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Reference Guide
rf401_importttreethx.C File Reference

Detailed Description

View in nbviewer Open in SWAN 'DATA AND CATEGORIES' RooFit tutorial macro #401

Overview of advanced option for importing data from ROOT TTree and THx histograms Basic import options are demonstrated in rf102_dataimport.C

␛[1mRooFit v3.60 -- Developed by Wouter Verkerke and David Kirkby␛[0m
Copyright (C) 2000-2013 NIKHEF, University of California & Stanford University
All rights reserved, please read http://roofit.sourceforge.net/license.txt
RooDataHist::dh[c,x] = 300 bins (2964 weights)
RooDataHist::dh[c,x] = 300 bins (2964 weights)
[#1] INFO:Eval -- RooTreeDataStore::loadValues(ds) Ignored 35 out of range events
RooDataSet::ds[x,y] = 65 entries
[#1] INFO:Eval -- RooTreeDataStore::loadValues(ds2) Ignored 36 out of range events
RooDataSet::ds2[x,y,z] = 26 entries
[#1] INFO:Eval -- RooAbsReal::attachToTree(i) TTree Int_t branch i will be converted to double precision
RooDataSet::ds3[i,x] = 100 entries
[#1] INFO:DataHandling -- RooAbsCategory::attachToTree(i) TTree branch i will be interpreted as category index
[#1] INFO:Eval -- RooTreeDataStore::loadValues(ds4) Ignored 33 out of range events
RooDataSet::ds4[i,x] = 67 entries
RooDataSet::dsABC[c,x,y] = 26 entries
#include "RooRealVar.h"
#include "RooDataSet.h"
#include "RooDataHist.h"
#include "RooCategory.h"
#include "RooGaussian.h"
#include "RooConstVar.h"
#include "TCanvas.h"
#include "TAxis.h"
#include "RooPlot.h"
#include "TH1.h"
#include "TTree.h"
#include "TRandom.h"
#include <map>
using namespace RooFit ;
TH1* makeTH1(const char* name, Double_t mean, Double_t sigma) ;
TTree* makeTTree() ;
void rf401_importttreethx()
{
// I m p o r t m u l t i p l e T H 1 i n t o a R o o D a t a H i s t
// --------------------------------------------------------------------------
// Create thee ROOT TH1 histograms
TH1* hh_1 = makeTH1("hh1",0,3) ;
TH1* hh_2 = makeTH1("hh2",-3,1) ;
TH1* hh_3 = makeTH1("hh3",+3,4) ;
// Declare observable x
RooRealVar x("x","x",-10,10) ;
// Create category observable c that serves as index for the ROOT histograms
RooCategory c("c","c") ;
c.defineType("SampleA") ;
c.defineType("SampleB") ;
c.defineType("SampleC") ;
// Create a binned dataset that imports contents of all TH1 mapped by index category c
RooDataHist* dh = new RooDataHist("dh","dh",x,Index(c),Import("SampleA",*hh_1),Import("SampleB",*hh_2),Import("SampleC",*hh_3)) ;
dh->Print() ;
// Alternative constructor form for importing multiple histograms
map<string,TH1*> hmap ;
hmap["SampleA"] = hh_1 ;
hmap["SampleB"] = hh_2 ;
hmap["SampleC"] = hh_3 ;
RooDataHist* dh2 = new RooDataHist("dh","dh",x,c,hmap) ;
dh2->Print() ;
// I m p o r t i n g a T T r e e i n t o a R o o D a t a S e t w i t h c u t s
// -----------------------------------------------------------------------------------------
TTree* tree = makeTTree() ;
// Define observables y,z
RooRealVar y("y","y",-10,10) ;
RooRealVar z("z","z",-10,10) ;
// Import only observables (y,z)
RooDataSet ds("ds","ds",RooArgSet(x,y),Import(*tree)) ;
ds.Print() ;
// Import observables (x,y,z) but only event for which (y+z<0) is true
RooDataSet ds2("ds2","ds2",RooArgSet(x,y,z),Import(*tree),Cut("y+z<0")) ;
ds2.Print() ;
// I m p o r t i n g i n t e g e r T T r e e b r a n c h e s
// ---------------------------------------------------------------
// Import integer tree branch as RooRealVar
RooRealVar i("i","i",0,5) ;
RooDataSet ds3("ds3","ds3",RooArgSet(i,x),Import(*tree)) ;
ds3.Print() ;
// Define category i
RooCategory icat("i","i") ;
icat.defineType("State0",0) ;
icat.defineType("State1",1) ;
// Import integer tree branch as RooCategory (only events with i==0 and i==1
// will be imported as those are the only defined states)
RooDataSet ds4("ds4","ds4",RooArgSet(icat,x),Import(*tree)) ;
ds4.Print() ;
// I m p o r t m u l t i p l e R o o D a t a S e t s i n t o a R o o D a t a S e t
// ----------------------------------------------------------------------------------------
// Create three RooDataSets in (y,z)
RooDataSet* dsA = (RooDataSet*) ds2.reduce(RooArgSet(x,y),"z<-5") ;
RooDataSet* dsB = (RooDataSet*) ds2.reduce(RooArgSet(x,y),"abs(z)<5") ;
RooDataSet* dsC = (RooDataSet*) ds2.reduce(RooArgSet(x,y),"z>5") ;
// Create a dataset that imports contents of all the above datasets mapped by index category c
RooDataSet* dsABC = new RooDataSet("dsABC","dsABC",RooArgSet(x,y),Index(c),Import("SampleA",*dsA),Import("SampleB",*dsB),Import("SampleC",*dsC)) ;
dsABC->Print() ;
}
TH1* makeTH1(const char* name, Double_t mean, Double_t sigma)
{
// Create ROOT TH1 filled with a Gaussian distribution
TH1D* hh = new TH1D(name,name,100,-10,10) ;
for (int i=0 ; i<1000 ; i++) {
hh->Fill(gRandom->Gaus(mean,sigma)) ;
}
return hh ;
}
TTree* makeTTree()
{
// Create ROOT TTree filled with a Gaussian distribution in x and a uniform distribution in y
TTree* tree = new TTree("tree","tree") ;
Double_t* px = new Double_t ;
Double_t* py = new Double_t ;
Double_t* pz = new Double_t ;
Int_t* pi = new Int_t ;
tree->Branch("x",px,"x/D") ;
tree->Branch("y",py,"y/D") ;
tree->Branch("z",pz,"z/D") ;
tree->Branch("i",pi,"i/I") ;
for (int i=0 ; i<100 ; i++) {
*px = gRandom->Gaus(0,3) ;
*py = gRandom->Uniform()*30 - 15 ;
*pz = gRandom->Gaus(0,5) ;
*pi = i % 3 ;
tree->Fill() ;
}
return tree ;
}
#define c(i)
Definition: RSha256.hxx:101
int Int_t
Definition: RtypesCore.h:41
double Double_t
Definition: RtypesCore.h:55
R__EXTERN TRandom * gRandom
Definition: TRandom.h:62
RooAbsData * reduce(const RooCmdArg &arg1, const RooCmdArg &arg2=RooCmdArg(), const RooCmdArg &arg3=RooCmdArg(), const RooCmdArg &arg4=RooCmdArg(), const RooCmdArg &arg5=RooCmdArg(), const RooCmdArg &arg6=RooCmdArg(), const RooCmdArg &arg7=RooCmdArg(), const RooCmdArg &arg8=RooCmdArg())
Create a reduced copy of this dataset.
Definition: RooAbsData.cxx:360
virtual void Print(Option_t *options=0) const
Print TNamed name and title.
Definition: RooAbsData.h:161
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgSet.h:28
RooCategory represents a fundamental (non-derived) discrete value object.
Definition: RooCategory.h:24
RooDataSet is a container class to hold N-dimensional binned data.
Definition: RooDataHist.h:40
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:31
RooRealVar represents a fundamental (non-derived) real valued object.
Definition: RooRealVar.h:36
1-D histogram with a double per channel (see TH1 documentation)}
Definition: TH1.h:614
The TH1 histogram class.
Definition: TH1.h:56
virtual Int_t Fill(Double_t x)
Increment bin with abscissa X by 1.
Definition: TH1.cxx:3251
virtual Double_t Gaus(Double_t mean=0, Double_t sigma=1)
Samples a random number from the standard Normal (Gaussian) Distribution with the given mean and sigm...
Definition: TRandom.cxx:256
virtual Double_t Uniform(Double_t x1=1)
Returns a uniform deviate on the interval (0, x1).
Definition: TRandom.cxx:627
A TTree object has a header with a name and a title.
Definition: TTree.h:71
const Double_t sigma
Double_t y[n]
Definition: legend1.C:17
Double_t x[n]
Definition: legend1.C:17
RooCmdArg Index(RooCategory &icat)
RooCmdArg Import(const char *state, TH1 &histo)
RooCmdArg Cut(const char *cutSpec)
static constexpr double pi
Definition: tree.py:1
Author
07/2008 - Wouter Verkerke

Definition in file rf401_importttreethx.C.