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.
- m(
- Returns:
- (
n_param, )numpy.ndarray The Gradient of the regularization function evaluated for the model provided.
- (