calipy.effects

This module provides the CalipyEffect base class that is used for specifying random and deterministic phenomena affecting measurements and provides a list of basic effects as well as the functionality needed to integrate them into the CalipyProbModel class for simulation and inference.

The classes are

CalipyEffect: Base class from which all concrete effects inherit. Blueprint

for effects that involve known parameters, unknown parameters, and random variables. Provides effect in form of differentiable forward map.

CalipyQuantity: Base class from which all concrete quantities inherit. Blueprint

for quantities, i.e. known parameters, unknown parameters, and random variables that are the building blocks for CalipyEffect objects.

The script is meant solely for educational and illustrative purposes. Written by Jemil Avers Butt, Atlas optimization GmbH, www.atlasoptimization.com.

Classes

CalipyEffect([type, name, info])	The CalipyEffect class provides a comprehensive representation of a specific effect.
CalipyQuantity([type, name, info])	The CalipyQuantity class provides a comprehensive representation of a specific quantity used in the construction of a CalipyEffect object.
KnownParam([type, name, info])
NoiseAddition(node_structure, **kwargs)	NoiseAddition is a subclass of CalipyEffect that produces an object whose forward() method emulates uncorrelated noise being added to an input.
UnknownParameter(node_structure[, constraint])	UnknownParameter is a subclass of CalipyQuantity that produces an object whose forward() method produces a parameter that is subject to inference.
UnknownVariance(node_structure, **kwargs)	UnknownVariance is a subclass of UnknownParameter that includes a positivity constraint.