SimPEG.objective_function.BaseObjectiveFunction#
- class SimPEG.objective_function.BaseObjectiveFunction(nP=None, mapping=None, has_fields=False, counter=None, debug=False)[source]#
Bases:
BaseSimPEGBase Objective Function
Inherit this to build your own objective function. If building a regularization, have a look at
SimPEG.regularization.BaseRegularizationas there are additional methods and properties tailored to regularization of a model. Similarly, for building a data misfit, seeSimPEG.DataMisfit.BaseDataMisfit.Attributes
A SimPEG.Maps instance
Number of model parameters expected.
Methods
__call__(x[, f])Evaluate the objective functions for a given model
deriv(x, **kwargs)First derivative of the objective function with respect to the model
deriv2(x[, v])Second derivative of the objective function with respect to the model
map_classBase class of expected maps
test([x, num])Run a convergence test on both the first and second derivatives - they should be second order!
Galleries and Tutorials using SimPEG.objective_function.BaseObjectiveFunction#
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
1D Inversion of Time-Domain Data for a Single Sounding
Sparse Inversion with Iteratively Re-Weighted Least-Squares
Sparse Norm Inversion for Total Magnetic Intensity Data on a Tensor Mesh
2.5D DC Resistivity and IP Least-Squares Inversion
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
Sparse Norm Inversion of 2D Seismic Tomography Data
Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data