'DATA AND CATEGORIES' RooFit tutorial macro #406
Demonstration of discrete-->discrete (invertable) functions
␛[1mRooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby␛[0m
Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University
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RooCategory::tagCat = Lepton(idx = 0)
RooCategory::b0flav = B0(idx = -1)
Table tcatType : pData
+----------------+------+
| Cut based | 5040 |
| Neural Network | 4960 |
+----------------+------+
Table b0Xtcat : pData
+---------------------+------+
| {B0;Lepton} | 1302 |
| {B0bar;Lepton} | 1192 |
| {B0;Kaon} | 1232 |
| {B0bar;Kaon} | 1314 |
| {B0;NetTagger-1} | 1242 |
| {B0bar;NetTagger-1} | 1208 |
| {B0;NetTagger-2} | 1282 |
| {B0bar;NetTagger-2} | 1228 |
+---------------------+------+
Table b0Xttype : pData
+------------------------+------+
| {B0;Cut based} | 2534 |
| {B0bar;Cut based} | 2506 |
| {B0;Neural Network} | 2524 |
| {B0bar;Neural Network} | 2436 |
+------------------------+------+
{
tagCat.defineType("Lepton") ;
tagCat.defineType("Kaon") ;
tagCat.defineType("NetTagger-1") ;
tagCat.defineType("NetTagger-2") ;
tagCat.Print() ;
b0flav.defineType("B0",-1) ;
b0flav.defineType("B0bar",1) ;
b0flav.Print() ;
tcatType.map("Lepton","Cut based") ;
tcatType.map("Kaon","Cut based") ;
tcatType.map("NetTagger*","Neural Network") ;
b0Xtcat.setLabel("{B0bar;Lepton}") ;
}
Roo1DTable implements a one-dimensional table.
virtual void Print(Option_t *options=0) const
Print TNamed name and title.
RooArgSet is a container object that can hold multiple RooAbsArg objects.
RooCategory represents a fundamental (non-derived) discrete value object.
RooDataSet is a container class to hold unbinned data.
RooMultiCategory consolidates several RooAbsCategory objects into a single category.
RooPolynomial implements a polynomial p.d.f of the form.
RooRealVar represents a fundamental (non-derived) real valued object.
RooSuperCategory consolidates several RooAbsCategoryLValue objects into a single category.
- Author
- 07/2008 - Wouter Verkerke
Definition in file rf406_cattocatfuncs.C.