PriorPenalized

class pmrf.problems.PriorPenalized(problem: AbstractProblem)

Bases: AbstractProblem

A problem penalized by the negative log prior of its parameters.

Minimizing a penalized problem gives the maximum a posteriori estimate, where the problem alone gives the maximum likelihood estimate. Priors are extracted over the whole problem, so the terms’ own hyper-parameters are covered alongside the model’s parameters.

Priors are metadata and are stripped by unwrapping, so they are extracted once on construction while the problem is still wrapped.

Parameters:

problem (pmrf.problems.AbstractProblem) – The problem to penalize.

__call__(*args, **kwargs) → Array

Evaluate the problem.

distributions: Any

The prior distributions of the problem’s parameters.

property inner: AbstractProblem

The problem itself, or the one it wraps, looking through any nesting.

property model: Any

problem: AbstractProblem

The problem being penalized.