simpeg.potential_fields.gravity.SimulationEquivalentSourceLayer#

class simpeg.potential_fields.gravity.SimulationEquivalentSourceLayer(mesh, cell_z_top, cell_z_bottom, **kwargs)[source]#

Bases: BaseEquivalentSourceLayerSimulation, Simulation3DIntegral

Equivalent source layer simulations

Parameters:
meshdiscretize.BaseMesh

A 2D tensor or tree mesh defining discretization along the x and y directions

cell_z_topnumpy.ndarray or float

Define the elevations for the top face of all cells in the layer. If an array it should be the same size as the active cell set.

cell_z_bottomnumpy.ndarray or float

Define the elevations for the bottom face of all cells in the layer. If an array it should be the same size as the active cell set.

Attributes

G

Gravity forward operator

clean_on_model_update

A list of solver objects to clean when the model is updated

counter

SimPEG Counter object to store iterations and run-times.

deleteTheseOnModelUpdate

A list of properties stored on this object to delete when the model is updated

engine

Engine that will be used to run the simulation.

gtg_diagonal

Diagonal of GtG

ind_active

Active topography cells.

linear_model

The model for a linear problem physical property model.

mesh

Mesh for the simulation.

model

The inversion model.

model_deriv

Derivative of The model for a linear problem wrt the model.

model_map

Mapping of the inversion model to The model for a linear problem.

needs_model

True if a model is necessary

numba_parallel

Run simulation in parallel or single-threaded when using Numba.

rho

Density physical property model.

rhoDeriv

Derivative of Density wrt the model.

rhoMap

Mapping of the inversion model to Density.

sensitivity_dtype

dtype of the sensitivity matrix.

sensitivity_path

Path to directory where sensitivity file is stored.

solver

Numerical solver used in the forward simulation.

solver_opts

Solver-specific parameters.

store_sensitivities

Options for storing sensitivities.

survey

The survey for the simulation.

verbose

Verbose progress printout.

n_processes

Methods

Jtvec(m, v[, f])

Sensitivity transposed times a vector

Jtvec_approx(m, v[, f])

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

Jvec(m, v[, f])

Sensitivity times a vector

Jvec_approx(m, v[, f])

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

dpred([m, f])

Predicted data for the model provided.

evaluate_integral(receiver_location, components)

Compute the forward linear relationship between the model and the physics at a point and for all components of the survey.

fields(m)

Forward model the gravity field of the mesh on the receivers in the survey

getJ(m[, f])

Sensitivity matrix

getJtJdiag(m[, W, f])

Return the diagonal of JtJ

linear_operator()

Return linear operator.

make_synthetic_data(m[, relative_error, ...])

Make synthetic data for the model and Gaussian noise provided.

residual(m, dobs[, f])

The data residual.