Dakota  Version 6.15
Explore and Predict with Confidence
 All Classes Namespaces Files Functions Variables Typedefs Enumerations Enumerator Friends Pages
Public Member Functions | Protected Member Functions | Private Member Functions | Static Private Member Functions | Private Attributes | List of all members
NonDMultilevelSampling Class Reference

Performs Multilevel Monte Carlo sampling for uncertainty quantification. More...

Inheritance diagram for NonDMultilevelSampling:
NonDHierarchSampling NonDEnsembleSampling NonDSampling NonD Analyzer Iterator NonDMultilevControlVarSampling

Public Member Functions

 NonDMultilevelSampling (ProblemDescDB &problem_db, Model &model)
 standard constructor More...
 
 ~NonDMultilevelSampling ()
 destructor
 
- Public Member Functions inherited from NonDHierarchSampling
 NonDHierarchSampling (ProblemDescDB &problem_db, Model &model)
 standard constructor More...
 
virtual ~NonDHierarchSampling ()
 destructor (virtual declaration should be redundant with ~Iterator, but this is top of MLMF diamond so doesn't hurt to be explicit)
 
- Public Member Functions inherited from NonDEnsembleSampling
 NonDEnsembleSampling (ProblemDescDB &problem_db, Model &model)
 standard constructor More...
 
 ~NonDEnsembleSampling ()
 destructor (virtual declaration should be redundant with ~Iterator, but this is top of MLMF diamond so doesn't hurt to be explicit)
 
bool resize ()
 reinitializes iterator based on new variable size
 
- Public Member Functions inherited from NonDSampling
 NonDSampling (Model &model, const RealMatrix &sample_matrix)
 alternate constructor for evaluating and computing statistics for the provided set of samples More...
 
 ~NonDSampling ()
 destructor
 
void compute_statistics (const RealMatrix &vars_samples, const IntResponseMap &resp_samples)
 For the input sample set, computes mean, standard deviation, and probability/reliability/response levels (aleatory uncertainties) or intervals (epsitemic or mixed uncertainties)
 
void compute_intervals (RealRealPairArray &extreme_fns)
 called by compute_statistics() to calculate min/max intervals using allResponses
 
void compute_intervals (const IntResponseMap &samples)
 called by compute_statistics() to calculate extremeValues from samples
 
void compute_intervals (RealRealPairArray &extreme_fns, const IntResponseMap &samples)
 called by compute_statistics() to calculate min/max intervals using samples
 
void compute_moments (const RealVectorArray &fn_samples)
 calculates sample moments from a matrix of observations for a set of QoI
 
void compute_moments (const IntResponseMap &samples)
 calculate sample moments and confidence intervals from a map of response observations
 
void compute_moments (const IntResponseMap &samples, RealMatrix &moment_stats, RealMatrix &moment_grads, RealMatrix &moment_conf_ints, short moments_type, const StringArray &labels)
 convert IntResponseMap to RealVectorArray and invoke helpers
 
void compute_moment_gradients (const RealVectorArray &fn_samples, const RealMatrixArray &grad_samples, const RealMatrix &moment_stats, RealMatrix &moment_grads, short moments_type)
 compute moment_grads from function and gradient samples
 
void compute_moment_confidence_intervals (const RealMatrix &moment_stats, RealMatrix &moment_conf_ints, const SizetArray &sample_counts, short moments_type)
 compute moment confidence intervals from moment values
 
void archive_moments (size_t inc_id=0)
 archive moment statistics in results DB
 
void archive_moment_confidence_intervals (size_t inc_id=0)
 archive moment confidence intervals in results DB
 
void archive_extreme_responses (size_t inc_id=0)
 archive extreme values (epistemic result) in results DB
 
void compute_level_mappings (const IntResponseMap &samples)
 called by compute_statistics() to calculate CDF/CCDF mappings of z to p/beta and of p/beta to z as well as PDFs More...
 
void print_statistics (std::ostream &s) const
 prints the statistics computed in compute_statistics()
 
void print_intervals (std::ostream &s) const
 prints the intervals computed in compute_intervals() with default qoi_type and moment_labels
 
void print_intervals (std::ostream &s, String qoi_type, const StringArray &interval_labels) const
 prints the intervals computed in compute_intervals()
 
void print_moments (std::ostream &s) const
 prints the moments computed in compute_moments() with default qoi_type and moment_labels
 
void print_moments (std::ostream &s, String qoi_type, const StringArray &moment_labels) const
 prints the moments computed in compute_moments()
 
void print_wilks_stastics (std::ostream &s) const
 prints the Wilks stastics
 
void update_final_statistics ()
 update finalStatistics from minValues/maxValues, momentStats, and computedProbLevels/computedRelLevels/computedRespLevels
 
void transform_samples (Pecos::ProbabilityTransformation &nataf, bool x_to_u=true)
 transform allSamples imported by alternate constructor. This is needed since random variable distribution parameters are not updated until run time and an imported sample_matrix is typically in x-space. More...
 
void transform_samples (Pecos::ProbabilityTransformation &nataf, RealMatrix &sample_matrix, int num_samples=0, bool x_to_u=true)
 transform the specified samples matrix from x to u or u to x
 
unsigned short sampling_scheme () const
 return sampleType
 
const String & random_number_generator () const
 return rngName
 
- 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
 
- 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()))
 alternate envelope constructor that assigns a representation pointer 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 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 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 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 variable_bounds (const RealVector &cv_lower_bnds, const RealVector &cv_upper_bnds)
 assign nonlinear inequality and equality constraint allowables for this iterator (user-functions mode for which Model updating is not used)
 
virtual void linear_constraints (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)
 assign linear inequality and linear equality constraints for this iterator (user-functions mode for which Model updating is not used)
 
virtual void nonlinear_constraints (const RealVector &nln_ineq_lb, const RealVector &nln_ineq_ub, const RealVector &nln_eq_tgt)
 assign nonlinear inequality and equality constraint allowables for this iterator (user-functions mode for which Model updating is not used)
 
virtual void initialize_graphics (int iterator_server_id=1)
 initialize the 2D graphics window and the tabular graphics data More...
 
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_increment ()
 increment to next in sequence of refinement samples
 
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 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)
 
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_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 ActiveSetactive_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< 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...
 
std::shared_ptr< TraitsBasetraits () 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 (const bool &tflag)
 Set the iterator's top level flag.
 

Protected Member Functions

void core_run ()
 
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
 
void evaluate_ml_sample_increment (unsigned short step)
 helper that consolidates sequence advancement, sample generation, sample export, and sample evaluation
 
void increment_ml_equivalent_cost (size_t new_N_l, Real lev_cost, Real ref_cost)
 increment the equivalent number of HF evaluations based on new model evaluations
 
void accumulate_ml_Ysums (IntRealMatrixMap &sum_Y, RealMatrix &sum_YY, size_t lev, const RealVector &offset, SizetArray &num_Y)
 update accumulators for multilevel telescoping running sums using set of model evaluations within allResponses
 
void accumulate_ml_Qsums (IntRealMatrixMap &sum_Q, size_t lev, const RealVector &offset, SizetArray &num_Q)
 update running QoI sums for one model (sum_Q) using set of model evaluations within allResponses; used for level 0 from other accumulators
 
Real aggregate_variance_Ysum (const Real *sum_Y, const Real *sum_YY, const SizetArray &N_l)
 sum up variances across QoI (using sum_YY with means from sum_Y)
 
Real aggregate_mse_Yvar (const Real *var_Y, const SizetArray &N_l)
 sum up Monte Carlo estimates for mean squared error (MSE) across QoI using discrepancy variances
 
Real aggregate_mse_Ysum (const Real *sum_Y, const Real *sum_YY, const SizetArray &N_l)
 sum up Monte Carlo estimates for mean squared error (MSE) across QoI using discrepancy sums
 
void configure_indices (unsigned short group, unsigned short form, size_t lev, short seq_type)
 manage response mode and active model key from {group,form,lev} triplet. seq_type defines the active dimension for a 1D model sequence.
 
void configure_indices (size_t group, size_t form, size_t lev, short seq_type)
 convert group and form and call overload
 
Real level_cost (const RealVector &cost, size_t step)
 return (aggregate) level cost
 
- Protected Member Functions inherited from NonDHierarchSampling
void uncorrected_surrogate_mode ()
 synchronize iteratedModel and activeSet on UNCORRECTED_SURROGATE mode
 
- Protected Member Functions inherited from NonDEnsembleSampling
virtual void print_variance_reduction (std::ostream &s)
 
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 print_results (std::ostream &s, short results_state=FINAL_RESULTS)
 print the final iterator results More...
 
void aggregated_models_mode ()
 synchronize iteratedModel and activeSet on AGGREGATED_MODELS mode
 
void bypass_surrogate_mode ()
 synchronize iteratedModel and activeSet on BYPASS_SURROGATE mode
 
void assign_specification_sequence (size_t index)
 advance any sequence specifications
 
int random_seed (size_t index) const
 extract current random seed from randomSeedSeqSpec More...
 
void compute_mc_estimator_variance (const RealVector &var_l, const SizetArray &N_l, RealVector &mc_est_var)
 compute the variance of the mean estimator (Monte Carlo sample average)
 
void project_mc_estimator_variance (const RealVector &var_l, const SizetArray &N_l, size_t new_samp, RealVector &mc_est_var)
 compute the variance of the mean estimator (Monte Carlo sample average) after projection with additional samples (var_l remains fixed)
 
void export_all_samples (String root_prepend, const Model &model, size_t iter, size_t step)
 export allSamples to tagged tabular file
 
void convert_moments (const RealMatrix &raw_mom, RealMatrix &final_mom)
 convert uncentered raw moments (multilevel expectations) to standardized moments
 
Real sum (const Real *vec, size_t vec_len) const
 compute sum of a set of observations
 
Real average (const Real *vec, size_t vec_len) const
 compute average of a set of observations
 
Real average (const RealVector &vec) const
 compute average of a set of observations
 
Real average (const SizetArray &sa) const
 compute average of a set of observations
 
void average (const RealMatrix &mat, size_t avg_index, RealVector &avg_vec) const
 compute row-averages for each column or column-averages for each row
 
- Protected Member Functions inherited from NonDSampling
 NonDSampling (ProblemDescDB &problem_db, Model &model)
 constructor More...
 
 NonDSampling (unsigned short method_name, Model &model, unsigned short sample_type, int samples, int seed, const String &rng, bool vary_pattern, short sampling_vars_mode)
 alternate constructor for sample generation and evaluation "on the fly" More...
 
 NonDSampling (unsigned short sample_type, int samples, int seed, const String &rng, const RealVector &lower_bnds, const RealVector &upper_bnds)
 alternate constructor for sample generation "on the fly" More...
 
 NonDSampling (unsigned short sample_type, int samples, int seed, const String &rng, const RealVector &means, const RealVector &std_devs, const RealVector &lower_bnds, const RealVector &upper_bnds, RealSymMatrix &correl)
 alternate constructor for sample generation of correlated normals "on the fly" More...
 
void pre_run ()
 pre-run portion of run (optional); re-implemented by Iterators which can generate all Variables (parameter sets) a priori More...
 
void core_run ()
 
int num_samples () const
 
void sampling_reset (int min_samples, bool all_data_flag, bool stats_flag)
 resets number of samples and sampling flags More...
 
void sampling_reference (int samples_ref)
 set reference number of samples, which is a lower bound during reset
 
void random_seed (int seed)
 assign randomSeed
 
void vary_pattern (bool pattern_flag)
 set varyPattern
 
void get_parameter_sets (Model &model)
 Uses lhsDriver to generate a set of samples from the distributions/bounds defined in the incoming model. More...
 
void get_parameter_sets (Model &model, const int num_samples, RealMatrix &design_matrix)
 Uses lhsDriver to generate a set of samples from the distributions/bounds defined in the incoming model and populates the specified design matrix. More...
 
void get_parameter_sets (Model &model, const int num_samples, RealMatrix &design_matrix, bool write_msg)
 core of get_parameter_sets that accepts message print control
 
void get_parameter_sets (const RealVector &lower_bnds, const RealVector &upper_bnds)
 Uses lhsDriver to generate a set of uniform samples over lower_bnds/upper_bnds. More...
 
void get_parameter_sets (const RealVector &means, const RealVector &std_devs, const RealVector &lower_bnds, const RealVector &upper_bnds, RealSymMatrix &correl)
 Uses lhsDriver to generate a set of normal samples. More...
 
void update_model_from_sample (Model &model, const Real *sample_vars)
 Override default update of continuous vars only.
 
void sample_to_variables (const Real *sample_vars, Variables &vars)
 override default mapping of continuous variables only
 
void variables_to_sample (const Variables &vars, Real *sample_vars)
 override default mapping of continuous variables only
 
const RealVector & response_error_estimates () const
 return error estimates associated with each of the finalStatistics
 
void initialize_lhs (bool write_message, int num_samples)
 increments numLHSRuns, sets random seed, and initializes lhsDriver
 
void active_set_mapping ()
 in the case of sub-iteration, map from finalStatistics.active_set() requests to activeSet used in evaluate_parameter_sets() More...
 
void mode_counts (const Variables &vars, size_t &cv_start, size_t &num_cv, size_t &div_start, size_t &num_div, size_t &dsv_start, size_t &num_dsv, size_t &drv_start, size_t &num_drv) const
 compute sampled subsets (all, active, uncertain) within all variables (acv/adiv/adrv) from samplingVarsMode and model More...
 
void mode_bits (const Variables &vars, BitArray &active_vars, BitArray &active_corr) const
 define subset views for sampling modes
 
- 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, 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 Responseresponse_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...
 
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 &fixed_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
 
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, const Sizet3DArray &N_l, Sizet2DArray &delta_N_l)
 distribute pilot sample specification across model forms and levels
 
void inflate_final_samples (const Sizet2DArray &N_l_2D, bool multilev, size_t fixed_index, Sizet3DArray &N_l_3D)
 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_samp)
 print evaluation summary for multilevel sampling across 1D profile
 
void print_multilevel_evaluation_summary (std::ostream &s, const Sizet2DArray &N_samp)
 print evaluation summary for multilevel sampling across 2D profile
 
void print_multilevel_evaluation_summary (std::ostream &s, const Sizet3DArray &N_samp, String type="Final")
 print evaluation summary for multilevel sampling across 3D profile
 
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_SQP)
 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 &current, const RealVector &targets, size_t power)
 compute a one-sided sample increment for multilevel methods to move current sampling level to a new target
 
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)
 alternate constructor for instantiations "on the fly" without a Model
 
 ~Analyzer ()
 destructor
 
virtual void update_model_from_variables (Model &model, const Variables &vars)
 update model's current variables with data from vars
 
void update_from_model (const Model &model)
 set inherited data attributes based on extractions from incoming model
 
void pre_output ()
 
const Modelalgorithm_space_model () const
 
const Variablesvariables_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, int num_samples)
 generate replicate parameter sets for use in variance-based decomposition More...
 
void compute_vbd_stats (const int num_samples, const IntResponseMap &resp_samples)
 compute VBD-based Sobol indices More...
 
void archive_sobol_indices () const
 archive VBD-based Sobol indices 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 print_sobol_indices (std::ostream &s) const
 Printing of VBD results. More...
 
void samples_to_variables_array (const RealMatrix &sample_matrix, VariablesArray &vars_array)
 convert samples array to variables array; e.g., allSamples to allVariables
 
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...
 
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...
 

Private Member Functions

void multilevel_mc_Ysum ()
 Perform multilevel Monte Carlo across the discretization levels for a particular model form using discrepancy accumulators (sum_Y) More...
 
void multilevel_mc_Qsum ()
 Perform multilevel Monte Carlo across the discretization levels for a particular model form using QoI accumulators (sum_Q) More...
 
void initialize_ml_Ysums (IntRealMatrixMap &sum_Y, size_t num_lev)
 initialize the ML accumulators for computing means, variances, and covariances across fidelity levels
 
void initialize_ml_Qsums (IntRealMatrixMap &sum_Ql, IntRealMatrixMap &sum_Qlm1, IntIntPairRealMatrixMap &sum_QlQlm1, size_t num_lev)
 initialize the ML accumulators for computing means, variances, and covariances across fidelity levels
 
void accumulate_offsets (RealVector &mu)
 accumulate initial approximation to mean vector, for use as offsets in subsequent accumulations
 
void accumulate_sums (IntRealMatrixMap &sum_Ql, IntRealMatrixMap &sum_Qlm1, IntIntPairRealMatrixMap &sum_QlQlm1, const size_t step, const RealVectorArray &offset, Sizet2DArray &N_l)
 update running QoI sums for one model (sum_Q) using set of model evaluations within allResponses; used for level 0 from other accumulators
 
void accumulate_ml_Qsums (IntRealMatrixMap &sum_Ql, IntRealMatrixMap &sum_Qlm1, IntIntPairRealMatrixMap &sum_QlQlm1, size_t lev, const RealVector &offset, SizetArray &num_Q)
 update running QoI sums for two models (sum_Ql, sum_Qlm1) using set of model evaluations within allResponses
 
void compute_ml_equivalent_cost (const SizetArray &raw_N_l, const RealVector &cost)
 
void compute_error_estimates (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const Sizet2DArray &num_Q)
 populate finalStatErrors for MLMC based on Q sums
 
Real variance_Ysum (Real sum_Y, Real sum_YY, size_t Nlq)
 compute variance from sum accumulators
 
Real variance_Qsum (Real sum_Ql, Real sum_Qlm1, Real sum_QlQl, Real sum_QlQlm1, Real sum_Qlm1Qlm1, size_t Nlq)
 compute variance from sum accumulators
 
Real var_lev_l (Real sum_Ql, Real sum_Qlm1, Real sum_QlQl, Real sum_Qlm1Qlm1, size_t Nlq)
 
void aggregate_variance_target_Qsum (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const Sizet2DArray &N_l, const size_t step, RealMatrix &agg_var_qoi)
 sum up variances for QoI (using sum_YY with means from sum_Y) based on allocation target
 
Real aggregate_variance_mean_Qsum (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const Sizet2DArray &N_l, const size_t step, const size_t qoi)
 wrapper for aggregate_variance_Qsum
 
Real aggregate_variance_Qsum (const Real *sum_Ql, const Real *sum_Qlm1, const Real *sum_QlQl, const Real *sum_QlQlm1, const Real *sum_Qlm1Qlm1, const SizetArray &N_l, const size_t lev)
 sum up variances across QoI (using sum_YY with means from sum_Y)
 
Real aggregate_variance_Qsum (const Real *sum_Ql, const Real *sum_Qlm1, const Real *sum_QlQl, const Real *sum_QlQlm1, const Real *sum_Qlm1Qlm1, const SizetArray &N_l, const size_t lev, const size_t qoi)
 sum up variances for QoI (using sum_YY with means from sum_Y)
 
Real aggregate_variance_variance_Qsum (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const Sizet2DArray &N_l, const size_t step, const size_t qoi)
 wrapper for var_of_var_ml
 
Real aggregate_variance_sigma_Qsum (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const Sizet2DArray &N_l, const size_t step, const size_t qoi)
 wrapper for var_of_sigma_ml
 
Real aggregate_variance_scalarization_Qsum (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const Sizet2DArray &N_l, const size_t step, const size_t qoi)
 wrapper for var_of_scalarization_ml More...
 
void aggregate_mse_target_Qsum (RealMatrix &agg_var_qoi, const Sizet2DArray &N_l, const size_t step, RealVector &estimator_var0_qoi)
 sum up Monte Carlo estimates for mean squared error (MSE) for QoI using discrepancy sums based on allocation target
 
void set_convergence_tol (const RealVector &estimator_var0_qoi, const RealVector &cost, RealVector &eps_sq_div_2_qoi)
 compute epsilon^2/2 term for each qoi based on reference estimator_var0 and relative convergence tolereance
 
void compute_sample_allocation_target (const RealMatrix &agg_var_qoi, const RealVector &cost, const Sizet2DArray &N_l, SizetArray &delta_N_l)
 compute sample allocation delta based on a budget constraint
 
void compute_sample_allocation_target (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const RealVector &eps_sq_div_2, const RealMatrix &agg_var_qoi, const RealVector &cost, const Sizet2DArray &N_l, SizetArray &delta_N_l)
 compute sample allocation delta based on current samples and based on allocation target. Single allocation target for each qoi, aggregated using max operation.
 
void compute_moments (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const Sizet2DArray &N_l)
 
void assign_static_member (const Real &conv_tol, size_t &qoi, const size_t &qoi_aggregation, const size_t &num_functions, const RealVector &level_cost_vec, const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const RealVector &pilot_samples, const RealMatrix &scalarization_response_mapping) const
 
void assign_static_member_problem18 (Real &var_L_exact, Real &var_H_exact, Real &mu_four_L_exact, Real &mu_four_H_exact, Real &Ax, RealVector &level_cost_vec) const
 

Static Private Member Functions

static Real variance_Ysum_static (Real sum_Y, Real sum_YY, size_t Nlq_pilot, size_t Nlq, bool compute_gradient, Real &grad)
 compute variance from sum accumulators, necessary for sample allocation optimization
 
static Real variance_Qsum_static (Real sum_Ql, Real sum_Qlm1, Real sum_QlQl, Real sum_QlQlm1, Real sum_Qlm1Qlm1, size_t Nlq_pilot, size_t Nlq, bool compute_gradient, Real &grad)
 compute variance from sum accumulators, necessary for sample allocation optimization
 
static Real var_lev_l_static (Real sum_Ql, Real sum_Qlm1, Real sum_QlQl, Real sum_Qlm1Qlm1, size_t Nlq_pilot, size_t Nlq, bool compute_gradient, Real &grad)
 
static Real unbiased_mean_product_pair (const Real sumQ1, const Real sumQ2, const Real sumQ1Q2, const size_t Nlq)
 compute the unbiased product of two sampling means
 
static Real unbiased_mean_product_triplet (const Real sumQ1, const Real sumQ2, const Real sumQ3, const Real sumQ1Q2, const Real sumQ1Q3, const Real sumQ2Q3, const Real sumQ1Q2Q3, const size_t Nlq)
 compute the unbiased product of three sampling means
 
static Real unbiased_mean_product_pairpair (const Real sumQ1, const Real sumQ2, const Real sumQ1Q2, const Real sumQ1sq, const Real sumQ2sq, const Real sumQ1sqQ2, const Real sumQ1Q2sq, const Real sumQ1sqQ2sq, const size_t Nlq)
 compute the unbiased product of two pairs of products of sampling means
 
static Real var_of_var_ml_l0 (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const size_t Nlq_pilot, const Real Nlq, const size_t qoi, const bool compute_gradient, Real &grad_g)
 
static Real var_of_var_ml_lmax (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const size_t Nlq_pilot, const Real Nlq, const size_t qoi, const bool compute_gradient, Real &grad_g)
 
static Real var_of_var_ml_l (const IntRealMatrixMap &sum_Ql, const IntRealMatrixMap &sum_Qlm1, const IntIntPairRealMatrixMap &sum_QlQlm1, const size_t Nlq_pilot, const Real Nlq, const size_t qoi, const size_t lev, const bool compute_gradient, Real &grad_g)
 
static void target_cost_objective_eval_optpp (int mode, int n, const RealVector &x, double &f, RealVector &grad_f, int &result_mode)
 OPTPP definition.
 
static void target_cost_constraint_eval_optpp (int mode, int n, const RealVector &x, RealVector &g, RealMatrix &grad_g, int &result_mode)
 
static void target_var_constraint_eval_optpp (int mode, int n, const RealVector &x, RealVector &g, RealMatrix &grad_g, int &result_mode)
 
static void target_var_constraint_eval_logscale_optpp (int mode, int n, const RealVector &x, RealVector &g, RealMatrix &grad_g, int &result_mode)
 
static void target_sigma_constraint_eval_optpp (int mode, int n, const RealVector &x, RealVector &g, RealMatrix &grad_g, int &result_mode)
 
static void target_sigma_constraint_eval_logscale_optpp (int mode, int n, const RealVector &x, RealVector &g, RealMatrix &grad_g, int &result_mode)
 
static void target_scalarization_constraint_eval_optpp (int mode, int n, const RealVector &x, RealVector &g, RealMatrix &grad_g, int &result_mode)
 
static void target_scalarization_constraint_eval_logscale_optpp (int mode, int n, const RealVector &x, RealVector &g, RealMatrix &grad_g, int &result_mode)
 
static void target_var_objective_eval_optpp (int mode, int n, const RealVector &x, double &f, RealVector &grad_f, int &result_mode)
 
static void target_var_objective_eval_logscale_optpp (int mode, int n, const RealVector &x, double &f, RealVector &grad_f, int &result_mode)
 
static void target_sigma_objective_eval_optpp (int mode, int n, const RealVector &x, double &f, RealVector &grad_f, int &result_mode)
 
static void target_sigma_objective_eval_logscale_optpp (int mode, int n, const RealVector &x, double &f, RealVector &grad_f, int &result_mode)
 
static void target_scalarization_objective_eval_optpp (int mode, int n, const RealVector &x, double &f, RealVector &grad_f, int &result_mode)
 
static void target_scalarization_objective_eval_logscale_optpp (int mode, int n, const RealVector &x, double &f, RealVector &grad_f, int &result_mode)
 
static void target_cost_objective_eval_npsol (int &mode, int &n, double *x, double &f, double *gradf, int &nstate)
 NPSOL definition (Wrapper using OPTPP implementation above under the hood)
 
static void target_cost_constraint_eval_npsol (int &mode, int &m, int &n, int &ldJ, int *needc, double *x, double *g, double *grad_g, int &nstate)
 
static void target_var_constraint_eval_npsol (int &mode, int &m, int &n, int &ldJ, int *needc, double *x, double *g, double *grad_g, int &nstate)
 
static void target_var_constraint_eval_logscale_npsol (int &mode, int &m, int &n, int &ldJ, int *needc, double *x, double *g, double *grad_g, int &nstate)
 
static void target_sigma_constraint_eval_npsol (int &mode, int &m, int &n, int &ldJ, int *needc, double *x, double *g, double *grad_g, int &nstate)
 
static void target_sigma_constraint_eval_logscale_npsol (int &mode, int &m, int &n, int &ldJ, int *needc, double *x, double *g, double *grad_g, int &nstate)
 
static void target_scalarization_constraint_eval_npsol (int &mode, int &m, int &n, int &ldJ, int *needc, double *x, double *g, double *grad_g, int &nstate)
 
static void target_scalarization_constraint_eval_logscale_npsol (int &mode, int &m, int &n, int &ldJ, int *needc, double *x, double *g, double *grad_g, int &nstate)
 
static void target_var_objective_eval_npsol (int &mode, int &n, double *x, double &f, double *gradf, int &nstate)
 
static void target_var_objective_eval_logscale_npsol (int &mode, int &n, double *x, double &f, double *gradf, int &nstate)
 
static void target_sigma_objective_eval_npsol (int &mode, int &n, double *x, double &f, double *gradf, int &nstate)
 
static void target_sigma_objective_eval_logscale_npsol (int &mode, int &n, double *x, double &f, double *gradf, int &nstate)
 
static void target_scalarization_objective_eval_npsol (int &mode, int &n, double *x, double &f, double *gradf, int &nstate)
 
static void target_scalarization_objective_eval_logscale_npsol (int &mode, int &n, double *x, double &f, double *gradf, int &nstate)
 
static void target_var_constraint_eval_optpp_problem18 (int mode, int n, const RealVector &x, RealVector &g, RealMatrix &grad_g, int &result_mode)
 
static void target_sigma_constraint_eval_optpp_problem18 (int mode, int n, const RealVector &x, RealVector &g, RealMatrix &grad_g, int &result_mode)
 
static double exact_var_of_var_problem18 (const RealVector &Nl)
 
static double exact_var_of_sigma_problem18 (const RealVector &Nl)
 

Private Attributes

unsigned short seq_index
 
short allocationTarget
 store the allocation_target input specification, prior to run-time Options right now: More...
 
bool useTargetVarianceOptimizationFlag
 option to switch on numerical optimization for solution of sample alloation of allocationTarget Variance
 
short qoiAggregation
 store the qoi_aggregation_norm input specification, prior to run-time Options right now: More...
 
short convergenceTolType
 
     store the convergence_tolerance_type input specification, prior to run-time

Options right now: More...

 
short convergenceTolTarget
 store the convergence_tolerance_target input specification, prior to run-time Options right now: More...
 
RealVector convergenceTolVec
 
RealMatrix scalarizationCoeffs
 "scalarization" response_mapping matrix applied to the mlmc sample allocation when a scalarization, i.e. alpha_1 * mean + alpha_2 * sigma, is the target.
 
RealMatrix NTargetQoi
 Helper data structure to store intermedia sample allocations.
 
RealMatrix NTargetQoiFN
 

Additional Inherited Members

- Static Public Member Functions inherited from NonDSampling
static void compute_moments (const RealVectorArray &fn_samples, SizetArray &sample_counts, RealMatrix &moment_stats, short moments_type, const StringArray &labels)
 core compute_moments() implementation with all data as inputs
 
static void compute_moments (const RealVectorArray &fn_samples, RealMatrix &moment_stats, short moments_type)
 core compute_moments() implementation with all data as inputs
 
static void compute_moments (const RealMatrix &fn_samples, RealMatrix &moment_stats, short moments_type)
 alternate RealMatrix samples API for use by external clients
 
static void print_moments (std::ostream &s, const RealMatrix &moment_stats, const RealMatrix moment_cis, String qoi_type, short moments_type, const StringArray &moment_labels, bool print_cis)
 core print moments that can be called without object
 
static int compute_wilks_sample_size (unsigned short order, Real alpha, Real beta, bool twosided=false)
 calculates the number of samples using the Wilks formula Static so I can test without instantiating a NonDSampling object - RWH
 
static Real compute_wilks_residual (unsigned short order, int nsamples, Real alpha, Real beta, bool twosided)
 Helper function - calculates the Wilks residual.
 
static Real compute_wilks_alpha (unsigned short order, int nsamples, Real beta, bool twosided=false)
 calculates the alpha paramter given number of samples using the Wilks formula Static so I can test without instantiating a NonDSampling object - RWH
 
static Real compute_wilks_beta (unsigned short order, int nsamples, Real alpha, bool twosided=false)
 calculates the beta paramter given number of samples using the Wilks formula Static so I can test without instantiating a NonDSampling object - RWH
 
static Real get_wilks_alpha_min ()
 Get the lower and upper bounds supported by Wilks bisection solves.
 
static Real get_wilks_alpha_max ()
 
static Real get_wilks_beta_min ()
 
static Real get_wilks_beta_max ()
 
- Static Protected Member Functions inherited from NonDEnsembleSampling
static void uncentered_to_centered (Real rm1, Real rm2, Real rm3, Real rm4, Real &cm1, Real &cm2, Real &cm3, Real &cm4, size_t Nlq)
 convert uncentered (raw) moments to centered moments; biased estimators More...
 
static void uncentered_to_centered (Real rm1, Real rm2, Real rm3, Real rm4, Real &cm1, Real &cm2, Real &cm3, Real &cm4)
 convert uncentered (raw) moments to centered moments; unbiased estimators More...
 
static void centered_to_standard (Real cm1, Real cm2, Real cm3, Real cm4, Real &sm1, Real &sm2, Real &sm3, Real &sm4)
 convert centered moments to standardized moments
 
static void check_negative (Real &cm)
 detect, warn, and repair a negative central moment (for even orders)
 
- Protected Attributes inherited from NonDEnsembleSampling
Sizet3DArray NLev
 total number of successful sample evaluations (excluding faults) for each model form, discretization level, and QoI
 
SizetArray pilotSamples
 store the pilot_samples input specification, prior to run-time invocation of load_pilot_sample()
 
SizetArray randomSeedSeqSpec
 user specification for seed_sequence
 
size_t mlmfIter
 major iteration counter
 
Real equivHFEvals
 equivalent number of high fidelity evaluations accumulated using samples across multiple model forms and/or discretization levels
 
bool exportSampleSets
 if defined, export each of the sample increments in ML, CV, MLCV using tagged tabular files
 
unsigned short exportSamplesFormat
 format for exporting sample increments using tagged tabular files
 
- 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

Performs Multilevel Monte Carlo sampling for uncertainty quantification.

Multilevel Monte Carlo (MLMC) is a variance-reduction technique that utilitizes lower fidelity simulations that have response QoI that are correlated with the high-fidelity response QoI.

Constructor & Destructor Documentation

NonDMultilevelSampling ( ProblemDescDB problem_db,
Model model 
)

standard constructor

This constructor is called for a standard letter-envelope iterator instantiation. In this case, set_db_list_nodes has been called and probDescDB can be queried for settings from the method specification.

References Dakota::abort_handler(), NonDMultilevelSampling::allocationTarget, ProblemDescDB::get_rv(), Analyzer::numFunctions, Iterator::probDescDB, NonDMultilevelSampling::qoiAggregation, and NonDMultilevelSampling::scalarizationCoeffs.

Member Function Documentation

void core_run ( )
protectedvirtual

The primary run function manages the general case: a hierarchy of model forms (from the ordered model fidelities within a HierarchSurrModel), each of which may contain multiple discretization levels.

Reimplemented from Iterator.

References Iterator::iteratedModel, Model::multifidelity_precedence(), NonDMultilevelSampling::multilevel_mc_Qsum(), and NonDMultilevelSampling::multilevel_mc_Ysum().

Referenced by NonDMultilevControlVarSampling::core_run().

void multilevel_mc_Ysum ( )
private
void multilevel_mc_Qsum ( )
private
Real aggregate_variance_scalarization_Qsum ( const IntRealMatrixMap &  sum_Ql,
const IntRealMatrixMap &  sum_Qlm1,
const IntIntPairRealMatrixMap &  sum_QlQlm1,
const Sizet2DArray &  N_l,
const size_t  step,
const size_t  qoi 
)
private

wrapper for var_of_scalarization_ml

For TARGET_SCALARIZATION we have the special case that we can also combine scalarization over multiple qoi This is respresented in the scalarization response mapping stored in scalarizationCoeffs This is for now neglecting cross terms for covariance terms inbetween different qois, e.g. V[mu_1 + 2 sigma_1 + 3 mu_2] = V[mu_1] + V[2 sigma_1] + 2 Cov[mu_1, 2 sigma_1] + V[3 mu_2] + 2 Cov[2 mu_1, 3 mu_2] + 2 Cov[2 sigma_1, 3 mu_2] V[mu_1] + V[2 sigma_1] + 2 Cov[mu_1, 2 sigma_1] + V[3 mu_2] (What we do)

References NonDMultilevelSampling::aggregate_variance_mean_Qsum(), NonDMultilevelSampling::aggregate_variance_sigma_Qsum(), Analyzer::numFunctions, and NonDMultilevelSampling::scalarizationCoeffs.

Referenced by NonDMultilevelSampling::aggregate_variance_target_Qsum().

Member Data Documentation

short allocationTarget
private

store the allocation_target input specification, prior to run-time Options right now:

  • Mean = First moment (Mean)
  • Variance = Second moment (Variance or standard deviation depending on moments central or standard)

Referenced by NonDMultilevelSampling::aggregate_variance_target_Qsum(), NonDMultilevelSampling::compute_sample_allocation_target(), NonDMultilevelSampling::multilevel_mc_Qsum(), NonDMultilevelSampling::nested_response_mappings(), and NonDMultilevelSampling::NonDMultilevelSampling().

short qoiAggregation
private

store the qoi_aggregation_norm input specification, prior to run-time Options right now:

  • sum = aggregate the variance over all QoIs, compute samples from that
  • max = take maximum sample allocation over QoIs for each level

Referenced by NonDMultilevelSampling::compute_sample_allocation_target(), and NonDMultilevelSampling::NonDMultilevelSampling().

short convergenceTolType
private

     store the convergence_tolerance_type input specification, prior to run-time

Options right now:

  • relative = computes reference tolerance in first iteration and sets convergence_tolerance as reference tolerance * convergence_tol
  • absolute = sets convergence tolerance from input

Referenced by NonDMultilevelSampling::set_convergence_tol().

short convergenceTolTarget
private

store the convergence_tolerance_target input specification, prior to run-time Options right now:

  • variance_constraint = minimizes cost for equality constraint on variance of estimator (rhs of constraint from convergenceTol)
  • cost_constraint = minizes variance of estimator for equality constraint on cost (rhs of constraint from convergenceTol)

Referenced by NonDMultilevelSampling::compute_sample_allocation_target(), and NonDMultilevelSampling::set_convergence_tol().


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