Dakota
Version 6.19
Explore and Predict with Confidence
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Class for the Dempster-Shafer Evidence Theory methods within DAKOTA/UQ. More...
Public Member Functions | |
NonDGlobalEvidence (ProblemDescDB &problem_db, Model &model) | |
constructor | |
~NonDGlobalEvidence () | |
destructor | |
void | initialize () |
perform any required initialization | |
void | set_cell_bounds () |
set the optimization variable bounds for each cell | |
void | get_best_sample (bool maximize, bool eval_approx) |
determine truthFnStar and approxFnStar | |
void | post_process_cell_results (bool maximize) |
post-process a cell minimization/maximization result | |
void | post_process_response_fn_results () |
post-process the interval computed for a response function | |
void | post_process_final_results () |
perform final post-processing | |
Public Member Functions inherited from NonDGlobalInterval | |
NonDGlobalInterval (ProblemDescDB &problem_db, Model &model) | |
constructor | |
~NonDGlobalInterval () | |
destructor | |
void | derived_init_communicators (ParLevLIter pl_iter) |
derived class contributions to initializing the communicators associated with this Iterator instance | |
void | derived_set_communicators (ParLevLIter pl_iter) |
derived class contributions to setting the communicators associated with this Iterator instance | |
void | derived_free_communicators (ParLevLIter pl_iter) |
derived class contributions to freeing the communicators associated with this Iterator instance | |
void | core_run () |
Performs an optimization to determine interval bounds for an entire function or interval bounds on a particular statistical estimator. | |
const Model & | algorithm_space_model () const |
Public Member Functions inherited from NonDInterval | |
NonDInterval (ProblemDescDB &problem_db, Model &model) | |
constructor | |
~NonDInterval () | |
destructor | |
void | print_results (std::ostream &s, short results_state=FINAL_RESULTS) |
print the cumulative distribution functions for belief and plausibility | |
bool | resize () |
reinitializes iterator based on new variable size | |
Public Member Functions inherited from NonD | |
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 | 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 | 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. | |
Additional Inherited Members | |
Protected Member Functions inherited from NonDGlobalInterval | |
void | post_process_run_results (bool maximize) |
post-process an optimization execution: output results, update convergence controls, and update GP approximation | |
void | evaluate_response_star_truth () |
evaluate the truth response at the optimal variables solution and update the GP with the new data | |
Protected Member Functions inherited from NonDInterval | |
void | initialize_final_statistics () |
initialize finalStatistics for belief/plausibility results sets | |
void | compute_evidence_statistics () |
method for computing belief and plausibility values for response levels or vice-versa | |
void | calculate_cells_and_bpas () |
computes the interval combinations (cells) and their bpas replaces CBPIIC_F77 from wrapper calculate_basic_prob_intervals() | |
void | calculate_cbf_cpf (bool complementary=true) |
function to compute (complementary) distribution functions on belief and plausibility replaces CCBFPF_F77 from wrapper calculate_cum_belief_plaus() | |
Protected Member Functions inherited from NonD | |
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 | 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 | 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_sequence (size_t &num_steps, size_t &secondary_index, short &seq_type) |
configure fidelity/level counts from model hierarchy More... | |
void | configure_cost (unsigned short num_steps, bool multilevel, RealVector &cost) |
extract cost estimates from model hierarchy (forms or resolutions) | |
bool | query_cost (unsigned short num_steps, bool multilevel, RealVector &cost) |
extract cost estimates from model hierarchy, if available | |
bool | query_cost (unsigned short num_steps, Model &model, RealVector &cost) |
extract cost estimates from model hierarchy, if available | |
bool | valid_cost_values (const RealVector &cost) |
test cost 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_delta (Real current, Real target) |
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 ¤t, const RealVector &targets, size_t power) |
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 ¤t, Real target, size_t power) |
compute a one-sided sample increment for multilevel methods to move current sampling level to a new target | |
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) | |
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 () |
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, bool log_best_flag) |
perform function evaluations to map parameter sets (allVariables) into response sets (allResponses) More... | |
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 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... | |
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... | |
Protected Attributes inherited from NonDGlobalInterval | |
Iterator | daceIterator |
LHS iterator for constructing initial GP for all response functions. | |
Model | fHatModel |
GP model of response, one approximation per response function. | |
Iterator | intervalOptimizer |
optimizer for solving surrogate-based subproblem: NCSU DIRECT optimizer for maximizing expected improvement or mixed EA if discrete variables. | |
Model | intervalOptModel |
recast model which formulates the surrogate-based optimization subproblem (recasts as design problem; may assimilate mean and variance to enable max(expected improvement)) | |
Real | approxFnStar |
approximate response corresponding to minimum/maximum truth response | |
Real | truthFnStar |
minimum/maximum truth response function value | |
Protected Attributes inherited from NonDInterval | |
size_t | numContIntervalVars |
number of variables of type CONTINUOUS_INTERVAL_UNCERTAIN | |
size_t | numDiscIntervalVars |
number of variables of type DISCRETE_INTERVAL_UNCERTAIN | |
size_t | numDiscSetIntUncVars |
number of variables of type DISCRETE_UNCERTAIN_SET_INT | |
size_t | numDiscSetRealUncVars |
number of variables of type DISCRETE_UNCERTAIN_SET_REAL | |
bool | singleIntervalFlag |
flag for SingleInterval derived class | |
RealVectorArray | ccBelFn |
Storage array to hold CCBF values. | |
RealVectorArray | ccPlausFn |
Storage array to hold CCPF values. | |
RealVectorArray | ccBelVal |
Storage array to hold CCB response values. | |
RealVectorArray | ccPlausVal |
Storage array to hold CCP response values. | |
RealVectorArray | cellContLowerBounds |
Storage array to hold cell lower bounds for continuous variables. | |
RealVectorArray | cellContUpperBounds |
Storage array to hold cell upper bounds for continuous variables. | |
IntVectorArray | cellIntRangeLowerBounds |
Storage array to hold cell lower bounds for discrete int range variables. | |
IntVectorArray | cellIntRangeUpperBounds |
Storage array to hold cell upper bounds for discrete int range variables. | |
IntVectorArray | cellIntSetBounds |
Storage array to hold cell values for discrete integer set variables. | |
IntVectorArray | cellRealSetBounds |
Storage array to hold cell value for discrete real set variables. | |
RealVectorArray | cellFnLowerBounds |
Storage array to hold cell min. | |
RealVectorArray | cellFnUpperBounds |
Storage array to hold cell max. | |
RealVector | cellBPA |
Storage array to hold cell bpa. | |
size_t | respFnCntr |
response function counter | |
size_t | cellCntr |
cell counter | |
size_t | numCells |
total number of interval combinations | |
Protected Attributes inherited from NonD | |
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() | |
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 inherited from NonD | |
static NonD * | nondInstance |
pointer to the active object instance used within static evaluator functions in order to avoid the need for static data | |
Class for the Dempster-Shafer Evidence Theory methods within DAKOTA/UQ.
The NonDEvidence class implements the propagation of epistemic uncertainty using Dempster-Shafer theory of evidence. In this approach, one assigns a set of basic probability assignments (BPA) to intervals defined for the uncertain variables. Input interval combinations are calculated, along with their BPA. Currently, the response function is evaluated at a set of sample points, then a response surface is constructed which is sampled extensively to find the minimum and maximum within each input interval cell, corresponding to the belief and plausibility within that cell, respectively. This data is then aggregated to calculate cumulative distribution functions for belief and plausibility.