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PolynomialRegressionTrainer Class Reference

#include <PolynomialRegressionTrainer.h>

Inheritance diagram for PolynomialRegressionTrainer:
[legend]

Public Types

typedef DataFileName DataFileParameterType
 

Public Member Functions

 PolynomialRegressionTrainer (const InputParameters &parameters)
 
virtual void preTrain () override
 
virtual void train () override
 
virtual void postTrain () override
 
virtual void initialize () final
 
virtual void execute () final
 
virtual void finalize () final
 
virtual void threadJoin (const UserObject &) 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 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
 
const std::string & modelMetaDataName () const
 Accessor for the name of the model meta data. More...
 
const FileName & getModelDataFileName () const
 Get the associated filename. More...
 
bool hasModelData () const
 Check if we need to load model data (if the filename parameter is used) More...
 
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 , typename... Args>
T & declareModelData (const std::string &data_name, Args &&... args)
 Declare model data for loading from file as well as restart. More...
 
template<typename T , typename... Args>
const T & getModelData (const std::string &data_name, Args &&... args) const
 Retrieve model data from the interface. More...
 
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

template<typename T >
const T & getTrainingData (const ReporterName &rname)
 
const std::vector< Real > & getSamplerData () const
 
const std::vector< Real > & getPredictorData () const
 
unsigned int getCurrentSampleSize () const
 
unsigned int getLocalSampleSize () const
 
virtual std::vector< Real > evaluateModelError (const SurrogateModel &surr)
 
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 ()
 
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)
 

Static Protected Member Functions

static std::string meshPropertyName (const std::string &data_name, const std::string &prefix)
 

Protected Attributes

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
 
Sampler & _sampler
 
dof_id_type _row
 During training loop, this is the row index of the data. More...
 
dof_id_type _local_row
 During training loop, this is the local row index of the data. More...
 
const Real * _rval
 Response value. More...
 
const std::vector< Real > * _rvecval
 Vector response value. More...
 
std::vector< const Real * > _pvals
 Predictor values from reporters. More...
 
std::vector< unsigned int > _pcols
 Columns from sampler for predictors. More...
 
unsigned int _n_dims
 Dimension of predictor data - either _sampler.getNumberOfCols() or _pvals.size() + _pcols.size(). More...
 
unsigned int & _n_outputs
 The number of outputs. More...
 

Static Protected Attributes

static const std::string _interpolated_old
 
static const std::string _interpolated_older
 

Private Attributes

const std::vector< Real > & _predictor_row
 Data from the current predictor row. More...
 
const MooseEnum & _regression_type
 Types for the polynomial regression. More...
 
const Real & _penalty
 The penalty parameter for Ridge regularization. More...
 
std::vector< std::vector< Real > > & _coeff
 Coefficients of regression model. More...
 
const unsigned int & _max_degree
 Maximum polynomial degree, limiting the sum of constituent polynomial degrees. More...
 
const std::vector< std::vector< unsigned int > > & _power_matrix
 Matirx co containing the touples of the powers for each term. More...
 
const unsigned int _n_poly_terms
 Number of terms in the polynomial expression. More...
 
std::vector< std::unique_ptr< RealCalculator > > _calculators
 Calculators used in standardizing polynomial features. More...
 
std::vector< Real > _r_sum
 Calculator used to sum response values. More...
 
DenseMatrix< Real > _matrix
 
std::vector< DenseVector< Real > > _rhs
 

Detailed Description

Definition at line 19 of file PolynomialRegressionTrainer.h.

Constructor & Destructor Documentation

◆ PolynomialRegressionTrainer()

PolynomialRegressionTrainer::PolynomialRegressionTrainer ( const InputParameters &  parameters)

Definition at line 32 of file PolynomialRegressionTrainer.C.

33  : SurrogateTrainer(parameters), // SurrogateTrainer(parameters),
34  _predictor_row(getPredictorData()),
35  _regression_type(getParam<MooseEnum>("regression_type")),
36  _penalty(getParam<Real>("penalty")),
37  _coeff(declareModelData<std::vector<std::vector<Real>>>("_coeff")),
38  _max_degree(
39  declareModelData<unsigned int>("_max_degree", getParam<unsigned int>("max_degree"))),
40  _power_matrix(declareModelData<std::vector<std::vector<unsigned int>>>(
41  "_power_matrix",
42  StochasticTools::MultiDimPolynomialGenerator::generateTuple(_n_dims, _max_degree + 1))),
43  _n_poly_terms(_power_matrix.size()),
44  _matrix(_n_poly_terms, _n_poly_terms),
45  _rhs(1, DenseVector<Real>(_n_poly_terms, 0.0)),
46  _r_sum(1, 0.0)
47 {
48  _coeff.resize(_n_poly_terms);
49 
50  // Throwing a warning if the penalty parameter is set with OLS regression
51  if (_regression_type == "ols" && _penalty != 0)
52  mooseWarning("Penalty parameter is not used for OLS regression, found penalty=", _penalty);
53 
54  // Check if we have enough data points to solve the problem
55  if (_sampler.getNumberOfRows() < _n_poly_terms)
56  mooseError("Number of data points must be greater than the number of terms in the polynomial.");
57 
58  // Creating calculators needed for feature standardization.
59  _calculators.resize(_n_poly_terms * 3);
60  for (const auto & term : make_range(_n_poly_terms))
61  {
62  _calculators[3 * term] = StochasticTools::makeCalculator(MooseEnumItem("mean"), *this);
63  _calculators[3 * term + 1] = StochasticTools::makeCalculator(MooseEnumItem("stddev"), *this);
64  _calculators[3 * term + 2] = StochasticTools::makeCalculator(MooseEnumItem("sum"), *this);
65  }
66 }
PolynomialRegressionTrainer::_n_poly_terms
const unsigned int _n_poly_terms
Number of terms in the polynomial expression.
Definition: PolynomialRegressionTrainer.h:52
SurrogateTrainer::_n_dims
unsigned int _n_dims
Dimension of predictor data - either _sampler.getNumberOfCols() or _pvals.size() + _pcols...
Definition: SurrogateTrainer.h:133
PolynomialRegressionTrainer::_predictor_row
const std::vector< Real > & _predictor_row
Data from the current predictor row.
Definition: PolynomialRegressionTrainer.h:34
PolynomialRegressionTrainer::_calculators
std::vector< std::unique_ptr< RealCalculator > > _calculators
Calculators used in standardizing polynomial features.
Definition: PolynomialRegressionTrainer.h:61
PolynomialRegressionTrainer::_coeff
std::vector< std::vector< Real > > & _coeff
Coefficients of regression model.
Definition: PolynomialRegressionTrainer.h:43
PolynomialRegressionTrainer::_penalty
const Real & _penalty
The penalty parameter for Ridge regularization.
Definition: PolynomialRegressionTrainer.h:40
PolynomialRegressionTrainer::_r_sum
std::vector< Real > _r_sum
Calculator used to sum response values.
Definition: PolynomialRegressionTrainer.h:64
GeneralUserObject::mooseWarning
void mooseWarning(Args &&... args) const
StochasticTools::MultiDimPolynomialGenerator::generateTuple
static std::vector< std::vector< unsigned int > > generateTuple(unsigned int n_dims, unsigned int max_degree, bool include_bias=true)
Function computing for computing _tuple Example for ndim = 3, order = 4: | 0 | 1 0 0 | 2 1 1 0 0 0 | ...
Definition: MultiDimPolynomialGenerator.C:16
StochasticTools::makeCalculator
std::unique_ptr< Calculator< InType, OutType > > makeCalculator(const MooseEnumItem &item, const libMesh::ParallelObject &other)
Definition: Calculators.h:335
PolynomialRegressionTrainer::_power_matrix
const std::vector< std::vector< unsigned int > > & _power_matrix
Matirx co containing the touples of the powers for each term.
Definition: PolynomialRegressionTrainer.h:49
PolynomialRegressionTrainer::_max_degree
const unsigned int & _max_degree
Maximum polynomial degree, limiting the sum of constituent polynomial degrees.
Definition: PolynomialRegressionTrainer.h:46
RestartableModelInterface::declareModelData
T & declareModelData(const std::string &data_name, Args &&... args)
Declare model data for loading from file as well as restart.
Definition: RestartableModelInterface.h:78
Sampler::getNumberOfRows
dof_id_type getNumberOfRows() const
PolynomialRegressionTrainer::_rhs
std::vector< DenseVector< Real > > _rhs
Definition: PolynomialRegressionTrainer.h:57
SurrogateTrainer::getPredictorData
const std::vector< Real > & getPredictorData() const
Definition: SurrogateTrainer.h:97
PolynomialRegressionTrainer::_regression_type
const MooseEnum & _regression_type
Types for the polynomial regression.
Definition: PolynomialRegressionTrainer.h:37
make_range
IntRange< T > make_range(T beg, T end)
GeneralUserObject::mooseError
void mooseError(Args &&... args) const
GeneralUserObject::parameters
const InputParameters & parameters() const
SurrogateTrainer::SurrogateTrainer
SurrogateTrainer(const InputParameters &parameters)
Definition: SurrogateTrainer.C:85

Member Function Documentation

◆ declareModelData()

template<typename T , typename... Args>
T & RestartableModelInterface::declareModelData ( const std::string &  data_name,
Args &&...  args 
)
inherited

Declare model data for loading from file as well as restart.

Definition at line 78 of file RestartableModelInterface.h.

79 {
80  return _model_restartable.declareRestartableData<T>(data_name, std::forward<Args>(args)...);
81 }
PublicRestartable::declareRestartableData
T & declareRestartableData(const std::string &data_name, Args &&... args)
Declare a piece of data as "restartable" and initialize it.
Definition: PublicRestartable.h:58
RestartableModelInterface::_model_restartable
PublicRestartable _model_restartable
Member for interfacing with the framework&#39;s restartable system.
Definition: RestartableModelInterface.h:68

◆ evaluateModelError()

std::vector< Real > SurrogateTrainer::evaluateModelError ( const SurrogateModel &  surr)
protectedvirtualinherited

Definition at line 347 of file SurrogateTrainer.C.

Referenced by SurrogateTrainer::crossValidate().

348 {
349  std::vector<Real> error(1, 0.0);
350 
351  if (_rval)
352  {
353  Real model_eval = surr.evaluate(_predictor_data);
354  error[0] = MathUtils::pow(model_eval - (*_rval), 2);
355  }
356  else if (_rvecval)
357  {
358  error.resize(_rvecval->size());
359 
360  // Evaluate for vector response.
361  std::vector<Real> model_eval(error.size());
362  surr.evaluate(_predictor_data, model_eval);
363  for (auto r : make_range(_rvecval->size()))
364  error[r] = MathUtils::pow(model_eval[r] - (*_rvecval)[r], 2);
365  }
366 
367  return error;
368 }
SurrogateTrainer::_rval
const Real * _rval
Response value.
Definition: SurrogateTrainer.h:125
SurrogateTrainer::_rvecval
const std::vector< Real > * _rvecval
Vector response value.
Definition: SurrogateTrainer.h:127
SurrogateTrainer::_predictor_data
std::vector< Real > _predictor_data
Predictor data for current row - can be combination of Sampler and Reporter values.
Definition: SurrogateTrainer.h:164
SurrogateModel::evaluate
virtual Real evaluate(const std::vector< Real > &x) const
Evaluate surrogate model given a row of parameters.
Definition: SurrogateModel.h:33
Real
DIE A HORRIBLE DEATH HERE typedef LIBMESH_DEFAULT_SCALAR_TYPE Real
make_range
IntRange< T > make_range(T beg, T end)
MathUtils::pow
T pow(T x, int e)

◆ execute()

void SurrogateTrainer::execute ( )
finalvirtualinherited

Implements GeneralUserObject.

Definition at line 176 of file SurrogateTrainer.C.

177 {
178  if (_doing_cv)
179  for (const auto & trial : make_range(_cv_n_trials))
180  {
181  std::vector<Real> trial_score = crossValidate();
182 
183  // Expand _cv_trial_scores with more columns if necessary, then insert values.
184  for (unsigned int r = _cv_trial_scores.size(); r < trial_score.size(); ++r)
185  _cv_trial_scores.push_back(std::vector<Real>(_cv_n_trials, 0.0));
186  for (auto r : make_range(trial_score.size()))
187  _cv_trial_scores[r][trial] = trial_score[r];
188  }
189 
190  _current_sample_size = _sampler.getNumberOfRows();
191  _local_sample_size = _sampler.getNumberOfLocalRows();
192  executeTraining();
193 }
SurrogateTrainer::_doing_cv
const bool _doing_cv
Set to true if cross validation is being performed, controls behavior in execute().
Definition: SurrogateTrainer.h:200
SurrogateTrainer::_cv_n_trials
const unsigned int & _cv_n_trials
Number of repeated trials of cross validation to perform.
Definition: SurrogateTrainer.h:192
SurrogateTrainer::_cv_trial_scores
std::vector< std::vector< Real > > & _cv_trial_scores
RMSE scores from each CV trial - can be grabbed by VPP or Reporter.
Definition: SurrogateTrainer.h:202
Sampler::getNumberOfLocalRows
dof_id_type getNumberOfLocalRows() const
SurrogateTrainer::crossValidate
std::vector< Real > crossValidate()
Definition: SurrogateTrainer.C:252
Sampler::getNumberOfRows
dof_id_type getNumberOfRows() const
make_range
IntRange< T > make_range(T beg, T end)
SurrogateTrainer::_local_sample_size
unsigned int _local_sample_size
Number of samples (locally) used to train the model.
Definition: SurrogateTrainer.h:176
SurrogateTrainer::_current_sample_size
unsigned int _current_sample_size
Number of samples used to train the model.
Definition: SurrogateTrainer.h:173

◆ finalize()

virtual void SurrogateTrainer::finalize ( )
inlinefinalvirtualinherited

Reimplemented from SurrogateTrainerBase.

Definition at line 63 of file SurrogateTrainer.h.

63 {}

◆ getCurrentSampleSize()

unsigned int SurrogateTrainer::getCurrentSampleSize ( ) const
inlineprotectedinherited

Definition at line 102 of file SurrogateTrainer.h.

Referenced by PolynomialChaosTrainer::postTrain(), and PolynomialChaosTrainer::preTrain().

102 { return _current_sample_size; };
SurrogateTrainer::_current_sample_size
unsigned int _current_sample_size
Number of samples used to train the model.
Definition: SurrogateTrainer.h:173

◆ getLocalSampleSize()

unsigned int SurrogateTrainer::getLocalSampleSize ( ) const
inlineprotectedinherited

Definition at line 107 of file SurrogateTrainer.h.

Referenced by NearestPointTrainer::preTrain(), GaussianProcessTrainer::preTrain(), and LibtorchANNTrainer::preTrain().

107 { return _local_sample_size; };
SurrogateTrainer::_local_sample_size
unsigned int _local_sample_size
Number of samples (locally) used to train the model.
Definition: SurrogateTrainer.h:176

◆ getModelData()

template<typename T , typename... Args>
const T & RestartableModelInterface::getModelData ( const std::string &  data_name,
Args &&...  args 
) const
inherited

Retrieve model data from the interface.

Definition at line 85 of file RestartableModelInterface.h.

86 {
87  return _model_restartable.getRestartableData<T>(data_name, std::forward<Args>(args)...);
88 }
PublicRestartable::getRestartableData
const T & getRestartableData(const std::string &data_name) const
Declare a piece of data as "restartable" and initialize it Similar to declareRestartableData but retu...
Definition: PublicRestartable.h:74
RestartableModelInterface::_model_restartable
PublicRestartable _model_restartable
Member for interfacing with the framework&#39;s restartable system.
Definition: RestartableModelInterface.h:68

◆ getModelDataFileName()

const FileName & RestartableModelInterface::getModelDataFileName ( ) const
inherited

Get the associated filename.

Definition at line 33 of file RestartableModelInterface.C.

34 {
35  return _model_object.getParam<FileName>("filename");
36 }
MooseObject::getParam
const T & getParam(const std::string &name) const
RestartableModelInterface::_model_object
const MooseObject & _model_object
Reference to the MooseObject that uses this interface.
Definition: RestartableModelInterface.h:57

◆ getPredictorData()

const std::vector<Real>& SurrogateTrainer::getPredictorData ( ) const
inlineprotectedinherited

Definition at line 97 of file SurrogateTrainer.h.

97 { return _predictor_data; };
SurrogateTrainer::_predictor_data
std::vector< Real > _predictor_data
Predictor data for current row - can be combination of Sampler and Reporter values.
Definition: SurrogateTrainer.h:164

◆ getSamplerData()

const std::vector<Real>& SurrogateTrainer::getSamplerData ( ) const
inlineprotectedinherited

Definition at line 92 of file SurrogateTrainer.h.

92 { return _row_data; };
SurrogateTrainer::_row_data
std::vector< Real > _row_data
Sampler data for the current row.
Definition: SurrogateTrainer.h:161

◆ getSurrogateModel() [1/2]

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

Definition at line 46 of file SurrogateModelInterface.C.

47 {
48  return getSurrogateModelByName<SurrogateModel>(_smi_params.get<UserObjectName>(name));
49 }
SurrogateModelInterface::_smi_params
const InputParameters & _smi_params
Parameters of the object with this interface.
Definition: SurrogateModelInterface.h:70
InputParameters::get
std::vector< std::pair< R1, R2 > > get(const std::string &param1, const std::string &param2) const
name
const std::string name
Definition: Setup.h:20

◆ getSurrogateModel() [2/2]

template<typename T >
T & SurrogateModelInterface::getSurrogateModel ( const std::string &  name) const
inherited

Get a SurrogateModel/Trainer with a given name.

Parameters
nameThe 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().

82 {
83  return getSurrogateModelByName<T>(_smi_params.get<UserObjectName>(name));
84 }
SurrogateModelInterface::_smi_params
const InputParameters & _smi_params
Parameters of the object with this interface.
Definition: SurrogateModelInterface.h:70
InputParameters::get
std::vector< std::pair< R1, R2 > > get(const std::string &param1, const std::string &param2) const
name
const std::string name
Definition: Setup.h:20

◆ getSurrogateModelByName() [1/2]

template<>
SurrogateModel& SurrogateModelInterface::getSurrogateModelByName ( const UserObjectName &  name) const
inherited

Definition at line 31 of file SurrogateModelInterface.C.

32 {
33  std::vector<SurrogateModel *> models;
34  _smi_feproblem.theWarehouse()
35  .query()
36  .condition<AttribName>(name)
37  .condition<AttribSystem>("SurrogateModel")
38  .queryInto(models);
39  if (models.empty())
40  mooseError("Unable to find a SurrogateModel object with the name '" + name + "'");
41  return *(models[0]);
42 }
mooseError
void mooseError(Args &&... args)
SurrogateModelInterface::_smi_feproblem
FEProblemBase & _smi_feproblem
Reference to FEProblemBase instance.
Definition: SurrogateModelInterface.h:73
FEProblemBase::theWarehouse
TheWarehouse & theWarehouse() const
name
const std::string name
Definition: Setup.h:20
TheWarehouse::query
Query query()

◆ getSurrogateModelByName() [2/2]

template<typename T >
T & SurrogateModelInterface::getSurrogateModelByName ( const UserObjectName &  name) const
inherited

Get a sampler with a given name.

Parameters
nameThe 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().

89 {
90  std::vector<T *> models;
91  _smi_feproblem.theWarehouse()
92  .query()
93  .condition<AttribName>(name)
94  .condition<AttribSystem>("SurrogateModel")
95  .queryInto(models);
96  if (models.empty())
97  mooseError("Unable to find a SurrogateModel object of type " + std::string(typeid(T).name()) +
98  " with the name '" + name + "'");
99  return *(models[0]);
100 }
mooseError
void mooseError(Args &&... args)
SurrogateModelInterface::_smi_feproblem
FEProblemBase & _smi_feproblem
Reference to FEProblemBase instance.
Definition: SurrogateModelInterface.h:73
FEProblemBase::theWarehouse
TheWarehouse & theWarehouse() const
name
const std::string name
Definition: Setup.h:20
TheWarehouse::query
Query query()

◆ getSurrogateTrainer() [1/2]

template<typename T >
T & SurrogateModelInterface::getSurrogateTrainer ( const std::string &  name) const
inherited

Definition at line 104 of file SurrogateModelInterface.h.

105 {
106  return getSurrogateTrainerByName<T>(_smi_params.get<UserObjectName>(name));
107 }
SurrogateModelInterface::_smi_params
const InputParameters & _smi_params
Parameters of the object with this interface.
Definition: SurrogateModelInterface.h:70
InputParameters::get
std::vector< std::pair< R1, R2 > > get(const std::string &param1, const std::string &param2) const
name
const std::string name
Definition: Setup.h:20

◆ getSurrogateTrainer() [2/2]

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

Definition at line 60 of file SurrogateModelInterface.C.

61 {
62  return getSurrogateTrainerByName<SurrogateTrainerBase>(_smi_params.get<UserObjectName>(name));
63 }
SurrogateModelInterface::_smi_params
const InputParameters & _smi_params
Parameters of the object with this interface.
Definition: SurrogateModelInterface.h:70
InputParameters::get
std::vector< std::pair< R1, R2 > > get(const std::string &param1, const std::string &param2) const
name
const std::string name
Definition: Setup.h:20

◆ getSurrogateTrainerByName() [1/2]

template<>
SurrogateTrainerBase& SurrogateModelInterface::getSurrogateTrainerByName ( const UserObjectName &  name) const
inherited

Definition at line 53 of file SurrogateModelInterface.C.

54 {
55  return _smi_feproblem.getUserObject<SurrogateTrainerBase>(name);
56 }
FEProblemBase::getUserObject
T & getUserObject(const std::string &name, unsigned int tid=0) const
SurrogateModelInterface::_smi_feproblem
FEProblemBase & _smi_feproblem
Reference to FEProblemBase instance.
Definition: SurrogateModelInterface.h:73
name
const std::string name
Definition: Setup.h:20
SurrogateTrainerBase
This is the base trainer class whose main functionality is the API for declaring model data...
Definition: SurrogateTrainer.h:32

◆ 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().

112 {
113  SurrogateTrainerBase * base_ptr =
114  &_smi_feproblem.getUserObject<SurrogateTrainerBase>(name, _smi_tid);
115  T * obj_ptr = dynamic_cast<T *>(base_ptr);
116  if (!obj_ptr)
117  mooseError("Failed to find a SurrogateTrainer object of type " + std::string(typeid(T).name()) +
118  " with the name '",
119  name,
120  "' for the desired type.");
121  return *obj_ptr;
122 }
FEProblemBase::getUserObject
T & getUserObject(const std::string &name, unsigned int tid=0) const
mooseError
void mooseError(Args &&... args)
SurrogateModelInterface::_smi_feproblem
FEProblemBase & _smi_feproblem
Reference to FEProblemBase instance.
Definition: SurrogateModelInterface.h:73
name
const std::string name
Definition: Setup.h:20
SurrogateModelInterface::_smi_tid
const THREAD_ID _smi_tid
Thread ID.
Definition: SurrogateModelInterface.h:76
SurrogateTrainerBase
This is the base trainer class whose main functionality is the API for declaring model data...
Definition: SurrogateTrainer.h:32

◆ getTrainingData()

template<typename T >
const T & SurrogateTrainer::getTrainingData ( const ReporterName &  rname)
protectedinherited

Definition at line 208 of file SurrogateTrainer.h.

209 {
210  auto it = _training_data.find(rname);
211  if (it != _training_data.end())
212  {
213  auto data = std::dynamic_pointer_cast<TrainingData<T>>(it->second);
214  if (!data)
215  mooseError("Reporter value ", rname, " already exists but is of different type.");
216  return data->get();
217  }
218  else
219  {
220  const std::vector<T> & rval = getReporterValueByName<std::vector<T>>(rname);
221  _training_data[rname] = std::make_shared<TrainingData<T>>(rval);
222  return std::dynamic_pointer_cast<TrainingData<T>>(_training_data[rname])->get();
223  }
224 }
SurrogateTrainer::_training_data
std::unordered_map< ReporterName, std::shared_ptr< TrainingDataBase > > _training_data
Vector of reporter names and their corresponding values (to be filled by getTrainingData) ...
Definition: SurrogateTrainer.h:179
GeneralUserObject::mooseError
void mooseError(Args &&... args) const

◆ hasModelData()

bool RestartableModelInterface::hasModelData ( ) const
inherited

Check if we need to load model data (if the filename parameter is used)

Definition at line 39 of file RestartableModelInterface.C.

40 {
41  return _model_object.isParamValid("filename");
42 }
MooseObject::isParamValid
bool isParamValid(const std::string &name) const
RestartableModelInterface::_model_object
const MooseObject & _model_object
Reference to the MooseObject that uses this interface.
Definition: RestartableModelInterface.h:57

◆ initialize()

void SurrogateTrainer::initialize ( )
finalvirtualinherited

Reimplemented from SurrogateTrainerBase.

Definition at line 153 of file SurrogateTrainer.C.

154 {
155  // Figure out if data is distributed
156  for (auto & pair : _training_data)
157  {
158  const ReporterName & name = pair.first;
159  TrainingDataBase & data = *pair.second;
160 
161  const auto & mode = _fe_problem.getReporterData().getReporterMode(name);
162  if (mode == REPORTER_MODE_DISTRIBUTED || (mode == REPORTER_MODE_ROOT && processor_id() != 0))
163  data.isDistributed() = true;
164  else if (mode == REPORTER_MODE_REPLICATED ||
165  (mode == REPORTER_MODE_ROOT && processor_id() == 0))
166  data.isDistributed() = false;
167  else
168  mooseError("Predictor reporter value ", name, " is not of supported mode.");
169  }
170 
171  if (_doing_cv)
172  _cv_surrogate = &getSurrogateModel("cv_surrogate");
173 }
SurrogateTrainer::_doing_cv
const bool _doing_cv
Set to true if cross validation is being performed, controls behavior in execute().
Definition: SurrogateTrainer.h:200
SurrogateModelInterface::getSurrogateModel
T & getSurrogateModel(const std::string &name) const
Get a SurrogateModel/Trainer with a given name.
Definition: SurrogateModelInterface.h:81
GeneralUserObject::name
virtual const std::string & name() const
FEProblemBase::getReporterData
const ReporterData & getReporterData() const
SurrogateTrainer::_training_data
std::unordered_map< ReporterName, std::shared_ptr< TrainingDataBase > > _training_data
Vector of reporter names and their corresponding values (to be filled by getTrainingData) ...
Definition: SurrogateTrainer.h:179
ReporterData::getReporterMode
const ReporterProducerEnum & getReporterMode(const ReporterName &reporter_name) const
GeneralUserObject::_fe_problem
FEProblemBase & _fe_problem
GeneralUserObject::mooseError
void mooseError(Args &&... args) const
SurrogateTrainer::_cv_surrogate
const SurrogateModel * _cv_surrogate
SurrogateModel used to evaluate model error relative to test points.
Definition: SurrogateTrainer.h:198
libMesh::ParallelObject::processor_id
processor_id_type processor_id() const

◆ modelMetaDataName()

const std::string& RestartableModelInterface::modelMetaDataName ( ) const
inlineinherited

Accessor for the name of the model meta data.

Definition at line 47 of file RestartableModelInterface.h.

Referenced by SurrogateTrainerOutput::output(), and MappingOutput::output().

47 { return _model_meta_data_name; }
RestartableModelInterface::_model_meta_data_name
const std::string _model_meta_data_name
The model meta data name.
Definition: RestartableModelInterface.h:61

◆ postTrain()

void PolynomialRegressionTrainer::postTrain ( )
overridevirtual

Reimplemented from SurrogateTrainer.

Definition at line 139 of file PolynomialRegressionTrainer.C.

140 {
141  // Make sure _rhs are all the same size
142  unsigned int nrval = _rhs.size();
143  gatherMax(nrval);
144  for (unsigned int r = _rhs.size(); r < nrval; ++r)
145  {
146  _rhs.emplace_back(_n_poly_terms, 0.0);
147  _r_sum.emplace_back(0.0);
148  }
149 
150  // Gather regression data
151  gatherSum(_matrix.get_values());
152  for (auto & it : _rhs)
153  gatherSum(it.get_values());
154 
155  // Gather response sums.
156  gatherSum(_r_sum);
157 
158  // Finalize calculators.
159  for (auto & calc : _calculators)
160  calc->finalizeCalculator(true);
161 
162  std::vector<Real> mu(_n_poly_terms);
163  std::vector<Real> sig(_n_poly_terms);
164  std::vector<Real> sum_pf(_n_poly_terms);
165 
166  for (unsigned int i = 0; i < _n_poly_terms; ++i)
167  {
168  // To handle intercept, use mu = 0, sig = 1.
169  mu[i] = i > 0 ? _calculators[3 * i]->getValue() : 0.0;
170  sig[i] = i > 0 ? _calculators[3 * i + 1]->getValue() : 1.0;
171  sum_pf[i] = _calculators[3 * i + 2]->getValue();
172  }
173 
174  // Transform _matrix and _rhs to match standardized features.
175  const Real n = sum_pf[0]; // Sum of intercept term = n.
176  for (unsigned int i = 0; i < _n_poly_terms; ++i)
177  {
178  for (unsigned int j = 0; j < _n_poly_terms; ++j)
179  {
180  _matrix(i, j) -= (mu[j] * sum_pf[i] + mu[i] * sum_pf[j]);
181  _matrix(i, j) += n * mu[i] * mu[j];
182  _matrix(i, j) /= (sig[i] * sig[j]);
183  }
184  for (unsigned int r = 0; r < _rhs.size(); ++r)
185  _rhs[r](i) = (_rhs[r](i) - mu[i] * _r_sum[r]) / sig[i];
186  }
187 
188  DenseVector<Real> sol;
189 
190  _coeff.resize(_rhs.size());
191  for (unsigned int r = 0; r < _rhs.size(); ++r)
192  {
193  _matrix.lu_solve(_rhs[r], sol);
194  _coeff[r] = sol.get_values();
195 
196  // Transform coefficients to match unstandardized features.
197  for (unsigned int i = 1; i < _n_poly_terms; ++i)
198  {
199  _coeff[r][i] /= sig[i];
200  _coeff[r][0] -= _coeff[r][i] * mu[i];
201  }
202  }
203 }
PolynomialRegressionTrainer::_n_poly_terms
const unsigned int _n_poly_terms
Number of terms in the polynomial expression.
Definition: PolynomialRegressionTrainer.h:52
GeneralUserObject::gatherMax
void gatherMax(T &value)
PolynomialRegressionTrainer::_calculators
std::vector< std::unique_ptr< RealCalculator > > _calculators
Calculators used in standardizing polynomial features.
Definition: PolynomialRegressionTrainer.h:61
PolynomialRegressionTrainer::_coeff
std::vector< std::vector< Real > > & _coeff
Coefficients of regression model.
Definition: PolynomialRegressionTrainer.h:43
PolynomialRegressionTrainer::_r_sum
std::vector< Real > _r_sum
Calculator used to sum response values.
Definition: PolynomialRegressionTrainer.h:64
GeneralUserObject::gatherSum
void gatherSum(T &value)
NS::mu
static const std::string mu
Definition: NS.h:123
DenseMatrix< Real >::get_values
std::vector< Real > & get_values()
DenseMatrix< Real >::lu_solve
void lu_solve(const DenseVector< Real > &b, DenseVector< Real > &x)
Real
DIE A HORRIBLE DEATH HERE typedef LIBMESH_DEFAULT_SCALAR_TYPE Real
PolynomialRegressionTrainer::_rhs
std::vector< DenseVector< Real > > _rhs
Definition: PolynomialRegressionTrainer.h:57
EM::j
static const std::complex< double > j(0, 1)
Complex number "j" (also known as "i")

◆ preTrain()

void PolynomialRegressionTrainer::preTrain ( )
overridevirtual

Init calculators.

Reimplemented from SurrogateTrainer.

Definition at line 69 of file PolynomialRegressionTrainer.C.

70 {
71  _matrix.zero();
72  for (unsigned int r = 0; r < _rhs.size(); ++r)
73  _rhs[r].zero();
74 
76  for (auto & calc : _calculators)
77  calc->initializeCalculator();
78 
79  _r_sum.assign(_rhs.size(), 0.0);
80 }
DenseMatrix< Real >::zero
virtual void zero() override final
PolynomialRegressionTrainer::_calculators
std::vector< std::unique_ptr< RealCalculator > > _calculators
Calculators used in standardizing polynomial features.
Definition: PolynomialRegressionTrainer.h:61
zero
const Number zero
PolynomialRegressionTrainer::_r_sum
std::vector< Real > _r_sum
Calculator used to sum response values.
Definition: PolynomialRegressionTrainer.h:64
PolynomialRegressionTrainer::_rhs
std::vector< DenseVector< Real > > _rhs
Definition: PolynomialRegressionTrainer.h:57

◆ threadJoin()

virtual void SurrogateTrainerBase::threadJoin ( const UserObject &  )
inlinefinalvirtualinherited

Reimplemented from GeneralUserObject.

Definition at line 40 of file SurrogateTrainer.h.

40 {} // GeneralUserObjects are not threaded

◆ train()

void PolynomialRegressionTrainer::train ( )
overridevirtual

Reimplemented from SurrogateTrainer.

Definition at line 83 of file PolynomialRegressionTrainer.C.

84 {
85  // Caching the different powers of data to accelerate the assembly of the
86  // system
87  DenseMatrix<Real> data_pow(_n_dims, _max_degree + 1);
88  for (unsigned int d = 0; d < _n_dims; ++d)
89  for (unsigned int i = 0; i <= _max_degree; ++i)
90  data_pow(d, i) = pow(_predictor_row[d], i);
91 
92  // Emplace new values if necessary
93  if (_rvecval)
94  for (unsigned int r = _rhs.size(); r < _rvecval->size(); ++r)
95  {
96  _rhs.emplace_back(_n_poly_terms, 0.0);
97  _r_sum.emplace_back(0.0);
98  }
99 
100  for (unsigned int i = 0; i < _n_poly_terms; ++i)
101  {
102  Real i_value(1.0);
103  for (unsigned int ii = 0; ii < _n_dims; ++ii)
104  i_value *= data_pow(ii, _power_matrix[i][ii]);
105 
106  for (unsigned int j = 0; j < _n_poly_terms; ++j)
107  {
108  Real j_value(1.0);
109  for (unsigned int jj = 0; jj < _n_dims; ++jj)
110  j_value *= data_pow(jj, _power_matrix[j][jj]);
111 
112  _matrix(i, j) += i_value * j_value;
113  }
114 
115  // Update calculators.
116  for (unsigned int c = i * 3; c < (i + 1) * 3; ++c)
117  _calculators[c]->updateCalculator(i_value);
118 
119  if (_rval)
120  _rhs[0](i) += i_value * (*_rval);
121  else if (_rvecval)
122  for (unsigned int r = 0; r < _rvecval->size(); ++r)
123  _rhs[r](i) += i_value * (*_rvecval)[r];
124  }
125 
126  if (_rval)
127  _r_sum[0] += (*_rval);
128  else if (_rvecval)
129  for (unsigned int r = 0; r < _rvecval->size(); ++r)
130  _r_sum[r] += (*_rvecval)[r];
131 
132  // Adding penalty term for Ridge regularization
133  if (_regression_type == "ridge")
134  for (unsigned int i = 0; i < _n_poly_terms; ++i)
135  _matrix(i, i) += _penalty;
136 }
PolynomialRegressionTrainer::_n_poly_terms
const unsigned int _n_poly_terms
Number of terms in the polynomial expression.
Definition: PolynomialRegressionTrainer.h:52
SurrogateTrainer::_rval
const Real * _rval
Response value.
Definition: SurrogateTrainer.h:125
SurrogateTrainer::_n_dims
unsigned int _n_dims
Dimension of predictor data - either _sampler.getNumberOfCols() or _pvals.size() + _pcols...
Definition: SurrogateTrainer.h:133
SurrogateTrainer::_rvecval
const std::vector< Real > * _rvecval
Vector response value.
Definition: SurrogateTrainer.h:127
PolynomialRegressionTrainer::_predictor_row
const std::vector< Real > & _predictor_row
Data from the current predictor row.
Definition: PolynomialRegressionTrainer.h:34
PolynomialRegressionTrainer::_calculators
std::vector< std::unique_ptr< RealCalculator > > _calculators
Calculators used in standardizing polynomial features.
Definition: PolynomialRegressionTrainer.h:61
PolynomialRegressionTrainer::_penalty
const Real & _penalty
The penalty parameter for Ridge regularization.
Definition: PolynomialRegressionTrainer.h:40
PolynomialRegressionTrainer::_r_sum
std::vector< Real > _r_sum
Calculator used to sum response values.
Definition: PolynomialRegressionTrainer.h:64
PolynomialRegressionTrainer::_power_matrix
const std::vector< std::vector< unsigned int > > & _power_matrix
Matirx co containing the touples of the powers for each term.
Definition: PolynomialRegressionTrainer.h:49
PolynomialRegressionTrainer::_max_degree
const unsigned int & _max_degree
Maximum polynomial degree, limiting the sum of constituent polynomial degrees.
Definition: PolynomialRegressionTrainer.h:46
pow
ExpressionBuilder::EBTerm pow(const ExpressionBuilder::EBTerm &left, T exponent)
Definition: ExpressionBuilder.h:677
Real
DIE A HORRIBLE DEATH HERE typedef LIBMESH_DEFAULT_SCALAR_TYPE Real
PolynomialRegressionTrainer::_rhs
std::vector< DenseVector< Real > > _rhs
Definition: PolynomialRegressionTrainer.h:57
PolynomialRegressionTrainer::_regression_type
const MooseEnum & _regression_type
Types for the polynomial regression.
Definition: PolynomialRegressionTrainer.h:37
EM::j
static const std::complex< double > j(0, 1)
Complex number "j" (also known as "i")

◆ validParams()

InputParameters PolynomialRegressionTrainer::validParams ( )
static

Definition at line 16 of file PolynomialRegressionTrainer.C.

17 {
18  InputParameters params = SurrogateTrainer::validParams();
19 
20  params.addClassDescription("Computes coefficients for polynomial regession model.");
21 
22  MooseEnum rtype("ols=0 ridge=1");
23  params.addRequiredParam<MooseEnum>(
24  "regression_type", rtype, "The type of regression to perform.");
25  params.addRequiredParam<unsigned int>("max_degree",
26  "Maximum polynomial degree to use for the regression.");
27  params.addParam<Real>("penalty", 0.0, "Penalty for Ridge regularization.");
28 
29  return params;
30 }
InputParameters::addParam
void addParam(const std::string &name, const std::initializer_list< typename T::value_type > &value, const std::string &doc_string)
InputParameters::addRequiredParam
void addRequiredParam(const std::string &name, const std::string &doc_string)
Real
DIE A HORRIBLE DEATH HERE typedef LIBMESH_DEFAULT_SCALAR_TYPE Real
InputParameters::addClassDescription
void addClassDescription(const std::string &doc_string)
SurrogateTrainer::validParams
static InputParameters validParams()
Definition: SurrogateTrainer.C:34

Member Data Documentation

◆ _calculators

std::vector<std::unique_ptr<RealCalculator> > PolynomialRegressionTrainer::_calculators
private

Calculators used in standardizing polynomial features.

Definition at line 61 of file PolynomialRegressionTrainer.h.

Referenced by PolynomialRegressionTrainer(), postTrain(), preTrain(), and train().

◆ _coeff

std::vector<std::vector<Real> >& PolynomialRegressionTrainer::_coeff
private

Coefficients of regression model.

Definition at line 43 of file PolynomialRegressionTrainer.h.

Referenced by PolynomialRegressionTrainer(), and postTrain().

◆ _local_row

dof_id_type SurrogateTrainer::_local_row
protectedinherited

During training loop, this is the local row index of the data.

Definition at line 123 of file SurrogateTrainer.h.

Referenced by SurrogateTrainer::executeTraining().

◆ _matrix

DenseMatrix<Real> PolynomialRegressionTrainer::_matrix
private

Matrix and rhs for the regression problem

Definition at line 56 of file PolynomialRegressionTrainer.h.

Referenced by postTrain(), preTrain(), and train().

◆ _max_degree

const unsigned int& PolynomialRegressionTrainer::_max_degree
private

Maximum polynomial degree, limiting the sum of constituent polynomial degrees.

Definition at line 46 of file PolynomialRegressionTrainer.h.

Referenced by train().

◆ _n_dims

unsigned int SurrogateTrainer::_n_dims
protectedinherited

Dimension of predictor data - either _sampler.getNumberOfCols() or _pvals.size() + _pcols.size().

Definition at line 133 of file SurrogateTrainer.h.

Referenced by NearestPointTrainer::NearestPointTrainer(), GaussianProcessTrainer::postTrain(), LibtorchANNTrainer::postTrain(), LibtorchANNTrainer::preTrain(), SurrogateTrainer::SurrogateTrainer(), NearestPointTrainer::train(), and train().

◆ _n_outputs

unsigned int& SurrogateTrainer::_n_outputs
protectedinherited

The number of outputs.

Definition at line 135 of file SurrogateTrainer.h.

Referenced by GaussianProcessTrainer::GaussianProcessTrainer(), GaussianProcessTrainer::postTrain(), and GaussianProcessTrainer::train().

◆ _n_poly_terms

const unsigned int PolynomialRegressionTrainer::_n_poly_terms
private

Number of terms in the polynomial expression.

Definition at line 52 of file PolynomialRegressionTrainer.h.

Referenced by PolynomialRegressionTrainer(), postTrain(), and train().

◆ _pcols

std::vector<unsigned int> SurrogateTrainer::_pcols
protectedinherited

Columns from sampler for predictors.

Definition at line 131 of file SurrogateTrainer.h.

Referenced by PolynomialChaosTrainer::PolynomialChaosTrainer(), SurrogateTrainer::SurrogateTrainer(), and SurrogateTrainer::updatePredictorRow().

◆ _penalty

const Real& PolynomialRegressionTrainer::_penalty
private

The penalty parameter for Ridge regularization.

Definition at line 40 of file PolynomialRegressionTrainer.h.

Referenced by PolynomialRegressionTrainer(), and train().

◆ _power_matrix

const std::vector<std::vector<unsigned int> >& PolynomialRegressionTrainer::_power_matrix
private

Matirx co containing the touples of the powers for each term.

Definition at line 49 of file PolynomialRegressionTrainer.h.

Referenced by train().

◆ _predictor_row

const std::vector<Real>& PolynomialRegressionTrainer::_predictor_row
private

Data from the current predictor row.

Definition at line 34 of file PolynomialRegressionTrainer.h.

Referenced by train().

◆ _pvals

std::vector<const Real *> SurrogateTrainer::_pvals
protectedinherited

Predictor values from reporters.

Definition at line 129 of file SurrogateTrainer.h.

Referenced by PolynomialChaosTrainer::PolynomialChaosTrainer(), SurrogateTrainer::SurrogateTrainer(), and SurrogateTrainer::updatePredictorRow().

◆ _r_sum

std::vector<Real> PolynomialRegressionTrainer::_r_sum
private

Calculator used to sum response values.

Definition at line 64 of file PolynomialRegressionTrainer.h.

Referenced by postTrain(), preTrain(), and train().

◆ _regression_type

const MooseEnum& PolynomialRegressionTrainer::_regression_type
private

Types for the polynomial regression.

Definition at line 37 of file PolynomialRegressionTrainer.h.

Referenced by PolynomialRegressionTrainer(), and train().

◆ _rhs

std::vector<DenseVector<Real> > PolynomialRegressionTrainer::_rhs
private

Definition at line 57 of file PolynomialRegressionTrainer.h.

Referenced by postTrain(), preTrain(), and train().

◆ _row

dof_id_type SurrogateTrainer::_row
protectedinherited

During training loop, this is the row index of the data.

Definition at line 121 of file SurrogateTrainer.h.

Referenced by SurrogateTrainer::executeTraining(), and PolynomialChaosTrainer::train().

◆ _rval

const Real* SurrogateTrainer::_rval
protectedinherited

Response value.

Definition at line 125 of file SurrogateTrainer.h.

Referenced by SurrogateTrainer::evaluateModelError(), SurrogateTrainer::SurrogateTrainer(), NearestPointTrainer::train(), train(), GaussianProcessTrainer::train(), and LibtorchANNTrainer::train().

◆ _rvecval

const std::vector<Real>* SurrogateTrainer::_rvecval
protectedinherited

Vector response value.

Definition at line 127 of file SurrogateTrainer.h.

Referenced by SurrogateTrainer::evaluateModelError(), SurrogateTrainer::SurrogateTrainer(), NearestPointTrainer::train(), train(), and GaussianProcessTrainer::train().

◆ _sampler

Sampler& SurrogateTrainer::_sampler
protectedinherited

Sampler being used for training

Definition at line 119 of file SurrogateTrainer.h.

Referenced by SurrogateTrainer::checkIntegrity(), SurrogateTrainer::crossValidate(), SurrogateTrainer::execute(), SurrogateTrainer::executeTraining(), GaussianProcessTrainer::GaussianProcessTrainer(), PolynomialChaosTrainer::PolynomialChaosTrainer(), PolynomialRegressionTrainer(), and SurrogateTrainer::SurrogateTrainer().

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