NonD Class Reference

Base class for all nondetermistic iterators (the DAKOTA/UQ branch). More...

Inheritance diagram for NonD:

Public Member Functions
void	requested_levels (const RealVectorArray &req_resp_levels, const RealVectorArray &req_prob_levels, const RealVectorArray &req_rel_levels, const RealVectorArray &req_gen_rel_levels, short resp_lev_tgt, short resp_lev_tgt_reduce, bool cdf_flag, bool pdf_output)
	set requestedRespLevels, requestedProbLevels, requestedRelLevels, requestedGenRelLevels, respLevelTarget, cdfFlag, and pdfOutput (used in combination with alternate ctors)
void	print_level_mappings (std::ostream &s) const
	prints the z/p/beta/beta* mappings reflected in {requested,computed}{Resp,Prob,Rel,GenRel}Levels for default qoi_type and qoi_labels
void	print_level_mappings (std::ostream &s, String qoi_type, const StringArray &qoi_labels) const
	prints the z/p/beta/beta* mappings reflected in {requested,computed}{Resp,Prob,Rel,GenRel}Levels More...
void	print_level_mappings (std::ostream &s, const RealVector &level_maps, bool moment_offset, const String &prepend="")
	print level mapping statistics using optional pre-pend More...
bool	resize ()
	reinitializes iterator based on new variable size
bool	pdf_output () const
	get pdfOutput
void	pdf_output (bool output)
	set pdfOutput
short	final_moments_type () const
	get finalMomentsType
void	final_moments_type (short type)
	set finalMomentsType
Public Member Functions inherited from Analyzer
const VariablesArray &	all_variables ()
	return the complete set of evaluated variables
const RealMatrix &	all_samples ()
	return the complete set of evaluated samples
const IntResponseMap &	all_responses () const
	return the complete set of computed responses
size_t	num_samples () const
virtual void	vary_pattern (bool pattern_flag)
	sets varyPattern in derived classes that support it
Public Member Functions inherited from Iterator
	Iterator (std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	default constructor More...
	Iterator (ProblemDescDB &problem_db, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	standard envelope constructor, which constructs its own model(s) More...
	Iterator (ProblemDescDB &problem_db, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	alternate envelope constructor which uses the ProblemDescDB but accepts a model from a higher level (meta-iterator) context, instead of constructing its own More...
	Iterator (const String &method_string, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	alternate envelope constructor for instantiations by name without the ProblemDescDB More...
	Iterator (const Iterator &iterator)
	copy constructor More...
virtual	~Iterator ()
	destructor
Iterator	operator= (const Iterator &iterator)
	assignment operator
virtual void	derived_free_communicators (ParLevLIter pl_iter)
	derived class contributions to freeing the communicators associated with this Iterator instance
virtual void	core_run ()
	core portion of run; implemented by all derived classes and may include pre/post steps in lieu of separate pre/post More...
virtual void	post_input ()
	read tabular data for post-run mode
virtual void	reset ()
	restore initial state for repeated sub-iterator executions
virtual void	nested_variable_mappings (const SizetArray &c_index1, const SizetArray &di_index1, const SizetArray &ds_index1, const SizetArray &dr_index1, const ShortArray &c_target2, const ShortArray &di_target2, const ShortArray &ds_target2, const ShortArray &dr_target2)
	set primaryA{CV,DIV,DRV}MapIndices, secondaryA{CV,DIV,DRV}MapTargets within derived Iterators; supports computation of higher-level sensitivities in nested contexts (e.g., derivatives of statistics w.r.t. inserted design variables)
virtual void	nested_response_mappings (const RealMatrix &primary_coeffs, const RealMatrix &secondary_coeffs)
	set primaryResponseCoefficients, secondaryResponseCoefficients within derived Iterators; Necessary for scalarization case in MLMC NonDMultilevelSampling to map scalarization in nested context
virtual void	initialize_iterator (int job_index)
	used by IteratorScheduler to set the starting data for a run
virtual void	pack_parameters_buffer (MPIPackBuffer &send_buffer, int job_index)
	used by IteratorScheduler to pack starting data for an iterator run
virtual void	unpack_parameters_buffer (MPIUnpackBuffer &recv_buffer, int job_index)
	used by IteratorScheduler to unpack starting data for an iterator run
virtual void	unpack_parameters_initialize (MPIUnpackBuffer &recv_buffer, int job_index)
	used by IteratorScheduler to unpack starting data and initialize an iterator run
virtual void	pack_results_buffer (MPIPackBuffer &send_buffer, int job_index)
	used by IteratorScheduler to pack results data from an iterator run
virtual void	unpack_results_buffer (MPIUnpackBuffer &recv_buffer, int job_index)
	used by IteratorScheduler to unpack results data from an iterator run
virtual void	update_local_results (int job_index)
	used by IteratorScheduler to update local results arrays
virtual const RealSymMatrix &	response_error_estimates () const
	return error estimates associated with the final iterator solution
virtual bool	accepts_multiple_points () const
	indicates if this iterator accepts multiple initial points. Default return is false. Override to return true if appropriate.
virtual void	initial_point (const Variables &pt)
	sets the initial point for this iterator (user-functions mode for which Model updating is not used)
virtual void	initial_point (const RealVector &pt)
	sets the initial point (active continuous variables) for this iterator (user-functions mode for which Model updating is not used)
virtual void	initial_points (const VariablesArray &pts)
	sets the multiple initial points for this iterator. This should only be used if accepts_multiple_points() returns true.
virtual void	update_callback_data (const RealVector &cv_initial, const RealVector &cv_lower_bnds, const RealVector &cv_upper_bnds, const RealMatrix &lin_ineq_coeffs, const RealVector &lin_ineq_lb, const RealVector &lin_ineq_ub, const RealMatrix &lin_eq_coeffs, const RealVector &lin_eq_tgt, const RealVector &nln_ineq_lb, const RealVector &nln_ineq_ub, const RealVector &nln_eq_tgt)
	assign variable values and bounds and constraint coefficients and bounds for this iterator (user-functions mode for which iteratedModel is null)
virtual const RealMatrix &	callback_linear_ineq_coefficients () const
	return linear constraint coefficients for this iterator (user-functions mode for which iteratedModel is null)
virtual const RealVector &	callback_linear_ineq_lower_bounds () const
	return linear constraint lower bounds for this iterator (user-functions mode for which iteratedModel is null)
virtual const RealVector &	callback_linear_ineq_upper_bounds () const
	return linear constraint upper bounds for this iterator (user-functions mode for which iteratedModel is null)
virtual void	initialize_graphics (int iterator_server_id=1)
	initialize the 2D graphics window and the tabular graphics data More...
virtual void	check_sub_iterator_conflict ()
	detect any conflicts due to recursive use of the same Fortran solver More...
virtual unsigned short	uses_method () const
	return name of any enabling iterator used by this iterator
virtual void	method_recourse (unsigned short method_name)
	perform a method switch, if possible, due to a detected conflict with the simultaneous use of method_name at an higher-level
virtual void	sampling_reset (size_t min_samples, bool all_data_flag, bool stats_flag)
	reset sampling iterator to use at least min_samples
virtual void	sampling_reference (size_t samples_ref)
	set reference number of samples, which is a lower bound during reset
virtual void	sampling_increment ()
	increment to next in sequence of refinement samples
virtual void	random_seed (int seed)
	set randomSeed, if present
virtual unsigned short	sampling_scheme () const
	return sampling name
virtual IntIntPair	estimate_partition_bounds ()
	estimate the minimum and maximum partition sizes that can be utilized by this Iterator
virtual void	declare_sources ()
	Declare sources to the evaluations database.
void	init_communicators (ParLevLIter pl_iter)
	initialize the communicators associated with this Iterator instance
void	set_communicators (ParLevLIter pl_iter)
	set the communicators associated with this Iterator instance
void	free_communicators (ParLevLIter pl_iter)
	free the communicators associated with this Iterator instance
void	resize_communicators (ParLevLIter pl_iter, bool reinit_comms)
	Resize the communicators. This is called from the letter's resize()
void	parallel_configuration_iterator (ParConfigLIter pc_iter)
	set methodPCIter
ParConfigLIter	parallel_configuration_iterator () const
	return methodPCIter
void	parallel_configuration_iterator_map (std::map< size_t, ParConfigLIter > pci_map)
	set methodPCIterMap
std::map< size_t, ParConfigLIter >	parallel_configuration_iterator_map () const
	return methodPCIterMap
void	run (ParLevLIter pl_iter)
	invoke set_communicators(pl_iter) prior to run()
void	run ()
	orchestrate initialize/pre/core/post/finalize phases More...
void	assign_rep (std::shared_ptr< Iterator > iterator_rep)
	replaces existing letter with a new one More...
void	iterated_model (const Model &model)
	set the iteratedModel (iterators and meta-iterators using a single model instance)
Model &	iterated_model ()
	return the iteratedModel (iterators & meta-iterators using a single model instance)
ProblemDescDB &	problem_description_db () const
	return the problem description database (probDescDB)
ParallelLibrary &	parallel_library () const
	return the parallel library (parallelLib)
void	method_name (unsigned short m_name)
	set the method name to an enumeration value
unsigned short	method_name () const
	return the method name via its native enumeration value
void	method_string (const String &m_str)
	set the method name by string
String	method_string () const
	return the method name by string
String	method_enum_to_string (unsigned short method_enum) const
	convert a method name enumeration value to a string
unsigned short	method_string_to_enum (const String &method_str) const
	convert a method name string to an enumeration value
String	submethod_enum_to_string (unsigned short submethod_enum) const
	convert a sub-method name enumeration value to a string
const String &	method_id () const
	return the method identifier (methodId)
int	maximum_evaluation_concurrency () const
	return the maximum evaluation concurrency supported by the iterator
void	maximum_evaluation_concurrency (int max_conc)
	set the maximum evaluation concurrency supported by the iterator
size_t	maximum_iterations () const
	return the maximum iterations for this iterator
void	maximum_iterations (size_t max_iter)
	set the maximum iterations for this iterator
void	convergence_tolerance (Real conv_tol)
	set the method convergence tolerance (convergenceTol)
Real	convergence_tolerance () const
	return the method convergence tolerance (convergenceTol)
void	output_level (short out_lev)
	set the method output level (outputLevel)
short	output_level () const
	return the method output level (outputLevel)
void	summary_output (bool summary_output_flag)
	Set summary output control; true enables evaluation/results summary.
size_t	num_final_solutions () const
	return the number of solutions to retain in best variables/response arrays
void	num_final_solutions (size_t num_final)
	set the number of solutions to retain in best variables/response arrays
void	active_set (const ActiveSet &set)
	set the default active set (for use with iterators that employ evaluate_parameter_sets())
const ActiveSet &	active_set () const
	return the default active set (used by iterators that employ evaluate_parameter_sets())
void	active_set_request_vector (const ShortArray &asv)
	return the default active set request vector (used by iterators that employ evaluate_parameter_sets())
const ShortArray &	active_set_request_vector () const
	return the default active set request vector (used by iterators that employ evaluate_parameter_sets())
void	active_set_request_values (short asv_val)
	return the default active set request vector (used by iterators that employ evaluate_parameter_sets())
void	sub_iterator_flag (bool si_flag)
	set subIteratorFlag (and update summaryOutputFlag if needed)
bool	is_null () const
	function to check iteratorRep (does this envelope contain a letter?)
std::shared_ptr< Iterator >	iterator_rep () const
	returns iteratorRep for access to derived class member functions that are not mapped to the top Iterator level
virtual void	eval_tag_prefix (const String &eval_id_str)
	set the hierarchical eval ID tag prefix More...
std::shared_ptr< TraitsBase >	traits () const
	returns methodTraits for access to derived class member functions that are not mapped to the top TraitsBase level
bool	top_level ()
	Return whether the iterator is the top level iterator.
void	top_level (bool tflag)
	Set the iterator's top level flag.

Protected Member Functions
	NonD (ProblemDescDB &problem_db, Model &model)
	constructor
	NonD (unsigned short method_name, Model &model)
	alternate constructor for sample generation and evaluation "on the fly"
	NonD (unsigned short method_name, Model &model, const ShortShortPair &approx_view)
	alternate constructor for sample generation and evaluation "on the fly"
	NonD (unsigned short method_name, const RealVector &lower_bnds, const RealVector &upper_bnds)
	alternate constructor for sample generation "on the fly"
	~NonD ()
	destructor
void	derived_set_communicators (ParLevLIter pl_iter)
	derived class contributions to setting the communicators associated with this Iterator instance
void	initialize_run ()
	utility function to perform common operations prior to pre_run(); typically memory initialization; setting of instance pointers More...
void	finalize_run ()
	utility function to perform common operations following post_run(); deallocation and resetting of instance pointers More...
const Response &	response_results () const
	return the final statistics from the nondeterministic iteration
void	response_results_active_set (const ActiveSet &set)
	set the active set within finalStatistics
virtual void	initialize_response_covariance ()
	initializes respCovariance
virtual void	initialize_final_statistics ()
	initializes finalStatistics for storing NonD final results More...
virtual void	update_final_statistics ()
	update finalStatistics::functionValues
virtual bool	discrepancy_sample_counts () const
	flag identifying whether sample counts correspond to level discrepancies
void	pull_level_mappings (RealVector &level_maps, size_t offset)
	concatenate computed{Resp,Prob,Rel,GenRel}Levels into level_maps
void	push_level_mappings (const RealVector &level_maps, size_t offset)
	update computed{Resp,Prob,Rel,GenRel}Levels from level_maps
void	configure_1d_sequence (size_t &num_steps, size_t &secondary_index, short &seq_type)
	configure a one-dimensional hierarchical sequence (ML or MF) More...
void	configure_2d_sequence (size_t &num_steps, size_t &secondary_index, short &seq_type)
	configure a two-dimensional hierarchical sequence (MLMF) More...
void	configure_enumeration (size_t &num_combinations, short &seq_type)
	configure the total number of model form/resolution level options More...
short	configure_cost (size_t num_steps, short seq_type, RealVector &cost)
	extract cost estimates from model ensemble, enforcing requirements (case without metadata support)
short	configure_cost (size_t num_steps, short seq_type, RealVector &cost, SizetSizetPairArray &cost_md_indices)
	extract cost estimates from model ensemble, enforcing requirements (case with metadata support)
short	query_cost (size_t num_steps, short seq_type, RealVector &cost)
	optionally extract cost estimates from model ensemble, if available (case without metadata support)
short	query_cost (size_t num_steps, short seq_type, RealVector &cost, BitArray &model_cost_spec, const SizetSizetPairArray &cost_md_indices)
	optionally extract cost estimates from model ensemble, if available (case with metadata support)
void	test_cost (short seq_type, const BitArray &model_cost_spec, SizetSizetPairArray &cost_md_indices)
	check cost specification and metadata indices for each active model
bool	test_cost (bool cost_spec, SizetSizetPair &cost_md_indices, const String &model_id)
	check cost specification and metadata indices for a given model
bool	valid_cost (Real cost) const
	test cost for value > 0
bool	valid_costs (const RealVector &costs) const
	test costs for valid values > 0
void	load_pilot_sample (const SizetArray &pilot_spec, size_t num_steps, SizetArray &delta_N_l)
	distribute pilot sample specification across model forms or levels
void	load_pilot_sample (const SizetArray &pilot_spec, short seq_type, const Sizet3DArray &N_l, Sizet2DArray &delta_N_l)
	distribute pilot sample specification across model forms and levels
template<typename ArrayType >
void	inflate_approx_samples (const ArrayType &N_l, bool multilev, size_t secondary_index, std::vector< ArrayType > &N_l_vec)
	update the relevant slice of N_l_3D from the final 2D multilevel or 2D multifidelity sample profile
template<typename ArrayType >
void	inflate_sequence_samples (const ArrayType &N_l, bool multilev, size_t secondary_index, std::vector< ArrayType > &N_l_vec)
	update the relevant slice of N_l_3D from the final 2D multilevel or 2D multifidelity sample profile
void	resize_final_statistics_gradients ()
	resizes finalStatistics::functionGradients based on finalStatistics ASV
void	update_aleatory_final_statistics ()
	update finalStatistics::functionValues from momentStats and computed{Prob,Rel,GenRel,Resp}Levels
void	update_system_final_statistics ()
	update system metrics from component metrics within finalStatistics
void	update_system_final_statistics_gradients ()
	update finalStatistics::functionGradients
void	initialize_level_mappings ()
	size computed{Resp,Prob,Rel,GenRel}Levels
void	compute_densities (const RealRealPairArray &min_max_fns, bool prob_refinement=false, bool all_levels_computed=false)
	compute the PDF bins from the CDF/CCDF values and store in computedPDF{Abscissas,Ordinates} More...
void	print_densities (std::ostream &s) const
	output the PDFs reflected in computedPDF{Abscissas,Ordinates} using default qoi_type and pdf_labels
void	print_densities (std::ostream &s, String qoi_type, const StringArray &pdf_labels) const
	output the PDFs reflected in computedPDF{Abscissas,Ordinates}
void	print_system_mappings (std::ostream &s) const
	print system series/parallel mappings for response levels
void	print_multilevel_evaluation_summary (std::ostream &s, const SizetArray &N_m)
	print evaluation summary for multilevel sampling across 1D level profile
void	print_multilevel_evaluation_summary (std::ostream &s, const Sizet2DArray &N_m)
	print evaluation summary for multilevel sampling across 2D level+QoI profile
void	print_multilevel_discrepancy_summary (std::ostream &s, const SizetArray &N_m)
	print evaluation summary for multilevel sampling across 1D level profile for discrepancy across levels
void	print_multilevel_discrepancy_summary (std::ostream &s, const SizetArray &N_m, const SizetArray &N_mp1)
	print evaluation summary for multilevel sampling across 1D level profile for discrepancy across model forms
void	print_multilevel_discrepancy_summary (std::ostream &s, const Sizet2DArray &N_m)
	print evaluation summary for multilevel sampling across 2D level+QoI profile for discrepancy across levels
void	print_multilevel_discrepancy_summary (std::ostream &s, const Sizet2DArray &N_m, const Sizet2DArray &N_mp1)
	print evaluation summary for multilevel sampling across 2D level+QoI profile for discrepancy across model forms
template<typename ArrayType >
void	print_multilevel_model_summary (std::ostream &s, const std::vector< ArrayType > &N_samp, String type, short seq_type, bool discrep_flag)
	print evaluation summary for multilevel sampling across 2D model+level profile (allocations) or 3D model+level+QoI profile (actual)
void	construct_lhs (Iterator &u_space_sampler, Model &u_model, unsigned short sample_type, int num_samples, int seed, const String &rng, bool vary_pattern, short sampling_vars_mode=ACTIVE)
	assign a NonDLHSSampling instance within u_space_sampler
unsigned short	sub_optimizer_select (unsigned short requested_sub_method, unsigned short default_sub_method=SUBMETHOD_NPSOL)
	utility for vetting sub-method request against optimizers within the package configuration
size_t	one_sided_relax_round (Real diff, Real relax_factor=1.)
	compute a one-sided sample increment for multilevel methods to move current sampling level to a new target
size_t	one_sided_delta (Real current, Real target, Real relax_factor=1.)
	compute a one-sided sample increment for multilevel methods to move current sampling level to a new target
size_t	one_sided_delta (const SizetArray &current, const RealVector &targets, Real relax_factor=1., size_t power=1)
	compute a one-sided sample increment for multilevel methods to move current sampling level to a new target
size_t	one_sided_delta (const SizetArray &current, Real target, Real relax_factor=1., size_t power=1)
	compute a one-sided sample increment for multilevel methods to move current sampling level to a new target
void	one_sided_delta (const SizetArray &current, const RealVector &targets, SizetArray &delta_N, Real relax_factor=1.)
	compute a one-sided sample increment vector to move current sampling levels to new targets
void	one_sided_delta (const Sizet2DArray &current, const RealVector &targets, SizetArray &delta_N, Real relax_factor=1.)
	compute a one-sided sample increment vector to move current sampling levels to new targets
bool	differ (size_t N_alloc_ij, const SizetArray &N_actual_ij) const
	return true if fine-grained reporting differs from coarse-grained
bool	differ (const SizetArray &N_alloc_i, const Sizet2DArray &N_actual_i) const
	return true if fine-grained reporting differs from coarse-grained
bool	differ (const Sizet2DArray &N_alloc, const Sizet3DArray &N_actual) const
	return true if fine-grained reporting differs from coarse-grained
void	archive_allocate_mappings ()
	allocate results array storage for distribution mappings
void	archive_from_resp (size_t fn_index, size_t inc_id=0)
	archive the mappings from specified response levels for specified fn
void	archive_to_resp (size_t fn_index, size_t inc_id=0)
	archive the mappings to computed response levels for specified fn and (optional) increment id.
void	archive_allocate_pdf ()
	allocate results array storage for pdf histograms
void	archive_pdf (size_t fn_index, size_t inc_id=0)
	archive a single pdf histogram for specified function
void	archive_equiv_hf_evals (const Real equiv_hf_evals)
	archive the equivalent number of HF evals (used by ML/MF methods)
bool	zeros (const SizetArray &N_m) const
	return true if N_m is empty or only populated with zeros
bool	zeros (const Sizet2DArray &N_m) const
	return true if N_m is empty or only populated with zeros
bool	zeros (const SizetVector &N_m) const
	return true if N_m is empty or only populated with zeros
bool	homogeneous (const SizetArray &N_l) const
	return true if N_l has consistent values
Protected Member Functions inherited from Analyzer
	Analyzer ()
	default constructor
	Analyzer (ProblemDescDB &problem_db, Model &model)
	standard constructor
	Analyzer (unsigned short method_name, Model &model)
	alternate constructor for instantiations "on the fly" with a Model
	Analyzer (unsigned short method_name, Model &model, const ShortShortPair &view_override)
	alternate constructor for instantiations "on the fly" with a Model
	Analyzer (unsigned short method_name)
	alternate constructor for instantiations "on the fly" without a Model
	~Analyzer ()
	destructor
virtual void	get_parameter_sets (Model &model)
	Generate one block of numSamples samples (ndim * num_samples), populating allSamples; ParamStudy is the only class that specializes to use allVariables.
virtual void	get_parameter_sets (Model &model, const size_t num_samples, RealMatrix &design_matrix)
	Generate one block of numSamples samples (ndim * num_samples), populating design_matrix.
virtual void	update_model_from_sample (Model &model, const Real *sample_vars)
	update model's current variables with data from sample
virtual void	update_model_from_variables (Model &model, const Variables &vars)
	update model's current variables with data from vars
virtual void	sample_to_variables (const Real *sample_vars, Variables &vars)
	convert column of samples array to variables; derived classes may reimplement for more than active continuous variables More...
void	update_from_model (const Model &model)
	set inherited data attributes based on extractions from incoming model
void	pre_run ()
	pre-run portion of run (optional); re-implemented by Iterators which can generate all Variables (parameter sets) a priori More...
void	post_run (std::ostream &s)
	post-run portion of run (optional); verbose to print results; re-implemented by Iterators that can read all Variables/Responses and perform final analysis phase in a standalone way More...
void	pre_output ()
void	print_results (std::ostream &s, short results_state=FINAL_RESULTS)
	print the final iterator results More...
const Model &	algorithm_space_model () const
const Variables &	variables_results () const
	return a single final iterator solution (variables)
const VariablesArray &	variables_array_results ()
	return multiple final iterator solutions (variables). This should only be used if returns_multiple_points() returns true.
const ResponseArray &	response_array_results ()
	return multiple final iterator solutions (response). This should only be used if returns_multiple_points() returns true.
bool	compact_mode () const
	returns Analyzer::compactMode
bool	returns_multiple_points () const
	indicates if this iterator returns multiple final points. Default return is false. Override to return true if appropriate.
void	evaluate_parameter_sets (Model &model, bool log_resp_flag=true, bool log_best_flag=false)
	perform function evaluations to map parameter sets (allVariables) into response sets (allResponses) More...
void	evaluate_batch (Model &model, int batch_id, bool log_best_flag=false)
	perform function evaluations to map a keyed batch of parameter sets (allVariablesMap[key]) into a corresponding batch of response sets (allResponsesMap[key])
const IntIntResponse2DMap &	synchronize_batches (Model &model, bool log_best_flag=false)
	perform function evaluations to map a keyed batch of parameter sets (allVariablesMap[key]) into a corresponding batch of response sets (allResponsesMap[key])
void	clear_batches ()
	since synchronize returns the aggregation of all evaluated batches, we use a separate call to indicate when processing of this data is complete and bookkeeping can be cleared
void	get_vbd_parameter_sets (Model &model, size_t num_samples)
	generate replicate parameter sets for use in variance-based decomposition More...
virtual void	archive_model_variables (const Model &, size_t idx) const
	archive model evaluation points
virtual void	archive_model_response (const Response &, size_t idx) const
	archive model evaluation responses
void	read_variables_responses (int num_evals, size_t num_vars)
	convenience function for reading variables/responses (used in derived classes post_input) More...
void	samples_to_variables_array (const RealMatrix &sample_matrix, VariablesArray &vars_array)
	convert samples array to variables array; e.g., allSamples to allVariables
virtual void	variables_to_sample (const Variables &vars, Real *sample_c_vars)
	convert the active continuous variables into a column of allSamples More...
void	variables_array_to_samples (const VariablesArray &vars_array, RealMatrix &sample_matrix)
	convert variables array to samples array; e.g., allVariables to allSamples
Protected Member Functions inherited from Iterator
	Iterator (BaseConstructor, ProblemDescDB &problem_db, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	constructor initializes the base class part of letter classes (BaseConstructor overloading avoids infinite recursion in the derived class constructors - Coplien, p. 139) More...
	Iterator (NoDBBaseConstructor, unsigned short method_name, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	alternate constructor for base iterator classes constructed on the fly More...
	Iterator (NoDBBaseConstructor, unsigned short method_name, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	alternate constructor for base iterator classes constructed on the fly More...
	Iterator (NoDBBaseConstructor, Model &model, size_t max_iter, size_t max_eval, Real conv_tol, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	alternate envelope constructor for instantiations without ProblemDescDB More...
virtual void	derived_init_communicators (ParLevLIter pl_iter)
	derived class contributions to initializing the communicators associated with this Iterator instance
virtual const VariablesArray &	initial_points () const
	gets the multiple initial points for this iterator. This will only be meaningful after a call to initial_points mutator.
StrStrSizet	run_identifier () const
	get the unique run identifier based on method name, id, and number of executions
void	initialize_model_graphics (Model &model, int iterator_server_id)
	helper function that encapsulates initialization operations, modular on incoming Model instance More...
void	export_final_surrogates (Model &data_fit_surr_model)
	export final surrogates generated, e.g., GP in EGO and friends More...

Protected Attributes
NonD *	prevNondInstance
	pointer containing previous value of nondInstance
size_t	startCAUV
	starting index of continuous aleatory uncertain variables within active continuous variables (convenience for managing offsets)
size_t	numCAUV
	number of active continuous aleatory uncertain variables
bool	epistemicStats
	flag for computing interval-type metrics instead of integrated metrics If any epistemic vars are active in a metric evaluation, then flag is set.
RealMatrix	momentStats
	standardized or central resp moments, as determined by finalMomentsType. Calculated in compute_moments()) and indexed as (moment,fn).
RealVectorArray	requestedRespLevels
	requested response levels for all response functions
RealVectorArray	computedProbLevels
	output probability levels for all response functions resulting from requestedRespLevels
RealVectorArray	computedRelLevels
	output reliability levels for all response functions resulting from requestedRespLevels
RealVectorArray	computedGenRelLevels
	output generalized reliability levels for all response functions resulting from requestedRespLevels
short	respLevelTarget
	indicates mapping of z->p (PROBABILITIES), z->beta (RELIABILITIES), or z->beta* (GEN_RELIABILITIES)
short	respLevelTargetReduce
	indicates component or system series/parallel failure metrics
RealVectorArray	requestedProbLevels
	requested probability levels for all response functions
RealVectorArray	requestedRelLevels
	requested reliability levels for all response functions
RealVectorArray	requestedGenRelLevels
	requested generalized reliability levels for all response functions
RealVectorArray	computedRespLevels
	output response levels for all response functions resulting from requestedProbLevels, requestedRelLevels, or requestedGenRelLevels
size_t	totalLevelRequests
	total number of levels specified within requestedRespLevels, requestedProbLevels, and requestedRelLevels
bool	cdfFlag
	flag for type of probabilities/reliabilities used in mappings: cumulative/CDF (true) or complementary/CCDF (false)
bool	pdfOutput
	flag for managing output of response probability density functions (PDFs)
RealVectorArray	computedPDFAbscissas
	sorted response PDF intervals bounds extracted from min/max sample and requested/computedRespLevels (vector lengths = num bins + 1)
RealVectorArray	computedPDFOrdinates
	response PDF densities computed from bin counts divided by (unequal) bin widths (vector lengths = num bins)
Response	finalStatistics
	final statistics from the uncertainty propagation used in strategies: response means, standard deviations, and probabilities of failure
short	finalMomentsType
	type of moments logged within finalStatistics: none, central, standard
size_t	miPLIndex
	index for the active ParallelLevel within ParallelConfiguration::miPLIters
BitArray	pdfComputed
	Whether PDF was computed for function i; used to determine whether a pdf should be archived.
Protected Attributes inherited from Analyzer
size_t	numFunctions
	number of response functions
size_t	numContinuousVars
	number of active continuous vars
size_t	numDiscreteIntVars
	number of active discrete integer vars
size_t	numDiscreteStringVars
	number of active discrete string vars
size_t	numDiscreteRealVars
	number of active discrete real vars
bool	compactMode
	switch for allSamples (compact mode) instead of allVariables (normal mode)
VariablesArray	allVariables
	array of all variables to be evaluated in evaluate_parameter_sets()
RealMatrix	allSamples
	compact alternative to allVariables
IntResponseMap	allResponses
	array of all responses to be computed in evaluate_parameter_sets()
IntIntVariables2DMap	batchVariablesMap
	alternate container for Variables samples supporting evaluate_batch() and synchronize_batches(), a 2D map with outer batch_id and inner eval_id
IntIntRealVector2DMap	batchSamplesMap
	alternate container for RealVector samples supporting evaluate_batch() and synchronize_batches(), a 2D map with outer batch_id and inner eval_id
IntIntResponse2DMap	batchResponsesMap
	alternate container for Response samples supporting evaluate_batch() and synchronize_batches(), a 2D map with outer batch_id and inner eval_id
StringArray	allHeaders
	array of headers to insert into output while evaluating allVariables
size_t	numObjFns
	number of objective functions
size_t	numLSqTerms
	number of least squares terms
RealPairPRPMultiMap	bestVarsRespMap
	map which stores best set of solutions
bool	vbdFlag
	flag indicating the activation of variance-bsaed decomposition for computing Sobol' indices, via either PCE or sampling
Real	vbdDropTol
	tolerance for omitting output of small VBD indices computed via either PCE or sampling
Protected Attributes inherited from Iterator
ProblemDescDB &	probDescDB
	class member reference to the problem description database More...
ParallelLibrary &	parallelLib
	class member reference to the parallel library
ParConfigLIter	methodPCIter
	the active ParallelConfiguration used by this Iterator instance
Model	iteratedModel
	the model to be iterated (for iterators and meta-iterators employing a single model instance)
size_t	myModelLayers
	number of Models locally (in Iterator or derived classes) wrapped around the initially passed in Model
unsigned short	methodName
	name of the iterator (the user's method spec)
Real	convergenceTol
	iteration convergence tolerance
size_t	maxIterations
	maximum number of iterations for the method
size_t	maxFunctionEvals
	maximum number of fn evaluations for the method
int	maxEvalConcurrency
	maximum number of concurrent model evaluations More...
ActiveSet	activeSet
	the response data requirements on each function evaluation
size_t	numFinalSolutions
	number of solutions to retain in best variables/response arrays
VariablesArray	bestVariablesArray
	collection of N best solution variables found during the study; always in context of Model originally passed to the Iterator (any in-flight Recasts must be undone)
ResponseArray	bestResponseArray
	collection of N best solution responses found during the study; always in context of Model originally passed to the Iterator (any in-flight Recasts must be undone)
bool	subIteratorFlag
	flag indicating if this Iterator is a sub-iterator (NestedModel::subIterator or DataFitSurrModel::daceIterator)
short	outputLevel
	output verbosity level: {SILENT,QUIET,NORMAL,VERBOSE,DEBUG}_OUTPUT
bool	summaryOutputFlag
	flag for summary output (evaluation stats, final results); default true, but false for on-the-fly (helper) iterators and sub-iterator use cases
ResultsManager &	resultsDB
	reference to the global iterator results database
EvaluationStore &	evaluationsDB
	reference to the global evaluation database
EvaluationsDBState	evaluationsDBState
	State of evaluations DB for this iterator.
ResultsNames	resultsNames
	valid names for iterator results
std::shared_ptr< TraitsBase >	methodTraits
	pointer that retains shared ownership of a TraitsBase object, or child thereof
bool	topLevel
	Whether this is the top level iterator.
bool	exportSurrogate = false
	whether to export final surrogates
String	surrExportPrefix
	base filename for exported surrogates
unsigned short	surrExportFormat = NO_MODEL_FORMAT
	(bitwise) format(s) to export

Static Protected Attributes
static NonD *	nondInstance
	pointer to the active object instance used within static evaluator functions in order to avoid the need for static data

Private Member Functions
void	initialize_counts ()
	initialize data based on variable counts
void	distribute_levels (RealVectorArray &levels, bool ascending=true)
	convenience function for distributing a vector of levels among multiple response functions if a short-hand specification is employed.
void	level_mappings_file (size_t fn_index, const String &qoi_label) const
	Write level mappings to a file for a single response. More...
void	print_level_map (std::ostream &s, size_t fn_index, const String &qoi_label) const
	Print level mapping for a single response function to ostream. More...
void	print_multilevel_row (std::ostream &s, const SizetArray &N_j)
	print an set of aggregated QoI sample counts for a level
void	print_multilevel_row (std::ostream &s, const SizetArray &N_j, const SizetArray &N_jp1)
	print an unrolled set of aggregated QoI sample counts for a level

Additional Inherited Members
Static Protected Member Functions inherited from Iterator
static void	gnewton_set_recast (const Variables &recast_vars, const ActiveSet &recast_set, ActiveSet &sub_model_set)
	conversion of request vector values for the Gauss-Newton Hessian approximation More...

Detailed Description

Base class for all nondetermistic iterators (the DAKOTA/UQ branch).

The base class for nondeterministic iterators consolidates uncertain variable data and probabilistic utilities for inherited classes.

Member Function Documentation

print_level_mappings() [1/2]

void print_level_mappings	(	std::ostream &	s,
		String	qoi_type,
		const StringArray &	qoi_labels
	)		const

prints the z/p/beta/beta* mappings reflected in {requested,computed}{Resp,Prob,Rel,GenRel}Levels

Print distribution mappings, including to file per response.

References NonD::level_mappings_file(), Analyzer::numFunctions, Iterator::outputLevel, NonD::print_densities(), NonD::print_level_map(), NonD::requestedGenRelLevels, NonD::requestedProbLevels, NonD::requestedRelLevels, NonD::requestedRespLevels, and Dakota::write_precision.

print_level_mappings() [2/2]

void print_level_mappings	(	std::ostream &	s,
		const RealVector &	level_maps,
		bool	moment_offset,
		const String &	prepend = ""
	)

print level mapping statistics using optional pre-pend

This version differs in its use of a concatenated vector of level mappings, rathen than computed{Resp,Prob,Real,GenRel}Levels.

References NonD::cdfFlag, Iterator::iteratedModel, Analyzer::numFunctions, NonD::requestedGenRelLevels, NonD::requestedProbLevels, NonD::requestedRelLevels, NonD::requestedRespLevels, NonD::respLevelTarget, Model::response_labels(), and Dakota::write_precision.

initialize_run()

void initialize_run ( )

inlineprotectedvirtual

utility function to perform common operations prior to pre_run(); typically memory initialization; setting of instance pointers

Perform initialization phases of run sequence, like allocating memory and setting instance pointers. Commonly used in sub-iterator executions. This is a virtual function; when re-implementing, a derived class must call its nearest parent's initialize_run(), typically before performing its own implementation steps.

Reimplemented from Analyzer.

References Analyzer::initialize_run(), NonD::nondInstance, and NonD::prevNondInstance.

finalize_run()

void finalize_run ( )

inlineprotectedvirtual

utility function to perform common operations following post_run(); deallocation and resetting of instance pointers

Optional: perform finalization phases of run sequence, like deallocating memory and resetting instance pointers. Commonly used in sub-iterator executions. This is a virtual function; when re-implementing, a derived class must call its nearest parent's finalize_run(), typically after performing its own implementation steps.

Reimplemented from Analyzer.

References Analyzer::finalize_run(), NonD::nondInstance, and NonD::prevNondInstance.

initialize_final_statistics()

void initialize_final_statistics ( )

protectedvirtual

initializes finalStatistics for storing NonD final results

Default definition of virtual function (used by sampling, reliability, and stochastic expansion methods) defines the set of statistical results to include the first two moments and level mappings for each QoI.

Reimplemented in NonDInterval, and NonDEnsembleSampling.

References Dakota::abort_handler(), NonD::cdfFlag, Model::cv(), ActiveSet::derivative_vector(), NonD::epistemicStats, NonD::finalMomentsType, NonD::finalStatistics, Response::function_labels(), Model::inactive_continuous_variable_ids(), Iterator::iteratedModel, Dakota::length(), Analyzer::numFunctions, NonD::requestedGenRelLevels, NonD::requestedProbLevels, NonD::requestedRelLevels, NonD::requestedRespLevels, NonD::respLevelTarget, NonD::respLevelTargetReduce, and NonD::totalLevelRequests.

Referenced by NonDEnsembleSampling::initialize_final_statistics(), NonDAdaptImpSampling::NonDAdaptImpSampling(), NonDAdaptiveSampling::NonDAdaptiveSampling(), NonDExpansion::NonDExpansion(), NonDGPImpSampling::NonDGPImpSampling(), NonDIntegration::NonDIntegration(), NonDLHSSampling::NonDLHSSampling(), NonDReliability::NonDReliability(), NonD::requested_levels(), and NonDReliability::resize().

configure_1d_sequence()

void configure_1d_sequence ( size_t &  num_steps, size_t &  secondary_index, short &  seq_type  )

protected

configure a one-dimensional hierarchical sequence (ML or MF)

A one-dimensional sequence is defined in this case.

References Dakota::abort_handler(), Iterator::iteratedModel, Model::multifidelity(), Model::multilevel(), Model::multilevel_multifidelity(), Model::subordinate_models(), and Dakota::SZ_MAX.

Referenced by NonD::configure_2d_sequence(), NonDMultilevelSampling::core_run(), NonDExpansion::multifidelity_individual_refinement(), NonDExpansion::multifidelity_integrated_refinement(), NonDExpansion::multifidelity_reference_expansion(), and NonDExpansion::multilevel_regression().

configure_2d_sequence()

void configure_2d_sequence ( size_t &  total_steps, size_t &  secondary_index, short &  seq_type  )

protected

configure a two-dimensional hierarchical sequence (MLMF)

A two-dimensional sequence is supported in this case.

References NonD::configure_1d_sequence(), Iterator::iteratedModel, Model::multilevel_multifidelity(), Model::subordinate_models(), and Dakota::SZ_MAX.

Referenced by NonDMultilevControlVarSampling::NonDMultilevControlVarSampling().

configure_enumeration()

void configure_enumeration ( size_t &  num_combinations, short &  seq_type  )

protected

configure the total number of model form/resolution level options

Both model forms and resolutions are enumerated, from head to tail with resolutions as inner loop.

References Iterator::iteratedModel, and Model::subordinate_models().

Referenced by NonDNonHierarchSampling::NonDNonHierarchSampling().

compute_densities()

void compute_densities ( const RealRealPairArray &  min_max_fns, bool  prob_refinement = false, bool  all_levels_computed = false  )

protected

compute the PDF bins from the CDF/CCDF values and store in computedPDF{Abscissas,Ordinates}

This function infers PDFs from the CDF/CCDF level mappings, in order to enable PDF computation after CDF/CCDF probability level refinement (e.g., from importance sampling).

prob_refinement alerts the routine to exclude inverse mappings from the PDF, since refinement only applies to z->p forward mappings and mixing refined and unrefined probability mappings results in an inconsistency (potentially manifesting as negative density values).

all_levels_computed is an option used by reliability methods where computed*Levels are defined across the union of all requested levels.

References NonD::archive_allocate_pdf(), NonD::cdfFlag, NonD::computedGenRelLevels, NonD::computedPDFAbscissas, NonD::computedPDFOrdinates, NonD::computedProbLevels, NonD::computedRespLevels, Analyzer::numFunctions, NonD::pdfComputed, NonD::pdfOutput, NonD::requestedGenRelLevels, NonD::requestedProbLevels, NonD::requestedRelLevels, NonD::requestedRespLevels, and NonD::respLevelTarget.

Referenced by NonDSampling::compute_level_mappings(), NonDExpansion::compute_numerical_statistics(), NonDAdaptImpSampling::core_run(), NonDLocalReliability::core_run(), and NonDGlobalReliability::importance_sampling().

level_mappings_file()

void level_mappings_file ( size_t  fn_index, const String &  qoi_label  ) const

private

Write level mappings to a file for a single response.

Write distribution mappings to a file for a single response.

References NonD::print_level_map(), and Dakota::write_precision.

Referenced by NonD::print_level_mappings().

print_level_map()

void print_level_map ( std::ostream &  s, size_t  fn_index, const String &  qoi_label  ) const

private

Print level mapping for a single response function to ostream.

Print the distribution mapping for a single response function to the passed output stream. This base class version maps from one requested level type to one computed level type; some derived class implementations (e.g., local and global reliability) output multiple computed level types.

References NonD::cdfFlag, NonD::computedGenRelLevels, NonD::computedProbLevels, NonD::computedRelLevels, NonD::computedRespLevels, NonD::requestedGenRelLevels, NonD::requestedProbLevels, NonD::requestedRelLevels, NonD::requestedRespLevels, NonD::respLevelTarget, and Dakota::write_precision.

Referenced by NonD::level_mappings_file(), and NonD::print_level_mappings().

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

• DakotaNonD.hpp
• DakotaNonD.cpp