`altar.models.Ensemble`

Module Contents

Classes

class altar.models.Ensemble.Ensemble(name, locator, **kwds)

Bases: altar.models.Bayesian.Bayesian

A collection of AlTar models that comprise a single model

models

doc = the collection of models in this ensemble

initialize(self, application): Initialize the state of the model given an {application} context

initializeSample(self, step): Fill {step.theta} with an initial random sample from my prior distribution.

priorLikelihood(self, step): Fill {step.prior} with the likelihoods of the samples in {step.theta} in the prior distribution

dataLikelihood(self, step): Fill {step.data} with the likelihoods of the samples in {step.theta} given the available data. This is what is usually referred to as the “forward model”

verify(self, step, mask): Check whether the samples in {step.theta} are consistent with the model requirements and update the {mask}, a vector with zeroes for valid samples and non-zero for invalid ones