#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. More...

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. More...

virtual void	initialize () override

virtual void	finalize () override

void	threadJoin (const UserObject &) final

bool	shouldStore () const override final

SubProblem &	getSubProblem () const

bool	shouldDuplicateInitialExecution () const

virtual Real	spatialValue (const Point &) const

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

void	setPrimaryThreadCopy (UserObject *primary)

UserObject *	primaryThreadCopy ()

std::set< UserObjectName >	getDependObjects () const

virtual bool	needThreadedCopy () const

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

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

unsigned int	systemNumber () const

virtual bool	enabled () const

std::shared_ptr< MooseObject >	getSharedPtr ()

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

MooseApp &	getMooseApp () const

const std::string &	type () const

virtual const std::string &	name () const

std::string	typeAndName () const

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

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

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

const InputParameters &	parameters () const

MooseObjectName	uniqueName () const

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

virtual void	initialSetup ()

virtual void	timestepSetup ()

virtual void	jacobianSetup ()

virtual void	residualSetup ()

virtual void	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 UserObject &	getUserObjectBase (const std::string &param_name, bool is_dependency=true) const

const UserObject &	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)

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

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	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

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. More...

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. More...

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

Static Public Member Functions
static InputParameters	validParams ()

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)

Public Attributes
const ConsoleStream	_console

Static Public Attributes
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: More...

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. More...

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

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

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. More...

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. More...

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

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

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

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 UserObject &uo) const override

void	addReporterDependencyHelper (const ReporterName &reporter_name) override

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)

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. More...

const Real &	_learning_function_threshold
	The learning function threshold. More...

const Real &	_learning_function_parameter
	The learning function parameter. More...

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

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

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

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

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

const int	_n_train
	Number of initial training points for GP. More...

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

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

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

bool	_decision
	GP pass/fail decision. More...

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

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

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

SubProblem &	_subproblem

FEProblemBase &	_fe_problem

SystemBase &	_sys

const THREAD_ID	_tid

Assembly &	_assembly

const Moose::CoordinateSystemType &	_coord_sys

const bool	_duplicate_initial_execution

std::set< std::string >	_depend_uo

const bool &	_enabled

MooseApp &	_app

const std::string	_type

const std::string	_name

const InputParameters &	_pars

Factory &	_factory

ActionFactory &	_action_factory

const ExecFlagEnum &	_execute_enum

const ExecFlagType &	_current_execute_flag

MooseApp &	_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 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

Detailed Description

Definition at line 17 of file ActiveLearningGPDecision.h.

Constructor & Destructor Documentation

◆ ActiveLearningGPDecision()

ActiveLearningGPDecision::ActiveLearningGPDecision ( const InputParameters & parameters )

Definition at line 43 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 131 of file StochasticReporter.h.

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

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

◆ 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 176 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 138 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 95 of file ActiveLearningGPDecision.C.

Referenced by preNeedSample().

 {
   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;
 }

◆ finalize()

virtual void StochasticReporter::finalize ( )

inlineoverridevirtualinherited

Implements GeneralReporter.

Reimplemented in MappingReporter, and EvaluateSurrogate.

Definition at line 114 of file StochasticReporter.h.

114 {}

◆ 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<>

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));
 }

◆ getSurrogateModel() [2/2]

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.

Referenced by SurrogateTrainer::initialize().

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

◆ getSurrogateModelByName() [1/2]

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]);
 }

◆ getSurrogateModelByName() [2/2]

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.

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

 {
   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]);
 }

◆ 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<>

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

inherited

Definition at line 53 of file SurrogateModelInterface.C.

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

◆ getSurrogateTrainerByName() [2/2]

template<typename T >

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

inherited

Definition at line 111 of file SurrogateModelInterface.h.

Referenced by SurrogateTrainerOutput::output().

 {
   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;
 }

◆ getTrainingSamples()

const int& ActiveLearningGPDecision::getTrainingSamples ( ) const

inline

Access the number of training samples.

Definition at line 25 of file ActiveLearningGPDecision.h.

25 { return _n_train; }

ActiveLearningGPDecision::_n_train

const int _n_train

Number of initial training points for GP.

Definition: ActiveLearningGPDecision.h:99

◆ initialize()

virtual void StochasticReporter::initialize ( )

inlineoverridevirtualinherited

Implements GeneralReporter.

Reimplemented in MappingReporter, and EvaluateSurrogate.

Definition at line 112 of file StochasticReporter.h.

112 {}

◆ 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 74 of file ActiveLearningGPDecision.C.

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

 {
   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;
 }

◆ 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 132 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 110 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; }

ActiveLearningReporterTempl< Real >::_sampler

Sampler & _sampler

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

Definition: ActiveLearningReporterBase.h:100

◆ 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 87 of file ActiveLearningGPDecision.C.

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

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

◆ validParams()

InputParameters ActiveLearningGPDecision::validParams ( )

static

Definition at line 19 of file ActiveLearningGPDecision.C.

Referenced by BiFidelityActiveLearningGPDecision::validParams().

 {
   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;
 }