simpeg.regularization.SmoothnessFirstOrder.deriv#

SmoothnessFirstOrder.deriv(m)[source]#

Gradient of the regularization function evaluated for the model provided.

Where \(\phi (\mathbf{m})\) is the discrete regularization function (objective function), this method evaluates and returns the derivative with respect to the model parameters; i.e. the gradient:

\[\frac{\partial \phi}{\partial \mathbf{m}}\]
Parameters:
m(n_param, ) numpy.ndarray

The model for which the gradient is evaluated.

Returns:
(n_param, ) numpy.ndarray

The Gradient of the regularization function evaluated for the model provided.