simpeg.utils.distance_weighting

simpeg.utils.distance_weighting(mesh, reference_locs, active_cells=None, exponent=2.0, threshold=None, engine='numba', cdist_opts=None)

Construct diagonal elements of a distance weighting matrix

Builds the model weights following the distance weighting strategy, a method to generate weights based on the distance between mesh cell centers and some reference location(s). Use these weights in regularizations to counteract the natural decay of potential field data with distance.

Parameters:

meshdiscretize.base.BaseMesh

Discretized model space.

reference_locs(n, ndim) numpy.ndarray

The coordinate of the reference location, usually the receiver locations, for the distance weighting. A 2d array, with multiple reference locations, where each row should contain the coordinates of a single location point in the following order: _x_, _y_, _z_ (for 3D meshes) or _x_, _z_ (for 2D meshes).

active_cells(mesh.n_cells) numpy.ndarray of bool, optional

Index vector for the active cells on the mesh. If None, every cell will be assumed to be active.

exponentfloat or None, optional

Exponent parameter for distance weighting. The exponent should match the natural decay power of the potential field. For example, for gravity acceleration, set it to 2; for magnetic fields, to 3.

thresholdfloat or None, optional

Threshold parameters used in the distance weighting. If None, it will be set to half of the smallest cell width.

engine: str, ‘numba’ or ‘scipy’

Pick between a scipy.spatial.distance.cdist computation (memory intensive) or for loop implementation, parallelized with numba if available. Default to "numba".

cdist_opts: dict, optional

Only valid with engine=="scipy". Options to pass to scipy.spatial.distance.cdist. Default to None.

Returns:

(n_active) numpy.ndarray

Normalized distance weights for the mesh at every active cell as a 1d-array.