autolens.SettingsInversion#

class SettingsInversion[source]#

Bases: object

The settings of an Inversion, customizing how a linear set of equations are solved for.

An Inversion is used to reconstruct a dataset, for example the luminous emission of a galaxy.

Parameters

  • use_w_tilde (bool) – Whether to use the w-tilde formalism to perform the inversion, which speeds up the construction of the simultaneous linear equations (by bypassing the construction of a mapping_matrix) for many dataset use cases.

  • use_positive_only_solver (Optional[bool]) – Whether to use a positive-only linear system solver, which requires that every reconstructed value is positive but is computationally much slower than the default solver (which allows for positive and negative values).

  • no_regularization_add_to_curvature_diag_value (Optional[float]) – If a linear func object does not have a corresponding regularization, this value is added to its diagonal entries of the curvature regularization matrix to ensure the matrix is positive-definite.

  • use_w_tilde_numpy (bool) – If True, the curvature_matrix is computed via numpy matrix multiplication (as opposed to numba functions which exploit sparsity to do the calculation normally in a more efficient way).

  • use_source_loop (bool) – Shhhh its a secret.

  • use_linear_operators (bool) – For an interferometer inversion, whether to use the linear operator solution to solve the linear system or not (this input does nothing for dataset data).

  • tolerance (float) – For an interferometer inversion using the linear operators method, sets the tolerance of the solver (this input does nothing for dataset data and other interferometer methods).

  • maxiter (int) – For an interferometer inversion using the linear operators method, sets the maximum number of iterations of the solver (this input does nothing for dataset data and other interferometer methods).

Methods

Attributes

no_regularization_add_to_curvature_diag_value

positive_only_uses_p_initial

use_positive_only_solver