A class for performing Affine Invariant Ensemble MCMC with differential sampler. More...

#include <AffineInvariantDES.h>

Inheritance diagram for AffineInvariantDES:

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

typedef DataFileName	DataFileParameterType

Public Member Functions
	AffineInvariantDES (const InputParameters &parameters)

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

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...

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

void	computeDifferential (const Real &state1, const Real &state2, const Real &rnd, const Real &scale, Real &diff)
	Compute the differential evolution from the current state. More...

void	tuneParams (Real &gamma, Real &b, const Real &scale)
	Tune the internal parameters. 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 std::vector< std::vector< Real > > &	_previous_state
	Reporter value with the previous state of all the walkers. More...

const std::vector< Real > &	_previous_state_var
	Reporter value with the previous state of all the walkers for variance. More...

const MooseEnum &	_tuning_option
	Tuning options for the internal params. More...

std::vector< Real >	_scales
	Scales for the parameters. More...

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

Detailed Description

A class for performing Affine Invariant Ensemble MCMC with differential sampler.

Definition at line 17 of file AffineInvariantDES.h.

Constructor & Destructor Documentation

◆ AffineInvariantDES()

AffineInvariantDES::AffineInvariantDES ( const InputParameters & parameters )

Definition at line 40 of file AffineInvariantDES.C.

   : PMCMCBase(parameters),
     _previous_state(getReporterValue<std::vector<std::vector<Real>>>("previous_state")),
     _previous_state_var(getReporterValue<std::vector<Real>>("previous_state_var")),
     _tuning_option(getParam<MooseEnum>("tuning_option"))
 {
   if (_num_parallel_proposals < 5)
     paramError(
         "num_parallel_proposals",
         "At least five parallel proposals should be used for the Differential Evolution Sampler.");
 
   if (_num_parallel_proposals < _priors.size())
     mooseWarning(
         "It is recommended that the parallel proposals be greater than or equal to the "
         "inferred parameters. This will allow the sampler to not get stuck on a hyper-plane.");
 
   if (isParamValid("scales"))
   {
     _scales = getParam<std::vector<Real>>("scales");
     if (_scales.size() != _priors.size())
       paramError("scales",
                  "The number of scales provided should match the number of tunable params.");
   }
   else
     _scales.assign(_priors.size(), 1.0);
 }

Member Function Documentation

◆ computeDifferential()

void AffineInvariantDES::computeDifferential	(	const Real &	state1,
		const Real &	state2,
		const Real &	rnd,
		const Real &	scale,
		Real &	diff
	)

protected

Compute the differential evolution from the current state.

Parameters

state1	A randomly selected state 1 of the sampler
state2	A randomly selected state 2 of the sampler
rnd	Random number between 0 and 1
scale	The scale of the input parameter
diff	Differential between two randomly selected states

Definition at line 68 of file AffineInvariantDES.C.

Referenced by proposeSamples().

 {
   Real gamma;
   Real b;
   tuneParams(gamma, b, scale);
   diff = gamma * (state1 - state2) + Normal::quantile(rnd, 0.0, b);
 }

◆ computeSample()

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

overrideprotectedvirtualinherited

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 AffineInvariantDES::decisionStep ( ) const

inlineoverridevirtual

Return the step after which decision making can begin.

Reimplemented from PMCMCBase.

Definition at line 24 of file AffineInvariantDES.h.

Referenced by proposeSamples().

24 { return 2; }

◆ executeSetUp()

void PMCMCBase::executeSetUp ( )

overrideprotectedvirtualinherited

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

inlineinherited

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

inlineinherited

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

inlineinherited

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

inherited

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

inherited

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

inherited

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

inherited

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

inherited

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 AffineInvariantDES::proposeSamples ( )

overrideprotectedvirtual

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

Parameters

seed_value The seed for the random number generator

Reimplemented from PMCMCBase.

Definition at line 88 of file AffineInvariantDES.C.

 {
   unsigned int j = 0;
   bool indicator;
   std::pair<unsigned int, unsigned int> index_req;
   Real diff;
   while (j < _num_parallel_proposals)
   {
     indicator = 0;
     index_req = randomIndexPair(_num_parallel_proposals, j);
     for (unsigned int i = 0; i < _priors.size(); ++i)
     {
       computeDifferential(_previous_state[index_req.first][i],
                           _previous_state[index_req.second][i],
                           random(),
                           _scales[i],
                           diff);
       _new_samples[j][i] = (_t_step + 1 > decisionStep()) ? (_previous_state[j][i] + diff)
                                                           : _priors[i]->quantile(random());
       if (_lower_bound)
         indicator =
             (_new_samples[j][i] < (*_lower_bound)[i] || _new_samples[j][i] > (*_upper_bound)[i])
                 ? 1
                 : indicator;
     }
     if (_var_prior)
     {
       computeDifferential(_previous_state_var[index_req.first],
                           _previous_state_var[index_req.second],
                           random(),
                           1.0,
                           diff);
       _new_var_samples[j] = (_t_step + 1 > decisionStep()) ? (_previous_state_var[j] + diff)
                                                            : _var_prior->quantile(random());
       if (_new_var_samples[j] < 0.0 || _new_var_samples[j] > _variance_bound)
         indicator = 1;
     }
     if (!indicator)
       ++j;
   }
 }

◆ random()

Real PMCMCBase::random ( )

protectedinherited

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 PMCMCBase::executeSetUp(), IndependentGaussianMH::proposeSamples(), proposeSamples(), AffineInvariantStretchSampler::proposeSamples(), BayesianActiveLearningSampler::proposeSamples(), and PMCMCBase::proposeSamples().

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

◆ randomIndex()

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

protectedinherited

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 PMCMCBase::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
	)

protectedinherited

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 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};
 }

◆ tuneParams()

void AffineInvariantDES::tuneParams	(	Real &	gamma,
		Real &	b,
		const Real &	scale
	)

protected

Tune the internal parameters.

Parameters

gamma	An internal parameter
b	An internal parameter
scale	The scale of the input parameter

Definition at line 78 of file AffineInvariantDES.C.

Referenced by computeDifferential().

 {
   if (_tuning_option == "Braak2006_static")
   {
     gamma = 2.38 / std::sqrt(2 * _priors.size());
     b = 1e-6 * scale;
   }
 }

◆ validParams()

InputParameters AffineInvariantDES::validParams ( )

static

Definition at line 24 of file AffineInvariantDES.C.

 {
   InputParameters params = PMCMCBase::validParams();
   params.addClassDescription("Perform Affine Invariant Ensemble MCMC with differential sampler.");
   params.addRequiredParam<ReporterName>(
       "previous_state", "Reporter value with the previous state of all the walkers.");
   params.addRequiredParam<ReporterName>(
       "previous_state_var",
       "Reporter value with the previous state of all the walkers for variance.");
   MooseEnum tuning_option("Braak2006_static", "Braak2006_static");
   params.addParam<MooseEnum>(
       "tuning_option", tuning_option, "The tuning option for internal parameters.");
   params.addParam<std::vector<Real>>("scales", "Scales for the parameters.");
   return params;
 }

Member Data Documentation

◆ _initial_values

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

protectedinherited

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

Definition at line 130 of file PMCMCBase.h.

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

◆ _lower_bound

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

protectedinherited

Lower bounds for making the next proposal.

Definition at line 121 of file PMCMCBase.h.

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

◆ _new_samples

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

protectedinherited

Vectors of new proposed samples.

Definition at line 133 of file PMCMCBase.h.

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

◆ _new_var_samples

std::vector<Real> PMCMCBase::_new_var_samples

protectedinherited

Vector of new proposed variance samples.

Definition at line 136 of file PMCMCBase.h.

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

◆ _num_parallel_proposals

const unsigned int PMCMCBase::_num_parallel_proposals

protectedinherited

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

Definition at line 112 of file PMCMCBase.h.

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

◆ _previous_state

const std::vector<std::vector<Real> >& AffineInvariantDES::_previous_state

protected

Reporter value with the previous state of all the walkers.

Definition at line 49 of file AffineInvariantDES.h.

Referenced by proposeSamples().

◆ _previous_state_var

const std::vector<Real>& AffineInvariantDES::_previous_state_var

protected

Reporter value with the previous state of all the walkers for variance.

Definition at line 52 of file AffineInvariantDES.h.

Referenced by proposeSamples().

◆ _priors

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

protectedinherited

Storage for prior distribution objects to be utilized.

Definition at line 115 of file PMCMCBase.h.

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

◆ _rnd_vec

std::vector<Real> PMCMCBase::_rnd_vec

protectedinherited

Vector of random numbers for decision making.

Definition at line 139 of file PMCMCBase.h.

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

◆ _scales

std::vector<Real> AffineInvariantDES::_scales

protected

Scales for the parameters.

Definition at line 58 of file AffineInvariantDES.h.

Referenced by AffineInvariantDES(), and proposeSamples().

◆ _tuning_option

const MooseEnum& AffineInvariantDES::_tuning_option

protected

Tuning options for the internal params.

Definition at line 55 of file AffineInvariantDES.h.

Referenced by tuneParams().

◆ _upper_bound

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

protectedinherited

Upper bounds for making the next proposal.

Definition at line 124 of file PMCMCBase.h.

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

◆ _var_prior

const Distribution* PMCMCBase::_var_prior

protectedinherited

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

Definition at line 118 of file PMCMCBase.h.

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

◆ _variance_bound

const Real& PMCMCBase::_variance_bound

protectedinherited

Upper bound for variance for making the next proposal.

Definition at line 127 of file PMCMCBase.h.

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

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

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

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Protected Member Functions

Protected Attributes

Detailed Description

Constructor & Destructor Documentation

◆ AffineInvariantDES()

Member Function Documentation

◆ computeDifferential()

◆ computeSample()

◆ decisionStep()

◆ executeSetUp()

◆ getNumberOfConfigParams()

◆ getNumberOfConfigValues()

◆ getNumParallelProposals()

◆ getPriors()

◆ getRandomNumbers()

◆ getSamples()

◆ getVarPrior()

◆ getVarSamples()

◆ proposeSamples()

◆ random()

◆ randomIndex()

◆ randomIndexPair()

◆ tuneParams()

◆ validParams()

Member Data Documentation

◆ _initial_values

◆ _lower_bound

◆ _new_samples

◆ _new_var_samples

◆ _num_parallel_proposals

◆ _previous_state

◆ _previous_state_var

◆ _priors

◆ _rnd_vec

◆ _scales

◆ _tuning_option

◆ _upper_bound

◆ _var_prior

◆ _variance_bound