29 virtual void execute()
override;
38 const DenseMatrix<Real> & input_matrix);
54 virtual void nextSamples(std::vector<Real> & req_inputs,
55 DenseMatrix<Real> & input_matrix,
56 const std::vector<Real> & tv,
57 const unsigned int & parallel_index);
66 virtual bool usingGP()
const {
return false; }
99 const std::vector<const Distribution *>
_priors;
const InputParameters & parameters() const
A base class used to perform Parallel Markov Chain Monte Carlo (MCMC) sampling.
PMCMCDecision will help making sample accept/reject decisions in MCMC schemes (for e....
const std::vector< Real > & _rnd_vec
Storage for the random numbers for decision making.
std::vector< Real > & _tpm
Transition probability matrix.
int _check_step
Ensure that the MCMC algorithm proceeds in a sequential fashion.
dof_id_type _num_confg_values
Storage for the number of experimental configuration values.
libMesh::Parallel::Communicator & _local_comm
Communicator that was split based on samples that have rows.
std::vector< const LikelihoodFunctionBase * > _likelihoods
Storage for the likelihood objects to be utilized.
std::vector< Real > & _variance
Model variance term.
virtual void execute() override
virtual void nextSeeds()
Compute the next set of seeds to facilitate proposals.
virtual void finalize() override
std::vector< std::vector< Real > > & _inputs
Model input data that is uncertain.
const std::vector< const Distribution * > _priors
Storage for the priors.
virtual void initialize() override
dof_id_type _num_confg_params
Storage for the number of experimental configuration parameters.
Sampler & _sampler
The MCMC sampler.
virtual bool usingGP() const
Flag to specify if a pre-trained Gaussian process model is used.
static InputParameters validParams()
virtual void nextSamples(std::vector< Real > &req_inputs, DenseMatrix< Real > &input_matrix, const std::vector< Real > &tv, const unsigned int ¶llel_index)
Resample inputs given the transition vector (after transition vector computed)
const std::vector< Real > * _output_value
Current output values.
std::vector< Real > _var_prev
Storage for previous variances.
DenseMatrix< Real > _data_prev
Storage for previous inputs.
const PMCMCBase *const _pmcmc
MCMC sampler base.
const Distribution * _var_prior
Storage for the prior over the variance.
Real & _noise
Model noise term to pass to Likelihoods object.
const std::vector< Real > & _new_var_samples
Storage for new proposed variance samples.
std::vector< Real > _outputs_prev
Storage for previous outputs.
virtual void computeTransitionVector(std::vector< Real > &tv, const std::vector< Real > &evidence)
Compute the transition probability vector (after the computation of evidence)
dof_id_type _props
Storage for the number of parallel proposals.
virtual void computeEvidence(std::vector< Real > &evidence, const DenseMatrix< Real > &input_matrix)
Compute the evidence (aka, betterness of the proposed sample vs the previous)
std::vector< Real > * _outputs_required
Transfer the right outputs to the file.