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 BaseDataMisfit class 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.

ϕ_{d} (m) = ‖ W f (m) ‖_{2}^{2}

where $m$ is the model vector, $W$ 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.
counterNone or simpeg.utils.Counter: Assign a SimPEG Counter object to store iterations and run-times.

Attributes

`W`	The data weighting matrix.
`counter`	SimPEG `Counter` object to store iterations and run-times.
`data`	A SimPEG data object.
`debug`	Print debugging information.
`mapping`	Mapping from the model to the quantity evaluated in the object function.
`nD`	Number of data.
`nP`	Number of model parameters.
`shape`	Shape of the Jacobian.
`simulation`	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, random_seed])	Run a convergence test on both the first and second derivatives.