A class used to generate a LinearSum function of observing model predictions. More...

#include <LinearSum.h>

Inheritance diagram for LinearSum:

Public Types
typedef DataFileName	DataFileParameterType

Public Member Functions
	LinearSum (const InputParameters &parameters)

virtual Real	function (const std::vector< Real > &x) const override
	Return the probability density or mass function at vector x.

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

Static Public Member Functions
static InputParameters	validParams ()

static Real	function (const std::vector< Real > &exp, const std::vector< Real > &model, const Real &noise)
	Return the probability density function.

static Real	function (const std::vector< Real > &exp, const std::vector< Real > &model, const Real &noise, const bool &log_likelihood)
	Return the probability density function.

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

const ReporterContextBase &	getReporterContextBaseByName (const ReporterName &reporter_name) const

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

virtual void	addReporterDependencyHelper (const ReporterName &)

const T &	getReporterValue (const std::string &param_name, const std::size_t time_index=0)

const T &	getReporterValue (const std::string &param_name, ReporterMode mode, const std::size_t time_index=0)

const T &	getReporterValue (const std::string &param_name, const std::size_t time_index=0)

const T &	getReporterValue (const std::string &param_name, ReporterMode mode, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, ReporterMode mode, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, const std::size_t time_index=0)

const T &	getReporterValueByName (const ReporterName &reporter_name, ReporterMode mode, const std::size_t time_index=0)

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

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

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

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

bool	hasReporterValueByName (const ReporterName &reporter_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

bool	hasReporterValueByName (const ReporterName &reporter_name) const

Protected Attributes
const bool	_log_likelihood
	return log-likelihood or likelihood

const Real &	_noise
	Noise value.

std::vector< Real >	_exp_values
	Experimental data values.

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
bool	reportersAdded () const

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

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

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

Private Attributes
const ParallelParamObject &	_parent

const MooseBase &	_si_moose_base

const FEProblemBase *	_si_problem

const InputParameters &	_ri_params

FEProblemBase &	_ri_fe_problem_base

const ReporterData &	_ri_reporter_data

const MooseObject &	_ri_moose_object

Detailed Description

A class used to generate a LinearSum function of observing model predictions.

Definition at line 17 of file LinearSum.h.

Constructor & Destructor Documentation

◆ LinearSum()

LinearSum::LinearSum ( const InputParameters & parameters )

Definition at line 23 of file LinearSum.C.

23: Gaussian(parameters) {}

Gaussian

A class used to generate a Gaussian likelihood of observing model predictions.

Definition Gaussian.h:19

MooseObject::parameters

const InputParameters & parameters() const

Member Function Documentation

◆ function() [1/3]

Real LinearSum::function	(	const std::vector< Real > &	exp,
		const std::vector< Real > &	model,
		const Real &	noise
	)

static

Return the probability density function.

Parameters

exp	The experimental measurement
model	The model prediction
noise	The standard deviation

Definition at line 26 of file LinearSum.C.

{
  mooseAssert(exp.size() == model.size(), "LinearSum: Vectors must be the same size.");
  mooseAssert(noise != 0.0, "LinearSum: Noise must not be zero.");
  Real result = 0.0;
  for (unsigned int i = 0; i < exp.size(); ++i)
  {
    const Real diff = exp[i] - model[i];
    result += diff * diff;
  }
  return result / (noise * noise);
}

◆ function() [2/3]

Real Gaussian::function	(	const std::vector< Real > &	exp,
		const std::vector< Real > &	model,
		const Real &	noise,
		const bool &	log_likelihood
	)

staticinherited

Return the probability density function.

Parameters

exp	The experimental measurement
model	The model prediction
noise	The standard deviation
log_likelihood	Bool to return the log likelihood value

Definition at line 58 of file Gaussian.C.

{
  Real result = 0.0;
  Real val1;
  for (unsigned i = 0; i < exp.size(); ++i)
  {
    val1 = Normal::pdf(exp[i], model[i], noise);
    val1 = std::log(val1);
    result += val1;
  }
  if (!log_likelihood)
    result = std::exp(result);
  return result;
}

◆ function() [3/3]

Real LinearSum::function ( const std::vector< Real > & x ) const

overridevirtual

Return the probability density or mass function at vector x.

Parameters

x	The input vector x

Reimplemented from Gaussian.

Definition at line 42 of file LinearSum.C.

{
  return function(_exp_values, x, _noise);
}

Referenced by function().

◆ validParams()

InputParameters LinearSum::validParams ( )

static

Definition at line 15 of file LinearSum.C.

{
  InputParameters params = LikelihoodFunctionBase::validParams();
  params.addClassDescription(
      "LinearSum function evaluating the model goodness against experiments.");
  return params;
}

Member Data Documentation

◆ _exp_values

std::vector<Real> Gaussian::_exp_values

protectedinherited

Experimental data values.

Definition at line 47 of file Gaussian.h.

Referenced by ExtremeValue::function(), Gaussian::function(), function(), TruncatedGaussian::function(), and Gaussian::Gaussian().

◆ _log_likelihood

const bool Gaussian::_log_likelihood

protectedinherited

return log-likelihood or likelihood

Definition at line 41 of file Gaussian.h.

Referenced by ExtremeValue::function(), Gaussian::function(), and TruncatedGaussian::function().

◆ _noise

const Real& Gaussian::_noise

protectedinherited

Noise value.

Definition at line 44 of file Gaussian.h.

Referenced by ExtremeValue::function(), Gaussian::function(), function(), and TruncatedGaussian::function().

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

stochastic_tools/include/likelihoods/LinearSum.h
stochastic_tools/src/likelihoods/LinearSum.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

Detailed Description

Constructor & Destructor Documentation

◆ LinearSum()

Member Function Documentation

◆ function() [1/3]

◆ function() [2/3]

◆ function() [3/3]

◆ validParams()

Member Data Documentation

◆ _exp_values

◆ _log_likelihood

◆ _noise