Derived approximation class for global basis polynomials. More...

Inheritance diagram for PecosApproximation:

Public Member Functions
	PecosApproximation ()
	default constructor
	PecosApproximation (const String &approx_type, const UShortArray &approx_order, size_t num_vars, short data_order)
	alternate constructor
	PecosApproximation (ProblemDescDB &problem_db, size_t num_vars)
	standard ProblemDescDB-driven constructor
	~PecosApproximation ()
	destructor
void	increment_order ()
	increment OrthogPolyApproximation::approxOrder uniformly
void	solution_approach (short soln_approach)
	set pecosBasisApprox.configOptions.expCoeffsSolnApproach
short	solution_approach () const
	get pecosBasisApprox.configOptions.expCoeffsSolnApproach
void	expansion_coefficient_flag (bool coeff_flag)
	set pecosBasisApprox.configOptions.expansionCoeffFlag
bool	expansion_coefficient_flag () const
	get pecosBasisApprox.configOptions.expansionCoeffFlag
void	expansion_gradient_flag (bool grad_flag)
	set pecosBasisApprox.configOptions.expansionGradFlag
bool	expansion_gradient_flag () const
	get pecosBasisApprox.configOptions.expansionGradFlag
void	refinement_control (short refine_cntl)
	set pecosBasisApprox.configOptions.refinementControl
short	refinement_control () const
	get pecosBasisApprox.configOptions.refinementControl
void	vbd_control (short vbd_cntl)
	set pecosBasisApprox.configOptions.vbdControl
short	vbd_control () const
	get pecosBasisApprox.configOptions.vbdControl
void	compute_component_effects ()
	Performs global sensitivity analysis using Sobol' Indices by computing component (main and interaction) effects.
void	compute_total_effects ()
	Performs global sensitivity analysis using Sobol' Indices by computing total effects.
const Pecos::IntIntMap &	sobol_index_map () const
	return polyApproxRep->sobolIndexMap
const Pecos::RealVector &	sobol_indices () const
	return polyApproxRep->sobolIndices
const Pecos::RealVector &	total_sobol_indices () const
	return polyApproxRep->totalSobolIndices
const Pecos::RealVector &	dimension_decay_rates () const
	return OrthogPolyApproximation::decayRates
void	random_variables_key (const Pecos::BoolDeque &random_vars_key)
	set pecosBasisApprox.randomVarsKey
void	integration_iterator (const Iterator &iterator)
	set pecosBasisApprox.driverRep
void	construct_basis (const Pecos::ShortArray &u_types, const Pecos::DistributionParams &dp, const Pecos::BasisConfigOptions &bc_options)
	invoke Pecos::OrthogPolyApproximation::construct_basis()
void	basis_types (const Pecos::ShortArray &basis_types)
	set Pecos::OrthogPolyApproximation::basisTypes
const Pecos::ShortArray &	basis_types () const
	get Pecos::OrthogPolyApproximation::basisTypes
void	polynomial_basis (const std::vector< Pecos::BasisPolynomial > &poly_basis)
	set Pecos::OrthogPolyApproximation::polynomialBasis
const std::vector < Pecos::BasisPolynomial > &	polynomial_basis () const
	get Pecos::OrthogPolyApproximation::polynomialBasis
void	coefficients_norms_flag (bool flag)
	invoke Pecos::OrthogPolyApproximation::coefficients_norms_flag()
void	expansion_terms (size_t terms)
	invoke Pecos::OrthogPolyApproximation::expansion_terms()
size_t	expansion_terms () const
	return Pecos::OrthogPolyApproximation::expansion_terms()
void	allocate_arrays ()
	invoke Pecos::PolynomialApproximation::allocate_arrays()
Real	mean ()
	return the mean of the expansion, treating all variables as random
Real	mean (const Pecos::RealVector &x)
	return the mean of the expansion for a given parameter vector, treating a subset of the variables as random
const Pecos::RealVector &	mean_gradient ()
	return the gradient of the expansion mean for a given parameter vector, treating all variables as random
const Pecos::RealVector &	mean_gradient (const Pecos::RealVector &x, const Pecos::SizetArray &dvv)
	return the gradient of the expansion mean for a given parameter vector and given DVV, treating a subset of the variables as random
Real	variance ()
	return the variance of the expansion, treating all variables as random
Real	variance (const Pecos::RealVector &x)
	return the variance of the expansion for a given parameter vector, treating a subset of the variables as random
const Pecos::RealVector &	variance_gradient ()
	return the gradient of the expansion variance for a given parameter vector, treating all variables as random
const Pecos::RealVector &	variance_gradient (const Pecos::RealVector &x, const Pecos::SizetArray &dvv)
	return the gradient of the expansion variance for a given parameter vector and given DVV, treating a subset of the variables as random
Real	covariance (PecosApproximation *pecos_approx_2)
	return the variance of the expansion, treating all variables as random
Real	covariance (const Pecos::RealVector &x, PecosApproximation *pecos_approx_2)
	return the variance of the expansion, treating a subset of the variables as random
void	compute_moments ()
	compute moments up to the order supported by the Pecos polynomial approximation
void	compute_moments (const Pecos::RealVector &x)
	compute moments in all-variables mode up to the order supported by the Pecos polynomial approximation
const RealVector &	moments () const
	return virtual Pecos::PolynomialApproximation::moments()
const RealVector &	expansion_moments () const
	return Pecos::PolynomialApproximation::expansionMoments
const RealVector &	numerical_moments () const
	return Pecos::PolynomialApproximation::numericalMoments
Pecos::BasisApproximation &	pecos_basis_approximation ()
	return pecosBasisApprox
Protected Member Functions
Real	get_value (const Pecos::RealVector &x)
	retrieve the approximate function value for a given parameter vector
const Pecos::RealVector &	get_gradient (const Pecos::RealVector &x)
	retrieve the approximate function gradient for a given parameter vector
const Pecos::RealSymMatrix &	get_hessian (const Pecos::RealVector &x)
	retrieve the approximate function Hessian for a given parameter vector
int	min_coefficients () const
	return the minimum number of samples (unknowns) required to build the derived class approximation type in numVars dimensions
void	build ()
	builds the approximation from scratch
void	rebuild ()
	rebuilds the approximation incrementally
void	pop (bool save_data)
	removes entries from end of SurrogateData::{vars,resp}Data (last points appended)
void	restore ()
	restores state prior to previous append()
bool	restore_available ()
	queries availability of restoration for trial set
size_t	restoration_index ()
	return index of trial set within restorable bookkeeping sets
void	finalize ()
	finalize approximation by applying all remaining trial sets
size_t	finalization_index (size_t i)
	return index of i-th trailing trial set within restorable bookkeeping sets
void	store ()
	store current approximation for later combination
void	combine (short corr_type)
	combine current approximation with previously stored approximation
void	print_coefficients (std::ostream &s) const
	print the coefficient array computed in build()/rebuild()
const RealVector &	approximation_coefficients () const
	return the coefficient array computed by build()/rebuild()
void	approximation_coefficients (const RealVector &approx_coeffs)
	set the coefficient array from external sources, rather than computing with build()/rebuild()
Private Member Functions
void	approx_type_to_basis_type (const String &approx_type, short &basis_type)
	utility to convert Dakota type string to Pecos type enumeration
Private Attributes
Pecos::BasisApproximation	pecosBasisApprox
	the Pecos basis approximation, encompassing OrthogPolyApproximation and InterpPolyApproximation
Pecos::PolynomialApproximation *	polyApproxRep
	convenience pointer to representation

Detailed Description

Derived approximation class for global basis polynomials.

The PecosApproximation class provides a global approximation based on basis polynomials. This includes orthogonal polynomials used for polynomial chaos expansions and interpolation polynomials used for stochastic collocation.