inversion_ideas.create_tikhonov_regularization

inversion_ideas.create_tikhonov_regularization(mesh, *, active_cells=None, cell_weights=None, reference_model=None, alpha_s=None, alpha_x=None, alpha_y=None, alpha_z=None, reference_model_in_flatness=False)

Create a linear combination of Tikhonov (L2) regularization terms.

Define a inversion_ideas.base.Combo with L2 smallness and flatness regularization terms.

Parameters:

meshdiscretize.base.BaseMesh

Mesh to use in the regularization.

active_cells(n_cells) array or None, optional

Array full of bools that indicate the active cells in the mesh. It must have the same amount of elements as cells in the mesh.

cell_weights(n_params) array or dict of (n_params) arrays or None, optional

Array with cell weights. For multiple cell weights, pass a dictionary where keys are strings and values are the different weights arrays. If None, no cell weights are going to be used.

reference_model(n_params) array or None, optional

Array with values for the reference model.

alpha_sfloat or None, optional

Multiplier for the smallness term.

alpha_x, alpha_y, alpha_zfloat or None, optional

Multipliers for the flatness terms.

Returns:

inversion_ideas.base.Combo

Combo of L2 regularization terms.

Notes

TODO