simpeg.simulation.LinearSimulation.getJ#
- LinearSimulation.getJ(m, f=None)[source]#
Returns the full Jacobian.
The general definition of the linear forward simulation is:
\[\mathbf{d} = \mathbf{G \, f}(\mathbf{m})\]where \(\mathbf{f}\) is a mapping operator (optional) from the model space to a user-defined parameter space, and \(\mathbf{G}\) is an (n_data, n_param) linear operator. The
getJ
method forms and returns the full Jacobian:\[\mathbf{J}(\mathbf{m}) = \mathbf{G} \frac{\partial \mathbf{f}}{\partial \mathbf{m}}\]for the model \(\mathbf{m}\) provided. When \(\mathbf{f}\) is the identity map (default), the Jacobian is no longer model-dependent and reduces to:
\[\mathbf{J} = \mathbf{G}\]- Parameters:
- m
numpy.ndarray
The model vector.
- f
None
Precomputed fields are not used to speed up the computation of the Jacobian for linear problems.
- m
- Returns:
- J(
n_data
,n_param
)numpy.ndarray
\(J = G\frac{\partial f}{\partial\mathbf{m}}\). Where \(f\) is
model_map
.
- J(