simpeg.potential_fields.gravity.SimulationEquivalentSourceLayer#

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

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.