A base class used to perform Parallel Markov Chain Monte Carlo (MCMC) sampling. More...

#include <PMCMCBase.h>

Inheritance diagram for PMCMCBase:

Public Types
enum	SampleMode { SampleMode::GLOBAL, SampleMode::LOCAL }

typedef DataFileName	DataFileParameterType

Public Member Functions
	PMCMCBase (const InputParameters &parameters)

dof_id_type	getNumberOfConfigValues () const
	Return the number of configuration parameters. More...

dof_id_type	getNumberOfConfigParams () const
	Return the number of configuration parameters. More...

dof_id_type	getNumParallelProposals () const
	Return the number of parallel proposals. More...

const std::vector< Real > &	getRandomNumbers () const
	Return the random numbers to facilitate decision making in reporters. More...

const std::vector< Real > &	getVarSamples () const
	Return the proposed variance samples to facilitate decision making in reporters. More...

const std::vector< std::vector< Real > > &	getSamples () const
	Return the proposed samples to facilitate decision making in reporters. More...

const std::vector< const Distribution * >	getPriors () const
	Return the priors to facilitate decision making in reporters. More...

const Distribution *	getVarPrior () const
	Return the prior over variance to facilitate decision making in reporters. More...

virtual int	decisionStep () const
	Return the step after which decision making can begin. More...

std::vector< Real >	getNextLocalRow ()

dof_id_type	getNumberOfRows () const

dof_id_type	getNumberOfCols () const

dof_id_type	getNumberOfLocalRows () const

const LocalRankConfig &	getRankConfig (bool batch_mode) const

virtual bool	isAdaptiveSamplingCompleted () const

libMesh::Parallel::Communicator &	getLocalComm ()

virtual bool	enabled () const

std::shared_ptr< MooseObject >	getSharedPtr ()

std::shared_ptr< const MooseObject >	getSharedPtr () const

bool	isKokkosObject () const

MooseApp &	getMooseApp () const

const std::string &	type () const

const std::string &	name () const

std::string	typeAndName () const

MooseObjectParameterName	uniqueParameterName (const std::string &parameter_name) const

MooseObjectName	uniqueName () const

const InputParameters &	parameters () const

const hit::Node *	getHitNode () const

bool	hasBase () const

const std::string &	getBase () const

const T &	getParam (const std::string &name) const

std::vector< std::pair< T1, T2 > >	getParam (const std::string &param1, const std::string &param2) const

const T *	queryParam (const std::string &name) const

const T &	getRenamedParam (const std::string &old_name, const std::string &new_name) const

T	getCheckedPointerParam (const std::string &name, const std::string &error_string="") const

bool	haveParameter (const std::string &name) const

bool	isParamValid (const std::string &name) const

bool	isParamSetByUser (const std::string &name) const

void	connectControllableParams (const std::string &parameter, const std::string &object_type, const std::string &object_name, const std::string &object_parameter) const

void	paramError (const std::string &param, Args... args) const

void	paramWarning (const std::string &param, Args... args) const

void	paramWarning (const std::string &param, Args... args) const

void	paramInfo (const std::string &param, Args... args) const

std::string	messagePrefix (const bool hit_prefix=true) const

std::string	errorPrefix (const std::string &) const

void	mooseError (Args &&... args) const

void	mooseDocumentedError (const std::string &repo_name, const unsigned int issue_num, Args &&... args) const

void	mooseErrorNonPrefixed (Args &&... args) const

void	mooseWarning (Args &&... args) const

void	mooseWarning (Args &&... args) const

void	mooseWarningNonPrefixed (Args &&... args) const

void	mooseWarningNonPrefixed (Args &&... args) const

void	mooseDeprecated (Args &&... args) const

void	mooseDeprecated (Args &&... args) const

void	mooseDeprecatedNoTrace (Args &&... args) const

void	mooseInfo (Args &&... args) const

void	callMooseError (std::string msg, const bool with_prefix, const hit::Node *node=nullptr, const bool show_trace=true) const

std::string	getDataFileName (const std::string &param) const

std::string	getDataFileNameByName (const std::string &relative_path) const

std::string	getDataFilePath (const std::string &relative_path) const

virtual void	initialSetup ()

virtual void	timestepSetup ()

virtual void	jacobianSetup ()

virtual void	residualSetup ()

virtual void	subdomainSetup ()

virtual void	customSetup (const ExecFlagType &)

const ExecFlagEnum &	getExecuteOnEnum () const

PerfGraph &	perfGraph ()

T &	getSampler (const std::string &name)

Sampler &	getSampler (const std::string &name)

T &	getSamplerByName (const SamplerName &name)

Sampler &	getSamplerByName (const SamplerName &name)

const VectorPostprocessorValue &	getVectorPostprocessorValue (const std::string &param_name, const std::string &vector_name) const

const VectorPostprocessorValue &	getVectorPostprocessorValue (const std::string &param_name, const std::string &vector_name, bool needs_broadcast) const

const VectorPostprocessorValue &	getVectorPostprocessorValueByName (const VectorPostprocessorName &name, const std::string &vector_name) const

const VectorPostprocessorValue &	getVectorPostprocessorValueByName (const VectorPostprocessorName &name, const std::string &vector_name, bool needs_broadcast) const

const VectorPostprocessorValue &	getVectorPostprocessorValueOld (const std::string &param_name, const std::string &vector_name) const

const VectorPostprocessorValue &	getVectorPostprocessorValueOld (const std::string &param_name, const std::string &vector_name, bool needs_broadcast) const

const VectorPostprocessorValue &	getVectorPostprocessorValueOldByName (const VectorPostprocessorName &name, const std::string &vector_name) const

const VectorPostprocessorValue &	getVectorPostprocessorValueOldByName (const VectorPostprocessorName &name, const std::string &vector_name, bool needs_broadcast) const

const ScatterVectorPostprocessorValue &	getScatterVectorPostprocessorValue (const std::string &param_name, const std::string &vector_name) const

const ScatterVectorPostprocessorValue &	getScatterVectorPostprocessorValueByName (const VectorPostprocessorName &name, const std::string &vector_name) const

const ScatterVectorPostprocessorValue &	getScatterVectorPostprocessorValueOld (const std::string &param_name, const std::string &vector_name) const

const ScatterVectorPostprocessorValue &	getScatterVectorPostprocessorValueOldByName (const VectorPostprocessorName &name, const std::string &vector_name) const

bool	hasVectorPostprocessor (const std::string &param_name, const std::string &vector_name) const

bool	hasVectorPostprocessor (const std::string &param_name) const

bool	hasVectorPostprocessorByName (const VectorPostprocessorName &name, const std::string &vector_name) const

bool	hasVectorPostprocessorByName (const VectorPostprocessorName &name) const

const VectorPostprocessorName &	getVectorPostprocessorName (const std::string &param_name) const

DenseMatrix< Real >	getGlobalSamples ()

DenseMatrix< Real >	getGlobalSamples ()

DenseMatrix< Real >	getLocalSamples ()

DenseMatrix< Real >	getLocalSamples ()

dof_id_type	getLocalRowBegin () const

dof_id_type	getLocalRowBegin () const

dof_id_type	getLocalRowEnd () const

dof_id_type	getLocalRowEnd () const

const Distribution &	getDistribution (const std::string &name) const

const T &	getDistribution (const std::string &name) const

const Distribution &	getDistribution (const std::string &name) const

const T &	getDistribution (const std::string &name) const

const Distribution &	getDistributionByName (const DistributionName &name) const

const T &	getDistributionByName (const std::string &name) const

const Distribution &	getDistributionByName (const DistributionName &name) const

const T &	getDistributionByName (const std::string &name) const

bool	isVectorPostprocessorDistributed (const std::string &param_name) const

bool	isVectorPostprocessorDistributed (const std::string &param_name) const

bool	isVectorPostprocessorDistributedByName (const VectorPostprocessorName &name) const

bool	isVectorPostprocessorDistributedByName (const VectorPostprocessorName &name) const

const Parallel::Communicator &	comm () const

processor_id_type	n_processors () const

processor_id_type	processor_id () const

bool	isImplicit ()

Moose::StateArg	determineState () const

Static Public Member Functions
static InputParameters	validParams ()

static void	callMooseError (MooseApp const app, const InputParameters &params, std::string msg, const bool with_prefix, const hit::Node node, const bool show_trace=true)

Public Attributes
	usingCombinedWarningSolutionWarnings

const ConsoleStream	_console

Static Public Attributes
static const std::string	type_param

static const std::string	name_param

static const std::string	unique_name_param

static const std::string	app_param

static const std::string	moose_base_param

static const std::string	kokkos_object_param

Protected Member Functions
virtual void	proposeSamples ()
	Fill in the _new_samples vector of vectors (happens within sampleSetUp) More...

virtual void	executeSetUp () override

virtual Real	computeSample (dof_id_type row_index, dof_id_type col_index) override

Real	random ()
	Sample a random number between 0 and 1. More...

unsigned int	randomIndex (const unsigned int &upper_bound, const unsigned int &exclude)
	Sample a random index excluding a specified index. More...

std::pair< unsigned int, unsigned int >	randomIndexPair (const unsigned int &upper_bound, const unsigned int &exclude)
	Sample two random indices without repitition excluding a specified index. More...

void	setNumberOfRandomSeeds (std::size_t number)

Real	getRand (std::size_t n, unsigned int index=0) const

unsigned int	getRandl (std::size_t n, unsigned int lower, unsigned int upper, unsigned int index=0) const

virtual LocalRankConfig	constructRankConfig (bool batch_mode) const

void	flagInvalidSolutionInternal (const InvalidSolutionID invalid_solution_id) const

InvalidSolutionID	registerInvalidSolutionInternal (const std::string &message, const bool warning) const

PerfID	registerTimedSection (const std::string &section_name, const unsigned int level) const

PerfID	registerTimedSection (const std::string &section_name, const unsigned int level, const std::string &live_message, const bool print_dots=true) const

std::string	timedSectionName (const std::string &section_name) const

virtual void	addVectorPostprocessorDependencyHelper (const VectorPostprocessorName &) const

const ReporterContextBase &	getReporterContextBaseByName (const ReporterName &reporter_name) const

const ReporterName &	getReporterName (const std::string &param_name) const

virtual void	addReporterDependencyHelper (const ReporterName &)

void	setNumberOfRows (dof_id_type n_rows)

void	setNumberOfRows (dof_id_type n_rows)

void	setNumberOfCols (dof_id_type n_cols)

void	setNumberOfCols (dof_id_type n_cols)

virtual void	computeSampleMatrix (DenseMatrix< Real > &matrix)

virtual void	computeSampleMatrix (DenseMatrix< Real > &matrix)

virtual void	computeLocalSampleMatrix (DenseMatrix< Real > &matrix)

virtual void	computeLocalSampleMatrix (DenseMatrix< Real > &matrix)

virtual void	computeSampleRow (dof_id_type i, std::vector< Real > &data)

virtual void	computeSampleRow (dof_id_type i, std::vector< Real > &data)

virtual void	advanceGenerators (const dof_id_type count)

virtual void	advanceGenerators (const dof_id_type count)

virtual void	advanceGenerator (const unsigned int seed_index, const dof_id_type count)

virtual void	advanceGenerator (const unsigned int seed_index, const dof_id_type count)

void	setAutoAdvanceGenerators (const bool state)

void	setAutoAdvanceGenerators (const bool state)

virtual void	executeTearDown ()

virtual void	executeTearDown ()

const T &	getReporterValue (const std::string &param_name, const std::size_t time_index=0)

const T &	getReporterValue (const std::string &param_name, ReporterMode mode, const std::size_t time_index=0)

const T &	getReporterValue (const std::string &param_name, const std::size_t time_index=0)

const T &	getReporterValue (const std::string &param_name, ReporterMode mode, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, ReporterMode mode, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, ReporterMode mode, const std::size_t time_index=0)

bool	hasReporterValue (const std::string &param_name) const

bool	hasReporterValue (const std::string &param_name) const

bool	hasReporterValue (const std::string &param_name) const

bool	hasReporterValue (const std::string &param_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

Protected Attributes
const unsigned int	_num_parallel_proposals
	Number of parallel proposals to be made and subApps to be executed. More...

std::vector< const Distribution * >	_priors
	Storage for prior distribution objects to be utilized. More...

const Distribution *	_var_prior
	Storage for prior distribution object of the variance to be utilized. More...

const std::vector< Real > *	_lower_bound
	Lower bounds for making the next proposal. More...

const std::vector< Real > *	_upper_bound
	Upper bounds for making the next proposal. More...

const Real &	_variance_bound
	Upper bound for variance for making the next proposal. More...

const std::vector< Real > &	_initial_values
	Initial values of the input params to get the MCMC scheme started. More...

std::vector< std::vector< Real > >	_new_samples
	Vectors of new proposed samples. More...

std::vector< Real >	_new_var_samples
	Vector of new proposed variance samples. More...

std::vector< Real >	_rnd_vec
	Vector of random numbers for decision making. More...

const dof_id_type	_min_procs_per_row

const dof_id_type	_max_procs_per_row

libMesh::Parallel::Communicator	_local_comm

const bool &	_enabled

MooseApp &	_app

Factory &	_factory

ActionFactory &	_action_factory

const std::string &	_type

const std::string &	_name

const InputParameters &	_pars

const ExecFlagEnum &	_execute_enum

const ExecFlagType &	_current_execute_flag

MooseApp &	_pg_moose_app

const std::string	_prefix

const Parallel::Communicator &	_communicator

const InputParameters &	_ti_params

FEProblemBase &	_ti_feproblem

bool	_is_implicit

Real &	_t

const Real &	_t_old

int &	_t_step

Real &	_dt

Real &	_dt_old

bool	_is_transient

Private Member Functions
void	combineWithExperimentalConfig ()
	Generates combinations of the new samples with the experimental configurations. More...

Private Attributes
const unsigned int	_num_random_seeds
	Initialize a certain number of random seeds. Change from the default only if you have to. More...

unsigned int	_seed_index
	Generator index when requesting random numbers. More...

std::size_t	_rand_index
	Running index for the random number generators. More...

std::vector< std::vector< Real > >	_confg_values
	Configuration values. More...

std::vector< std::vector< Real > >	_new_samples_confg
	Vectors of new proposed samples combined with the experimental configuration values. More...

Detailed Description

A base class used to perform Parallel Markov Chain Monte Carlo (MCMC) sampling.

Definition at line 19 of file PMCMCBase.h.

Constructor & Destructor Documentation

◆ PMCMCBase()

PMCMCBase::PMCMCBase ( const InputParameters & parameters )

Definition at line 49 of file PMCMCBase.C.

   : Sampler(parameters),
     TransientInterface(this),
     _num_parallel_proposals(getParam<unsigned int>("num_parallel_proposals")),
     _lower_bound(isParamValid("lower_bound") ? &getParam<std::vector<Real>>("lower_bound")
                                              : nullptr),
     _upper_bound(isParamValid("upper_bound") ? &getParam<std::vector<Real>>("upper_bound")
                                              : nullptr),
     _variance_bound(getParam<Real>("variance_bound")),
     _initial_values(getParam<std::vector<Real>>("initial_values")),
     _num_random_seeds(getParam<unsigned int>("num_random_seeds")),
     _seed_index(0),
     _rand_index(0)
 {
   // Filling the `priors` vector with the user-provided distributions.
   for (const DistributionName & name :
        getParam<std::vector<DistributionName>>("prior_distributions"))
     _priors.push_back(&getDistributionByName(name));
 
   // Filling the `var_prior` object with the user-provided distribution for the variance.
   if (isParamValid("prior_variance"))
     _var_prior = &getDistributionByName(getParam<DistributionName>("prior_variance"));
   else
     _var_prior = nullptr;
 
   // Read the experimental configurations from a csv file
   MooseUtils::DelimitedFileReader reader(getParam<FileName>("file_name"));
   reader.read();
   _confg_values.resize(1);
   if (isParamValid("file_column_name"))
     _confg_values[0] = reader.getData(getParam<std::string>("file_column_name"));
   else if (isParamValid("num_columns"))
   {
     _confg_values.resize(getParam<unsigned int>("num_columns"));
     for (unsigned int i = 0; i < _confg_values.size(); ++i)
       _confg_values[i] = reader.getData(i);
   }
   else
     _confg_values[0] = reader.getData(0);
 
   // Setting the number of sampler rows to be equal to the number of parallel proposals
   setNumberOfRows(_num_parallel_proposals * _confg_values[0].size());
 
   // Setting the number of columns in the sampler matrix (equal to the number of distributions).
   setNumberOfCols(_priors.size() + _confg_values.size());
 
   // Resizing the vectors and vector of vectors
   _new_samples.resize(_num_parallel_proposals, _initial_values);
   _new_samples_confg.resize(_num_parallel_proposals * _confg_values[0].size(),
                             std::vector<Real>(_priors.size() + _confg_values.size(), 0.0));
   _rnd_vec.resize(_num_parallel_proposals);
   _new_var_samples.assign(_num_parallel_proposals, 0.0);
 
   setNumberOfRandomSeeds(_num_random_seeds);
   setAutoAdvanceGenerators(false);
 
   // Check whether both the lower and the upper bounds are specified and of same size
   bool bound_check1 = _lower_bound && !_upper_bound;
   bool bound_check2 = !_lower_bound && _upper_bound;
   if (bound_check1 || bound_check2)
     mooseError("Both lower and upper bounds should be specified.");
   bool size_check = _lower_bound ? ((*_lower_bound).size() != (*_upper_bound).size()) : 0;
   if (size_check)
     mooseError("Lower and upper bounds should be of the same size.");
 
   // Check whether the priors, bounds, and initial values are all of the same size
   if (_priors.size() != _initial_values.size())
     mooseError("The priors and initial values should be of the same size.");
 }

Member Function Documentation

◆ combineWithExperimentalConfig()

void PMCMCBase::combineWithExperimentalConfig ( )

private

Generates combinations of the new samples with the experimental configurations.

Definition at line 167 of file PMCMCBase.C.

Referenced by computeSample().

 {
   unsigned int index1;
   int index2 = -1;
   std::vector<Real> tmp;
   for (unsigned int i = 0; i < _num_parallel_proposals * _confg_values[0].size(); ++i)
   {
     index1 = i % _num_parallel_proposals;
     if (index1 == 0)
       ++index2;
     tmp = _new_samples[index1];
     for (unsigned int j = 0; j < _confg_values.size(); ++j)
       tmp.push_back(_confg_values[j][index2]);
     _new_samples_confg[i] = tmp;
   }
 }

◆ computeSample()

Real PMCMCBase::computeSample	(	dof_id_type	row_index,
		dof_id_type	col_index
	)

overrideprotectedvirtual

Implements Sampler.

Definition at line 215 of file PMCMCBase.C.

 {
   if (_t_step < 1)
     for (unsigned int i = 0; i < _num_parallel_proposals; ++i)
       _new_samples[i] = _initial_values;
 
   // Combine the proposed samples with experimental configurations
   combineWithExperimentalConfig();
 
   return _new_samples_confg[row_index][col_index];
 }

◆ decisionStep()

virtual int PMCMCBase::decisionStep ( ) const

inlinevirtual

Return the step after which decision making can begin.

Reimplemented in AffineInvariantDES, AffineInvariantStretchSampler, and IndependentGaussianMH.

Definition at line 73 of file PMCMCBase.h.

Referenced by PMCMCDecision::execute().

73 { return 1; }

◆ executeSetUp()

void PMCMCBase::executeSetUp ( )

overrideprotectedvirtual

Reimplemented from Sampler.

Definition at line 128 of file PMCMCBase.C.

 {
   _seed_index = _t_step;
   _rand_index = 0;
 
   // Filling the new_samples vector of vectors with new proposal samples
   proposeSamples();
 
   // Draw random numbers to facilitate decision making later on
   for (unsigned int j = 0; j < _num_parallel_proposals; ++j)
     _rnd_vec[j] = random();
 }

◆ getNumberOfConfigParams()

dof_id_type PMCMCBase::getNumberOfConfigParams ( ) const

inline

Return the number of configuration parameters.

Definition at line 34 of file PMCMCBase.h.

Referenced by BayesianActiveLearner::BayesianActiveLearner(), and PMCMCDecision::PMCMCDecision().

34 { return _confg_values.size(); }

PMCMCBase::_confg_values

std::vector< std::vector< Real > > _confg_values

Configuration values.

Definition: PMCMCBase.h:157

◆ getNumberOfConfigValues()

dof_id_type PMCMCBase::getNumberOfConfigValues ( ) const

inline

Return the number of configuration parameters.

Definition at line 29 of file PMCMCBase.h.

Referenced by BayesianActiveLearner::BayesianActiveLearner(), and PMCMCDecision::PMCMCDecision().

29 { return _confg_values[0].size(); }

PMCMCBase::_confg_values

std::vector< std::vector< Real > > _confg_values

Configuration values.

Definition: PMCMCBase.h:157

◆ getNumParallelProposals()

dof_id_type PMCMCBase::getNumParallelProposals ( ) const

inline

Return the number of parallel proposals.

Definition at line 39 of file PMCMCBase.h.

Referenced by PMCMCDecision::PMCMCDecision().

39 { return _num_parallel_proposals; }

PMCMCBase::_num_parallel_proposals

const unsigned int _num_parallel_proposals

Number of parallel proposals to be made and subApps to be executed.

Definition: PMCMCBase.h:112

◆ getPriors()

const std::vector< const Distribution * > PMCMCBase::getPriors ( ) const

Return the priors to facilitate decision making in reporters.

Definition at line 203 of file PMCMCBase.C.

 {
   return _priors;
 }

◆ getRandomNumbers()

const std::vector< Real > & PMCMCBase::getRandomNumbers ( ) const

Return the random numbers to facilitate decision making in reporters.

Definition at line 185 of file PMCMCBase.C.

 {
   return _rnd_vec;
 }

◆ getSamples()

const std::vector< std::vector< Real > > & PMCMCBase::getSamples ( ) const

Return the proposed samples to facilitate decision making in reporters.

In MCMC schemes, there is a decision-making step after evaluating the computational model on whether or not to accept the proposed samples. To facilitate this decision-making, which happens in the Reporter, we have to provide it the proposed samples.

Definition at line 197 of file PMCMCBase.C.

 {
   return _new_samples;
 }

◆ getVarPrior()

const Distribution * PMCMCBase::getVarPrior ( ) const

Return the prior over variance to facilitate decision making in reporters.

Definition at line 209 of file PMCMCBase.C.

 {
   return _var_prior;
 }

◆ getVarSamples()

const std::vector< Real > & PMCMCBase::getVarSamples ( ) const

Return the proposed variance samples to facilitate decision making in reporters.

Definition at line 191 of file PMCMCBase.C.

 {
   return _new_var_samples;
 }

◆ proposeSamples()

void PMCMCBase::proposeSamples ( )

protectedvirtual

Fill in the _new_samples vector of vectors (happens within sampleSetUp)

Parameters

seed_value The seed for the random number generator

Reimplemented in BayesianActiveLearningSampler, AffineInvariantStretchSampler, AffineInvariantDES, and IndependentGaussianMH.

Definition at line 120 of file PMCMCBase.C.

Referenced by executeSetUp().

 {
   for (unsigned int j = 0; j < _num_parallel_proposals; ++j)
     for (unsigned int i = 0; i < _priors.size(); ++i)
       _new_samples[j][i] = _priors[i]->quantile(random());
 }

◆ random()

Real PMCMCBase::random ( )

protected

Sample a random number between 0 and 1.

Parameters

upper_bound The upper bound provided

Returns: The required index

Definition at line 142 of file PMCMCBase.C.

Referenced by executeSetUp(), IndependentGaussianMH::proposeSamples(), AffineInvariantDES::proposeSamples(), AffineInvariantStretchSampler::proposeSamples(), BayesianActiveLearningSampler::proposeSamples(), and proposeSamples().

 {
   return getRand(_rand_index++, _seed_index);
 }

◆ randomIndex()

unsigned int PMCMCBase::randomIndex	(	const unsigned int &	upper_bound,
		const unsigned int &	exclude
	)

protected

Sample a random index excluding a specified index.

Parameters

upper_bound The upper bound provided

Returns: The required index

Definition at line 148 of file PMCMCBase.C.

Referenced by AffineInvariantStretchSampler::proposeSamples(), and randomIndexPair().

 {
   auto req_index = exclude;
   while (req_index == exclude)
     req_index = getRandl(_rand_index++, 0, upper_bound, _seed_index);
   return req_index;
 }

◆ randomIndexPair()

std::pair< unsigned int, unsigned int > PMCMCBase::randomIndexPair	(	const unsigned int &	upper_bound,
		const unsigned int &	exclude
	)

protected

Sample two random indices without repitition excluding a specified index.

Parameters

upper_bound	The upper bound provided
exclude	The index to be excluded from sampling

Returns: Pair of required indices

Definition at line 157 of file PMCMCBase.C.

Referenced by AffineInvariantDES::proposeSamples().

 {
   auto req_index1 = randomIndex(upper_bound, exclude);
   auto req_index2 = req_index1;
   while (req_index1 == req_index2)
     req_index2 = randomIndex(upper_bound, exclude);
   return {req_index1, req_index2};
 }

◆ validParams()

InputParameters PMCMCBase::validParams ( )

static

Definition at line 18 of file PMCMCBase.C.

Referenced by AffineInvariantDES::validParams(), IndependentGaussianMH::validParams(), AffineInvariantStretchSampler::validParams(), and BayesianActiveLearningSampler::validParams().

 {
   InputParameters params = Sampler::validParams();
   params.addClassDescription("Parallel Markov chain Monte Carlo base.");
   params.addRequiredParam<std::vector<DistributionName>>(
       "prior_distributions", "The prior distributions of the parameters to be calibrated.");
   params.addParam<DistributionName>(
       "prior_variance", "The prior distribution of the variance parameter to be calibrated.");
   params.addRequiredParam<unsigned int>(
       "num_parallel_proposals",
       "Number of proposals to make and corresponding subApps executed in "
       "parallel.");
   params.addRequiredParam<FileName>("file_name", "Name of the CSV file with configuration values.");
   params.addParam<std::string>(
       "file_column_name", "Name of column in CSV file to use, by default first column is used.");
   params.addParam<unsigned int>(
       "num_columns", "Number of columns to be used in the CSV file with the configuration values.");
   params.addParam<std::vector<Real>>("lower_bound", "Lower bounds for making the next proposal.");
   params.addParam<std::vector<Real>>("upper_bound", "Upper bounds for making the next proposal.");
   params.addParam<Real>("variance_bound",
                         std::numeric_limits<Real>::max(),
                         "Upper bound for variance for making the next proposal.");
   params.addRequiredParam<std::vector<Real>>("initial_values",
                                              "The starting values of the inputs to be calibrated.");
   params.addParam<unsigned int>(
       "num_random_seeds",
       100000,
       "Initialize a certain number of random seeds. Change from the default only if you have to.");
   return params;
 }

Member Data Documentation

◆ _confg_values

std::vector<std::vector<Real> > PMCMCBase::_confg_values

private

Configuration values.

Definition at line 157 of file PMCMCBase.h.

Referenced by combineWithExperimentalConfig(), getNumberOfConfigParams(), getNumberOfConfigValues(), and PMCMCBase().

◆ _initial_values

const std::vector<Real>& PMCMCBase::_initial_values

protected

Initial values of the input params to get the MCMC scheme started.

Definition at line 130 of file PMCMCBase.h.

Referenced by computeSample(), PMCMCBase(), and IndependentGaussianMH::proposeSamples().

◆ _lower_bound

const std::vector<Real>* PMCMCBase::_lower_bound

protected

Lower bounds for making the next proposal.

Definition at line 121 of file PMCMCBase.h.

Referenced by PMCMCBase(), AffineInvariantDES::proposeSamples(), IndependentGaussianMH::proposeSamples(), and AffineInvariantStretchSampler::proposeSamples().

◆ _new_samples

std::vector<std::vector<Real> > PMCMCBase::_new_samples

protected

Vectors of new proposed samples.

Definition at line 133 of file PMCMCBase.h.

Referenced by combineWithExperimentalConfig(), computeSample(), getSamples(), PMCMCBase(), AffineInvariantDES::proposeSamples(), IndependentGaussianMH::proposeSamples(), AffineInvariantStretchSampler::proposeSamples(), BayesianActiveLearningSampler::proposeSamples(), and proposeSamples().

◆ _new_samples_confg

std::vector<std::vector<Real> > PMCMCBase::_new_samples_confg

private

Vectors of new proposed samples combined with the experimental configuration values.

Definition at line 160 of file PMCMCBase.h.

Referenced by combineWithExperimentalConfig(), computeSample(), and PMCMCBase().

◆ _new_var_samples

std::vector<Real> PMCMCBase::_new_var_samples

protected

Vector of new proposed variance samples.

Definition at line 136 of file PMCMCBase.h.

Referenced by getVarSamples(), PMCMCBase(), AffineInvariantDES::proposeSamples(), AffineInvariantStretchSampler::proposeSamples(), and BayesianActiveLearningSampler::proposeSamples().

◆ _num_parallel_proposals

const unsigned int PMCMCBase::_num_parallel_proposals

protected

Number of parallel proposals to be made and subApps to be executed.

Definition at line 112 of file PMCMCBase.h.

Referenced by AffineInvariantDES::AffineInvariantDES(), AffineInvariantStretchSampler::AffineInvariantStretchSampler(), combineWithExperimentalConfig(), computeSample(), executeSetUp(), getNumParallelProposals(), PMCMCBase(), IndependentGaussianMH::proposeSamples(), AffineInvariantDES::proposeSamples(), AffineInvariantStretchSampler::proposeSamples(), BayesianActiveLearningSampler::proposeSamples(), and proposeSamples().

◆ _num_random_seeds

const unsigned int PMCMCBase::_num_random_seeds

private

Initialize a certain number of random seeds. Change from the default only if you have to.

Definition at line 148 of file PMCMCBase.h.

Referenced by PMCMCBase().

◆ _priors

std::vector<const Distribution *> PMCMCBase::_priors

protected

Storage for prior distribution objects to be utilized.

Definition at line 115 of file PMCMCBase.h.

Referenced by AffineInvariantDES::AffineInvariantDES(), AffineInvariantStretchSampler::AffineInvariantStretchSampler(), getPriors(), IndependentGaussianMH::IndependentGaussianMH(), PMCMCBase(), IndependentGaussianMH::proposeSamples(), AffineInvariantDES::proposeSamples(), AffineInvariantStretchSampler::proposeSamples(), BayesianActiveLearningSampler::proposeSamples(), proposeSamples(), and AffineInvariantDES::tuneParams().

◆ _rand_index

std::size_t PMCMCBase::_rand_index

private

Running index for the random number generators.

Definition at line 154 of file PMCMCBase.h.

Referenced by executeSetUp(), random(), and randomIndex().

◆ _rnd_vec

std::vector<Real> PMCMCBase::_rnd_vec

protected

Vector of random numbers for decision making.

Definition at line 139 of file PMCMCBase.h.

Referenced by executeSetUp(), getRandomNumbers(), and PMCMCBase().

◆ _seed_index

unsigned int PMCMCBase::_seed_index

private

Generator index when requesting random numbers.

Definition at line 151 of file PMCMCBase.h.

Referenced by executeSetUp(), random(), and randomIndex().

◆ _upper_bound

const std::vector<Real>* PMCMCBase::_upper_bound

protected

Upper bounds for making the next proposal.

Definition at line 124 of file PMCMCBase.h.

Referenced by PMCMCBase(), and IndependentGaussianMH::proposeSamples().

◆ _var_prior

const Distribution* PMCMCBase::_var_prior

protected

Storage for prior distribution object of the variance to be utilized.

Definition at line 118 of file PMCMCBase.h.

Referenced by getVarPrior(), PMCMCBase(), AffineInvariantDES::proposeSamples(), AffineInvariantStretchSampler::proposeSamples(), and BayesianActiveLearningSampler::proposeSamples().

◆ _variance_bound

const Real& PMCMCBase::_variance_bound

protected

Upper bound for variance for making the next proposal.

Definition at line 127 of file PMCMCBase.h.

Referenced by AffineInvariantDES::proposeSamples(), and AffineInvariantStretchSampler::proposeSamples().

The documentation for this class was generated from the following files:

stochastic_tools/include/samplers/PMCMCBase.h
stochastic_tools/src/samplers/PMCMCBase.C

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Protected Member Functions

Protected Attributes

Private Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ PMCMCBase()

Member Function Documentation

◆ combineWithExperimentalConfig()

◆ computeSample()

◆ decisionStep()

◆ executeSetUp()

◆ getNumberOfConfigParams()

◆ getNumberOfConfigValues()

◆ getNumParallelProposals()

◆ getPriors()

◆ getRandomNumbers()

◆ getSamples()

◆ getVarPrior()

◆ getVarSamples()

◆ proposeSamples()

◆ random()

◆ randomIndex()

◆ randomIndexPair()

◆ validParams()

Member Data Documentation

◆ _confg_values

◆ _initial_values

◆ _lower_bound

◆ _new_samples

◆ _new_samples_confg

◆ _new_var_samples

◆ _num_parallel_proposals

◆ _num_random_seeds

◆ _priors

◆ _rand_index

◆ _rnd_vec

◆ _seed_index

◆ _upper_bound

◆ _var_prior

◆ _variance_bound