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Dakota
Version 6.13
Explore and Predict with Confidence
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Class for the Gaussian Process-based Importance Sampling method. More...
Public Member Functions | |
NonDGPImpSampling (ProblemDescDB &problem_db, Model &model) | |
standard constructor More... | |
~NonDGPImpSampling () | |
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 () |
perform the GP importance sampling and return probability of failure More... | |
void | print_results (std::ostream &s, short results_state=FINAL_RESULTS) |
print the final statistics | |
Real | final_probability () |
returns the probability calculated by the importance sampling | |
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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 | |
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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 | |
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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 | |
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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 | 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_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 | 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) | |
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 | |
int | maximum_iterations () const |
return the maximum iterations for this iterator | |
void | maximum_iterations (int 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 (const bool &tflag) |
Set the iterator's top level flag. | |
Private Member Functions | |
RealVector | calcExpIndicator (const int respFnCount, const Real respThresh) |
function to calculate the expected indicator probabilities | |
Real | calcExpIndPoint (const int respFnCount, const Real respThresh, const RealVector this_mean, const RealVector this_var) |
function to calculate the expected indicator probabilities for one point | |
void | calcRhoDraw () |
function to update the rhoDraw data, adding x values and rho draw values | |
RealVector | drawNewX (int this_k) |
function to pick the next X value to be evaluated by the Iterated model | |
Private Attributes | |
Iterator | gpBuild |
LHS iterator for building the initial GP. | |
Iterator | gpEval |
LHS iterator for sampling on the GP. | |
Model | gpModel |
GP model of response, one approximation per response function. | |
Iterator | sampleRhoOne |
LHS iterator for sampling from the rhoOneDistribution. | |
int | numPtsAdd |
the number of points added to the original set of LHS samples | |
int | numPtsTotal |
the total number of points | |
int | numEmulEval |
the number of points evaluated by the GP each iteration | |
Real | finalProb |
the final calculated probability (p) | |
RealVectorArray | gpCvars |
Vector to hold the current values of the current sample inputs on the GP. | |
RealVectorArray | gpMeans |
Vector to hold the current values of the current mean estimates for the sample values on the GP. | |
RealVectorArray | gpVar |
Vector to hold the current values of the current variance estimates for the sample values on the GP. | |
RealVector | expIndicator |
Vector to hold the expected indicator values for the current GP samples. | |
RealVector | rhoDraw |
Vector to hold the rhoDraw values for the current GP samples. | |
RealVector | normConst |
Vector to hold the normalization constant calculated for each point added. | |
RealVector | indicator |
IntVector to hold indicator for actual simulation values vs. threshold. | |
RealVectorArray | xDrawThis |
xDrawThis, appended to locally to hold the X values of emulator points chosen | |
RealVector | expIndThis |
expIndThis, appended locally to hold the expected indicator | |
RealVector | rhoDrawThis |
rhoDrawThis, appended locally to hold the rhoDraw density for calculating draws | |
RealVector | rhoMix |
rhoMix, mixture density | |
RealVector | rhoOne |
rhoOne, original importance density | |
Additional Inherited Members | |
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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 () |
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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 | |
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static void | accumulate_mean (const RealVectorArray &fn_samples, size_t q, size_t &num_samp, Real &mean) |
helper to accumulate sum of finite samples | |
static void | accumulate_moments (const RealVectorArray &fn_samples, size_t q, short moments_type, Real *moments) |
helper to accumulate higher order sums of finite samples | |
static void | accumulate_moment_gradients (const RealVectorArray &fn_samples, const RealMatrixArray &grad_samples, size_t q, short moments_type, Real mean, Real mom2, Real *mean_grad, Real *mom2_grad) |
helper to accumulate gradient sums | |
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int | seedSpec |
the user seed specification (default is 0) | |
int | randomSeed |
the current seed | |
const int | samplesSpec |
initial specification of number of samples | |
int | samplesRef |
reference number of samples updated for refinement | |
int | numSamples |
the current number of samples to evaluate | |
String | rngName |
name of the random number generator | |
unsigned short | sampleType |
the sample type: default, random, lhs, < incremental random, or incremental lhs | |
bool | wilksFlag |
flags use of Wilks formula to calculate num samples | |
unsigned short | wilksOrder |
Real | wilksAlpha |
Real | wilksBeta |
short | wilksSidedness |
RealMatrix | momentGrads |
gradients of standardized or central moments of response functions, as determined by finalMomentsType. Calculated in compute_moments() and indexed as (var,moment) when moment id runs from 1:2*numFunctions. | |
RealVector | finalStatErrors |
standard errors (estimator std deviation) for each of the finalStatistics | |
int | samplesIncrement |
current increment in a sequence of samples | |
Pecos::LHSDriver | lhsDriver |
the C++ wrapper for the F90 LHS library | |
bool | statsFlag |
flags computation/output of statistics | |
bool | allDataFlag |
flags update of allResponses < (allVariables or allSamples already defined) | |
short | samplingVarsMode |
the sampling mode: ALEATORY_UNCERTAIN{,_UNIFORM}, EPISTEMIC_UNCERTAIN{,_UNIFORM}, UNCERTAIN{,_UNIFORM}, ACTIVE{,_UNIFORM}, or ALL{,_UNIFORM}. This is a secondary control on top of the variables view that allows sampling over subsets of variables that may differ from the view. | |
short | sampleRanksMode |
mode for input/output of LHS sample ranks: IGNORE_RANKS, GET_RANKS, SET_RANKS, or SET_GET_RANKS | |
bool | varyPattern |
flag for generating a sequence of seed values within multiple get_parameter_sets() calls so that these executions (e.g., for SBO/SBNLS) are not repeated, but are still repeatable | |
RealMatrix | sampleRanks |
data structure to hold the sample ranks | |
SensAnalysisGlobal | nonDSampCorr |
initialize statistical post processing | |
bool | backfillFlag |
flags whether to use backfill to enforce uniqueness of discrete LHS samples | |
RealRealPairArray | extremeValues |
Minimum and maximum values of response functions for epistemic calculations (calculated in compute_intervals()),. | |
bool | functionMomentsComputed |
Function moments have been computed; used to determine whether to archive the moments. | |
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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 Gaussian Process-based Importance Sampling method.
The NonDGPImpSampling implements a method developed by Keith Dalbey that uses a Gaussian process surrogate in the calculation of the importance density. Specifically, the mean and variance of the GP prediction are used to calculate an expected value that a particular point fails, and that is used as part of the computation of the "draw distribution." The normalization constants and the mixture distribution used are defined in (need to get SAND report).
NonDGPImpSampling | ( | 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 Response::active_set(), Iterator::assign_rep(), Model::assign_rep(), NonD::construct_lhs(), Model::current_response(), ProblemDescDB::get_bool(), ProblemDescDB::get_int(), ProblemDescDB::get_string(), ProblemDescDB::get_ushort(), NonDGPImpSampling::gpBuild, NonDGPImpSampling::gpEval, NonDGPImpSampling::gpModel, Model::gradient_type(), Model::hessian_type(), Iterator::iteratedModel, Iterator::maxIterations, NonDGPImpSampling::numEmulEval, NonDGPImpSampling::numPtsAdd, NonDSampling::numSamples, Iterator::outputLevel, Iterator::probDescDB, NonDSampling::randomSeed, ActiveSet::request_values(), NonDSampling::rngName, NonDGPImpSampling::sampleRhoOne, NonDSampling::sampleType, NonDSampling::samplingVarsMode, NonDSampling::statsFlag, NonDSampling::vary_pattern(), and NonDSampling::varyPattern.
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virtual |
perform the GP importance sampling and return probability of failure
Calculate the failure probabilities for specified probability levels using Gaussian process based importance sampling.
Reimplemented from Iterator.
References Model::acv(), Iterator::all_responses(), Analyzer::all_samples(), Iterator::all_samples(), Model::append_approximation(), Model::approximation_data(), Model::approximation_variances(), Model::build_approximation(), NonDGPImpSampling::calcExpIndicator(), NonDGPImpSampling::calcExpIndPoint(), NonDGPImpSampling::calcRhoDraw(), NonD::cdfFlag, NonD::computedProbLevels, Model::continuous_lower_bounds(), Model::continuous_upper_bounds(), Model::continuous_variables(), Model::current_response(), Model::current_variables(), NonDGPImpSampling::drawNewX(), Model::evaluate(), Model::evaluation_id(), NonDGPImpSampling::expIndicator, NonDGPImpSampling::expIndThis, NonDGPImpSampling::finalProb, Response::function_values(), NonDGPImpSampling::gpCvars, NonDGPImpSampling::gpEval, NonDGPImpSampling::gpMeans, NonDGPImpSampling::gpModel, NonDGPImpSampling::gpVar, NonDGPImpSampling::indicator, NonD::initialize_level_mappings(), Iterator::iteratedModel, Iterator::methodPCIter, NonD::miPLIndex, NonDGPImpSampling::normConst, NonDGPImpSampling::numEmulEval, Analyzer::numFunctions, NonDGPImpSampling::numPtsAdd, NonDGPImpSampling::numPtsTotal, NonDSampling::numSamples, Iterator::outputLevel, Model::pop_approximation(), NonD::requestedRespLevels, NonDGPImpSampling::rhoDraw, NonDGPImpSampling::rhoDrawThis, NonDGPImpSampling::rhoMix, NonDGPImpSampling::rhoOne, Iterator::run(), NonDGPImpSampling::sampleRhoOne, and NonDGPImpSampling::xDrawThis.