SimPEG.meta.MultiprocessingRepeatedSimulation.Jvec_approx#

MultiprocessingRepeatedSimulation.Jvec_approx(m, v, f=None)[source]#

Approximation of the Jacobian times a vector for the model provided.

The Jacobian defines the derivative of the predicted data vector with respect to the model parameters. For a data vector d predicted for a set of model parameters m, the Jacobian is an (n_data, n_param) matrix whose elements are given by:

Jij=dimj

For a model m and vector v, the Jvec_approx method approximates the matrix-vector product:

u=Jv
Parameters:
m(n_param, ) numpy.ndarray

The model parameters.

v(n_data, ) numpy.ndarray

Vector we are multiplying.

fSimPEG.field.Fields, optional

If provided, fields will not need to be recomputed for the current model to compute Jtvec.

Returns:
(n_param, ) numpy.ndarray

Approximation of the Jacobian times a vector for the model provided.