#include <PolynomialChaos.h>

Inheritance diagram for PolynomialChaos:

Public Types
typedef DataFileName	DataFileParameterType

Public Member Functions
	PolynomialChaos (const InputParameters &parameters)

virtual Real	evaluate (const std::vector< Real > &x) const override
	Evaluate surrogate model given a row of parameters.

std::size_t	getNumberOfParameters () const
	Access number of dimensions/parameters.

std::size_t	getNumberofCoefficients () const
	Number of terms in expansion.

const std::vector< Real > &	getCoefficients () const
	Access computed expansion coefficients.

virtual Real	computeMean () const
	Evaluate mean: \mu = E[u].

virtual Real	computeStandardDeviation () const
	Evaluate standard deviation: \sigma = sqrt(E[(u-\mu)^2])

Real	powerExpectation (const unsigned int n) const
	Compute expectation of a certain power of the QoI: E[(u-\mu)^n].

Real	computeDerivative (const unsigned int dim, const std::vector< Real > &x) const
	Evaluates partial derivative of expansion: du(x)/dx_dim.

Real	computePartialDerivative (const std::vector< unsigned int > &dim, const std::vector< Real > &x) const
	Evaluates sum of partial derivative of expansion.

Real	computeSobolIndex (const std::set< unsigned int > &ind) const
	Computes Sobol sensitivities S_{i_1,i_2,...,i_s}, where ind = i_1,i_2,...,i_s.

Real	computeSobolTotal (const unsigned int dim) const

void	store (nlohmann::json &json) const

virtual Real	evaluate (const std::vector< Real > &x) const
	Evaluate surrogate model given a row of parameters.

virtual void	evaluate (const std::vector< Real > &x, std::vector< Real > &y) const
	Various evaluate methods that can be overriden.

virtual Real	evaluate (const std::vector< Real > &x, Real &std) const
	Evaluate methods that also return predicted standard deviation (see GaussianProcess.h)

virtual void	evaluate (const std::vector< Real > &x, std::vector< Real > &y, std::vector< Real > &) const

virtual bool	enabled () const

std::shared_ptr< MooseObject >	getSharedPtr ()

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

bool	isKokkosObject () const

MooseApp &	getMooseApp () const

const std::string &	type () const

const std::string &	name () const

std::string	typeAndName () const

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

MooseObjectName	uniqueName () const

const InputParameters &	parameters () const

const hit::Node *	getHitNode () const

bool	hasBase () const

const std::string &	getBase () const

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

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

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

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

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

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

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

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

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

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

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

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

std::string	messagePrefix (const bool hit_prefix=true) const

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

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

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

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

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

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

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

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

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

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

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

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

void	callMooseError (std::string msg, const bool with_prefix, const hit::Node *node=nullptr, const bool show_trace=true) const

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

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

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

const Parallel::Communicator &	comm () const

processor_id_type	n_processors () const

processor_id_type	processor_id () const

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

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

T &	getSamplerByName (const SamplerName &name)

Sampler &	getSamplerByName (const SamplerName &name)

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

const std::string &	modelMetaDataName () const
	Accessor for the name of the model meta data.

const FileName &	getModelDataFileName () const
	Get the associated filename.

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


const std::vector< std::vector< unsigned int > > &	getPolynomialOrders () const
	Access polynomial orders from tuple /.

unsigned int	getPolynomialOrder (const unsigned int dim, const unsigned int i) const


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

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


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

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


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.


template<typename T , typename... Args>
const T &	getModelData (const std::string &data_name, Args &&... args) const
	Retrieve model data from the interface.

Static Public Member Functions
static InputParameters	validParams ()

static MooseEnum	defaultPredictorTypes ()

static MooseEnum	defaultResponseTypes ()

static void	callMooseError (MooseApp const app, const InputParameters &params, std::string msg, const bool with_prefix, const hit::Node node, const bool show_trace=true)

Public Attributes
	usingCombinedWarningSolutionWarnings

const ConsoleStream	_console

Static Public Attributes
static const std::string	type_param

static const std::string	name_param

static const std::string	unique_name_param

static const std::string	app_param

static const std::string	moose_base_param

static const std::string	kokkos_object_param

Protected Member Functions
void	flagInvalidSolutionInternal (const InvalidSolutionID invalid_solution_id) const

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

Protected Attributes
const bool &	_enabled

MooseApp &	_app

Factory &	_factory

ActionFactory &	_action_factory

const std::string &	_type

const std::string &	_name

const InputParameters &	_pars

const Parallel::Communicator &	_communicator

Private Member Functions
template<typename P , typename R >
void	evaluateError (P x, R y, bool with_std=false) const

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

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

Private Attributes
const unsigned int &	_order
	Maximum polynomial order. The sum of 1D polynomial orders does not go above this value.

const unsigned int &	_ndim
	Total number of parameters/dimensions.

const std::size_t &	_ncoeff
	Total number of coefficient (defined by size of _tuple)

const std::vector< std::vector< unsigned int > > &	_tuple
	A _ndim-by-_ncoeff matrix containing the appropriate one-dimensional polynomial order.

const std::vector< Real > &	_coeff
	These are the coefficients we are after in the PC expansion.

const std::vector< std::unique_ptr< const PolynomialQuadrature::Polynomial > > &	_poly
	The distributions used for sampling.

const ParallelParamObject &	_parent

const MooseBase &	_si_moose_base

const FEProblemBase *	_si_problem

const InputParameters &	_si_params

FEProblemBase &	_si_feproblem

THREAD_ID	_si_tid

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

FEProblemBase &	_smi_feproblem
	Reference to FEProblemBase instance.

const THREAD_ID	_smi_tid
	Thread ID.

const MooseObject &	_model_object
	Reference to the MooseObject that uses this interface.

const std::string	_model_meta_data_name
	The model meta data name.

PublicRestartable	_model_restartable
	Member for interfacing with the framework's restartable system.

Friends
void	to_json (nlohmann::json &json, const PolynomialChaos *const &pc)

dof_id_type	_n_local_coeff = std::numeric_limits<dof_id_type>::max()
	Variables calculation and for looping over the computed coefficients in parallel.

dof_id_type	_local_coeff_begin = 0

dof_id_type	_local_coeff_end = 0

void	linearPartitionCoefficients () const

Detailed Description

Definition at line 19 of file PolynomialChaos.h.

Constructor & Destructor Documentation

◆ PolynomialChaos()

PolynomialChaos::PolynomialChaos ( const InputParameters & parameters )

Definition at line 24 of file PolynomialChaos.C.

  : SurrogateModel(parameters),
    _order(getModelData<unsigned int>("_order")),
    _ndim(getModelData<unsigned int>("_ndim")),
    _ncoeff(getModelData<std::size_t>("_ncoeff")),
    _tuple(getModelData<std::vector<std::vector<unsigned int>>>("_tuple")),
    _coeff(getModelData<std::vector<Real>>("_coeff")),
    _poly(
        getModelData<std::vector<std::unique_ptr<const PolynomialQuadrature::Polynomial>>>("_poly"))
{
}

Member Function Documentation

◆ computeDerivative()

Real PolynomialChaos::computeDerivative	(	const unsigned int	dim,
		const std::vector< Real > &	x
	)		const

Evaluates partial derivative of expansion: du(x)/dx_dim.

Definition at line 139 of file PolynomialChaos.C.

{
  return computePartialDerivative({dim}, x);
}

Referenced by PolynomialChaosReporter::computeLocalSensitivity().

◆ computeMean()

Real PolynomialChaos::computeMean ( ) const

virtual

Evaluate mean: \mu = E[u].

Definition at line 79 of file PolynomialChaos.C.

{
  mooseAssert(_coeff.size() > 0, "The coefficient matrix is empty.");
  return _coeff[0];
}

Referenced by computeSobolIndex().

◆ computePartialDerivative()

Real PolynomialChaos::computePartialDerivative	(	const std::vector< unsigned int > &	dim,
		const std::vector< Real > &	x
	)		const

Evaluates sum of partial derivative of expansion.

Example: computeGradient({0, 2, 3}, x) = du(x)/dx_0dx_2dx_3

Definition at line 145 of file PolynomialChaos.C.

{
  mooseAssert(x.size() == _ndim, "Number of inputted parameters does not match PC model.");
 
  std::vector<unsigned int> grad(_ndim);
  for (const auto & d : dim)
  {
    mooseAssert(d < _ndim, "Specified dimension is greater than total number of parameters.");
    grad[d]++;
  }
 
  DenseMatrix<Real> poly_val(_ndim, _order);
 
  // Evaluate polynomials to avoid duplication
  for (unsigned int d = 0; d < _ndim; ++d)
    for (unsigned int i = 0; i < _order; ++i)
      poly_val(d, i) = _poly[d]->computeDerivative(i, x[d], grad[d]);
 
  Real val = 0;
  for (std::size_t i = 0; i < _ncoeff; ++i)
  {
    Real tmp = _coeff[i];
    for (unsigned int d = 0; d < _ndim; ++d)
      tmp *= poly_val(d, _tuple[i][d]);
    val += tmp;
  }
 
  return val;
}

Referenced by computeDerivative().

◆ computeSobolIndex()

Real PolynomialChaos::computeSobolIndex ( const std::set< unsigned int > & ind ) const

Computes Sobol sensitivities S_{i_1,i_2,...,i_s}, where ind = i_1,i_2,...,i_s.

Definition at line 177 of file PolynomialChaos.C.

{
  linearPartitionCoefficients();
 
  // If set is empty, compute mean
  if (ind.empty())
    return computeMean();
 
  // Do some sanity checks in debug
  mooseAssert(ind.size() <= _ndim, "Number of indices is greater than number of parameters.");
  mooseAssert(*ind.rbegin() < _ndim, "Maximum index provided exceeds number of parameters.");
 
  Real val = 0.0;
  for (dof_id_type i = _local_coeff_begin; i < _local_coeff_end; ++i)
  {
    Real tmp = _coeff[i] * _coeff[i];
    for (unsigned int d = 0; d < _ndim; ++d)
    {
      if ((ind.find(d) != ind.end() && _tuple[i][d] > 0) ||
          (ind.find(d) == ind.end() && _tuple[i][d] == 0))
      {
        tmp *= _poly[d]->innerProduct(_tuple[i][d]);
      }
      else
      {
        tmp = 0.0;
        break;
      }
    }
    val += tmp;
  }
 
  return val;
}

◆ computeSobolTotal()

Real PolynomialChaos::computeSobolTotal ( const unsigned int dim ) const

Definition at line 213 of file PolynomialChaos.C.

{
  linearPartitionCoefficients();
 
  // Do some sanity checks in debug
  mooseAssert(dim < _ndim, "Requested dimension is greater than number of parameters.");
 
  Real val = 0.0;
  for (dof_id_type i = _local_coeff_begin; i < _local_coeff_end; ++i)
    if (_tuple[i][dim] > 0)
      val += _coeff[i] * _coeff[i] * _poly[dim]->innerProduct(_tuple[i][dim]);
 
  return val;
}

◆ computeStandardDeviation()

Real PolynomialChaos::computeStandardDeviation ( ) const

virtual

Evaluate standard deviation: \sigma = sqrt(E[(u-\mu)^2])

Definition at line 86 of file PolynomialChaos.C.

{
  Real var = 0;
  for (std::size_t i = 1; i < _ncoeff; ++i)
  {
    Real norm = 1.0;
    for (std::size_t d = 0; d < _ndim; ++d)
      norm *= _poly[d]->innerProduct(_tuple[i][d]);
    var += _coeff[i] * _coeff[i] * norm;
  }
 
  return std::sqrt(var);
}

◆ 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 73 of file RestartableModelInterface.h.

{
  return _model_restartable.declareRestartableData<T>(data_name, std::forward<Args>(args)...);
}

◆ defaultPredictorTypes()

static MooseEnum SurrogateModel::defaultPredictorTypes ( )

inlinestaticinherited

Definition at line 27 of file SurrogateModel.h.

27{ return MooseEnum("real"); }

MooseEnum

◆ defaultResponseTypes()

static MooseEnum SurrogateModel::defaultResponseTypes ( )

inlinestaticinherited

Definition at line 28 of file SurrogateModel.h.

28{ return MooseEnum("real vector_real"); }

Referenced by EvaluateSurrogate::validParams().

◆ evaluate() [1/5]

virtual Real SurrogateModel::evaluate ( const std::vector< Real > & x ) const

inlinevirtual

Evaluate surrogate model given a row of parameters.

Reimplemented from SurrogateModel.

Definition at line 33 of file SurrogateModel.h.

  {
    evaluateError(x, Real());
    return 0.0;
  };

◆ evaluate() [2/5]

Real PolynomialChaos::evaluate ( const std::vector< Real > & x ) const

overridevirtual

Evaluate surrogate model given a row of parameters.

Reimplemented from SurrogateModel.

Definition at line 37 of file PolynomialChaos.C.

{
  mooseAssert(x.size() == _ndim, "Number of inputted parameters does not match PC model.");
 
  DenseMatrix<Real> poly_val(_ndim, _order);
 
  // Evaluate polynomials to avoid duplication
  for (unsigned int d = 0; d < _ndim; ++d)
    for (unsigned int i = 0; i < _order; ++i)
      poly_val(d, i) = _poly[d]->compute(i, x[d], /*normalize =*/false);
 
  Real val = 0;
  for (std::size_t i = 0; i < _ncoeff; ++i)
  {
    Real tmp = _coeff[i];
    for (unsigned int d = 0; d < _ndim; ++d)
      tmp *= poly_val(d, _tuple[i][d]);
    val += tmp;
  }
 
  return val;
}

Referenced by PolynomialChaosReporter::computeLocalSensitivity().

◆ evaluate() [3/5]

virtual Real SurrogateModel::evaluate	(	const std::vector< Real > &	x,
		Real &	std
	)		const

inlinevirtual

Evaluate methods that also return predicted standard deviation (see GaussianProcess.h)

Reimplemented from SurrogateModel.

Definition at line 53 of file SurrogateModel.h.

  {
    evaluateError(x, std, true);
    return 0.0;
  }

◆ evaluate() [4/5]

virtual void SurrogateModel::evaluate	(	const std::vector< Real > &	x,
		std::vector< Real > &	y
	)		const

inlinevirtual

Various evaluate methods that can be overriden.

Reimplemented from SurrogateModel.

Definition at line 43 of file SurrogateModel.h.

  {
    evaluateError(x, y);
  }

◆ evaluate() [5/5]

virtual void SurrogateModel::evaluate	(	const std::vector< Real > &	x,
		std::vector< Real > &	y,
		std::vector< Real > &
	)		const

inlinevirtual

Reimplemented from SurrogateModel.

Definition at line 59 of file SurrogateModel.h.

  {
    evaluateError(x, y, true);
  }

◆ evaluateError()

template<typename P , typename R >

void SurrogateModel::evaluateError	(	P	x,
		R	y,
		bool	with_std = `false`
	)		const

privateinherited

Definition at line 72 of file SurrogateModel.h.

{
  std::stringstream ss;
  ss << "Evaluate method";
  if (with_std)
    ss << " (including standard deviation computation)";
  ss << " with predictor type " << MooseUtils::prettyCppType<P>();
  ss << " and response type " << MooseUtils::prettyCppType<R>();
  ss << " has not been implemented.";
  mooseError(ss.str());
}

Referenced by SurrogateModel::evaluate(), SurrogateModel::evaluate(), SurrogateModel::evaluate(), and SurrogateModel::evaluate().

◆ getCoefficients()

const std::vector< Real > & PolynomialChaos::getCoefficients ( ) const

Access computed expansion coefficients.

Definition at line 73 of file PolynomialChaos.C.

{
  return _coeff;
}

Referenced by store().

◆ 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 80 of file RestartableModelInterface.h.

{
  return _model_restartable.getRestartableData<T>(data_name, std::forward<Args>(args)...);
}

◆ getModelDataFileName()

const FileName & RestartableModelInterface::getModelDataFileName ( ) const

inherited

Get the associated filename.

Definition at line 33 of file RestartableModelInterface.C.

{
  return _model_object.getParam<FileName>("filename");
}

◆ getNumberofCoefficients()

std::size_t PolynomialChaos::getNumberofCoefficients ( ) const

inline

Number of terms in expansion.

Definition at line 31 of file PolynomialChaos.h.

31{ return _tuple.size(); }

Referenced by store().

◆ getNumberOfParameters()

std::size_t PolynomialChaos::getNumberOfParameters ( ) const

inline

Access number of dimensions/parameters.

Definition at line 28 of file PolynomialChaos.h.

28{ return _poly.size(); }

Referenced by store().

◆ getPolynomialOrder()

unsigned PolynomialChaos::getPolynomialOrder	(	const unsigned int	dim,
		const unsigned int	i
	)		const

Definition at line 67 of file PolynomialChaos.C.

{
  return _tuple[i][dim];
}

◆ getPolynomialOrders()

const std::vector< std::vector< unsigned int > > & PolynomialChaos::getPolynomialOrders ( ) const

Access polynomial orders from tuple /.

Definition at line 61 of file PolynomialChaos.C.

{
  return _tuple;
}

Referenced by store().

◆ getSurrogateModel() [1/2]

template<typename T >

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

inherited

Get a SurrogateModel/Trainer with a given name.

Parameters

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

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

Definition at line 81 of file SurrogateModelInterface.h.

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

Referenced by SurrogateTrainer::initialize().

◆ getSurrogateModel() [2/2]

template<>

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

inherited

Definition at line 46 of file SurrogateModelInterface.C.

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

◆ getSurrogateModelByName() [1/2]

template<typename T >

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

inherited

Get a sampler with a given name.

Parameters

name	The name of the sampler to retrieve

Returns: The sampler with name 'name'

Definition at line 88 of file SurrogateModelInterface.h.

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

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

◆ getSurrogateModelByName() [2/2]

template<>

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

inherited

Definition at line 31 of file SurrogateModelInterface.C.

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

◆ getSurrogateTrainer() [1/2]

template<typename T >

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

inherited

Definition at line 104 of file SurrogateModelInterface.h.

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

◆ getSurrogateTrainer() [2/2]

template<>

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

inherited

Definition at line 60 of file SurrogateModelInterface.C.

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

◆ getSurrogateTrainerByName() [1/2]

template<typename T >

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

inherited

Definition at line 111 of file SurrogateModelInterface.h.

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

Referenced by SurrogateTrainerOutput::output().

◆ getSurrogateTrainerByName() [2/2]

template<>

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

inherited

Definition at line 53 of file SurrogateModelInterface.C.

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

◆ 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.

{
  return _model_object.isParamValid("filename");
}

◆ linearPartitionCoefficients()

void PolynomialChaos::linearPartitionCoefficients ( ) const

private

Definition at line 229 of file PolynomialChaos.C.

{
  if (_n_local_coeff == std::numeric_limits<dof_id_type>::max())
    MooseUtils::linearPartitionItems(_ncoeff,
                                     n_processors(),
                                     processor_id(),
                                     _n_local_coeff,
                                     _local_coeff_begin,
                                     _local_coeff_end);
}

Referenced by computeSobolIndex(), and computeSobolTotal().

◆ 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.

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

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

◆ powerExpectation()

Real PolynomialChaos::powerExpectation ( const unsigned int n ) const

Compute expectation of a certain power of the QoI: E[(u-\mu)^n].

Definition at line 101 of file PolynomialChaos.C.

{
  std::vector<StochasticTools::WeightedCartesianProduct<unsigned int, Real>> order;
  order.reserve(_ndim);
  std::vector<std::vector<Real>> c_1d(n, std::vector<Real>(_coeff.begin() + 1, _coeff.end()));
  for (unsigned int d = 0; d < _ndim; ++d)
  {
    std::vector<std::vector<unsigned int>> order_1d(n, std::vector<unsigned int>(_ncoeff - 1));
    for (std::size_t i = 1; i < _ncoeff; ++i)
      for (unsigned int m = 0; m < n; ++m)
        order_1d[m][i - 1] = _tuple[i][d];
    order.push_back(StochasticTools::WeightedCartesianProduct<unsigned int, Real>(order_1d, c_1d));
  }
 
  dof_id_type n_local, st_local, end_local;
  MooseUtils::linearPartitionItems(
      order[0].numRows(), n_processors(), processor_id(), n_local, st_local, end_local);
 
  Real val = 0;
  for (dof_id_type i = st_local; i < end_local; ++i)
  {
    Real tmp = order[0].computeWeight(i);
    for (unsigned int d = 0; d < _ndim; ++d)
    {
      if (MooseUtils::absoluteFuzzyEqual(tmp, 0.0))
        break;
      std::vector<unsigned int> comb(n);
      for (unsigned int m = 0; m < n; ++m)
        comb[m] = order[d].computeValue(i, m);
      tmp *= _poly[d]->productIntegral(comb);
    }
    val += tmp;
  }
 
  return val;
}

◆ store()

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

Definition at line 241 of file PolynomialChaos.C.

{
  json["order"] = _order;
  json["ndim"] = getNumberOfParameters();
  json["ncoeff"] = getNumberofCoefficients();
  json["tuple"] = getPolynomialOrders();
  json["coeff"] = getCoefficients();
  for (const auto & p : _poly)
  {
    nlohmann::json jsonp;
    p->store(jsonp);
    json["poly"].push_back(jsonp);
  }
}

◆ validParams()

InputParameters PolynomialChaos::validParams ( )

static

Definition at line 17 of file PolynomialChaos.C.

{
  InputParameters params = SurrogateModel::validParams();
  params.addClassDescription("Computes and evaluates polynomial chaos surrogate model.");
  return params;
}

Friends And Related Symbol Documentation

◆ to_json

void to_json	(	nlohmann::json &	json,
		const PolynomialChaos *const &	pc
	)

friend

Definition at line 150 of file PolynomialChaosReporter.C.

{
  pc->store(json);
}

Member Data Documentation

◆ _coeff

const std::vector<Real>& PolynomialChaos::_coeff

private

These are the coefficients we are after in the PC expansion.

Definition at line 97 of file PolynomialChaos.h.

Referenced by computeMean(), computePartialDerivative(), computeSobolIndex(), computeSobolTotal(), computeStandardDeviation(), evaluate(), getCoefficients(), and powerExpectation().

◆ _local_coeff_begin

dof_id_type PolynomialChaos::_local_coeff_begin = 0

mutableprivate

Definition at line 77 of file PolynomialChaos.h.

Referenced by computeSobolIndex(), computeSobolTotal(), and linearPartitionCoefficients().

◆ _local_coeff_end

dof_id_type PolynomialChaos::_local_coeff_end = 0

mutableprivate

Definition at line 78 of file PolynomialChaos.h.

Referenced by computeSobolIndex(), computeSobolTotal(), and linearPartitionCoefficients().

◆ _model_meta_data_name

const std::string RestartableModelInterface::_model_meta_data_name

privateinherited

The model meta data name.

This is used to store the restartable data within the RestartableDataMap.

Definition at line 61 of file RestartableModelInterface.h.

Referenced by RestartableModelInterface::modelMetaDataName(), and RestartableModelInterface::RestartableModelInterface().

◆ _model_object

const MooseObject& RestartableModelInterface::_model_object

privateinherited

Reference to the MooseObject that uses this interface.

Definition at line 57 of file RestartableModelInterface.h.

Referenced by RestartableModelInterface::getModelDataFileName(), RestartableModelInterface::hasModelData(), and RestartableModelInterface::RestartableModelInterface().

◆ _model_restartable

PublicRestartable RestartableModelInterface::_model_restartable

privateinherited

Member for interfacing with the framework's restartable system.

We need this because we would like to have the capability to handle the model data separately from the other data members used for checkpointing.

Definition at line 68 of file RestartableModelInterface.h.

Referenced by RestartableModelInterface::declareModelData(), and RestartableModelInterface::getModelData().

◆ _n_local_coeff

dof_id_type PolynomialChaos::_n_local_coeff = std::numeric_limits<dof_id_type>::max()

mutableprivate

Variables calculation and for looping over the computed coefficients in parallel.

The various utility methods in this class require the coefficients be partitioned in parallel, but the data being partitioned is loaded from the trainer so it might not be available. Thus, the partitioning is done on demand, if needed.

The methods are marked const because they do not modify the loaded data, to keep this interface the partitioning uses mutable variables.

Definition at line 76 of file PolynomialChaos.h.

Referenced by linearPartitionCoefficients().

◆ _ncoeff

const std::size_t& PolynomialChaos::_ncoeff

private

Total number of coefficient (defined by size of _tuple)

Definition at line 91 of file PolynomialChaos.h.

Referenced by computePartialDerivative(), computeStandardDeviation(), evaluate(), linearPartitionCoefficients(), and powerExpectation().

◆ _ndim

const unsigned int& PolynomialChaos::_ndim

private

Total number of parameters/dimensions.

Definition at line 88 of file PolynomialChaos.h.

Referenced by computePartialDerivative(), computeSobolIndex(), computeSobolTotal(), computeStandardDeviation(), evaluate(), and powerExpectation().

◆ _order

const unsigned int& PolynomialChaos::_order

private

Maximum polynomial order. The sum of 1D polynomial orders does not go above this value.

Definition at line 85 of file PolynomialChaos.h.

Referenced by computePartialDerivative(), evaluate(), and store().

◆ _poly

const std::vector<std::unique_ptr<const PolynomialQuadrature::Polynomial> >& PolynomialChaos::_poly

private

The distributions used for sampling.

Definition at line 100 of file PolynomialChaos.h.

Referenced by computePartialDerivative(), computeSobolIndex(), computeSobolTotal(), computeStandardDeviation(), evaluate(), getNumberOfParameters(), powerExpectation(), and store().

◆ _smi_feproblem

FEProblemBase& SurrogateModelInterface::_smi_feproblem

privateinherited

Reference to FEProblemBase instance.

Definition at line 73 of file SurrogateModelInterface.h.

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

◆ _smi_params

const InputParameters& SurrogateModelInterface::_smi_params

privateinherited

Parameters of the object with this interface.

Definition at line 70 of file SurrogateModelInterface.h.

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

◆ _smi_tid

const THREAD_ID SurrogateModelInterface::_smi_tid

privateinherited

Thread ID.

Definition at line 76 of file SurrogateModelInterface.h.

Referenced by SurrogateModelInterface::getSurrogateTrainerByName().

◆ _tuple

const std::vector<std::vector<unsigned int> >& PolynomialChaos::_tuple

private

A _ndim-by-_ncoeff matrix containing the appropriate one-dimensional polynomial order.

Definition at line 94 of file PolynomialChaos.h.

Referenced by computePartialDerivative(), computeSobolIndex(), computeSobolTotal(), computeStandardDeviation(), evaluate(), getNumberofCoefficients(), getPolynomialOrder(), getPolynomialOrders(), and powerExpectation().

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

stochastic_tools/include/surrogates/PolynomialChaos.h
stochastic_tools/src/surrogates/PolynomialChaos.C

Public Types

Public Member Functions

Static Public Member Functions

Public Attributes

Static Public Attributes

Protected Member Functions

Protected Attributes

Private Member Functions

Static Private Member Functions

Private Attributes

Friends

Detailed Description

Constructor & Destructor Documentation

◆ PolynomialChaos()

Member Function Documentation

◆ computeDerivative()

◆ computeMean()

◆ computePartialDerivative()

◆ computeSobolIndex()

◆ computeSobolTotal()

◆ computeStandardDeviation()

◆ declareModelData()

◆ defaultPredictorTypes()

◆ defaultResponseTypes()

◆ evaluate() [1/5]

◆ evaluate() [2/5]

◆ evaluate() [3/5]

◆ evaluate() [4/5]

◆ evaluate() [5/5]

◆ evaluateError()

◆ getCoefficients()

◆ getModelData()

◆ getModelDataFileName()

◆ getNumberofCoefficients()

◆ getNumberOfParameters()

◆ getPolynomialOrder()

◆ getPolynomialOrders()

◆ getSurrogateModel() [1/2]

◆ getSurrogateModel() [2/2]

◆ getSurrogateModelByName() [1/2]

◆ getSurrogateModelByName() [2/2]

◆ getSurrogateTrainer() [1/2]

◆ getSurrogateTrainer() [2/2]

◆ getSurrogateTrainerByName() [1/2]

◆ getSurrogateTrainerByName() [2/2]

◆ hasModelData()

◆ linearPartitionCoefficients()

◆ modelMetaDataName()

◆ powerExpectation()

◆ store()

◆ validParams()

Friends And Related Symbol Documentation

◆ to_json

Member Data Documentation

◆ _coeff

◆ _local_coeff_begin

◆ _local_coeff_end

◆ _model_meta_data_name

◆ _model_object

◆ _model_restartable

◆ _n_local_coeff

◆ _ncoeff

◆ _ndim

◆ _order

◆ _poly

◆ _smi_feproblem

◆ _smi_params

◆ _smi_tid

◆ _tuple