Dakota
Version 6.19
Explore and Predict with Confidence
|
Body class for method specification data. More...
Public Member Functions | |
~DataMethodRep () | |
destructor | |
Public Attributes | |
String | idMethod |
string identifier for the method specification data set (from the id_method specification in MethodIndControl) | |
String | modelPointer |
string pointer to the model specification to be used by this method (from the model_pointer specification in MethodIndControl) | |
String | lowFidModelPointer |
string to point to the low fidelity model for Bayesian experimental design | |
short | methodOutput |
method verbosity control: {SILENT,QUIET,NORMAL,VERBOSE,DEBUG}_OUTPUT (from the output specification in MethodIndControl) | |
size_t | maxIterations |
maximum number of iterations allowed for the method (from the max_iterations specification in MethodIndControl) | |
size_t | maxRefineIterations |
maximum number of refinement iterations allowed for a uniform/adaptive refinement approach (from the max_refinement_iterations specification in MethodIndControl) | |
size_t | maxSolverIterations |
maximum number of internal solver iterations allowed for the method (from the max_solver_iterations specification in MethodIndControl) | |
size_t | maxFunctionEvals |
maximum number of function evaluations allowed for the method (from the max_function_evaluations specification in MethodIndControl) | |
bool | speculativeFlag |
flag for use of speculative gradient approaches for maintaining parallel load balance during the line search portion of optimization algorithms (from the speculative specification in MethodIndControl) | |
bool | methodUseDerivsFlag |
flag for usage of derivative data to enhance the computation of surrogate models (PCE/SC expansions, GP models for EGO/EGRA/EGIE) based on the use_derivatives specification | |
Real | constraintTolerance |
tolerance for controlling the amount of infeasibility that is allowed before an active constraint is considered to be violated (from the constraint_tolerance specification in MethodIndControl) | |
bool | methodScaling |
flag indicating scaling status (from the scaling specification in MethodIndControl) | |
size_t | numFinalSolutions |
number of final solutions returned from the iterator | |
Real | convergenceTolerance |
iteration convergence tolerance for the method (from the convergence_tolerance specification in MethodIndControl) | |
bool | relativeConvMetric |
controls use of convergence tolerance in a relative (true) or absolute (false) context | |
short | statsMetricMode |
mode of computing statistics metrics used for convergence assessment of multilevel/multifidelity refinement processes: active or combined | |
unsigned short | methodName |
the method selection: one of the optimizer, least squares, nond, dace, or parameter study methods | |
unsigned short | subMethod |
enum value for a sub-method type | |
String | subMethodName |
string identifier for a sub-method name within a multi-option method specification (e.g., from meta-iterators) | |
String | subModelPointer |
string pointer for a sub-model specification used by a meta-iterator | |
String | subMethodPointer |
string pointer for a sub-method specification used by a meta-iterator | |
int | iteratorServers |
number of servers for concurrent iterator parallelism (from the iterator_servers specification) | |
int | procsPerIterator |
number of processors for each concurrent iterator partition (from the processors_per_iterator specification) | |
short | iteratorScheduling |
type of scheduling ({DEFAULT,MASTER,PEER}_SCHEDULING) used in concurrent iterator parallelism (from the iterator_scheduling specification) | |
StringArray | hybridMethodNames |
array of methods for the sequential and collaborative hybrid meta-iterators (from the method_name_list specification) | |
StringArray | hybridModelPointers |
array of models for the sequential and collaborative hybrid meta-iterators (from the model_pointer_list specification) | |
StringArray | hybridMethodPointers |
array of methods for the sequential and collaborative hybrid meta-iterators (from the method_pointer_list specification) | |
String | hybridGlobalMethodName |
global method name for embedded hybrids (from the global_method_name specification) | |
String | hybridGlobalModelPointer |
global model pointer for embedded hybrids (from the global_model_pointer specification) | |
String | hybridGlobalMethodPointer |
global method pointer for embedded hybrids (from the global_method_pointer specification) | |
String | hybridLocalMethodName |
local method name for embedded hybrids (from the local_method_name specification) | |
String | hybridLocalModelPointer |
local model pointer for embedded hybrids (from the local_model_pointer specification) | |
String | hybridLocalMethodPointer |
local method pointer for embedded hybrids (from the local_method_pointer specification) | |
Real | hybridLSProb |
local search probability for embedded hybrids (from the local_search_probability specification) | |
int | concurrentRandomJobs |
number of random jobs to perform in the pareto_set and multi_start meta-iterators (from the random_starts and random_weight_sets specifications) | |
RealVector | concurrentParameterSets |
user-specified (i.e., nonrandom) parameter sets to evaluate in the pareto_set and multi_start meta-iterators (from the starting_points and weight_sets specifications) | |
unsigned short | softConvLimit |
number of consecutive iterations with change less than convergenceTolerance required to trigger convergence | |
bool | surrBasedLocalLayerBypass |
flag to indicate user-specification of a bypass of any/all layerings in evaluating truth response values in SBL. | |
RealVector | trustRegionInitSize |
initial trust region sizes in the surrogate-based local method (from the initial_size specification in MethodSBL), one size per surrogate model (notes: no trust region for the truth model; sizes are relative values, e.g., 0.1 = 10% of range of global bounds for each variable | |
Real | trustRegionMinSize |
minimum trust region size in the surrogate-based local method (from the minimum_size specification in MethodSBL), if the trust region size falls below this threshold the SBL iterations are terminated (note: if kriging is used with SBL, the min trust region size is set to 1.0e-3 in attempt to avoid ill-conditioned matrixes that arise in kriging over small trust regions) | |
Real | trustRegionContractTrigger |
trust region minimum improvement level (ratio of actual to predicted decrease in objective fcn) in the surrogate-based local method (from the contract_threshold specification in MethodSBL), the trust region shrinks or is rejected if the ratio is below this value ("eta_1" in the Conn-Gould-Toint trust region book) | |
Real | trustRegionExpandTrigger |
trust region sufficient improvement level (ratio of actual to predicted decrease in objective fn) in the surrogate-based local method (from the expand_threshold specification in MethodSBL), the trust region expands if the ratio is above this value ("eta_2" in the Conn-Gould-Toint trust region book) | |
Real | trustRegionContract |
trust region contraction factor in the surrogate-based local method (from the contraction_factor specification in MethodSBL) | |
Real | trustRegionExpand |
trust region expansion factor in the surrogate-based local method (from the expansion_factor specification in MethodSBL) | |
short | surrBasedLocalSubProbObj |
SBL approximate subproblem objective: ORIGINAL_PRIMARY, SINGLE_OBJECTIVE, LAGRANGIAN_OBJECTIVE, or AUGMENTED_LAGRANGIAN_OBJECTIVE. | |
short | surrBasedLocalSubProbCon |
SBL approximate subproblem constraints: NO_CONSTRAINTS, LINEARIZED_CONSTRAINTS, or ORIGINAL_CONSTRAINTS. | |
short | surrBasedLocalMeritFn |
SBL merit function type: BASIC_PENALTY, ADAPTIVE_PENALTY, BASIC_LAGRANGIAN, or AUGMENTED_LAGRANGIAN. | |
short | surrBasedLocalAcceptLogic |
SBL iterate acceptance logic: TR_RATIO or FILTER. | |
short | surrBasedLocalConstrRelax |
SBL constraint relaxation method: NO_RELAX or HOMOTOPY. | |
bool | surrBasedGlobalReplacePts |
user-specified method for adding points to the set upon which the next surrogate is based in the surrogate_based_global method. | |
String | dlDetails |
string of options for a dynamically linked solver | |
void * | dlLib |
handle to dynamically loaded library | |
int | verifyLevel |
the verify_level specification in MethodNPSOLDC | |
Real | functionPrecision |
the function_precision specification in MethodNPSOLDC and the EPSILON specification in NOMAD | |
Real | lineSearchTolerance |
the linesearch_tolerance specification in MethodNPSOLDC | |
Real | absConvTol |
absolute function convergence tolerance | |
Real | xConvTol |
x-convergence tolerance | |
Real | singConvTol |
singular convergence tolerance | |
Real | singRadius |
radius for singular convergence test | |
Real | falseConvTol |
false-convergence tolerance | |
Real | initTRRadius |
initial trust radius | |
int | covarianceType |
kind of covariance required | |
bool | regressDiag |
whether to print the regression diagnostic vector | |
String | searchMethod |
the search_method specification for Newton and nonlinear interior-point methods in MethodOPTPPDC | |
Real | gradientTolerance |
the gradient_tolerance specification in MethodOPTPPDC | |
Real | maxStep |
the max_step specification in MethodOPTPPDC | |
short | meritFn |
the merit_function specification for nonlinear interior-point methods in MethodOPTPPDC | |
Real | stepLenToBoundary |
the steplength_to_boundary specification for nonlinear interior-point methods in MethodOPTPPDC | |
Real | centeringParam |
the centering_parameter specification for nonlinear interior-point methods in MethodOPTPPDC | |
int | searchSchemeSize |
the search_scheme_size specification for PDS methods in MethodOPTPPDC | |
Real | initStepLength |
the initStepLength choice for nonlinearly constrained APPS in MethodAPPSDC | |
Real | contractStepLength |
the contractStepLength choice for nonlinearly constrained APPS in MethodAPPSDC | |
Real | threshStepLength |
the threshStepLength choice for nonlinearly constrained APPS in MethodAPPSDC | |
String | meritFunction |
the meritFunction choice for nonlinearly constrained APPS in MethodAPPSDC | |
Real | constrPenalty |
the constrPenalty choice for nonlinearly constrained APPS in MethodAPPSDC | |
Real | smoothFactor |
the initial smoothFactor value for nonlinearly constrained APPS in MethodAPPSDC | |
Real | constraintPenalty |
the initial constraint_penalty for COLINY methods in MethodAPPS, MethodSCOLIBDIR, MethodSCOLIBPS, MethodSCOLIBSW and MethodSCOLIBEA | |
bool | constantPenalty |
the constant_penalty flag for COLINY methods in MethodSCOLIBPS and MethodSCOLIBSW | |
Real | globalBalanceParam |
the global_balance_parameter for the DIRECT method in MethodSCOLIBDIR | |
Real | localBalanceParam |
the local_balance_parameter for the DIRECT method in MethodSCOLIBDIR | |
Real | maxBoxSize |
the max_boxsize_limit for the DIRECT method in MethodSCOLIBDIR | |
Real | minBoxSize |
the min_boxsize_limit for the DIRECT method in MethodSCOLIBDIR and MethodNCSUDC | |
String | boxDivision |
the division setting (major_dimension or all_dimensions ) for the DIRECT method in MethodSCOLIBDIR | |
bool | mutationAdaptive |
the non_adaptive specification for the coliny_ea method in MethodSCOLIBEA | |
bool | showMiscOptions |
the show_misc_options specification in MethodSCOLIBDC | |
StringArray | miscOptions |
the misc_options specification in MethodSCOLIBDC | |
Real | solnTarget |
the solution_target specification in MethodSCOLIBDC | |
Real | crossoverRate |
the crossover_rate specification for EA methods in MethodSCOLIBEA | |
Real | mutationRate |
the mutation_rate specification for EA methods in MethodSCOLIBEA | |
Real | mutationScale |
the mutation_scale specification for EA methods in MethodSCOLIBEA | |
Real | mutationMinScale |
the min_scale specification for mutation in EA methods in MethodSCOLIBEA | |
Real | initDelta |
the initial_delta specification for APPS/COBYLA/PS/SW methods in MethodAPPS, MethodSCOLIBCOB, MethodSCOLIBPS, and MethodSCOLIBSW | |
Real | threshDelta |
the variable_tolerance specification for APPS/COBYLA/PS/SW methods in MethodAPPS, MethodSCOLIBCOB, MethodSCOLIBPS, and MethodSCOLIBSW | |
Real | contractFactor |
the contraction_factor specification for APPS/PS/SW methods in MethodAPPS, MethodSCOLIBPS, and MethodSCOLIBSW | |
int | newSolnsGenerated |
the new_solutions_generated specification for GA/EPSA methods in MethodSCOLIBEA | |
int | numberRetained |
the integer assignment to random, chc, or elitist in the replacement_type specification for GA/EPSA methods in MethodSCOLIBEA | |
bool | expansionFlag |
the no_expansion specification for APPS/PS/SW methods in MethodAPPS, MethodSCOLIBPS, and MethodSCOLIBSW | |
int | expandAfterSuccess |
the expand_after_success specification for PS/SW methods in MethodSCOLIBPS and MethodSCOLIBSW | |
int | contractAfterFail |
the contract_after_failure specification for the SW method in MethodSCOLIBSW | |
int | mutationRange |
the mutation_range specification for the pga_int method in MethodSCOLIBEA | |
int | totalPatternSize |
the total_pattern_size specification for PS methods in MethodSCOLIBPS | |
bool | randomizeOrderFlag |
the stochastic specification for the PS method in MethodSCOLIBPS | |
String | selectionPressure |
the fitness_type specification for EA methods in MethodSCOLIBEA | |
String | replacementType |
the replacement_type specification for EA methods in MethodSCOLIBEA | |
String | crossoverType |
the crossover_type specification for EA methods in MethodSCOLIBEA | |
String | mutationType |
the mutation_type specification for EA methods in MethodSCOLIBEA | |
String | exploratoryMoves |
the exploratory_moves specification for the PS method in MethodSCOLIBPS | |
String | patternBasis |
the pattern_basis specification for APPS/PS methods in MethodAPPS and MethodSCOLIBPS | |
String | betaSolverName |
beta solvers don't need documentation | |
short | evalSynchronize |
the synchronization setting for parallel pattern search methods in MethodSCOLIBPS and MethodAPPS | |
size_t | numCrossPoints |
The number of crossover points or multi-point schemes. | |
size_t | numParents |
The number of parents to use in a crossover operation. | |
size_t | numOffspring |
The number of children to produce in a crossover operation. | |
String | fitnessType |
the fitness assessment operator to use. | |
String | convergenceType |
The means by which this JEGA should converge. | |
Real | percentChange |
The minimum percent change before convergence for a fitness tracker converger. | |
size_t | numGenerations |
The number of generations over which a fitness tracker converger should track. | |
Real | fitnessLimit |
The cutoff value for survival in fitness limiting selectors (e.g., below_limit selector). | |
Real | shrinkagePercent |
The minimum percentage of the requested number of selections that must take place on each call to the selector (0, 1). | |
String | nichingType |
The niching type. | |
RealVector | nicheVector |
The discretization percentage along each objective. | |
size_t | numDesigns |
The maximum number of designs to keep when using the max_designs nicher. | |
String | postProcessorType |
The post processor type. | |
RealVector | distanceVector |
The discretization percentage along each objective. | |
String | initializationType |
The means by which the JEGA should initialize the population. | |
String | flatFile |
The filename to use for initialization. | |
String | logFile |
The filename to use for logging. | |
int | populationSize |
the population_size specification for GA methods in MethodSCOLIBEA | |
bool | printPopFlag |
The print_each_pop flag to set the printing of the population at each generation. | |
Real | volBoxSize |
the volume_boxsize_limit for the DIRECT method in MethodNCSUDC | |
int | numSymbols |
the symbols specification for DACE methods | |
bool | mainEffectsFlag |
the main_effects specification for sampling methods in MethodDDACE) | |
bool | latinizeFlag |
the latinize specification for FSU QMC and CVT methods in MethodFSUDACE | |
bool | volQualityFlag |
the quality_metrics specification for sampling methods (FSU QMC and CVT methods in MethodFSUDACE) | |
IntVector | sequenceStart |
the sequenceStart specification in MethodFSUDACE | |
IntVector | sequenceLeap |
the sequenceLeap specification in MethodFSUDACE | |
IntVector | primeBase |
the primeBase specification in MethodFSUDACE | |
int | numTrials |
the numTrials specification in MethodFSUDACE | |
String | trialType |
the trial_type specification in MethodFSUDACE | |
int | randomSeed |
the seed specification for COLINY, NonD, & DACE methods | |
SizetArray | randomSeedSeq |
the seed_sequence specification for multilevel UQ methods | |
RealVector | scalarizationRespCoeffs |
the coefficient mapping for the scalarization term for multilevel UQ methods | |
Real | initMeshSize |
the initMeshSize choice for NOMAD in MethodNOMADDC | |
Real | minMeshSize |
the minMeshSize choice for NOMAD in MethodNOMADDC | |
String | historyFile |
the HISTORY_FILE specification for NOMAD | |
String | displayFormat |
the DISPLAY_STATS specification for NOMAD | |
Real | vns |
the VNS specification for NOMAD | |
int | neighborOrder |
the NEIGHBOR_ORDER specification for NOMAD | |
bool | showAllEval |
the DISPLAY_ALL_EVAL specification for NOMAD | |
String | useSurrogate |
the HAS_SGTE specification for NOMAD | |
int | maxCrossIterations |
maximum number of cross iterations | |
Real | solverTol |
optimization tolerance for FT regression | |
Real | solverRoundingTol |
Rounding tolerance for FT regression. | |
Real | statsRoundingTol |
arithmetic (rounding) tolerance for FT sums and products | |
unsigned short | startOrder |
starting polynomial order | |
unsigned short | kickOrder |
polynomial order increment when adapting | |
unsigned short | maxOrder |
maximum order of basis polynomials | |
bool | adaptOrder |
whether or not to adapt order by cross validation | |
size_t | startRank |
starting rank | |
size_t | kickRank |
rank increment when adapting | |
size_t | maxRank |
maximum rank | |
bool | adaptRank |
whether or not to adapt rank | |
size_t | maxCVRankCandidates |
maximum number of cross-validation candidates for adaptRank | |
unsigned short | maxCVOrderCandidates |
maximum number of cross-validation candidates for adaptOrder | |
short | c3AdvanceType |
quantity to increment (start rank, start order, max rank, max order, max rank + max order) for FT (uniform) p-refinement | |
UShortArray | startOrderSeq |
starting polynomial order | |
SizetArray | startRankSeq |
starting rank | |
int | numSamples |
the samples specification for NonD & DACE methods | |
bool | fixedSeedFlag |
flag for fixing the value of the seed among different NonD/DACE sample sets. This results in the use of the same sampling stencil/pattern throughout an execution with repeated sampling. | |
bool | fixedSequenceFlag |
flag for fixing the sequence for Halton or Hammersley QMC sample sets. This results in the use of the same sampling stencil/pattern throughout an execution with repeated sampling. | |
bool | vbdFlag |
the var_based_decomp specification for computing Sobol' indices via either PCE or sampling | |
Real | vbdDropTolerance |
the var_based_decomp tolerance for omitting Sobol' indices computed via either PCE or sampling | |
unsigned short | vbdViaSamplingMethod |
Sampling method for computing Sobol indices: Mahadevan (default) or Saltelli. | |
int | vbdViaSamplingNumBins |
Number of bins to use in case the Mahadevan method is selected (default is the square root of the number of samples) | |
bool | backfillFlag |
the backfill option allows one to augment in LHS sample by enforcing the addition of unique discrete variables to the sample | |
bool | pcaFlag |
Flag to specify the calculation of principal components when using LHS. | |
Real | percentVarianceExplained |
The percentage of variance explained by using a truncated number of principal components in PCA. | |
bool | wilksFlag |
Flag to specify use of Wilks formula to calculate num samples. | |
unsigned short | wilksOrder |
Wilks order parameter. | |
Real | wilksConfidenceLevel |
Wilks confidence interval parameter. | |
short | wilksSidedInterval |
Wilks sided interval type. | |
bool | rank1LatticeFlag |
Flag to indicate rank-1 lattice sampling. | |
bool | noRandomShiftFlag |
Flag to indicate randomization of rank-1 lattice rule. | |
int | log2MaxPoints |
(log2 of) maximum number of points of low-discrepancy generator | |
IntVector | generatingVector |
Inline generating vector of the rank-1 lattice rule. | |
String | generatingVectorFileName |
Name of file with generating vector. | |
bool | kuo |
Predefined generating vectors. | |
bool | cools_kuo_nuyens |
bool | naturalOrdering |
Ordering of the lattice points. | |
bool | radicalInverseOrdering |
bool | digitalNetFlag |
Flag to indicate digital net sampling. | |
bool | noDigitalShiftFlag |
Flag to indicate randomization of digital net. | |
bool | noScramblingFlag |
Flag to indicate scrambling of the digital net. | |
bool | mostSignificantBitFirst |
Flag to indicate integers in generating matrices are stored with most significant bit first. | |
bool | leastSignificantBitFirst |
Flag to indicate integers in generating matrices are stored with least significant bit first. | |
int | numberOfBits |
Number of bits in each integer in the generating matrices. | |
int | scrambleSize |
Number of rows in the linear scramble matrix. | |
IntVector | generatingMatrices |
Inline generating matrices of the digital net. | |
String | generatingMatricesFileName |
Name of file with generating matrices. | |
bool | joe_kuo |
Predefined generating matrices. | |
bool | sobol_order_2 |
bool | grayCodeOrdering |
Ordering of the digital net points. | |
bool | stdRegressionCoeffs |
flag indicating the calculation/output of standardized regression coefficients | |
bool | toleranceIntervalsFlag |
Flag to specify use of double sided tolerance interval equivalent normal. | |
Real | tiCoverage |
Coverage parameter for the calculation of double sided tolerance interval equivalent normal. | |
Real | tiConfidenceLevel |
Confidence level parameter for the calculation of double sided tolerance interval equivalent normal. | |
bool | respScalingFlag |
flag to indicate bounds-based scaling of current response data set prior to build in surrogate-based methods; important for ML/MF data fits of decaying discrepancy data using regression with absolute tolerances | |
unsigned short | vbdOrder |
a sub-specification of vbdFlag: interaction order limit for calculation/output of component VBD indices | |
short | covarianceControl |
restrict the calculation of a full response covariance matrix for high dimensional outputs: {DEFAULT,DIAGONAL,FULL}_COVARIANCE | |
String | rngName |
the basic random-number generator for NonD | |
short | refinementType |
refinement type for stochastic expansions from dimension refinement keyword group | |
short | refinementControl |
refinement control for stochastic expansions from dimension refinement keyword group | |
short | nestingOverride |
override for default point nesting policy: NO_NESTING_OVERRIDE, NESTED, or NON_NESTED | |
short | growthOverride |
override for default point growth restriction policy: NO_GROWTH_OVERRIDE, RESTRICTED, or UNRESTRICTED | |
short | expansionType |
enumeration for u-space type that defines u-space variable targets for probability space transformations: EXTENDED_U (default), ASKEY_U, PARTIAL_ASKEY_U, STD_NORMAL_U, or STD_UNIFORM_U | |
bool | piecewiseBasis |
boolean indicating presence of piecewise keyword | |
short | expansionBasisType |
enumeration for type of basis in sparse grid interpolation (Pecos::{NODAL,HIERARCHICAL}_INTERPOLANT) or regression (Pecos::{TENSOR_PRODUCT,TOTAL_ORDER,ADAPTED}_BASIS). | |
UShortArray | quadratureOrderSeq |
the quadrature_order_sequence specification in MethodNonDPCE and MethodNonDSC | |
UShortArray | sparseGridLevelSeq |
the sparse_grid_level_sequence specification in MethodNonDPCE and MethodNonDSC | |
UShortArray | expansionOrderSeq |
the expansion_order_sequence specification in MethodNonDPCE | |
SizetArray | collocationPointsSeq |
the collocation_points_sequence specification in MethodNonDPCE | |
SizetArray | expansionSamplesSeq |
the expansion_samples_sequence specification in MethodNonDPCE | |
unsigned short | quadratureOrder |
the quadrature_order specification in MethodNonDPCE and MethodNonDSC | |
unsigned short | sparseGridLevel |
the sparse_grid_level specification in MethodNonDPCE and MethodNonDSC | |
unsigned short | expansionOrder |
the expansion_order specification in MethodNonDPCE | |
size_t | collocationPoints |
the collocation_points specification in MethodNonDPCE | |
size_t | expansionSamples |
the expansion_samples specification in MethodNonDPCE | |
RealVector | anisoDimPref |
the dimension_preference specification for tensor and sparse grids and expansion orders in MethodNonDPCE and MethodNonDSC | |
unsigned short | cubIntOrder |
the cubature_integrand specification in MethodNonDPCE | |
Real | collocationRatio |
the collocation_ratio specification in MethodNonDPCE | |
Real | collocRatioTermsOrder |
order applied to the number of expansion terms when applying or computing the collocation ratio within regression PCE; based on the ratio_order specification in MethodNonDPCE | |
short | regressionType |
type of regression: LS, OMP, BP, BPDN, LARS, or LASSO | |
short | lsRegressionType |
type of least squares regression: SVD or EQ_CON_QR | |
RealVector | regressionNoiseTol |
noise tolerance(s) for OMP, BPDN, LARS, and LASSO | |
Real | regressionL2Penalty |
L2 regression penalty for a variant of LASSO known as the elastic net method (default of 0 gives standard LASSO) | |
bool | crossValidation |
flag indicating the use of cross-validation across expansion orders (given a prescribed maximum order) and, for some methods, noise tolerances | |
bool | crossValidNoiseOnly |
flag indicating the restriction of cross-validation to estimate only the most effective noise tolerance; used to reduce cost from performing CV over both noise tolerances and expansion orders | |
unsigned short | adaptedBasisAdvancements |
initial grid level for the ADAPTED_BASIS_EXPANDING_FRONT approach to defining the candidate basis for sparse recovery (compressed sensing) | |
bool | normalizedCoeffs |
flag indicating the output of PCE coefficients corresponding to normalized basis polynomials | |
String | pointReuse |
allows PCE construction to reuse points from previous sample sets or data import using the reuse_points specification in MethodNonDPCE | |
bool | tensorGridFlag |
flag for usage of a sub-sampled set of tensor-product grid points within regression PCE; based on the tensor_grid specification in MethodNonDPCE | |
UShortArray | tensorGridOrder |
order of tensor-product grid points that are sub-sampled within orthogonal least interpolation PCE; based on the tensor_grid specification in MethodNonDPCE | |
String | importExpansionFile |
the import_expansion_file specification in MethodNonDPCE | |
String | exportExpansionFile |
the export_expansion_file specification in MethodNonDPCE | |
unsigned short | sampleType |
the sample_type specification in MethodNonDMC, MethodNonDPCE, and MethodNonDSC | |
bool | dOptimal |
whether to generate D-optimal designs | |
size_t | numCandidateDesigns |
number of candidate designss in D-optimal design selection | |
String | reliabilityIntegration |
the first_order or second_order integration selection in MethodNonDLocalRel | |
unsigned short | integrationRefine |
the import , adapt_import , or mm_adapt_import integration refinement selection in MethodNonDLocalRel, MethodNonDPCE, and MethodNonDSC | |
IntVector | refineSamples |
Sequence of refinement samples, e.g., the size of the batch (e.g. number of supplemental points added) to be added to be added to the build points for an emulator at each iteration. | |
unsigned short | optSubProbSolver |
the method used for solving an optimization sub-problem (e.g., pre-solve for the MAP point) | |
unsigned short | numericalSolveMode |
approach for overriding an analytic solution based on simplifying assumptions that might be violated, suggesting a fallback approach, or lacking robustness, suggesting an optional override replacement | |
SizetArray | pilotSamples |
the pilot_samples selection in MethodMultilevelMC | |
short | ensembleSampSolnMode |
the solution_mode selection for ML/MF sampling methods | |
bool | truthPilotConstraint |
the truth_fixed_by_pilot flag for ACV methods | |
short | dagRecursionType |
option specified for extent of DAG enumeration within search_model_graphs for generalized ACV methods | |
unsigned short | dagDepthLimit |
option specified for depth_limit in generalized ACV methods with partial graph recursion | |
short | modelSelectType |
option specified for model_selection within search_model_graphs for generalized ACV methods | |
short | allocationTarget |
the allocationTarget selection in MethodMultilevelMC | |
bool | useTargetVarianceOptimizationFlag |
the allocation_target selection in MethodMultilevelMC | |
short | qoiAggregation |
the |c qoi_aggregation_norm selection in MethodMultilevelMC | |
short | convergenceToleranceType |
the |c convergence_tolerance_type selection in MethodMultilevelMC | |
short | convergenceToleranceTarget |
the |c convergence_tolerance_type selection in MethodMultilevelMC | |
short | multilevAllocControl |
the allocation_control selection in MethodMultilevelPCE | |
Real | multilevEstimatorRate |
the estimator_rate selection in MethodMultilevelPCE | |
short | multilevDiscrepEmulation |
type of discrepancy emulation in multilevel methods: distinct or recursive | |
short | finalStatsType |
specification of the type of final statistics in MethodNonD | |
short | finalMomentsType |
the final_moments specification in MethodNonD, subordinate to the type of final statistics | |
short | distributionType |
the distribution cumulative or complementary specification in MethodNonD | |
short | responseLevelTarget |
the compute probabilities , reliabilities , or gen_reliabilities specification in MethodNonD | |
short | responseLevelTargetReduce |
the system series or parallel specification in MethodNonD | |
RealVectorArray | responseLevels |
the response_levels specification in MethodNonD | |
RealVectorArray | probabilityLevels |
the probability_levels specification in MethodNonD | |
RealVectorArray | reliabilityLevels |
the reliability_levels specification in MethodNonD | |
RealVectorArray | genReliabilityLevels |
the gen_reliability_levels specification in MethodNonD | |
int | chainSamples |
the number of MCMC chain samples | |
int | buildSamples |
the number of samples to construct an emulator, e.g., for Bayesian calibration methods | |
int | samplesOnEmulator |
number of samples to perform on emulator | |
int | emulatorOrder |
The total order to be used in construction of a VPS surrogate. | |
short | emulatorType |
the emulator specification in MethodNonDBayesCalib | |
String | mcmcType |
the mcmc type specification in MethodNonDBayesCalib | |
bool | standardizedSpace |
use of standardized probability spaces for MCMC within Bayesian inference | |
bool | adaptPosteriorRefine |
flag indicating adaptive refinement of the emulator in regions of high posterior probability | |
bool | logitTransform |
flag indicating user activation of logit transform option within QUESO | |
bool | gpmsaNormalize |
whether to apply GPMSA-internal normalization | |
bool | posteriorStatsKL |
flag indicating the calculation of KL divergence between prior and posterior in Bayesian methods | |
bool | posteriorStatsMutual |
flag indicating the calculation of mutual information between prior and posterior in Bayesian methods | |
bool | posteriorStatsKDE |
flag indicating calculation of kernel density estimate of posterior distributions | |
bool | chainDiagnostics |
flag indicating calculation of chain diagnostics | |
bool | chainDiagnosticsCI |
flag indicating calculation of confidence intervals as a chain diagnositc | |
bool | modelEvidence |
flag indicating calculation of the evidence of the model | |
bool | modelEvidMC |
flag indicating use of Monte Carlo approximation for evidence calc. | |
int | evidenceSamples |
number of prior samples to use in model evidence calculation | |
bool | modelEvidLaplace |
flag indicating use of Laplace approximation for evidence calc. | |
String | proposalCovType |
the type of proposal covariance: user, derivatives, or prior | |
Real | priorPropCovMult |
optional multiplier for prior-based proposal covariance | |
int | proposalCovUpdatePeriod |
number of samples after which to update the proposal covariance from misfit Hessian (using residual values and derivatives) | |
String | proposalCovInputType |
the format of proposal covariance input: diagonal or matrix | |
RealVector | proposalCovData |
raw list of real data for the proposal covariance | |
String | proposalCovFile |
file from which to read proposal covariance in diagonal or matrix format | |
String | advancedOptionsFilename |
file containing advanced ROL option overrides | |
String | quesoOptionsFilename |
file containing advanced QUESO option overrides | |
String | fitnessMetricType |
the fitness metric type specification in MethodNonDAdaptive | |
String | batchSelectionType |
the batch selection type specification in MethodNonDAdaptive | |
String | lipschitzType |
the Lipschitz type specification in MethodNonDPOFDarts (e.g. either local or global estimation) | |
unsigned short | calibrateErrorMode |
calibration mode for observation error multipliers (CALIBRATE_*) | |
RealVector | hyperPriorAlphas |
hyperparameters inverse gamma prior alphas | |
RealVector | hyperPriorBetas |
hyperparameters inverse gamma prior alphas | |
int | burnInSamples |
number of MCMC samples to discard from acceptance chain | |
int | subSamplingPeriod |
period or skip in post-processing the acceptance chain | |
bool | calModelDiscrepancy |
flag to calculate model discrepancy | |
size_t | numPredConfigs |
number of prediction configurations at which to calculate model discrepancy | |
RealVector | predictionConfigList |
list of prediction configurations at which to calculate model discrepancy | |
String | importPredConfigs |
whether to import prediction configurations at which to calculate model discrepancy | |
unsigned short | importPredConfigFormat |
tabular format for prediction configurations import file | |
String | modelDiscrepancyType |
type of model discrepancy emulation | |
short | polynomialOrder |
polynomial order for model discrepancy calculations: either gaussian process trend order or polynomial basis order | |
String | exportCorrModelFile |
specify the name of file to which corrected model (model+discrepancy) calculations are output | |
unsigned short | exportCorrModelFormat |
tabular format for corrected model (model+discrepancy) export file | |
String | exportCorrVarFile |
specify the name of file to which corrected model variance calculations are output | |
unsigned short | exportCorrVarFormat |
tabular format for corrected model variance export file | |
String | exportDiscrepFile |
specify the name of file to which discrepancy calculations are output | |
unsigned short | exportDiscrepFormat |
tabular format for model discrepancy export file | |
bool | adaptExpDesign |
whether to perform adaptive Bayesian design of experiments | |
String | importCandPtsFile |
whether to import candidate design points for adaptive Bayesian experimental design | |
unsigned short | importCandFormat |
tabular format for the candidate design points import file | |
size_t | numCandidates |
number of candidate designs for adaptive Bayesian experimental design | |
int | maxHifiEvals |
maximum number of highfidelity model runs to be used for adaptive Bayesian experimental design | |
int | batchSize |
number of optimal designs selected per iteration of experimental design algorithm; also number of concurrent GP refinement points for EGO | |
int | batchSizeExplore |
portion of batchSize earmarked for exploration rather than acquisition | |
bool | mutualInfoKSG2 |
indicate that the KSG2 algorithm is to be employed in the calculation of the mutual information | |
int | numChains |
number of concurrent chains | |
int | numCR |
number of CR-factors | |
int | crossoverChainPairs |
number of crossover chain pairs | |
Real | grThreshold |
threshold for the Gelmin-Rubin statistic | |
int | jumpStep |
how often to perform a long jump in generations | |
int | numPushforwardSamples |
Number of samples from the prior that is pushed forward through the model to obtain the initial set of pushforward samples. | |
String | dataDistType |
the type of data distribution: kde, or gaussian | |
String | dataDistCovInputType |
the format of data distribution gaussian covariance input: diagonal or matrix | |
RealVector | dataDistMeans |
raw list of real data for the data distribution gaussian means | |
RealVector | dataDistCovariance |
raw list of real data for the data distribution gaussian covariance | |
String | dataDistFile |
file from which to read data distribution data (covariance or samples ) | |
String | posteriorDensityExportFilename |
The filename of the export file containing an arbitrary set of samples and their corresponding density values. | |
String | posteriorSamplesExportFilename |
The filename of the export file containing samples from the posterior and their corresponding density values. | |
String | posteriorSamplesImportFilename |
The filename of the import file containing samples at which the posterior will be evaluated. | |
bool | generatePosteriorSamples |
Flag specifying whether to generate random samples from the posterior. | |
bool | evaluatePosteriorDensity |
Flag specifying whether to evaluate the posterior density at a set of samples. | |
RealVector | finalPoint |
the final_point specification in MethodPSVPS | |
RealVector | stepVector |
the step_vector specification in MethodPSVPS and MethodPSCPS | |
int | numSteps |
the num_steps specification in MethodPSVPS | |
IntVector | stepsPerVariable |
the deltas_per_variable specification in MethodPSCPS | |
RealVector | listOfPoints |
the list_of_points specification in MethodPSLPS | |
String | pstudyFilename |
the import_points_file spec for a file-based parameter study | |
unsigned short | pstudyFileFormat |
tabular format for the parameter study points file | |
bool | pstudyFileActive |
whether to import active variables only | |
UShortArray | varPartitions |
the partitions specification for PStudy method in MethodPSMPS | |
Real | refinementRate |
rate of mesh refinement in Richardson extrapolation | |
String | importBuildPtsFile |
the file name from the import_build_points_file specification | |
unsigned short | importBuildFormat |
tabular format for the build point import file | |
bool | importBuildActive |
whether to import active variables only | |
String | importApproxPtsFile |
the file name from the import_approx_points_file specification | |
unsigned short | importApproxFormat |
tabular format for the approx point import file | |
bool | importApproxActive |
whether to import active variables only | |
String | exportApproxPtsFile |
the file name from the export_approx_points_file specification | |
unsigned short | exportApproxFormat |
tabular format for the approx point export file | |
String | exportMCMCPtsFile |
the file name from the export_mcmc_points_file specification | |
bool | exportSampleSeqFlag |
flag for exporting the sequence of sample increments within multilevel sampling from the export_sample_sequence specification | |
unsigned short | exportSamplesFormat |
tabular format for the MCMC chain and MLMC sample sequence exports | |
bool | exportSurrogate |
Option to turn on surrogate model export (export_model) | |
String | modelExportPrefix |
the filename prefix for export_model | |
unsigned short | modelExportFormat |
Format selection for export_model. | |
Private Member Functions | |
DataMethodRep () | |
constructor | |
void | write (std::ostream &s) const |
write a DataInterfaceRep object to an std::ostream | |
void | read (MPIUnpackBuffer &s) |
read a DataInterfaceRep object from a packed MPI buffer | |
void | write (MPIPackBuffer &s) const |
write a DataInterfaceRep object to a packed MPI buffer | |
Friends | |
class | DataMethod |
the handle class can access attributes of the body class directly | |
Body class for method specification data.
The DataMethodRep class is used to contain the data from a method keyword specification. Default values are managed in the DataMethodRep constructor. Data is public to avoid maintaining set/get functions, but is still encapsulated within ProblemDescDB since ProblemDescDB::dataMethodList is private.