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Reference Guide
rf102_dataimport.C
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1 /// \file
2 /// \ingroup tutorial_roofit
3 /// \notebook -js
4 /// \brief Basic functionality: importing data from ROOT TTrees and THx histograms.
5 ///
6 /// \macro_image
7 /// \macro_output
8 /// \macro_code
9 ///
10 /// \date 07/2008
11 /// \author Wouter Verkerke
12 
13 #include "RooRealVar.h"
14 #include "RooDataSet.h"
15 #include "RooDataHist.h"
16 #include "RooGaussian.h"
17 #include "TCanvas.h"
18 #include "RooPlot.h"
19 #include "TTree.h"
20 #include "TH1D.h"
21 #include "TRandom.h"
22 using namespace RooFit;
23 
24 TH1 *makeTH1();
25 TTree *makeTTree();
26 
27 void rf102_dataimport()
28 {
29  // ---------------------------------------------------
30  // I m p o r t i n g R O O T h i s t o g r a m s
31  // ===================================================
32 
33  // I m p o r t T H 1 i n t o a R o o D a t a H i s t
34  // ---------------------------------------------------------
35 
36  // Create a ROOT TH1 histogram
37  TH1 *hh = makeTH1();
38 
39  // Declare observable x
40  RooRealVar x("x", "x", -10, 10);
41 
42  // Create a binned dataset that imports contents of TH1 and associates its contents to observable 'x'
43  RooDataHist dh("dh", "dh", x, Import(*hh));
44 
45  // P l o t a n d f i t a R o o D a t a H i s t
46  // ---------------------------------------------------
47 
48  // Make plot of binned dataset showing Poisson error bars (RooFit default)
49  RooPlot *frame = x.frame(Title("Imported TH1 with Poisson error bars"));
50  dh.plotOn(frame);
51 
52  // Fit a Gaussian p.d.f to the data
53  RooRealVar mean("mean", "mean", 0, -10, 10);
54  RooRealVar sigma("sigma", "sigma", 3, 0.1, 10);
55  RooGaussian gauss("gauss", "gauss", x, mean, sigma);
56  gauss.fitTo(dh);
57  gauss.plotOn(frame);
58 
59  // P l o t a n d f i t a R o o D a t a H i s t w i t h i n t e r n a l e r r o r s
60  // ---------------------------------------------------------------------------------------------
61 
62  // If histogram has custom error (i.e. its contents is does not originate from a Poisson process
63  // but e.g. is a sum of weighted events) you can data with symmetric 'sum-of-weights' error instead
64  // (same error bars as shown by ROOT)
65  RooPlot *frame2 = x.frame(Title("Imported TH1 with internal errors"));
66  dh.plotOn(frame2, DataError(RooAbsData::SumW2));
67  gauss.plotOn(frame2);
68 
69  // Please note that error bars shown (Poisson or SumW2) are for visualization only, the are NOT used
70  // in a maximum likelihood fit
71  //
72  // A (binned) ML fit will ALWAYS assume the Poisson error interpretation of data (the mathematical definition
73  // of likelihood does not take any external definition of errors). Data with non-unit weights can only be correctly
74  // fitted with a chi^2 fit (see rf602_chi2fit.C)
75 
76  // -----------------------------------------
77  // I m p o r t i n g R O O T T T r e e s
78  // =========================================
79 
80  // I m p o r t T T r e e i n t o a R o o D a t a S e t
81  // -----------------------------------------------------------
82 
83  TTree *tree = makeTTree();
84 
85  // Define 2nd observable y
86  RooRealVar y("y", "y", -10, 10);
87 
88  // Construct unbinned dataset importing tree branches x and y matching between branches and RooRealVars
89  // is done by name of the branch/RRV
90  //
91  // Note that ONLY entries for which x,y have values within their allowed ranges as defined in
92  // RooRealVar x and y are imported. Since the y values in the import tree are in the range [-15,15]
93  // and RRV y defines a range [-10,10] this means that the RooDataSet below will have less entries than the TTree
94  // 'tree'
95 
96  RooDataSet ds("ds", "ds", RooArgSet(x, y), Import(*tree));
97 
98  // U s e a s c i i i m p o r t / e x p o r t f o r d a t a s e t s
99  // ------------------------------------------------------------------------------------
100  {
101  // Write data to output stream
102  std::ofstream outstream("rf102_testData.txt");
103  // Optionally, adjust the stream here (e.g. std::setprecision)
104  ds.write(outstream);
105  outstream.close();
106  }
107 
108  // Read data from input stream. The variables of the dataset need to be supplied
109  // to the RooDataSet::read() function.
110  std::cout << "\n-----------------------\nReading data from ASCII\n";
111  RooDataSet *dataReadBack =
112  RooDataSet::read("rf102_testData.txt",
113  RooArgList(x, y), // variables to be read. If the file has more fields, these are ignored.
114  "D"); // Prints if a RooFit message stream listens for debug messages. Use Q for quiet.
115 
116  dataReadBack->Print("V");
117 
118  std::cout << "\nOriginal data, line 20:\n";
119  ds.get(20)->Print("V");
120 
121  std::cout << "\nRead-back data, line 20:\n";
122  dataReadBack->get(20)->Print("V");
123 
124  // P l o t d a t a s e t s w i t h m u l t i p l e b i n n i n g c h o i c e s
125  // ------------------------------------------------------------------------------------
126 
127  // Print number of events in dataset
128  ds.Print();
129 
130  // Print unbinned dataset with default frame binning (100 bins)
131  RooPlot *frame3 = y.frame(Title("Unbinned data shown in default frame binning"));
132  ds.plotOn(frame3);
133 
134  // Print unbinned dataset with custom binning choice (20 bins)
135  RooPlot *frame4 = y.frame(Title("Unbinned data shown with custom binning"));
136  ds.plotOn(frame4, Binning(20));
137 
138  RooPlot *frame5 = y.frame(Title("Unbinned data read back from ASCII file"));
139  ds.plotOn(frame5, Binning(20));
140  dataReadBack->plotOn(frame5, Binning(20), MarkerColor(kRed), MarkerStyle(5));
141 
142  // Draw all frames on a canvas
143  TCanvas *c = new TCanvas("rf102_dataimport", "rf102_dataimport", 1000, 800);
144  c->Divide(3, 2);
145  c->cd(1);
146  gPad->SetLeftMargin(0.15);
147  frame->GetYaxis()->SetTitleOffset(1.4);
148  frame->Draw();
149  c->cd(2);
150  gPad->SetLeftMargin(0.15);
151  frame2->GetYaxis()->SetTitleOffset(1.4);
152  frame2->Draw();
153 
154  c->cd(4);
155  gPad->SetLeftMargin(0.15);
156  frame3->GetYaxis()->SetTitleOffset(1.4);
157  frame3->Draw();
158  c->cd(5);
159  gPad->SetLeftMargin(0.15);
160  frame4->GetYaxis()->SetTitleOffset(1.4);
161  frame4->Draw();
162  c->cd(6);
163  gPad->SetLeftMargin(0.15);
164  frame4->GetYaxis()->SetTitleOffset(1.4);
165  frame5->Draw();
166 }
167 
168 // Create ROOT TH1 filled with a Gaussian distribution
169 TH1 *makeTH1()
170 {
171  TH1D *hh = new TH1D("hh", "hh", 25, -10, 10);
172  for (int i = 0; i < 100; i++) {
173  hh->Fill(gRandom->Gaus(0, 3));
174  }
175  return hh;
176 }
177 
178 // Create ROOT TTree filled with a Gaussian distribution in x and a uniform distribution in y
179 TTree *makeTTree()
180 {
181  TTree *tree = new TTree("tree", "tree");
182  Double_t *px = new Double_t;
183  Double_t *py = new Double_t;
184  tree->Branch("x", px, "x/D");
185  tree->Branch("y", py, "y/D");
186  for (int i = 0; i < 100; i++) {
187  *px = gRandom->Gaus(0, 3);
188  *py = gRandom->Uniform() * 30 - 15;
189  tree->Fill();
190  }
191  return tree;
192 }
c
#define c(i)
Definition: RSha256.hxx:101
RooPlot::Draw
virtual void Draw(Option_t *options=0)
Draw this plot and all of the elements it contains.
Definition: RooPlot.cxx:691
TRandom::Gaus
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:263
RooAbsData::SumW2
@ SumW2
Definition: RooAbsData.h:96
RooFit::DataError
RooCmdArg DataError(Int_t)
Definition: RooGlobalFunc.cxx:156
tree
Definition: tree.py:1
RooArgList
RooArgList is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgList.h:21
TTree
A TTree represents a columnar dataset.
Definition: TTree.h:79
RooGaussian.h
TH1D
1-D histogram with a double per channel (see TH1 documentation)}
Definition: TH1.h:616
extract_docstrings.ds
ds
Definition: extract_docstrings.py:40
RooFit::MarkerStyle
RooCmdArg MarkerStyle(Style_t style)
Definition: RooGlobalFunc.cxx:85
TRandom.h
TRandom::Uniform
virtual Double_t Uniform(Double_t x1=1)
Returns a uniform deviate on the interval (0, x1).
Definition: TRandom.cxx:635
RooAbsData::Print
virtual void Print(Option_t *options=0) const
Print TNamed name and title.
Definition: RooAbsData.h:182
x
Double_t x[n]
Definition: legend1.C:17
RooGaussian
Plain Gaussian p.d.f.
Definition: RooGaussian.h:25
TCanvas.h
TTree.h
RooFit::Binning
RooCmdArg Binning(const RooAbsBinning &binning)
Definition: RooGlobalFunc.cxx:82
RooDataSet.h
RooDataSet::get
virtual const RooArgSet * get(Int_t index) const override
Return RooArgSet with coordinates of event 'index'.
Definition: RooDataSet.cxx:1038
RooDataHist
The RooDataHist is a container class to hold N-dimensional binned data.
Definition: RooDataHist.h:39
TGeant4Unit::gauss
static constexpr double gauss
Definition: TGeant4SystemOfUnits.h:263
RooFit
The namespace RooFit contains mostly switches that change the behaviour of functions of PDFs (or othe...
Definition: RooCFunction1Binding.h:29
RooAbsData::plotOn
virtual RooPlot * plotOn(RooPlot *frame, const RooCmdArg &arg1=RooCmdArg::none(), const RooCmdArg &arg2=RooCmdArg::none(), const RooCmdArg &arg3=RooCmdArg::none(), const RooCmdArg &arg4=RooCmdArg::none(), const RooCmdArg &arg5=RooCmdArg::none(), const RooCmdArg &arg6=RooCmdArg::none(), const RooCmdArg &arg7=RooCmdArg::none(), const RooCmdArg &arg8=RooCmdArg::none()) const
Definition: RooAbsData.cxx:547
RooDataHist.h
RooPlot.h
RooPlot::GetYaxis
TAxis * GetYaxis() const
Definition: RooPlot.cxx:1258
TH1::Fill
virtual Int_t Fill(Double_t x)
Increment bin with abscissa X by 1.
Definition: TH1.cxx:3327
gRandom
R__EXTERN TRandom * gRandom
Definition: TRandom.h:62
RooPlot
A RooPlot is a plot frame and a container for graphics objects within that frame.
Definition: RooPlot.h:44
y
Double_t y[n]
Definition: legend1.C:17
RooRealVar.h
kRed
@ kRed
Definition: Rtypes.h:66
RooDataSet::read
static RooDataSet * read(const char *filename, const RooArgList &variables, const char *opts="", const char *commonPath="", const char *indexCatName=0)
Read given list of ascii files, and construct a data set, using the given ArgList as structure defini...
Definition: RooDataSet.cxx:1710
sigma
const Double_t sigma
Definition: h1analysisProxy.h:11
Double_t
double Double_t
Definition: RtypesCore.h:59
TCanvas
The Canvas class.
Definition: TCanvas.h:23
TH1
TH1 is the base class of all histogramm classes in ROOT.
Definition: TH1.h:58
gPad
#define gPad
Definition: TVirtualPad.h:287
RooDataSet
RooDataSet is a container class to hold unbinned data.
Definition: RooDataSet.h:33
RooFit::MarkerColor
RooCmdArg MarkerColor(Color_t color)
Definition: RooGlobalFunc.cxx:87
RooAbsCollection::Print
virtual void Print(Option_t *options=0) const
This method must be overridden when a class wants to print itself.
Definition: RooAbsCollection.h:199
TAttAxis::SetTitleOffset
virtual void SetTitleOffset(Float_t offset=1)
Set distance between the axis and the axis title.
Definition: TAttAxis.cxx:293
RooRealVar
RooRealVar represents a variable that can be changed from the outside.
Definition: RooRealVar.h:36
TH1D.h
RooFit::Title
RooCmdArg Title(const char *name)
Definition: RooGlobalFunc.cxx:173
RooArgSet
RooArgSet is a container object that can hold multiple RooAbsArg objects.
Definition: RooArgSet.h:28
RooFit::Import
RooCmdArg Import(const char *state, TH1 &histo)
Definition: RooGlobalFunc.cxx:98