simpeg.meta.MultiprocessingSumMetaSimulation.Jtvec#
- MultiprocessingSumMetaSimulation.Jtvec(m, v, f=None)[source]#
Compute the Jacobian transpose 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
predicted for a set of model parameters , the Jacobian is an(n_data, n_param)
matrix whose elements are given by:For a model m and vector v, the
Jtvec
method computes the matrix-vector product with the adjoint-sensitivity- Parameters:
- m(
n_param
, )numpy.ndarray
The model parameters.
- v(
n_data
, )numpy.ndarray
Vector we are multiplying.
- f
simpeg.field.Fields
,optional
If provided, fields will not need to be recomputed for the current model to compute Jtvec.
- m(
- Returns:
- (
n_param
, )numpy.ndarray
The Jacobian transpose times a vector for the model and vector provided.
- (