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SPARSE_GRID_GL\ Sparse Grids Based on Gauss-Legendre Rules {#sparse_grid_gl-sparse-grids-based-on-gauss-legendre-rules align=”center”} ==========================================

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SPARSE_GRID_GL is a C++ library which constructs sparse grids based on 1D Gauss-Legendre rules.

Sparse grids are more naturally constructed from a nested family of quadrature rules. Gauss-Legendre rules are not nested, but have higher accuracy. Thus, there is a tradeoff. If we compare two sparse grids of the same “level”, one using Gauss-Legendre rules and the other, say, Clenshaw-Curtis rules, then the Gauss-Legendre sparse grid will have higher accuracy…but also a significantly greater number of points. When measuring efficiency, we really need to balance the cost in quadrature points against the accuracy, and so it is not immediately obvious which choice is best!

To slightly complicate matters, Gauss-Legendre rules are very weakly nested, in that the rules of odd order all include the abscissa value X=0.0. A sparse grid constructed from Gauss-Legendre rules will thus have to keep track of this minor point as well.

Here is a table showing the number of points in a sparse grid based on Gauss-Legendre rules, indexed by the spatial dimension, and by the “level”, which is simply an index for the family of sparse grids.

DIM: 1 2 3 4 5 ———— ——- ——- ——- ——- ——– LEVEL_MAX           0 1 1 1 1 1 1 3 5 7 9 11 2 9 21 37 57 81 3 23 73 159 289 471 4 53 225 597 1265 2341 5 115 637 2031 4969 10363 6 241 1693 6405 17945 41913             DIM: 6 7 8 9 10 LEVEL_MAX           0 1 1 1 1 1 1 13 15 17 19 21 2 109 141 177 217 261 3 713 1023 1409 1879 2441 4 3953 6245 9377 13525 18881 5 19397 33559 54673 84931 126925             DIM: 100         LEVEL_MAX           0 1         1 201         2 20601        

Web Link: {#web-link align=”center”}

A version of the sparse grid library is available in http://tasmanian.ornl.gov, the TASMANIAN library, available from Oak Ridge National Laboratory.

Licensing: {#licensing align=”center”}

The code described and made available on this web page is distributed under the GNU LGPL license.

Languages: {#languages align=”center”}

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

Related Data and Programs: {#related-data-and-programs align=”center”}

CC_DISPLAY, a MATLAB library which can compute and display Clenshaw Curtis grids in two dimensions, as well as sparse grids formed from sums of Clenshaw Curtis grids.

QUADRATURE_RULES, a dataset directory which contains quadrature rules; a number of examples of sparse grid quadrature rules are included.

QUADRULE, a C++ library which defines quadrature rules for various intervals and weight functions.

SGMG, a C++ library which creates a sparse grid dataset based on a mixed set of 1D factor rules, and experiments with the use of a linear growth rate for the quadrature rules.

SGMGA, a C++ library which creates sparse grids based on a mixture of 1D quadrature rules, allowing anisotropic weights for each dimension.

SMOLPACK, a C library which implements Novak and Ritter’s method for estimating the integral of a function over a multidimensional hypercube using sparse grids.

SPARSE_GRID_CC, a C++ library which define sparse grids based on 1D Clenshaw Curtis quadrature rules.

SPARSE_GRID_CLOSED, a C++ library which define sparse grids based on closed nested quadrature rules.

SPARSE_GRID_DISPLAY, a MATLAB library which can display a 2D or 3D sparse grid.

SPARSE_GRID_F2, a dataset directory which contains sparse grids based on a Fejer Type 2 rule.

SPARSE_GRID_GL, a dataset directory of sparse grids based on a Gauss Legendre rule.

SPARSE_GRID_GP, a dataset directory of sparse grids based on a Gauss Patterson rule.

SPARSE_GRID_HERMITE, a C++ library which creates sparse grids based on Gauss-Hermite rules.

SPARSE_GRID_LAGUERRE, a C++ library which creates sparse grids based on Gauss-Laguerre rules.

SPARSE_GRID_MIXED, a C++ library which constructs a sparse grid using different rules in each spatial dimension.

SPARSE_GRID_NCC, a dataset directory of sparse grids based on a Newton Cotes closed rule.

SPARSE_GRID_NCO, a dataset directory of sparse grids based on a Newton Cotes open rule.

SPARSE_GRID_OPEN, a C++ library which defines sparse grids based on open nested quadrature rules.

TOMS847, a MATLAB program which uses sparse grids to carry out multilinear hierarchical interpolation. It is commonly known as SPINTERP, and is by Andreas Klimke.

Reference: {#reference align=”center”}

1. Volker Barthelmann, Erich Novak, Klaus Ritter,\ High Dimensional Polynomial Interpolation on Sparse Grids,\ Advances in Computational Mathematics,\ Volume 12, Number 4, 2000, pages 273-288.
2. Thomas Gerstner, Michael Griebel,\ Numerical Integration Using Sparse Grids,\ Numerical Algorithms,\ Volume 18, Number 3-4, 1998, pages 209-232.
3. Albert Nijenhuis, Herbert Wilf,\ Combinatorial Algorithms for Computers and Calculators,\ Second Edition,\ Academic Press, 1978,\ ISBN: 0-12-519260-6,\ LC: QA164.N54.
4. 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.
5. Sergey Smolyak,\ Quadrature and Interpolation Formulas for Tensor Products of Certain Classes of Functions,\ Doklady Akademii Nauk SSSR,\ Volume 4, 1963, pages 240-243.
6. Dennis Stanton, Dennis White,\ Constructive Combinatorics,\ Springer, 1986,\ ISBN: 0387963472,\ LC: QA164.S79.

Source Code: {#source-code align=”center”}

• sparse_grid_gl.cpp, the source code.
• sparse_grid_gl.hpp, the include file.

Examples and Tests: {#examples-and-tests align=”center”}

• sparse_grid_gl_prb.cpp, a sample calling program.
• sparse_grid_gl_prb_output.txt, the output file.
• gl_d2_level3_r.txt, the “R” data for a sparse quadrature rule.
• gl_d2_level3_w.txt, the “W” data for a sparse quadrature rule.
• gl_d2_level3_x.txt, the “X” data for a sparse quadrature rule.

List of Routines: {#list-of-routines align=”center”}

• COMP_NEXT computes the compositions of the integer N into K parts.
• GL_ABSCISSA sets abscissas for multidimensional Gauss-Legendre quadrature.
• GL_WEIGHTS returns weights for certain Gauss-Legendre quadrature rules.
• CHOOSE computes the binomial coefficient C(N,K).
• I4_LOG_2 returns the integer part of the logarithm base 2 of an I4.
• I4_MAX returns the maximum of two I4’s.
• I4_MIN returns the smaller of two I4’s.
• I4_MODP returns the nonnegative remainder of I4 division.
• I4_POWER returns the value of I\^J.
• I4_TO_STRING converts an I4 to a C++ string.
• I4VEC_PRODUCT multiplies the entries of an I4VEC.
• INDEX_LEVEL_GL: determine first level at which given index is generated.
• LEVEL_TO_ORDER_OPEN converts a level to an order for open rules.
• MONOMIAL_INT01 returns the integral of a monomial over the [0,1] hypercube.
• MONOMIAL_QUADRATURE applies a quadrature rule to a monomial.
• MONOMIAL_VALUE evaluates a monomial.
• MULTIGRID_INDEX_Z returns an indexed multidimensional grid.
• PRODUCT_WEIGHT_GL: weights for a product Gauss-Legendre rule.
• R8_EPSILON returns the R8 roundoff unit.
• R8_HUGE returns a “huge” R8.
• R8MAT_WRITE writes an R8MAT file.
• R8VEC_DIRECT_PRODUCT2 creates a direct product of R8VEC’s.
• S_LEN_TRIM returns the length of a string to the last nonblank.
• SPARSE_GRID_GL computes a sparse grid of Gauss-Legendre points.
• SPARSE_GRID_GL_INDEX indexes the points forming a sparse grid of GL points.
• SPARSE_GRID_GL_SIZE sizes a sparse grid of Gauss-Legendre points.
• TIMESTAMP prints the current YMDHMS date as a time stamp.
• VEC_COLEX_NEXT2 generates vectors in colex order.

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

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Last revised on 07 November 2009.