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function [lGrid, points] = tsgMakeGlobal(sGridName, iDim, iOut, s1D, sType, iDepth, mTransformAB, vAlphaBeta, vAnisotropy, lCustomRule, sConformalMap, vConfromalWeights, vLimitLevels)
%
% [lGrid, points] =
% tsgMakeGlobal(sGridName, iDim, iOut, s1D, sType, iDepth,
% mTransformAB, vAlphaBeta, vAnisotropy, lCustomRule,
% sConformalMap, vConfromalWeights)
%
% creates a new sparse grid using a global rule
%
% INPUT:
%
% sGridName: the name of the grid, give it a string name,
% i.e. 'myGrid' or '1' or 'pi314'
% DO NOT LEAVE THIS EMPTY
%
% iDim: (integer, positive)
% the number of inputs
%
% iOut: (integer, non-negative)
% the number of outputs
%
% s1D: (string for the underlying 1-D rule that induces the grid)
%
% Interpolation rules (Note: the quadrature induced by those rules is
% constructed by integrating the interpolant)
%
% 'clenshaw-curtis' 'clenshaw-curtis-zero' 'fejer2'
% 'leja' 'leja-odd' 'max-lebesgue' 'max-lebesgue-odd'
% 'rleja' 'rleja-odd' 'rleja-double2' 'rleja-double4'
% 'rleja-shifted' 'rleja-shifted-even'
% 'min-lebesgue' 'min-lebesgue-odd' 'min-delta' 'min-delta-odd'
%
% 'chebyshev' 'chebyshev-odd'
% approximation using roots of Chebyshev polynomials
% non-nested case (in contrast to Clenshaw-Curtis nodes)
% Note: the quadrature induced by those rules is
% constructed by integrating the interpolant
%
% Quadrature rules, the weights target exactness with respect to the
% highest polynomial degree possible
%
% 'gauss-legendre' 'gauss-legendre-odd'
% approximation using roots of polynomials orthogonal in
% measure Uniform
%
% 'gauss-patterson' (a.k.a. nested Gauss-Legendre)
% Note: the nodes and weights are hard-coded hence there
% is a limit on the highest possible depth
% Note: nestedness gives an interpolation rule
%
% 'gauss-chebyshev1' 'gauss-chebyshev1-odd'
% 'gauss-chebyshev2' 'gauss-chebyshev2-odd'
% approximation using roots of polynomials orthogonal in
% measures 1/sqrt(1-x^2) and sqrt(1-x^2) (respectively)
%
% 'gauss-gegenbauer' 'gauss-gegenbauer-odd'
% approximation using roots of polynomials orthogonal in
% measure (1-x^2)^alpha
%
% 'gauss-jacobi'
% approximation using roots of polynomials orthogonal in
% measure (1-x)^alpha * (1+x)^beta
%
% 'gauss-laguerre'
% approximation using roots of polynomials orthogonal in
% measure x^alpha * epx(-x)
%
% 'gauss-hermite' 'gauss-hermite-odd'
% approximation using roots of polynomials orthogonal in
% measure |x|^alpha * epx(-x^2)
%
% sType: (string giving the tensor selection strategy)
% 'level' 'curved' 'hyperbolic' 'tensor'
% 'iptotal' 'ipcurved' 'iphyperbolic' 'iptensor'
% 'qptotal' 'qpcurved' 'qphyperbolic' 'qptensor'
%
% iDepth: (integer non-negative)
% controls the density of the grid, i.e., the offset for the tensor
% selection, the meaning of iDepth depends on sType
% Example 1: sType == 'iptotal' will give a grid that interpolates
% exactly all polynomials of degree up to and including iDepth
% Example 2: sType == 'qptotal' will give a grid that integrates
% exactly all polynomials of degree up to and including iDepth
%
% vAnisotropy: (optional vector of positive integers, length iDim or 2*iDim)
% the anisotropic weights associated with sType
%
% vAlphaBeta: (optional vector of length 1 or 2)
% vAlphaBeta(1) is the alpha parameter for Gegenbauer, Jacobi,
% Hermite and Laguerre rules
% vAlphaBeta(2) is the beta parameter for Jacobi rules
%
% mTransformAB: (optional matrix of size iDim x 2)
% for all but gauss-laguerre and gauss-hermite grids, the
% transform specifies the lower and upper bound of the domain
% in each direction. For gauss-laguerre and gauss-hermite
% grids, the transform gives the a and b parameters that
% change the weight to
% exp(-b (x - a)) and exp(-b (x - a)^2)
%
% lCustomRule: (global grids of custom-tabulated rule)
% custom_rule can be either of 3 things:
%
% string containing filename with a defined custom name
%
% structure containing the filed lCustomRule.sFilename,
% which is the name of a file containing the user defined
% rule
%
% structure defining the fields
% lCustomRule.sDescription
% lCustomRule.iMaxLevel
% lCustomRule.vLevels
% lCustomRule.vPrecision
% lCustomRule.vNodes
% lCustomRule.vWeights
%
% see help tsgWriteCustomRuleFile.m for definition of
% each field of the structure
%
% sConformalMap: (optional string giving the type of transform)
% conformal maps provide a non-linear domain transform,
% approximation (quadrature or interpolation) is done
% on the composition of f and the transform. A suitable
% transform could reduce the error by as much as an
% order of magnitude.
%
% 'asin': truncated MacLaurin series of arch-sin
%
% vConfromalWeights: (optional parameters for the conformal trnasform)
% 'asin': indicate the number of terms to keep after
% truncation
%
% vLimitLevels: (optional vector of integers of size iDim)
% limit the level in each direction, no points beyond the
% specified limit will be used, e.g., in 2D using
% clenshaw-curtis rule, [1, 99] forces the grid to have
% at most 3 possible values in the first variable and
% ~2^99 (practicallyt infinite) number in the second
% direction. vLimitLevels works in conjunction with
% iDepth and sType, the points added to the grid will
% obey both bounds
%
% OUTPUT:
%
% lGrid: list containing information about the sparse grid, can be used
% to call other functions
%
% points: (optional) the points of the grid in an array
% of dimension [num_poits, dim]
%
% [lGrid, points] =
% tsgMakeGlobal(sGridName, iDim, iOut, s1D, sType, iDepth,
% mTransformAB, vAlphaBeta, vAnisotropy, lCustomRule,
% sConformalMap, vConfromalWeights)%
if (~isnumeric(iDim) || ~isreal(iDim) || ~(rem(iDim,1) == 0) || ~(sum(size(iDim) == [1,1])) || ~(iDim > 0))
error('iDim must be a positive integer')
end
if (~isnumeric(iOut) || ~isreal(iOut) || ~(rem(iOut,1) == 0) || ~(sum(size(iOut) == [1,1])) || ~(iOut > 0))
error('iOut must be a positive integer')
end
% create lGrid object
lGrid.sName = sGridName;
lGrid.sFilename = tsgMakeGridFilename(sGridName);
lGrid.iDim = iDim;
lGrid.iOut = iOut;
lGrid.sType = 'global';
% check for conflict with tsgMakeQuadrature
if (strcmp(sGridName, ''))
error('sGridName cannot be empty');
end
% generate filenames
[sFiles, sTasGrid] = tsgGetPaths();
[sFileG, sFileX, sFileV, sFileO, sFileW, sFileC, sFileL] = tsgMakeFilenames(lGrid);
sCommand = [sTasGrid,' -makeglobal'];
sCommand = [sCommand, ' -gridfile ', sFileG];
sCommand = [sCommand, ' -dimensions ', num2str(lGrid.iDim)];
sCommand = [sCommand, ' -outputs ', num2str(lGrid.iOut)];
sCommand = [sCommand, ' -onedim ', s1D];
sCommand = [sCommand, ' -depth ', num2str(iDepth)];
sCommand = [sCommand, ' -type ', sType];
% set the domain transformation
if (exist('mTransformAB') && (max(size(mTransformAB)) ~= 0))
if (size(mTransformAB, 2) ~= 2)
error(' mTransformAB must be a matrix with 2 columns');
end
if (size(mTransformAB, 1) ~= lGrid.iDim)
error(' mTransformAB must be a matrix with iDim number of rows');
end
tsgWriteMatrix(sFileV, mTransformAB);
lClean.sFileV = 1;
sCommand = [sCommand, ' -tf ',sFileV];
end
% set anisotropy
if (exist('vAnisotropy') && (max(size(vAnisotropy)) ~= 0))
if (min(size(vAnisotropy)) ~= 1)
error(' vAnisotropy must be a vector, i.e., one row or one column');
end
if (max(size(vAnisotropy)) ~= lGrid.iDim)
error(' vAnisotropy must be a vector of size iDim');
end
if (size(vAnisotropy, 1) > size(vAnisotropy, 2))
tsgWriteMatrix(sFileW, vAnisotropy');
else
tsgWriteMatrix(sFileW, vAnisotropy);
end
lClean.sFileW = 1;
sCommand = [sCommand, ' -anisotropyfile ', sFileW];
end
% set alpha and beta
if (exist('vAlphaBeta') && (max(size(vAlphaBeta)) ~= 0))
if (min(size(vAlphaBeta)) ~= 1)
error(' vAlphaBeta must be a vector, i.e., one row or one column');
end
if (max(size(vAlphaBeta)) > 2)
error(' vAlphaBeta must be a vector of size at most 2');
end
sCommand = [sCommand, ' -alpha ',num2str(vAlphaBeta(1), 16)];
if (max(size(vAlphaBeta)) > 1)
sCommand = [sCommand, ' -beta ',num2str(vAlphaBeta(2), 16)];
end
end
% set custom rule
if (strcmp(s1D, 'custom-tabulated'))
if (exist('lCustomRule'))
if (ischar(lCustomRule))
sCommand = [sCommand, ' -cf ', lCustomRule];
elseif (isfield(lCustomRule, 'filename')) % DEPRECATED syntax, do this for backward compatibility
sCommand = [sCommand, ' -cf ', lCustomRule.filename];
elseif (isfield(lCustomRule, 'sFilename'))
sCommand = [sCommand, ' -cf ', lCustomRule.sFilename];
else
tsgWriteCustomRuleFile(sFileX, lCustomRule);
lClean.sFileX = 1;
sCommand = [sCommand, ' -cf ', sFileX];
end
else
disp(['ERROR: must provide a lCustomRule variable to use with a custom rule']);
return;
end
end
% set conformal mapping
if (exist('sConformalMap') && (max(size(sConformalMap)) ~= 0))
if (~exist('vConfromalWeights'))
error(' sConformalMap requires vConfromalWeights')
end
sCommand = [sCommand, ' -conformaltype ', sConformalMap];
if (size(vConfromalWeights, 1) > size(vConfromalWeights, 2))
tsgWriteMatrix(sFileC, vConfromalWeights');
else
tsgWriteMatrix(sFileC, vConfromalWeights);
end
lClean.sFileC = 1;
sCommand = [sCommand, ' -conformalfile ', sFileC];
end
% set level limits
if (exist('vLimitLevels') && (max(size(vLimitLevels)) ~= 0))
if (min(size(vLimitLevels)) ~= 1)
error(' vLimitLevels must be a vector, i.e., one row or one column');
end
if (max(size(vLimitLevels)) ~= lGrid.iDim)
error(' vLimitLevels must be a vector of size iDim');
end
if (size(vLimitLevels, 1) > size(vLimitLevels, 2))
tsgWriteMatrix(sFileL, vLimitLevels');
else
tsgWriteMatrix(sFileL, vLimitLevels);
end
lClean.sFileL = 1;
sCommand = [sCommand, ' -levellimitsfile ', sFileL];
end
% read the points for the grid
if (nargout > 1)
sCommand = [sCommand, ' -of ', sFileO];
lClean.sFileO = 1;
end
[status, cmdout] = system(sCommand);
if (max(size(strfind(cmdout, 'ERROR'))) ~= 0)
disp(cmdout);
error('The tasgrid execurable returned an error, see above');
return;
else
if (~isempty(cmdout))
fprintf(1,['WARNING: Command had non-empty output:\n']);
disp(cmdout);
end
if (nargout > 1)
points = tsgReadMatrix(sFileO);
end
end
if (exist('lClean'))
tsgCleanTempFiles(lGrid, lClean);
end
end
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