autoarray.inversion.regularization.Constant

class Constant

Bases: AbstractRegularization

Regularization which uses the neighbors of the mesh (e.g. shared Voronoi vertexes) and a single value to smooth an inversion’s solution.

For this regularization scheme, there is only 1 regularization coefficient that is applied to all neighboring pixels / parameters. This means that the matrix B only needs to regularize pixels / parameters in one direction (e.g. pixel 0 regularizes pixel 1, but NOT visa versa). For example:

B = [-1, 1] [0->1]

[0, -1] 1 does not regularization with 0

A small numerical value of 1.0e-8 is added to all elements in constant regularization matrix, to ensure that it is positive definite.

A full description of regularization and this matrix can be found in the parent AbstractRegularization class.

Parameters:

coefficient (float) – The regularization coefficient which controls the degree of smooth of the inversion reconstruction.

Methods

regularization_matrix_from	Returns the regularization matrix with shape [pixels, pixels].
regularization_weights_from	Returns the regularization weights of this regularization scheme.

regularization_weights_from(linear_obj)

Returns the regularization weights of this regularization scheme.

The regularization weights define the level of regularization applied to each parameter in the linear object (e.g. the pixels in a Mapper).

For standard regularization (e.g. Constant) are weights are equal, however for adaptive schemes (e.g. AdaptiveBrightness) they vary to adapt to the data being reconstructed.

Parameters:

linear_obj (LinearObj) – The linear object (e.g. a Mapper) which uses these weights when performing regularization.

Return type:

The regularization weights.

regularization_matrix_from(linear_obj)

Returns the regularization matrix with shape [pixels, pixels].

Parameters:

linear_obj (LinearObj) – The linear object (e.g. a Mapper) which uses this matrix to perform regularization.

Return type:

The regularization matrix.