Dakota  Version 6.4
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Pages
Public Member Functions | Private Member Functions | Static Private Member Functions | Private Attributes | Static Private Attributes | List of all members
NonDGlobalReliability Class Reference

Class for global reliability methods within DAKOTA/UQ. More...

Inheritance diagram for NonDGlobalReliability:
NonDReliability NonD Analyzer Iterator

Public Member Functions

 NonDGlobalReliability (ProblemDescDB &problem_db, Model &model)
 constructor
 
 ~NonDGlobalReliability ()
 destructor
 
bool resize ()
 reinitializes iterator based on new variable size
 
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 ()
 core portion of run; implemented by all derived classes and may include pre/post steps in lieu of separate pre/post More...
 
void print_results (std::ostream &s)
 print the final iterator results More...
 
- Public Member Functions inherited from NonDReliability
bool resize ()
 reinitializes iterator based on new variable size
 
- Public Member Functions inherited from NonD
void initialize_random_variables (short u_space_type)
 initialize natafTransform based on distribution data from iteratedModel More...
 
void initialize_random_variables (const Pecos::ProbabilityTransformation &transform, bool deep_copy=false)
 alternate form: initialize natafTransform based on incoming data More...
 
void initialize_random_variable_transformation ()
 instantiate natafTransform
 
void initialize_random_variable_types ()
 initializes ranVarTypesX within natafTransform (u-space not needed) More...
 
void initialize_random_variable_types (short u_space_type)
 initializes ranVarTypesX and ranVarTypesU within natafTransform More...
 
void initialize_random_variable_parameters ()
 initializes ranVarMeansX, ranVarStdDevsX, ranVarLowerBndsX, ranVarUpperBndsX, and ranVarAddtlParamsX within natafTransform More...
 
void initialize_random_variable_correlations ()
 propagate iteratedModel correlations to natafTransform
 
void verify_correlation_support (short u_space_type)
 verify that correlation warping is supported by Nataf for given variable types
 
void transform_correlations ()
 perform correlation warping for variable types supported by Nataf
 
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 distribution_parameter_derivatives (bool dist_param_derivs)
 set distParamDerivs
 
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...
 
bool pdf_output () const
 get pdfOutput
 
void pdf_output (bool output)
 set pdfOutput
 
Pecos::ProbabilityTransformation & variable_transformation ()
 return natafTransform
 
- 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
 
int 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 ()
 default constructor More...
 
 Iterator (ProblemDescDB &problem_db)
 standard envelope constructor, which constructs its own model(s) More...
 
 Iterator (ProblemDescDB &problem_db, Model &model)
 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)
 alternate envelope constructor for instantiations by name without the ProblemDescDB More...
 
 Iterator (const Iterator &iterator)
 copy constructor More...
 
virtual ~Iterator ()
 destructor More...
 
Iterator operator= (const Iterator &iterator)
 assignment operator 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 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)
 used by IteratorScheduler to unpack starting data for an iterator run
 
virtual void unpack_parameters_initialize (MPIUnpackBuffer &recv_buffer)
 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 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_points (const VariablesArray &pts)
 sets the multiple initial points for this iterator. This should only be used if accepts_multiple_points() returns true.
 
virtual unsigned short uses_method () const
 return name of any enabling iterator used by this iterator More...
 
virtual void method_recourse ()
 perform a method switch, if possible, due to a detected conflict
 
virtual void sampling_reset (int min_samples, bool all_data_flag, bool stats_flag)
 reset sampling iterator to use at least min_samples
 
virtual void sampling_reference (int 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 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
 
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 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 (Iterator *iterator_rep, bool ref_count_incr=true)
 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)
 
Modeliterated_model ()
 return the iteratedModel (iterators & meta-iterators using a single model instance)
 
ProblemDescDBproblem_description_db () const
 return the problem description database (probDescDB)
 
ParallelLibraryparallel_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_name) const
 convert a method name enumeration value to a string
 
unsigned short method_string_to_enum (const String &method_name) const
 convert a method name string to an enumeration value
 
String submethod_enum_to_string (unsigned short submethod_name) const
 convert a 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
 
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 vector (for use with iterators that employ evaluate_parameter_sets())
 
const ActiveSetactive_set () const
 return the default active set vector (used by iterators that employ evaluate_parameter_sets())
 
void sub_iterator_flag (bool si_flag)
 set subIteratorFlag (and update summaryOutputFlag if needed)
 
void active_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
 
bool is_null () const
 function to check iteratorRep (does this envelope contain a letter?)
 
Iteratoriterator_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...
 

Private Member Functions

void optimize_gaussian_process ()
 construct the GP using EGO/SKO
 
void importance_sampling ()
 perform multimodal adaptive importance sampling on the GP
 
void get_best_sample ()
 determine current best solution from among sample data for expected imporovement function in Performance Measure Approach (PMA)
 
Real constraint_penalty (const Real &constraint, const RealVector &c_variables)
 calculate the penalty to be applied to the PMA constraint value
 
Real expected_improvement (const RealVector &expected_values, const Variables &recast_vars)
 expected improvement function for the GP
 
Real expected_feasibility (const RealVector &expected_values, const Variables &recast_vars)
 expected feasibility function for the GP
 

Static Private Member Functions

static void EIF_objective_eval (const Variables &sub_model_vars, const Variables &recast_vars, const Response &sub_model_response, Response &recast_response)
 static function used as the objective function in the Expected Improvement (EIF) problem formulation for PMA
 
static void EFF_objective_eval (const Variables &sub_model_vars, const Variables &recast_vars, const Response &sub_model_response, Response &recast_response)
 static function used as the objective function in the Expected Feasibility (EFF) problem formulation for RIA
 

Private Attributes

Real fnStar
 minimum penalized response from among true function evaluations
 
short meritFunctionType
 type of merit function used to penalize sample data
 
Real lagrangeMult
 Lagrange multiplier for standard Lagrangian merit function.
 
Real augLagrangeMult
 Lagrange multiplier for augmented Lagrangian merit function.
 
Real penaltyParameter
 penalty parameter for augmented Lagrangian merit funciton
 
Real lastConstraintViolation
 constraint violation at last iteration, used to determine if the current iterate should be accepted (must reduce violation)
 
bool lastIterateAccepted
 flag to determine if last iterate was accepted this controls update of parameters for augmented Lagrangian merit fn
 
short dataOrder
 order of the data used for surrogate construction, in ActiveSet request vector 3-bit format; user may override responses spec
 

Static Private Attributes

static NonDGlobalReliabilitynondGlobRelInstance
 pointer to the active object instance used within the static evaluator functions in order to avoid the need for static data
 

Additional Inherited Members

- Protected Member Functions inherited from NonDReliability
 NonDReliability (ProblemDescDB &problem_db, Model &model)
 constructor
 
 ~NonDReliability ()
 destructor
 
void initialize_graphics (int iterator_server_id=1)
 initialize graphics customized for reliability methods
 
const Modelalgorithm_space_model () const
 
- Static Protected Member Functions inherited from NonD
static void vars_u_to_x_mapping (const Variables &u_vars, Variables &x_vars)
 static function for RecastModels used for forward mapping of u-space variables from NonD Iterators to x-space variables for Model evaluations More...
 
static void vars_x_to_u_mapping (const Variables &x_vars, Variables &u_vars)
 static function for RecastModels used for inverse mapping of x-space variables from data import to u-space variables for NonD Iterators More...
 
static void set_u_to_x_mapping (const Variables &u_vars, const ActiveSet &u_set, ActiveSet &x_set)
 static function for RecastModels used to map u-space ActiveSets from NonD Iterators to x-space ActiveSets for Model evaluations More...
 
static void resp_x_to_u_mapping (const Variables &x_vars, const Variables &u_vars, const Response &x_response, Response &u_response)
 static function for RecastModels used to map x-space responses from Model evaluations to u-space responses for return to NonD Iterator.
 
- Protected Attributes inherited from NonDReliability
Model uSpaceModel
 Model representing the limit state in u-space, after any recastings and data fits.
 
Model mppModel
 RecastModel which formulates the optimization subproblem: RIA, PMA, EGO.
 
Iterator mppOptimizer
 Iterator which optimizes the mppModel.
 
unsigned short mppSearchType
 the MPP search type selection: MV, x/u-space AMV, x/u-space AMV+, x/u-space TANA, x/u-space EGO, or NO_APPROX
 
Iterator importanceSampler
 importance sampling instance used to compute/refine probabilities
 
unsigned short integrationRefinement
 integration refinement type (NO_INT_REFINE, IS, AIS, or MMAIS) provided by refinement specification
 
size_t numRelAnalyses
 number of invocations of core_run()
 
size_t approxIters
 number of approximation cycles for the current respFnCount/levelCount
 
bool approxConverged
 indicates convergence of approximation-based iterations
 
int respFnCount
 counter for which response function is being analyzed
 
size_t levelCount
 counter for which response/probability level is being analyzed
 
size_t statCount
 counter for which final statistic is being computed
 
bool pmaMaximizeG
 flag indicating maximization of G(u) within PMA formulation
 
Real requestedTargetLevel
 the {response,reliability,generalized reliability} level target for the current response function
 
- Static Protected Attributes inherited from NonD
static NonDnondInstance
 pointer to the active object instance used within static evaluator functions in order to avoid the need for static data
 

Detailed Description

Class for global reliability methods within DAKOTA/UQ.

The NonDGlobalReliability class implements EGO/SKO for global MPP search, which maximizes an expected improvement function derived from Gaussian process models. Once the limit state has been characterized, a multimodal importance sampling approach is used to compute probabilities.

Member Function Documentation

void core_run ( )
virtual

core portion of run; implemented by all derived classes and may include pre/post steps in lieu of separate pre/post

Virtual run function for the iterator class hierarchy. All derived classes need to redefine it.

Reimplemented from Iterator.

References NonDGlobalReliability::importance_sampling(), NonD::initialize_random_variable_parameters(), NonDGlobalReliability::nondGlobRelInstance, NonDReliability::numRelAnalyses, NonDGlobalReliability::optimize_gaussian_process(), and NonD::transform_correlations().

void print_results ( std::ostream &  s)
virtual

print the final iterator results

This virtual function provides additional iterator-specific final results outputs beyond the function evaluation summary printed in finalize_run().

Reimplemented from Analyzer.

References NonD::cdfFlag, NonD::computedGenRelLevels, NonD::computedProbLevels, NonD::computedRespLevels, Iterator::iteratedModel, Analyzer::numFunctions, NonD::print_densities(), Model::response_labels(), and Dakota::write_precision.


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