# SGMGA Sparse Grid Mixed Growth Anisotropic Rules.

SGMGA is a MATLAB library which implements a family of sparse grid rules. These rules are "mixed", in that a different 1D quadrature rule can be specified for each dimension. Moreover, each 1D quadrature rule comes in a family of increasing size whose growth rate (typically linear or exponential) is chosen by the user. Finally, the user may also specify different weights for each dimension, resulting in anisotropic rules.

SGMGA calls many routines from the SANDIA_RULES library. Copies of both libraries must be available when a program wishes to use the SGMGA library.

Thanks to Drew Kouri, who pointed out a discrepancy in the computation of the variable level_1d_max which meant that certain sparse grids requested the generation of a 1D rule of a level that was higher than necessary by 1. In particular, if the Gauss-Patterson rule was involved, sparse grids that actually only needed rules of level 7 would ask also for level 8, resulting in the computation being terminated. This problem was corrected on 25 April 2011.

Index Name Abbreviation Default Growth Rule Interval Weight function
1 Clenshaw-Curtis CC Moderate Exponential [-1,+1] 1
2 Fejer Type 2 F2 Moderate Exponential [-1,+1] 1
3 Gauss Patterson GP Moderate Exponential [-1,+1] 1
4 Gauss-Legendre GL Moderate Linear [-1,+1] 1
5 Gauss-Hermite GH Moderate Linear (-oo,+oo) e-x*x
6 Generalized Gauss-Hermite GGH Moderate Linear (-oo,+oo) |x|alpha e-x*x
7 Gauss-Laguerre LG Moderate Linear [0,+oo) e-x
8 Generalized Gauss-Laguerre GLG Moderate Linear [0,+oo) xalpha e-x
9 Gauss-Jacobi GJ Moderate Linear [-1,+1] (1-x)alpha (1+x)beta
10 Hermite Genz-Keister HGK Moderate Exponential (-oo,+oo) e-x*x
11 User Supplied Open UO Moderate Linear ? ?
12 User Supplied Closed UC Moderate Linear ? ?

For a given family, a growth rule can be prescribed, which determines the orders O of the sequence of rules selected from the family. The selected rules are indexed by L, which starts at 0. The polynomial precision P of the rule is sometimes used to determine the appropriate order O.
Index Name Order Formula
0 Default "DF", moderate exponential or moderate linear
1 "SL", Slow linear O=L+1
2 "SO", Slow Linear Odd O=1+2*((L+1)/2)
3 "ML", Moderate Linear O=2L+1
4 "SE", Slow Exponential select smallest exponential order O so that 2L+1 <= P
5 "ME", Moderate Exponential select smallest exponential order O so that 4L+1 <= P
6 "FE", Full Exponential O=2^L+1 for Clenshaw Curtis, O=2^(L+1)-1 otherwise.

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

### Languages:

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

### Related Data and Programs:

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

NINT_EXACTNESS_MIXED, a MATLAB program which measures the polynomial exactness of a multidimensional quadrature rule based on a mixture of 1D quadrature rule factors.

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

SANDIA_RULES, a MATLAB library which generates Gauss quadrature rules of various orders and types.

SANDIA_SGMGG, a MATLAB library which explores a generalized construction method for sparse grids.

SANDIA_SPARSE, a MATLAB library which computes the points and weights of a Smolyak sparse grid, based on a variety of 1-dimensional quadrature rules.

SGMGA, a dataset directory which contains SGMGA files (Sparse Grid Mixed Growth Anisotropic), that is, multidimensional Smolyak sparse grids based on a mixture of 1D rules, and with a choice of exponential and linear growth rates for the 1D rules and anisotropic weights for the dimensions.

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, by Knut Petras.

SPARSE_GRID_CC, a MATLAB library which can define a multidimensional sparse grid based on a 1D Clenshaw Curtis rule.

SPARSE_GRID_GL, a MATLAB library which creates sparse grids based on Gauss-Legendre rules.

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

SPARSE_GRID_HW, a MATLAB library which creates sparse grids based on Gauss-Legendre, Gauss-Hermite, Gauss-Patterson, or a nested variation of Gauss-Hermite rules, by Florian Heiss and Viktor Winschel.

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

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

SPINTERP, a MATLAB library which carries out piecewise multilinear hierarchical sparse grid interpolation; an earlier version of this software is ACM TOMS Algorithm 847, by Andreas Klimke;

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:

1. Milton Abramowitz, Irene Stegun,
Handbook of Mathematical Functions,
National Bureau of Standards, 1964,
ISBN: 0-486-61272-4,
LC: QA47.A34.
2. Charles Clenshaw, Alan Curtis,
A Method for Numerical Integration on an Automatic Computer,
Numerische Mathematik,
Volume 2, Number 1, December 1960, pages 197-205.
3. Philip Davis, Philip Rabinowitz,
Methods of Numerical Integration,
Second Edition,
Dover, 2007,
ISBN: 0486453391,
LC: QA299.3.D28.
4. Walter Gautschi,
Numerical Quadrature in the Presence of a Singularity,
SIAM Journal on Numerical Analysis,
Volume 4, Number 3, September 1967, pages 357-362.
5. Thomas Gerstner, Michael Griebel,
Numerical Integration Using Sparse Grids,
Numerical Algorithms,
Volume 18, Number 3-4, 1998, pages 209-232.
6. Gene Golub, John Welsch,
Mathematics of Computation,
Volume 23, Number 106, April 1969, pages 221-230.
7. Prem Kythe, Michael Schaeferkotter,
Handbook of Computational Methods for Integration,
Chapman and Hall, 2004,
ISBN: 1-58488-428-2,
LC: QA299.3.K98.
8. Albert Nijenhuis, Herbert Wilf,
Combinatorial Algorithms for Computers and Calculators,
Second Edition,
ISBN: 0-12-519260-6,
LC: QA164.N54.
9. 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.
10. Fabio Nobile, Raul Tempone, Clayton Webster,
An Anisotropic Sparse Grid Stochastic Collocation Method for Partial Differential Equations with Random Input Data,
SIAM Journal on Numerical Analysis,
Volume 46, Number 5, 2008, pages 2411-2442.
11. Thomas Patterson,
Mathematics of Computation,
Volume 22, Number 104, October 1968, pages 847-856.
12. Knut Petras,
Smolyak Cubature of Given Polynomial Degree with Few Nodes for Increasing Dimension,
Numerische Mathematik,
Volume 93, Number 4, February 2003, pages 729-753.
13. Sergey Smolyak,
Quadrature and Interpolation Formulas for Tensor Products of Certain Classes of Functions,
Volume 4, 1963, pages 240-243.
14. Arthur Stroud, Don Secrest,
Prentice Hall, 1966,
LC: QA299.4G3S7.
15. Joerg Waldvogel,
Fast Construction of the Fejer and Clenshaw-Curtis Quadrature Rules,
BIT Numerical Mathematics,
Volume 43, Number 1, 2003, pages 1-18.

### Examples and Tests:

SGMGA_ANISO_BALANCE_TEST tests SGMGA_ANISO_BALANCE.

SGMGA_ANISO_NORMALIZE_TEST tests b>SGMGA_ANISO_NORMALIZE.

SGMGA_IMPORTANCE_TO_ANISO_TEST tests SGMGA_IMPORTANCE_TO_ANISO.

SGMGA_INDEX_TEST tests SGMGA_INDEX:

SGMGA_POINT_TEST tests SGMGA_POINT:

SGMGA_PRODUCT_WEIGHT_TEST tests SGMGA_PRODUCT_WEIGHT:

SGMGA_SIZE_TEST tests SGMGA_SIZE and SGMGA_SIZE_TOTAL:

SGMGA_SIZE_TABLE tabulates the point counts from SGMGA_SIZE for an isotropic rule over a range of dimensions and levels.

SGMGA_UNIQUE_INDEX_TEST tests SGMGA_UNIQUE_INDEX:

SGMGA_VCN_TEST tests SGMGA_VCN:

SGMGA_VCN_COEF_TEST tests SGMGA_VCN_COEF:

SGMGA_VCN_ORDERED_TEST tests SGMGA_VCN_ORDERED:

SGMGA_VCN_TIMING_TEST times SGMGA_VCN and SGMGA_VCN_NAIVE:

SGMGA_WEIGHT_TEST tests SGMGA_WEIGHT:

SGMGA_WRITE_TEST tests SGMGA_WRITE:

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

Last revised on 20 May 2010.