#include <ActiveLearningGPDecision.h>

Inheritance diagram for ActiveLearningGPDecision:

Public Types
typedef DataFileName	DataFileParameterType

Public Member Functions
	ActiveLearningGPDecision (const InputParameters &parameters)

const int &	getTrainingSamples () const
	Access the number of training samples.

virtual void	execute () override
	Here we loop through the samples and call the needSample function to determine if the sample needs to be run and define a value in its place.

virtual void	initialize () override final

virtual void	finalize () override

void	threadJoin (const UserObject &) final

bool	shouldStore () const override final

virtual Real	spatialValue (const Point &) const

virtual const std::vector< Point >	spatialPoints () const

void	setPrimaryThreadCopy (UserObject *primary)

UserObject *	primaryThreadCopy ()

SubProblem &	getSubProblem () const

bool	shouldDuplicateInitialExecution () const

void	gatherSum (T &value)

void	gatherMax (T &value)

void	gatherMin (T &value)

void	gatherProxyValueMax (T1 &proxy, T2 &value)

void	gatherProxyValueMin (T1 &proxy, T2 &value)

std::set< UserObjectName >	getDependObjects () const

const std::set< std::string > &	getRequestedItems () override

const std::set< std::string > &	getSuppliedItems () override

unsigned int	systemNumber () const

virtual bool	needThreadedCopy () const

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	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	customSetup (const ExecFlagType &)

const ExecFlagEnum &	getExecuteOnEnum () const

UserObjectName	getUserObjectName (const std::string &param_name) const

const T &	getUserObject (const std::string &param_name, bool is_dependency=true) const

const T &	getUserObjectByName (const UserObjectName &object_name, bool is_dependency=true) const

const UserObjectBase &	getUserObjectBase (const std::string &param_name, bool is_dependency=true) const

const UserObjectBase &	getUserObjectBaseByName (const UserObjectName &object_name, bool is_dependency=true) const

const std::vector< MooseVariableScalar * > &	getCoupledMooseScalarVars ()

const std::set< TagID > &	getScalarVariableCoupleableVectorTags () const

const std::set< TagID > &	getScalarVariableCoupleableMatrixTags () const

const GenericMaterialProperty< T, is_ad > &	getGenericMaterialProperty (const std::string &name, MaterialData &material_data, const unsigned int state=0)

const GenericMaterialProperty< T, is_ad > &	getGenericMaterialProperty (const std::string &name, const unsigned int state=0)

const GenericMaterialProperty< T, is_ad > &	getGenericMaterialProperty (const std::string &name, const unsigned int state=0)

const MaterialProperty< T > &	getMaterialProperty (const std::string &name, MaterialData &material_data, const unsigned int state=0)

const MaterialProperty< T > &	getMaterialProperty (const std::string &name, const unsigned int state=0)

const MaterialProperty< T > &	getMaterialProperty (const std::string &name, const unsigned int state=0)

const ADMaterialProperty< T > &	getADMaterialProperty (const std::string &name, MaterialData &material_data)

const ADMaterialProperty< T > &	getADMaterialProperty (const std::string &name)

const ADMaterialProperty< T > &	getADMaterialProperty (const std::string &name)

const MaterialProperty< T > &	getMaterialPropertyOld (const std::string &name, MaterialData &material_data)

const MaterialProperty< T > &	getMaterialPropertyOld (const std::string &name)

const MaterialProperty< T > &	getMaterialPropertyOld (const std::string &name)

const MaterialProperty< T > &	getMaterialPropertyOlder (const std::string &name, MaterialData &material_data)

const MaterialProperty< T > &	getMaterialPropertyOlder (const std::string &name)

const MaterialProperty< T > &	getMaterialPropertyOlder (const std::string &name)

const GenericMaterialProperty< T, is_ad > &	getGenericMaterialPropertyByName (const MaterialPropertyName &name, MaterialData &material_data, const unsigned int state)

const GenericMaterialProperty< T, is_ad > &	getGenericMaterialPropertyByName (const MaterialPropertyName &name, const unsigned int state=0)

const GenericMaterialProperty< T, is_ad > &	getGenericMaterialPropertyByName (const MaterialPropertyName &name, const unsigned int state=0)

const MaterialProperty< T > &	getMaterialPropertyByName (const MaterialPropertyName &name, MaterialData &material_data, const unsigned int state=0)

const MaterialProperty< T > &	getMaterialPropertyByName (const MaterialPropertyName &name, const unsigned int state=0)

const MaterialProperty< T > &	getMaterialPropertyByName (const MaterialPropertyName &name, const unsigned int state=0)

const ADMaterialProperty< T > &	getADMaterialPropertyByName (const MaterialPropertyName &name, MaterialData &material_data)

const ADMaterialProperty< T > &	getADMaterialPropertyByName (const MaterialPropertyName &name)

const ADMaterialProperty< T > &	getADMaterialPropertyByName (const MaterialPropertyName &name)

const MaterialProperty< T > &	getMaterialPropertyOldByName (const MaterialPropertyName &name, MaterialData &material_data)

const MaterialProperty< T > &	getMaterialPropertyOldByName (const MaterialPropertyName &name)

const MaterialProperty< T > &	getMaterialPropertyOldByName (const MaterialPropertyName &name)

const MaterialProperty< T > &	getMaterialPropertyOlderByName (const MaterialPropertyName &name, MaterialData &material_data)

const MaterialProperty< T > &	getMaterialPropertyOlderByName (const MaterialPropertyName &name)

const MaterialProperty< T > &	getMaterialPropertyOlderByName (const MaterialPropertyName &name)

Moose::Kokkos::MaterialProperty< T, dimension >	getKokkosMaterialPropertyByName (const std::string &prop_name_in)

Moose::Kokkos::MaterialProperty< T, dimension >	getKokkosMaterialPropertyOldByName (const std::string &prop_name)

Moose::Kokkos::MaterialProperty< T, dimension >	getKokkosMaterialPropertyOlderByName (const std::string &prop_name)

Moose::Kokkos::MaterialProperty< T, dimension >	getKokkosMaterialProperty (const std::string &name)

Moose::Kokkos::MaterialProperty< T, dimension >	getKokkosMaterialPropertyOld (const std::string &name)

Moose::Kokkos::MaterialProperty< T, dimension >	getKokkosMaterialPropertyOlder (const std::string &name)

std::pair< const MaterialProperty< T > *, std::set< SubdomainID > >	getBlockMaterialProperty (const MaterialPropertyName &name)

std::pair< Moose::Kokkos::MaterialProperty< T, dimension >, std::set< SubdomainID > >	getKokkosBlockMaterialProperty (const MaterialPropertyName &name)

const GenericMaterialProperty< T, is_ad > &	getGenericZeroMaterialProperty (const std::string &name)

const GenericMaterialProperty< T, is_ad > &	getGenericZeroMaterialProperty ()

const GenericMaterialProperty< T, is_ad > &	getGenericZeroMaterialPropertyByName (const std::string &prop_name)

const MaterialProperty< T > &	getZeroMaterialProperty (Ts... args)

std::set< SubdomainID >	getMaterialPropertyBlocks (const std::string &name)

std::vector< SubdomainName >	getMaterialPropertyBlockNames (const std::string &name)

std::set< BoundaryID >	getMaterialPropertyBoundaryIDs (const std::string &name)

std::vector< BoundaryName >	getMaterialPropertyBoundaryNames (const std::string &name)

void	checkBlockAndBoundaryCompatibility (std::shared_ptr< MaterialBase > discrete)

std::unordered_map< SubdomainID, std::vector< MaterialBase * > >	buildRequiredMaterials (bool allow_stateful=true)

void	statefulPropertiesAllowed (bool)

virtual bool	getMaterialPropertyCalled () const

virtual const std::unordered_set< unsigned int > &	getMatPropDependencies () const

virtual void	resolveOptionalProperties ()

const GenericMaterialProperty< T, is_ad > &	getPossiblyConstantGenericMaterialPropertyByName (const MaterialPropertyName &prop_name, MaterialData &material_data, const unsigned int state)

bool	isImplicit ()

Moose::StateArg	determineState () const

virtual void	store (nlohmann::json &json) const

virtual void	declareLateValues ()

void	buildOutputHideVariableList (std::set< std::string > variable_names)

const std::set< OutputName > &	getOutputs ()

virtual void	subdomainSetup () override

virtual void	subdomainSetup () override

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

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

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

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

bool	hasUserObjectByName (const UserObjectName &object_name) const

bool	hasUserObjectByName (const UserObjectName &object_name) const

bool	hasUserObjectByName (const UserObjectName &object_name) const

bool	hasUserObjectByName (const UserObjectName &object_name) const

const GenericOptionalMaterialProperty< T, is_ad > &	getGenericOptionalMaterialProperty (const std::string &name, const unsigned int state=0)

const GenericOptionalMaterialProperty< T, is_ad > &	getGenericOptionalMaterialProperty (const std::string &name, const unsigned int state=0)

const OptionalMaterialProperty< T > &	getOptionalMaterialProperty (const std::string &name, const unsigned int state=0)

const OptionalMaterialProperty< T > &	getOptionalMaterialProperty (const std::string &name, const unsigned int state=0)

const OptionalADMaterialProperty< T > &	getOptionalADMaterialProperty (const std::string &name)

const OptionalADMaterialProperty< T > &	getOptionalADMaterialProperty (const std::string &name)

const OptionalMaterialProperty< T > &	getOptionalMaterialPropertyOld (const std::string &name)

const OptionalMaterialProperty< T > &	getOptionalMaterialPropertyOld (const std::string &name)

const OptionalMaterialProperty< T > &	getOptionalMaterialPropertyOlder (const std::string &name)

const OptionalMaterialProperty< T > &	getOptionalMaterialPropertyOlder (const std::string &name)

MaterialBase &	getMaterial (const std::string &name)

MaterialBase &	getMaterial (const std::string &name)

MaterialBase &	getMaterialByName (const std::string &name, bool no_warn=false)

MaterialBase &	getMaterialByName (const std::string &name, bool no_warn=false)

bool	hasMaterialProperty (const std::string &name)

bool	hasMaterialProperty (const std::string &name)

bool	hasMaterialPropertyByName (const std::string &name)

bool	hasMaterialPropertyByName (const std::string &name)

bool	hasADMaterialProperty (const std::string &name)

bool	hasADMaterialProperty (const std::string &name)

bool	hasADMaterialPropertyByName (const std::string &name)

bool	hasADMaterialPropertyByName (const std::string &name)

bool	hasKokkosMaterialProperty (const std::string &name)

bool	hasKokkosMaterialProperty (const std::string &name)

bool	hasKokkosMaterialPropertyByName (const std::string &name)

bool	hasKokkosMaterialPropertyByName (const std::string &name)

bool	hasGenericMaterialProperty (const std::string &name)

bool	hasGenericMaterialProperty (const std::string &name)

bool	hasGenericMaterialPropertyByName (const std::string &name)

bool	hasGenericMaterialPropertyByName (const std::string &name)

const Function &	getFunction (const std::string &name) const

const Function &	getFunctionByName (const FunctionName &name) const

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

bool	hasFunctionByName (const FunctionName &name) const

Moose::Kokkos::Function	getKokkosFunction (const std::string &name) const

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

Moose::Kokkos::Function	getKokkosFunctionByName (const FunctionName &name) const

const T &	getKokkosFunctionByName (const FunctionName &name) const

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

bool	hasKokkosFunctionByName (const FunctionName &name) const

bool	isDefaultPostprocessorValue (const std::string &param_name, const unsigned int index=0) const

bool	hasPostprocessor (const std::string &param_name, const unsigned int index=0) const

bool	hasPostprocessorByName (const PostprocessorName &name) const

std::size_t	coupledPostprocessors (const std::string &param_name) const

const PostprocessorName &	getPostprocessorName (const std::string &param_name, const unsigned int index=0) const

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

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

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

T &	getSamplerByName (const SamplerName &name)

Sampler &	getSamplerByName (const SamplerName &name)

virtual void	meshChanged ()

virtual void	meshDisplaced ()

PerfGraph &	perfGraph ()

const PostprocessorValue &	getPostprocessorValue (const std::string &param_name, const unsigned int index=0) const

const PostprocessorValue &	getPostprocessorValue (const std::string &param_name, const unsigned int index=0) const

const PostprocessorValue &	getPostprocessorValueOld (const std::string &param_name, const unsigned int index=0) const

const PostprocessorValue &	getPostprocessorValueOld (const std::string &param_name, const unsigned int index=0) const

const PostprocessorValue &	getPostprocessorValueOlder (const std::string &param_name, const unsigned int index=0) const

const PostprocessorValue &	getPostprocessorValueOlder (const std::string &param_name, const unsigned int index=0) const

virtual const PostprocessorValue &	getPostprocessorValueByName (const PostprocessorName &name) const

virtual const PostprocessorValue &	getPostprocessorValueByName (const PostprocessorName &name) const

const PostprocessorValue &	getPostprocessorValueOldByName (const PostprocessorName &name) const

const PostprocessorValue &	getPostprocessorValueOldByName (const PostprocessorName &name) const

const PostprocessorValue &	getPostprocessorValueOlderByName (const PostprocessorName &name) const

const PostprocessorValue &	getPostprocessorValueOlderByName (const PostprocessorName &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 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

const Parallel::Communicator &	comm () const

processor_id_type	n_processors () const

processor_id_type	processor_id () const

template<>
SurrogateModel &	getSurrogateModel (const std::string &name) const

template<>
SurrogateTrainerBase &	getSurrogateTrainer (const std::string &name) const

template<>
SurrogateModel &	getSurrogateModelByName (const UserObjectName &name) const

template<>
SurrogateTrainerBase &	getSurrogateTrainerByName (const UserObjectName &name) const


template<typename T = SurrogateModel>
T &	getSurrogateModel (const std::string &name) const
	Get a SurrogateModel/Trainer with a given name.

template<typename T = SurrogateTrainerBase>
T &	getSurrogateTrainer (const std::string &name) const


template<typename T = SurrogateModel>
T &	getSurrogateModelByName (const UserObjectName &name) const
	Get a sampler with a given name.

template<typename T = SurrogateTrainerBase>
T &	getSurrogateTrainerByName (const UserObjectName &name) 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)

static void	sort (typename std::vector< T > &vector)

static void	sortDFS (typename std::vector< T > &vector)

static void	cyclicDependencyError (CyclicDependencyException< T2 > &e, const std::string &header, NameFunc &&name_func)

static void	cyclicDependencyError (CyclicDependencyException< T2 > &e, const std::string &header)

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

static constexpr PropertyValue::id_type	default_property_id

static constexpr PropertyValue::id_type	zero_property_id

static constexpr auto	SYSTEM

static constexpr auto	NAME

Protected Member Functions
virtual void	preNeedSample () override
	This is where most of the computations happen:

virtual bool	needSample (const std::vector< Real > &row, dof_id_type local_ind, dof_id_type global_ind, Real &val) override
	Based on the computations in preNeedSample, the decision to get more data is passed and results from the GP fills.

virtual bool	facilitateDecision ()
	Make decisions whether to call the full model or not based on GP prediction and uncertainty.

virtual void	setupData (const std::vector< std::vector< Real > > &inputs, const std::vector< Real > &outputs)
	This sets up data for re-training the GP.

bool	learningFunction (const Real &gp_mean, const Real &gp_std) const
	This method evaluates the active learning acquisition function and returns bool that indicates whether the GP model failed.

virtual ReporterName	declareStochasticReporterClone (const Sampler &sampler, const ReporterData &from_data, const ReporterName &from_reporter, std::string prefix="") override
	This is overriden for the following reasons: 1) Only one vector can be declared and must match the type of this class.

const Sampler &	sampler () const
	Get a const reference to the sampler from the parameters.

const std::vector< std::vector< Real > > &	getGlobalInputData () const

const std::vector< Real > &	getGlobalOutputData () const
	Get a const reference to the output data.

template<typename T >
std::vector< T > &	declareStochasticReporter (std::string value_name, const Sampler &sampler)

virtual void	addPostprocessorDependencyHelper (const PostprocessorName &name) const override

virtual void	addVectorPostprocessorDependencyHelper (const VectorPostprocessorName &name) const override

virtual void	addUserObjectDependencyHelper (const UserObjectBase &uo) const override

void	addReporterDependencyHelper (const ReporterName &reporter_name) override

void	flagInvalidSolutionInternal (const InvalidSolutionID invalid_solution_id) const

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

const ReporterContextBase &	getReporterContextBaseByName (const ReporterName &reporter_name) const

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

T &	declareRestartableData (const std::string &data_name, Args &&... args)

ManagedValue< T >	declareManagedRestartableDataWithContext (const std::string &data_name, void *context, Args &&... args)

const T &	getRestartableData (const std::string &data_name) const

T &	declareRestartableDataWithContext (const std::string &data_name, void *context, Args &&... args)

T &	declareRecoverableData (const std::string &data_name, Args &&... args)

T &	declareRestartableDataWithObjectName (const std::string &data_name, const std::string &object_name, Args &&... args)

T &	declareRestartableDataWithObjectNameWithContext (const std::string &data_name, const std::string &object_name, void *context, Args &&... args)

std::string	restartableName (const std::string &data_name) const

const T &	getMeshProperty (const std::string &data_name, const std::string &prefix)

const T &	getMeshProperty (const std::string &data_name)

bool	hasMeshProperty (const std::string &data_name, const std::string &prefix) const

bool	hasMeshProperty (const std::string &data_name, const std::string &prefix) const

bool	hasMeshProperty (const std::string &data_name) const

bool	hasMeshProperty (const std::string &data_name) const

std::string	meshPropertyName (const std::string &data_name) 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

bool	isCoupledScalar (const std::string &var_name, unsigned int i=0) const

unsigned int	coupledScalarComponents (const std::string &var_name) const

unsigned int	coupledScalar (const std::string &var_name, unsigned int comp=0) const

libMesh::Order	coupledScalarOrder (const std::string &var_name, unsigned int comp=0) const

const VariableValue &	coupledScalarValue (const std::string &var_name, unsigned int comp=0) const

const ADVariableValue &	adCoupledScalarValue (const std::string &var_name, unsigned int comp=0) const

const GenericVariableValue< is_ad > &	coupledGenericScalarValue (const std::string &var_name, unsigned int comp=0) const

const GenericVariableValue< false > &	coupledGenericScalarValue (const std::string &var_name, const unsigned int comp) const

const GenericVariableValue< true > &	coupledGenericScalarValue (const std::string &var_name, const unsigned int comp) const

const VariableValue &	coupledVectorTagScalarValue (const std::string &var_name, TagID tag, unsigned int comp=0) const

const VariableValue &	coupledMatrixTagScalarValue (const std::string &var_name, TagID tag, unsigned int comp=0) const

const VariableValue &	coupledScalarValueOld (const std::string &var_name, unsigned int comp=0) const

const VariableValue &	coupledScalarValueOlder (const std::string &var_name, unsigned int comp=0) const

const VariableValue &	coupledScalarDot (const std::string &var_name, unsigned int comp=0) const

const ADVariableValue &	adCoupledScalarDot (const std::string &var_name, unsigned int comp=0) const

const VariableValue &	coupledScalarDotDot (const std::string &var_name, unsigned int comp=0) const

const VariableValue &	coupledScalarDotOld (const std::string &var_name, unsigned int comp=0) const

const VariableValue &	coupledScalarDotDotOld (const std::string &var_name, unsigned int comp=0) const

const VariableValue &	coupledScalarDotDu (const std::string &var_name, unsigned int comp=0) const

const VariableValue &	coupledScalarDotDotDu (const std::string &var_name, unsigned int comp=0) const

const MooseVariableScalar *	getScalarVar (const std::string &var_name, unsigned int comp) const

virtual void	checkMaterialProperty (const std::string &name, const unsigned int state)

virtual void	getKokkosMaterialPropertyHook (const std::string &, const unsigned int)

void	markMatPropRequested (const std::string &)

MaterialPropertyName	getMaterialPropertyName (const std::string &name) const

void	checkExecutionStage ()

T &	declareUnusedValue (Args &&... args)

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

const GenericMaterialProperty< T, is_ad > *	defaultGenericMaterialProperty (const std::string &name)

const GenericMaterialProperty< T, is_ad > *	defaultGenericMaterialProperty (const std::string &name)

const MaterialProperty< T > *	defaultMaterialProperty (const std::string &name)

const MaterialProperty< T > *	defaultMaterialProperty (const std::string &name)

const ADMaterialProperty< T > *	defaultADMaterialProperty (const std::string &name)

const ADMaterialProperty< T > *	defaultADMaterialProperty (const std::string &name)

T &	declareValue (const std::string &param_name, Args &&... args)

T &	declareValue (const std::string &param_name, ReporterMode mode, Args &&... args)

T &	declareValue (const std::string &param_name, Args &&... args)

T &	declareValue (const std::string &param_name, ReporterMode mode, Args &&... args)

T &	declareValue (const std::string &param_name, Args &&... args)

T &	declareValue (const std::string &param_name, ReporterMode mode, Args &&... args)

T &	declareValue (const std::string &param_name, Args &&... args)

T &	declareValue (const std::string &param_name, ReporterMode mode, Args &&... args)

T &	declareValueByName (const ReporterValueName &value_name, Args &&... args)

T &	declareValueByName (const ReporterValueName &value_name, ReporterMode mode, Args &&... args)

T &	declareValueByName (const ReporterValueName &value_name, Args &&... args)

T &	declareValueByName (const ReporterValueName &value_name, ReporterMode mode, Args &&... args)

T &	declareValueByName (const ReporterValueName &value_name, Args &&... args)

T &	declareValueByName (const ReporterValueName &value_name, ReporterMode mode, Args &&... args)

T &	declareValueByName (const ReporterValueName &value_name, Args &&... args)

T &	declareValueByName (const ReporterValueName &value_name, ReporterMode mode, Args &&... args)

Static Protected Member Functions
static std::string	meshPropertyName (const std::string &data_name, const std::string &prefix)

Protected Attributes
const MooseEnum &	_learning_function
	The learning function for active learning.

const Real &	_learning_function_threshold
	The learning function threshold.

const Real &	_learning_function_parameter
	The learning function parameter.

std::vector< std::vector< Real > >	_inputs_batch
	Store all the input vectors used for training.

std::vector< Real >	_outputs_batch
	Store all the outputs used for training.

const ActiveLearningGaussianProcess &	_al_gp
	The active learning GP trainer that permits re-training.

const SurrogateModel &	_gp_eval
	The GP evaluator object that permits re-evaluations.

std::vector< bool > &	_flag_sample
	Flag samples when the GP fails.

const int	_n_train
	Number of initial training points for GP.

std::vector< std::vector< Real > > &	_inputs
	Storage for the input vectors to be transferred to the output file.

std::vector< Real > &	_gp_mean
	Broadcast the GP mean prediciton to JSON.

std::vector< Real > &	_gp_std
	Broadcast the GP standard deviation to JSON.

bool	_decision
	GP pass/fail decision.

const std::vector< std::vector< Real > > &	_inputs_global
	Reference to global input data requested from base class.

const std::vector< Real > &	_outputs_global
	Reference to global output data requested from base class.

Sampler &	_sampler
	Sampler given in the parameters, must match the one used to declare the transferred values.

const Moose::CoordinateSystemType &	_coord_sys

const THREAD_ID	_tid

SubProblem &	_subproblem

FEProblemBase &	_fe_problem

SystemBase &	_sys

Assembly &	_assembly

const bool	_duplicate_initial_execution

std::set< std::string >	_depend_uo

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 &	_restartable_app

const std::string	_restartable_system_name

const THREAD_ID	_restartable_tid

const bool	_restartable_read_only

FEProblemBase &	_mci_feproblem

FEProblemBase &	_mdi_feproblem

MooseApp &	_pg_moose_app

const std::string	_prefix

FEProblemBase &	_sc_fe_problem

const THREAD_ID	_sc_tid

const Real &	_real_zero

const VariableValue &	_scalar_zero

const Point &	_point_zero

const InputParameters &	_mi_params

const std::string	_mi_name

const MooseObjectName	_mi_moose_object_name

FEProblemBase &	_mi_feproblem

SubProblem &	_mi_subproblem

const THREAD_ID	_mi_tid

const bool	_is_kokkos_object

const Moose::MaterialDataType	_material_data_type

MaterialData &	_material_data

bool	_stateful_allowed

bool	_get_material_property_called

std::vector< std::unique_ptr< PropertyValue > >	_default_properties

std::unordered_set< unsigned int >	_material_property_dependencies

const MaterialPropertyName	_get_suffix

const bool	_use_interpolated_state

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

const Parallel::Communicator &	_communicator

Static Protected Attributes
static const std::string	_interpolated_old

static const std::string	_interpolated_older

Private Member Functions
const Moose::FunctionBase *	getKokkosFunctionByNameHelper (const FunctionName &name) const

const UserObjectBase &	getUserObjectFromFEProblem (const UserObjectName &object_name, const THREAD_ID tid=0) const

const T &	castUserObject (const UserObjectBase &uo_base, const std::string &param_name="") const

void	mooseObjectError (const std::string &param_name, std::stringstream &oss) const

const std::string &	userObjectType (const UserObjectBase &uo) const

const std::string &	userObjectName (const UserObjectBase &uo) const

const PostprocessorName &	getPostprocessorNameInternal (const std::string &param_name, const unsigned int index, const bool allow_default_value=true) const

bool	isDefaultPostprocessorValueByName (const PostprocessorName &name) const

PostprocessorValue	getDefaultPostprocessorValueByName (const PostprocessorName &name) const

void	checkParam (const std::string &param_name, const unsigned int index=std::numeric_limits< unsigned int >::max()) const

bool	postprocessorsAdded () const

const VectorPostprocessorValue &	getVectorPostprocessorByNameHelper (const VectorPostprocessorName &name, const std::string &vector_name, bool broadcast, std::size_t t_index) const

const VectorPostprocessorContext< VectorPostprocessorValue > &	getVectorPostprocessorContextByNameHelper (const VectorPostprocessorName &name, const std::string &vector_name) const

bool	vectorPostprocessorsAdded () const

bool	reportersAdded () const

void	possiblyCheckHasReporter (const ReporterName &reporter_name, const std::string &param_name="") const

RestartableDataValue &	registerRestartableDataOnApp (std::unique_ptr< RestartableDataValue > data, THREAD_ID tid) const

void	registerRestartableNameWithFilterOnApp (const std::string &name, Moose::RESTARTABLE_FILTER filter)

RestartableData< T > &	declareRestartableDataHelper (const std::string &data_name, void *context, Args &&... args) const

virtual std::string	meshPropertyPrefix (const std::string &data_name) const

const RestartableDataValue &	getMeshPropertyInternal (const std::string &data_name, const std::string &prefix) const

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

const VariableValue *	getDefaultValue (const std::string &var_name) const

const ADVariableValue *	getADDefaultValue (const std::string &var_name) const

void	checkVar (const std::string &var_name) const

void	validateExecutionerType (const std::string &name, const std::string &fn_name) const

Moose::MaterialDataType	getMaterialDataType (const std::set< BoundaryID > &boundary_ids) const

unsigned int	getMaxQps () const

void	addConsumedPropertyName (const MooseObjectName &obj_name, const std::string &prop_name)

const ReporterValueName &	getReporterValueName (const std::string &param_name) const

const PostprocessorValue &	getPostprocessorValueInternal (const std::string &param_name, unsigned int index, std::size_t t_index) const

const PostprocessorValue &	getPostprocessorValueInternal (const std::string &param_name, unsigned int index, std::size_t t_index) const

const PostprocessorValue &	getPostprocessorValueByNameInternal (const PostprocessorName &name, std::size_t t_index) const

const PostprocessorValue &	getPostprocessorValueByNameInternal (const PostprocessorName &name, std::size_t t_index) const

void	possiblyCheckHasVectorPostprocessor (const std::string &param_name, const std::string &vector_name) const

void	possiblyCheckHasVectorPostprocessor (const std::string &param_name, const std::string &vector_name) const

void	possiblyCheckHasVectorPostprocessorByName (const VectorPostprocessorName &name, const std::string &vector_name) const

void	possiblyCheckHasVectorPostprocessorByName (const VectorPostprocessorName &name, const std::string &vector_name) const

Static Private Member Functions
static const hit::Node *	getHitNode (const InputParameters &params)

static std::string	messagePrefix (const InputParameters &params, const bool hit_prefix)

Private Attributes
std::vector< bool > &	_need_sample
	Reporter value determining whether we need to evaluate the sample through a multiapp or other means.

std::vector< Real > *	_data
	Reporter value declared with the transfer.

bool	_input_data_requested
	Whether or not to gather global input data.

bool	_output_data_requested
	Whether or not to gather global output data.

std::vector< std::vector< Real > >	_input_data
	Global input data from sampler.

std::vector< Real >	_output_data
	Global output data from sampler.

const unsigned int	_parallel_type

std::deque< std::unique_ptr< StochasticReporterValueBase > >	_vectors
	Container for declared values that we may need to resize at initialize.

const bool	_always_store

UserObject *	_primary_thread_copy

std::set< std::string >	_supplied_uo

const ParallelParamObject &	_parent

const MooseBase &	_si_moose_base

const FEProblemBase *	_si_problem

ExecFlagEnum	_empty_execute_enum

const MooseObject &	_fni_object

const InputParameters &	_fni_params

FEProblemBase &	_fni_feproblem

const THREAD_ID	_fni_tid

const MooseObject &	_uoi_moose_object

const FEProblemBase &	_uoi_feproblem

const THREAD_ID	_uoi_tid

const MooseObject &	_ppi_moose_object

const InputParameters &	_ppi_params

const FEProblemBase &	_ppi_feproblem

std::map< PostprocessorName, std::unique_ptr< PostprocessorValue > >	_default_values

const bool	_broadcast_by_default

const MooseObject &	_vpi_moose_object

const FEProblemBase &	_vpi_feproblem

const THREAD_ID	_vpi_tid

const InputParameters &	_ri_params

FEProblemBase &	_ri_fe_problem_base

const ReporterData &	_ri_reporter_data

const MooseObject &	_ri_moose_object

const InputParameters &	_dni_params

FEProblemBase &	_dni_feproblem

const MooseObject *const	_dni_moose_object_ptr

const InputParameters &	_si_params

FEProblemBase &	_si_feproblem

THREAD_ID	_si_tid

const RestartableDataMapName	_metaname

std::string	_restartable_name

MooseApp &	_meta_data_app

const MooseObject *const	_meta_data_object

const InputParameters &	_sc_parameters

const std::string &	_sc_name

const bool	_sc_is_implicit

std::unordered_map< std::string, std::vector< MooseVariableScalar * > >	_coupled_scalar_vars

std::unordered_map< std::string, std::unique_ptr< VariableValue > >	_default_value

std::unordered_map< std::string, std::unique_ptr< ADVariableValue > >	_dual_default_value

std::vector< MooseVariableScalar * >	_coupled_moose_scalar_vars

std::unordered_map< std::string, std::vector< MooseVariableFieldBase * > >	_sc_coupled_vars

std::set< TagID >	_sc_coupleable_vector_tags

std::set< TagID >	_sc_coupleable_matrix_tags

const MooseObject &	_mi_moose_object

const bool	_mi_boundary_restricted

const std::set< SubdomainID > &	_mi_block_ids

const std::set< BoundaryID > &	_mi_boundary_ids

std::vector< std::unique_ptr< OptionalMaterialPropertyProxyBase< MaterialPropertyInterface > > >	_optional_property_proxies

const std::string	_ti_name

const MooseObject &	_reporter_moose_object

const InputParameters &	_reporter_params

const std::string &	_reporter_name

FEProblemBase &	_reporter_fe_problem

ReporterData &	_reporter_data

std::vector< std::unique_ptr< UnusedWrapperBase > >	_unused_values

MooseApp &	_oi_moose_app

OutputWarehouse &	_oi_output_warehouse

std::set< OutputName >	_oi_outputs

const InputParameters &	_smi_params
	Parameters of the object with this interface.

FEProblemBase &	_smi_feproblem
	Reference to FEProblemBase instance.

const THREAD_ID	_smi_tid
	Thread ID.

Detailed Description

Definition at line 18 of file ActiveLearningGPDecision.h.

Constructor & Destructor Documentation

◆ ActiveLearningGPDecision()

ActiveLearningGPDecision::ActiveLearningGPDecision ( const InputParameters & parameters )

Definition at line 44 of file ActiveLearningGPDecision.C.

  : ActiveLearningReporterTempl<Real>(parameters),
    SurrogateModelInterface(this),
    _learning_function(getParam<MooseEnum>("learning_function")),
    _learning_function_threshold(getParam<Real>("learning_function_threshold")),
    _learning_function_parameter(getParam<Real>("learning_function_parameter")),
    _al_gp(getUserObject<ActiveLearningGaussianProcess>("al_gp")),
    _gp_eval(getSurrogateModel<GaussianProcessSurrogate>("gp_evaluator")),
    _flag_sample(declareValue<std::vector<bool>>(
        "flag_sample", std::vector<bool>(sampler().getNumberOfRows(), false))),
    _n_train(getParam<int>("n_train")),
    _inputs(declareValue<std::vector<std::vector<Real>>>(
        "inputs",
        std::vector<std::vector<Real>>(sampler().getNumberOfRows(),
                                       std::vector<Real>(sampler().getNumberOfCols())))),
    _gp_mean(
        declareValue<std::vector<Real>>("gp_mean", std::vector<Real>(sampler().getNumberOfRows()))),
    _gp_std(
        declareValue<std::vector<Real>>("gp_std", std::vector<Real>(sampler().getNumberOfRows()))),
    _decision(true),
    _inputs_global(getGlobalInputData()),
    _outputs_global(getGlobalOutputData())
{
  if (_learning_function == "Ufunction" &&
      !parameters.isParamSetByUser("learning_function_parameter"))
    paramError("learning_function",
               "The Ufunction requires the model failure threshold ('learning_function_parameter') "
               "to be specified.");
}

Member Function Documentation

◆ declareStochasticReporter()

template<typename T >

std::vector< T > & StochasticReporter::declareStochasticReporter	(	std::string	value_name,
		const Sampler &	sampler
	)

protectedinherited

Definition at line 164 of file StochasticReporter.h.

{
  const ReporterMode mode =
      this->_parallel_type == 0 ? REPORTER_MODE_DISTRIBUTED : REPORTER_MODE_ROOT;
  std::vector<T> & vector =
      this->template declareValueByName<std::vector<T>, StochasticReporterContext<T>>(
          value_name, mode, sampler);
 
  _vectors.push_back(std::make_unique<StochasticReporterValue<T>>(vector, sampler));
  return vector;
}

Referenced by StochasticReporter::declareStochasticReporterClone(), and SamplerReporterTransfer::intitializeStochasticReporters().

◆ declareStochasticReporterClone()

ReporterName ActiveLearningReporterTempl< Real >::declareStochasticReporterClone	(	const Sampler &	sampler,
		const ReporterData &	from_data,
		const ReporterName &	from_reporter,
		std::string	prefix = `""`
	)

overrideprotectedvirtualinherited

This is overriden for the following reasons: 1) Only one vector can be declared and must match the type of this class.

2) Check that the inputted sampler matches the one given in the parameters. 3) We actually get a pointer to the declared value so we can replace it (if necessary) in the needSample routine. 4) Declare the "need_sample" value which can be used to evaluate the sample or not.

Reimplemented from StochasticReporter.

Definition at line 47 of file ActiveLearningReporterBase.h.

{
  // Only one value is allowed to be declared
  if (_data)
    this->mooseError(type(), " can only declare a single reporter value.");
  // Make sure the inputted sampler is the same one in the parameters
  else if (sampler.name() != _sampler.name())
    this->paramError("sampler",
                     "Inputted sampler, ",
                     _sampler.name(),
                     ", is not the same as the one producing data, ",
                     sampler.name(),
                     ".");
  // Make sure reporter value exists
  else if (!from_data.hasReporterValue(from_reporter))
    this->mooseError("Reporter value ", from_reporter, " has not been declared.");
  // Make sure the reporter value is the right type
  else if (!from_data.hasReporterValue<T>(from_reporter))
    this->mooseError(
        type(), " can only use reporter values of type ", MooseUtils::prettyCppType<T>(), ".");
 
  std::string value_name = (prefix.empty() ? "" : prefix + ":") + from_reporter.getObjectName() +
                           ":" + from_reporter.getValueName();
  _data = &this->declareStochasticReporter<T>(value_name, sampler);
  return {name(), value_name};
}

◆ execute()

void ActiveLearningReporterTempl< Real >::execute ( )

overridevirtualinherited

Here we loop through the samples and call the needSample function to determine if the sample needs to be run and define a value in its place.

Reimplemented from StochasticReporter.

Definition at line 35 of file ActiveLearningReporterBase.h.

{
  // If requesting global data, fill it in
  if (_input_data_requested)
  {
    // Gather inputs for the current step
    _input_data.assign(_sampler.getNumberOfRows(),
                       std::vector<Real>(_sampler.getNumberOfCols(), 0.0));
    for (dof_id_type i = _sampler.getLocalRowBegin(); i < _sampler.getLocalRowEnd(); ++i)
      _input_data[i] = _sampler.getNextLocalRow();
    for (auto & inp : _input_data)
      gatherSum(inp);
  }
  if (_output_data_requested)
  {
    if (!_data)
      mooseError("Output data has been requested, but none was declared in this object.");
    _output_data = *_data;
    _communicator.allgather(_output_data);
  }
 
  // Optional call for before sampler loop
  preNeedSample();
 
  // Dummy value in case _data has not been declared yet
  T dummy;
  // Loop over samples to determine if sample is needed. Replace value in _data
  // (typically only if a sample is not needed). We insert a dummy value in case
  // _data has not been declared.
  for (const auto & i : make_range(_sampler.getNumberOfLocalRows()))
    _need_sample[i] = needSample(_sampler.getNextLocalRow(),
                                 i,
                                 i + _sampler.getLocalRowBegin(),
                                 (_data ? (*_data)[i] : dummy));
}

◆ facilitateDecision()

bool ActiveLearningGPDecision::facilitateDecision ( )

protectedvirtual

Make decisions whether to call the full model or not based on GP prediction and uncertainty.

Returns: bool Whether a full order model evaluation is required

Reimplemented in BiFidelityActiveLearningGPDecision.

Definition at line 96 of file ActiveLearningGPDecision.C.

{
  for (dof_id_type i = 0; i < _inputs.size(); ++i)
  {
    _gp_mean[i] = _gp_eval.evaluate(_inputs[i], _gp_std[i]);
    _flag_sample[i] = !learningFunction(_gp_mean[i], _gp_std[i]);
  }
 
  for (const auto & fs : _flag_sample)
    if (!fs)
      return false;
  return true;
}

Referenced by preNeedSample().

◆ finalize()

virtual void StochasticReporter::finalize ( )

inlineoverridevirtualinherited

Implements GeneralReporter.

Reimplemented in EvaluateSurrogate, and MappingReporter.

Definition at line 145 of file StochasticReporter.h.

145{}

◆ getGlobalInputData()

const std::vector< std::vector< Real > > & ActiveLearningReporterTempl< Real >::getGlobalInputData ( ) const

inlineprotectedinherited

Definition at line 59 of file ActiveLearningReporterBase.h.

  {
    _input_data_requested = true;
    return _input_data;
  }

◆ getGlobalOutputData()

const std::vector< Real > & ActiveLearningReporterTempl< Real >::getGlobalOutputData ( ) const

inlineprotectedinherited

Get a const reference to the output data.

Definition at line 68 of file ActiveLearningReporterBase.h.

  {
    _output_data_requested = true;
    return _output_data;
  }

◆ getSurrogateModel() [1/2]

template<typename T >

T & SurrogateModelInterface::getSurrogateModel ( const std::string & name ) const

inherited

Get a SurrogateModel/Trainer with a given name.

Parameters

name	The name of the parameter key of the sampler to retrieve

Returns: The sampler with name associated with the parameter 'name'

Definition at line 81 of file SurrogateModelInterface.h.

{
  return getSurrogateModelByName<T>(_smi_params.get<UserObjectName>(name));
}

Referenced by SurrogateTrainer::initialize().

◆ getSurrogateModel() [2/2]

template<>

SurrogateModel & SurrogateModelInterface::getSurrogateModel ( const std::string & name ) const

inherited

Definition at line 46 of file SurrogateModelInterface.C.

{
  return getSurrogateModelByName<SurrogateModel>(_smi_params.get<UserObjectName>(name));
}

◆ getSurrogateModelByName() [1/2]

template<typename T >

T & SurrogateModelInterface::getSurrogateModelByName ( const UserObjectName & name ) const

inherited

Get a sampler with a given name.

Parameters

name	The name of the sampler to retrieve

Returns: The sampler with name 'name'

Definition at line 88 of file SurrogateModelInterface.h.

{
  std::vector<T *> models;
  _smi_feproblem.theWarehouse()
      .query()
      .condition<AttribName>(name)
      .condition<AttribSystem>("SurrogateModel")
      .queryInto(models);
  if (models.empty())
    mooseError("Unable to find a SurrogateModel object of type " + std::string(typeid(T).name()) +
               " with the name '" + name + "'");
  return *(models[0]);
}

Referenced by CrossValidationScores::CrossValidationScores(), EvaluateSurrogate::EvaluateSurrogate(), and InverseMapping::initialSetup().

◆ getSurrogateModelByName() [2/2]

template<>

SurrogateModel & SurrogateModelInterface::getSurrogateModelByName ( const UserObjectName & name ) const

inherited

Definition at line 31 of file SurrogateModelInterface.C.

{
  std::vector<SurrogateModel *> models;
  _smi_feproblem.theWarehouse()
      .query()
      .condition<AttribName>(name)
      .condition<AttribSystem>("SurrogateModel")
      .queryInto(models);
  if (models.empty())
    mooseError("Unable to find a SurrogateModel object with the name '" + name + "'");
  return *(models[0]);
}

◆ getSurrogateTrainer() [1/2]

template<typename T >

T & SurrogateModelInterface::getSurrogateTrainer ( const std::string & name ) const

inherited

Definition at line 104 of file SurrogateModelInterface.h.

{
  return getSurrogateTrainerByName<T>(_smi_params.get<UserObjectName>(name));
}

◆ getSurrogateTrainer() [2/2]

template<>

SurrogateTrainerBase & SurrogateModelInterface::getSurrogateTrainer ( const std::string & name ) const

inherited

Definition at line 60 of file SurrogateModelInterface.C.

{
  return getSurrogateTrainerByName<SurrogateTrainerBase>(_smi_params.get<UserObjectName>(name));
}

◆ getSurrogateTrainerByName() [1/2]

template<typename T >

T & SurrogateModelInterface::getSurrogateTrainerByName ( const UserObjectName & name ) const

inherited

Definition at line 111 of file SurrogateModelInterface.h.

{
  SurrogateTrainerBase * base_ptr =
      &_smi_feproblem.getUserObject<SurrogateTrainerBase>(name, _smi_tid);
  T * obj_ptr = dynamic_cast<T *>(base_ptr);
  if (!obj_ptr)
    mooseError("Failed to find a SurrogateTrainer object of type " + std::string(typeid(T).name()) +
                   " with the name '",
               name,
               "' for the desired type.");
  return *obj_ptr;
}

Referenced by SurrogateTrainerOutput::output().

◆ getSurrogateTrainerByName() [2/2]

template<>

SurrogateTrainerBase & SurrogateModelInterface::getSurrogateTrainerByName ( const UserObjectName & name ) const

inherited

Definition at line 53 of file SurrogateModelInterface.C.

{
  return _smi_feproblem.getUserObject<SurrogateTrainerBase>(name);
}

◆ getTrainingSamples()

const int & ActiveLearningGPDecision::getTrainingSamples ( ) const

inline

Access the number of training samples.

Definition at line 26 of file ActiveLearningGPDecision.h.

26{ return _n_train; }

◆ initialize()

void StochasticReporter::initialize ( )

finaloverridevirtualinherited

Implements GeneralReporter.

Definition at line 40 of file StochasticReporter.C.

{
  for (auto & vector : _vectors)
    vector->initialize();
}

Referenced by SamplerReporterTransfer::initializeFromMultiapp().

◆ learningFunction()

bool ActiveLearningGPDecision::learningFunction	(	const Real &	gp_mean,
		const Real &	gp_std
	)		const

protected

This method evaluates the active learning acquisition function and returns bool that indicates whether the GP model failed.

Parameters

gp_mean	Mean of the gaussian process model
gp_mean	Standard deviation of the gaussian process model

Returns: bool If the GP model failed

Definition at line 75 of file ActiveLearningGPDecision.C.

{
  if (_learning_function == "Ufunction")
    return (std::abs(gp_mean - _learning_function_parameter) / gp_std) >
           _learning_function_threshold;
  else if (_learning_function == "COV")
    return (gp_std / std::abs(gp_mean)) < _learning_function_threshold;
  else
    mooseError("Invalid learning function ", std::string(_learning_function));
  return false;
}

Referenced by facilitateDecision(), and BiFidelityActiveLearningGPDecision::facilitateDecision().

◆ needSample()

bool ActiveLearningGPDecision::needSample	(	const std::vector< Real > &	row,
		dof_id_type	local_ind,
		dof_id_type	global_ind,
		Real &	val
	)

overrideprotectedvirtual

Based on the computations in preNeedSample, the decision to get more data is passed and results from the GP fills.

Parameters

val
row	Input parameters to the model
local_ind	Current processor row index
global_ind	All processors row index
val	Output predicted by either the LF model + GP correction or the HF model

Returns: bool Whether a full order model evaluation is required

Reimplemented from ActiveLearningReporterTempl< Real >.

Reimplemented in BiFidelityActiveLearningGPDecision.

Definition at line 133 of file ActiveLearningGPDecision.C.

{
  if (!_decision)
    val = _gp_mean[global_ind];
  return _decision;
}

◆ preNeedSample()

void ActiveLearningGPDecision::preNeedSample ( )

overrideprotectedvirtual

This is where most of the computations happen:

Data is accumulated for training
GP models are trained
Decision is made whether more data is needed for GP training

Reimplemented from ActiveLearningReporterTempl< Real >.

Reimplemented in BiFidelityActiveLearningGPDecision.

Definition at line 111 of file ActiveLearningGPDecision.C.

{
  // Accumulate inputs and outputs if we previously decided we needed a sample
  if (_t_step > 1 && _decision)
  {
    // Accumulate data into _batch members
    setupData(_inputs, _outputs_global);
 
    // Retrain if we are outside the training phase
    if (_t_step > _n_train)
      _al_gp.reTrain(_inputs_batch, _outputs_batch);
  }
 
  // Gather inputs for the current step
  _inputs = _inputs_global;
 
  // Evaluate GP and decide if we need more data if outside training phase
  if (_t_step > _n_train)
    _decision = facilitateDecision();
}

◆ sampler()

const Sampler & ActiveLearningReporterTempl< Real >::sampler ( ) const

inlineprotectedinherited

Get a const reference to the sampler from the parameters.

This is preferred over having _sampler being a protected member since we don't want derived classes changing the state of the sampler during the loop in execute.

Definition at line 57 of file ActiveLearningReporterBase.h.

57{ return _sampler; }

◆ setupData()

void ActiveLearningGPDecision::setupData	(	const std::vector< std::vector< Real > > &	inputs,
		const std::vector< Real > &	outputs
	)

protectedvirtual

This sets up data for re-training the GP.

Parameters

inputs	Matrix of inputs for the current step
outputs	Vector of outputs for the current step

Definition at line 88 of file ActiveLearningGPDecision.C.

{
  _inputs_batch.insert(_inputs_batch.end(), inputs.begin(), inputs.end());
  _outputs_batch.insert(_outputs_batch.end(), outputs.begin(), outputs.end());
}

Referenced by preNeedSample(), and BiFidelityActiveLearningGPDecision::preNeedSample().

◆ validParams()

InputParameters ActiveLearningGPDecision::validParams ( )

static

Definition at line 20 of file ActiveLearningGPDecision.C.

{
  InputParameters params = ActiveLearningReporterTempl<Real>::validParams();
  params.addClassDescription(
      "Evaluates a GP surrogate model, determines its prediction quality, "
      "launches full model if GP prediction is inadequate, and retrains GP.");
  MooseEnum learning_function("Ufunction COV");
  params.addRequiredParam<MooseEnum>(
      "learning_function", learning_function, "The learning function for active learning.");
  params.addRequiredParam<Real>("learning_function_threshold", "The learning function threshold.");
  params.addParam<Real>("learning_function_parameter",
                        std::numeric_limits<Real>::max(),
                        "The learning function parameter.");
  params.addRequiredParam<UserObjectName>("al_gp", "Active learning GP trainer.");
  params.addRequiredParam<UserObjectName>("gp_evaluator", "Evaluate the trained GP.");
  params.addRequiredParam<SamplerName>("sampler", "The sampler object.");
  params.addParam<ReporterValueName>("flag_sample", "flag_sample", "Flag samples.");
  params.addRequiredParam<int>("n_train", "Number of training steps.");
  params.addParam<ReporterValueName>("inputs", "inputs", "The inputs.");
  params.addParam<ReporterValueName>("gp_mean", "gp_mean", "The GP mean prediction.");
  params.addParam<ReporterValueName>("gp_std", "gp_std", "The GP standard deviation.");
  return params;
}

Referenced by BiFidelityActiveLearningGPDecision::validParams().

Member Data Documentation

◆ _al_gp

const ActiveLearningGaussianProcess& ActiveLearningGPDecision::_al_gp

protected

The active learning GP trainer that permits re-training.

Definition at line 92 of file ActiveLearningGPDecision.h.

Referenced by preNeedSample(), and BiFidelityActiveLearningGPDecision::preNeedSample().

◆ _data

std::vector<Real >* ActiveLearningReporterTempl< Real >::_data

privateinherited

Reporter value declared with the transfer.

Definition at line 107 of file ActiveLearningReporterBase.h.

◆ _decision

bool ActiveLearningGPDecision::_decision

protected

GP pass/fail decision.

Definition at line 111 of file ActiveLearningGPDecision.h.

Referenced by needSample(), BiFidelityActiveLearningGPDecision::needSample(), preNeedSample(), and BiFidelityActiveLearningGPDecision::preNeedSample().

◆ _flag_sample

std::vector<bool>& ActiveLearningGPDecision::_flag_sample

protected

Flag samples when the GP fails.

Definition at line 97 of file ActiveLearningGPDecision.h.

Referenced by facilitateDecision(), and BiFidelityActiveLearningGPDecision::facilitateDecision().

◆ _gp_eval

const SurrogateModel& ActiveLearningGPDecision::_gp_eval

protected

The GP evaluator object that permits re-evaluations.

Definition at line 94 of file ActiveLearningGPDecision.h.

Referenced by facilitateDecision(), and BiFidelityActiveLearningGPDecision::facilitateDecision().

◆ _gp_mean

std::vector<Real>& ActiveLearningGPDecision::_gp_mean

protected

Broadcast the GP mean prediciton to JSON.

Definition at line 106 of file ActiveLearningGPDecision.h.

Referenced by facilitateDecision(), BiFidelityActiveLearningGPDecision::facilitateDecision(), needSample(), and BiFidelityActiveLearningGPDecision::needSample().

◆ _gp_std

std::vector<Real>& ActiveLearningGPDecision::_gp_std

protected

Broadcast the GP standard deviation to JSON.

Definition at line 108 of file ActiveLearningGPDecision.h.

Referenced by facilitateDecision(), and BiFidelityActiveLearningGPDecision::facilitateDecision().

◆ _input_data

std::vector<std::vector<Real> > ActiveLearningReporterTempl< Real >::_input_data

privateinherited

Global input data from sampler.

Definition at line 114 of file ActiveLearningReporterBase.h.

◆ _input_data_requested

bool ActiveLearningReporterTempl< Real >::_input_data_requested

mutableprivateinherited

Whether or not to gather global input data.

Definition at line 110 of file ActiveLearningReporterBase.h.

◆ _inputs

std::vector<std::vector<Real> >& ActiveLearningGPDecision::_inputs

protected

Storage for the input vectors to be transferred to the output file.

Definition at line 103 of file ActiveLearningGPDecision.h.

Referenced by facilitateDecision(), BiFidelityActiveLearningGPDecision::facilitateDecision(), preNeedSample(), and BiFidelityActiveLearningGPDecision::preNeedSample().

◆ _inputs_batch

std::vector<std::vector<Real> > ActiveLearningGPDecision::_inputs_batch

protected

Store all the input vectors used for training.

Definition at line 87 of file ActiveLearningGPDecision.h.

Referenced by preNeedSample(), BiFidelityActiveLearningGPDecision::preNeedSample(), and setupData().

◆ _inputs_global

const std::vector<std::vector<Real> >& ActiveLearningGPDecision::_inputs_global

protected

Reference to global input data requested from base class.

Definition at line 114 of file ActiveLearningGPDecision.h.

Referenced by preNeedSample(), and BiFidelityActiveLearningGPDecision::preNeedSample().

◆ _learning_function

const MooseEnum& ActiveLearningGPDecision::_learning_function

protected

The learning function for active learning.

Definition at line 80 of file ActiveLearningGPDecision.h.

Referenced by ActiveLearningGPDecision(), and learningFunction().

◆ _learning_function_parameter

const Real& ActiveLearningGPDecision::_learning_function_parameter

protected

The learning function parameter.

Definition at line 84 of file ActiveLearningGPDecision.h.

Referenced by learningFunction().

◆ _learning_function_threshold

const Real& ActiveLearningGPDecision::_learning_function_threshold

protected

The learning function threshold.

Definition at line 82 of file ActiveLearningGPDecision.h.

Referenced by learningFunction().

◆ _n_train

const int ActiveLearningGPDecision::_n_train

protected

Number of initial training points for GP.

Definition at line 100 of file ActiveLearningGPDecision.h.

Referenced by getTrainingSamples(), preNeedSample(), and BiFidelityActiveLearningGPDecision::preNeedSample().

◆ _need_sample

std::vector<bool>& ActiveLearningReporterTempl< Real >::_need_sample

privateinherited

Reporter value determining whether we need to evaluate the sample through a multiapp or other means.

Definition at line 105 of file ActiveLearningReporterBase.h.

◆ _output_data

std::vector<Real > ActiveLearningReporterTempl< Real >::_output_data

privateinherited

Global output data from sampler.

Definition at line 116 of file ActiveLearningReporterBase.h.

◆ _output_data_requested

bool ActiveLearningReporterTempl< Real >::_output_data_requested

mutableprivateinherited

Whether or not to gather global output data.

Definition at line 112 of file ActiveLearningReporterBase.h.

◆ _outputs_batch

std::vector<Real> ActiveLearningGPDecision::_outputs_batch

protected

Store all the outputs used for training.

Definition at line 89 of file ActiveLearningGPDecision.h.

Referenced by preNeedSample(), BiFidelityActiveLearningGPDecision::preNeedSample(), and setupData().

◆ _outputs_global

const std::vector<Real>& ActiveLearningGPDecision::_outputs_global

protected

Reference to global output data requested from base class.

Definition at line 116 of file ActiveLearningGPDecision.h.

Referenced by preNeedSample(), and BiFidelityActiveLearningGPDecision::preNeedSample().

◆ _parallel_type

const unsigned int StochasticReporter::_parallel_type

privateinherited

Definition at line 157 of file StochasticReporter.h.

Referenced by StochasticReporter::declareStochasticReporter().

◆ _sampler

Sampler& ActiveLearningReporterTempl< Real >::_sampler

protectedinherited

Sampler given in the parameters, must match the one used to declare the transferred values.

Definition at line 100 of file ActiveLearningReporterBase.h.

◆ _smi_feproblem

FEProblemBase& SurrogateModelInterface::_smi_feproblem

privateinherited

Reference to FEProblemBase instance.

Definition at line 73 of file SurrogateModelInterface.h.

Referenced by SurrogateModelInterface::getSurrogateModelByName(), and SurrogateModelInterface::getSurrogateTrainerByName().

◆ _smi_params

const InputParameters& SurrogateModelInterface::_smi_params

privateinherited

Parameters of the object with this interface.

Definition at line 70 of file SurrogateModelInterface.h.

Referenced by SurrogateModelInterface::getSurrogateModel(), and SurrogateModelInterface::getSurrogateTrainer().

◆ _smi_tid

const THREAD_ID SurrogateModelInterface::_smi_tid

privateinherited

Thread ID.

Definition at line 76 of file SurrogateModelInterface.h.

Referenced by SurrogateModelInterface::getSurrogateTrainerByName().

◆ _vectors

std::deque<std::unique_ptr<StochasticReporterValueBase> > StochasticReporter::_vectors

privateinherited

Container for declared values that we may need to resize at initialize.

Definition at line 159 of file StochasticReporter.h.

Referenced by StochasticReporter::declareStochasticReporter(), and StochasticReporter::initialize().

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

stochastic_tools/include/reporters/ActiveLearningGPDecision.h
stochastic_tools/src/reporters/ActiveLearningGPDecision.C

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Protected Member Functions

Static Protected Member Functions

Protected Attributes

Static Protected Attributes

Private Member Functions

Static Private Member Functions

Private Attributes

Detailed Description

Constructor & Destructor Documentation

◆ ActiveLearningGPDecision()

Member Function Documentation

◆ declareStochasticReporter()

◆ declareStochasticReporterClone()

◆ execute()

◆ facilitateDecision()

◆ finalize()

◆ getGlobalInputData()

◆ getGlobalOutputData()

◆ getSurrogateModel() [1/2]

◆ getSurrogateModel() [2/2]

◆ getSurrogateModelByName() [1/2]

◆ getSurrogateModelByName() [2/2]

◆ getSurrogateTrainer() [1/2]

◆ getSurrogateTrainer() [2/2]

◆ getSurrogateTrainerByName() [1/2]

◆ getSurrogateTrainerByName() [2/2]

◆ getTrainingSamples()

◆ initialize()

◆ learningFunction()

◆ needSample()

◆ preNeedSample()

◆ sampler()

◆ setupData()

◆ validParams()

Member Data Documentation

◆ _al_gp

◆ _data

◆ _decision

◆ _flag_sample

◆ _gp_eval

◆ _gp_mean

◆ _gp_std

◆ _input_data

◆ _input_data_requested

◆ _inputs

◆ _inputs_batch

◆ _inputs_global

◆ _learning_function

◆ _learning_function_parameter

◆ _learning_function_threshold

◆ _n_train

◆ _need_sample

◆ _output_data

◆ _output_data_requested

◆ _outputs_batch

◆ _outputs_global

◆ _parallel_type

◆ _sampler

◆ _smi_feproblem

◆ _smi_params

◆ _smi_tid

◆ _vectors