Logo ROOT  
Reference Guide
tree0.C
Go to the documentation of this file.
1/// \file
2/// \ingroup tutorial_tree
3/// \notebook -nodraw
4/// Simple Event class example
5///
6/// execute as: .x tree0.C++
7///
8/// You have to copy it first to a directory where you have write access!
9/// Note that .x tree0.C cannot work with this example
10///
11/// ### Effect of ClassDef() and ClassImp() macros
12///
13/// After running this macro create an instance of Det and Event
14///
15/// ~~~
16/// Det d;
17/// Event e;
18/// ~~~
19///
20/// now you can see the effect of the ClassDef() and ClassImp() macros.
21/// (for the Det class these commands are commented!)
22/// For instance 'e' now knows who it is:
23///
24/// ~~~
25/// cout<<e.Class_Name()<<endl;
26/// ~~~
27///
28/// whereas d does not.
29///
30/// The methods that are added by the ClassDef()/Imp() macro can be listed with
31///
32/// ~~~
33/// .class
34/// .class Event
35/// .class Det
36/// ~~~
37///
38/// \macro_code
39///
40/// \author Heiko.Scheit@mpi-hd.mpg.de
41
42#include <TRandom.h>
43#include <TTree.h>
44#include <TCanvas.h>
45#include <TStyle.h>
46
47#include <Riostream.h>
48
49//class Det : public TObject {
50class Det { // each detector gives an energy and time signal
51public:
52 Double_t e; //energy
53 Double_t t; //time
54
55// ClassDef(Det,1)
56};
57
58//ClassImp(Det)
59
60//class Event { //TObject is not required by this example
61class Event : public TObject {
62public:
63
64 Det a; // say there are two detectors (a and b) in the experiment
65 Det b;
67};
68
70
71void tree0() {
72 // create a TTree
73 TTree *tree = new TTree("tree","treelibrated tree");
74 Event *e = new Event;
75
76 // create a branch with energy
77 tree->Branch("event",&e);
78
79 // fill some events with random numbers
80 Int_t nevent=10000;
81 for (Int_t iev=0;iev<nevent;iev++) {
82 if (iev%1000==0) cout<<"Processing event "<<iev<<"..."<<endl;
83
84 Float_t ea,eb;
85 gRandom->Rannor(ea,eb); // the two energies follow a gaus distribution
86 e->a.e=ea;
87 e->b.e=eb;
88 e->a.t=gRandom->Rndm(); // random
89 e->b.t=e->a.t + gRandom->Gaus(0.,.1); // identical to a.t but a gaussian
90 // 'resolution' was added with sigma .1
91
92 tree->Fill(); // fill the tree with the current event
93 }
94
95 // start the viewer
96 // here you can investigate the structure of your Event class
97 tree->StartViewer();
98
99 //gROOT->SetStyle("Plain"); // uncomment to set a different style
100
101 // now draw some tree variables
102 TCanvas *c1 = new TCanvas();
103 c1->Divide(2,2);
104 c1->cd(1);
105 tree->Draw("a.e"); //energy of det a
106 tree->Draw("a.e","3*(-.2<b.e && b.e<.2)","same"); // same but with condition on energy b; scaled by 3
107 c1->cd(2);
108 tree->Draw("b.e:a.e","","colz"); // one energy against the other
109 c1->cd(3);
110 tree->Draw("b.t","","e"); // time of b with errorbars
111 tree->Draw("a.t","","same"); // overlay time of detector a
112 c1->cd(4);
113 tree->Draw("b.t:a.t"); // plot time b again time a
114
115 cout<<endl;
116 cout<<"You can now examine the structure of your tree in the TreeViewer"<<endl;
117 cout<<endl;
118}
119
#define e(i)
Definition: RSha256.hxx:103
int Int_t
Definition: RtypesCore.h:45
float Float_t
Definition: RtypesCore.h:57
double Double_t
Definition: RtypesCore.h:59
#define ClassDef(name, id)
Definition: Rtypes.h:335
#define ClassImp(name)
Definition: Rtypes.h:375
Option_t Option_t TPoint TPoint const char GetTextMagnitude GetFillStyle GetLineColor GetLineWidth GetMarkerStyle GetTextAlign GetTextColor GetTextSize void char Point_t Rectangle_t WindowAttributes_t Float_t Float_t Float_t b
R__EXTERN TRandom * gRandom
Definition: TRandom.h:62
The Canvas class.
Definition: TCanvas.h:23
Mother of all ROOT objects.
Definition: TObject.h:41
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:274
Double_t Rndm() override
Machine independent random number generator.
Definition: TRandom.cxx:552
virtual void Rannor(Float_t &a, Float_t &b)
Return 2 numbers distributed following a gaussian with mean=0 and sigma=1.
Definition: TRandom.cxx:500
A TTree represents a columnar dataset.
Definition: TTree.h:79
return c1
Definition: legend1.C:41
Definition: tree.py:1
TArc a
Definition: textangle.C:12