UNIFORM
A Uniform Random Number Generator


UNIFORM is a C library, using single or double precision arithmetic, which returns a sequence of uniformly distributed pseudorandom numbers.

The fundamental underlying random number generator in UNIFORM is based on a simple, old, and limited linear congruential random number generator originally used in the IBM System 360. If you want state of the art random number generation, look elsewhere!

The C math library already has random number functions, which can return pseudorandom numbers rapidly, in bulk, and generally with less correlation than UNIFORM provides.

However, this library makes it possible to compare certain computations that use uniform random numbers, written in C, C++, FORTRAN77, FORTRAN90, Mathematica or MATLAB.

Various types of random data can be computed. The routine names are chosen to indicate the corresponding type:

In some cases, a one dimensional vector or two dimensional array of values is to be generated, and part of the name will therefore include:

The underlying random numbers are generally defined over some unit interval or region. Routines are available which return these "unit" values, while other routines allow the user to specify limits between which the unit values are rescaled. If a routine returns unit values, its name will include a special indicator:

The random number generator embodied here is not very sophisticated. It will not have the best properties of distribution, noncorrelation and long period. It is not the purpose of this library to achieve such worthy goals. This is simply a reasonably portable library that can be implemented in various languages, on various machines, and for which it is possible, for instance, to regard the output as a function of the seed, and moreover, to work directly with the sequence of seeds, if necessary.

Licensing:

The computer code and data files described and made available on this web page are distributed under the GNU LGPL license.

Related Data and Programs:

CVT is a C++ library which computes elements of a Centroidal Voronoi Tessellation.

FAURE is a C++ library which computes elements of a Faure quasirandom sequence.

GRID is a C++ library which computes elements of a grid dataset.

HALTON is a C++ library which computes elements of a Halton quasirandom sequence.

HAMMERSLEY is a C++ library which computes elements of a Hammersley quasirandom sequence.

HEX_GRID is a C++ library which computes elements of a hexagonal grid dataset.

HEX_GRID_ANGLE is a FORTRAN90 library which computes elements of an angled hexagonal grid dataset.

IHS is a C++ library which computes elements of an improved distributed Latin hypercube dataset.

LATIN_CENTER is a C++ library which computes elements of a Latin Hypercube dataset, choosing center points.

LATIN_EDGE is a C++ library which computes elements of a Latin Hypercube dataset, choosing edge points.

LATIN_RANDOM is a C++ library which computes elements of a Latin Hypercube dataset, choosing points at random.

LCVT is a C++ library which computes a latinized Centroidal Voronoi Tessellation.

NIEDERREITER2 is a C++ library which computes elements of a Niederreiter quasirandom sequence with base 2.

NORMAL is a C library which computes elements of a sequence of pseudorandom normally distributed values.

RBOX is a C program which generates a set of points in a region, selected at random according to a given distribution.

SOBOL is a C++ library which computes elements of a Sobol quasirandom sequence.

UNIFORM is also available in a C++ version and a FORTRAN77 version and a FORTRAN90 version and a Mathematica version and a MATLAB version

VAN_DER_CORPUT is a C++ library which computes elements of a van der Corput quasirandom sequence.

ZIGGURAT is a C library which computes elements of uniform, normal or exponential pseudorandom sequence using the ziggurat method.

Reference:

  1. Paul Bratley, Bennett Fox, Linus Schrage,
    A Guide to Simulation,
    Second Edition,
    Springer, 1987,
    ISBN: 0387964673,
    LC: QA76.9.C65.B73.
  2. Bennett Fox,
    Algorithm 647: Implementation and Relative Efficiency of Quasirandom Sequence Generators,
    ACM Transactions on Mathematical Software,
    Volume 12, Number 4, December 1986, pages 362-376.
  3. Donald Knuth,
    The Art of Computer Programming,
    Volume 2, Seminumerical Algorithms,
    Third Edition,
    Addison Wesley, 1997,
    ISBN: 0201896842,
    LC: QA76.6.K64.
  4. Pierre LEcuyer,
    Random Number Generation,
    in Handbook of Simulation,
    edited by Jerry Banks,
    Wiley, 1998,
    ISBN: 0471134031,
    LC: T57.62.H37.
  5. Peter Lewis, Allen Goodman, James Miller,
    A Pseudo-Random Number Generator for the System/360,
    IBM Systems Journal,
    Volume 8, Number 2, 1969, pages 136-143.
  6. Eric Weisstein,
    CRC Concise Encyclopedia of Mathematics,
    CRC Press, 2002,
    Second edition,
    ISBN: 1584883472,
    LC: QA5.W45.
  7. Barry Wilkinson, Michael Allen,
    Parallel Programming: Techniques and Applications Using Networked Workstations and Parallel Computers,
    Prentice Hall,
    ISBN: 0-13-140563-2,
    LC: QA76.642.W54.

Source Code:

Examples and Tests:

List of Routines:

You can go up one level to the C source codes.


Last revised on 21 May 2008.