library: libCore #include "TRandom.h" |
TRandom(UInt_t seed = 65539) | |
TRandom(const TRandom&) | |
virtual | ~TRandom() |
void | TObject::AbstractMethod(const char* method) const |
virtual void | TObject::AppendPad(Option_t* option = "") |
virtual Int_t | Binomial(Int_t ntot, Double_t prob) |
virtual Double_t | BreitWigner(Double_t mean = 0, Double_t gamma = 1) |
virtual void | TObject::Browse(TBrowser* b) |
virtual void | Circle(Double_t& x, Double_t& y, Double_t r) |
static TClass* | Class() |
virtual const char* | TObject::ClassName() const |
virtual void | TNamed::Clear(Option_t* option = "") |
virtual TObject* | TNamed::Clone(const char* newname = "") const |
virtual Int_t | TNamed::Compare(const TObject* obj) const |
virtual void | TNamed::Copy(TObject& named) const |
virtual void | TObject::Delete(Option_t* option = "") |
virtual Int_t | TObject::DistancetoPrimitive(Int_t px, Int_t py) |
virtual void | TObject::Draw(Option_t* option = "") |
virtual void | TObject::DrawClass() const |
virtual TObject* | TObject::DrawClone(Option_t* option = "") const |
virtual void | TObject::Dump() const |
virtual void | TObject::Error(const char* method, const char* msgfmt) const |
virtual void | TObject::Execute(const char* method, const char* params, Int_t* error = 0) |
virtual void | TObject::Execute(TMethod* method, TObjArray* params, Int_t* error = 0) |
virtual void | TObject::ExecuteEvent(Int_t event, Int_t px, Int_t py) |
virtual Double_t | Exp(Double_t tau) |
virtual void | TObject::Fatal(const char* method, const char* msgfmt) const |
virtual void | TNamed::FillBuffer(char*& buffer) |
virtual TObject* | TObject::FindObject(const char* name) const |
virtual TObject* | TObject::FindObject(const TObject* obj) const |
virtual Double_t | Gaus(Double_t mean = 0, Double_t sigma = 1) |
virtual Option_t* | TObject::GetDrawOption() const |
static Long_t | TObject::GetDtorOnly() |
virtual const char* | TObject::GetIconName() const |
virtual const char* | TNamed::GetName() const |
virtual char* | TObject::GetObjectInfo(Int_t px, Int_t py) const |
static Bool_t | TObject::GetObjectStat() |
virtual Option_t* | TObject::GetOption() const |
virtual UInt_t | GetSeed() |
virtual const char* | TNamed::GetTitle() const |
virtual UInt_t | TObject::GetUniqueID() const |
virtual Bool_t | TObject::HandleTimer(TTimer* timer) |
virtual ULong_t | TNamed::Hash() const |
virtual void | TObject::Info(const char* method, const char* msgfmt) const |
virtual Bool_t | TObject::InheritsFrom(const char* classname) const |
virtual Bool_t | TObject::InheritsFrom(const TClass* cl) const |
virtual void | TObject::Inspect() const |
virtual UInt_t | Integer(UInt_t imax) |
void | TObject::InvertBit(UInt_t f) |
virtual TClass* | IsA() const |
virtual Bool_t | TObject::IsEqual(const TObject* obj) const |
virtual Bool_t | TObject::IsFolder() const |
Bool_t | TObject::IsOnHeap() const |
virtual Bool_t | TNamed::IsSortable() const |
Bool_t | TObject::IsZombie() const |
virtual Double_t | Landau(Double_t mean = 0, Double_t sigma = 1) |
virtual void | TNamed::ls(Option_t* option = "") const |
void | TObject::MayNotUse(const char* method) const |
virtual Bool_t | TObject::Notify() |
static void | TObject::operator delete(void* ptr) |
static void | TObject::operator delete(void* ptr, void* vp) |
static void | TObject::operator delete[](void* ptr) |
static void | TObject::operator delete[](void* ptr, void* vp) |
void* | TObject::operator new(size_t sz) |
void* | TObject::operator new(size_t sz, void* vp) |
void* | TObject::operator new[](size_t sz) |
void* | TObject::operator new[](size_t sz, void* vp) |
TRandom& | operator=(const TRandom&) |
virtual void | TObject::Paint(Option_t* option = "") |
virtual Int_t | Poisson(Double_t mean) |
virtual Double_t | PoissonD(Double_t mean) |
virtual void | TObject::Pop() |
virtual void | TNamed::Print(Option_t* option = "") const |
virtual void | Rannor(Float_t& a, Float_t& b) |
virtual void | Rannor(Double_t& a, Double_t& b) |
virtual Int_t | TObject::Read(const char* name) |
virtual void | ReadRandom(const char* filename) |
virtual void | TObject::RecursiveRemove(TObject* obj) |
void | TObject::ResetBit(UInt_t f) |
virtual Double_t | Rndm(Int_t i = 0) |
virtual void | RndmArray(Int_t n, Float_t* array) |
virtual void | RndmArray(Int_t n, Double_t* array) |
virtual void | TObject::SaveAs(const char* filename = "", Option_t* option = "") const |
virtual void | TObject::SavePrimitive(ostream& out, Option_t* option = "") |
void | TObject::SetBit(UInt_t f) |
void | TObject::SetBit(UInt_t f, Bool_t set) |
virtual void | TObject::SetDrawOption(Option_t* option = "") |
static void | TObject::SetDtorOnly(void* obj) |
virtual void | TNamed::SetName(const char* name) |
virtual void | TNamed::SetNameTitle(const char* name, const char* title) |
static void | TObject::SetObjectStat(Bool_t stat) |
virtual void | SetSeed(UInt_t seed = 65539) |
virtual void | TNamed::SetTitle(const char* title = "") |
virtual void | TObject::SetUniqueID(UInt_t uid) |
virtual void | ShowMembers(TMemberInspector& insp, char* parent) |
virtual Int_t | TNamed::Sizeof() const |
virtual void | Sphere(Double_t& x, Double_t& y, Double_t& z, Double_t r) |
virtual void | Streamer(TBuffer& b) |
void | StreamerNVirtual(TBuffer& b) |
virtual void | TObject::SysError(const char* method, const char* msgfmt) const |
Bool_t | TObject::TestBit(UInt_t f) const |
Int_t | TObject::TestBits(UInt_t f) const |
virtual Double_t | Uniform(Double_t x1 = 1) |
virtual Double_t | Uniform(Double_t x1, Double_t x2) |
virtual void | TObject::UseCurrentStyle() |
virtual void | TObject::Warning(const char* method, const char* msgfmt) const |
virtual Int_t | TObject::Write(const char* name = "0", Int_t option = 0, Int_t bufsize = 0) |
virtual Int_t | TObject::Write(const char* name = "0", Int_t option = 0, Int_t bufsize = 0) const |
virtual void | WriteRandom(const char* filename) |
virtual void | TObject::DoError(int level, const char* location, const char* fmt, va_list va) const |
void | TObject::MakeZombie() |
enum TObject::EStatusBits { | kCanDelete | |
kMustCleanup | ||
kObjInCanvas | ||
kIsReferenced | ||
kHasUUID | ||
kCannotPick | ||
kNoContextMenu | ||
kInvalidObject | ||
}; | ||
enum TObject::[unnamed] { | kIsOnHeap | |
kNotDeleted | ||
kZombie | ||
kBitMask | ||
kSingleKey | ||
kOverwrite | ||
kWriteDelete | ||
}; |
UInt_t | fSeed | Random number generator seed |
TString | TNamed::fName | object identifier |
TString | TNamed::fTitle | object title |
TRandom basic Random number generator class (periodicity = 10**9). Note that this is a very simple generator (linear congruential) which is known to have defects (the lower random bits are correlated) and therefore should NOT be used in any statistical study. One should use instead TRandom1, TRandom2 or TRandom3. TRandom3, is based on the "Mersenne Twister generator", and is the recommended one, since it has good random proprieties (period of about 10**6000 ) and it is fast. TRandom1, based on the RANLUX algorithm, has mathematically proven random proprieties and a period of about 10**171. It is however slower than the others. TRandom2, is based on the Tausworthe generator of L'Ecuyer, and it has the advantage of being fast and using only 3 words (of 32 bits) for the state. The period is 10**26. The following table shows some timings (in nanoseconds/call) for the random numbers obtained using an Intel Pentium 3.0 GHz running Linux and using the gcc 3.2.3 compiler TRandom 34 ns/call (BAD Generator) TRandom1 242 ns/call TRandom2 37 ns/call TRandom3 45 ns/call The following basic Random distributions 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/call\n",sw.CpuTime()*cpn); sw.Start(); for (i=0;i<N;i++) { x = gRandom->Gaus(0,1); } printf("Gaus.............. %8.3f\n",sw.CpuTime()*cpn); sw.Start(); for (i=0;i<N;i++) { x = gRandom->Landau(0,1); } printf("Landau............ %8.3f\n",sw.CpuTime()*cpn); sw.Start(); for (i=0;i<N;i++) { x = gRandom->Binomial(5,0.5); } printf("Binomial(5,0.5)... %8.3f\n",sw.CpuTime()*cpn); sw.Start(); for (i=0;i<N;i++) { x = gRandom->Binomial(15,0.5); } printf("Binomial(15,0.5).. %8.3f\n",sw.CpuTime()*cpn); sw.Start(); for (i=0;i<N;i++) { x = gRandom->Poisson(3); } printf("Poisson(3)........ %8.3f\n",sw.CpuTime()*cpn); sw.Start(); for (i=0;i<N;i++) { x = gRandom->Poisson(10); } printf("Poisson(10)....... %8.3f\n",sw.CpuTime()*cpn); sw.Start(); for (i=0;i<N;i++) { x = gRandom->Poisson(70); } printf("Poisson(70)....... %8.3f\n",sw.CpuTime()*cpn); sw.Start(); for (i=0;i<N;i++) { x = gRandom->Poisson(100); } printf("Poisson(100)...... %8.3f\n",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........... %8.3f\n",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......... %8.3f\n",sw.CpuTime()*cpn); }
*-*-*-*-*-*-*-*-*-*-*default constructor*-*-*-*-*-*-*-*-*-*-*-*-*-*-* *-* ===================
*-*-*-*-*-*-*-*-*-*-*default destructor*-*-*-*-*-*-*-*-*-*-*-*-*-*-* *-* ==================
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)).
Return a number distributed following a BreitWigner function with mean and gamma
generates random vectors, uniformly distributed over a circle of given radius. Input : r = circle radius Output: x,y a random 2-d vector of length r
Return a number distributed following a gaussian with mean and 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)
Generates a random integer N according to a Poisson law. Prob(N) = exp(-mean)*mean^N/Factorial(N) Use a different procedure according to the mean value. The algorithm is the same used by CLHEP For lower value (mean < 25) use the rejection method based on the exponential For higher values use a rejection method comparing with a Lorentzian distribution, as suggested by several authors This routine since is returning 32 bits integer will not work for values larger than 2*10**9 One should then use the Trandom::PoissonD for such large values
Generates a random number according to a Poisson law. Prob(N) = exp(-mean)*mean^N/Factorial(N) This function is a variant of TRandom::Poisson returning a double instead of an integer.
Return 2 numbers distributed following a gaussian with mean=0 and sigma=1
Return 2 numbers distributed following a gaussian with mean=0 and sigma=1
Machine independent random number generator. Based on the BSD Unix (Rand) Linear congrential generator Produces uniformly-distributed floating points between 0 and 1. Identical sequence on all machines of >= 32 bits. Periodicity = 2**31 generates a number in ]0,1] Note that this is a generator which is known to have defects (the lower random bits are correlated) and therefore should NOT be used in any statistical study.
Return an array of n random numbers uniformly distributed in ]0,1]
Return an array of n random numbers uniformly distributed in ]0,1]
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!
generates random vectors, uniformly distributed over the surface of a sphere of given radius. Input : r = sphere radius Output: x,y,z a random 3-d vector of length r Method: (based on algorithm suggested by Knuth and attributed to Robert E Knop) which uses less random numbers than the CERNLIB RN23DIM algorithm