SPARSE_GRID_MIXED_DATASET
Create Sparse Grid Using Mixed Rules


SPARSE_GRID_MIXED_DATASET is a C++ program which creates a sparse grid dataset from a mixture of 1D rules, using instructions from a user.

The available 1D quadrature rules are identified by a 2 or 3 letter code, and include:

  1. CC, Clenshaw-Curtis:
    defined on [-1,+1], with w(x)=1,
    a closed, fully nested rule.
  2. F2, Fejer Type 2:
    defined on (-1,+1), with w(x)=1,
    an open, fully nested rule.
  3. GP, Gauss Patterson:
    defined on (-1,+1), with w(x)=1,
    a family of the midpoint rule, the 3 point Gauss Legendre rule, and then successive Patterson refinements,
    an open, fully nested rule.
  4. GL, Gauss Legendre:
    defined on (-1,+1), with w(x)=1,
    an open, weakly nested rule.
  5. GH, Gauss Hermite:
    defined on (-oo,+oo), with w(x)=exp(-x*x),
    an open, weakly nested rule.
  6. GGH, Generalized Gauss Hermite:
    defined on (-oo,+oo), with w(x)=|x|^alpha * exp(-x*x),
    an open, weakly nested rule.
  7. LG, Gauss Laguerre:
    defined on (0,+oo) with w(x)=exp(-x),
    an open, non-nested rule.
  8. GLG, Generalized Gauss Laguerre:
    defined on (0,+oo) with w(x)=x^alpha * exp(-x),
    an open, non-nested rule.
  9. GJ, Gauss Jacobi:
    defined on [-1,+1] with w(x)=(1-x)^alpha (1+x)^beta
    an open, non-nested rule.
  10. GW, Golub Welsch:
    a rule defined by the user based on the Golub-Welsch algorithm,
    with points and weights supplied by external routines,
    presumably an open, non-nested rule.
    (not supported yet)
  11. CCS, Clenshaw-Curtis Slow-Growth:
    defined on [-1,+1], with w(x)=1,
    a closed, fully nested rule.
  12. F2S, Fejer Type 2, Slow-Growth:
    defined on (-1,+1), with w(x)=1,
    an open, fully nested rule.
  13. GPS, Gauss Patterson, Slow-Growth:
    defined on (-1,+1), with w(x)=1,
    a family of the midpoint rule, the 3 point Gauss Legendre rule, and then successive Patterson refinements,
    an open, fully nested rule.

Usage:

The user first specifies:

and these two values can actuallyb be specified on the command line.

Then the user specifies rules for each of the M dimensions. A rule, when specified, may be used for one, or for multiple consecutive dimensions.

Finally, the user specifies a "file identifier", that is, the main part of a string to be used when creating the files.

Licensing:

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

Languages:

SPARSE_GRID_MIXED_DATASET is available in a C++ version and a FORTRAN90 version and a MATLAB version.

Related Data and Programs:

SANDIA_RULES, a C++ library which produces 1D quadrature rules of Chebyshev, Clenshaw Curtis, Fejer 2, Gegenbauer, generalized Hermite, generalized Laguerre, Hermite, Jacobi, Laguerre, Legendre and Patterson types.

SPARSE_GRID_CC, a dataset directory which contains multidimensional Smolyak sparse grids based on the 1D Clenshaw Curtis rule;

SPARSE_GRID_CC_DATASET, a C++ program which creates a sparse grid dataset based on Clenshaw-Curtis rules.

SPARSE_GRID_CCS, a dataset directory which contains multidimensional Smolyak sparse grids based on the 1D Clenshaw Curtis rule with Slow Exponential Growth;

SPARSE_GRID_F2, a dataset directory which contains multidimensional Smolyak sparse grids based on the 1D Fejer type 2 rule;

SPARSE_GRID_GL, a dataset directory which contains multidimensional Smolyak sparse grids based on the 1D Gauss-Legendre rule;

SPARSE_GRID_GL_DATASET, a C++ program which creates a sparse grid dataset based on Gauss-Legendre rules.

SPARSE_GRID_GP, a dataset directory which contains multidimensional Smolyak sparse grids based on the 1D Gauss-Patterson rule;

SPARSE_GRID_HERMITE, a dataset directory which contains multidimensional Smolyak sparse grids based on the 1D Gauss-Hermite rule;

SPARSE_GRID_HERMITE_DATASET, a C++ program which creates a sparse grid dataset based on Gauss-Hermite rules.

SPARSE_GRID_LAGUERRE, a dataset directory which contains multidimensional Smolyak sparse grids based on the 1D Gauss-Laguerre rule;

SPARSE_GRID_LAGUERRE_DATASET, a C++ program which creates a sparse grid dataset based on Gauss-Laguerrre rules.

SPARSE_GRID_MIXED, a C++ library which creates a sparse grid dataset based on a mixed set of 1D factor rules.

SPARSE_GRID_MIXED, a dataset directory which contains multidimensional Smolyak sparse grids based on a mixed set of 1D factor rules.

SPARSE_GRID_NCC, a dataset directory which contains multidimensional Smolyak sparse grids based on the 1D Newton Cotes Closed rule;

SPARSE_GRID_NCO, a dataset directory which contains multidimensional Smolyak sparse grids based on the 1D Newton Cotes Open rule;

SPARSE_GRID_OPEN_DATASET, a C++ program which creates a sparse grid dataset based on open rules (Fejer 2, Gauss-Patterson, Newton-Cotes-Open).

SPARSE_GRID_TANH_SINH, a dataset directory which contains multidimensional Smolyak sparse grids based on a 1D tanh-sinh rule;

Reference:

  1. Thomas Gerstner, Michael Griebel,
    Numerical Integration Using Sparse Grids,
    Numerical Algorithms,
    Volume 18, Number 3-4, 1998, pages 209-232.
  2. Fabio Nobile, Raul Tempone, Clayton Webster,
    A Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data,
    SIAM Journal on Numerical Analysis,
    Volume 46, Number 5, 2008, pages 2309-2345.
  3. Sergey Smolyak,
    Quadrature and Interpolation Formulas for Tensor Products of Certain Classes of Functions,
    Doklady Akademii Nauk SSSR,
    Volume 4, 1963, pages 240-243.

Source Code:

List of Routines:

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


Last revised on 25 December 2009.