///////////////////////////////////////////////////////////////////////// // // 'MULTIDIMENSIONAL MODELS' RooFit tutorial macro #305 // // Multi-dimensional p.d.f.s with conditional p.d.fs in product // // pdf = gauss(x,f(y),sx | y ) * gauss(y,ms,sx) with f(y) = a0 + a1*y // // // 07/2008 - Wouter Verkerke // ///////////////////////////////////////////////////////////////////////// #ifndef __CINT__ #include "RooGlobalFunc.h" #endif #include "RooRealVar.h" #include "RooDataSet.h" #include "RooGaussian.h" #include "RooConstVar.h" #include "RooPolyVar.h" #include "RooProdPdf.h" #include "RooPlot.h" #include "TCanvas.h" #include "TAxis.h" #include "TH1.h" using namespace RooFit ; void rf305_condcorrprod() { // C r e a t e c o n d i t i o n a l p d f g x ( x | y ) // ----------------------------------------------------------- // Create observables RooRealVar x("x","x",-5,5) ; RooRealVar y("y","y",-5,5) ; // Create function f(y) = a0 + a1*y RooRealVar a0("a0","a0",-0.5,-5,5) ; RooRealVar a1("a1","a1",-0.5,-1,1) ; RooPolyVar fy("fy","fy",y,RooArgSet(a0,a1)) ; // Create gaussx(x,f(y),sx) RooRealVar sigmax("sigma","width of gaussian",0.5) ; RooGaussian gaussx("gaussx","Gaussian in x with shifting mean in y",x,fy,sigmax) ; // C r e a t e p d f g y ( y ) // ----------------------------------------------------------- // Create gaussy(y,0,5) RooGaussian gaussy("gaussy","Gaussian in y",y,RooConst(0),RooConst(3)) ; // C r e a t e p r o d u c t g x ( x | y ) * g y ( y ) // ------------------------------------------------------- // Create gaussx(x,sx|y) * gaussy(y) RooProdPdf model("model","gaussx(x|y)*gaussy(y)",gaussy,Conditional(gaussx,x)) ; // S a m p l e , f i t a n d p l o t p r o d u c t p d f // --------------------------------------------------------------- // Generate 1000 events in x and y from model RooDataSet *data = model.generate(RooArgSet(x,y),10000) ; // Plot x distribution of data and projection of model on x = Int(dy) model(x,y) RooPlot* xframe = x.frame() ; data->plotOn(xframe) ; model.plotOn(xframe) ; // Plot x distribution of data and projection of model on y = Int(dx) model(x,y) RooPlot* yframe = y.frame() ; data->plotOn(yframe) ; model.plotOn(yframe) ; // Make two-dimensional plot in x vs y TH1* hh_model = model.createHistogram("hh_model",x,Binning(50),YVar(y,Binning(50))) ; hh_model->SetLineColor(kBlue) ; // Make canvas and draw RooPlots TCanvas *c = new TCanvas("rf305_condcorrprod","rf05_condcorrprod",1200, 400); c->Divide(3); c->cd(1) ; gPad->SetLeftMargin(0.15) ; xframe->GetYaxis()->SetTitleOffset(1.6) ; xframe->Draw() ; c->cd(2) ; gPad->SetLeftMargin(0.15) ; yframe->GetYaxis()->SetTitleOffset(1.6) ; yframe->Draw() ; c->cd(3) ; gPad->SetLeftMargin(0.20) ; hh_model->GetZaxis()->SetTitleOffset(2.5) ; hh_model->Draw("surf") ; }