altar.models.emhp.EMHP

Module Contents

Classes

class altar.models.emhp.EMHP.EMHP(name, locator, **kwds)

Bases: altar.models.bayesian

A diagnostic tool

initialize(self, application)

Initialize the state of the model given a {problem} specification

initializeSample(self, step)

File {step.theta} with an initial random sample form 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