simpeg.base.BasePDESimulation#

class simpeg.base.BasePDESimulation(mesh, solver=None, solver_opts=None, **kwargs)[source]#

Base simulation for PDE solutions.

Parameters:

meshdiscretize.base.BaseMesh: Mesh on which the forward problem is discretized.
solvertype[pymatsolver.base.Base], optional: Numerical solver used to solve the forward problem. If None, an appropriate solver specific to the simulation class is set by default.
solver_optsdict, optional: Solver-specific parameters. If None, default parameters are used for the solver set by solver. Otherwise, the dict must contain appropriate pairs of keyword arguments and parameter values for the solver. Please visit pymatsolver to learn more about solvers and their parameters.

Attributes

`Mcc`	Cell center inner product matrix.
`Me`	Edge inner product matrix.
`MeI`	Edge inner product inverse matrix.
`Mf`	Face inner product matrix.
`MfI`	Face inner product inverse matrix.
`Mn`	Node inner product matrix.
`MnI`	Node inner product inverse matrix.
`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`	HasModel.deleteTheseOnModelUpdate has been deprecated.
`mesh`	Mesh for the simulation.
`model`	The inversion model.
`needs_model`	True if a model is necessary
`sensitivity_path`	Path to directory where sensitivity file is stored.
`solver`	Numerical solver used in the forward simulation.
`solver_opts`	Solver-specific parameters.
`survey`	The survey for the simulation.
`verbose`	Verbose progress printout.

MccI
Vol

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.
`make_synthetic_data`(m[, relative_error, ...])	Make synthetic data for the model and Gaussian noise provided.
`residual`(m, dobs[, f])	The data residual.