simpeg.directives.PairedBetaEstimate_ByEig

class simpeg.directives.PairedBetaEstimate_ByEig(inversion=None, dmisfit=None, reg=None, verbose=False, **kwargs)

Bases: InversionDirective

Estimate the trade-off parameter, beta, between pairs of data misfit(s) and the regularization(s) as a multiple of the ratio between the highest eigenvalue of the data misfit term and the highest eigenvalue of the regularization. The highest eigenvalues are estimated through power iterations and Rayleigh quotient.

Attributes

debug	verbose.debug has been deprecated.
dmisfit	Data misfit associated with the directive.
invProb	Inverse problem associated with the directive.
inversion	Inversion object associated with the directive.
opt	Optimization algorithm associated with the directive.
reg	Regularization associated with the directive.
simulation	Return simulation for all data misfits.
survey	Return survey for all data misfits
verbose	Whether or not to print debugging information.

seed

Methods

endIter()	Update inversion parameter(s) according to directive at end of iteration.
finish()	Update inversion parameter(s) according to directive at end of inversion.
initialize()	The initial beta is calculated by comparing the estimated eigenvalues of \(J^T J\) and \(W^T W\).
validate([directiveList])	Validate directive.

Notes

This class assumes the order of the data misfits for each model parameter match the order for the respective regularizations, i.e.

>>> data_misfits = [phi_d_m1, phi_d_m2, phi_d_m3]
>>> regs = [phi_m_m1, phi_m_m2, phi_m_m3]

In which case it will estimate regularization parameters for each respective pair.

Galleries and Tutorials using simpeg.directives.PairedBetaEstimate_ByEig

Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data

Cross-gradient Joint Inversion of Gravity and Magnetic Anomaly Data