simpeg.potential_fields.magnetics.Simulation3DIntegral#

class simpeg.potential_fields.magnetics.Simulation3DIntegral(mesh, chi=None, chiMap=None, model_type='scalar', is_amplitude_data=False, engine='geoana', numba_parallel=True, **kwargs)[source]#

Bases: BasePFSimulation

Magnetic simulation in integral form.

Parameters:

meshdiscretize.TreeMesh or discretize.TensorMesh

Mesh use to run the magnetic simulation.

surveysimpeg.potential_fields.magnetics.Survey

Magnetic survey with information of the receivers.

active_cells(n_cells) numpy.ndarray, optional

Array that indicates which cells in mesh are active cells.

chinumpy.ndarray, optional

Susceptibility array for the active cells in the mesh.

chiMapMapping, optional

Model mapping.

model_typestr, optional

Whether the model are susceptibilities of the cells ("scalar"), or effective susceptibilities ("vector").

is_amplitude_databool, optional

If True, the returned fields will be the amplitude of the magnetic field. If False, the fields will be returned unmodified.

sensitivity_dtypenumpy.dtype, optional

Data type that will be used to build the sensitivity matrix.

store_sensitivities{“ram”, “disk”, “forward_only”}

Options for storing sensitivity matrix. There are 3 options

‘ram’: sensitivities are stored in the computer’s RAM
‘disk’: sensitivities are written to a directory
‘forward_only’: you intend only do perform a forward simulation and sensitivities do not need to be stored

sensitivity_pathstr, optional

Path to store the sensitivity matrix if store_sensitivities is set to "disk". Default to “./sensitivities”.

engine{“geoana”, “choclo”}, optional

Choose which engine should be used to run the forward model.

numba_parallelbool, optional

If True, the simulation will run in parallel. If False, it will run in serial. If engine is not "choclo" this argument will be ignored.

Attributes

`G`	The linear operator.
`M`	M: ndarray
`active_cells`	Active cells in the mesh.
`chi`	Magnetic susceptibility (si) physical property model.
`chiDeriv`	Derivative of Magnetic Susceptibility (SI) wrt the model.
`chiMap`	Mapping of the inversion model to Magnetic Susceptibility (SI).
`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.
`engine`	Engine that will be used to run the simulation.
`ind_active`	active_cells.ind_active has been deprecated.
`linear_model`	The model for a linear problem physical property model.
`mesh`	Mesh for the integral potential field simulations.
`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.
`model_type`	Type of magnetization model
`nD`	Number of data
`n_processes`	Number of processes to use for forward modeling.
`needs_model`	True if a model is necessary
`numba_parallel`	Run simulation in parallel or single-threaded when using Numba.
`sensitivity_dtype`	dtype of the sensitivity matrix.
`sensitivity_path`	Path to directory where sensitivity file is stored.
`store_sensitivities`	Options for storing sensitivities.
`survey`	The survey for the simulation.
`verbose`	Verbose progress printout.

ampDeriv
is_amplitude_data
tmi_projection

Methods

`Jtvec`(m, v[, f])	Dot product between transposed sensitivity matrix and a vector.
`Jtvec_approx`(m, v[, f])	Approximation of the Jacobian transpose times a vector for the model provided.
`Jvec`(m, v[, f])	Dot product between sensitivity matrix and a vector.
`Jvec_approx`(m, v[, f])	Approximation of the Jacobian times a vector for the model provided.
`compute_amplitude`(b_xyz)	Compute amplitude of the magnetic field
`dpred`([m, f])	Predicted data for the model provided.
`evaluate_integral`(receiver_location, components)	Load in the active nodes of a tensor mesh and computes the magnetic forward relation between a cuboid and a given observation location outside the Earth [obsx, obsy, obsz]
`fields`(model)	Return the computed geophysical fields for the model provided.
`getJ`(m[, f])	Sensitivity matrix \(\mathbf{J}\).
`getJtJdiag`(m[, W, f])	Compute diagonal of \(\mathbf{J}^T \mathbf{J}`\).
`linear_operator`()	Return linear operator.
`make_synthetic_data`(m[, relative_error, ...])	Make synthetic data for the model and Gaussian noise provided.
`normalized_fields`(fields)	Return the normalized B fields
`residual`(m, dobs[, f])	The data residual.