simpeg.electromagnetics.static.resistivity.Simulation1DLayers#

class simpeg.electromagnetics.static.resistivity.Simulation1DLayers(survey=None, sigma=None, sigmaMap=None, rho=None, rhoMap=None, thicknesses=None, thicknessesMap=None, hankel_filter='key_201_2012', fix_Jmatrix=False, **kwargs)[source]#

Bases: BaseSimulation

1D DC Simulation

Attributes

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

fix_Jmatrix

Whether to fix the sensitivity matrix between iterations.

hankel_filter

The hankel filter key.

mesh

Mesh for the simulation.

model

The inversion model.

needs_model

True if a model is necessary

rho

Electrical resistivity (ohm m) physical property model.

rhoDeriv

Derivative of Electrical resistivity (Ohm m) wrt the model.

rhoMap

Mapping of the inversion model to Electrical resistivity (Ohm m).

sensitivity_path

Path to directory where sensitivity file is stored.

sigma

Electrical conductivity (s/m) physical property model.

sigmaDeriv

Derivative of Electrical conductivity (S/m) wrt the model.

sigmaMap

Mapping of the inversion model to Electrical conductivity (S/m).

solver

Numerical solver used in the forward simulation.

solver_opts

Solver-specific parameters.

storeJ

Whether to store the sensitivity matrix.

survey

The DC survey object.

thicknesses

Thicknesses of the layers physical property model.

thicknessesDeriv

Derivative of thicknesses of the layers wrt the model.

thicknessesMap

Mapping of the inversion model to thicknesses of the layers.

verbose

Verbose progress printout.

Methods

Jtvec(m, v[, f])

Compute adjoint sensitivity matrix (J^T) and vector (v) product.

Jtvec_approx(m, v[, f])

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

Jvec(m, v[, f])

Compute sensitivity matrix (J) and vector (v) product.

Jvec_approx(m, v[, f])

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

dpred([m, f])

Project fields to receiver locations :param Fields u: fields object :rtype: numpy.ndarray :return: data

fields(m)

Return the computed geophysical fields for the model provided.

getJ(m[, f, factor])

Generate Full sensitivity matrix using central difference

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

Make synthetic data for the model and Gaussian noise provided.

residual(m, dobs[, f])

The data residual.

Galleries and Tutorials using simpeg.electromagnetics.static.resistivity.Simulation1DLayers#

Simulate a 1D Sounding over a Layered Earth

Simulate a 1D Sounding over a Layered Earth

Least-Squares 1D Inversion of Sounding Data

Least-Squares 1D Inversion of Sounding Data

Sparse 1D Inversion of Sounding Data

Sparse 1D Inversion of Sounding Data

Parametric 1D Inversion of Sounding Data

Parametric 1D Inversion of Sounding Data