simpeg.regularization.SmoothnessSecondOrder.deriv#

SmoothnessSecondOrder.deriv(m)[source]#

Gradient of the regularization function evaluated for the model provided.

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

$$\frac{\partial \varphi }{\partial \mathbf{m}}$$

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.