SimPEG.regularization.CrossGradient.deriv#
- CrossGradient.deriv(model)[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. For a model \(\mathbf{m}\) consisting of two physical properties such that:
\[\begin{split}\mathbf{m} = \begin{bmatrix} \mathbf{m_1} \\ \mathbf{m_2} \end{bmatrix}\end{split}\]The gradient has the form:
\[\begin{split}2 \frac{\partial \phi}{\partial \mathbf{m}} = \begin{bmatrix} \dfrac{\partial \phi}{\partial \mathbf{m_1}} \\ \dfrac{\partial \phi}{\partial \mathbf{m_2}} \end{bmatrix}\end{split}\]- Parameters:
- model(
n_param
, )numpy.ndarray
The model; a vector array containing all physical properties.
- model(
- Returns:
- (
n_param
, )numpy.ndarray
Gradient of the regularization function evaluated for the model provided.
- (