A class used to perform Parallel Subset Simulation Sampling. More...

#include <ParallelSubsetSimulation.h>

Inheritance diagram for ParallelSubsetSimulation:

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

typedef DataFileName	DataFileParameterType

Public Member Functions
	ParallelSubsetSimulation (const InputParameters &parameters)

const unsigned int &	getNumSamplesSub () const
	Access the number samples per subset. More...

const bool &	getUseAbsoluteValue () const
	Access use absolute value bool. More...

const Real &	getSubsetProbability () const
	Access the subset probability. More...

virtual bool	isAdaptiveSamplingCompleted () const override
	Returns true if the adaptive sampling is completed. 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

libMesh::Parallel::Communicator &	getLocalComm ()

virtual bool	enabled () const

std::shared_ptr< MooseObject >	getSharedPtr ()

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

MooseApp &	getMooseApp () const

const std::string &	type () const

virtual const std::string &	name () const

std::string	typeAndName () const

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

void	callMooseError (std::string msg, const bool with_prefix) const

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

const InputParameters &	parameters () const

MooseObjectName	uniqueName () 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	isParamValid (const std::string &name) const

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

void	paramError (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

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

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

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

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

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

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

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

void	mooseInfo (Args &&... args) 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

Static Public Member Functions
static InputParameters	validParams ()

Public Attributes
const ConsoleStream	_console

Protected Types
enum	CommMethod

Protected Member Functions
virtual void	sampleSetUp (const Sampler::SampleMode mode) override

virtual Real	computeSample (dof_id_type row_index, dof_id_type col_index) override

void	setNumberOfRandomSeeds (std::size_t number)

Real	getRand (unsigned int index=0)

uint32_t	getRandl (unsigned int index, uint32_t lower, uint32_t upper)

virtual LocalRankConfig	constructRankConfig (bool batch_mode) 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 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	sampleTearDown (const SampleMode)

virtual void	sampleTearDown (const SampleMode)

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)

void	shuffle (std::vector< T > &data, const std::size_t seed_index=0, const CommMethod method=CommMethod::LOCAL)

void	shuffle (std::vector< T > &data, const std::size_t seed_index=0, const CommMethod method=CommMethod::LOCAL)

virtual void	executeSetUp ()

virtual void	executeSetUp ()

virtual void	executeTearDown ()

virtual void	executeTearDown ()

void	saveGeneratorState ()

void	saveGeneratorState ()

void	restoreGeneratorState ()

void	restoreGeneratorState ()

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_samplessub
	Number of samples per subset. More...

const unsigned int &	_num_subsets
	Number of subsets. More...

const bool &	_use_absolute_value
	Absolute value of the model result. Use this when failure is defined as a non-exceedance rather than an exceedance. More...

const Real &	_subset_probability
	The subset conditional failure probability. More...

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

const std::vector< Real > &	_outputs
	Reporter value containing calculated outputs. More...

const std::vector< std::vector< Real > > &	_inputs
	Reporter value containing input values from decision reporter. More...

const int &	_step
	Track the current step of the main App. More...

const unsigned int	_count_max
	Maximum length of markov chains based on subset probability. More...

int	_check_step
	Ensure that the MCMC algorithm proceeds in a sequential fashion. More...

unsigned int	_subset
	Track the current subset index. More...

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

bool	_is_sampling_completed
	True if the sampling is completed. More...

	NONE

	LOCAL

	SEMI_LOCAL

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

const std::string	_type

const std::string	_name

const InputParameters &	_pars

Factory &	_factory

ActionFactory &	_action_factory

const ExecFlagEnum &	_execute_enum

const ExecFlagType &	_current_execute_flag

MooseApp &	_pg_moose_app

const std::string	_prefix

const Parallel::Communicator &	_communicator

Private Attributes
std::vector< std::vector< Real > >	_inputs_sto
	Storage for the previously accepted sample inputs across all the subsets. More...

std::vector< Real >	_outputs_sto
	Storage for previously accepted sample outputs across all the subsets. More...

std::vector< std::vector< Real > >	_inputs_sorted
	Store the sorted input samples according to their corresponding outputs. More...

std::vector< std::vector< Real > >	_markov_seed
	Mean input vector for the next proposed sample inputs across several processors. More...

Detailed Description

A class used to perform Parallel Subset Simulation Sampling.

Definition at line 18 of file ParallelSubsetSimulation.h.

Constructor & Destructor Documentation

◆ ParallelSubsetSimulation()

ParallelSubsetSimulation::ParallelSubsetSimulation ( const InputParameters & parameters )

Definition at line 46 of file ParallelSubsetSimulation.C.

   : Sampler(parameters),
     _num_samplessub(getParam<unsigned int>("num_samplessub")),
     _num_subsets(getParam<unsigned int>("num_subsets")),
     _use_absolute_value(getParam<bool>("use_absolute_value")),
     _subset_probability(getParam<Real>("subset_probability")),
     _num_random_seeds(getParam<unsigned int>("num_random_seeds")),
     _outputs(getReporterValue<std::vector<Real>>("output_reporter")),
     _inputs(getReporterValue<std::vector<std::vector<Real>>>("inputs_reporter")),
     _step(getCheckedPointerParam<FEProblemBase *>("_fe_problem_base")->timeStep()),
     _count_max(std::floor(1 / _subset_probability)),
     _check_step(0),
     _subset(0),
     _is_sampling_completed(false)
 {
   // Fixing the number of rows to the number of processors
   const dof_id_type nchains = isParamValid("num_parallel_chains")
                                   ? getParam<unsigned int>("num_parallel_chains")
                                   : n_processors() / _min_procs_per_row;
   setNumberOfRows(nchains);
   if ((_num_samplessub / nchains) % _count_max > 0)
     mooseError("Number of model evaluations per chain per subset (",
                _num_samplessub / nchains,
                ") should be a multiple of requested chain length (",
                _count_max,
                ").");
 
   // Filling the `distributions` vector with the user-provided distributions.
   for (const DistributionName & name : getParam<std::vector<DistributionName>>("distributions"))
     _distributions.push_back(&getDistributionByName(name));
 
   // Setting the number of columns in the sampler matrix (equal to the number of distributions).
   setNumberOfCols(_distributions.size());
 
   /* `inputs_sto` is a member variable that aids in deciding the next set of samples
   in the Subset Simulation algorithm by storing the input parameter values*/
   _inputs_sto.resize(_distributions.size(), std::vector<Real>(_num_samplessub, 0.0));
   _outputs_sto.resize(_num_samplessub, 0.0);
 
   /* `inputs_sorted` is a member variable which also aids in deciding the next set of samples
   in the Subset Simulation algorithm by storing the sorted input parameter values
   by their corresponding output values*/
   _inputs_sorted.resize(_distributions.size());
 
   /* `markov_seed` is a member variable to store the seed input values for proposing
   the next set of Markov chain samples.*/
   _markov_seed.resize(_distributions.size());
 
   setNumberOfRandomSeeds(_num_random_seeds);
 }

Member Function Documentation

◆ computeSample()

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

overrideprotectedvirtual

Implements Sampler.

Definition at line 182 of file ParallelSubsetSimulation.C.

 {
   unsigned int seed_value = _step > 0 ? (_step - 1) * 2 : 0;
   Real val;
 
   if (_subset == 0)
     val = getRand(seed_value);
   else
   {
     const dof_id_type loc_ind = row_index - getLocalRowBegin();
     const Real rv = Normal::quantile(getRand(seed_value), _markov_seed[col_index][loc_ind], 1.0);
     const Real acceptance_ratio = std::log(Normal::pdf(rv, 0, 1)) -
                                   std::log(Normal::pdf(_markov_seed[col_index][loc_ind], 0, 1));
     const Real new_sample = acceptance_ratio > std::log(getRand(seed_value + 1))
                                 ? rv
                                 : _markov_seed[col_index][loc_ind];
     val = Normal::cdf(new_sample, 0, 1);
   }
 
   return _distributions[col_index]->quantile(val);
 }

◆ getNumSamplesSub()

const unsigned int & ParallelSubsetSimulation::getNumSamplesSub ( ) const

Access the number samples per subset.

Definition at line 98 of file ParallelSubsetSimulation.C.

Referenced by AdaptiveMonteCarloDecision::AdaptiveMonteCarloDecision(), and AdaptiveMonteCarloDecision::execute().

 {
   return _num_samplessub;
 }

◆ getSubsetProbability()

const Real & ParallelSubsetSimulation::getSubsetProbability ( ) const

Access the subset probability.

Definition at line 110 of file ParallelSubsetSimulation.C.

Referenced by AdaptiveMonteCarloDecision::execute().

 {
   return _subset_probability;
 }

◆ getUseAbsoluteValue()

const bool & ParallelSubsetSimulation::getUseAbsoluteValue ( ) const

Access use absolute value bool.

Definition at line 104 of file ParallelSubsetSimulation.C.

Referenced by AdaptiveMonteCarloDecision::execute().

 {
   return _use_absolute_value;
 }

◆ isAdaptiveSamplingCompleted()

virtual bool ParallelSubsetSimulation::isAdaptiveSamplingCompleted ( ) const

inlineoverridevirtual

Returns true if the adaptive sampling is completed.

Reimplemented from Sampler.

Definition at line 37 of file ParallelSubsetSimulation.h.

37 { return _is_sampling_completed; }

ParallelSubsetSimulation::_is_sampling_completed

bool _is_sampling_completed

True if the sampling is completed.

Definition: ParallelSubsetSimulation.h:80

◆ sampleSetUp()

void ParallelSubsetSimulation::sampleSetUp ( const Sampler::SampleMode mode )

overrideprotectedvirtual

Reimplemented from Sampler.

Definition at line 116 of file ParallelSubsetSimulation.C.

 {
   if (_step <= 1 || _check_step == _step)
     return;
   _check_step = _step;
 
   if (_is_sampling_completed)
     mooseError("Internal bug: the adaptive sampling is supposed to be completed but another sample "
                "has been requested.");
 
   _subset = ((_step - 1) * getNumberOfRows()) / _num_samplessub;
   const unsigned int sub_ind = (_step - 1) - (_num_samplessub / getNumberOfRows()) * _subset;
   const unsigned int offset = sub_ind * getNumberOfRows();
 
   // Get and store the accepted samples input across all the procs from the previous step
   for (dof_id_type j = 0; j < _distributions.size(); ++j)
     for (dof_id_type ss = 0; ss < getNumberOfRows(); ++ss)
       _inputs_sto[j][ss + offset] = Normal::quantile(_distributions[j]->cdf(_inputs[j][ss]), 0, 1);
 
   // Get the accepted sample outputs across all the procs from the previous step
   std::vector<Real> tmp =
       _use_absolute_value ? AdaptiveMonteCarloUtils::computeVectorABS(_outputs) : _outputs;
   if (mode == Sampler::SampleMode::GLOBAL)
     _communicator.allgather(tmp);
   else
     _local_comm.allgather(tmp);
   for (dof_id_type ss = 0; ss < getNumberOfRows(); ++ss)
     _outputs_sto[ss + offset] = tmp[ss];
 
   // These are the subsequent subsets which use Markov Chain Monte Carlo sampling scheme
   if (_subset > 0)
   {
     // Check whether the subset index has changed
     if (sub_ind == 0)
     {
       // _inputs_sorted contains the input values corresponding to the largest po percentile
       // output values
       _inputs_sorted = AdaptiveMonteCarloUtils::sortInput(
           _inputs_sto, _outputs_sto, _num_samplessub, _subset_probability);
     }
 
     // Reinitialize the starting inputs values for the next set of Markov chains
     if (sub_ind % _count_max == 0)
     {
       const unsigned int soffset = (sub_ind / _count_max) * getNumberOfRows();
       for (dof_id_type j = 0; j < _distributions.size(); ++j)
         _markov_seed[j].assign(_inputs_sorted[j].begin() + soffset + getLocalRowBegin(),
                                _inputs_sorted[j].begin() + soffset + getLocalRowEnd());
     }
     // Otherwise, use the previously accepted input values to propose the next set of input
     // values
     else
     {
       for (dof_id_type j = 0; j < _distributions.size(); ++j)
         _markov_seed[j].assign(_inputs_sto[j].begin() + offset + getLocalRowBegin(),
                                _inputs_sto[j].begin() + offset + getLocalRowEnd());
     }
   }
 
   // check if we have completed the last sample (sub_ind == _num_samplessub /getNumberOfRows() - 1)
   // of the last subset (_subset == _num_subsets - 1)
   if (_subset == _num_subsets - 1 && sub_ind == _num_samplessub / getNumberOfRows() - 1)
     _is_sampling_completed = true;
 }

◆ validParams()

InputParameters ParallelSubsetSimulation::validParams ( )

static

Definition at line 18 of file ParallelSubsetSimulation.C.

 {
   InputParameters params = Sampler::validParams();
   params.addClassDescription("Parallel Subset Simulation sampler.");
   params.addRequiredParam<std::vector<DistributionName>>(
       "distributions",
       "The distribution names to be sampled, the number of distributions provided defines the "
       "number of columns per matrix.");
   params.addRequiredParam<ReporterName>("output_reporter",
                                         "Reporter with results of samples created by the SubApp.");
   params.addRequiredParam<ReporterName>("inputs_reporter", "Reporter with input parameters.");
   params.addRangeCheckedParam<Real>("subset_probability",
                                     0.1,
                                     "subset_probability>0 & subset_probability<=1",
                                     "Conditional probability of each subset");
   params.addRequiredParam<unsigned int>("num_samplessub", "Number of samples per subset");
   params.addRequiredParam<unsigned int>("num_subsets", "Number of desired subsets");
   params.addParam<unsigned int>("num_parallel_chains",
                                 "Number of Markov chains to run in parallel, default is based on "
                                 "the number of processors used.");
   params.addParam<bool>("use_absolute_value", false, "Use absolute value of the sub app output");
   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

◆ _check_step

int ParallelSubsetSimulation::_check_step

protected

Ensure that the MCMC algorithm proceeds in a sequential fashion.

Definition at line 71 of file ParallelSubsetSimulation.h.

Referenced by sampleSetUp().

◆ _count_max

const unsigned int ParallelSubsetSimulation::_count_max

protected

Maximum length of markov chains based on subset probability.

Definition at line 68 of file ParallelSubsetSimulation.h.

Referenced by ParallelSubsetSimulation(), and sampleSetUp().

◆ _distributions

std::vector<Distribution const *> ParallelSubsetSimulation::_distributions

protected

Storage for distribution objects to be utilized.

Definition at line 77 of file ParallelSubsetSimulation.h.

Referenced by computeSample(), ParallelSubsetSimulation(), and sampleSetUp().

◆ _inputs

const std::vector<std::vector<Real> >& ParallelSubsetSimulation::_inputs

protected

Reporter value containing input values from decision reporter.

Definition at line 62 of file ParallelSubsetSimulation.h.

Referenced by sampleSetUp().

◆ _inputs_sorted

std::vector<std::vector<Real> > ParallelSubsetSimulation::_inputs_sorted

private

Store the sorted input samples according to their corresponding outputs.

Definition at line 90 of file ParallelSubsetSimulation.h.

Referenced by ParallelSubsetSimulation(), and sampleSetUp().

◆ _inputs_sto

std::vector<std::vector<Real> > ParallelSubsetSimulation::_inputs_sto

private

Storage for the previously accepted sample inputs across all the subsets.

Definition at line 84 of file ParallelSubsetSimulation.h.

Referenced by ParallelSubsetSimulation(), and sampleSetUp().

◆ _is_sampling_completed

bool ParallelSubsetSimulation::_is_sampling_completed

protected

True if the sampling is completed.

Definition at line 80 of file ParallelSubsetSimulation.h.

Referenced by isAdaptiveSamplingCompleted(), and sampleSetUp().

◆ _markov_seed

std::vector<std::vector<Real> > ParallelSubsetSimulation::_markov_seed

private

Mean input vector for the next proposed sample inputs across several processors.

Definition at line 93 of file ParallelSubsetSimulation.h.

Referenced by computeSample(), ParallelSubsetSimulation(), and sampleSetUp().

◆ _num_random_seeds

const unsigned int& ParallelSubsetSimulation::_num_random_seeds

protected

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

Definition at line 56 of file ParallelSubsetSimulation.h.

Referenced by ParallelSubsetSimulation().

◆ _num_samplessub

const unsigned int& ParallelSubsetSimulation::_num_samplessub

protected

Number of samples per subset.

Definition at line 44 of file ParallelSubsetSimulation.h.

Referenced by getNumSamplesSub(), ParallelSubsetSimulation(), and sampleSetUp().

◆ _num_subsets

const unsigned int& ParallelSubsetSimulation::_num_subsets

protected

Number of subsets.

Definition at line 47 of file ParallelSubsetSimulation.h.

Referenced by sampleSetUp().

◆ _outputs

const std::vector<Real>& ParallelSubsetSimulation::_outputs

protected

Reporter value containing calculated outputs.

Definition at line 59 of file ParallelSubsetSimulation.h.

Referenced by sampleSetUp().

◆ _outputs_sto

std::vector<Real> ParallelSubsetSimulation::_outputs_sto

private

Storage for previously accepted sample outputs across all the subsets.

Definition at line 87 of file ParallelSubsetSimulation.h.

Referenced by ParallelSubsetSimulation(), and sampleSetUp().

◆ _step

const int& ParallelSubsetSimulation::_step

protected

Track the current step of the main App.

Definition at line 65 of file ParallelSubsetSimulation.h.

Referenced by computeSample(), and sampleSetUp().

◆ _subset

unsigned int ParallelSubsetSimulation::_subset

protected

Track the current subset index.

Definition at line 74 of file ParallelSubsetSimulation.h.

Referenced by computeSample(), and sampleSetUp().

◆ _subset_probability

const Real& ParallelSubsetSimulation::_subset_probability

protected

The subset conditional failure probability.

Definition at line 53 of file ParallelSubsetSimulation.h.

Referenced by getSubsetProbability(), and sampleSetUp().

◆ _use_absolute_value

const bool& ParallelSubsetSimulation::_use_absolute_value

protected

Absolute value of the model result. Use this when failure is defined as a non-exceedance rather than an exceedance.

Definition at line 50 of file ParallelSubsetSimulation.h.

Referenced by getUseAbsoluteValue(), and sampleSetUp().

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

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

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Protected Types

Protected Member Functions

Protected Attributes

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ ParallelSubsetSimulation()

Member Function Documentation

◆ computeSample()

◆ getNumSamplesSub()

◆ getSubsetProbability()

◆ getUseAbsoluteValue()

◆ isAdaptiveSamplingCompleted()

◆ sampleSetUp()

◆ validParams()

Member Data Documentation

◆ _check_step

◆ _count_max

◆ _distributions

◆ _inputs

◆ _inputs_sorted

◆ _inputs_sto

◆ _is_sampling_completed

◆ _markov_seed

◆ _num_random_seeds

◆ _num_samplessub

◆ _num_subsets

◆ _outputs

◆ _outputs_sto

◆ _step

◆ _subset

◆ _subset_probability

◆ _use_absolute_value