TRandom


class description - source file - inheritance tree

class TRandom : public TNamed

    private:
protected:
public:
TRandom TRandom(UInt_t seed = 65539) TRandom TRandom(TRandom&) virtual void ~TRandom() virtual Int_t Binomial(Int_t ntot, Double_t prob) static TClass* Class() virtual Double_t Exp(Double_t tau) virtual Double_t Gaus(Double_t mean = 0, Double_t sigma = 1) virtual UInt_t GetSeed() virtual UInt_t Integer(UInt_t imax) virtual TClass* IsA() const virtual Double_t Landau(Double_t mean = 0, Double_t sigma = 1) virtual Int_t Poisson(Double_t mean) virtual void Rannor(Float_t& a, Float_t& b) virtual void Rannor(Double_t& a, Double_t& b) virtual Double_t Rndm(Int_t i = 0) virtual void SetSeed(UInt_t seed = 65539) virtual void ShowMembers(TMemberInspector& insp, char* parent) virtual void Streamer(TBuffer& b) void StreamerNVirtual(TBuffer& b) virtual Double_t Uniform(Double_t x1 = 1)

Data Members

    private:
protected:
UInt_t fSeed Random number generator seed public:


See also

TRandom2, TRandom3

Class Description

 TRandom

 basic Random number generator class (periodicity = 10**8).

 The following basic Random generators are provided:
 ===================================================
   -Exp(tau)
   -Integer(imax)
   -Gaus(mean,sigma)
   -Rndm()
   -Uniform(x1)
   -Landau(mpv,sigma)
   -Poisson(mean)
   -Binomial(ntot,prob)

 Random numbers distributed according to 1-d, 2-d or 3-d distributions
 =====================================================================
 contained in TF1, TF2 or TF3 objects.
 For example, to get a random number distributed following abs(sin(x)/x)*sqrt(x)
 you can do:
   TF1 *f1 = new TF1("f1","abs(sin(x)/x)*sqrt(x)",0,10);
   double r = f1->GetRandom();
 The technique of using a TF1,2 or 3 function is very powerful.
 It is also more precise than using the basic functions (except Rndm).
 With a TF1 function, for example, the real integral of the function
 is correctly calculated in the specified range of the function.
 Getting a number from a TF1 function is also very fast.
 The following table shows some timings (in microsecons/call)
 for basic functions and TF1 functions.
 The left column is with the compiler, the right column with CINT.
 Numbers have been obtained on a Pentium 233Mhz running Linux.

                          g++        CINT
   Rndm..............    0.330       4.15
   Gaus..............    2.220       6.77
   Landau............   21.590      46.82
   Binomial(5,0.5)...    0.890       5.34
   Binomial(15,0.5)..    0.920       5.36
   Poisson(3)........    2.170       5.93
   Poisson(10).......    4.160       7.95
   Poisson(70).......   21.510      25.27
   Poisson(100)......    2.910       6.72
   GausTF1...........    2.070       4.73
   LandauTF1.........    2.100       4.73

  Note that the time to generate a number from an arbitrary TF1 function
  is independent of the complexity of the function.
  For Landau distribution, it is recommended to use the TF1 technique.

  TH1::FillRandom(TH1 *) or TH1::FillRandom(const char *tf1name)
  ==============================================================
  can be used to fill an histogram (1-d, 2-d, 3-d from an existing histogram
  or from an existing function.

  Note this interesting feature when working with objects
  =======================================================
  You can use several TRandom objects, each with their "independent"
  random sequence. For example, one can imagine
     TRandom *eventGenerator = new TRandom();
     TRandom *tracking       = new TRandom();
  eventGenerator can be used to generate the event kinematics.
  tracking can be used to track the generated particles with random numbers
  independent from eventGenerator.
  This very interesting feature gives the possibility to work with simple
  and very fast random number generators without worrying about
  random number periodicity as it was the case with Fortran.
  One can use TRandom::SetSeed to modify the seed of one generator.

  a TRandom object may be written to a Root file
  ==============================================
    -as part of another object
    -or with its own key (example gRandom->Write("Random");

  The small program below has been used to get the values in the table above.
   #ifndef __CINT__
      #include "TROOT.h"
   #include "TF1.h"
   #include "TRandom.h"
   #include "TStopwatch.h"
   void rand();

   //______________________________________________________________________________
   int main()
   {
     TROOT simple("simple","Test of random numbers");

     rand();
   }
   #endif
   void rand() {
     int i, N = 1000000;
     double cpn = 1000000./N;
     double x;
     TStopwatch sw;
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Rndm(i);
     }
     printf("Rndm.............. %8.3f microseconds/calln",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Gaus(0,1);
     }
     printf("Gaus.............. %8.3fn",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Landau(0,1);
     }
     printf("Landau............ %8.3fn",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Binomial(5,0.5);
     }
     printf("Binomial(5,0.5)... %8.3fn",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Binomial(15,0.5);
     }
     printf("Binomial(15,0.5).. %8.3fn",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Poisson(3);
     }
     printf("Poisson(3)........ %8.3fn",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Poisson(10);
     }
     printf("Poisson(10)....... %8.3fn",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Poisson(70);
     }
     printf("Poisson(70)....... %8.3fn",sw.CpuTime()*cpn);
     sw.Start();
     for (i=0;i<N;i++) {
        x = gRandom->Poisson(100);
     }
     printf("Poisson(100)...... %8.3fn",sw.CpuTime()*cpn);

     TF1 *f1 = new TF1("f1","gaus",-4,4);
     f1->SetParameters(1,0,1);
     sw.Start();
     for (i=0;i<N;i++) {
        x = f1->GetRandom();
     }
     printf("GausTF1........... %8.3fn",sw.CpuTime()*cpn);

     TF1 *f2 = new TF1("f2","landau",-5,15);
     f2->SetParameters(1,0,1);
     sw.Start();
     for (i=0;i<N;i++) {
        x = f2->GetRandom();
     }
     printf("LandauTF1......... %8.3fn",sw.CpuTime()*cpn);

   }


TRandom(UInt_t seed): TNamed("Random","Default Random number generator")
*-*-*-*-*-*-*-*-*-*-*default constructor*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ===================

~TRandom()
*-*-*-*-*-*-*-*-*-*-*default destructor*-*-*-*-*-*-*-*-*-*-*-*-*-*-*
*-*                  ==================

Int_t Binomial(Int_t ntot, Double_t prob)
 Generates a random integer N according to the binomial law
 Coded from Los Alamos report LA-5061-MS

 N is binomially distributed between 0 and ntot inclusive
 with mean prob*ntot.
 prob is between 0 and 1.

 Note: This function should not be used when ntot is large (say >100).
 The normal approximation is then recommended instead
 (with mean =*ntot+0.5 and standard deviation sqrt(ntot*prob*(1-prob)).

Double_t Exp(Double_t tau)
 returns an exponential deviate.

          exp( -t/tau )

Double_t Gaus(Double_t mean, Double_t sigma)
      Return a number distributed following a gaussian with mean and sigma

UInt_t Integer(UInt_t imax)
  returns a random integer on [ 0, imax-1 ].

Double_t Landau(Double_t mpv, Double_t sigma)
  Generate a random number following a Landau distribution
  with mpv(most probable value) and sigma
  Converted by Rene Brun from CERNLIB routine ranlan(G110)

Int_t Poisson(Double_t mean)
 Generates a random integer N according to a Poisson law.
 Coded from Los Alamos report LA-5061-MS
 Prob(N) = exp(-mean)*mean^N/Factorial(N)


void Rannor(Float_t &a, Float_t &b)
      Return 2 numbers distributed following a gaussian with mean=0 and sigma=1

void Rannor(Double_t &a, Double_t &b)
      Return 2 numbers distributed following a gaussian with mean=0 and sigma=1

Double_t Rndm(Int_t)
  Machine independent random number generator.
  Produces uniformly-distributed floating points between 0 and 1.
  Identical sequence on all machines of >= 32 bits.
  Periodicity = 10**8
  Universal version (Fred james 1985).
  generates a number in [0,1]

void SetSeed(UInt_t seed)
  Set the random generator seed
  if seed is zero, the seed is set to the current  machine clock
  Note that the machine clock is returned with a precision of 1 second.
  If one calls SetSeed(0) within a loop and the loop time is less than 1s,
  all generated numbers will be identical!

Double_t Uniform(Double_t x1)
 returns a uniform deviate on the interval ( 0, x1 ].



Inline Functions


             UInt_t GetSeed()
            TClass* Class()
            TClass* IsA() const
               void ShowMembers(TMemberInspector& insp, char* parent)
               void Streamer(TBuffer& b)
               void StreamerNVirtual(TBuffer& b)
            TRandom TRandom(TRandom&)


Author: Rene Brun 15/12/95
Last update: root/base:$Name: $:$Id: TRandom.cxx,v 1.7 2001/04/20 07:29:46 brun Exp $
Copyright (C) 1995-2000, Rene Brun and Fons Rademakers. *


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