class TRandom: public TNamed

 Default constructor. For seed see SetSeed().

 Default destructor. Can reset gRandom to 0 if gRandom points to this
 generator.

 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 and 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

 Returns an exponential deviate.

          exp( -t/tau )

 Samples a random number from the standard Normal (Gaussian) Distribution
 with the given mean and sigma.
 Uses the Acceptance-complement ratio from W. Hoermann and G. Derflinger
 This is one of the fastest existing method for generating normal random variables.
 It is a factor 2/3 faster than the polar (Box-Muller) method used in the previous
 version of TRandom::Gaus. The speed is comparable to the Ziggurat method (from Marsaglia)
 implemented for example in GSL and available in the MathMore library.

 REFERENCE:  - W. Hoermann and G. Derflinger (1990):
              The ACR Method for generating normal random variables,
              OR Spektrum 12 (1990), 181-185.

 Implementation taken from
 UNURAN (c) 2000  W. Hoermann & J. Leydold, Institut f. Statistik, WU Wien

 Returns a random integer on [ 0, imax-1 ].

 Generate a random number following a Landau distribution
 with location parameter mu and scale parameter sigma:
      Landau( (x-mu)/sigma )
 Note that mu is not the mpv(most probable value) of the Landa distribution
 and sigma is not the standard deviation of the distribution which is not defined.
 For mu  =0 and sigma=1, the mpv = -0.22278

 The Landau random number generation is implemented using the
 function landau_quantile(x,sigma), which provides
 the inverse of the landau cumulative distribution.
 landau_quantile has been converted from CERNLIB 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.

 Reads saved random generator status from filename.

  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. Note that default value is zero, which is
 different than the default value used when constructing the class.
 If the seed is zero the seed is set to a random value
 which in case of TRandom depends on the lowest 4 bytes of TUUID
 The UUID will be identical if SetSeed(0) is called with time smaller than 100 ns
 Instead if a different generator implementation is used (TRandom1, 2 or 3)
 the seed is generated using a 128 bit UUID. This results in different seeds
 and then random sequence for every SetSeed(0) call.

 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

 Returns a uniform deviate on the interval  (0, x1).

 Returns a uniform deviate on the interval (x1, x2).

 Writes random generator status to filename.