////////////////////////////////////////////////////////////////////////// // // 'MULTIDIMENSIONAL MODELS' RooFit tutorial macro #306 // // Complete example with use of conditional p.d.f. with per-event errors // // // // 07/2008 - Wouter Verkerke // ///////////////////////////////////////////////////////////////////////// #ifndef __CINT__ #include "RooGlobalFunc.h" #endif #include "RooRealVar.h" #include "RooDataSet.h" #include "RooGaussian.h" #include "RooConstVar.h" #include "RooGaussModel.h" #include "RooDecay.h" #include "RooLandau.h" #include "RooPlot.h" #include "TCanvas.h" #include "TAxis.h" #include "TH2D.h" using namespace RooFit ; void rf306_condpereventerrors() { // B - p h y s i c s p d f w i t h p e r - e v e n t G a u s s i a n r e s o l u t i o n // ---------------------------------------------------------------------------------------------- // Observables RooRealVar dt("dt","dt",-10,10) ; RooRealVar dterr("dterr","per-event error on dt",0.01,10) ; // Build a gaussian resolution model scaled by the per-event error = gauss(dt,bias,sigma*dterr) RooRealVar bias("bias","bias",0,-10,10) ; RooRealVar sigma("sigma","per-event error scale factor",1,0.1,10) ; RooGaussModel gm("gm1","gauss model scaled bt per-event error",dt,bias,sigma,dterr) ; // Construct decay(dt) (x) gauss1(dt|dterr) RooRealVar tau("tau","tau",1.548) ; RooDecay decay_gm("decay_gm","decay",dt,tau,gm,RooDecay::DoubleSided) ; // C o n s t r u c t f a k e ' e x t e r n a l ' d a t a w i t h p e r - e v e n t e r r o r // ------------------------------------------------------------------------------------------------------ // Use landau p.d.f to get somewhat realistic distribution with long tail RooLandau pdfDtErr("pdfDtErr","pdfDtErr",dterr,RooConst(1),RooConst(0.25)) ; RooDataSet* expDataDterr = pdfDtErr.generate(dterr,10000) ; // S a m p l e d a t a f r o m c o n d i t i o n a l d e c a y _ g m ( d t | d t e r r ) // --------------------------------------------------------------------------------------------- // Specify external dataset with dterr values to use decay_dm as conditional p.d.f. RooDataSet* data = decay_gm.generate(dt,ProtoData(*expDataDterr)) ; // F i t c o n d i t i o n a l d e c a y _ d m ( d t | d t e r r ) // --------------------------------------------------------------------- // Specify dterr as conditional observable decay_gm.fitTo(*data,ConditionalObservables(dterr), Verbose()) ; RooNLLVar *nll = new RooNLLVar("nll","-log(L)",decay_gm,*data, ConditionalObservables(dterr)); }