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Reference Guide
hsum.C
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1 /// \file
2 /// \ingroup tutorial_hist
3 /// \notebook -js
4 /// Histograms filled and drawn in a loop.
5 /// Simple example illustrating how to use the C++ interpreter
6 /// to fill histograms in a loop and show the graphics results
7 ///
8 /// \macro_image
9 /// \macro_code
10 ///
11 /// \author Rene Brun
12 
13 void hsum() {
14  TCanvas *c1 = new TCanvas("c1","The HSUM example",200,10,600,400);
15  c1->SetGrid();
16 
17  gBenchmark->Start("hsum");
18 
19  // Create some histograms.
20  auto total = new TH1F("total","This is the total distribution",100,-4,4);
21  auto main = new TH1F("main","Main contributor",100,-4,4);
22  auto s1 = new TH1F("s1","This is the first signal",100,-4,4);
23  auto s2 = new TH1F("s2","This is the second signal",100,-4,4);
24  total->Sumw2(); // store the sum of squares of weights
25  total->SetMarkerStyle(21);
26  total->SetMarkerSize(0.7);
27  main->SetFillColor(16);
28  s1->SetFillColor(42);
29  s2->SetFillColor(46);
30  TSlider *slider = 0;
31 
32  // Fill histograms randomly
33  gRandom->SetSeed();
34  const Int_t kUPDATE = 500;
35  Float_t xs1, xs2, xmain;
36  for ( Int_t i=0; i<10000; i++) {
37  xmain = gRandom->Gaus(-1,1.5);
38  xs1 = gRandom->Gaus(-0.5,0.5);
39  xs2 = gRandom->Landau(1,0.15);
40  main->Fill(xmain);
41  s1->Fill(xs1,0.3);
42  s2->Fill(xs2,0.2);
43  total->Fill(xmain);
44  total->Fill(xs1,0.3);
45  total->Fill(xs2,0.2);
46  if (i && (i%kUPDATE) == 0) {
47  if (i == kUPDATE) {
48  total->Draw("e1p");
49  main->Draw("same");
50  s1->Draw("same");
51  s2->Draw("same");
52  c1->Update();
53  slider = new TSlider("slider",
54  "test",4.2,0,4.6,total->GetMaximum(),38);
55  slider->SetFillColor(46);
56  }
57  if (slider) slider->SetRange(0,Float_t(i)/10000.);
58  c1->Modified();
59  c1->Update();
60  }
61  }
62  slider->SetRange(0,1);
63  total->Draw("sameaxis"); // to redraw axis hidden by the fill area
64  c1->Modified();
65  gBenchmark->Show("hsum");
66 }
float Float_t
Definition: RtypesCore.h:53
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
return c1
Definition: legend1.C:41
THist< 1, float, THistStatContent, THistStatUncertainty > TH1F
Definition: THist.hxx:285
virtual void SetRange(Double_t xmin=0, Double_t xmax=1)
Set Slider range in [0,1].
Definition: TSlider.cxx:204
virtual void Show(const char *name)
Stops Benchmark name and Prints results.
Definition: TBenchmark.cxx:157
int Int_t
Definition: RtypesCore.h:41
A specialized TPad including a TSliderBox object.
Definition: TSlider.h:18
virtual void Start(const char *name)
Starts Benchmark with the specified name.
Definition: TBenchmark.cxx:174
virtual void SetSeed(ULong_t seed=0)
Set the random generator seed.
Definition: TRandom.cxx:589
virtual void SetGrid(Int_t valuex=1, Int_t valuey=1)
Definition: TPad.h:327
int main(int argc, char **argv)
virtual void SetFillColor(Color_t fcolor)
Set the fill area color.
Definition: TAttFill.h:37
R__EXTERN TBenchmark * gBenchmark
Definition: TBenchmark.h:59
#define s1(x)
Definition: RSha256.hxx:91
R__EXTERN TRandom * gRandom
Definition: TRandom.h:62
static unsigned int total
The Canvas class.
Definition: TCanvas.h:31
virtual void Update()
Update canvas pad buffers.
Definition: TCanvas.cxx:2248
Definition: hsum.py:1
virtual Double_t Landau(Double_t mean=0, Double_t sigma=1)
Generate a random number following a Landau distribution with location parameter mu and scale paramet...
Definition: TRandom.cxx:361
void Modified(Bool_t flag=1)
Definition: TPad.h:414