Fill multiple histograms with different functions and automatic binning. 
Illustrates merging with the power-of-two autobin algorithm
 
 OBJ: TStatistic   min   Mean = -0.11339 +- 0.106   RMS = 0.33525     Count = 10     Min = -0.79716    Max = 0.32411
 OBJ: TStatistic   max   Mean = 6.367 +- 0.167   RMS = 0.52811     Count = 10     Min = 5.7717   Max = 7.3347
 OBJ: TStatistic   dif   Mean = 6.4804 +- 0.1777    RMS = 0.56186     Count = 10     Min = 5.7029   Max = 7.5097
 OBJ: TStatistic   mean     Mean = 2.9951 +- 0.009736     RMS = 0.030789    Count = 10     Min = 2.9511   Max = 3.0373
 OBJ: TStatistic   rms   Mean = 0.993 +- 0.008528   RMS = 0.026967    Count = 10     Min = 0.95509     Max = 1.0375
 ent: 10010
TH1.Print Name  = myh0, Entries= 10010, Total sum= 10005
TH1.Print Name  = myhref, Entries= 10010, Total sum= 10002
 
 
TF1 *
gam = 
new TF1(
"gam", 
"1/(1+0.1*x*0.1*x)", -100., 100.);
 
TF1 *
gam1 = 
new TF1(
"gam", 
"1/(1+0.1*x*0.1*x)", -1., .25);
 
TF1 *
iga = 
new TF1(
"inv gam", 
"1.-1/(1+0.1*x*0.1*x)", -100., 100.);
 
TF1 *
iga1 = 
new TF1(
"inv gam", 
"1.-1/(1+0.1*x*0.1*x)", -.5, 1.);
 
 
{
 
 
 
   
   auto href = 
new TH1D(
"myhref", 
"current", 50, 0., -1.);
 
 
   
   auto href2 = 
new TH1D(
"myhref", 
"Auto P2, sequential", 50, 0., -1.);
 
 
 
 
      auto hw = 
new TH1D(
hname.Data(), 
"Auto P2, merged", nbins, 0., -1.);
 
 
 
         switch (opt) {
         case 1: 
xx = 
rndm.Gaus(3, 1); 
break;
 
         case 2: 
xx = 
rndm.Rndm() * 100. - 50.; 
break;
 
         case 3: 
xx = 
gam->GetRandom(); 
break;
 
         case 4: 
xx = 
gam1->GetRandom(); 
break;
 
         case 5: 
xx = 
iga->GetRandom(); 
break;
 
         case 6: 
xx = 
iga1->GetRandom(); 
break;
 
         default: 
xx = 
rndm.Gaus(0, 1);
 
         }
 
         }
            
         }
      }
 
   }
 
 
      return;
 
 
   if (
gROOT->GetListOfCanvases()->FindObject(
"c3"))
 
      delete gROOT->GetListOfCanvases()->FindObject(
"c3");
 
 
 
   std::cout << 
" ent: " << 
h0->GetEntries() << 
"\n";
 
}
ROOT::Detail::TRangeCast< T, true > TRangeDynCast
TRangeDynCast is an adapter class that allows the typed iteration through a TCollection.
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 r
R__EXTERN TStyle * gStyle
1-D histogram with a double per channel (see TH1 documentation)
@ kAutoBinPTwo
different than 1.
Random number generator class based on M.
Statistical variable, defined by its mean and variance (RMS).
static TString Format(const char *fmt,...)
Static method which formats a string using a printf style format descriptor and return a TString.
void SetOptStat(Int_t stat=1)
The type of information printed in the histogram statistics box can be selected via the parameter mod...
- Date
- November 2017 
- Author
- Gerardo Ganis 
Definition in file fillhistosauto2p.C.