suppy.perturbations

The Perturbations module contains the underlying perturbation strategies that are usable in the superiorization algorithms.

Public perturbation strategies

PowerSeriesGradientPerturbation(func, grad)

Objective function perturbation using gradient descent with step size reduction according to a power series.

Underlying base classes

Perturbation()	Abstract base class for perturbations applied to feasibility seeking algorithms.
ObjectivePerturbation(func, func_args[, n_red])	Base class for perturbations performed by decreasing an objective function.
GradientPerturbation(func, grad, func_args, ...)	A class for perturbations performed by decreasing an objective function using the gradient.