SimPEG.data_misfit.BaseDataMisfit#
- class SimPEG.data_misfit.BaseDataMisfit(data, simulation, debug=False, counter=None, **kwargs)[source]#
- Bases: - L2ObjectiveFunction- Base data misfit class. - Inherit this class to build your own data misfit function. The - BaseDataMisfitclass inherits the- SimPEG.objective_function.L2ObjectiveFunction. And as a result, it is limited to building data misfit functions of the form:- Important - This class is not meant to be instantiated. You should inherit from it to create your own data misfit class. \[\phi_d (\mathbf{m}) = \| \mathbf{W} f(\mathbf{m}) \|_2^2\]- where \(\mathbf{m}\) is the model vector, \(\mathbf{W}\) is a linear weighting matrix, and \(f\) is a mapping function that acts on the model. - Parameters:
- dataSimPEG.data.Data
- A SimPEG data object. 
- simulationSimPEG.simulation.BaseSimulation
- A SimPEG simulation object. 
- debugbool
- Print debugging information. 
- counterNoneorSimPEG.utils.Counter
- Assign a SimPEG - Counterobject to store iterations and run-times.
 
- data
 - Attributes - The data weighting matrix. - SimPEG - Counterobject to store iterations and run-times.- A SimPEG data object. - Print debugging information. - Mapping from the model to the quantity evaluated in the object function. - Number of data. - Number of model parameters. - Shape of the Jacobian. - A SimPEG simulation object. - Methods - __call__(m)- Evaluate the objective function for a given model. - deriv(m)- Gradient of the objective function evaluated for the model provided. - deriv2(m[, v])- Hessian of the objective function evaluated for the model provided. - map_class- alias of - IdentityMap- residual(m[, f])- Computes the data residual vector for a given model. - test([x, num])- Run a convergence test on both the first and second derivatives. 
Galleries and Tutorials using SimPEG.data_misfit.BaseDataMisfit#
 
Method of Equivalent Sources for Removing VRM Responses
 
Petrophysically guided inversion (PGI): Linear example
 
Petrophysically guided inversion: Joint linear example with nonlinear relationships
 
Heagy et al., 2017 1D RESOLVE and SkyTEM Bookpurnong Inversions
 
Heagy et al., 2017 1D RESOLVE Bookpurnong Inversion
 
Sparse Inversion with Iteratively Re-Weighted Least-Squares
 
Joint PGI of Gravity + Magnetic on an Octree mesh using full petrophysical information
 
Joint PGI of Gravity + Magnetic on an Octree mesh without petrophysical information
 
Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data
 
2.5D DC Resistivity and IP Least-Squares Inversion
 
Sparse Norm Inversion of 2D Seismic Tomography Data
 
1D Inversion of Time-Domain Data for a Single Sounding
 
Sparse Norm Inversion for Total Magnetic Intensity Data on a Tensor Mesh
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
