SimPEG.regularization.WeightedLeastSquares.deriv#
- WeightedLeastSquares.deriv(m, f=None)[source]#
Gradient of the objective function evaluated for the model provided.
Where \(\phi (\mathbf{m})\) is the 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 objective function evaluated for the model provided.
- (