Reference / binference.samplers.Engine

binference.samplers.Engine

class binference.samplers.Engine(model, *, rng=None, progress=False)

Base class of all inference engines.

Engines are configured at construction and executed with run(), which returns a PopulationResult (or a PointEstimate for MAP).

Parameters:

modelPopulationModel

The model to infer.

rngint, numpy.random.Generator, or None

Random number generator.

progressbool

Show a progress bar.

__init__(model, *, rng=None, progress=False)

Methods

__init__(model, *[, rng, progress])
run(*args, **kwargs)
unsupported(model)	Why the engine cannot run on model, or None when it can.

Attributes

approximate
joint	whether the engine infers a selection from injections or a tallied response jointly (DECISIONS #30, #80, #81)
markov	whether its draws are Markov chains, described by R-hat and ESS
name

joint = False

whether the engine infers a selection from injections or a tallied response jointly (DECISIONS #30, #80, #81)

markov = False

whether its draws are Markov chains, described by R-hat and ESS

classmethod unsupported(model)

Why the engine cannot run on model, or None when it can.

Parameters:

modelPopulationModel

The model to run on.