DiscrepancyCorrection Class Reference

Base class for discrepancy corrections. More...

Public Member Functions
	DiscrepancyCorrection ()
	default constructor
	DiscrepancyCorrection (Model &surr_model, const SizetSet &surr_fn_indices, short corr_type, short corr_order, String approx_type="local_taylor", short approx_order=SHRT_MAX)
	standard constructor
	DiscrepancyCorrection (const SizetSet &surr_fn_indices, size_t num_fns, size_t num_vars, short corr_type, short corr_order, String approx_type="local_taylor", short approx_order=SHRT_MAX)
	alternate constructor
	~DiscrepancyCorrection ()
	destructor
void	initialize (Model &surr_model, const SizetSet &surr_fn_indices, short corr_type, short corr_order, String approx_type="local_taylor", short approx_order=SHRT_MAX)
	initialize the DiscrepancyCorrection data
void	initialize (const SizetSet &surr_fn_indices, size_t num_fns, size_t num_vars, short corr_type, short corr_order, String approx_type="local_taylor", short approx_order=SHRT_MAX)
	initialize the DiscrepancyCorrection data
void	compute (const Variables &vars, const Response &truth_response, const Response &approx_response, bool quiet_flag=false)
	compute the correction required to bring approx_response into agreement with truth_response and store in {add,mult}Corrections More...
void	compute (const Response &truth_response, const Response &approx_response, Response &discrepancy_response, bool quiet_flag=false)
	compute the correction required to bring approx_response into agreement with truth_response and store in discrepancy_response
void	compute (const VariablesArray &vars_array, const ResponseArray &truth_response_array, const ResponseArray &approx_response, bool quiet_flag=false)
	compute the correction required to bring approx_response into agreement with truth_response as a function of the variables and store in {add,mult}Corrections
void	apply (const Variables &vars, Response &approx_response, bool quiet_flag=false)
	apply the correction computed in compute() to approx_response
void	compute_variance (const VariablesArray &vars_array, RealMatrix &approx_variance, bool quiet_flag=false)
	compute the variance of approx_response
void	correction_type (short corr_type)
	update correctionType
short	correction_type () const
	return correctionType
void	correction_order (short order)
	update correctionOrder
short	correction_order () const
	return correctionOrder
void	data_order (short order)
	update dataOrder
short	data_order () const
	return dataOrder
bool	computed () const
	return correctionComputed
bool	initialized () const
	return initializedFlag

Protected Attributes
SizetSet	surrogateFnIndices
	for mixed response sets, this array specifies the response function subset that is approximated
bool	initializedFlag
	indicates that discrepancy correction instance has been initialized following construction
short	correctionType
	approximation correction approach to be used: NO_CORRECTION, ADDITIVE_CORRECTION, MULTIPLICATIVE_CORRECTION, or COMBINED_CORRECTION.
short	correctionOrder
	approximation correction order to be used: 0, 1, or 2
short	dataOrder
	order of correction data in 3-bit format: overlay of 1 (value), 2 (gradient), and 4 (Hessian)
bool	correctionComputed
	flag indicating whether or not a correction has been computed and is available for application
size_t	numFns
	total number of response functions (of which surrogateFnIndices may define a subset)
size_t	numVars
	number of continuous variables active in the correction

Private Member Functions
void	initialize (short corr_type, short corr_order, String approx_type, short approx_order)
	initialize types and orders
void	initialize_corrections ()
	internal convenience function shared by overloaded initialize() variants
bool	check_multiplicative (const RealVector &truth_fns, const RealVector &approx_fns)
	define badScalingFlag
void	compute_additive (const Response &truth_response, const Response &approx_response, int index, Real &discrep_fn, RealVector &discrep_grad, RealSymMatrix &discrep_hess)
	internal convenience function for computing additive corrections between truth and approximate responses
void	compute_multiplicative (const Response &truth_response, const Response &approx_response, int index, Real &discrep_fn, RealVector &discrep_grad, RealSymMatrix &discrep_hess)
	internal convenience function for computing multiplicative corrections between truth and approximate responses
void	apply_additive (const Variables &vars, Response &approx_response)
	internal convenience function for applying additive corrections to an approximate response
void	apply_multiplicative (const Variables &vars, Response &approx_response)
	internal convenience function for applying multiplicative corrections to an approximate response
void	apply_additive (const Variables &vars, RealVector &approx_fns)
	internal convenience function for applying additive corrections to a set of response functions
void	apply_multiplicative (const Variables &vars, RealVector &approx_fns)
	internal convenience function for applying multiplicative corrections to a set of response functions
const Response &	search_db (const Variables &search_vars, const ShortArray &search_asv)
	search data_pairs for missing approximation data

Private Attributes
Pecos::DiscrepancyCalculator	discrepCalc
	helper utility for calculating discrepancies
bool	badScalingFlag
	flag used to indicate function values near zero for multiplicative corrections; triggers an automatic switch to additive corrections
bool	computeAdditive
	flag indicating the need for additive correction calculations
bool	computeMultiplicative
	flag indicating the need for multiplicative correction calculations
String	approxType
	string indicating the discrepancy approximation type
short	approxOrder
	polynomial order of the discrepancy approximation (basis or trend order)
bool	addAnchor
	flag indicating that data additions are anchor points (for updating local and multipoint approximations)
SharedApproxData	sharedData
	data that is shared among all correction Approximations
std::vector< Approximation >	addCorrections
	array of additive corrections; surrogate models of a model discrepancy function (formed from model differences)
std::vector< Approximation >	multCorrections
	array of multiplicative corrections; surrogate models of a model discrepancy function (formed from model ratios)
Model	surrModel
	shallow copy of the surrogate model instance as returned by Model::surrogate_model() (the DataFitSurrModel or or one of EnsembleSurrModel::approxModels)
RealVector	combineFactors
	factors for combining additive and multiplicative corrections. Each factor is the weighting applied to the additive correction and 1.-factor is the weighting applied to the multiplicative correction. The factor value is determined by an additional requirement to match the high fidelity function value at the previous correction point (e.g., previous trust region center). This results in a multipoint correction instead of a strictly local correction.
Variables	correctionPrevCenterPt
	copy of center point from the previous correction cycle
RealVector	truthFnsCenter
	truth function values at the current correction point
RealVector	approxFnsCenter
	Surrogate function values at the current correction point.
RealMatrix	approxGradsCenter
	Surrogate gradient values at the current correction point.
RealVector	truthFnsPrevCenter
	copy of truth function values at center of previous correction cycle
RealVector	approxFnsPrevCenter
	copy of approximate function values at center of previous correction cycle

Detailed Description

Base class for discrepancy corrections.

The DiscrepancyCorrection class provides common functions for computing and applying corrections to approximations.

Member Function Documentation

compute()

void compute	(	const Variables &	vars,
		const Response &	truth_response,
		const Response &	approx_response,
		bool	quiet_flag = false
	)

compute the correction required to bring approx_response into agreement with truth_response and store in {add,mult}Corrections

Compute an additive or multiplicative correction that corrects the approx_response to have 0th-order consistency (matches values), 1st-order consistency (matches values and gradients), or 2nd-order consistency (matches values, gradients, and Hessians) with the truth_response at a single point (e.g., the center of a trust region). The 0th-order, 1st-order, and 2nd-order corrections use scalar values, linear scaling functions, and quadratic scaling functions, respectively, for each response function.

References Response::active_set(), Approximation::add(), DiscrepancyCorrection::addAnchor, DiscrepancyCorrection::addCorrections, DiscrepancyCorrection::apply(), DiscrepancyCorrection::apply_additive(), DiscrepancyCorrection::apply_multiplicative(), DiscrepancyCorrection::approxFnsCenter, DiscrepancyCorrection::approxFnsPrevCenter, DiscrepancyCorrection::approxGradsCenter, DiscrepancyCorrection::badScalingFlag, Approximation::clear_current_active_data(), DiscrepancyCorrection::combineFactors, DiscrepancyCorrection::computeAdditive, DiscrepancyCorrection::computeMultiplicative, Variables::continuous_variables(), Response::copy(), DiscrepancyCorrection::correctionComputed, DiscrepancyCorrection::correctionOrder, DiscrepancyCorrection::correctionPrevCenterPt, DiscrepancyCorrection::correctionType, DiscrepancyCorrection::dataOrder, DiscrepancyCorrection::discrepCalc, Variables::discrete_int_variables(), Variables::discrete_real_variables(), Response::function_gradient_view(), Response::function_gradients(), Response::function_hessian(), Response::function_value(), Response::function_values(), Model::is_null(), DiscrepancyCorrection::multCorrections, DiscrepancyCorrection::numFns, DiscrepancyCorrection::numVars, ActiveSet::request_values(), DiscrepancyCorrection::sharedData, DiscrepancyCorrection::surrModel, DiscrepancyCorrection::surrogateFnIndices, DiscrepancyCorrection::truthFnsCenter, and DiscrepancyCorrection::truthFnsPrevCenter.

Referenced by DiscrepancyCorrection::compute(), EnsembleSurrModel::compute_apply_delta(), DataFitSurrModel::derived_evaluate(), DataFitSurrModel::derived_synchronize(), DataFitSurrModel::derived_synchronize_nowait(), and EnsembleSurrModel::single_apply().

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

• DiscrepancyCorrection.hpp
• DiscrepancyCorrection.cpp