sobol


sobol, a C++ code which computes elements of the Sobol quasirandom sequence, by Bennett Fox.

A quasirandom or low discrepancy sequence, such as the Faure, Halton, Hammersley, Niederreiter or Sobol sequences, is "less random" than a pseudorandom number sequence, but more useful for such tasks as approximation of integrals in higher dimensions, and in global optimization. This is because low discrepancy sequences tend to sample space "more uniformly" than random numbers. Algorithms that use such sequences may have superior convergence.

SOBOL is an adapation of the INSOBL and GOSOBL routines in ACM TOMS Algorithm 647 and ACM TOMS Algorithm 659. The original code can only compute the "next" element of the sequence. The revised code allows the user to specify the index of any desired element.

A remark by Joe and Kuo shows how to extend the algorithm from the original maximum spatial dimension of 40 up to a maximum spatial dimension of 1111. The FORTRAN90 and C++ versions of this program have been updated in this way. In particular, the extra data in the C++ version of the program was kindly formatted and supplied by Steffan Berridge.

The routines with a prefix of I8_ use 64 bit integers, and use the long int to get this. On some systems, a long int is simply 32 bits. In that case, try using the long long int datatype instead.

The original, true, correct versions of ACM TOMS Algorithm 647 and ACM TOMS Algorithm 659 are available in the TOMS subdirectory of the NETLIB web site. The version displayed here has been converted to FORTRAN90, and other internal changes have been made to suit me.

Licensing:

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

Languages:

sobol is available in a C++ version and a FORTRAN90 version and a MATLAB version and a Python version

Related Data and Programs:

BOX_BEHNKEN, a C++ code which computes a Box-Behnken design, that is, a set of arguments to sample the behavior of a function of multiple parameters;

CVT, a C++ code which computes points in a Centroidal Voronoi Tessellation.

FAURE, a C++ code which computes Faure sequences.

HALTON, a C++ code which computes elements of a Halton Quasi Monte Carlo (QMC) sequence, using a simple interface.

HAMMERSLEY, a C++ code which computes elements of a Hammersley Quasi Monte Carlo (QMC) sequence, using a simple interface.

IHS, a C++ code which computes improved Latin Hypercube datasets.

LATIN_CENTER, a C++ code which computes Latin square data choosing the center value.

LATIN_EDGE, a C++ code which computes Latin square data choosing the edge value.

LATIN_RANDOM, a C++ code which computes Latin square data choosing a random value in the square.

NIEDERREITER2, a C++ code which computes Niederreiter sequences with base 2.

NORMAL, a C++ code which computes elements of a sequence of pseudorandom normally distributed values.

sobol_test

UNIFORM, a C++ code which computes uniform random values.

VAN_DER_CORPUT, a C++ code which computes a van der Corput sequences.

Author:

Original FORTRAN77 version by Bennett Fox; C++ version by John Burkardt.

Reference:

  1. IA Antonov, VM Saleev,
    An Economic Method of Computing LP Tau-Sequences,
    USSR Computational Mathematics and Mathematical Physics,
    Volume 19, 1980, pages 252-256.
  2. Paul Bratley, Bennett Fox,
    Algorithm 659: Implementing Sobol's Quasirandom Sequence Generator,
    ACM Transactions on Mathematical Software,
    Volume 14, Number 1, March 1988, pages 88-100.
  3. Paul Bratley, Bennett Fox, Harald Niederreiter,
    Implementation and Tests of Low Discrepancy Sequences,
    ACM Transactions on Modeling and Computer Simulation,
    Volume 2, Number 3, July 1992, pages 195-213.
  4. Paul Bratley, Bennett Fox, Linus Schrage,
    A Guide to Simulation,
    Second Edition,
    Springer, 1987,
    ISBN: 0387964673,
    LC: QA76.9.C65.B73.
  5. 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.
  6. Stephen Joe, Frances Kuo,
    Remark on Algorithm 659: Implementing Sobol's Quasirandom Sequence Generator,
    ACM Transactions on Mathematical Software,
    Volume 29, Number 1, March 2003, pages 49-57.
  7. Harald Niederreiter,
    Random Number Generation and quasi-Monte Carlo Methods,
    SIAM, 1992,
    ISBN13: 978-0-898712-95-7,
    LC: QA298.N54.
  8. William Press, Brian Flannery, Saul Teukolsky, William Vetterling,
    Numerical Recipes in FORTRAN: The Art of Scientific Computing,
    Second Edition,
    Cambridge University Press, 1992,
    ISBN: 0-521-43064-X,
    LC: QA297.N866.
  9. Ilya Sobol,
    Uniformly Distributed Sequences with an Additional Uniform Property,
    USSR Computational Mathematics and Mathematical Physics,
    Volume 16, 1977, pages 236-242.
  10. Ilya Sobol, YL Levitan,
    The Production of Points Uniformly Distributed in a Multidimensional Cube (in Russian),
    Preprint IPM Akademii Nauk SSSR,
    Number 40, Moscow 1976.

Source Code:


Last revised on 13 April 2020.