename("dataWithSWeights"));
}
//____________________________________
RooStats::SPlot* DoSPlot(RooWorkspace* ws){
//Users will have to edit this functioon to account for changes made for their own model
//This will mainly involve matching the variable names to those defined in AddModel and AddData
std::cout << "Calculate sWeights" << std::endl;
// get what we need out of the workspace to do the fit
RooAbsPdf* model = ws->pdf(pdfName);
RooDataSet* data = (RooDataSet*) ws->data(dataSetName);
// fit the model to the data.
model->fitTo(*data, Extended() );
// The sPlot technique requires that we fix the parameters
// of the model that are not yields after doing the fit.
ws->var(TString("SigMean"))->setConstant();
ws->var(TString("SigWidth"))->setConstant();
ws->var(TString("l0"))->setConstant();
ws->var(TString("l1"))->setConstant();
ws->var(TString("l2"))->setConstant();
//The only 2 free parameters will now be the signal and background yields
//Note, if we have more than 2 types of event we would need to get additional yeilds here
RooRealVar* s_Yield = ws->var(TString("SigYield"));
RooRealVar* b_Yield = ws->var(TString("BckYield"));
RooMsgService::instance().setSilentMode(true);
// Now we use the SPlot class to add SWeights to our data set
// based on our model and our yield variables
RooStats::SPlot* sData = new RooStats::SPlot(pdfName+"SW","An SPlot",
*data, model, RooArgList(*s_Yield,*b_Yield) );
//Check that our weights have the desired properties
std::cout << "Check SWeights:" << std::endl;
std::cout << std::endl << "Yield of Signal is "
<< s_Yield->getVal() << ". From sWeights it is "
<< sData->GetYieldFromSWeight(TString("SigYield")) << std::endl;
std::cout << "Yield of Background is "
<< b_Yield->getVal() << ". From sWeights it is "
<< sData->GetYieldFromSWeight(TString("BckYield")) << std::endl
<< std::endl;
for(Int_t i=0; i < 10; i++)
{
std::cout << "signal Weight " << sData->GetSWeight(i,TString("SigYield"))
<< " background Weight " << sData->GetSWeight(i,TString("BckYield"))
<< " Total Weight " << sData->GetSumOfEventSWeight(i)
<< std::endl;
}
std::cout << std::endl;
//Now plot the fit resluts for checking
//Users will have to edit this for the variables they are using
RooRealVar* vML = ws->var("Mmiss");
RooAbsPdf* b_Model = ws->pdf("BackPDF");
RooPlot* frame = vML->frame() ;
data->plotOn(frame, DataError(RooAbsData::SumW2) ) ; //plot the data
model->plotOn(frame,LineStyle(kDashed), LineColor(kRed)) ; //model = signal + back fit result
model->plotOn(frame,Components(*b_Model),LineStyle(kDashed),LineColor(kGreen)) ; //just the back fit result
model->paramOn(frame,
FillColor(kRed),
Label("Global Fit parameters:"),
Layout(0.1, 0.4, 0.9),
Format("NEU",AutoPrecision(3)),
ShowConstants());
frame->SetTitle("M#Lambda distribution fit");
frame->Draw() ;
canvas->Modified();
canvas->Update();
cin.get();//wait here until users ready to continue
//Write fit plot canvas to output file
TDirectory* savedir=gDirectory;
outPlots->cd();
canvas->SetName(pdfName);
canvas->Write();
savedir->cd();
//return the finished RooStats::sPlot object
return sData;
}