////////////////////////////////////////////////////////////////////////// // // 'DATA AND CATEGORIES' RooFit tutorial macro #402 // // Tools for manipulation of (un)binned datasets // // // // 07/2008 - Wouter Verkerke // ///////////////////////////////////////////////////////////////////////// #ifndef __CINT__ #include "RooGlobalFunc.h" #endif #include "RooRealVar.h" #include "RooDataSet.h" #include "RooDataHist.h" #include "RooGaussian.h" #include "RooConstVar.h" #include "RooCategory.h" #include "TCanvas.h" #include "TAxis.h" #include "RooPlot.h" #include "TFile.h" using namespace RooFit ; // WVE Add reduction by range void rf402_datahandling() { // Binned (RooDataHist) and unbinned datasets (RooDataSet) share // many properties and inherit from a common abstract base class // (RooAbsData), that provides an interface for all operations // that can be performed regardless of the data format RooRealVar x("x","x",-10,10) ; RooRealVar y("y","y", 0, 40) ; RooCategory c("c","c") ; c.defineType("Plus",+1) ; c.defineType("Minus",-1) ; // B a s i c O p e r a t i o n s o n u n b i n n e d d a t a s e t s // -------------------------------------------------------------- // RooDataSet is an unbinned dataset (a collection of points in N-dimensional space) RooDataSet d("d","d",RooArgSet(x,y,c)) ; // Unlike RooAbsArgs (RooAbsPdf,RooFormulaVar,....) datasets are not attached to // the variables they are constructed from. Instead they are attached to an internal // clone of the supplied set of arguments // Fill d with dummy values Int_t i ; for (i=0 ; i<1000 ; i++) { x = i/50 - 10 ; y = sqrt(1.0*i) ; c.setLabel((i%2)?"Plus":"Minus") ; // We must explicitly refer to x,y,c here to pass the values because // d is not linked to them (as explained above) d.add(RooArgSet(x,y,c)) ; } d.Print("v") ; cout << endl ; // The get() function returns a pointer to the internal copy of the RooArgSet(x,y,c) // supplied in the constructor const RooArgSet* row = d.get() ; row->Print("v") ; cout << endl ; // Get with an argument loads a specific data point in row and returns // a pointer to row argset. get() always returns the same pointer, unless // an invalid row number is specified. In that case a null ptr is returned d.get(900)->Print("v") ; cout << endl ; // R e d u c i n g , A p p e n d i n g a n d M e r g i n g // ------------------------------------------------------------- // The reduce() function returns a new dataset which is a subset of the original cout << endl << ">> d1 has only columns x,c" << endl ; RooDataSet* d1 = (RooDataSet*) d.reduce(RooArgSet(x,c)) ; d1->Print("v") ; cout << endl << ">> d2 has only column y" << endl ; RooDataSet* d2 = (RooDataSet*) d.reduce(RooArgSet(y)) ; d2->Print("v") ; cout << endl << ">> d3 has only the points with y>5.17" << endl ; RooDataSet* d3 = (RooDataSet*) d.reduce("y>5.17") ; d3->Print("v") ; cout << endl << ">> d4 has only columns x,c for data points with y>5.17" << endl ; RooDataSet* d4 = (RooDataSet*) d.reduce(RooArgSet(x,c),"y>5.17") ; d4->Print("v") ; // The merge() function adds two data set column-wise cout << endl << ">> merge d2(y) with d1(x,c) to form d1(x,c,y)" << endl ; d1->merge(d2) ; d1->Print("v") ; // The append() function addes two datasets row-wise cout << endl << ">> append data points of d3 to d1" << endl ; d1->append(*d3) ; d1->Print("v") ; // O p e r a t i o n s o n b i n n e d d a t a s e t s // --------------------------------------------------------- // A binned dataset can be constructed empty, from an unbinned dataset, or // from a ROOT native histogram (TH1,2,3) cout << ">> construct dh (binned) from d(unbinned) but only take the x and y dimensions," << endl << ">> the category 'c' will be projected in the filling process" << endl ; // The binning of real variables (like x,y) is done using their fit range // 'get/setRange()' and number of specified fit bins 'get/setBins()'. // Category dimensions of binned datasets get one bin per defined category state x.setBins(10) ; y.setBins(10) ; RooDataHist dh("dh","binned version of d",RooArgSet(x,y),d) ; dh.Print("v") ; RooPlot* yframe = y.frame(Bins(10),Title("Operations on binned datasets")) ; dh.plotOn(yframe) ; // plot projection of 2D binned data on y // Examine the statistics of a binned dataset cout << ">> number of bins in dh : " << dh.numEntries() << endl ; cout << ">> sum of weights in dh : " << dh.sum(kFALSE) << endl ; cout << ">> integral over histogram: " << dh.sum(kTRUE) << endl ; // accounts for bin volume // Locate a bin from a set of coordinates and retrieve its properties x = 0.3 ; y = 20.5 ; cout << ">> retrieving the properties of the bin enclosing coordinate (x,y) = (0.3,20.5) " << endl ; cout << " bin center:" << endl ; dh.get(RooArgSet(x,y))->Print("v") ; // load bin center coordinates in internal buffer cout << " weight = " << dh.weight() << endl ; // return weight of last loaded coordinates // Reduce the 2-dimensional binned dataset to a 1-dimensional binned dataset // // All reduce() methods are interfaced in RooAbsData. All reduction techniques // demonstrated on unbinned datasets can be applied to binned datasets as well. cout << ">> Creating 1-dimensional projection on y of dh for bins with x>0" << endl ; RooDataHist* dh2 = (RooDataHist*) dh.reduce(y,"x>0") ; dh2->Print("v") ; // Add dh2 to yframe and redraw dh2->plotOn(yframe,LineColor(kRed),MarkerColor(kRed)) ; // S a v i n g a n d l o a d i n g f r o m f i l e // ------------------------------------------------------- // Datasets can be persisted with ROOT I/O cout << endl << ">> Persisting d via ROOT I/O" << endl ; TFile f("rf402_datahandling.root","RECREATE") ; d.Write() ; f.ls() ; // To read back in future session: // > TFile f("rf402_datahandling.root") ; // > RooDataSet* d = (RooDataSet*) f.FindObject("d") ; new TCanvas("rf402_datahandling","rf402_datahandling",600,600) ; gPad->SetLeftMargin(0.15) ; yframe->GetYaxis()->SetTitleOffset(1.4) ; yframe->Draw() ; }