simpeg.directives.AlphasSmoothEstimate_ByEig#

class simpeg.directives.AlphasSmoothEstimate_ByEig(alpha0_ratio=1.0, n_pw_iter=4, random_seed=None, **kwargs)[source]#

Bases: InversionDirective

Estimate the alphas multipliers for the smoothness terms of the regularization as a multiple of the ratio between the highest eigenvalue of the smallness term and the highest eigenvalue of each smoothness term of the regularization. The highest eigenvalue are estimated through power iterations and Rayleigh quotient.

Attributes

`alpha0_ratio`	the estimated Alpha_smooth is multiplied by this ratio (int or array).
`dmisfit`	Data misfit associated with the directive.
`invProb`	Inverse problem associated with the directive.
`inversion`	Inversion object associated with the directive.
`n_pw_iter`	Number of power iterations for estimation.
`opt`	Optimization algorithm associated with the directive.
`random_seed`	Random seed to initialize with.
`reg`	Regularization associated with the directive.
`seed`	random_seed.seed has been deprecated.
`simulation`	Return simulation for all data misfits.
`survey`	Return survey for all data misfits
`verbose`	Whether or not to print debugging information.

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.
`validate`([directiveList])	Validate directive.