ActiveSet | Container class for active set tracking information. Contains the active set request vector and the derivative variables vector |
AddAttributeVisitor | Objects of this class are called by boost::appy_visitor to add attributes to HDF5 objects |
Approximation | Base class for the approximation class hierarchy |
C3Approximation | Derived approximation class for global basis polynomials |
GaussProcApproximation | Derived approximation class for Gaussian Process implementation |
PecosApproximation | Derived approximation class for global basis polynomials |
QMEApproximation | Derived approximation class for QMEA Quadratic Multipoint Exponential Approximation (a multipoint approximation) |
SurfpackApproximation | Derived approximation class for Surfpack approximation classes. Interface between Surfpack and Dakota |
SurrogatesBaseApprox | Derived Approximation class for new Surrogates modules |
SurrogatesGPApprox | Derived approximation class for Surrogates approximation classes |
SurrogatesPolyApprox | Derived approximation class for Surrogates Polynomial approximation classes |
TANA3Approximation | Derived approximation class for TANA-3 two-point exponential approximation (a multipoint approximation) |
TaylorApproximation | Derived approximation class for first- or second-order Taylor series (a local approximation) |
VPSApproximation | Derived approximation class for VPS implementation |
APPSEvalMgr | Evaluation manager class for APPSPACK |
ApreproWriter | Utility used in derived write_core to write in aprepro format |
AttachScaleVisitor | Objects of this class are called by boost::appy_visitor to add dimension scales (RealScale or StringScale) to HDF5 datasets |
BaseConstructor | Dummy struct for overloading letter-envelope constructors |
BootstrapSamplerBase< Data > | Base class/interface for the bootstrap sampler |
BootstrapSampler< Data > | Actual boostrap sampler implementation for common data types |
BootstrapSamplerWithGS< Data, Getter, Setter > | A derived sampler to allow for user specification of the accessor methods |
BootstrapSamplerBase< Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > > | |
BootstrapSampler< Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > > | Bootstrap sampler that is specialized to allow for the boostrapping of RealMatrix |
C3FnTrainData | Handle for reference-counted pointer to C3FnTrainDataRep body |
callback_data | |
COLINApplication | |
CommandShell | Utility class which defines convenience operators for spawning processes with system calls |
ConsoleRedirector | |
Constraints | Base class for the variable constraints class hierarchy |
MixedVarConstraints | Derived class within the Constraints hierarchy which separates continuous and discrete variables (no domain type array merging) |
RelaxedVarConstraints | Derived class within the Constraints hierarchy which employs relaxation of discrete variables |
DakotaROLEqConstraints | |
DakotaROLEqConstraintsGrad | |
DakotaROLEqConstraintsHess | |
DakotaROLIneqConstraints | |
DakotaROLIneqConstraintsGrad | |
DakotaROLIneqConstraintsHess | |
DakotaROLObjective | |
DakotaROLObjectiveGrad | |
DakotaROLObjectiveHess | |
DataEnvironment | Handle class for environment specification data |
DataEnvironmentRep | Body class for environment specification data |
DataInterface | Handle class for interface specification data |
DataMethod | Handle class for method specification data |
DataMethodRep | Body class for method specification data |
DataModel | Handle class for model specification data |
DataModelRep | Body class for model specification data |
DataResponses | Handle class for responses specification data |
DataResponsesRep | Body class for responses specification data |
DataScaler | Computes the scaling coefficients and scales a 2D data matrix with dimensions num_samples by num_features |
NormalizationScaler | Normalizes the data using max and min feature values |
NoScaler | Leaves the data unscaled |
StandardizationScaler | Standardizes the data so the each feature has zero mean and unit variance |
DataVariables | Handle class for variables specification data |
DataVariablesRep | Body class for variables specification data |
DerivInformedPropCovLogitTK< V, M > | Dakota transition kernel that updates proposal covariance based on derivatives (for logit random walk case) |
DerivInformedPropCovTK< V, M > | Dakota transition kernel that updates proposal covariance based on derivatives (for random walk case) |
DiscrepancyCorrection | Base class for discrepancy corrections |
JEGAOptimizer::Driver | A subclass of the JEGA front end driver that exposes the individual protected methods to execute the algorithm |
Environment | Base class for the environment class hierarchy |
ExecutableEnvironment | Environment corresponding to execution as a stand-alone application |
LibraryEnvironment | Environment corresponding to execution as an embedded library |
NomadOptimizer::Evaluator | NOMAD-based Evaluator class |
JEGAOptimizer::Evaluator | An evaluator specialization that knows how to interact with Dakota |
JEGAOptimizer::EvaluatorCreator | A specialization of the JEGA::FrontEnd::EvaluatorCreator that creates a new instance of a Evaluator |
ExperimentData | Interpolation method for interpolating between experimental and model data. I need to work on inputs/outputs to this method. For now, this assumes interpolation of functional data |
FileReadException | Base class for Dakota file read exceptions (to allow catching both tabular and general file truncation issues) |
ResultsFileError | Exception throw for other results file read error |
TabularDataTruncated | Exception thrown when data read truncated |
FunctionEvalFailure | Exception class for function evaluation failures |
GeneralReader | Utility used in derived read_core to read in generic format |
GeneralWriter | Utility used in derived write_core to write in generic format |
GetLongOpt | GetLongOpt is a general command line utility from S. Manoharan (Advanced Computer Research Institute, Lyon, France) |
CommandLineHandler | Utility class for managing command line inputs to DAKOTA |
GP_Objective | ROL objective function for the Gaussian Process (GP) surrogate |
Graphics | Single interface to 2D (motif) and 3D (PLPLOT) graphics; there is only one instance of this OutputManager::dakotaGraphics |
HDF5IOHelper | |
IntegerScale | Data structure for storing int-valued dimension scale |
Interface | Base class for the interface class hierarchy |
ApplicationInterface | Derived class within the interface class hierarchy for supporting interfaces to simulation codes |
DirectApplicInterface | Derived application interface class which spawns simulation codes and testers using direct procedure calls |
MatlabInterface | |
Pybind11Interface | |
PythonInterface | |
ScilabInterface | |
TestDriverInterface | |
ParallelDirectApplicInterface | Sample derived interface class for testing parallel simulator plug-ins using assign_rep() |
SerialDirectApplicInterface | Sample derived interface class for testing serial simulator plug-ins using assign_rep() |
SoleilDirectApplicInterface | Sample derived interface class for testing serial simulator plug-ins using assign_rep() |
ProcessApplicInterface | Derived application interface class that spawns a simulation code using a separate process and communicates with it through files |
ProcessHandleApplicInterface | Derived application interface class that spawns a simulation code using a separate process, receives a process identifier, and communicates with the spawned process through files |
ForkApplicInterface | Derived application interface class which spawns simulation codes using fork/execvp/waitpid |
SpawnApplicInterface | Derived application interface class which spawns simulation codes using spawnvp |
SysCallApplicInterface | Derived application interface class which spawns simulation codes using system calls |
GridApplicInterface | Derived application interface class which spawns simulation codes using grid services such as Condor or Globus |
ApproximationInterface | Derived class within the interface class hierarchy for supporting approximations to simulation-based results |
Iterator | Base class for the iterator class hierarchy |
Analyzer | Base class for NonD, DACE, and ParamStudy branches of the iterator hierarchy |
NonD | Base class for all nondetermistic iterators (the DAKOTA/UQ branch) |
NonDCalibration | |
NonDBayesCalibration | Base class for Bayesian inference: generates posterior distribution on model parameters given experimental data |
NonDDREAMBayesCalibration | Bayesian inference using the DREAM approach |
NonDMUQBayesCalibration | Dakota interface to MUQ (MIT Uncertainty Quantification) library |
NonDQUESOBayesCalibration | Bayesian inference using the QUESO library from UT Austin |
NonDGPMSABayesCalibration | Generates posterior distribution on model parameters given experiment data |
NonDWASABIBayesCalibration | WASABI - Weighted Adaptive Surrogate Approximations for Bayesian Inference |
NonDExpansion | Base class for polynomial chaos expansions (PCE), stochastic collocation (SC) and functional tensor train (FT) |
NonDC3FunctionTrain | Nonintrusive uncertainty quantification with the C3 library .. |
NonDMultilevelFunctionTrain | Nonintrusive polynomial chaos expansion approaches to uncertainty quantification |
NonDPolynomialChaos | Nonintrusive polynomial chaos expansion approaches to uncertainty quantification |
NonDMultilevelPolynomialChaos | Nonintrusive polynomial chaos expansion approaches to uncertainty quantification |
NonDStochCollocation | Nonintrusive stochastic collocation approaches to uncertainty quantification |
NonDMultilevelStochCollocation | Nonintrusive stochastic collocation approaches to uncertainty quantification |
NonDSurrogateExpansion | Generic uncertainty quantification with Model-based stochastic expansions |
NonDIntegration | Derived nondeterministic class that generates N-dimensional numerical integration points for evaluation of expectation integrals |
NonDCubature | Derived nondeterministic class that generates N-dimensional numerical cubature points for evaluation of expectation integrals |
NonDQuadrature | Derived nondeterministic class that generates N-dimensional numerical quadrature points for evaluation of expectation integrals over uncorrelated standard normals/uniforms/exponentials/betas/gammas |
NonDSparseGrid | Derived nondeterministic class that generates N-dimensional Smolyak sparse grids for numerical evaluation of expectation integrals over independent standard random variables |
NonDInterval | Base class for interval-based methods within DAKOTA/UQ |
NonDGlobalInterval | Class for using global nongradient-based optimization approaches to calculate interval bounds for epistemic uncertainty quantification |
NonDGlobalEvidence | Class for the Dempster-Shafer Evidence Theory methods within DAKOTA/UQ |
NonDGlobalSingleInterval | Class for using global nongradient-based optimization approaches to calculate interval bounds for epistemic uncertainty quantification |
NonDLHSInterval | Class for the LHS-based interval methods within DAKOTA/UQ |
NonDLHSEvidence | Class for the Dempster-Shafer Evidence Theory methods within DAKOTA/UQ |
NonDLHSSingleInterval | Class for pure interval propagation using LHS |
NonDLocalInterval | Class for using local gradient-based optimization approaches to calculate interval bounds for epistemic uncertainty quantification |
NonDLocalEvidence | Class for the Dempster-Shafer Evidence Theory methods within DAKOTA/UQ |
NonDLocalSingleInterval | Class for using local gradient-based optimization approaches to calculate interval bounds for epistemic uncertainty quantification |
NonDPOFDarts | Base class for POF Dart methods within DAKOTA/UQ |
NonDReliability | Base class for the reliability methods within DAKOTA/UQ |
NonDGlobalReliability | Class for global reliability methods within DAKOTA/UQ |
NonDLocalReliability | Class for the reliability methods within DAKOTA/UQ |
NonDRKDDarts | Base class for the Recursive k-d Dart methods within DAKOTA/UQ |
NonDSampling | Base class for common code between NonDLHSSampling, NonDAdaptImpSampling, and other specializations |
NonDAdaptImpSampling | Class for the Adaptive Importance Sampling methods within DAKOTA |
NonDAdaptiveSampling | Class for testing various Adaptively sampling methods using geometric, statisctical, and topological information of the surrogate |
NonDEnsembleSampling | Base class for Monte Carlo sampling across Model ensembles |
NonDHierarchSampling | Performs Hierarch Monte Carlo sampling for uncertainty quantification |
NonDControlVariateSampling | Performs Multifidelity Monte Carlo sampling for UQ |
NonDMultilevControlVarSampling | Performs multilevel-multifidelity Monte Carlo sampling for uncertainty quantification |
NonDMultilevelSampling | Performs Multilevel Monte Carlo sampling for uncertainty quantification |
NonDMultilevControlVarSampling | Performs multilevel-multifidelity Monte Carlo sampling for uncertainty quantification |
NonDNonHierarchSampling | Perform Approximate Control Variate Monte Carlo sampling for UQ |
NonDACVSampling | Perform Approximate Control Variate Monte Carlo sampling for UQ |
NonDMultifidelitySampling | Perform Approximate Control Variate Monte Carlo sampling for UQ |
NonDGPImpSampling | Class for the Gaussian Process-based Importance Sampling method |
NonDLHSSampling | Performs LHS and Monte Carlo sampling for uncertainty quantification |
PStudyDACE | Base class for managing common aspects of parameter studies and design of experiments methods |
DDACEDesignCompExp | Wrapper class for the DDACE design of experiments library |
FSUDesignCompExp | Wrapper class for the FSUDace QMC/CVT library |
ParamStudy | Class for vector, list, centered, and multidimensional parameter studies |
PSUADEDesignCompExp | Wrapper class for the PSUADE library |
Verification | Base class for managing common aspects of verification studies |
RichExtrapVerification | Class for Richardson extrapolation for code and solution verification |
MetaIterator | Base class for meta-iterators |
CollabHybridMetaIterator | Meta-iterator for hybrid iteration using multiple collaborating optimization and nonlinear least squares methods |
ConcurrentMetaIterator | Meta-iterator for multi-start iteration or pareto set optimization |
EmbedHybridMetaIterator | Meta-iterator for closely-coupled hybrid iteration, typically involving the embedding of local search methods within global search methods |
SeqHybridMetaIterator | Method for sequential hybrid iteration using multiple optimization and nonlinear least squares methods on multiple models of varying fidelity |
Minimizer | Base class for the optimizer and least squares branches of the iterator hierarchy |
LeastSq | Base class for the nonlinear least squares branch of the iterator hierarchy |
NL2SOLLeastSq | Wrapper class for the NL2SOL nonlinear least squares library |
NLSSOLLeastSq | Wrapper class for the NLSSOL nonlinear least squares library |
SNLLLeastSq | Wrapper class for the OPT++ optimization library |
Optimizer | Base class for the optimizer branch of the iterator hierarchy |
APPSOptimizer | Wrapper class for HOPSPACK |
COLINOptimizer | Wrapper class for optimizers defined using COLIN |
CONMINOptimizer | Wrapper class for the CONMIN optimization library |
JEGAOptimizer | A version of Dakota::Optimizer for instantiation of John Eddy's Genetic Algorithms (JEGA) |
NCSUOptimizer | Wrapper class for the NCSU DIRECT optimization library |
NonlinearCGOptimizer | |
NOWPACOptimizer | Wrapper class for the (S)NOWPAC optimization algorithms from Florian Augustin (MIT) |
OptDartsOptimizer | Wrapper class for OptDarts Optimizer |
ROLOptimizer | |
SNLLOptimizer | Wrapper class for the OPT++ optimization library |
SurrBasedMinimizer | Base class for local/global surrogate-based optimization/least squares |
EffGlobalMinimizer | |
SurrBasedGlobalMinimizer | |
SurrBasedLocalMinimizer | Class for provably-convergent local surrogate-based optimization and nonlinear least squares |
IteratorScheduler | This class encapsulates scheduling operations for concurrent sub-iteration within an outer level context (e.g., meta-iteration, nested models) |
Kernel | Kernel functions for the Gaussian Process surrogate |
Matern32Kernel | Stationary kernel with C^1 smooth realizations |
Matern52Kernel | Stationary kernel with C^2 smooth realizations |
SquaredExponentialKernel | Stationary kernel with C^ smooth realizations |
LabelsWriter | Utility used in derived write_core to write labels in tabular format |
LightWtBaseConstructor | Dummy struct for overloading constructors used in on-the-fly Model instantiations |
LinearSolverBase | Serves as an API for derived solvers |
CholeskySolver | Used to solve linear systems with a symmetric matrix with a pivoted Cholesky decomposition |
LUSolver | Used to solve linear systems with the LU decomposition |
QRSolver | Solves the linear least squares problem with a QR decomposition |
SVDSolver | Used to solve linear systems with the singular value decomposition |
MatchesWC | Predicate that returns true when the passed path matches the wild_card with which it was configured. Currently supports * and ? |
Model | Base class for the model class hierarchy |
AdapterModel | Derived model class which wraps call-back functions for solving minimization sub-problems |
MinimizerAdapterModel | Derived model class which wraps call-back functions for solving minimization sub-problems |
NestedModel | Derived model class which performs a complete sub-iterator execution within every evaluation of the model |
RecastModel | Derived model class which provides a thin wrapper around a sub-model in order to recast the form of its inputs and/or outputs |
DataTransformModel | Data transformation specialization of RecastModel |
ProbabilityTransformModel | Probability transformation specialization of RecastModel |
RandomFieldModel | Random field model, capable of generating and then forward propagating |
ScalingModel | Scaling specialization of RecastModel |
SubspaceModel | Subspace model for input (variable space) reduction |
ActiveSubspaceModel | Active subspace model for input (variable space) reduction |
AdaptedBasisModel | Adapted basis model for input (variable space) reduction |
WeightingModel | Weighting specialization of RecastModel |
SimulationModel | Derived model class which utilizes a simulation-based application interface to map variables into responses |
SurrogateModel | Base class for surrogate models (DataFitSurrModel and HierarchSurrModel) |
DataFitSurrModel | Derived model class within the surrogate model branch for managing data fit surrogates (global and local) |
EnsembleSurrModel | Derived model class within the surrogate model branch for managing subordinate models of varying fidelity |
HierarchSurrModel | Derived model class within the surrogate model branch for managing hierarchical surrogates (models of varying fidelity) |
NonHierarchSurrModel | Derived model class within the surrogate model branch for managing unordered surrogate models of varying fidelity |
MPIManager | Class MPIManager to manage Dakota's MPI world, which may be a subset of MPI_COMM_WORLD |
MPIPackBuffer | Class for packing MPI message buffers |
MPIUnpackBuffer | Class for unpacking MPI message buffers |
NL2Res | Auxiliary information passed to calcr and calcj via ur |
NoDBBaseConstructor | Dummy struct for overloading constructors used in on-the-fly instantiations without ProblemDescDB support |
NOWPACBlackBoxEvaluator | Derived class for plugging Dakota evaluations into NOWPAC solver |
OutputManager | Class to manage redirection of stdout/stderr, keep track of current redir state, and manage rank 0 output. Also manage tabular data output for post-processing with Matlab, Tecplot, etc. and delegate to Graphics for X Windows Graphics |
OutputWriter | |
ParallelConfiguration | Container class for a set of ParallelLevel list iterators that collectively identify a particular multilevel parallel configuration |
ParallelLevel | Container class for the data associated with a single level of communicator partitioning |
ParallelLibrary | Class for partitioning multiple levels of parallelism and managing message passing within these levels |
ParamResponsePair | Container class for a variables object, a response object, and an evaluation id |
partial_prp_equality | Predicate for comparing ONLY the interfaceId and Vars attributes of PRPair |
partial_prp_hash | Wrapper to delegate to the ParamResponsePair hash_value function |
PebbldBranching | Main Branching class for the PEBBL-based Minimizer |
PebbldBranchSub | Sub Branch class for the PEBBL-based Minimizer |
PrefixingLineFilter | |
ProblemDescDB | The database containing information parsed from the DAKOTA input file |
NIDRProblemDescDB | The derived input file database utilizing the new IDR parser |
ProgramOptions | ProgramOptions stores options whether from the CLH or from library user; initially valid only on worldRank = 0, but then broadcast in ParallelLibrary::push_output_tag() |
QuesoJointPdf< V, M > | Dakota specialization of QUESO generic joint PDF |
QuesoVectorRV< V, M > | Dakota specialization of QUESO vector-valued random variable |
RealScale | Data structure for storing real-valued dimension scale |
ReducedBasis | |
Response | Container class for response functions and their derivatives. Response provides the enveloper base class |
ExperimentResponse | Container class for response functions and their derivatives. ExperimentResponse provides the body class |
SimulationResponse | Container class for response functions and their derivatives. SimulationResponse provides the body class |
RestartWriter | |
ResultAttribute< T > | Data structure for a single Real, String, or int valued attribute |
ResultsDBBase | |
ResultsDBAny | |
ResultsDBHDF5 | Manage interactions between ResultsManager and the low-level HDFIOHelper class |
ResultsEntry< StoredType > | Class to manage in-core vs. file database lookups |
ResultsManager | Results manager for iterator final data |
ResultsNames | List of valid names for iterator results |
ScalingOptions | Simple container for user-provided scaling data, possibly expanded by replicates through the models |
SensAnalysisGlobal | Class for a utility class containing correlation calculations and variance-based decomposition |
TrackerHTTP::Server | Struct to hold tracker/proxy pairs |
SharedApproxData | Base class for the shared approximation data class hierarchy |
SharedC3ApproxData | Derived approximation class for global basis polynomials |
SharedPecosApproxData | Derived approximation class for global basis polynomials |
SharedSurfpackApproxData | Derived approximation class for Surfpack approximation classes. Interface between Surfpack and Dakota |
SharedResponseData | Container class encapsulating variables data that can be shared among a set of Response instances |
SharedResponseDataRep | The representation of a SharedResponseData instance. This representation, or body, may be shared by multiple SharedResponseData handle instances |
SharedVariablesData | Container class encapsulating variables data that can be shared among a set of Variables instances |
SharedVariablesDataRep | The representation of a SharedVariablesData instance. This representation, or body, may be shared by multiple SharedVariablesData handle instances |
SNLLBase | Base class for OPT++ optimization and least squares methods |
SNLLLeastSq | Wrapper class for the OPT++ optimization library |
SNLLOptimizer | Wrapper class for the OPT++ optimization library |
SOLBase | Base class for Stanford SOL software |
NLSSOLLeastSq | Wrapper class for the NLSSOL nonlinear least squares library |
StringScale | Data structure for storing string-valued dimension scale |
Surrogate | Parent class for surrogate models |
GaussianProcess | The GaussianProcess constructs a Gaussian Process regressor surrogate given a matrix of data |
PolynomialRegression | Constructs a polynomial regressor using ordinary least squares |
PyPolyReg | Extend PolynomialRegression with a new type for Python |
TabularReader | Utility used in derived read_core to read values in tabular format |
TabularWriter | Utility used in derived write_core to write values in tabular format |
TKFactoryDIPC | Custom RW TKfactory: passes Dakota QUESO instance pointer to the TK at build |
TKFactoryDIPCLogit | Custom Logit RW TKfactory: passed Dakota QUESO instance pointer to the TK at build |
TPLDataTransfer | |
TrackerHTTP | TrackerHTTP: a usage tracking module that uses HTTP/HTTPS via the curl library |
TraitsBase | Base class for traits |
AppsTraits | HOPSPACK-specific traits class |
COLINTraits | A version of TraitsBase specialized for COLIN optimizers |
CONMINTraits | A version of TraitsBase specialized for CONMIN optimizers |
DataFitSurrBasedLocalTraits | Class for provably-convergent local surrogate-based optimization and nonlinear least squares |
DLSolverTraits | A version of TraitsBase specialized for DLSolver |
DOTTraits | Wrapper class for the DOT optimization library |
EffGlobalTraits | Implementation of Efficient Global Optimization/Least Squares algorithms |
HierarchSurrBasedLocalTraits | Class for multilevel-multifidelity optimization algorithm |
JEGATraits | A version of TraitsBase specialized for John Eddy's Genetic Algorithms (JEGA) |
NCSUTraits | A version of TraitsBase specialized for NCSU optimizers |
NL2SOLLeastSqTraits | A version of TraitsBase specialized for NL2SOL nonlinear least squares library |
NLPQLPTraits | Wrapper class for the NLPQLP optimization library, Version 2.0 |
NLSSOLLeastSqTraits | A version of TraitsBase specialized for NLSSOL nonlinear least squares library |
NomadTraits | Wrapper class for NOMAD Optimizer |
NonlinearCGTraits | A version of TraitsBase specialized for NonlinearCG optimizers |
NOWPACTraits | A version of TraitsBase specialized for NOWPAC optimizers |
NPSOLTraits | Wrapper class for the NPSOL optimization library |
OptDartsTraits | A version of TraitsBase specialized for OptDarts |
PebbldTraits | Wrapper class for experimental PebbldMinimizer |
ROLTraits | |
SNLLLeastSqTraits | A version of TraitsBase specialized for SNLLLeastSq |
SNLLTraits | A version of TraitsBase specialized for SNLL optimizers |
SurrBasedGlobalTraits | The global surrogate-based minimizer which sequentially minimizes and updates a global surrogate model without trust region controls |
UsageTracker | Lightweight class to manage conditionally active Curl-based HTTP tracker via PIMPL |
Var_icheck | Structure for verifying bounds and initial point for string-valued vars |
Var_rcheck | Structure for verifying bounds and initial point for real-valued vars |
Variables | Base class for the variables class hierarchy |
MixedVariables | Derived class within the Variables hierarchy which separates continuous and discrete variables (no domain type array merging) |
RelaxedVariables | Derived class within the Variables hierarchy which employs the relaxation of discrete variables |
VLint | Structure for validating integer uncertain variable labels, bounds, values |
VLreal | Structure for validating real uncertain variable labels, bounds, values |
VLstr | Structure for validating string uncertain variable labels, bounds, values |
WorkdirHelper | |