`altar.models.cdm.CDM`

Module Contents

Classes

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

Bases: altar.models.bayesian

An implementation of the Compound Dislocation Model, Nikhoo et al. [2017]

psets

doc = the model parameter meta-data

observations

doc = the number of model degrees of freedom

norm

default

doc = the norm to use when computing the data log likelihood

case

doc = the directory with the input files

displacements

doc = the name of the file with the displacements

covariance

doc = the name of the file with the data covariance

nu

doc = the Poisson ratio

mode

doc = the implementation strategy

validators

parameters = 0

strategy

ifs

d

los

oid

points

cd

xIdx = 0

yIdx = 0

dIdx = 0

openingIdx = 0

aXIdx = 0

aYIdx = 0

aZIdx = 0

omegaXIdx = 0

omegaYIdx = 0

omegaZIdx = 0

offsetIdx = 0

cd_inv

normalization = 1

initialize(self, application): Initialize the state of the model given a {problem} specification

initializeSample(self, step): Fill {step.θ} 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

initializeParameterSets(self): Initialize my parameter sets

mountInputDataspace(self, pfs): Mount the directory with my input files

loadInputs(self): Load the data in the input files into memory

computeNormalization(self): Compute the normalization of the L2 norm

computeCovarianceInverse(self): Compute the inverse of my data covariance

meta(self): Persist the sample layout by recording the parameter set metadata

show(self, job, channel): Place model information in the supplied {channel}