BarycentricDictOperator#

class minterpy.schemes.barycentric.operators.BarycentricDictOperator(transformation, transformation_data)[source]#

Bases: BarycentricOperator

Concrete implementation of the BarycentricOperator given by the edge case given by decomposition to the 1D atomic sub-problems.

Properties

`array_repr_full`	Array representation of the global transformation matrix.
`array_repr_sparse`	Array representation of the sub-transformation matrix transforming only the active monomials.
`array_representation`	Reconstructs the global transformation matrix.

Methods

`merging_fct`(leaf_positions)	Reconstructing the global transformation matrix from the precomputed transformation in dictionary format.
`transformation_fct`(coeffs_out, trafo_dict, ...)	Transformation using a dictionary encoding (= a triangular array piece for every leaf node combination).

Parameters:: transformation (TransformationABC)

transformation_fct(coeffs_out, trafo_dict, leaf_positions)#

Transformation using a dictionary encoding (= a triangular array piece for every leaf node combination).

Parameters:

coeffs_in (ndarray) – the coefficients to be transformed
coeffs_out (ndarray) – a placeholder for the output coefficients
trafo_dict (Dict[Tuple[int, int], ndarray]) – dictionary with matrix pieces
leaf_positions (ndarray) – starting positions in the input and output coeffs arrays

Return type:

None

Notes

Depending on the problem size it might be more performant to use a different implementation of this transformation! (e.g. regular DDS or leaf level DDS (factorised format)

Transforms and sums up the respective parts (slices) of the coefficients.

merging_fct(leaf_positions)#

Reconstructing the global transformation matrix from the precomputed transformation in dictionary format.

Parameters:

trafo_dict (Dict[Tuple[int, int], ndarray]) – transformation dictionary
leaf_positions (ndarray) – leaf positions

Returns:

reconstructed transformation matrix

Return type:

ndarray

__init__(transformation, transformation_data)#

Parameters:: transformation (TransformationABC)

__matmul__(other)#

Applies the transformation operator on the input.

Parameters:: other (OperatorABC | ndarray)
Return type:: MatrixOperator | ndarray

__weakref__#: list of weak references to the object (if defined)

_get_array_repr()#: Reconstructs the global transformation matrix.

property array_repr_full: ndarray#

Array representation of the global transformation matrix.

Returns:: the matrix representation of the transformation.

Notes

The output transforms the whole basis (not only the active monomials)!

property array_repr_sparse: ndarray#

Array representation of the sub-transformation matrix transforming only the active monomials.

Returns:: the transformation matrix for the active monomials.

Notes

This is an experimental feature which is part of ongoing work.

property array_representation: ndarray#: Reconstructs the global transformation matrix.