SimPEG.potential_fields.base.BaseEquivalentSourceLayerSimulation#
- class SimPEG.potential_fields.base.BaseEquivalentSourceLayerSimulation(mesh, cell_z_top, cell_z_bottom, **kwargs)[source]#
- Bases: - BasePFSimulation- Base equivalent source layer simulation class. - Parameters:
- meshdiscretize.BaseMesh
- A 2D tensor or tree mesh defining discretization along the x and y directions 
- cell_z_topnumpy.ndarrayorfloat
- 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.ndarrayorfloat
- 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. 
 
- mesh
 - Attributes - The linear operator. - A list of solver objects to clean when the model is updated - SimPEG - Counterobject to store iterations and run-times.- A list of properties stored on this object to delete when the model is updated - Active topography cells. - The model for a linear problem physical property model. - Mesh for the simulation. - The inversion model. - Derivative of The model for a linear problem wrt the model. - Mapping of the inversion model to The model for a linear problem. - True if a model is necessary - dtype of the sensitivity matrix. - Path to directory where sensitivity file is stored. - Numerical solver used in the forward simulation. - Solver-specific parameters. - Options for storing sensitivities. - The survey for the simulation. - Verbose progress printout. - n_processes - Methods - Jtvec(m, v[, f])- Compute the Jacobian transpose times a vector for the model provided. - Jtvec_approx(m, v[, f])- Approximation of the Jacobian transpose times a vector for the model provided. - Jvec(m, v[, f])- Compute the Jacobian times a vector for the model provided. - 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. - fields(m)- Return the computed geophysical fields for the model provided. - getJ(m[, f])- Returns the full Jacobian. - 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.