sgpykit.tools.converter_functions

Functions

asreduced(pts_list[, wgs_list])

Construct a reduced sparse grid structure from given points and weights.

tensor_to_sparse(T[, idx])

Convert a tensor grid into a sparse grid structure.
sgpykit.tools.converter_functions.asreduced(pts_list, wgs_list=None)[source]

Construct a reduced sparse grid structure from given points and weights.

Parameters:
pts_listarray_like

List of knot points. The “knots” field of the returned sparse grid structure is set to this list.

wgs_listarray_like, optional

List of weights corresponding to the knot points. If provided, the “weights” field of the returned sparse grid structure is set to this list. The default is None.

Returns:
Sstruct

A reduced sparse grid structure with the following fields: - knots : array_like

The knot points.

  • weightsarray_like

    The weights corresponding to the knot points.

  • sizeint

    The number of knot points.

  • nlist

    Empty list.

  • mlist

    Empty list.

Raises:
ValueError

If the number of points and weights are different.

Notes

The knots in pts_list are assumed to be all different; the list is not checked for duplicates.

sgpykit.tools.converter_functions.tensor_to_sparse(T, idx=None)[source]

Convert a tensor grid into a sparse grid structure.

This function converts a tensor grid into a sparse grid structure of the same type as CREATE_SPARSE_GRID, by adding the missing fields.

Parameters:
TStruct

The tensor grid to be converted.

idxarray_like, optional

The index vector. If not provided, it will be computed based on the knots per dimension.

Returns:
SStruct or StructArray

The sparse grid structure with added fields.

Notes

The function copies the fields of T into S and adds the following:

  • S.coeff = 1

  • S.idx = vector with idx(i) = length(T.knots_per_dim{i}) if idx is not provided

  • S.idx = idx if idx is provided