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Dakota Namespace Reference

The primary namespace for DAKOTA. More...

Classes

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

Typedefs

typedef boost::tuple< std::string, std::string, size_t, std::string > ResultsKeyType
 Data type for results key (instance name / id, unique run, label), where data_key is a valid colon-delimited string from ResultsNames tuple<method_name, method_id, execution_number, data_key>
 
typedef std::string MetaDataKeyType
 Data type for metadata key.
 
typedef std::vector< std::string > MetaDataValueType
 Data type for metadata value.
 
typedef std::map< MetaDataKeyType, MetaDataValueType > MetaDataType
 A single MetaData entry is map<string, vector<string> > Example: pair( "Column labels", ["Mean", "Std Dev", "Skewness", "Kurtosis"] )
 
typedef boost::tuple< std::string, std::string, size_t > StrStrSizet
 Iterator unique ID: <method_name, method_id, exec_num>
 
typedef std::multimap< int, boost::variant< StringScale, RealScale, IntegerScale > > DimScaleMap
 Datatype to communicate scales (stored in boost::variant) and their associated dimension (the int) to the ResultsManager instance.
 
typedef std::vector< boost::variant< ResultAttribute< int >, ResultAttribute< String >, ResultAttribute< Real > > > AttributeArray
 Datatype to communcate metadata (attributes) to the ResultsManager instance.
 
typedef boost::bimap< unsigned short, std::string > UShortStrBimap
 bimaps to convert from enums <--> strings
 
using RespMetadataT = double
 
typedef void(* dl_core_run_t) (void *, Optimizer1 *, char *)
 
typedef void(* dl_destructor_t) (void **)
 
typedef Teuchos::SerialDenseSolver< int, Real > RealSolver
 
typedef Teuchos::SerialSpdDenseSolver< int, Real > RealSpdSolver
 
typedef int(* start_grid_computing_t) (char *analysis_driver_script, char *params_file, char *results_file)
 definition of start grid computing type (function pointer)
 
typedef int(* perform_analysis_t) (char *iteration_num)
 definition of perform analysis type (function pointer)
 
typedef int *(* get_jobs_completed_t) ()
 definition of get completed jobs type (function pointer)
 
typedef int(* stop_grid_computing_t) ()
 definition of stop grid computing type (function pointer)
 
typedef int MPI_Comm
 
typedef void * MPI_Request
 
typedef unsigned char u_char
 
typedef unsigned short u_short
 
typedef unsigned int u_int
 
typedef unsigned long u_long
 
typedef long long long_long
 
typedef unsigned long UL
 
typedef void(* Calcrj) (int *n, int *p, Real *x, int *nf, Real *r, int *ui, void *ur, Vf vf)
 
typedef void(* Vf) ()
 
typedef void(* DbCallbackFunctionPtr) (Dakota::ProblemDescDB *db, void *data_ptr)
 
typedef boost::tuple< bfs::path, bfs::path, bfs::path > PathTriple
 Triplet of filesystem paths: e.g., params, results, workdir.
 
typedef bmi::multi_index_container< Dakota::ParamResponsePair, bmi::indexed_by< bmi::ordered_non_unique< bmi::tag< ordered >, bmi::const_mem_fun< Dakota::ParamResponsePair, const IntStringPair &, &Dakota::ParamResponsePair::eval_interface_ids > >, bmi::hashed_non_unique< bmi::tag< hashed >, bmi::identity< Dakota::ParamResponsePair >, partial_prp_hash, partial_prp_equality > > > PRPMultiIndexCache
 Boost Multi-Index Container for globally caching ParamResponsePairs. More...
 
typedef PRPMultiIndexCache PRPCache
 
typedef PRPCache::index_iterator< ordered >::type PRPCacheOIter
 
typedef PRPCache::index_const_iterator< ordered >::type PRPCacheOCIter
 
typedef PRPCache::index_iterator< hashed >::type PRPCacheHIter
 
typedef PRPCache::index_const_iterator< hashed >::type PRPCacheHCIter
 
typedef PRPCacheOIter PRPCacheIter
 default cache iterator <0>
 
typedef PRPCacheOCIter PRPCacheCIter
 default cache const iterator <0> default cache const reverse iterator <0>
 
typedef boost::reverse_iterator< PRPCacheCIter > PRPCacheCRevIter
 
typedef bmi::multi_index_container< Dakota::ParamResponsePair, bmi::indexed_by< bmi::ordered_unique< bmi::tag< ordered >, bmi::const_mem_fun< Dakota::ParamResponsePair, int, &Dakota::ParamResponsePair::eval_id > >, bmi::hashed_non_unique< bmi::tag< hashed >, bmi::identity< Dakota::ParamResponsePair >, partial_prp_hash, partial_prp_equality > > > PRPMultiIndexQueue
 Boost Multi-Index Container for locally queueing ParamResponsePairs. More...
 
typedef PRPMultiIndexQueue PRPQueue
 
typedef PRPQueue::index_iterator< ordered >::type PRPQueueOIter
 
typedef PRPQueue::index_const_iterator< ordered >::type PRPQueueOCIter
 
typedef PRPQueue::index_iterator< hashed >::type PRPQueueHIter
 
typedef PRPQueue::index_const_iterator< hashed >::type PRPQueueHCIter
 
typedef PRPQueueOIter PRPQueueIter
 
typedef PRPQueueOCIter PRPQueueCIter
 
typedef std::pair< boost::any, MetaDataType > ResultsValueType
 Core data storage type: boost::any, with optional metadata (see other types in results_types.hpp)
 
typedef boost::function< bool(const bfs::path &src_path, const bfs::path &dest_path, bool overwrite)> file_op_function
 define a function type that operates from src to dest, with option to overwrite
 
typedef boost::filter_iterator< MatchesWC, bfs::directory_iterator > glob_iterator
 a glob_iterator filters a directory_iterator based on a wildcard predicate
 

Enumerations

enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 enum for Dakota abort reasons; using negative numbers to distinguish Dakota exit states from signals / uncaught signals. These need to be in range [-63, -1], so exit code (256+enum) is in [193, 255]. See RATIONALE in dakota_global_defs.cpp.
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 enum for selecting the models that store evaluations More...
 
enum  {
  INTERF_EVAL_STORE_SIMULATION = 0, INTERF_EVAL_STORE_NONE, INTERF_EVAL_STORE_ALL, OBJECTIVE,
  INEQUALITY_CONSTRAINT, EQUALITY_CONSTRAINT, SILENT_OUTPUT, QUIET_OUTPUT,
  NORMAL_OUTPUT, VERBOSE_OUTPUT, DEBUG_OUTPUT, NO_CORRECTION =0,
  ADDITIVE_CORRECTION, MULTIPLICATIVE_CORRECTION, COMBINED_CORRECTION, EMPTY_VIEW =0,
  RELAXED_ALL, MIXED_ALL, RELAXED_DESIGN, RELAXED_UNCERTAIN,
  RELAXED_ALEATORY_UNCERTAIN, RELAXED_EPISTEMIC_UNCERTAIN, RELAXED_STATE, MIXED_DESIGN,
  MIXED_UNCERTAIN, MIXED_ALEATORY_UNCERTAIN, MIXED_EPISTEMIC_UNCERTAIN, MIXED_STATE,
  DAUSVar_histogram_point_str = 0, DAUSVar_Nkinds = 1, NEW_CANDIDATE = 1, CANDIDATE_ACCEPTED = 2,
  CANDIDATE_STATE = (NEW_CANDIDATE | CANDIDATE_ACCEPTED), NEW_CENTER = 8, CENTER_BUILT = 16, CENTER_STATE = (NEW_CENTER | CENTER_BUILT),
  NEW_TR_FACTOR = 64, NEW_TRUST_REGION = (NEW_CENTER | NEW_TR_FACTOR), HARD_CONVERGED = 128, SOFT_CONVERGED = 256,
  MIN_TR_CONVERGED = 512, MAX_ITER_CONVERGED = 1024, CONVERGED
}
 enum for selecting the interfaces that store evaluations
 
enum  {
  ABORT_EXITS, ABORT_THROWS, NO_RESULTS =0, REFINEMENT_RESULTS,
  INTERMEDIATE_RESULTS, FINAL_RESULTS, RF_KARHUNEN_LOEVE =0, RF_PCA_GP,
  RF_ICA, ALL_VARS =0, ACTIVE_VARS, INACTIVE_VARS,
  DAURVar_histogram_point_real = 0, DAURVar_Nkinds = 1
}
 enum for dakota abort behaviors
 
enum  {
  CV_ID_DEFAULT = 0, MINIMUM_METRIC, RELATIVE_TOLERANCE, DECREASE_TOLERANCE,
  DEFAULT_SYNCHRONIZATION =0, BLOCKING_SYNCHRONIZATION, NONBLOCKING_SYNCHRONIZATION, NOCOVAR =0,
  EXP_L2, EXP_L1, EMPTY_TYPE =0, CONTINUOUS_DESIGN,
  DISCRETE_DESIGN_RANGE, DISCRETE_DESIGN_SET_INT, DISCRETE_DESIGN_SET_STRING, DISCRETE_DESIGN_SET_REAL,
  NORMAL_UNCERTAIN, LOGNORMAL_UNCERTAIN, UNIFORM_UNCERTAIN, LOGUNIFORM_UNCERTAIN,
  TRIANGULAR_UNCERTAIN, EXPONENTIAL_UNCERTAIN, BETA_UNCERTAIN, GAMMA_UNCERTAIN,
  GUMBEL_UNCERTAIN, FRECHET_UNCERTAIN, WEIBULL_UNCERTAIN, HISTOGRAM_BIN_UNCERTAIN,
  POISSON_UNCERTAIN, BINOMIAL_UNCERTAIN, NEGATIVE_BINOMIAL_UNCERTAIN, GEOMETRIC_UNCERTAIN,
  HYPERGEOMETRIC_UNCERTAIN, HISTOGRAM_POINT_UNCERTAIN_INT, HISTOGRAM_POINT_UNCERTAIN_STRING, HISTOGRAM_POINT_UNCERTAIN_REAL,
  CONTINUOUS_INTERVAL_UNCERTAIN, DISCRETE_INTERVAL_UNCERTAIN, DISCRETE_UNCERTAIN_SET_INT, DISCRETE_UNCERTAIN_SET_STRING,
  DISCRETE_UNCERTAIN_SET_REAL, CONTINUOUS_STATE, DISCRETE_STATE_RANGE, DISCRETE_STATE_SET_INT,
  DISCRETE_STATE_SET_STRING, DISCRETE_STATE_SET_REAL, CEUVar_interval = 0, CEUVar_Nkinds = 1
}
 enum for active subspace cross validation identification
 
enum  {
  TABULAR_NONE = 0, TABULAR_HEADER = 1, TABULAR_EVAL_ID = 2, TABULAR_IFACE_ID = 4,
  TABULAR_EXPER_ANNOT = TABULAR_HEADER | TABULAR_EVAL_ID, TABULAR_ANNOTATED = TABULAR_HEADER | TABULAR_EVAL_ID | TABULAR_IFACE_ID, DEFAULT_SCHEDULING, MASTER_SCHEDULING,
  PEER_SCHEDULING, PEER_DYNAMIC_SCHEDULING, PEER_STATIC_SCHEDULING, DYNAMIC_SCHEDULING,
  STATIC_SCHEDULING, SUBSPACE_NORM_DEFAULT =0, SUBSPACE_NORM_MEAN_VALUE, SUBSPACE_NORM_MEAN_GRAD,
  SUBSPACE_NORM_LOCAL_GRAD, TOTAL_CDV =0, TOTAL_DDIV, TOTAL_DDSV,
  TOTAL_DDRV, TOTAL_CAUV, TOTAL_DAUIV, TOTAL_DAUSV,
  TOTAL_DAURV, TOTAL_CEUV, TOTAL_DEUIV, TOTAL_DEUSV,
  TOTAL_DEURV, TOTAL_CSV, TOTAL_DSIV, TOTAL_DSSV,
  TOTAL_DSRV, NUM_VC_TOTALS, DEUIVar_interval = 0, DEUIVar_set_int = 1,
  DEUIVar_Nkinds = 2
}
 options for tabular columns
 
enum  {
  RESULTS_OUTPUT_TEXT = 1, RESULTS_OUTPUT_HDF5 = 2, DEFAULT_CONFIG, PUSH_DOWN,
  PUSH_UP, ROTATION_METHOD_UNRANKED, ROTATION_METHOD_RANKED, DEUSVar_set_str = 0,
  DEUSVar_Nkinds = 1
}
 Results output format.
 
enum  {
  FLEXIBLE_RESULTS, LABELED_RESULTS, STD_NORMAL_U, STD_UNIFORM_U,
  PARTIAL_ASKEY_U, ASKEY_U, EXTENDED_U, NO_PARALLEL_MODE =0,
  SURROGATE_MODEL_MODE, TRUTH_MODEL_MODE, SUB_MODEL_MODE, INTERFACE_MODE,
  DEURVar_set_real = 0, DEURVar_Nkinds = 1
}
 options for results file format
 
enum  {
  NO_MODEL_FORMAT =0, TEXT_ARCHIVE =1, BINARY_ARCHIVE =2, ALGEBRAIC_FILE =4,
  ALGEBRAIC_CONSOLE =8, DEFAULT_COVARIANCE, NO_COVARIANCE, DIAGONAL_COVARIANCE,
  FULL_COVARIANCE, NO_DERIVS =0, ALL_DERIVS, MIXED_DERIVS,
  DiscSetVar_design_set_int = 0, DiscSetVar_design_set_str = 1, DiscSetVar_design_set_real = 2, DiscSetVar_state_set_int = 3,
  DiscSetVar_state_set_str = 4, DiscSetVar_state_set_real = 5, DiscSetVar_Nkinds = 6
}
 define special values for surrogateExportFormats
 
enum  ScaleScope { SHARED, UNSHARED }
 Enum to specify whether a scale shared among responses.
 
enum  ResultsOutputType { REAL, INTEGER, UINTEGER, STRING }
 enum for setting type on allocted matrix for Results Output
 
enum  CONSTRAINT_TYPE { LINEAR, NONLINEAR }
 
enum  CONSTRAINT_EQUALITY_TYPE { EQUALITY, INEQUALITY }
 
enum  LINEAR_INEQUALITY_FORMAT { NONE, TWO_SIDED, ONE_SIDED_LOWER, ONE_SIDED_UPPER }
 
enum  NONLINEAR_EQUALITY_FORMAT { NONE, TRUE_EQUALITY, TWO_INEQUALITY }
 
enum  NONLINEAR_INEQUALITY_FORMAT { NONE, ONE_SIDED_UPPER, ONE_SIDED_LOWER, TWO_SIDED }
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 special values for interface type
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 interface synchronization types More...
 
enum  {
  INTERF_EVAL_STORE_SIMULATION = 0, INTERF_EVAL_STORE_NONE, INTERF_EVAL_STORE_ALL, OBJECTIVE,
  INEQUALITY_CONSTRAINT, EQUALITY_CONSTRAINT, SILENT_OUTPUT, QUIET_OUTPUT,
  NORMAL_OUTPUT, VERBOSE_OUTPUT, DEBUG_OUTPUT, NO_CORRECTION =0,
  ADDITIVE_CORRECTION, MULTIPLICATIVE_CORRECTION, COMBINED_CORRECTION, EMPTY_VIEW =0,
  RELAXED_ALL, MIXED_ALL, RELAXED_DESIGN, RELAXED_UNCERTAIN,
  RELAXED_ALEATORY_UNCERTAIN, RELAXED_EPISTEMIC_UNCERTAIN, RELAXED_STATE, MIXED_DESIGN,
  MIXED_UNCERTAIN, MIXED_ALEATORY_UNCERTAIN, MIXED_EPISTEMIC_UNCERTAIN, MIXED_STATE,
  DAUSVar_histogram_point_str = 0, DAUSVar_Nkinds = 1, NEW_CANDIDATE = 1, CANDIDATE_ACCEPTED = 2,
  CANDIDATE_STATE = (NEW_CANDIDATE | CANDIDATE_ACCEPTED), NEW_CENTER = 8, CENTER_BUILT = 16, CENTER_STATE = (NEW_CENTER | CENTER_BUILT),
  NEW_TR_FACTOR = 64, NEW_TRUST_REGION = (NEW_CENTER | NEW_TR_FACTOR), HARD_CONVERGED = 128, SOFT_CONVERGED = 256,
  MIN_TR_CONVERGED = 512, MAX_ITER_CONVERGED = 1024, CONVERGED
}
 define algebraic function types
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 Sub-methods, including sampling, inference algorithm, opt algorithm types. More...
 
enum  {
  INTERF_EVAL_STORE_SIMULATION = 0, INTERF_EVAL_STORE_NONE, INTERF_EVAL_STORE_ALL, OBJECTIVE,
  INEQUALITY_CONSTRAINT, EQUALITY_CONSTRAINT, SILENT_OUTPUT, QUIET_OUTPUT,
  NORMAL_OUTPUT, VERBOSE_OUTPUT, DEBUG_OUTPUT, NO_CORRECTION =0,
  ADDITIVE_CORRECTION, MULTIPLICATIVE_CORRECTION, COMBINED_CORRECTION, EMPTY_VIEW =0,
  RELAXED_ALL, MIXED_ALL, RELAXED_DESIGN, RELAXED_UNCERTAIN,
  RELAXED_ALEATORY_UNCERTAIN, RELAXED_EPISTEMIC_UNCERTAIN, RELAXED_STATE, MIXED_DESIGN,
  MIXED_UNCERTAIN, MIXED_ALEATORY_UNCERTAIN, MIXED_EPISTEMIC_UNCERTAIN, MIXED_STATE,
  DAUSVar_histogram_point_str = 0, DAUSVar_Nkinds = 1, NEW_CANDIDATE = 1, CANDIDATE_ACCEPTED = 2,
  CANDIDATE_STATE = (NEW_CANDIDATE | CANDIDATE_ACCEPTED), NEW_CENTER = 8, CENTER_BUILT = 16, CENTER_STATE = (NEW_CENTER | CENTER_BUILT),
  NEW_TR_FACTOR = 64, NEW_TRUST_REGION = (NEW_CENTER | NEW_TR_FACTOR), HARD_CONVERGED = 128, SOFT_CONVERGED = 256,
  MIN_TR_CONVERGED = 512, MAX_ITER_CONVERGED = 1024, CONVERGED
}
 
enum  {
  ABORT_EXITS, ABORT_THROWS, NO_RESULTS =0, REFINEMENT_RESULTS,
  INTERMEDIATE_RESULTS, FINAL_RESULTS, RF_KARHUNEN_LOEVE =0, RF_PCA_GP,
  RF_ICA, ALL_VARS =0, ACTIVE_VARS, INACTIVE_VARS,
  DAURVar_histogram_point_real = 0, DAURVar_Nkinds = 1
}
 
enum  {
  CV_ID_DEFAULT = 0, MINIMUM_METRIC, RELATIVE_TOLERANCE, DECREASE_TOLERANCE,
  DEFAULT_SYNCHRONIZATION =0, BLOCKING_SYNCHRONIZATION, NONBLOCKING_SYNCHRONIZATION, NOCOVAR =0,
  EXP_L2, EXP_L1, EMPTY_TYPE =0, CONTINUOUS_DESIGN,
  DISCRETE_DESIGN_RANGE, DISCRETE_DESIGN_SET_INT, DISCRETE_DESIGN_SET_STRING, DISCRETE_DESIGN_SET_REAL,
  NORMAL_UNCERTAIN, LOGNORMAL_UNCERTAIN, UNIFORM_UNCERTAIN, LOGUNIFORM_UNCERTAIN,
  TRIANGULAR_UNCERTAIN, EXPONENTIAL_UNCERTAIN, BETA_UNCERTAIN, GAMMA_UNCERTAIN,
  GUMBEL_UNCERTAIN, FRECHET_UNCERTAIN, WEIBULL_UNCERTAIN, HISTOGRAM_BIN_UNCERTAIN,
  POISSON_UNCERTAIN, BINOMIAL_UNCERTAIN, NEGATIVE_BINOMIAL_UNCERTAIN, GEOMETRIC_UNCERTAIN,
  HYPERGEOMETRIC_UNCERTAIN, HISTOGRAM_POINT_UNCERTAIN_INT, HISTOGRAM_POINT_UNCERTAIN_STRING, HISTOGRAM_POINT_UNCERTAIN_REAL,
  CONTINUOUS_INTERVAL_UNCERTAIN, DISCRETE_INTERVAL_UNCERTAIN, DISCRETE_UNCERTAIN_SET_INT, DISCRETE_UNCERTAIN_SET_STRING,
  DISCRETE_UNCERTAIN_SET_REAL, CONTINUOUS_STATE, DISCRETE_STATE_RANGE, DISCRETE_STATE_SET_INT,
  DISCRETE_STATE_SET_STRING, DISCRETE_STATE_SET_REAL, CEUVar_interval = 0, CEUVar_Nkinds = 1
}
 
enum  {
  TABULAR_NONE = 0, TABULAR_HEADER = 1, TABULAR_EVAL_ID = 2, TABULAR_IFACE_ID = 4,
  TABULAR_EXPER_ANNOT = TABULAR_HEADER | TABULAR_EVAL_ID, TABULAR_ANNOTATED = TABULAR_HEADER | TABULAR_EVAL_ID | TABULAR_IFACE_ID, DEFAULT_SCHEDULING, MASTER_SCHEDULING,
  PEER_SCHEDULING, PEER_DYNAMIC_SCHEDULING, PEER_STATIC_SCHEDULING, DYNAMIC_SCHEDULING,
  STATIC_SCHEDULING, SUBSPACE_NORM_DEFAULT =0, SUBSPACE_NORM_MEAN_VALUE, SUBSPACE_NORM_MEAN_GRAD,
  SUBSPACE_NORM_LOCAL_GRAD, TOTAL_CDV =0, TOTAL_DDIV, TOTAL_DDSV,
  TOTAL_DDRV, TOTAL_CAUV, TOTAL_DAUIV, TOTAL_DAUSV,
  TOTAL_DAURV, TOTAL_CEUV, TOTAL_DEUIV, TOTAL_DEUSV,
  TOTAL_DEURV, TOTAL_CSV, TOTAL_DSIV, TOTAL_DSSV,
  TOTAL_DSRV, NUM_VC_TOTALS, DEUIVar_interval = 0, DEUIVar_set_int = 1,
  DEUIVar_Nkinds = 2
}
 
enum  {
  RESULTS_OUTPUT_TEXT = 1, RESULTS_OUTPUT_HDF5 = 2, DEFAULT_CONFIG, PUSH_DOWN,
  PUSH_UP, ROTATION_METHOD_UNRANKED, ROTATION_METHOD_RANKED, DEUSVar_set_str = 0,
  DEUSVar_Nkinds = 1
}
 
enum  {
  FLEXIBLE_RESULTS, LABELED_RESULTS, STD_NORMAL_U, STD_UNIFORM_U,
  PARTIAL_ASKEY_U, ASKEY_U, EXTENDED_U, NO_PARALLEL_MODE =0,
  SURROGATE_MODEL_MODE, TRUTH_MODEL_MODE, SUB_MODEL_MODE, INTERFACE_MODE,
  DEURVar_set_real = 0, DEURVar_Nkinds = 1
}
 
enum  {
  NO_MODEL_FORMAT =0, TEXT_ARCHIVE =1, BINARY_ARCHIVE =2, ALGEBRAIC_FILE =4,
  ALGEBRAIC_CONSOLE =8, DEFAULT_COVARIANCE, NO_COVARIANCE, DIAGONAL_COVARIANCE,
  FULL_COVARIANCE, NO_DERIVS =0, ALL_DERIVS, MIXED_DERIVS,
  DiscSetVar_design_set_int = 0, DiscSetVar_design_set_str = 1, DiscSetVar_design_set_real = 2, DiscSetVar_state_set_int = 3,
  DiscSetVar_state_set_str = 4, DiscSetVar_state_set_real = 5, DiscSetVar_Nkinds = 6
}
 
enum  {
  NO_INT_REFINE =0, IS, AIS, MMAIS,
  FT_LS, FT_RLS2, NUM_UNC_REAL_CONT = 4
}
 
enum  {
  PROBABILITIES, RELIABILITIES, GEN_RELIABILITIES, NO_C3_ADVANCEMENT =0,
  START_RANK_ADVANCEMENT, START_ORDER_ADVANCEMENT, MAX_RANK_ADVANCEMENT, MAX_ORDER_ADVANCEMENT,
  MAX_RANK_ORDER_ADVANCEMENT, NUM_UNC_INT_CONT = 2
}
 
enum  { COMPONENT =0, SYSTEM_SERIES, SYSTEM_PARALLEL, NUM_UNC_STR_CONT = 2 }
 
enum  { CUMULATIVE, COMPLEMENTARY }
 
enum  { DEFAULT_LS =0, SVD_LS, EQ_CON_LS }
 
enum  {
  DEFAULT_MLMF_CONTROL =0, ESTIMATOR_VARIANCE, RIP_SAMPLING, RANK_SAMPLING,
  GREEDY_REFINEMENT
}
 
enum  { DEFAULT_EMULATION, DISTINCT_EMULATION, RECURSIVE_EMULATION }
 
enum  {
  NO_EMULATOR, PCE_EMULATOR, ML_PCE_EMULATOR, MF_PCE_EMULATOR,
  SC_EMULATOR, MF_SC_EMULATOR, GP_EMULATOR, KRIGING_EMULATOR,
  EXPGP_EMULATOR, VPS_EMULATOR
}
 
enum  {
  CALIBRATE_NONE = 0, CALIBRATE_ONE, CALIBRATE_PER_EXPER, CALIBRATE_PER_RESP,
  CALIBRATE_BOTH
}
 
enum  { IGNORE_RANKS, SET_RANKS, GET_RANKS, SET_GET_RANKS }
 
enum  {
  DESIGN, UNCERTAIN, UNCERTAIN_UNIFORM, ALEATORY_UNCERTAIN,
  ALEATORY_UNCERTAIN_UNIFORM, EPISTEMIC_UNCERTAIN, EPISTEMIC_UNCERTAIN_UNIFORM, STATE,
  ACTIVE, ACTIVE_UNIFORM, ALL, ALL_UNIFORM
}
 
enum  {
  ONE_SIDED_LOWER, ONE_SIDED_UPPER, NONE, TWO_SIDED,
  ONE_SIDED_LOWER, ONE_SIDED_UPPER, TWO_SIDED, NONE,
  ONE_SIDED_UPPER, ONE_SIDED_LOWER, TWO_SIDED
}
 
enum  { NO_FINAL_STATS =0, QOI_STATISTICS, ESTIMATOR_PERFORMANCE }
 
enum  { QOI_AGGREGATION_MAX, QOI_AGGREGATION_SUM }
 
enum  { TARGET_MEAN, TARGET_VARIANCE, TARGET_SIGMA, TARGET_SCALARIZATION }
 
enum  { CONVERGENCE_TOLERANCE_TYPE_RELATIVE, CONVERGENCE_TOLERANCE_TYPE_ABSOLUTE }
 
enum  { CONVERGENCE_TOLERANCE_TARGET_VARIANCE_CONSTRAINT, CONVERGENCE_TOLERANCE_TARGET_COST_CONSTRAINT }
 
enum  { ONLINE_PILOT, OFFLINE_PILOT, PILOT_PROJECTION }
 
enum  { REORDERED_FALLBACK, NUMERICAL_FALLBACK, NUMERICAL_OVERRIDE }
 
enum  { BREITUNG, HOHENRACK, HONG }
 
enum  { ORIGINAL_PRIMARY, SINGLE_OBJECTIVE, LAGRANGIAN_OBJECTIVE, AUGMENTED_LAGRANGIAN_OBJECTIVE }
 
enum  { NO_CONSTRAINTS, LINEARIZED_CONSTRAINTS, ORIGINAL_CONSTRAINTS }
 
enum  { NO_RELAX, HOMOTOPY, COMPOSITE_STEP }
 
enum  { PENALTY_MERIT, ADAPTIVE_PENALTY_MERIT, LAGRANGIAN_MERIT, AUGMENTED_LAGRANGIAN_MERIT }
 
enum  { FILTER, TR_RATIO }
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 define special values for pointsManagement
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 define special values for SurrogateModel::responseMode More...
 
enum  {
  INTERF_EVAL_STORE_SIMULATION = 0, INTERF_EVAL_STORE_NONE, INTERF_EVAL_STORE_ALL, OBJECTIVE,
  INEQUALITY_CONSTRAINT, EQUALITY_CONSTRAINT, SILENT_OUTPUT, QUIET_OUTPUT,
  NORMAL_OUTPUT, VERBOSE_OUTPUT, DEBUG_OUTPUT, NO_CORRECTION =0,
  ADDITIVE_CORRECTION, MULTIPLICATIVE_CORRECTION, COMBINED_CORRECTION, EMPTY_VIEW =0,
  RELAXED_ALL, MIXED_ALL, RELAXED_DESIGN, RELAXED_UNCERTAIN,
  RELAXED_ALEATORY_UNCERTAIN, RELAXED_EPISTEMIC_UNCERTAIN, RELAXED_STATE, MIXED_DESIGN,
  MIXED_UNCERTAIN, MIXED_ALEATORY_UNCERTAIN, MIXED_EPISTEMIC_UNCERTAIN, MIXED_STATE,
  DAUSVar_histogram_point_str = 0, DAUSVar_Nkinds = 1, NEW_CANDIDATE = 1, CANDIDATE_ACCEPTED = 2,
  CANDIDATE_STATE = (NEW_CANDIDATE | CANDIDATE_ACCEPTED), NEW_CENTER = 8, CENTER_BUILT = 16, CENTER_STATE = (NEW_CENTER | CENTER_BUILT),
  NEW_TR_FACTOR = 64, NEW_TRUST_REGION = (NEW_CENTER | NEW_TR_FACTOR), HARD_CONVERGED = 128, SOFT_CONVERGED = 256,
  MIN_TR_CONVERGED = 512, MAX_ITER_CONVERGED = 1024, CONVERGED
}
 define special values for approxCorrectionType
 
enum  {
  ABORT_EXITS, ABORT_THROWS, NO_RESULTS =0, REFINEMENT_RESULTS,
  INTERMEDIATE_RESULTS, FINAL_RESULTS, RF_KARHUNEN_LOEVE =0, RF_PCA_GP,
  RF_ICA, ALL_VARS =0, ACTIVE_VARS, INACTIVE_VARS,
  DAURVar_histogram_point_real = 0, DAURVar_Nkinds = 1
}
 define types of random field approximations
 
enum  {
  CV_ID_DEFAULT = 0, MINIMUM_METRIC, RELATIVE_TOLERANCE, DECREASE_TOLERANCE,
  DEFAULT_SYNCHRONIZATION =0, BLOCKING_SYNCHRONIZATION, NONBLOCKING_SYNCHRONIZATION, NOCOVAR =0,
  EXP_L2, EXP_L1, EMPTY_TYPE =0, CONTINUOUS_DESIGN,
  DISCRETE_DESIGN_RANGE, DISCRETE_DESIGN_SET_INT, DISCRETE_DESIGN_SET_STRING, DISCRETE_DESIGN_SET_REAL,
  NORMAL_UNCERTAIN, LOGNORMAL_UNCERTAIN, UNIFORM_UNCERTAIN, LOGUNIFORM_UNCERTAIN,
  TRIANGULAR_UNCERTAIN, EXPONENTIAL_UNCERTAIN, BETA_UNCERTAIN, GAMMA_UNCERTAIN,
  GUMBEL_UNCERTAIN, FRECHET_UNCERTAIN, WEIBULL_UNCERTAIN, HISTOGRAM_BIN_UNCERTAIN,
  POISSON_UNCERTAIN, BINOMIAL_UNCERTAIN, NEGATIVE_BINOMIAL_UNCERTAIN, GEOMETRIC_UNCERTAIN,
  HYPERGEOMETRIC_UNCERTAIN, HISTOGRAM_POINT_UNCERTAIN_INT, HISTOGRAM_POINT_UNCERTAIN_STRING, HISTOGRAM_POINT_UNCERTAIN_REAL,
  CONTINUOUS_INTERVAL_UNCERTAIN, DISCRETE_INTERVAL_UNCERTAIN, DISCRETE_UNCERTAIN_SET_INT, DISCRETE_UNCERTAIN_SET_STRING,
  DISCRETE_UNCERTAIN_SET_REAL, CONTINUOUS_STATE, DISCRETE_STATE_RANGE, DISCRETE_STATE_SET_INT,
  DISCRETE_STATE_SET_STRING, DISCRETE_STATE_SET_REAL, CEUVar_interval = 0, CEUVar_Nkinds = 1
}
 define types of analytic covariance functions
 
enum  {
  TABULAR_NONE = 0, TABULAR_HEADER = 1, TABULAR_EVAL_ID = 2, TABULAR_IFACE_ID = 4,
  TABULAR_EXPER_ANNOT = TABULAR_HEADER | TABULAR_EVAL_ID, TABULAR_ANNOTATED = TABULAR_HEADER | TABULAR_EVAL_ID | TABULAR_IFACE_ID, DEFAULT_SCHEDULING, MASTER_SCHEDULING,
  PEER_SCHEDULING, PEER_DYNAMIC_SCHEDULING, PEER_STATIC_SCHEDULING, DYNAMIC_SCHEDULING,
  STATIC_SCHEDULING, SUBSPACE_NORM_DEFAULT =0, SUBSPACE_NORM_MEAN_VALUE, SUBSPACE_NORM_MEAN_GRAD,
  SUBSPACE_NORM_LOCAL_GRAD, TOTAL_CDV =0, TOTAL_DDIV, TOTAL_DDSV,
  TOTAL_DDRV, TOTAL_CAUV, TOTAL_DAUIV, TOTAL_DAUSV,
  TOTAL_DAURV, TOTAL_CEUV, TOTAL_DEUIV, TOTAL_DEUSV,
  TOTAL_DEURV, TOTAL_CSV, TOTAL_DSIV, TOTAL_DSSV,
  TOTAL_DSRV, NUM_VC_TOTALS, DEUIVar_interval = 0, DEUIVar_set_int = 1,
  DEUIVar_Nkinds = 2
}
 define special values for active subspace normalizations
 
enum  {
  RESULTS_OUTPUT_TEXT = 1, RESULTS_OUTPUT_HDF5 = 2, DEFAULT_CONFIG, PUSH_DOWN,
  PUSH_UP, ROTATION_METHOD_UNRANKED, ROTATION_METHOD_RANKED, DEUSVar_set_str = 0,
  DEUSVar_Nkinds = 1
}
 
enum  {
  FLEXIBLE_RESULTS, LABELED_RESULTS, STD_NORMAL_U, STD_UNIFORM_U,
  PARTIAL_ASKEY_U, ASKEY_U, EXTENDED_U, NO_PARALLEL_MODE =0,
  SURROGATE_MODEL_MODE, TRUTH_MODEL_MODE, SUB_MODEL_MODE, INTERFACE_MODE,
  DEURVar_set_real = 0, DEURVar_Nkinds = 1
}
 define special values for componentParallelMode (active model for parallel scheduling)
 
enum  {
  NO_MODEL_FORMAT =0, TEXT_ARCHIVE =1, BINARY_ARCHIVE =2, ALGEBRAIC_FILE =4,
  ALGEBRAIC_CONSOLE =8, DEFAULT_COVARIANCE, NO_COVARIANCE, DIAGONAL_COVARIANCE,
  FULL_COVARIANCE, NO_DERIVS =0, ALL_DERIVS, MIXED_DERIVS,
  DiscSetVar_design_set_int = 0, DiscSetVar_design_set_str = 1, DiscSetVar_design_set_real = 2, DiscSetVar_state_set_int = 3,
  DiscSetVar_state_set_str = 4, DiscSetVar_state_set_real = 5, DiscSetVar_Nkinds = 6
}
 define special values for distParamDerivs
 
enum  {
  NO_INT_REFINE =0, IS, AIS, MMAIS,
  FT_LS, FT_RLS2, NUM_UNC_REAL_CONT = 4
}
 
enum  {
  PROBABILITIES, RELIABILITIES, GEN_RELIABILITIES, NO_C3_ADVANCEMENT =0,
  START_RANK_ADVANCEMENT, START_ORDER_ADVANCEMENT, MAX_RANK_ADVANCEMENT, MAX_ORDER_ADVANCEMENT,
  MAX_RANK_ORDER_ADVANCEMENT, NUM_UNC_INT_CONT = 2
}
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 special values for derived Response type
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 values for primary response types More...
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 
enum  {
  INTERF_EVAL_STORE_SIMULATION = 0, INTERF_EVAL_STORE_NONE, INTERF_EVAL_STORE_ALL, OBJECTIVE,
  INEQUALITY_CONSTRAINT, EQUALITY_CONSTRAINT, SILENT_OUTPUT, QUIET_OUTPUT,
  NORMAL_OUTPUT, VERBOSE_OUTPUT, DEBUG_OUTPUT, NO_CORRECTION =0,
  ADDITIVE_CORRECTION, MULTIPLICATIVE_CORRECTION, COMBINED_CORRECTION, EMPTY_VIEW =0,
  RELAXED_ALL, MIXED_ALL, RELAXED_DESIGN, RELAXED_UNCERTAIN,
  RELAXED_ALEATORY_UNCERTAIN, RELAXED_EPISTEMIC_UNCERTAIN, RELAXED_STATE, MIXED_DESIGN,
  MIXED_UNCERTAIN, MIXED_ALEATORY_UNCERTAIN, MIXED_EPISTEMIC_UNCERTAIN, MIXED_STATE,
  DAUSVar_histogram_point_str = 0, DAUSVar_Nkinds = 1, NEW_CANDIDATE = 1, CANDIDATE_ACCEPTED = 2,
  CANDIDATE_STATE = (NEW_CANDIDATE | CANDIDATE_ACCEPTED), NEW_CENTER = 8, CENTER_BUILT = 16, CENTER_STATE = (NEW_CENTER | CENTER_BUILT),
  NEW_TR_FACTOR = 64, NEW_TRUST_REGION = (NEW_CENTER | NEW_TR_FACTOR), HARD_CONVERGED = 128, SOFT_CONVERGED = 256,
  MIN_TR_CONVERGED = 512, MAX_ITER_CONVERGED = 1024, CONVERGED
}
 
enum  {
  ABORT_EXITS, ABORT_THROWS, NO_RESULTS =0, REFINEMENT_RESULTS,
  INTERMEDIATE_RESULTS, FINAL_RESULTS, RF_KARHUNEN_LOEVE =0, RF_PCA_GP,
  RF_ICA, ALL_VARS =0, ACTIVE_VARS, INACTIVE_VARS,
  DAURVar_histogram_point_real = 0, DAURVar_Nkinds = 1
}
 values differentiating subsets of variables for I/O
 
enum  {
  CV_ID_DEFAULT = 0, MINIMUM_METRIC, RELATIVE_TOLERANCE, DECREASE_TOLERANCE,
  DEFAULT_SYNCHRONIZATION =0, BLOCKING_SYNCHRONIZATION, NONBLOCKING_SYNCHRONIZATION, NOCOVAR =0,
  EXP_L2, EXP_L1, EMPTY_TYPE =0, CONTINUOUS_DESIGN,
  DISCRETE_DESIGN_RANGE, DISCRETE_DESIGN_SET_INT, DISCRETE_DESIGN_SET_STRING, DISCRETE_DESIGN_SET_REAL,
  NORMAL_UNCERTAIN, LOGNORMAL_UNCERTAIN, UNIFORM_UNCERTAIN, LOGUNIFORM_UNCERTAIN,
  TRIANGULAR_UNCERTAIN, EXPONENTIAL_UNCERTAIN, BETA_UNCERTAIN, GAMMA_UNCERTAIN,
  GUMBEL_UNCERTAIN, FRECHET_UNCERTAIN, WEIBULL_UNCERTAIN, HISTOGRAM_BIN_UNCERTAIN,
  POISSON_UNCERTAIN, BINOMIAL_UNCERTAIN, NEGATIVE_BINOMIAL_UNCERTAIN, GEOMETRIC_UNCERTAIN,
  HYPERGEOMETRIC_UNCERTAIN, HISTOGRAM_POINT_UNCERTAIN_INT, HISTOGRAM_POINT_UNCERTAIN_STRING, HISTOGRAM_POINT_UNCERTAIN_REAL,
  CONTINUOUS_INTERVAL_UNCERTAIN, DISCRETE_INTERVAL_UNCERTAIN, DISCRETE_UNCERTAIN_SET_INT, DISCRETE_UNCERTAIN_SET_STRING,
  DISCRETE_UNCERTAIN_SET_REAL, CONTINUOUS_STATE, DISCRETE_STATE_RANGE, DISCRETE_STATE_SET_INT,
  DISCRETE_STATE_SET_STRING, DISCRETE_STATE_SET_REAL, CEUVar_interval = 0, CEUVar_Nkinds = 1
}
 
enum  {
  TABULAR_NONE = 0, TABULAR_HEADER = 1, TABULAR_EVAL_ID = 2, TABULAR_IFACE_ID = 4,
  TABULAR_EXPER_ANNOT = TABULAR_HEADER | TABULAR_EVAL_ID, TABULAR_ANNOTATED = TABULAR_HEADER | TABULAR_EVAL_ID | TABULAR_IFACE_ID, DEFAULT_SCHEDULING, MASTER_SCHEDULING,
  PEER_SCHEDULING, PEER_DYNAMIC_SCHEDULING, PEER_STATIC_SCHEDULING, DYNAMIC_SCHEDULING,
  STATIC_SCHEDULING, SUBSPACE_NORM_DEFAULT =0, SUBSPACE_NORM_MEAN_VALUE, SUBSPACE_NORM_MEAN_GRAD,
  SUBSPACE_NORM_LOCAL_GRAD, TOTAL_CDV =0, TOTAL_DDIV, TOTAL_DDSV,
  TOTAL_DDRV, TOTAL_CAUV, TOTAL_DAUIV, TOTAL_DAUSV,
  TOTAL_DAURV, TOTAL_CEUV, TOTAL_DEUIV, TOTAL_DEUSV,
  TOTAL_DEURV, TOTAL_CSV, TOTAL_DSIV, TOTAL_DSSV,
  TOTAL_DSRV, NUM_VC_TOTALS, DEUIVar_interval = 0, DEUIVar_set_int = 1,
  DEUIVar_Nkinds = 2
}
 
enum  var_t {
  VAR_x1, VAR_x2, VAR_x3, VAR_b,
  VAR_h, VAR_P, VAR_M, VAR_Y,
  VAR_w, VAR_t, VAR_R, VAR_E,
  VAR_X, VAR_area_type, VAR_Fs, VAR_P1,
  VAR_P2, VAR_P3, VAR_B, VAR_D,
  VAR_H, VAR_F0, VAR_d, VAR_MForm,
  VAR_x, VAR_xi, VAR_Af, VAR_Ac,
  VAR_y, VAR_theta, VAR_theta1, VAR_theta2,
  VAR_delta, VAR_gamma
}
 enumeration of possible variable types (to index to names)
 
enum  driver_t {
  NO_DRIVER =0, CANTILEVER_BEAM, MOD_CANTILEVER_BEAM, CANTILEVER_BEAM_ML,
  CYLINDER_HEAD, EXTENDED_ROSENBROCK, GENERALIZED_ROSENBROCK, LF_ROSENBROCK,
  EXTRA_LF_ROSENBROCK, MF_ROSENBROCK, MODIFIED_ROSENBROCK, ROSENBROCK,
  LF_POLY_PROD, POLY_PROD, GERSTNER, SCALABLE_GERSTNER,
  LOGNORMAL_RATIO, MULTIMODAL, PLUGIN_ROSENBROCK, PLUGIN_TEXT_BOOK,
  SHORT_COLUMN, LF_SHORT_COLUMN, MF_SHORT_COLUMN, SIDE_IMPACT_COST,
  SIDE_IMPACT_PERFORMANCE, SOBOL_RATIONAL, SOBOL_G_FUNCTION, SOBOL_ISHIGAMI,
  STEEL_COLUMN_COST, STEEL_COLUMN_PERFORMANCE, TEXT_BOOK, TEXT_BOOK1,
  TEXT_BOOK2, TEXT_BOOK3, TEXT_BOOK_OUU, SCALABLE_TEXT_BOOK,
  SCALABLE_MONOMIALS, MOGATEST1, MOGATEST2, MOGATEST3,
  ILLUMINATION, BARNES, BARNES_LF, HERBIE,
  SMOOTH_HERBIE, SHUBERT, SALINAS, MODELCENTER,
  GENZ, DAMPED_OSCILLATOR, ANISOTROPIC_QUADRATIC_FORM, BAYES_LINEAR,
  STEADY_STATE_DIFFUSION_1D, SS_DIFFUSION_DISCREPANCY, TRANSIENT_DIFFUSION_1D, PREDATOR_PREY,
  PROBLEM18, TUNABLE_MODEL
}
 enumeration of possible direct driver types (to index to names)
 
enum  local_data_t { VARIABLES_MAP =1, VARIABLES_VECTOR =2 }
 enumeration for how local variables are stored (values must employ a bit representation)
 
enum  sigtype { NO_SIGMA, SCALAR_SIGMA, DIAGONAL_SIGMA, MATRIX_SIGMA }
 special values for sigmaType
 
enum  edtype { SCALAR_DATA, FUNCTIONAL_DATA }
 special values for experimental data type
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 
enum  {
  INTERF_EVAL_STORE_SIMULATION = 0, INTERF_EVAL_STORE_NONE, INTERF_EVAL_STORE_ALL, OBJECTIVE,
  INEQUALITY_CONSTRAINT, EQUALITY_CONSTRAINT, SILENT_OUTPUT, QUIET_OUTPUT,
  NORMAL_OUTPUT, VERBOSE_OUTPUT, DEBUG_OUTPUT, NO_CORRECTION =0,
  ADDITIVE_CORRECTION, MULTIPLICATIVE_CORRECTION, COMBINED_CORRECTION, EMPTY_VIEW =0,
  RELAXED_ALL, MIXED_ALL, RELAXED_DESIGN, RELAXED_UNCERTAIN,
  RELAXED_ALEATORY_UNCERTAIN, RELAXED_EPISTEMIC_UNCERTAIN, RELAXED_STATE, MIXED_DESIGN,
  MIXED_UNCERTAIN, MIXED_ALEATORY_UNCERTAIN, MIXED_EPISTEMIC_UNCERTAIN, MIXED_STATE,
  DAUSVar_histogram_point_str = 0, DAUSVar_Nkinds = 1, NEW_CANDIDATE = 1, CANDIDATE_ACCEPTED = 2,
  CANDIDATE_STATE = (NEW_CANDIDATE | CANDIDATE_ACCEPTED), NEW_CENTER = 8, CENTER_BUILT = 16, CENTER_STATE = (NEW_CENTER | CENTER_BUILT),
  NEW_TR_FACTOR = 64, NEW_TRUST_REGION = (NEW_CENTER | NEW_TR_FACTOR), HARD_CONVERGED = 128, SOFT_CONVERGED = 256,
  MIN_TR_CONVERGED = 512, MAX_ITER_CONVERGED = 1024, CONVERGED
}
 
enum  {
  ABORT_EXITS, ABORT_THROWS, NO_RESULTS =0, REFINEMENT_RESULTS,
  INTERMEDIATE_RESULTS, FINAL_RESULTS, RF_KARHUNEN_LOEVE =0, RF_PCA_GP,
  RF_ICA, ALL_VARS =0, ACTIVE_VARS, INACTIVE_VARS,
  DAURVar_histogram_point_real = 0, DAURVar_Nkinds = 1
}
 
enum  {
  CV_ID_DEFAULT = 0, MINIMUM_METRIC, RELATIVE_TOLERANCE, DECREASE_TOLERANCE,
  DEFAULT_SYNCHRONIZATION =0, BLOCKING_SYNCHRONIZATION, NONBLOCKING_SYNCHRONIZATION, NOCOVAR =0,
  EXP_L2, EXP_L1, EMPTY_TYPE =0, CONTINUOUS_DESIGN,
  DISCRETE_DESIGN_RANGE, DISCRETE_DESIGN_SET_INT, DISCRETE_DESIGN_SET_STRING, DISCRETE_DESIGN_SET_REAL,
  NORMAL_UNCERTAIN, LOGNORMAL_UNCERTAIN, UNIFORM_UNCERTAIN, LOGUNIFORM_UNCERTAIN,
  TRIANGULAR_UNCERTAIN, EXPONENTIAL_UNCERTAIN, BETA_UNCERTAIN, GAMMA_UNCERTAIN,
  GUMBEL_UNCERTAIN, FRECHET_UNCERTAIN, WEIBULL_UNCERTAIN, HISTOGRAM_BIN_UNCERTAIN,
  POISSON_UNCERTAIN, BINOMIAL_UNCERTAIN, NEGATIVE_BINOMIAL_UNCERTAIN, GEOMETRIC_UNCERTAIN,
  HYPERGEOMETRIC_UNCERTAIN, HISTOGRAM_POINT_UNCERTAIN_INT, HISTOGRAM_POINT_UNCERTAIN_STRING, HISTOGRAM_POINT_UNCERTAIN_REAL,
  CONTINUOUS_INTERVAL_UNCERTAIN, DISCRETE_INTERVAL_UNCERTAIN, DISCRETE_UNCERTAIN_SET_INT, DISCRETE_UNCERTAIN_SET_STRING,
  DISCRETE_UNCERTAIN_SET_REAL, CONTINUOUS_STATE, DISCRETE_STATE_RANGE, DISCRETE_STATE_SET_INT,
  DISCRETE_STATE_SET_STRING, DISCRETE_STATE_SET_REAL, CEUVar_interval = 0, CEUVar_Nkinds = 1
}
 
enum  {
  TABULAR_NONE = 0, TABULAR_HEADER = 1, TABULAR_EVAL_ID = 2, TABULAR_IFACE_ID = 4,
  TABULAR_EXPER_ANNOT = TABULAR_HEADER | TABULAR_EVAL_ID, TABULAR_ANNOTATED = TABULAR_HEADER | TABULAR_EVAL_ID | TABULAR_IFACE_ID, DEFAULT_SCHEDULING, MASTER_SCHEDULING,
  PEER_SCHEDULING, PEER_DYNAMIC_SCHEDULING, PEER_STATIC_SCHEDULING, DYNAMIC_SCHEDULING,
  STATIC_SCHEDULING, SUBSPACE_NORM_DEFAULT =0, SUBSPACE_NORM_MEAN_VALUE, SUBSPACE_NORM_MEAN_GRAD,
  SUBSPACE_NORM_LOCAL_GRAD, TOTAL_CDV =0, TOTAL_DDIV, TOTAL_DDSV,
  TOTAL_DDRV, TOTAL_CAUV, TOTAL_DAUIV, TOTAL_DAUSV,
  TOTAL_DAURV, TOTAL_CEUV, TOTAL_DEUIV, TOTAL_DEUSV,
  TOTAL_DEURV, TOTAL_CSV, TOTAL_DSIV, TOTAL_DSSV,
  TOTAL_DSRV, NUM_VC_TOTALS, DEUIVar_interval = 0, DEUIVar_set_int = 1,
  DEUIVar_Nkinds = 2
}
 
enum  {
  RESULTS_OUTPUT_TEXT = 1, RESULTS_OUTPUT_HDF5 = 2, DEFAULT_CONFIG, PUSH_DOWN,
  PUSH_UP, ROTATION_METHOD_UNRANKED, ROTATION_METHOD_RANKED, DEUSVar_set_str = 0,
  DEUSVar_Nkinds = 1
}
 
enum  {
  FLEXIBLE_RESULTS, LABELED_RESULTS, STD_NORMAL_U, STD_UNIFORM_U,
  PARTIAL_ASKEY_U, ASKEY_U, EXTENDED_U, NO_PARALLEL_MODE =0,
  SURROGATE_MODEL_MODE, TRUTH_MODEL_MODE, SUB_MODEL_MODE, INTERFACE_MODE,
  DEURVar_set_real = 0, DEURVar_Nkinds = 1
}
 
enum  {
  NO_MODEL_FORMAT =0, TEXT_ARCHIVE =1, BINARY_ARCHIVE =2, ALGEBRAIC_FILE =4,
  ALGEBRAIC_CONSOLE =8, DEFAULT_COVARIANCE, NO_COVARIANCE, DIAGONAL_COVARIANCE,
  FULL_COVARIANCE, NO_DERIVS =0, ALL_DERIVS, MIXED_DERIVS,
  DiscSetVar_design_set_int = 0, DiscSetVar_design_set_str = 1, DiscSetVar_design_set_real = 2, DiscSetVar_state_set_int = 3,
  DiscSetVar_state_set_str = 4, DiscSetVar_state_set_real = 5, DiscSetVar_Nkinds = 6
}
 
enum  {
  NO_INT_REFINE =0, IS, AIS, MMAIS,
  FT_LS, FT_RLS2, NUM_UNC_REAL_CONT = 4
}
 number of real-valued uncertain contiguous containers
 
enum  {
  PROBABILITIES, RELIABILITIES, GEN_RELIABILITIES, NO_C3_ADVANCEMENT =0,
  START_RANK_ADVANCEMENT, START_ORDER_ADVANCEMENT, MAX_RANK_ADVANCEMENT, MAX_ORDER_ADVANCEMENT,
  MAX_RANK_ORDER_ADVANCEMENT, NUM_UNC_INT_CONT = 2
}
 number of int-valued uncertain contiguous containers
 
enum  { COMPONENT =0, SYSTEM_SERIES, SYSTEM_PARALLEL, NUM_UNC_STR_CONT = 2 }
 number of string-valued uncertain contiguous containers
 
enum  miAlg : unsigned short { MI_ALG_KSG1 = 0, MI_ALG_KSG2 = 1 }
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  CG_UPDATETYPE {
  CG_STEEPEST, CG_FLETCHER_REEVES, CG_POLAK_RIBIERE, CG_POLAK_RIBIERE_PLUS,
  CG_HESTENES_STIEFEL
}
 NonlinearCG update options.
 
enum  CG_LINESEARCHTYPE { CG_FIXED_STEP, CG_LS_SIMPLE, CG_LS_BRENT, CG_LS_WOLFE }
 NonlinearCG linesearch options.
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 to restrict type of auto scaling allowed
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 indicate type of scaling active for a component (bitwise)
 
enum  EvalType { NO_EVALUATOR, NLF_EVALUATOR, CON_EVALUATOR }
 enumeration for the type of evaluator function
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 
enum  {
  INTERF_EVAL_STORE_SIMULATION = 0, INTERF_EVAL_STORE_NONE, INTERF_EVAL_STORE_ALL, OBJECTIVE,
  INEQUALITY_CONSTRAINT, EQUALITY_CONSTRAINT, SILENT_OUTPUT, QUIET_OUTPUT,
  NORMAL_OUTPUT, VERBOSE_OUTPUT, DEBUG_OUTPUT, NO_CORRECTION =0,
  ADDITIVE_CORRECTION, MULTIPLICATIVE_CORRECTION, COMBINED_CORRECTION, EMPTY_VIEW =0,
  RELAXED_ALL, MIXED_ALL, RELAXED_DESIGN, RELAXED_UNCERTAIN,
  RELAXED_ALEATORY_UNCERTAIN, RELAXED_EPISTEMIC_UNCERTAIN, RELAXED_STATE, MIXED_DESIGN,
  MIXED_UNCERTAIN, MIXED_ALEATORY_UNCERTAIN, MIXED_EPISTEMIC_UNCERTAIN, MIXED_STATE,
  DAUSVar_histogram_point_str = 0, DAUSVar_Nkinds = 1, NEW_CANDIDATE = 1, CANDIDATE_ACCEPTED = 2,
  CANDIDATE_STATE = (NEW_CANDIDATE | CANDIDATE_ACCEPTED), NEW_CENTER = 8, CENTER_BUILT = 16, CENTER_STATE = (NEW_CENTER | CENTER_BUILT),
  NEW_TR_FACTOR = 64, NEW_TRUST_REGION = (NEW_CENTER | NEW_TR_FACTOR), HARD_CONVERGED = 128, SOFT_CONVERGED = 256,
  MIN_TR_CONVERGED = 512, MAX_ITER_CONVERGED = 1024, CONVERGED
}
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 
enum  {
  COBYLA, DIRECT, EA, MS,
  PS, SW, BETA, VARS_ERROR = -10,
  RESP_ERROR = -9, APPROX_ERROR = -8, METHOD_ERROR = -7, MODEL_ERROR = -6,
  IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2,
  OTHER_ERROR = -1, DEFAULT_INTERFACE =0, APPROX_INTERFACE, FORK_INTERFACE =PROCESS_INTERFACE_BIT,
  SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE =DIRECT_INTERFACE_BIT, PLUGIN_INTERFACE,
  MATLAB_INTERFACE, LEGACY_PYTHON_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE,
  DEFAULT_METHOD =0, HYBRID =(META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START,
  RICHARDSON_EXTRAP =(ANALYZER_BIT | VERIF_BIT), CENTERED_PARAMETER_STUDY =(ANALYZER_BIT | PSTUDYDACE_BIT), LIST_PARAMETER_STUDY, MULTIDIM_PARAMETER_STUDY,
  VECTOR_PARAMETER_STUDY, DACE, FSU_CVT, FSU_HALTON,
  FSU_HAMMERSLEY, PSUADE_MOAT, LOCAL_RELIABILITY =(ANALYZER_BIT | NOND_BIT), GLOBAL_RELIABILITY,
  SURROGATE_BASED_UQ, POLYNOMIAL_CHAOS, MULTILEVEL_POLYNOMIAL_CHAOS, MULTIFIDELITY_POLYNOMIAL_CHAOS,
  STOCH_COLLOCATION, MULTIFIDELITY_STOCH_COLLOCATION, C3_FUNCTION_TRAIN, MULTILEVEL_FUNCTION_TRAIN,
  MULTIFIDELITY_FUNCTION_TRAIN, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION,
  BAYES_CALIBRATION, GPAIS, POF_DARTS, RKD_DARTS,
  IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, MULTILEVEL_SAMPLING, MULTIFIDELITY_SAMPLING,
  MULTILEVEL_MULTIFIDELITY_SAMPLING, APPROXIMATE_CONTROL_VARIATE, LIST_SAMPLING, RANDOM_SAMPLING,
  LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE,
  SURROGATE_BASED_LOCAL =(MINIMIZER_BIT | SURRBASED_BIT), DATA_FIT_SURROGATE_BASED_LOCAL, HIERARCH_SURROGATE_BASED_LOCAL, SURROGATE_BASED_GLOBAL,
  EFFICIENT_GLOBAL, NL2SOL =(MINIMIZER_BIT | LEASTSQ_BIT), NLSSOL_SQP, OPTPP_G_NEWTON,
  ASYNCH_PATTERN_SEARCH =(MINIMIZER_BIT | OPTIMIZER_BIT), OPTPP_PDS, COLINY_BETA, COLINY_COBYLA,
  COLINY_DIRECT, COLINY_MULTI_START, COLINY_EA, COLINY_PATTERN_SEARCH,
  COLINY_SOLIS_WETS, MOGA, SOGA, NCSU_DIRECT,
  MESH_ADAPTIVE_SEARCH, MIT_NOWPAC, MIT_SNOWPAC, GENIE_OPT_DARTS,
  GENIE_DIRECT, DEMO_TPL, NONLINEAR_CG, OPTPP_CG,
  OPTPP_Q_NEWTON, OPTPP_FD_NEWTON, OPTPP_NEWTON, NPSOL_SQP,
  NLPQL_SQP, DOT_BFGS, DOT_FRCG, DOT_MMFD,
  DOT_SLP, DOT_SQP, CONMIN_FRCG, CONMIN_MFD,
  ROL, DL_SOLVER, BRANCH_AND_BOUND =(MINIMIZER_BIT | OPTIMIZER_BIT | LEASTSQ_BIT), DEFAULT_POINTS,
  MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS, BASE_RESPONSE =0,
  SIMULATION_RESPONSE, EXPERIMENT_RESPONSE, DEFAULT_DOMAIN =0, RELAXED_DOMAIN,
  MIXED_DOMAIN, DEFAULT_CORRECTION = 0, SINGLE_CORRECTION, FULL_MODEL_FORM_CORRECTION,
  FULL_SOLUTION_LEVEL_CORRECTION, SEQUENCE_CORRECTION, SETUP_MODEL, SETUP_USERFUNC,
  CAUVar_normal = 0, CAUVar_lognormal = 1, CAUVar_uniform = 2, CAUVar_loguniform = 3,
  CAUVar_triangular = 4, CAUVar_exponential = 5, CAUVar_beta = 6, CAUVar_gamma = 7,
  CAUVar_gumbel = 8, CAUVar_frechet = 9, CAUVar_weibull = 10, CAUVar_histogram_bin = 11,
  CAUVar_Nkinds = 12, ANALYTIC_SOLUTION = 1, REORDERED_ANALYTIC_SOLUTION, R_ONLY_LINEAR_CONSTRAINT,
  N_VECTOR_LINEAR_CONSTRAINT, R_AND_N_NONLINEAR_CONSTRAINT, N_VECTOR_LINEAR_OBJECTIVE, FULL_TENSOR,
  FILTERED_TENSOR, RANDOM_TENSOR, AS_FUNC =1, AS_GRAD =2,
  AS_HESS =4, DISALLOW, TARGET, BOUNDS,
  SCALE_NONE = 0, SCALE_VALUE = 1, SCALE_LOG = 2, SCALE_AUTO = 4,
  APPROX_RESPONSE =1, TRUTH_RESPONSE, TH_SILENT_OUTPUT, TH_QUIET_OUTPUT,
  TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT, DIR_CLEAN,
  DIR_PERSIST, DIR_ERROR
}
 define directory creation options
 
enum  {
  MODEL_EVAL_STORE_TOP_METHOD = 0, MODEL_EVAL_STORE_NONE, MODEL_EVAL_STORE_ALL, MODEL_EVAL_STORE_ALL_METHODS,
  SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE, SUBMETHOD_DEFAULT =0, SUBMETHOD_NONE,
  SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS,
  SUBMETHOD_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID,
  SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_MFMC, SUBMETHOD_ACV_IS,
  SUBMETHOD_ACV_MF, SUBMETHOD_ACV_KL, SUBMETHOD_DREAM, SUBMETHOD_GPMSA,
  SUBMETHOD_MUQ, SUBMETHOD_QUESO, SUBMETHOD_WASABI, SUBMETHOD_CONMIN,
  SUBMETHOD_DOT, SUBMETHOD_NLPQL, SUBMETHOD_NPSOL, SUBMETHOD_OPTPP,
  SUBMETHOD_EA, SUBMETHOD_DIRECT, SUBMETHOD_EGO, SUBMETHOD_SBLO,
  SUBMETHOD_SBGO, SUBMETHOD_AMV_X, SUBMETHOD_AMV_U, SUBMETHOD_AMV_PLUS_X,
  SUBMETHOD_AMV_PLUS_U, SUBMETHOD_TANA_X, SUBMETHOD_TANA_U, SUBMETHOD_QMEA_X,
  SUBMETHOD_QMEA_U, SUBMETHOD_NO_APPROX, SUBMETHOD_EGRA_X, SUBMETHOD_EGRA_U,
  SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER, NO_SURROGATE =0,
  UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY,
  AGGREGATED_MODELS, GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS,
  DEFAULT_VIEW =0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW,
  ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW, DAUIVar_poisson = 0,
  DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4,
  DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6, TYPE_U =1, TYPE_B =2,
  TYPE_E =3, TYPE_EB =4, CORR_APPROX_RESPONSE =1, UNCORR_APPROX_RESPONSE,
  CORR_TRUTH_RESPONSE, UNCORR_TRUTH_RESPONSE, FILEOP_SILENT, FILEOP_WARN,
  FILEOP_ERROR
}
 enum indicating action on failed file operation More...
 

Functions

void batch_means_interval (RealMatrix &mcmc_matrix, RealMatrix &interval_matrix, RealMatrix &means_matrix, int moment, Real alpha)
 
void batch_means_percentile (RealMatrix &mcmc_matrix, RealMatrix &interval_matrix, RealMatrix &means_matrix, Real percentile, Real alpha)
 
CommandShell & flush (CommandShell &shell)
 convenient shell manipulator function to "flush" the shell More...
 
void read_sized_data (std::istream &s, RealVectorArray &va, size_t num_rows, int num_cols)
 
void read_fixed_rowsize_data (std::istream &s, RealVectorArray &va, int num_cols, bool row_major)
 
void read_unsized_data (std::istream &s, RealVectorArray &va, bool row_major)
 
void read_config_vars_multifile (const std::string &basename, int num_expts, int ncv, std::vector< Variables > &config_vars)
 
void read_config_vars_singlefile (const std::string &basename, int num_expts, int ncv, std::vector< Variables > &config_vars)
 
void read_field_values (const std::string &basename, int expt_num, RealVectorArray &field_vars)
 
void read_field_values (const std::string &basename, int expt_num, RealVector &field_vars)
 
void read_coord_values (const std::string &basename, int expt_num, RealMatrix &coords)
 
void read_coord_values (const std::string &basename, RealMatrix &coords)
 
void read_covariance (const std::string &basename, int expt_num, RealMatrix &cov_vals)
 
void read_covariance (const std::string &basename, int expt_num, Dakota::CovarianceMatrix::FORMAT format, int num_vals, RealMatrix &cov_vals)
 
bool nearby (const RealVector &rv1, const RealVector &rv2, Real rel_tol)
 tolerance-based equality operator for RealVector
 
bool operator== (const ShortArray &dsa1, const ShortArray &dsa2)
 equality operator for ShortArray
 
bool operator== (const StringArray &dsa1, const StringArray &dsa2)
 equality operator for StringArray
 
Real rel_change_L2 (const RealVector &curr_rv, const RealVector &prev_rv)
 Computes relative change between RealVectors using Euclidean L2 norm.
 
Real rel_change_L2 (const RealVector &curr_rv1, const RealVector &prev_rv1, const IntVector &curr_iv, const IntVector &prev_iv, const RealVector &curr_rv2, const RealVector &prev_rv2)
 Computes relative change between Real/int/Real vector triples using Euclidean L2 norm.
 
void compute_col_means (RealMatrix &matrix, RealVector &avg_vals)
 Computes means of columns of matrix.
 
void compute_col_stdevs (RealMatrix &matrix, RealVector &avg_vals, RealVector &std_devs)
 Computes standard deviations of columns of matrix.
 
void remove_column (RealMatrix &matrix, int index)
 Removes column from matrix.
 
std::vector< std::string > strsplit (const std::string &input)
 Trim then split a string on {space, tab} and return as vector of strings.
 
std::string::size_type longest_strlen (const std::vector< std::string > &vecstr)
 Return the length of the longest string in the passed vector.
 
void iround (const RealVector &input_vec, IntVector &rounded_vec)
 round entries of a RealVector yielding an IntVector
 
bool operator== (const IntArray &dia1, const IntArray &dia2)
 equality operator for IntArray
 
template<typename T >
bool operator== (const std::vector< T > &vec, typename boost::multi_array< T, 1 >::template const_array_view< 1 >::type mav)
 equality operator for std::vector and boost::multi_array::const_array_view
 
template<typename T >
bool operator== (typename boost::multi_array< T, 1 >::template const_array_view< 1 >::type mav, const std::vector< T > &vec)
 equality operator for boost::multi_array::const_array_view and std::vector
 
template<typename T >
bool operator== (const boost::multi_array< T, 1 > &ma, typename boost::multi_array< T, 1 >::template const_array_view< 1 >::type mav)
 equality operator for boost::multi_array and boost::multi_array::const_array_view
 
template<typename T >
bool operator== (typename boost::multi_array< T, 1 >::template const_array_view< 1 >::type mav, const boost::multi_array< T, 1 > &ma)
 equality operator for boost::multi_array::const_array_view and boost::multi_array
 
bool operator!= (const IntArray &dia1, const IntArray &dia2)
 inequality operator for IntArray
 
bool operator!= (const ShortArray &dsa1, const ShortArray &dsa2)
 inequality operator for ShortArray
 
bool operator!= (const StringArray &dsa1, const StringArray &dsa2)
 inequality operator for StringArray
 
template<typename T >
bool operator!= (const std::vector< T > &vec, typename boost::multi_array< T, 1 >::template const_array_view< 1 >::type mav)
 inequality operator for std::vector and boost::multi_array::const_array_view
 
template<typename T >
bool operator!= (typename boost::multi_array< T, 1 >::template const_array_view< 1 >::type mav, const std::vector< T > &vec)
 inequality operator for boost::multi_array::const_array_view and std::vector
 
template<typename T >
bool operator!= (const boost::multi_array< T, 1 > &ma, typename boost::multi_array< T, 1 >::template const_array_view< 1 >::type mav)
 inequality operator for boost::multi_array and boost::multi_array::const_array_view
 
template<typename T >
bool operator!= (typename boost::multi_array< T, 1 >::template const_array_view< 1 >::type mav, const boost::multi_array< T, 1 > &ma)
 inequality operator for boost::multi_array::const_array_view and boost::multi_array
 
template<typename OrdinalType >
bool non_zero (const std::vector< OrdinalType > &vec)
 checks for any non-zero value in std::vector(); useful for determining whether an array of request codes (e.g., an ASV) has any actionable content
 
template<typename VectorType >
bool is_equal_vec (const RealVector &vec1, const VectorType &vec2)
 equality function for RealVector and a vector of arbitrary type
 
template<typename MatrixType , typename VectorType >
void apply_matrix_partial (const MatrixType &M, const VectorType &v1, VectorType &v2)
 Applies a RealMatrix to a vector (or subset of vector) v1. More...
 
template<typename VectorType >
void apply_matrix_transpose_partial (const RealMatrix &M, const VectorType &v1, VectorType &v2)
 Applies transpose of a RealMatrix to a vector (or subset of vector) v1. More...
 
std::string strtolower (const std::string &s)
 Return lowercase copy of string s.
 
bool strbegins (const std::string &input, const std::string &test)
 Return true if input string begins with string test.
 
bool strends (const std::string &input, const std::string &test)
 Return true if input string ends with string test.
 
bool strcontains (const std::string &input, const std::string &test)
 Return true if input string contains string test.
 
void build_label (String &label, const String &root_label, size_t tag, const String &separator="")
 create a label by appending a numerical tag to the root_label, o
 
void build_labels (StringArray &label_array, const String &root_label)
 create an array of labels by tagging root_label for each entry in label_array. Uses build_label().
 
void build_labels (StringMultiArray &label_array, const String &root_label)
 create an array of labels by tagging root_label for each entry in label_array. Uses build_label().
 
void build_labels_partial (StringArray &label_array, const String &root_label, size_t start_index, size_t num_items)
 create a partial array of labels by tagging root_label for a subset of entries in label_array. Uses build_label().
 
template<typename vecType , typename valueType >
void assign_value (vecType &target, valueType val)
 assign a value to an arbitrary vector
 
template<typename vecType , typename valueType >
void assign_value (vecType &target, valueType val, size_t start, size_t len)
 assign a value to a portion of an arbitrary vector
 
template<typename OrdinalType , typename ScalarType >
void copy_data (const std::vector< Teuchos::SerialDenseVector< OrdinalType, ScalarType > > &sdva, Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > &sdm)
 copy Array<Teuchos::SerialDenseVector<OT,ST> > to Teuchos::SerialDenseMatrix<OT,ST> - used by read_data_tabular - RWH
 
template<typename OrdinalType , typename ScalarType >
void copy_data_transpose (const std::vector< Teuchos::SerialDenseVector< OrdinalType, ScalarType > > &sdva, Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > &sdm)
 copy Array<Teuchos::SerialDenseVector<OT,ST> > to transposed Teuchos::SerialDenseMatrix<OT,ST> - used by read_data_tabular - RWH
 
template<typename OrdinalType1 , typename OrdinalType2 , typename ScalarType >
void copy_data (const Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv, Teuchos::SerialDenseMatrix< OrdinalType1, ScalarType > &sdm, OrdinalType2 nr, OrdinalType2 nc)
 copy Teuchos::SerialDenseVector<OT,ST> to Teuchos::SerialDenseMatrix<OT,ST> - used by NestedModel::update_sub_iterator - RWH
 
template<typename T >
void copy_data (const std::vector< std::vector< T > > &d2a, std::vector< T > &da)
 copy std::vector<vector<T> > to std::vector<T>(unroll vecOfvecs into vector) - used by ProcessApplicInterface::write_parameters_files - RWH
 
template<typename T >
void copy_data (const std::map< int, T > &im, std::vector< T > &da)
 copy map<int, T> to std::vector<T> (discard integer keys) - used by SurrBasedGlobalMinimizer::core_run - RWH
 
template<typename OrdinalType , typename ScalarType >
void copy_data (const Teuchos::SerialDenseVector< OrdinalType, ScalarType > &sdv1, Teuchos::SerialDenseVector< OrdinalType, ScalarType > &sdv2)
 copy Teuchos::SerialDenseVector<OrdinalType, ScalarType> to same (used in place of operator= when a deep copy is required) - used by Response - MSE
 
template<typename OrdinalType , typename ScalarType >
void copy_data (const Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > &sdm1, Teuchos::SerialDenseMatrix< OrdinalType, ScalarType > &sdm2)
 copy Teuchos::SerialDenseMatrix<OrdinalType, ScalarType> to same (used in place of operator= when a deep copy is required) - used by Response - MSE
 
template<typename OrdinalType , typename ScalarType >
void copy_data (const Teuchos::SerialSymDenseMatrix< OrdinalType, ScalarType > &ssdm1, Teuchos::SerialSymDenseMatrix< OrdinalType, ScalarType > &ssdm2)
 copy Teuchos::SerialSymDenseMatrix<OrdinalType, ScalarType> to same (used in place of operator= when a deep copy is required) - used by Response - MSE
 
void copy_data (const RealMatrix &source, RealMatrix &dest, int num_rows, int num_cols, int start_row=0, int start_col=0)
 Taken from pecos/src/MathTools.hpp, BUT not templated because the implementation is specific to RealMatrix.
 
template<typename OrdinalType , typename ScalarType , typename VecType >
void copy_data (const Teuchos::SerialDenseVector< OrdinalType, ScalarType > &sdv, VecType &vec)
 copy Teuchos::SerialDenseVector<OrdinalType, ScalarType> to VecType - used by APPS for HOPS vector types
 
template<typename OrdinalType , typename ScalarType1 , typename ScalarType2 >
void copy_data (const Teuchos::SerialDenseVector< OrdinalType, ScalarType1 > &sdv, std::vector< ScalarType2 > &vec)
 copy Teuchos::SerialDenseVector<OrdinalType, ScalarType> to std::vector<ScalarType> - used by DakotaModel
 
template<typename OrdinalType , typename ScalarType >
void copy_data (const std::vector< ScalarType > &da, Teuchos::SerialDenseVector< OrdinalType, ScalarType > &sdv)
 copy Array<ScalarType> to Teuchos::SerialDenseVector<OrdinalType, ScalarType> - used by NOWPACOptimizer - MSE
 
template<typename OrdinalType1 , typename OrdinalType2 , typename ScalarType >
void copy_data (const ScalarType *ptr, const OrdinalType2 ptr_len, Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv)
 copy ScalarType* to Teuchos::SerialDenseVector<OrdinalType, ScalarType> - used by ScalingModel::response_modify_n2s - RWH
 
template<typename OrdinalType1 , typename OrdinalType2 , typename ScalarType >
void copy_data (const Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv, ScalarType *ptr, const OrdinalType2 ptr_len)
 copy ScalarType* to Teuchos::SerialDenseVector<OrdinalType, ScalarType> - used by NL2SOLLeastSq::core_run - RWH
 
template<typename OrdinalType1 , typename OrdinalType2 , typename ScalarType >
void copy_data (const Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv, std::vector< Teuchos::SerialDenseVector< OrdinalType1, ScalarType > > &sdva, OrdinalType2 num_vec, OrdinalType2 vec_len)
 copy SerialDenseVector<> to Array<SerialDenseVector<> > - used by ConcurrentMetaIterator constructor - RWH
 
template<typename vecType1 , typename vecType2 >
void copy_data_partial (const vecType1 &source, size_t source_start_idx, vecType2 &target, size_t target_start_idx, size_t len)
 copy a portion arbitrary vector to all of another arbitrary vector
 
template<typename OrdinalType1 , typename OrdinalType2 , typename ScalarType >
void copy_data_partial (const Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv1, OrdinalType2 start_index1, OrdinalType2 num_items, Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv2)
 copy portion of first SerialDenseVector to all of second SerialDenseVector - used by DataTransformModel::vars_mapping - RWH
 
template<typename OrdinalType1 , typename OrdinalType2 , typename ScalarType >
void copy_data_partial (const Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv1, Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv2, OrdinalType2 start_index2)
 copy all of first SerialDenseVector to portion of second SerialDenseVector - used by MixedVariables - RWH, NLSSOLLeastSq - BMA
 
template<typename OrdinalType1 , typename OrdinalType2 , typename ScalarType >
void copy_data_partial (const Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv1, OrdinalType2 start_index1, OrdinalType2 num_items, Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv2, OrdinalType2 start_index2)
 copy portion of first SerialDenseVector to portion of second SerialDenseVector - used by ScalingModel::secondary_resp_scaled2native - RWH
 
template<typename OrdinalType1 , typename OrdinalType2 , typename ScalarType >
void copy_data_partial (const Teuchos::SerialDenseVector< OrdinalType1, ScalarType > &sdv1, std::vector< ScalarType > &da2, OrdinalType2 start_index2)
 copy all of first SerialDenseVector to portion of second SerialDenseVector - used by SharedSurfpackApproxData::merge_variable_arrays - RWH
 
template<typename T >
void copy_data_partial (const std::vector< T > &da1, size_t start_index1, size_t num_items, std::vector< T > &da2)
 copy portion of first Array<T> to all of second Array<T> - used by SharedResponseDataRep constructor - RWH
 
template<typename T >
void copy_data_partial (const std::vector< T > &da1, std::vector< T > &da2, size_t start_index2)
 copy all of first Array<T> to portion of second Array<T> - used by ParamStudy::multidim_loop - RWH
 
template<typename T >
void copy_data_partial (const std::vector< T > &da, boost::multi_array< T, 1 > &bma, size_t start_index_bma)
 copy all of first Array<T> to portion of boost::multi_array<T, 1> - used by RelaxedVariables - RWH
 
template<typename VectorType >
void copy_column_vector (const RealMatrix &m, RealMatrix::ordinalType j, VectorType &col)
 Copies a column of a Teuchos_SerialDenseMatrix<int,Real> to std::vector<Real>
 
template<typename VectorType >
void copy_row_vector (const RealMatrix &m, RealMatrix::ordinalType i, VectorType &row)
 Copies a row of a Teuchos_SerialDenseMatrix<int,Real> to std::vector<Real>
 
template<typename ScalarType >
void insert_row_vector (const std::vector< ScalarType > &row, RealMatrix::ordinalType i, RealMatrix &m)
 Inserts a std::vector<Real> into a row of a Teuchos_SerialDenseMatrix<int,Real>
 
void merge_data_partial (const IntVector &d_vec, RealVector &m_vec, size_t start_index_ma)
 merge a discrete integer vector into a single continuous vector
 
void merge_data_partial (const IntVector &d_vec, RealArray &m_array, size_t start_index_ma)
 merge a discrete integer vector into a single continuous array
 
template<typename OrdinalType , typename ScalarType >
const ScalarType & set_index_to_value (OrdinalType index, const std::set< ScalarType > &values)
 retrieve the set value corresponding to the passed index
 
template<typename ScalarType >
size_t set_value_to_index (const ScalarType &value, const std::set< ScalarType > &values)
 calculate the set index corresponding to the passed value
 
template<typename OrdinalType , typename KeyType , typename ValueType >
const KeyType & map_index_to_key (OrdinalType index, const std::map< KeyType, ValueType > &pairs)
 retrieve the set value corresponding to the passed index
 
template<typename OrdinalType , typename KeyType , typename ValueType >
const ValueType & map_index_to_value (OrdinalType index, const std::map< KeyType, ValueType > &pairs)
 retrieve the set value corresponding to the passed index
 
template<typename KeyType , typename ValueType >
void map_keys_to_set (const std::map< KeyType, ValueType > &source_map, std::set< KeyType > &target_set)
 calculate the map index corresponding to the passed key
 
template<typename KeyType , typename ValueType >
size_t map_key_to_index (const KeyType &key, const std::map< KeyType, ValueType > &pairs)
 calculate the map index corresponding to the passed key
 
template<typename KeyType , typename ValueType >
size_t map_value_to_index (const ValueType &value, const std::map< KeyType, ValueType > &pairs)
 calculate the map index corresponding to the passed value (not the key)
 
template<typename KeyType , typename ValueType >
size_t map_value_to_index (const ValueType &value, const std::multimap< KeyType, ValueType > &pairs)
 calculate the map index corresponding to the passed value (not the key)
 
template<typename OrdinalType , typename ScalarType >
void x_y_pairs_to_x_set (const Teuchos::SerialDenseVector< OrdinalType, ScalarType > &xy_pairs, std::set< ScalarType > &x_set)
 convert a SerialDenseVector of head-to-tail (x,y) pairs into a std::set of (x), discarding the y values
 
template<typename ScalarType >
ScalarType find_min (const std::vector< ScalarType > &vec)
 
template<typename OrdinalType , typename ScalarType >
ScalarType find_min (const std::vector< ScalarType > &vec, OrdinalType start, OrdinalType end)
 
template<typename OrdinalType , typename ScalarType >
ScalarType find_min (const Teuchos::SerialDenseVector< OrdinalType, ScalarType > &vec)
 
template<typename OrdinalType , typename ScalarType >
ScalarType find_min (const ScalarType *vec, OrdinalType len)
 
template<typename ScalarType >
ScalarType find_max (const std::vector< ScalarType > &vec)
 
template<typename OrdinalType , typename ScalarType >
ScalarType find_max (const Teuchos::SerialDenseVector< OrdinalType, ScalarType > &vec)
 
template<typename OrdinalType , typename ScalarType >
ScalarType find_max (const ScalarType *vec, const OrdinalType len)
 
template<typename ContainerType >
size_t find_index (const ContainerType &c, const typename ContainerType::value_type &search_data)
 generic find_index (inactive)
 
template<typename T >
size_t find_index (const boost::multi_array< T, 1 > &bma, const T &search_data)
 compute the index of an entry within a boost::multi_array
 
size_t find_index (SizetMultiArrayConstView bmacv, size_t search_data)
 compute the index of an entry within a boost::multi_array view
 
size_t find_index (StringMultiArrayConstView bmacv, const String &search_data)
 compute the index of an entry within a boost::multi_array view
 
template<typename ListT >
size_t find_index (const ListT &l, const typename ListT::value_type &val)
 compute the index of an entry within a std::list
 
template<typename ListT >
ListT::const_iterator find_if (const ListT &c, bool(*test_fn)(const typename ListT::value_type &, const std::string &), const std::string &test_fn_data)
 return an iterator to the first list element satisfying the predicate test_fn w.r.t. the passed test_fn_data; end if not found
 
template<typename VectorType , typename ScalarType >
void copy_data (const std::vector< VectorType > &va, ScalarType *ptr, int ptr_len)
 
void copy_data (SizetMultiArrayConstView ma, SizetArray &da)
 copy boost::multi_array view to Array - used by ActiveSet::derivative_vector - RWH
 
void copy_data (StringMultiArrayConstView ma, StringArray &da)
 copy boost::multi_array view to Array - used by Pecos::copy_data - RWH
 
template<typename DakContainerType >
bool contains (const DakContainerType &v, const typename DakContainerType::value_type &val)
 return true if the item val appears in container v
 
template<class RandomIt , class URBG >
void rand_shuffle (RandomIt first, RandomIt last, URBG &&g)
 Random shuffle with C++17 shuffle API, but using Boost for portability.
 
void abort_handler (int code)
 global function which handles serial or parallel aborts
 
void abort_throw_or_exit (int dakota_code)
 throw or exit depending on abort_mode More...
 
void register_signal_handlers ()
 Tie various signal handlers to Dakota's abort_handler function. More...
 
void mpi_debug_hold ()
 Global function to hold Dakota processes to help with MPI debugging. More...
 
template<typename T >
T abort_handler_t (int code)
 
void svd (RealMatrix &matrix, RealVector &singular_vals, RealMatrix &v_trans, bool compute_vectors=true)
 Compute the SVD of an arbitrary matrix A = USV^T. More...
 
void singular_values (RealMatrix &matrix, RealVector &singular_values)
 compute the singular values without storing any singular vectors (A will be destroyed)
 
int qr (RealMatrix &A)
 Compute an in-place QR factorization A = QR. More...
 
int qr_rsolve (const RealMatrix &q_r, bool transpose, RealMatrix &rhs)
 Perform a multiple right-hand sides Rinv * rhs solve using the R from a qr factorization. More...
 
double det_AtransA (RealMatrix &A)
 Use SVD to compute det(A'*A), destroying A with the SVD.
 
std::string string_to_tmpfile (const std::string &dump_string)
 utility to write an input string to a tmpfile in PWD
 
std::string pyprepro_input (const std::string &template_file, const std::string &preproc_cmd="pyprepro.py")
 run pyprepro on the user-provided input file and return generated tmp output
 
ResultsKeyType make_key (const StrStrSizet &iterator_id, const std::string &data_name)
 Make a full ResultsKeyType from the passed iterator_id and data_name.
 
MetaDataValueType make_metadatavalue (StringMultiArrayConstView labels)
 create MetaDataValueType from the passed strings
 
MetaDataValueType make_metadatavalue (StringMultiArrayConstView cv_labels, StringMultiArrayConstView div_labels, StringMultiArrayConstView drv_labels, const StringArray &resp_labels)
 create MetaDataValueType from the passed strings
 
MetaDataValueType make_metadatavalue (const StringArray &resp_labels)
 create MetaDataValueType from the passed strings
 
MetaDataValueType make_metadatavalue (const std::string &)
 create MetaDataValueType from the passed strings
 
MetaDataValueType make_metadatavalue (const std::string &, const std::string &)
 create MetaDataValueType from the passed strings
 
MetaDataValueType make_metadatavalue (const std::string &, const std::string &, const std::string &)
 create MetaDataValueType from the passed strings
 
MetaDataValueType make_metadatavalue (const std::string &, const std::string &, const std::string &, const std::string &)
 create MetaDataValueType from the passed strings
 
MetaDataValueType make_metadatavalue (StringMultiArrayConstView cv_labels, StringMultiArrayConstView div_labels, StringMultiArrayConstView dsv_labels, StringMultiArrayConstView drv_labels, const StringArray &resp_labels)
 
int generate_system_seed ()
 clock microseconds-based random seed in [1, 1000000] More...
 
std::istream & operator>> (std::istream &s, ActiveSet &set)
 std::istream extraction operator for ActiveSet. Calls read(std::istream&).
 
std::ostream & operator<< (std::ostream &s, const ActiveSet &set)
 std::ostream insertion operator for ActiveSet. Calls write(std::istream&).
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &s, ActiveSet &set)
 MPIUnpackBuffer extraction operator for ActiveSet. Calls read(MPIUnpackBuffer&).
 
MPIPackBuffer & operator<< (MPIPackBuffer &s, const ActiveSet &set)
 MPIPackBuffer insertion operator for ActiveSet. Calls write(MPIPackBuffer&).
 
bool operator!= (const ActiveSet &set1, const ActiveSet &set2)
 inequality operator for ActiveSet More...
 
std::istream & operator>> (std::istream &s, Constraints &con)
 std::istream extraction operator for Constraints
 
std::ostream & operator<< (std::ostream &s, const Constraints &con)
 std::ostream insertion operator for Constraints
 
std::string re_match (const std::string &token, const boost::regex &re)
 Global utility function to ease migration from CtelRegExp to Boost.Regex.
 
bool interface_id_compare (const Interface &interface_in, const void *id)
 global comparison function for Interface
 
bool method_id_compare (const Iterator &iterator, const void *id)
 global comparison function for Iterator
 
bool model_id_compare (const Model &model, const void *id)
 global comparison function for Model
 
bool operator== (const Model &m1, const Model &m2)
 equality operator for Envelope is true if same letter instance More...
 
bool operator!= (const Model &m1, const Model &m2)
 inequality operator for Envelope is true if different letter instance More...
 
template<typename VecT >
void get_initial_values (const Model &model, VecT &values)
 
template<typename VecT >
bool get_bounds (const RealVector &lower_source, const RealVector &upper_source, VecT &lower_target, VecT &upper_target, Real big_real_bound_size, Real no_value)
 
template<typename VecT >
void get_bounds (const Model &model, VecT &lower_target, VecT &upper_target)
 
template<typename SetT , typename VecT >
void get_bounds (const SetT &source_set, VecT &lower_target, VecT &upper_target, int target_offset)
 
template<typename OrdinalType , typename ScalarType , typename VectorType2 , typename MaskType , typename SetArray >
bool get_mixed_bounds (const MaskType &mask_set, const SetArray &source_set, const Teuchos::SerialDenseVector< OrdinalType, ScalarType > &lower_source, const Teuchos::SerialDenseVector< OrdinalType, ScalarType > &upper_source, VectorType2 &lower_target, VectorType2 &upper_target, ScalarType bigBoundSize, ScalarType no_value, int target_offset=0)
 
template<typename AdapterT >
bool get_variable_bounds (Model &model, Real big_real_bound_size, int big_int_bound_size, typename AdapterT::VecT &lower, typename AdapterT::VecT &upper)
 
template<typename RVecT , typename IVecT >
int configure_inequality_constraint_maps (const Model &model, Real big_real_bound_size, CONSTRAINT_TYPE ctype, IVecT &map_indices, RVecT &map_multipliers, RVecT &map_offsets, Real scaling=1.0)
 
template<typename RVecT , typename IVecT >
void configure_equality_constraint_maps (Model &model, CONSTRAINT_TYPE ctype, IVecT &indices, size_t index_offset, RVecT &multipliers, RVecT &values, bool make_one_sided)
 
template<typename AdapterT >
void get_linear_constraints (Model &model, Real big_real_bound_size, typename AdapterT::VecT &lin_ineq_lower_bnds, typename AdapterT::VecT &lin_ineq_upper_bnds, typename AdapterT::VecT &lin_eq_targets, typename AdapterT::MatT &lin_ineq_coeffs, typename AdapterT::MatT &lin_eq_coeffs)
 
template<typename VecT >
void apply_linear_constraints (const Model &model, CONSTRAINT_EQUALITY_TYPE etype, const VecT &in_vals, VecT &values, bool adjoint=false)
 
template<typename VecT >
void apply_nonlinear_constraints (const Model &model, CONSTRAINT_EQUALITY_TYPE etype, const VecT &in_vals, VecT &values, bool adjoint=false)
 
template<typename VectorType1 , typename VectorType2 , typename SetArray >
void copy_variables (const VectorType1 &source, const BitArray &set_bits, const SetArray &set_vars, VectorType2 &dest, size_t offset, size_t len)
 
template<typename VectorType1 , typename VectorType2 , typename SetArray >
void copy_variables (const VectorType1 &source, const SetArray &set_vars, VectorType2 &dest, size_t offset, size_t len)
 
template<typename VectorType1 , typename VectorType2 >
void copy_variables (const VectorType1 &source, VectorType2 &dest, const BitArray &int_set_bits, const IntSetArray &set_int_vars, size_t offset, size_t len)
 
template<typename AdapterT >
void set_best_responses (typename AdapterT::OptT &optimizer, const Model &model, bool set_objectives, size_t num_user_primary_fns, const std::vector< int > constraint_map_indices, const std::vector< double > constraint_map_multipliers, const std::vector< double > constraint_map_offsets, ResponseArray &response_array)
 
template<typename VectorType >
void set_variables (const VectorType &source, Model &model, Variables &vars)
 
template<typename VectorType >
void get_variables (Model &model, VectorType &vec)
 
template<typename vectorType >
void get_responses (const Model &model, const RealVector &dak_fn_vals, const std::vector< int > constraint_map_indices, const std::vector< double > constraint_map_multipliers, const std::vector< double > constraint_map_offsets, vectorType &f_vec, vectorType &cEqs_vec, vectorType &cIneqs_vec)
 
template<typename VecT >
void get_nonlinear_eq_constraints (const Model &model, VecT &values, Real scale, int offset=-1)
 
template<typename VecT >
void get_nonlinear_eq_constraints (Model &model, const RealVector &curr_resp_vals, VecT &values, Real scale, int offset=0)
 
template<typename VecT >
void get_nonlinear_ineq_constraints (const Model &model, VecT &values)
 
template<typename VecT >
void get_nonlinear_bounds (Model &model, VecT &nonlin_ineq_lower, VecT &nonlin_ineq_upper, VecT &nonlin_eq_targets)
 Would like to combine the previous adapter with this one (based on APPSOptimizer and COLINOptimizer) and then see how much more generalization is needed to support other TPLs like JEGA. More...
 
bool responses_id_compare (const Response &resp, const void *id)
 global comparison function for Response
 
std::istream & operator>> (std::istream &s, Response &response)
 std::istream extraction operator for Response. Calls read(std::istream&).
 
std::ostream & operator<< (std::ostream &s, const Response &response)
 std::ostream insertion operator for Response. Calls write(std::ostream&).
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &s, Response &response)
 MPIUnpackBuffer extraction operator for Response. Calls read(MPIUnpackBuffer&).
 
MPIPackBuffer & operator<< (MPIPackBuffer &s, const Response &response)
 MPIPackBuffer insertion operator for Response. Calls write(MPIPackBuffer&).
 
bool operator!= (const Response &resp1, const Response &resp2)
 inequality operator for Response More...
 
void set_model_gp_options (Model &model, const String &options_file)
 
bool variables_id_compare (const Variables &vars, const void *id)
 global comparison function for Variables
 
std::istream & operator>> (std::istream &s, Variables &vars)
 std::istream extraction operator for Variables.
 
std::ostream & operator<< (std::ostream &s, const Variables &vars)
 std::ostream insertion operator for Variables.
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &s, Variables &vars)
 MPIUnpackBuffer extraction operator for Variables.
 
MPIPackBuffer & operator<< (MPIPackBuffer &s, const Variables &vars)
 MPIPackBuffer insertion operator for Variables.
 
bool operator!= (const Variables &vars1, const Variables &vars2)
 inequality operator for Variables More...
 
template<typename OrdinalType , typename ScalarType1 , typename ScalarType2 , typename ScalarType3 , typename ScalarType4 >
void write_ordered (std::ostream &s, const SizetArray &comp_totals, const Teuchos::SerialDenseVector< OrdinalType, ScalarType1 > &c_vector, const Teuchos::SerialDenseVector< OrdinalType, ScalarType2 > &di_vector, const Teuchos::SerialDenseVector< OrdinalType, ScalarType3 > &ds_vector, const Teuchos::SerialDenseVector< OrdinalType, ScalarType4 > &dr_vector)
 free function to write Variables data vectors in input spec ordering More...
 
template<typename OrdinalType , typename ScalarType1 , typename ScalarType2 , typename ScalarType3 , typename ScalarType4 >
void write_ordered (std::ostream &s, const SizetArray &comp_totals, const Teuchos::SerialDenseVector< OrdinalType, ScalarType1 > &c_vector, const Teuchos::SerialDenseVector< OrdinalType, ScalarType2 > &di_vector, const boost::multi_array< ScalarType3, 1 > &ds_array, const Teuchos::SerialDenseVector< OrdinalType, ScalarType4 > &dr_vector)
 free function to write Variables data vectors in input spec ordering More...
 
template<typename ScalarType >
void write_ordered (std::ostream &s, const SizetArray &comp_totals, const std::vector< ScalarType > &c_array, const std::vector< ScalarType > &di_array, const std::vector< ScalarType > &ds_array, const std::vector< ScalarType > &dr_array)
 free function to write Variables data vectors in input spec ordering
 
void size_and_fill (const SharedVariablesData &svd, size_t array_size, VariablesArray &vars_array)
 Reinitialize var_array to contain array_size freshly constructed Variables, sharing provided SVD.
 
MPIPackBuffer & operator<< (MPIPackBuffer &s, const DataEnvironment &data)
 MPIPackBuffer insertion operator for DataEnvironment.
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &s, DataEnvironment &data)
 MPIUnpackBuffer extraction operator for DataEnvironment.
 
std::ostream & operator<< (std::ostream &s, const DataEnvironment &data)
 std::ostream insertion operator for DataEnvironment
 
String interface_enum_to_string (unsigned short interface_type)
 
MPIPackBuffer & operator<< (MPIPackBuffer &s, const DataInterface &data)
 MPIPackBuffer insertion operator for DataInterface.
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &s, DataInterface &data)
 MPIUnpackBuffer extraction operator for DataInterface.
 
std::ostream & operator<< (std::ostream &s, const DataInterface &data)
 std::ostream insertion operator for DataInterface
 
MPIPackBuffer & operator<< (MPIPackBuffer &s, const DataMethod &data)
 MPIPackBuffer insertion operator for DataMethod.
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &s, DataMethod &data)
 MPIUnpackBuffer extraction operator for DataMethod.
 
std::ostream & operator<< (std::ostream &s, const DataMethod &data)
 std::ostream insertion operator for DataMethod
 
MPIPackBuffer & operator<< (MPIPackBuffer &s, const DataModel &data)
 MPIPackBuffer insertion operator for DataModel.
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &s, DataModel &data)
 MPIUnpackBuffer extraction operator for DataModel.
 
std::ostream & operator<< (std::ostream &s, const DataModel &data)
 std::ostream insertion operator for DataModel
 
MPIPackBuffer & operator<< (MPIPackBuffer &s, const DataResponses &data)
 MPIPackBuffer insertion operator for DataResponses.
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &s, DataResponses &data)
 MPIUnpackBuffer extraction operator for DataResponses.
 
std::ostream & operator<< (std::ostream &s, const DataResponses &data)
 std::ostream insertion operator for DataResponses
 
MPIPackBuffer & operator<< (MPIPackBuffer &s, const DataVariables &data)
 MPIPackBuffer insertion operator for DataVariables.
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &s, DataVariables &data)
 MPIUnpackBuffer extraction operator for DataVariables.
 
std::ostream & operator<< (std::ostream &s, const DataVariables &data)
 std::ostream insertion operator for DataVariables
 
int dlsolver_option (Opt_Info *)
 
RealVector const * continuous_lower_bounds (Optimizer1 *o)
 
RealVector const * continuous_upper_bounds (Optimizer1 *o)
 
RealVector const * nonlinear_ineq_constraint_lower_bounds (Optimizer1 *o)
 
RealVector const * nonlinear_ineq_constraint_upper_bounds (Optimizer1 *o)
 
RealVector const * nonlinear_eq_constraint_targets (Optimizer1 *o)
 
RealVector const * linear_ineq_constraint_lower_bounds (Optimizer1 *o)
 
RealVector const * linear_ineq_constraint_upper_bounds (Optimizer1 *o)
 
RealVector const * linear_eq_constraint_targets (Optimizer1 *o)
 
RealMatrix const * linear_ineq_constraint_coeffs (Optimizer1 *o)
 
RealMatrix const * linear_eq_constraint_coeffs (Optimizer1 *o)
 
void ComputeResponses (Optimizer1 *o, int mode, int n, double *x)
 
void GetFuncs (Optimizer1 *o, int m0, int m1, double *f)
 
void GetGrads (Optimizer1 *o, int m0, int m1, int n, int is, int js, double *g)
 
void GetContVars (Optimizer1 *o, int n, double *x)
 
void SetBestContVars (Optimizer1 *o, int n, double *x)
 
void SetBestRespFns (Optimizer1 *o, int n, double *x)
 
void * dl_constructor (Optimizer1 *, Dakota_funcs *, dl_core_run_t *, dl_destructor_t *)
 
static RealVector const * continuous_lower_bounds1 (Optimizer1 *o)
 
static RealVector const * continuous_upper_bounds1 (Optimizer1 *o)
 
static RealVector const * nonlinear_ineq_constraint_lower_bounds1 (Optimizer1 *o)
 
static RealVector const * nonlinear_ineq_constraint_upper_bounds1 (Optimizer1 *o)
 
static RealVector const * nonlinear_eq_constraint_targets1 (Optimizer1 *o)
 
static RealVector const * linear_ineq_constraint_lower_bounds1 (Optimizer1 *o)
 
static RealVector const * linear_ineq_constraint_upper_bounds1 (Optimizer1 *o)
 
static RealVector const * linear_eq_constraint_targets1 (Optimizer1 *o)
 
static RealMatrix const * linear_eq_constraint_coeffs1 (Optimizer1 *o)
 
static RealMatrix const * linear_ineq_constraint_coeffs1 (Optimizer1 *o)
 
static void ComputeResponses1 (Optimizer1 *o, int mode, int n, double *x)
 
static void GetFuncs1 (Optimizer1 *o, int m0, int m1, double *f)
 
static void GetGrads1 (Optimizer1 *o, int m0, int m1, int n, int is, int js, double *g)
 
static void GetContVars1 (Optimizer1 *o, int n, double *x)
 
static void SetBestContVars1 (Optimizer1 *o, int n, double *x)
 
static void SetBestDiscVars1 (Optimizer1 *o, int n, int *x)
 
static void SetBestRespFns1 (Optimizer1 *o, int n, double *x)
 
static double Get_Real1 (Optimizer1 *o, const char *name)
 
static int Get_Int1 (Optimizer1 *o, const char *name)
 
static bool Get_Bool1 (Optimizer1 *o, const char *name)
 
DOTOptimizer * new_DOTOptimizer (ProblemDescDB &problem_db)
 
DOTOptimizer * new_DOTOptimizer (Model &model)
 
DOTOptimizer * new_DOTOptimizer (ProblemDescDB &problem_db, Model &model)
 
void copy_field_data (const RealVector &fn_vals, RealMatrix &fn_grad, const RealSymMatrixArray &fn_hess, size_t offset, size_t num_fns, Response &response)
 
void copy_field_data (const RealVector &fn_vals, RealMatrix &fn_grad, const RealSymMatrixArray &fn_hess, size_t offset, size_t num_fns, short total_asv, Response &response)
 
void interpolate_simulation_field_data (const Response &sim_resp, const RealMatrix &exp_coords, size_t field_num, short total_asv, size_t interp_resp_offset, Response &interp_resp)
 
void linear_interpolate_1d (const RealMatrix &build_pts, const RealVector &build_vals, const RealMatrix &build_grads, const RealSymMatrixArray &build_hessians, const RealMatrix &pred_pts, RealVector &pred_vals, RealMatrix &pred_grads, RealSymMatrixArray &pred_hessians)
 Returns the value of at 1D function f and its gradient and hessians (if available) at the points of vector pred_pts using linear interpolation. The vector build_pts specifies the coordinates of the underlying interval at which the values (build_vals) of the function f are known. The length of output pred_vals is equal to the length of pred_pts. This function assumes the build_pts is in ascending order.
 
void symmetric_eigenvalue_decomposition (const RealSymMatrix &matrix, RealVector &eigenvalues, RealMatrix &eigenvectors)
 Computes the eigenvalues and, optionally, eigenvectors of a real symmetric matrix A. More...
 
void compute_column_means (RealMatrix &matrix, RealVector &avg_vals)
 Compute the means of each column of an arbitrary matrix.
 
void sort_vector (const RealVector &vec, RealVector &sort_vec, IntVector &indices)
 Sort incoming vector with result and corresponding indices returned in passed arguments.
 
void sort_matrix_columns (const RealMatrix &mat, RealMatrix &sort_mat, IntMatrix &indices)
 Sort incoming matrix columns with result and corresponding indices returned in passed arguments.
 
bool is_matrix_symmetric (const RealMatrix &matrix)
 Test if incoming matrix is symmetric.
 
template<typename O , typename T >
int binary_search (T target, Teuchos::SerialDenseVector< O, T > &data)
 find the interval containing a target value. This function assumes the data is in ascending order.
 
Real getdist (const RealVector &x1, const RealVector &x2)
 
Real mindist (const RealVector &x, const RealMatrix &xset, int except)
 
Real mindistindx (const RealVector &x, const RealMatrix &xset, const IntArray &indx)
 
Real getRmax (const RealMatrix &xset)
 
int start_grid_computing (char *analysis_driver_script, char *params_file, char *results_file)
 
int stop_grid_computing ()
 
int perform_analysis (char *iteration_num)
 
int length (const StringMultiArrayConstView &vec)
 Return the length of a StringMultiArrayConstView.
 
H5::DataType h5_file_dtype (const short &)
 Return the HDF5 datatype to store a short.
 
H5::DataType h5_file_dtype (const int &)
 Return the HDF5 datatype to store a int.
 
H5::DataType h5_file_dtype (const unsigned int &)
 
H5::DataType h5_file_dtype (const unsigned long &)
 
H5::DataType h5_file_dtype (const unsigned long long &)
 
H5::DataType h5_file_dtype (const Real &)
 Return the HDF5 datatype to store a Real.
 
H5::DataType h5_file_dtype (const char *)
 Return the HDF5 datatype to store a string.
 
H5::DataType h5_file_dtype (const ResultsOutputType t)
 Overloads for ResultsOutputType (used when creating empty datasets)
 
H5::DataType h5_file_dtype (const String &)
 Return the HDF5 datatype to store a string.
 
H5::DataType h5_mem_dtype (const Real &)
 Return the HDF5 datatype to read a Real in memory.
 
H5::DataType h5_mem_dtype (const short &)
 Return the HDF5 datatype to read a short in memory.
 
H5::DataType h5_mem_dtype (const int &)
 Return the HDF5 datatype to read an int in memory.
 
H5::DataType h5_mem_dtype (const unsigned int &)
 Return the HDF5 datatype to read an unsigned int in memory.
 
H5::DataType h5_mem_dtype (const unsigned long &)
 Return the HDF5 datatype to read an unsigned long (maybe a size_t) in memory.
 
H5::DataType h5_mem_dtype (const unsigned long long &)
 Return the HDF5 datatype to read an unsigned long long (maybe a size_t) in memory.
 
H5::DataType h5_mem_dtype (const char *)
 Return the HDF5 datatype to read a string in memory.
 
H5::DataType h5_mem_dtype (const String &)
 Return the HDF5 datatype to read a string in memory.
 
H5::DataType h5_mem_dtype (const ResultsOutputType t)
 Overloads for ResultsOutputType (used when creating empty datasets)
 
template<typename T >
int length (const std::vector< T > &vec)
 Return the length of seeral types.
 
template<typename T >
int length (const Teuchos::SerialDenseVector< int, T > &vec)
 Return the length of an SDV.
 
template<typename T >
std::vector< const char * > pointers_to_strings (const T &data)
 Return a vector of pointers to strings.
 
template<typename T >
string asstring (const T &val)
 Creates a string from the argument val using an ostringstream. More...
 
 PACKBUF (int, MPI_INT) PACKBUF(u_int
 
MPI_UNSIGNED PACKBUF (long, MPI_LONG) PACKBUF(u_long
 
MPI_UNSIGNED MPI_UNSIGNED_LONG PACKBUF (long long, MPI_LONG_LONG) PACKBUF(unsigned long long
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG PACKBUF (short, MPI_SHORT) PACKBUF(u_short
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG MPI_UNSIGNED_SHORT PACKBUF (char, MPI_CHAR) PACKBUF(u_char
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG MPI_UNSIGNED_SHORT MPI_UNSIGNED_CHAR PACKBUF (double, MPI_DOUBLE) PACKBUF(float
 
 UNPACKBUF (int, MPI_INT) UNPACKBUF(u_int
 
MPI_UNSIGNED UNPACKBUF (long, MPI_LONG) UNPACKBUF(u_long
 
MPI_UNSIGNED MPI_UNSIGNED_LONG UNPACKBUF (long long, MPI_LONG_LONG) UNPACKBUF(unsigned long long
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG UNPACKBUF (short, MPI_SHORT) UNPACKBUF(u_short
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG MPI_UNSIGNED_SHORT UNPACKBUF (char, MPI_CHAR) UNPACKBUF(u_char
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG MPI_UNSIGNED_SHORT MPI_UNSIGNED_CHAR UNPACKBUF (double, MPI_DOUBLE) UNPACKBUF(float
 
 PACKSIZE (int, MPI_INT) PACKSIZE(u_int
 
MPI_UNSIGNED PACKSIZE (long, MPI_LONG) PACKSIZE(u_long
 
MPI_UNSIGNED MPI_UNSIGNED_LONG PACKSIZE (long long, MPI_LONG_LONG) PACKSIZE(unsigned long long
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG PACKSIZE (short, MPI_SHORT) PACKSIZE(u_short
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG MPI_UNSIGNED_SHORT PACKSIZE (char, MPI_CHAR) PACKSIZE(u_char
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG MPI_UNSIGNED_SHORT MPI_UNSIGNED_CHAR PACKSIZE (double, MPI_DOUBLE) PACKSIZE(float
 
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_LONG_LONG MPI_UNSIGNED_SHORT MPI_UNSIGNED_CHAR MPI_FLOAT int MPIPackSize (const bool &data, const int num=1)
 return packed size of a bool
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const int &data)
 insert an int
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const u_int &data)
 insert a u_int
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const long &data)
 insert a long
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const u_long &data)
 insert a u_long
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const long long &data)
 insert a long long
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const unsigned long long &data)
 insert a unsigned long long
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const short &data)
 insert a short
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const u_short &data)
 insert a u_short
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const char &data)
 insert a char
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const u_char &data)
 insert a u_char
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const double &data)
 insert a double
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const float &data)
 insert a float
 
MPIPackBuffer & operator<< (MPIPackBuffer &buff, const bool &data)
 insert a bool
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, int &data)
 extract an int
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, u_int &data)
 extract a u_int
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, long &data)
 extract a long
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, u_long &data)
 extract a u_long
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, long long &data)
 extract a long long
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, unsigned long long &data)
 extract an unsigned long long
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, short &data)
 extract a short
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, u_short &data)
 extract a u_short
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, char &data)
 extract a char
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, u_char &data)
 extract a u_char
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, double &data)
 extract a double
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, float &data)
 extract a float
 
MPIUnpackBuffer & operator>> (MPIUnpackBuffer &buff, bool &data)
 extract a bool
 
int MPIPackSize (const int &data, const int num=1)
 return packed size of an int
 
int MPIPackSize (const u_int &data, const int num=1)
 return packed size of a u_int
 
int MPIPackSize (const long &data, const int num=1)
 return packed size of a long
 
int MPIPackSize (const u_long &data, const int num=1)
 return packed size of a u_long
 
int MPIPackSize (const long long &data, const int num=1)
 return packed size of a long long
 
int MPIPackSize (const unsigned long long &data, const int num=1)
 return packed size of an unsigned long long
 
int MPIPackSize (const short &data, const int num=1)
 return packed size of a short
 
int MPIPackSize (const u_short &data, const int num=1)
 return packed size of a u_short
 
int MPIPackSize (const char &data, const int num=1)
 return packed size of a char
 
int MPIPackSize (const u_char &data, const int num=1)
 return packed size of a u_char
 
int MPIPackSize (const double &data, const int num=1)
 return packed size of a double
 
int MPIPackSize (const float &data, const int num=1)
 return packed size of a float
 
int nidr_parse (const char *, FILE *)
 
const char ** arg_list_adjust (const char **, void **)
 
int not_executable (const char *driver_name, const char *tdir)
 
static void scale_chk (StringArray &ST, RealVector &S, const char *what, const char **univ)
 
static void BuildLabels (StringArray *sa, size_t nsa, size_t n1, size_t n2, const char *stub)
 
static int mixed_check (IntSet *S, int n, IntArray *iv, const char *what)
 
static void mixed_check2 (size_t n, IntArray *iv, const char *what)
 
static int wronglen (size_t n, RealVector *V, const char *what)
 
static int wronglen (size_t n, IntVector *V, const char *what)
 
static void Vcopyup (RealVector *V, RealVector *M, size_t i, size_t n)
 
static void Set_rv (RealVector *V, double d, size_t n)
 
static void Set_iv (IntVector *V, int d, size_t n)
 
static void wrong_number (const char *what, const char *kind, size_t nsv, size_t m)
 
static void too_small (const char *kind)
 
static void not_div (const char *kind, size_t nsv, size_t m)
 
static void suppressed (const char *kind, int ndup, int *ip, String *sp, Real *rp)
 
static void bad_initial_ivalue (const char *kind, int val)
 
static void bad_initial_svalue (const char *kind, String val)
 
static void bad_initial_rvalue (const char *kind, Real val)
 
static void Vgen_ContinuousDes (DataVariablesRep *dv, size_t offset)
 
static void Vgen_DiscreteDesRange (DataVariablesRep *dv, size_t offset)
 
static void Vgen_ContinuousState (DataVariablesRep *dv, size_t offset)
 
static void Vgen_DiscreteStateRange (DataVariablesRep *dv, size_t offset)
 
static void Vchk_NormalUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_NormalUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_LognormalUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_LognormalUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_UniformUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_UniformUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_LoguniformUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_LoguniformUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_TriangularUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_TriangularUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_ExponentialUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_ExponentialUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_BetaUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_BetaUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_GammaUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_GammaUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_GumbelUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_GumbelUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_FrechetUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_FrechetUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_WeibullUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_WeibullUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_HistogramBinUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 Check the histogram bin input data, normalize the counts and populate the histogramUncBinPairs map data structure; map keys are guaranteed unique since the abscissas must increase.
 
static void Vgen_HistogramBinUnc (DataVariablesRep *dv, size_t offset)
 Infer lower/upper bounds for histogram and set initial variable values based on initial_point or moments, snapping to bounds as needed. (Histogram bin doesn't have lower/upper bounds specifcation)
 
static void Vchk_PoissonUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_PoissonUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_BinomialUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_BinomialUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_NegBinomialUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_NegBinomialUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_GeometricUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_GeometricUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_HyperGeomUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_HyperGeomUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_HistogramPtIntUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 Check the histogram point integer input data, normalize the counts, and populate DataVariables::histogramUncPointIntPairs; map keys are guaranteed unique since the abscissas must increase.
 
static void Vgen_HistogramPtIntUnc (DataVariablesRep *dv, size_t offset)
 Use the integer-valued point histogram data to initialize the lower, upper, and initial values of the variables, using value closest to mean if no initial point.
 
static void Vchk_HistogramPtStrUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 Check the histogram point string input data, normalize the counts, and populate DataVariables::histogramUncPointStrPairs; map keys are guaranteed unique since the abscissas must increase (lexicographically)
 
static void Vgen_HistogramPtStrUnc (DataVariablesRep *dv, size_t offset)
 Use the string-valued point histogram data to initialize the lower, upper, and initial values of the variables, using index closest to mean index if no initial point.
 
static void Vchk_HistogramPtRealUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 Check the histogram point integer real data, normalize the counts, and populate DataVariables::histogramUncPointRealPairs; map keys are guaranteed unique since the abscissas must increase.
 
static void Vgen_HistogramPtRealUnc (DataVariablesRep *dv, size_t offset)
 Use the real-valued point histogram data to initialize the lower, upper, and initial values of the variables, using value closest to mean if no initial point.
 
static void Vchk_ContinuousIntervalUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 Check the continuous interval uncertain input data and populate DataVariables::continuousIntervalUncBasicProbs; map keys (real intervals) are checked for uniqueness because we don't have a theoretically sound way to combine duplicate intervals.
 
static void Vgen_ContinuousIntervalUnc (DataVariablesRep *dv, size_t offset)
 
static void Vchk_DiscreteIntervalUnc (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 Check the discrete interval uncertain input data and populate DataVariables::discreteIntervalUncBasicProbs; map keys (integer intervals) are checked for uniqueness because we don't have a theoretically sound way to combine duplicate intervals.
 
static void Vgen_DiscreteIntervalUnc (DataVariablesRep *dv, size_t offset)
 
static bool check_set_keys (size_t num_v, size_t ds_len, const char *kind, IntArray *input_nds, int &avg_num_ds)
 validate the number of set elements (values) given the number of variables and an optional apportionment with elements_per_variable; return the average number per variable if equally distributed
 
static void Vchk_DIset (size_t num_v, const char *kind, IntArray *input_ndsi, IntVector *input_dsi, IntSetArray &dsi_all, IntVector &dsi_init_pt)
 check discrete sets of integers (design and state variables); error if a duplicate value is specified error if not ordered to prevent user confusion
 
static void Vchk_DIset (size_t num_v, const char *kind, IntArray *input_ndsi, IntVector *input_dsi, RealVector *input_dsip, IntRealMapArray &dsi_vals_probs, IntVector &dsi_init_pt)
 check discrete sets of integers (uncertain variables); error if a duplicate value is specified error if not ordered to prevent user confusion
 
static void Vchk_DSset (size_t num_v, const char *kind, IntArray *input_ndss, StringArray *input_dss, StringSetArray &dss_all, StringArray &dss_init_pt)
 
static void Vchk_DSset (size_t num_v, const char *kind, IntArray *input_ndss, StringArray *input_dss, RealVector *input_dssp, StringRealMapArray &dss_vals_probs, StringArray &dss_init_pt)
 
static void Vchk_DRset (size_t num_v, const char *kind, IntArray *input_ndsr, RealVector *input_dsr, RealSetArray &dsr_all, RealVector &dsr_init_pt)
 
static void Vchk_DRset (size_t num_v, const char *kind, IntArray *input_ndsr, RealVector *input_dsr, RealVector *input_dsrp, RealRealMapArray &dsr_vals_probs, RealVector &dsr_init_pt)
 
static void Vchk_Adjacency (size_t num_v, const char *kind, const IntArray &num_e, const IntVector &input_ddsa, RealMatrixArray &dda_all)
 
static bool check_LUV_size (size_t num_v, IntVector &L, IntVector &U, IntVector &V, bool aggregate_LUV, size_t offset)
 
static bool check_LUV_size (size_t num_v, StringArray &L, StringArray &U, StringArray &V, bool aggregate_LUV, size_t offset)
 
static bool check_LUV_size (size_t num_v, RealVector &L, RealVector &U, RealVector &V, bool aggregate_LUV, size_t offset)
 
template<typename T >
T midpoint (T a, T b)
 Compute the midpoint of floating-point or integer range [a, b] (a <= b), possibly indices, rounding toward a if needed. (Eventually replace with C++20 midpoint, which is more general.)
 
static size_t mid_or_next_lower_index (const size_t num_inds)
 get the middle or left-of-middle index among indices [0,num_inds-1]
 
static void Vgen_DIset (size_t num_v, IntSetArray &sets, IntVector &L, IntVector &U, IntVector &V, bool aggregate_LUV=false, size_t offset=0)
 
static void Vgen_DSset (size_t num_v, StringSetArray &sets, StringArray &L, StringArray &U, StringArray &V, bool aggregate_LUV=false, size_t offset=0)
 generate lower, upper, and initial point for string-valued sets
 
static void Vgen_DIset (size_t num_v, IntRealMapArray &vals_probs, IntVector &IP, IntVector &L, IntVector &U, IntVector &V, bool aggregate_LUV=false, size_t offset=0)
 
static void Vgen_DRset (size_t num_v, RealSetArray &sets, RealVector &L, RealVector &U, RealVector &V, bool aggregate_LUV=false, size_t offset=0)
 
static void Vgen_DRset (size_t num_v, RealRealMapArray &vals_probs, RealVector &IP, RealVector &L, RealVector &U, RealVector &V, bool aggregate_LUV=false, size_t offset=0)
 
static void Vgen_DSset (size_t num_v, StringRealMapArray &vals_probs, StringArray &IP, StringArray &L, StringArray &U, StringArray &V, bool aggregate_LUV=false, size_t offset=0)
 
static void Vchk_DiscreteDesSetInt (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_DiscreteDesSetInt (DataVariablesRep *dv, size_t offset)
 
static void Vchk_DiscreteDesSetStr (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_DiscreteDesSetStr (DataVariablesRep *dv, size_t offset)
 
static void Vchk_DiscreteDesSetReal (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_DiscreteDesSetReal (DataVariablesRep *dv, size_t offset)
 
static void Vchk_DiscreteUncSetInt (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_DiscreteUncSetInt (DataVariablesRep *dv, size_t offset)
 
static void Vchk_DiscreteUncSetStr (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_DiscreteUncSetStr (DataVariablesRep *dv, size_t offset)
 
static void Vchk_DiscreteUncSetReal (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_DiscreteUncSetReal (DataVariablesRep *dv, size_t offset)
 
static void Vchk_DiscreteStateSetInt (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_DiscreteStateSetInt (DataVariablesRep *dv, size_t offset)
 
static void Vchk_DiscreteStateSetStr (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_DiscreteStateSetStr (DataVariablesRep *dv, size_t offset)
 
static void Vchk_DiscreteStateSetReal (DataVariablesRep *dv, size_t offset, Var_Info *vi)
 
static void Vgen_DiscreteStateSetReal (DataVariablesRep *dv, size_t offset)
 
static const char * Var_Name (StringArray *sa, char *buf, size_t i)
 
static void Var_RealBoundIPCheck (DataVariablesRep *dv, Var_rcheck *b)
 For real-valued variables: verify lengths of bounds and initial point, validate bounds and adjust initial point to bounds.
 
static void Var_IntBoundIPCheck (DataVariablesRep *dv, Var_icheck *ib)
 For integer-valued variables: verify lengths of bounds and initial point, validate bounds and initial point against bounds.
 
static void flatten_rva (RealVectorArray *rva, RealVector **prv)
 
static void flatten_iva (IntVectorArray *iva, IntVector **piv)
 
static void flatten_rsm (RealSymMatrix *rsm, RealVector **prv)
 
static void flatten_rsa (RealSetArray *rsa, RealVector **prv)
 
static void flatten_ssa (StringSetArray *ssa, StringArray **psa)
 
static void flatten_isa (IntSetArray *isa, IntVector **piv)
 
static void flatten_rrma_keys (RealRealMapArray *rrma, RealVector **prv)
 
static void flatten_rrma_values (RealRealMapArray *rrma, RealVector **prv)
 
static void flatten_irma_keys (IntRealMapArray *irma, IntVector **piv)
 
static void flatten_irma_values (IntRealMapArray *irma, RealVector **prv)
 
static void flatten_srma_keys (StringRealMapArray *srma, StringArray **psa)
 
static void flatten_srma_values (StringRealMapArray *srma, RealVector **prv)
 
static void flatten_real_intervals (const RealRealPairRealMapArray &rrprma, RealVector **probs, RealVector **lb, RealVector **ub)
 Flatten real-valued interval uncertain variable intervals and probabilities back into separate arrays.
 
static void flatten_int_intervals (const IntIntPairRealMapArray &iiprma, RealVector **probs, IntVector **lb, IntVector **ub)
 Flatten integer-valued interval uncertain variable intervals and probabilities back into separate arrays.
 
static void var_iulbl (const char *keyname, Values *val, VarLabel *vl)
 
static Iface_mp_Rlit MP3 (failAction, recoveryFnVals, recover)
 
static Iface_mp_ilit MP3 (failAction, retryLimit, retry)
 
static Iface_mp_lit MP2 (failAction, abort)
 
static Iface_mp_lit MP2 (failAction, continuation)
 
static Iface_mp_type MP2s (analysisScheduling, MASTER_SCHEDULING)
 
static Iface_mp_type MP2s (analysisScheduling, PEER_SCHEDULING)
 
static Iface_mp_type MP2s (evalScheduling, MASTER_SCHEDULING)
 
static Iface_mp_type MP2s (evalScheduling, PEER_DYNAMIC_SCHEDULING)
 
static Iface_mp_type MP2s (evalScheduling, PEER_STATIC_SCHEDULING)
 
static Iface_mp_type MP2s (asynchLocalEvalScheduling, DYNAMIC_SCHEDULING)
 
static Iface_mp_type MP2s (asynchLocalEvalScheduling, STATIC_SCHEDULING)
 
static Iface_mp_utype MP2s (interfaceType, TEST_INTERFACE)
 
static Iface_mp_utype MP2s (interfaceType, FORK_INTERFACE)
 
static Iface_mp_utype MP2s (interfaceType, GRID_INTERFACE)
 
static Iface_mp_utype MP2s (interfaceType, LEGACY_PYTHON_INTERFACE)
 
static Iface_mp_utype MP2s (interfaceType, MATLAB_INTERFACE)
 
static Iface_mp_utype MP2s (interfaceType, PLUGIN_INTERFACE)
 
static Iface_mp_utype MP2s (interfaceType, PYTHON_INTERFACE)
 
static Iface_mp_utype MP2s (interfaceType, SCILAB_INTERFACE)
 
static Iface_mp_utype MP2s (interfaceType, SYSTEM_INTERFACE)
 
static Iface_mp_utype MP2s (resultsFileFormat, LABELED_RESULTS)
 
static String MP_ (algebraicMappings)
 
static String MP_ (idInterface)
 
static String MP_ (inputFilter)
 
static String MP_ (outputFilter)
 
static String MP_ (parametersFile)
 
static String MP_ (pluginLibraryPath)
 
static String MP_ (resultsFile)
 
static String MP_ (workDir)
 
static String2DArray MP_ (analysisComponents)
 
static StringArray MP_ (analysisDrivers)
 
static StringArray MP_ (copyFiles)
 
static StringArray MP_ (linkFiles)
 
static bool MP_ (activeSetVectorFlag)
 
static bool MP_ (allowExistingResultsFlag)
 
static bool MP_ (apreproFlag)
 
static bool MP_ (asynchFlag)
 
static bool MP_ (batchEvalFlag)
 
static bool MP_ (dirSave)
 
static bool MP_ (dirTag)
 
static bool MP_ (evalCacheFlag)
 
static bool MP_ (fileSaveFlag)
 
static bool MP_ (fileTagFlag)
 
static bool MP_ (nearbyEvalCacheFlag)
 
static bool MP_ (numpyFlag)
 
static bool MP_ (restartFileFlag)
 
static bool MP_ (templateReplace)
 
static bool MP_ (useWorkdir)
 
static bool MP_ (verbatimFlag)
 
static int MP_ (analysisServers)
 
static int MP_ (asynchLocalAnalysisConcurrency)
 
static int MP_ (asynchLocalEvalConcurrency)
 
static int MP_ (evalServers)
 
static int MP_ (procsPerAnalysis)
 
static int MP_ (procsPerEval)
 
static Real MP_ (nearbyEvalCacheTol)
 
static IntVector MP_ (primeBase)
 
static IntVector MP_ (refineSamples)
 
static IntVector MP_ (sequenceLeap)
 
static IntVector MP_ (sequenceStart)
 
static IntVector MP_ (stepsPerVariable)
 
static Method_mp_ilit2 MP3 (replacementType, numberRetained, chc)
 
static Method_mp_ilit2 MP3 (replacementType, numberRetained, elitist)
 
static Method_mp_ilit2 MP3 (replacementType, numberRetained, random)
 
static Method_mp_ilit2z MP3 (crossoverType, numCrossPoints, multi_point_binary)
 
static Method_mp_ilit2z MP3 (crossoverType, numCrossPoints, multi_point_parameterized_binary)
 
static Method_mp_ilit2z MP3 (crossoverType, numCrossPoints, multi_point_real)
 
static Method_mp_lit MP2 (batchSelectionType, naive)
 
static Method_mp_lit MP2 (batchSelectionType, distance)
 
static Method_mp_lit MP2 (batchSelectionType, topology)
 
static Method_mp_lit MP2 (batchSelectionType, cl)
 
static Method_mp_lit MP2 (boxDivision, all_dimensions)
 
static Method_mp_lit MP2 (boxDivision, major_dimension)
 
static Method_mp_lit MP2 (convergenceType, average_fitness_tracker)
 
static Method_mp_lit MP2 (convergenceType, best_fitness_tracker)
 
static Method_mp_lit MP2 (convergenceType, metric_tracker)
 
static Method_mp_lit MP2 (crossoverType, blend)
 
static Method_mp_lit MP2 (crossoverType, two_point)
 
static Method_mp_lit MP2 (crossoverType, uniform)
 
static Method_mp_lit MP2 (dataDistCovInputType, diagonal)
 
static Method_mp_lit MP2 (dataDistCovInputType, matrix)
 
static Method_mp_lit MP2 (exploratoryMoves, adaptive)
 
static Method_mp_lit MP2 (exploratoryMoves, multi_step)
 
static Method_mp_lit MP2 (exploratoryMoves, simple)
 
static Method_mp_lit MP2 (fitnessType, domination_count)
 
static Method_mp_lit MP2 (fitnessType, layer_rank)
 
static Method_mp_lit MP2 (fitnessType, linear_rank)
 
static Method_mp_lit MP2 (fitnessType, merit_function)
 
static Method_mp_lit MP2 (fitnessType, proportional)
 
static Method_mp_lit MP2 (fitnessMetricType, predicted_variance)
 
static Method_mp_lit MP2 (fitnessMetricType, distance)
 
static Method_mp_lit MP2 (fitnessMetricType, gradient)
 
static Method_mp_lit MP2 (initializationType, random)
 
static Method_mp_lit MP2 (initializationType, unique_random)
 
static Method_mp_lit MP2 (lipschitzType, global)
 
static Method_mp_lit MP2 (lipschitzType, local)
 
static Method_mp_lit MP2 (meritFunction, merit_max)
 
static Method_mp_lit MP2 (meritFunction, merit_max_smooth)
 
static Method_mp_lit MP2 (meritFunction, merit1)
 
static Method_mp_lit MP2 (meritFunction, merit1_smooth)
 
static Method_mp_lit MP2 (meritFunction, merit2)
 
static Method_mp_lit MP2 (meritFunction, merit2_smooth)
 
static Method_mp_lit MP2 (meritFunction, merit2_squared)
 
static Method_mp_lit MP2 (mcmcType, adaptive_metropolis)
 
static Method_mp_lit MP2 (mcmcType, delayed_rejection)
 
static Method_mp_lit MP2 (mcmcType, dram)
 
static Method_mp_lit MP2 (mcmcType, metropolis_hastings)
 
static Method_mp_lit MP2 (mcmcType, multilevel)
 
static Method_mp_lit MP2 (modelDiscrepancyType, global_kriging)
 
static Method_mp_lit MP2 (modelDiscrepancyType, global_polynomial)
 
static Method_mp_lit MP2 (mutationType, bit_random)
 
static Method_mp_lit MP2 (mutationType, offset_cauchy)
 
static Method_mp_lit MP2 (mutationType, offset_normal)
 
static Method_mp_lit MP2 (mutationType, offset_uniform)
 
static Method_mp_lit MP2 (mutationType, replace_uniform)
 
static Method_mp_lit MP2 (patternBasis, coordinate)
 
static Method_mp_lit MP2 (patternBasis, simplex)
 
static Method_mp_lit MP2 (pointReuse, all)
 
static Method_mp_lit MP2 (proposalCovInputType, diagonal)
 
static Method_mp_lit MP2 (proposalCovInputType, matrix)
 
static Method_mp_lit MP2 (proposalCovType, derivatives)
 
static Method_mp_lit MP2 (proposalCovType, prior)
 
static Method_mp_lit MP2 (proposalCovType, user)
 
static Method_mp_lit MP2 (reliabilityIntegration, first_order)
 
static Method_mp_lit MP2 (reliabilityIntegration, second_order)
 
static Method_mp_lit MP2 (replacementType, elitist)
 
static Method_mp_lit MP2 (replacementType, favor_feasible)
 
static Method_mp_lit MP2 (replacementType, roulette_wheel)
 
static Method_mp_lit MP2 (replacementType, unique_roulette_wheel)
 
static Method_mp_lit MP2 (rngName, mt19937)
 
static Method_mp_lit MP2 (rngName, rnum2)
 
static Method_mp_lit MP2 (searchMethod, gradient_based_line_search)
 
static Method_mp_lit MP2 (searchMethod, tr_pds)
 
static Method_mp_lit MP2 (searchMethod, trust_region)
 
static Method_mp_lit MP2 (searchMethod, value_based_line_search)
 
static Method_mp_lit MP2 (trialType, grid)
 
static Method_mp_lit MP2 (trialType, halton)
 
static Method_mp_lit MP2 (trialType, random)
 
static Method_mp_lit MP2 (useSurrogate, inform_search)
 
static Method_mp_lit MP2 (useSurrogate, optimize)
 
static Method_mp_litc MP3 (crossoverType, crossoverRate, shuffle_random)
 
static Method_mp_litc MP3 (crossoverType, crossoverRate, null_crossover)
 
static Method_mp_litc MP3 (mutationType, mutationRate, null_mutation)
 
static Method_mp_litc MP3 (mutationType, mutationRate, offset_cauchy)
 
static Method_mp_litc MP3 (mutationType, mutationRate, offset_normal)
 
static Method_mp_litc MP3 (mutationType, mutationRate, offset_uniform)
 
static Method_mp_litc MP3 (replacementType, fitnessLimit, below_limit)
 
static Method_mp_litrv MP3 (nichingType, nicheVector, distance)
 
static Method_mp_litrv MP3 (nichingType, nicheVector, max_designs)
 
static Method_mp_litrv MP3 (nichingType, nicheVector, radial)
 
static Method_mp_litrv MP3 (postProcessorType, distanceVector, distance_postprocessor)
 
static Method_mp_slit2 MP3 (initializationType, flatFile, flat_file)
 
static Method_mp_utype_lit MP3s (methodName, dlDetails, DL_SOLVER)
 
static Real MP_ (absConvTol)
 
static Real MP_ (centeringParam)
 
static Real MP_ (collocationRatio)
 
static Real MP_ (collocRatioTermsOrder)
 
static Real MP_ (constraintPenalty)
 
static Real MP_ (constrPenalty)
 
static Real MP_ (constraintTolerance)
 
static Real MP_ (contractFactor)
 
static Real MP_ (contractStepLength)
 
static Real MP_ (convergenceTolerance)
 
static Real MP_ (crossoverRate)
 
static Real MP_ (falseConvTol)
 
static Real MP_ (functionPrecision)
 
static Real MP_ (globalBalanceParam)
 
static Real MP_ (gradientTolerance)
 
static Real MP_ (hybridLSProb)
 
static Real MP_ (grThreshold)
 
static Real MP_ (initDelta)
 
static Real MP_ (initMeshSize)
 
static Real MP_ (initStepLength)
 
static Real MP_ (initTRRadius)
 
static Real MP_ (lineSearchTolerance)
 
static Real MP_ (localBalanceParam)
 
static Real MP_ (maxBoxSize)
 
static Real MP_ (maxStep)
 
static Real MP_ (minBoxSize)
 
static Real MP_ (minMeshSize)
 
static Real MP_ (multilevEstimatorRate)
 
static Real MP_ (mutationRate)
 
static Real MP_ (mutationScale)
 
static Real MP_ (percentVarianceExplained)
 
static Real MP_ (priorPropCovMult)
 
static Real MP_ (refinementRate)
 
static Real MP_ (regressionL2Penalty)
 
static Real MP_ (shrinkagePercent)
 
static Real MP_ (singConvTol)
 
static Real MP_ (singRadius)
 
static Real MP_ (smoothFactor)
 
static Real MP_ (solnTarget)
 
static Real MP_ (solverRoundingTol)
 
static Real MP_ (solverTol)
 
static Real MP_ (statsRoundingTol)
 
static Real MP_ (stepLenToBoundary)
 
static Real MP_ (threshDelta)
 
static Real MP_ (threshStepLength)
 
static Real MP_ (trustRegionContract)
 
static Real MP_ (trustRegionContractTrigger)
 
static Real MP_ (trustRegionExpand)
 
static Real MP_ (trustRegionExpandTrigger)
 
static Real MP_ (trustRegionMinSize)
 
static Real MP_ (vbdDropTolerance)
 
static Real MP_ (volBoxSize)
 
static Real MP_ (vns)
 
static Real MP_ (wilksConfidenceLevel)
 
static Real MP_ (xConvTol)
 
static RealVector MP_ (anisoDimPref)
 
static RealVector MP_ (concurrentParameterSets)
 
static RealVector MP_ (dataDistCovariance)
 
static RealVector MP_ (dataDistMeans)
 
static RealVector MP_ (finalPoint)
 
static RealVector MP_ (hyperPriorAlphas)
 
static RealVector MP_ (hyperPriorBetas)
 
static RealVector MP_ (listOfPoints)
 
static RealVector MP_ (predictionConfigList)
 
static RealVector MP_ (proposalCovData)
 
static RealVector MP_ (regressionNoiseTol)
 
static RealVector MP_ (scalarizationRespCoeffs)
 
static RealVector MP_ (stepVector)
 
static RealVector MP_ (trustRegionInitSize)
 
static RealVectorArray MP_ (genReliabilityLevels)
 
static RealVectorArray MP_ (probabilityLevels)
 
static RealVectorArray MP_ (reliabilityLevels)
 
static RealVectorArray MP_ (responseLevels)
 
static unsigned short MP_ (adaptedBasisAdvancements)
 
static unsigned short MP_ (cubIntOrder)
 
static unsigned short MP_ (expansionOrder)
 
static unsigned short MP_ (kickOrder)
 
static unsigned short MP_ (maxCVOrderCandidates)
 
static unsigned short MP_ (maxOrder)
 
static unsigned short MP_ (quadratureOrder)
 
static unsigned short MP_ (softConvLimit)
 
static unsigned short MP_ (sparseGridLevel)
 
static unsigned short MP_ (startOrder)
 
static unsigned short MP_ (vbdOrder)
 
static unsigned short MP_ (wilksOrder)
 
static SizetArray MP_ (collocationPointsSeq)
 
static SizetArray MP_ (expansionSamplesSeq)
 
static SizetArray MP_ (pilotSamples)
 
static SizetArray MP_ (randomSeedSeq)
 
static SizetArray MP_ (startRankSeq)
 
static UShortArray MP_ (expansionOrderSeq)
 
static UShortArray MP_ (quadratureOrderSeq)
 
static UShortArray MP_ (sparseGridLevelSeq)
 
static UShortArray MP_ (startOrderSeq)
 
static UShortArray MP_ (tensorGridOrder)
 
static UShortArray MP_ (varPartitions)
 
static String MP_ (advancedOptionsFilename)
 
static String MP_ (betaSolverName)
 
static String MP_ (dataDistFile)
 
static String MP_ (displayFormat)
 
static String MP_ (exportApproxPtsFile)
 
static String MP_ (exportCorrModelFile)
 
static String MP_ (exportCorrVarFile)
 
static String MP_ (exportDiscrepFile)
 
static String MP_ (exportExpansionFile)
 
static String MP_ (exportMCMCPtsFile)
 
static String MP_ (historyFile)
 
static String MP_ (hybridGlobalMethodName)
 
static String MP_ (hybridGlobalMethodPointer)
 
static String MP_ (hybridGlobalModelPointer)
 
static String MP_ (hybridLocalMethodName)
 
static String MP_ (hybridLocalMethodPointer)
 
static String MP_ (hybridLocalModelPointer)
 
static String MP_ (idMethod)
 
static String MP_ (importApproxPtsFile)
 
static String MP_ (importBuildPtsFile)
 
static String MP_ (importCandPtsFile)
 
static String MP_ (importExpansionFile)
 
static String MP_ (importPredConfigs)
 
static String MP_ (logFile)
 
static String MP_ (lowFidModelPointer)
 
static String MP_ (modelExportPrefix)
 
static String MP_ (modelPointer)
 
static String MP_ (posteriorDensityExportFilename)
 
static String MP_ (posteriorSamplesExportFilename)
 
static String MP_ (posteriorSamplesImportFilename)
 
static String MP_ (proposalCovFile)
 
static String MP_ (pstudyFilename)
 
static String MP_ (subMethodName)
 
static String MP_ (subMethodPointer)
 
static String MP_ (subModelPointer)
 
static StringArray MP_ (hybridMethodNames)
 
static StringArray MP_ (hybridMethodPointers)
 
static StringArray MP_ (hybridModelPointers)
 
static StringArray MP_ (miscOptions)
 
static bool MP_ (adaptExpDesign)
 
static bool MP_ (adaptOrder)
 
static bool MP_ (adaptPosteriorRefine)
 
static bool MP_ (adaptRank)
 
static bool MP_ (backfillFlag)
 
static bool MP_ (calModelDiscrepancy)
 
static bool MP_ (chainDiagnostics)
 
static bool MP_ (chainDiagnosticsCI)
 
static bool MP_ (constantPenalty)
 
static bool MP_ (crossValidation)
 
static bool MP_ (crossValidNoiseOnly)
 
static bool MP_ (dOptimal)
 
static bool MP_ (evaluatePosteriorDensity)
 
static bool MP_ (expansionFlag)
 
static bool MP_ (exportSampleSeqFlag)
 
static bool MP_ (exportSurrogate)
 
static bool MP_ (fixedSeedFlag)
 
static bool MP_ (fixedSequenceFlag)
 
static bool MP_ (generatePosteriorSamples)
 
static bool MP_ (gpmsaNormalize)
 
static bool MP_ (importApproxActive)
 
static bool MP_ (importBuildActive)
 
static bool MP_ (latinizeFlag)
 
static bool MP_ (logitTransform)
 
static bool MP_ (mainEffectsFlag)
 
static bool MP_ (methodScaling)
 
static bool MP_ (methodUseDerivsFlag)
 
static bool MP_ (modelEvidence)
 
static bool MP_ (modelEvidLaplace)
 
static bool MP_ (modelEvidMC)
 
static bool MP_ (mutualInfoKSG2)
 
static bool MP_ (mutationAdaptive)
 
static bool MP_ (normalizedCoeffs)
 
static bool MP_ (pcaFlag)
 
static bool MP_ (posteriorStatsKL)
 
static bool MP_ (posteriorStatsKDE)
 
static bool MP_ (posteriorStatsMutual)
 
static bool MP_ (printPopFlag)
 
static bool MP_ (pstudyFileActive)
 
static bool MP_ (randomizeOrderFlag)
 
static bool MP_ (regressDiag)
 
static bool MP_ (relativeConvMetric)
 
static bool MP_ (respScalingFlag)
 
static bool MP_ (showAllEval)
 
static bool MP_ (showMiscOptions)
 
static bool MP_ (speculativeFlag)
 
static bool MP_ (standardizedSpace)
 
static bool MP_ (useTargetVarianceOptimizationFlag)
 
static bool MP_ (tensorGridFlag)
 
static bool MP_ (surrBasedGlobalReplacePts)
 
static bool MP_ (surrBasedLocalLayerBypass)
 
static bool MP_ (truthPilotConstraint)
 
static bool MP_ (vbdFlag)
 
static bool MP_ (volQualityFlag)
 
static bool MP_ (wilksFlag)
 
static short MP_ (polynomialOrder)
 
static int MP_ (batchSize)
 
static int MP_ (batchSizeExplore)
 
static int MP_ (buildSamples)
 
static int MP_ (burnInSamples)
 
static int MP_ (chainSamples)
 
static int MP_ (concurrentRandomJobs)
 
static int MP_ (contractAfterFail)
 
static int MP_ (covarianceType)
 
static int MP_ (crossoverChainPairs)
 
static int MP_ (emulatorOrder)
 
static int MP_ (expandAfterSuccess)
 
static int MP_ (evidenceSamples)
 
static int MP_ (iteratorServers)
 
static int MP_ (jumpStep)
 
static int MP_ (maxCrossIterations)
 
static int MP_ (maxHifiEvals)
 
static int MP_ (mutationRange)
 
static int MP_ (neighborOrder)
 
static int MP_ (newSolnsGenerated)
 
static int MP_ (numChains)
 
static int MP_ (numCR)
 
static int MP_ (numSamples)
 
static int MP_ (numSteps)
 
static int MP_ (numSymbols)
 
static int MP_ (numTrials)
 
static int MP_ (populationSize)
 
static int MP_ (procsPerIterator)
 
static int MP_ (proposalCovUpdatePeriod)
 
static int MP_ (numPushforwardSamples)
 
static int MP_ (randomSeed)
 
static int MP_ (samplesOnEmulator)
 
static int MP_ (searchSchemeSize)
 
static int MP_ (subSamplingPeriod)
 
static int MP_ (totalPatternSize)
 
static int MP_ (verifyLevel)
 
static size_t MP_ (collocationPoints)
 
static size_t MP_ (expansionSamples)
 
static size_t MP_ (kickRank)
 
static size_t MP_ (maxCVRankCandidates)
 
static size_t MP_ (maxFunctionEvals)
 
static size_t MP_ (maxIterations)
 
static size_t MP_ (maxRank)
 
static size_t MP_ (maxRefineIterations)
 
static size_t MP_ (maxSolverIterations)
 
static size_t MP_ (numCandidateDesigns)
 
static size_t MP_ (numCandidates)
 
static size_t MP_ (numDesigns)
 
static size_t MP_ (numFinalSolutions)
 
static size_t MP_ (numGenerations)
 
static size_t MP_ (numOffspring)
 
static size_t MP_ (numParents)
 
static size_t MP_ (numPredConfigs)
 
static size_t MP_ (startRank)
 
static Method_mp_type MP2s (allocationTarget, TARGET_MEAN)
 
static Method_mp_type MP2s (allocationTarget, TARGET_SCALARIZATION)
 
static Method_mp_type MP2s (allocationTarget, TARGET_SIGMA)
 
static Method_mp_type MP2s (allocationTarget, TARGET_VARIANCE)
 
static Method_mp_type MP2s (c3AdvanceType, MAX_ORDER_ADVANCEMENT)
 
static Method_mp_type MP2s (c3AdvanceType, MAX_RANK_ADVANCEMENT)
 
static Method_mp_type MP2s (c3AdvanceType, MAX_RANK_ORDER_ADVANCEMENT)
 
static Method_mp_type MP2s (c3AdvanceType, START_ORDER_ADVANCEMENT)
 
static Method_mp_type MP2s (c3AdvanceType, START_RANK_ADVANCEMENT)
 
static Method_mp_type MP2s (convergenceToleranceTarget, CONVERGENCE_TOLERANCE_TARGET_COST_CONSTRAINT)
 
static Method_mp_type MP2s (convergenceToleranceTarget, CONVERGENCE_TOLERANCE_TARGET_VARIANCE_CONSTRAINT)
 
static Method_mp_type MP2s (convergenceToleranceType, CONVERGENCE_TOLERANCE_TYPE_ABSOLUTE)
 
static Method_mp_type MP2s (convergenceToleranceType, CONVERGENCE_TOLERANCE_TYPE_RELATIVE)
 
static Method_mp_type MP2s (covarianceControl, DIAGONAL_COVARIANCE)
 
static Method_mp_type MP2s (covarianceControl, FULL_COVARIANCE)
 
static Method_mp_type MP2s (distributionType, COMPLEMENTARY)
 
static Method_mp_type MP2s (distributionType, CUMULATIVE)
 
static Method_mp_type MP2s (emulatorType, EXPGP_EMULATOR)
 
static Method_mp_type MP2s (emulatorType, GP_EMULATOR)
 
static Method_mp_type MP2s (emulatorType, KRIGING_EMULATOR)
 
static Method_mp_type MP2s (emulatorType, MF_PCE_EMULATOR)
 
static Method_mp_type MP2s (emulatorType, MF_SC_EMULATOR)
 
static Method_mp_type MP2s (emulatorType, ML_PCE_EMULATOR)
 
static Method_mp_type MP2s (emulatorType, PCE_EMULATOR)
 
static Method_mp_type MP2s (emulatorType, SC_EMULATOR)
 
static Method_mp_type MP2s (emulatorType, VPS_EMULATOR)
 
static Method_mp_type MP2s (ensembleSampSolnMode, OFFLINE_PILOT)
 
static Method_mp_type MP2s (ensembleSampSolnMode, ONLINE_PILOT)
 
static Method_mp_type MP2s (ensembleSampSolnMode, PILOT_PROJECTION)
 
static Method_mp_type MP2s (evalSynchronize, BLOCKING_SYNCHRONIZATION)
 
static Method_mp_type MP2s (evalSynchronize, NONBLOCKING_SYNCHRONIZATION)
 
static Method_mp_type MP2p (expansionBasisType, ADAPTED_BASIS_EXPANDING_FRONT)
 
static Method_mp_type MP2p (expansionBasisType, ADAPTED_BASIS_GENERALIZED)
 
static Method_mp_type MP2p (expansionBasisType, HIERARCHICAL_INTERPOLANT)
 
static Method_mp_type MP2p (expansionBasisType, NODAL_INTERPOLANT)
 
static Method_mp_type MP2p (expansionBasisType, TENSOR_PRODUCT_BASIS)
 
static Method_mp_type MP2p (expansionBasisType, TOTAL_ORDER_BASIS)
 
static Method_mp_type MP2s (expansionType, ASKEY_U)
 
static Method_mp_type MP2s (expansionType, STD_NORMAL_U)
 
static Method_mp_type MP2p (finalMomentsType, CENTRAL_MOMENTS)
 
static Method_mp_type MP2p (finalMomentsType, NO_MOMENTS)
 
static Method_mp_type MP2p (finalMomentsType, STANDARD_MOMENTS)
 
static Method_mp_type MP2s (finalStatsType, ESTIMATOR_PERFORMANCE)
 
static Method_mp_type MP2s (finalStatsType, NO_FINAL_STATS)
 
static Method_mp_type MP2s (finalStatsType, QOI_STATISTICS)
 
static Method_mp_type MP2p (growthOverride, RESTRICTED)
 
static Method_mp_type MP2p (growthOverride, UNRESTRICTED)
 
static Method_mp_type MP2s (iteratorScheduling, MASTER_SCHEDULING)
 
static Method_mp_type MP2s (iteratorScheduling, PEER_SCHEDULING)
 
static Method_mp_type MP2s (lsRegressionType, EQ_CON_LS)
 
static Method_mp_type MP2s (lsRegressionType, SVD_LS)
 
static Method_mp_type MP2o (meritFn, ArgaezTapia)
 
static Method_mp_type MP2o (meritFn, NormFmu)
 
static Method_mp_type MP2o (meritFn, VanShanno)
 
static Method_mp_type MP2s (methodOutput, DEBUG_OUTPUT)
 
static Method_mp_type MP2s (methodOutput, NORMAL_OUTPUT)
 
static Method_mp_type MP2s (methodOutput, QUIET_OUTPUT)
 
static Method_mp_type MP2s (methodOutput, SILENT_OUTPUT)
 
static Method_mp_type MP2s (methodOutput, VERBOSE_OUTPUT)
 
static Method_mp_type MP2s (multilevAllocControl, ESTIMATOR_VARIANCE)
 
static Method_mp_type MP2s (multilevAllocControl, GREEDY_REFINEMENT)
 
static Method_mp_type MP2s (multilevAllocControl, RANK_SAMPLING)
 
static Method_mp_type MP2s (multilevAllocControl, RIP_SAMPLING)
 
static Method_mp_type MP2s (multilevDiscrepEmulation, DISTINCT_EMULATION)
 
static Method_mp_type MP2s (multilevDiscrepEmulation, RECURSIVE_EMULATION)
 
static Method_mp_type MP2p (nestingOverride, NESTED)
 
static Method_mp_type MP2p (nestingOverride, NON_NESTED)
 
static Method_mp_type MP2s (qoiAggregation, QOI_AGGREGATION_MAX)
 
static Method_mp_type MP2s (qoiAggregation, QOI_AGGREGATION_SUM)
 
static Method_mp_type MP2p (refinementControl, DIMENSION_ADAPTIVE_CONTROL_GENERALIZED)
 
static Method_mp_type MP2p (refinementControl, DIMENSION_ADAPTIVE_CONTROL_DECAY)
 
static Method_mp_type MP2p (refinementControl, DIMENSION_ADAPTIVE_CONTROL_SOBOL)
 
static Method_mp_type MP2p (refinementControl, LOCAL_ADAPTIVE_CONTROL)
 
static Method_mp_type MP2p (refinementControl, UNIFORM_CONTROL)
 
static Method_mp_type MP2p (refinementType, P_REFINEMENT)
 
static Method_mp_type MP2p (refinementType, H_REFINEMENT)
 
static Method_mp_type MP2p (regressionType, BASIS_PURSUIT)
 
static Method_mp_type MP2p (regressionType, BASIS_PURSUIT_DENOISING)
 
static Method_mp_type MP2p (regressionType, DEFAULT_LEAST_SQ_REGRESSION)
 
static Method_mp_type MP2p (regressionType, LASSO_REGRESSION)
 
static Method_mp_type MP2p (regressionType, LEAST_ANGLE_REGRESSION)
 
static Method_mp_type MP2p (regressionType, ORTHOG_LEAST_INTERPOLATION)
 
static Method_mp_type MP2p (regressionType, ORTHOG_MATCH_PURSUIT)
 
static Method_mp_type MP2s (regressionType, FT_LS)
 
static Method_mp_type MP2s (regressionType, FT_RLS2)
 
static Method_mp_type MP2s (responseLevelTarget, GEN_RELIABILITIES)
 
static Method_mp_type MP2s (responseLevelTarget, PROBABILITIES)
 
static Method_mp_type MP2s (responseLevelTarget, RELIABILITIES)
 
static Method_mp_type MP2s (responseLevelTargetReduce, SYSTEM_PARALLEL)
 
static Method_mp_type MP2s (responseLevelTargetReduce, SYSTEM_SERIES)
 
static Method_mp_type MP2p (statsMetricMode, ACTIVE_EXPANSION_STATS)
 
static Method_mp_type MP2p (statsMetricMode, COMBINED_EXPANSION_STATS)
 
static Method_mp_type MP2s (surrBasedLocalAcceptLogic, FILTER)
 
static Method_mp_type MP2s (surrBasedLocalAcceptLogic, TR_RATIO)
 
static Method_mp_type MP2s (surrBasedLocalConstrRelax, HOMOTOPY)
 
static Method_mp_type MP2s (surrBasedLocalMeritFn, ADAPTIVE_PENALTY_MERIT)
 
static Method_mp_type MP2s (surrBasedLocalMeritFn, AUGMENTED_LAGRANGIAN_MERIT)
 
static Method_mp_type MP2s (surrBasedLocalMeritFn, LAGRANGIAN_MERIT)
 
static Method_mp_type MP2s (surrBasedLocalMeritFn, PENALTY_MERIT)
 
static Method_mp_type MP2s (surrBasedLocalSubProbCon, LINEARIZED_CONSTRAINTS)
 
static Method_mp_type MP2s (surrBasedLocalSubProbCon, NO_CONSTRAINTS)
 
static Method_mp_type MP2s (surrBasedLocalSubProbCon, ORIGINAL_CONSTRAINTS)
 
static Method_mp_type MP2s (surrBasedLocalSubProbObj, AUGMENTED_LAGRANGIAN_OBJECTIVE)
 
static Method_mp_type MP2s (surrBasedLocalSubProbObj, LAGRANGIAN_OBJECTIVE)
 
static Method_mp_type MP2s (surrBasedLocalSubProbObj, ORIGINAL_PRIMARY)
 
static Method_mp_type MP2s (surrBasedLocalSubProbObj, SINGLE_OBJECTIVE)
 
static Method_mp_type MP2s (wilksSidedInterval, ONE_SIDED_LOWER)
 
static Method_mp_type MP2s (wilksSidedInterval, ONE_SIDED_UPPER)
 
static Method_mp_type MP2s (wilksSidedInterval, TWO_SIDED)
 
static Method_mp_utype MP2s (calibrateErrorMode, CALIBRATE_ONE)
 
static Method_mp_utype MP2s (calibrateErrorMode, CALIBRATE_PER_EXPER)
 
static Method_mp_utype MP2s (calibrateErrorMode, CALIBRATE_PER_RESP)
 
static Method_mp_utype MP2s (calibrateErrorMode, CALIBRATE_BOTH)
 
static Method_mp_utype MP2s (exportApproxFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (exportApproxFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (exportApproxFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (exportApproxFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (exportApproxFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (exportCorrModelFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (exportCorrModelFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (exportCorrModelFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (exportCorrModelFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (exportCorrModelFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (exportCorrVarFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (exportCorrVarFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (exportCorrVarFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (exportCorrVarFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (exportCorrVarFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (exportDiscrepFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (exportDiscrepFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (exportDiscrepFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (exportDiscrepFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (exportDiscrepFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (exportSamplesFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (exportSamplesFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (exportSamplesFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (exportSamplesFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (exportSamplesFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (importApproxFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (importApproxFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (importApproxFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (importApproxFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (importApproxFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (importBuildFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (importBuildFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (importBuildFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (importBuildFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (importBuildFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (importCandFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (importCandFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (importCandFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (importCandFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (importCandFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (importPredConfigFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (importPredConfigFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (importPredConfigFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (importPredConfigFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (importPredConfigFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (integrationRefine, AIS)
 
static Method_mp_utype MP2s (integrationRefine, IS)
 
static Method_mp_utype MP2s (integrationRefine, MMAIS)
 
static Method_mp_utype MP2s (methodName, APPROXIMATE_CONTROL_VARIATE)
 
static Method_mp_utype MP2s (methodName, ASYNCH_PATTERN_SEARCH)
 
static Method_mp_utype MP2s (methodName, BRANCH_AND_BOUND)
 
static Method_mp_utype MP2s (methodName, C3_FUNCTION_TRAIN)
 
static Method_mp_utype MP2s (methodName, COLINY_BETA)
 
static Method_mp_utype MP2s (methodName, COLINY_COBYLA)
 
static Method_mp_utype MP2s (methodName, COLINY_DIRECT)
 
static Method_mp_utype MP2s (methodName, COLINY_EA)
 
static Method_mp_utype MP2s (methodName, COLINY_PATTERN_SEARCH)
 
static Method_mp_utype MP2s (methodName, COLINY_SOLIS_WETS)
 
static Method_mp_utype MP2s (methodName, CONMIN_FRCG)
 
static Method_mp_utype MP2s (methodName, CONMIN_MFD)
 
static Method_mp_utype MP2s (methodName, DACE)
 
static Method_mp_utype MP2s (methodName, DATA_FIT_SURROGATE_BASED_LOCAL)
 
static Method_mp_utype MP2s (methodName, DOT_BFGS)
 
static Method_mp_utype MP2s (methodName, DOT_FRCG)
 
static Method_mp_utype MP2s (methodName, DOT_MMFD)
 
static Method_mp_utype MP2s (methodName, DOT_SLP)
 
static Method_mp_utype MP2s (methodName, DOT_SQP)
 
static Method_mp_utype MP2s (methodName, EFFICIENT_GLOBAL)
 
static Method_mp_utype MP2s (methodName, FSU_CVT)
 
static Method_mp_utype MP2s (methodName, FSU_HALTON)
 
static Method_mp_utype MP2s (methodName, FSU_HAMMERSLEY)
 
static Method_mp_utype MP2s (methodName, HIERARCH_SURROGATE_BASED_LOCAL)
 
static Method_mp_utype MP2s (methodName, HYBRID)
 
static Method_mp_utype MP2s (methodName, MESH_ADAPTIVE_SEARCH)
 
static Method_mp_utype MP2s (methodName, MOGA)
 
static Method_mp_utype MP2s (methodName, MULTI_START)
 
static Method_mp_utype MP2s (methodName, NCSU_DIRECT)
 
static Method_mp_utype MP2s (methodName, ROL)
 
static Method_mp_utype MP2s (methodName, DEMO_TPL)
 
static Method_mp_utype MP2s (methodName, NL2SOL)
 
static Method_mp_utype MP2s (methodName, NLPQL_SQP)
 
static Method_mp_utype MP2s (methodName, NLSSOL_SQP)
 
static Method_mp_utype MP2s (methodName, MIT_NOWPAC)
 
static Method_mp_utype MP2s (methodName, MIT_SNOWPAC)
 
static Method_mp_utype MP2s (methodName, ADAPTIVE_SAMPLING)
 
static Method_mp_utype MP2s (methodName, BAYES_CALIBRATION)
 
static Method_mp_utype MP2s (methodName, GENIE_DIRECT)
 
static Method_mp_utype MP2s (methodName, GENIE_OPT_DARTS)
 
static Method_mp_utype MP2s (methodName, GPAIS)
 
static Method_mp_utype MP2s (methodName, GLOBAL_EVIDENCE)
 
static Method_mp_utype MP2s (methodName, GLOBAL_INTERVAL_EST)
 
static Method_mp_utype MP2s (methodName, GLOBAL_RELIABILITY)
 
static Method_mp_utype MP2s (methodName, IMPORTANCE_SAMPLING)
 
static Method_mp_utype MP2s (methodName, LOCAL_EVIDENCE)
 
static Method_mp_utype MP2s (methodName, LOCAL_INTERVAL_EST)
 
static Method_mp_utype MP2s (methodName, LOCAL_RELIABILITY)
 
static Method_mp_utype MP2s (methodName, MULTIFIDELITY_FUNCTION_TRAIN)
 
static Method_mp_utype MP2s (methodName, MULTIFIDELITY_POLYNOMIAL_CHAOS)
 
static Method_mp_utype MP2s (methodName, MULTIFIDELITY_SAMPLING)
 
static Method_mp_utype MP2s (methodName, MULTIFIDELITY_STOCH_COLLOCATION)
 
static Method_mp_utype MP2s (methodName, MULTILEVEL_FUNCTION_TRAIN)
 
static Method_mp_utype MP2s (methodName, MULTILEVEL_MULTIFIDELITY_SAMPLING)
 
static Method_mp_utype MP2s (methodName, MULTILEVEL_POLYNOMIAL_CHAOS)
 
static Method_mp_utype MP2s (methodName, MULTILEVEL_SAMPLING)
 
static Method_mp_utype MP2s (methodName, POF_DARTS)
 
static Method_mp_utype MP2s (methodName, RKD_DARTS)
 
static Method_mp_utype MP2s (methodName, POLYNOMIAL_CHAOS)
 
static Method_mp_utype MP2s (methodName, STOCH_COLLOCATION)
 
static Method_mp_utype MP2s (methodName, SURROGATE_BASED_UQ)
 
static Method_mp_utype MP2s (methodName, RANDOM_SAMPLING)
 
static Method_mp_utype MP2s (methodName, NONLINEAR_CG)
 
static Method_mp_utype MP2s (methodName, NPSOL_SQP)
 
static Method_mp_utype MP2s (methodName, OPTPP_CG)
 
static Method_mp_utype MP2s (methodName, OPTPP_FD_NEWTON)
 
static Method_mp_utype MP2s (methodName, OPTPP_G_NEWTON)
 
static Method_mp_utype MP2s (methodName, OPTPP_NEWTON)
 
static Method_mp_utype MP2s (methodName, OPTPP_PDS)
 
static Method_mp_utype MP2s (methodName, OPTPP_Q_NEWTON)
 
static Method_mp_utype MP2s (methodName, PARETO_SET)
 
static Method_mp_utype MP2s (methodName, PSUADE_MOAT)
 
static Method_mp_utype MP2s (methodName, RICHARDSON_EXTRAP)
 
static Method_mp_utype MP2s (methodName, SOGA)
 
static Method_mp_utype MP2s (methodName, SURROGATE_BASED_GLOBAL)
 
static Method_mp_utype MP2s (methodName, SURROGATE_BASED_LOCAL)
 
static Method_mp_utype MP2s (methodName, VECTOR_PARAMETER_STUDY)
 
static Method_mp_utype MP2s (methodName, LIST_PARAMETER_STUDY)
 
static Method_mp_utype MP2s (methodName, CENTERED_PARAMETER_STUDY)
 
static Method_mp_utype MP2s (methodName, MULTIDIM_PARAMETER_STUDY)
 
static Method_mp_utype MP2s (modelExportFormat, TEXT_ARCHIVE)
 
static Method_mp_utype MP2s (modelExportFormat, BINARY_ARCHIVE)
 
static Method_mp_utype MP2s (numericalSolveMode, NUMERICAL_FALLBACK)
 
static Method_mp_utype MP2s (numericalSolveMode, NUMERICAL_OVERRIDE)
 
static Method_mp_utype MP2s (optSubProbSolver, SUBMETHOD_NONE)
 
static Method_mp_utype MP2s (optSubProbSolver, SUBMETHOD_OPTPP)
 
static Method_mp_utype MP2s (optSubProbSolver, SUBMETHOD_NPSOL)
 
static Method_mp_utype MP2s (optSubProbSolver, SUBMETHOD_SBLO)
 
static Method_mp_utype MP2s (optSubProbSolver, SUBMETHOD_EA)
 
static Method_mp_utype MP2s (optSubProbSolver, SUBMETHOD_EGO)
 
static Method_mp_utype MP2s (optSubProbSolver, SUBMETHOD_SBGO)
 
static Method_mp_utype MP2s (optSubProbSolver, SUBMETHOD_LHS)
 
static Method_mp_utype MP2s (pstudyFileFormat, TABULAR_NONE)
 
static Method_mp_utype MP2s (pstudyFileFormat, TABULAR_HEADER)
 
static Method_mp_utype MP2s (pstudyFileFormat, TABULAR_EVAL_ID)
 
static Method_mp_utype MP2s (pstudyFileFormat, TABULAR_IFACE_ID)
 
static Method_mp_utype MP2s (pstudyFileFormat, TABULAR_ANNOTATED)
 
static Method_mp_utype MP2s (sampleType, SUBMETHOD_LHS)
 
static Method_mp_utype MP2s (sampleType, SUBMETHOD_RANDOM)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_AMV_PLUS_U)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_AMV_PLUS_X)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_AMV_U)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_AMV_X)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_QMEA_U)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_QMEA_X)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_TANA_U)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_TANA_X)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_NO_APPROX)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_EGRA_U)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_EGRA_X)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_ACV_IS)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_ACV_KL)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_ACV_MF)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_COLLABORATIVE)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_EMBEDDED)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_SEQUENTIAL)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_MUQ)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_DREAM)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_WASABI)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_GPMSA)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_QUESO)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_LHS)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_RANDOM)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_OA_LHS)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_OAS)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_BOX_BEHNKEN)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_CENTRAL_COMPOSITE)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_GRID)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_CONVERGE_ORDER)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_CONVERGE_QOI)
 
static Method_mp_utype MP2s (subMethod, SUBMETHOD_ESTIMATE_ORDER)
 
static SizetSet MP_ (surrogateFnIndices)
 
static Model_mp_lit MP2 (approxPointReuse, all)
 
static Model_mp_lit MP2 (approxPointReuse, none)
 
static Model_mp_lit MP2 (approxPointReuse, region)
 
static Model_mp_lit MP2 (marsInterpolation, linear)
 
static Model_mp_lit MP2 (marsInterpolation, cubic)
 
static Model_mp_lit MP2 (modelType, active_subspace)
 
static Model_mp_lit MP2 (modelType, adapted_basis)
 
static Model_mp_lit MP2 (modelType, nested)
 
static Model_mp_lit MP2 (modelType, random_field)
 
static Model_mp_lit MP2 (modelType, simulation)
 
static Model_mp_lit MP2 (modelType, surrogate)
 
static Model_mp_lit MP2 (surrogateType, hierarchical)
 
static Model_mp_lit MP2 (surrogateType, non_hierarchical)
 
static Model_mp_lit MP2 (surrogateType, global_exp_gauss_proc)
 
static Model_mp_lit MP2 (surrogateType, global_exp_poly)
 
static Model_mp_lit MP2 (surrogateType, global_function_train)
 
static Model_mp_lit MP2 (surrogateType, global_gaussian)
 
static Model_mp_lit MP2 (surrogateType, global_kriging)
 
static Model_mp_lit MP2 (surrogateType, global_mars)
 
static Model_mp_lit MP2 (surrogateType, global_moving_least_squares)
 
static Model_mp_lit MP2 (surrogateType, global_neural_network)
 
static Model_mp_lit MP2 (surrogateType, global_polynomial)
 
static Model_mp_lit MP2 (surrogateType, global_radial_basis)
 
static Model_mp_lit MP2 (surrogateType, global_voronoi_surrogate)
 
static Model_mp_lit MP2 (surrogateType, local_taylor)
 
static Model_mp_lit MP2 (surrogateType, multipoint_qmea)
 
static Model_mp_lit MP2 (surrogateType, multipoint_tana)
 
static Model_mp_lit MP2 (trendOrder, none)
 
static Model_mp_lit MP2 (trendOrder, constant)
 
static Model_mp_lit MP2 (trendOrder, linear)
 
static Model_mp_lit MP2 (trendOrder, reduced_quadratic)
 
static Model_mp_lit MP2 (trendOrder, quadratic)
 
static Model_mp_ord MP2s (approxCorrectionOrder, 0)
 
static Model_mp_ord MP2s (approxCorrectionOrder, 1)
 
static Model_mp_ord MP2s (approxCorrectionOrder, 2)
 
static Model_mp_ord MP2s (polynomialOrder, 1)
 
static Model_mp_ord MP2s (polynomialOrder, 2)
 
static Model_mp_ord MP2s (polynomialOrder, 3)
 
static Model_mp_type MP2s (approxCorrectionType, ADDITIVE_CORRECTION)
 
static Model_mp_type MP2s (approxCorrectionType, COMBINED_CORRECTION)
 
static Model_mp_type MP2s (approxCorrectionType, MULTIPLICATIVE_CORRECTION)
 
static Model_mp_type MP2s (pointsManagement, MINIMUM_POINTS)
 
static Model_mp_type MP2s (pointsManagement, RECOMMENDED_POINTS)
 
static Model_mp_type MP2s (subMethodScheduling, MASTER_SCHEDULING)
 
static Model_mp_type MP2s (method_rotation, ROTATION_METHOD_UNRANKED)
 
static Model_mp_type MP2s (method_rotation, ROTATION_METHOD_RANKED)
 
static Model_mp_type MP2s (subMethodScheduling, PEER_SCHEDULING)
 
static Model_mp_utype MP2s (analyticCovIdForm, EXP_L2)
 
static Model_mp_utype MP2s (analyticCovIdForm, EXP_L1)
 
static Model_mp_utype MP2s (exportApproxVarianceFormat, TABULAR_NONE)
 
static Model_mp_utype MP2s (exportApproxVarianceFormat, TABULAR_HEADER)
 
static Model_mp_utype MP2s (exportApproxVarianceFormat, TABULAR_EVAL_ID)
 
static Model_mp_utype MP2s (exportApproxVarianceFormat, TABULAR_IFACE_ID)
 
static Model_mp_utype MP2s (exportApproxVarianceFormat, TABULAR_ANNOTATED)
 
static Model_mp_utype MP2s (importChallengeFormat, TABULAR_NONE)
 
static Model_mp_utype MP2s (importChallengeFormat, TABULAR_HEADER)
 
static Model_mp_utype MP2s (importChallengeFormat, TABULAR_EVAL_ID)
 
static Model_mp_utype MP2s (importChallengeFormat, TABULAR_IFACE_ID)
 
static Model_mp_utype MP2s (importChallengeFormat, TABULAR_ANNOTATED)
 
static Model_mp_utype MP2s (modelExportFormat, ALGEBRAIC_FILE)
 
static Model_mp_utype MP2s (modelExportFormat, ALGEBRAIC_CONSOLE)
 
static Model_mp_utype MP2s (modelImportFormat, TEXT_ARCHIVE)
 
static Model_mp_utype MP2s (modelImportFormat, BINARY_ARCHIVE)
 
static Model_mp_utype MP2s (randomFieldIdForm, RF_KARHUNEN_LOEVE)
 
static Model_mp_utype MP2s (randomFieldIdForm, RF_PCA_GP)
 
static Model_mp_utype MP2s (subspaceNormalization, SUBSPACE_NORM_MEAN_VALUE)
 
static Model_mp_utype MP2s (subspaceNormalization, SUBSPACE_NORM_MEAN_GRAD)
 
static Model_mp_utype MP2s (subspaceNormalization, SUBSPACE_NORM_LOCAL_GRAD)
 
static Model_mp_utype MP2s (subspaceSampleType, SUBMETHOD_LHS)
 
static Model_mp_utype MP2s (subspaceSampleType, SUBMETHOD_RANDOM)
 
static Model_mp_utype MP2s (subspaceIdCVMethod, MINIMUM_METRIC)
 
static Model_mp_utype MP2s (subspaceIdCVMethod, RELATIVE_TOLERANCE)
 
static Model_mp_utype MP2s (subspaceIdCVMethod, DECREASE_TOLERANCE)
 
static Real MP_ (adaptedBasisCollocRatio)
 
static Real MP_ (annRange)
 
static Real MP_ (decreaseTolerance)
 
static Real MP_ (discontGradThresh)
 
static Real MP_ (discontJumpThresh)
 
static Real MP_ (krigingNugget)
 
static Real MP_ (percentFold)
 
static Real MP_ (relTolerance)
 
static Real MP_ (truncationTolerance)
 
static Real MP_ (adaptedBasisTruncationTolerance)
 
static RealVector MP_ (krigingCorrelations)
 
static RealVector MP_ (primaryRespCoeffs)
 
static RealVector MP_ (secondaryRespCoeffs)
 
static RealVector MP_ (solutionLevelCost)
 
static String MP_ (costRecoveryMetadata)
 
static String MP_ (decompCellType)
 
static String MP_ (exportApproxVarianceFile)
 
static String MP_ (idModel)
 
static String MP_ (importChallengePtsFile)
 
static String MP_ (interfacePointer)
 
static String MP_ (krigingOptMethod)
 
static String MP_ (modelImportPrefix)
 
static String MP_ (optionalInterfRespPointer)
 
static String MP_ (propagationModelPointer)
 
static String MP_ (refineCVMetric)
 
static String MP_ (responsesPointer)
 
static String MP_ (rfDataFileName)
 
static String MP_ (solutionLevelControl)
 
static String MP_ (truthModelPointer)
 
static String MP_ (variablesPointer)
 
static StringArray MP_ (diagMetrics)
 
static StringArray MP_ (ensembleModelPointers)
 
static StringArray MP_ (primaryVarMaps)
 
static StringArray MP_ (secondaryVarMaps)
 
static bool MP_ (autoRefine)
 
static bool MP_ (crossValidateFlag)
 
static bool MP_ (decompDiscontDetect)
 
static bool MP_ (importSurrogate)
 
static bool MP_ (hierarchicalTags)
 
static bool MP_ (identityRespMap)
 
static bool MP_ (importChallengeActive)
 
static bool MP_ (importChalUseVariableLabels)
 
static bool MP_ (importUseVariableLabels)
 
static bool MP_ (modelUseDerivsFlag)
 
static bool MP_ (domainDecomp)
 
static bool MP_ (pointSelection)
 
static bool MP_ (pressFlag)
 
static bool MP_ (subspaceIdBingLi)
 
static bool MP_ (subspaceIdConstantine)
 
static bool MP_ (subspaceIdEnergy)
 
static bool MP_ (subspaceBuildSurrogate)
 
static bool MP_ (subspaceIdCV)
 
static bool MP_ (subspaceCVIncremental)
 
static unsigned short MP_ (adaptedBasisSparseGridLev)
 
static unsigned short MP_ (adaptedBasisExpOrder)
 
static short MP_ (annNodes)
 
static short MP_ (annRandomWeight)
 
static short MP_ (c3AdvanceType)
 
static short MP_ (krigingFindNugget)
 
static short MP_ (krigingMaxTrials)
 
static short MP_ (marsMaxBases)
 
static short MP_ (mlsWeightFunction)
 
static short MP_ (rbfBases)
 
static short MP_ (rbfMaxPts)
 
static short MP_ (rbfMaxSubsets)
 
static short MP_ (rbfMinPartition)
 
static int MP_ (decompSupportLayers)
 
static int MP_ (initialSamples)
 
static int MP_ (numFolds)
 
static int MP_ (numReplicates)
 
static int MP_ (numRestarts)
 
static int MP_ (pointsTotal)
 
static int MP_ (refineCVFolds)
 
static int MP_ (softConvergenceLimit)
 
static int MP_ (subMethodProcs)
 
static int MP_ (subMethodServers)
 
static int MP_ (subspaceDimension)
 
static int MP_ (subspaceCVMaxRank)
 
static IntSet MP_ (idAnalyticGrads)
 
static IntSet MP_ (idAnalyticHessians)
 
static IntSet MP_ (idNumericalGrads)
 
static IntSet MP_ (idNumericalHessians)
 
static IntSet MP_ (idQuasiHessians)
 
static IntVector MP_ (fieldLengths)
 
static IntVector MP_ (numCoordsPerField)
 
static RealVector MP_ (expConfigVars)
 
static RealVector MP_ (expObservations)
 
static RealVector MP_ (primaryRespFnWeights)
 
static RealVector MP_ (nonlinearEqTargets)
 
static RealVector MP_ (nonlinearIneqLowerBnds)
 
static RealVector MP_ (nonlinearIneqUpperBnds)
 
static RealVector MP_ (simVariance)
 
static RealVector MP_ (fdGradStepSize)
 
static RealVector MP_ (fdHessStepSize)
 
static RealVector MP_ (primaryRespFnScales)
 
static RealVector MP_ (nonlinearEqScales)
 
static RealVector MP_ (nonlinearIneqScales)
 
static Resp_mp_lit MP2 (gradientType, analytic)
 
static Resp_mp_lit MP2 (gradientType, mixed)
 
static Resp_mp_lit MP2 (gradientType, none)
 
static Resp_mp_lit MP2 (gradientType, numerical)
 
static Resp_mp_lit MP2 (hessianType, analytic)
 
static Resp_mp_lit MP2 (hessianType, mixed)
 
static Resp_mp_lit MP2 (hessianType, none)
 
static Resp_mp_lit MP2 (hessianType, numerical)
 
static Resp_mp_lit MP2 (hessianType, quasi)
 
static Resp_mp_lit MP2 (intervalType, central)
 
static Resp_mp_lit MP2 (intervalType, forward)
 
static Resp_mp_lit MP2 (methodSource, dakota)
 
static Resp_mp_lit MP2 (methodSource, vendor)
 
static Resp_mp_lit MP2 (fdGradStepType, absolute)
 
static Resp_mp_lit MP2 (fdGradStepType, bounds)
 
static Resp_mp_lit MP2 (fdGradStepType, relative)
 
static Resp_mp_lit MP2 (fdHessStepType, absolute)
 
static Resp_mp_lit MP2 (fdHessStepType, bounds)
 
static Resp_mp_lit MP2 (fdHessStepType, relative)
 
static Resp_mp_lit MP2 (quasiHessianType, bfgs)
 
static Resp_mp_lit MP2 (quasiHessianType, damped_bfgs)
 
static Resp_mp_lit MP2 (quasiHessianType, sr1)
 
static String MP_ (dataPathPrefix)
 
static String MP_ (scalarDataFileName)
 
static String MP_ (idResponses)
 
static StringArray MP_ (metadataLabels)
 
static StringArray MP_ (nonlinearEqScaleTypes)
 
static StringArray MP_ (nonlinearIneqScaleTypes)
 
static StringArray MP_ (primaryRespFnScaleTypes)
 
static StringArray MP_ (primaryRespFnSense)
 
static StringArray MP_ (responseLabels)
 
static StringArray MP_ (varianceType)
 
static bool MP_ (calibrationDataFlag)
 
static bool MP_ (centralHess)
 
static bool MP_ (interpolateFlag)
 
static bool MP_ (ignoreBounds)
 
static bool MP_ (readFieldCoords)
 
static size_t MP_ (numExpConfigVars)
 
static size_t MP_ (numExperiments)
 
static size_t MP_ (numFieldLeastSqTerms)
 
static size_t MP_ (numFieldObjectiveFunctions)
 
static size_t MP_ (numFieldResponseFunctions)
 
static size_t MP_ (numLeastSqTerms)
 
static size_t MP_ (numNonlinearEqConstraints)
 
static size_t MP_ (numNonlinearIneqConstraints)
 
static size_t MP_ (numObjectiveFunctions)
 
static size_t MP_ (numResponseFunctions)
 
static size_t MP_ (numScalarLeastSqTerms)
 
static size_t MP_ (numScalarObjectiveFunctions)
 
static size_t MP_ (numScalarResponseFunctions)
 
static Resp_mp_utype MP2s (scalarDataFormat, TABULAR_NONE)
 
static Resp_mp_utype MP2s (scalarDataFormat, TABULAR_HEADER)
 
static Resp_mp_utype MP2s (scalarDataFormat, TABULAR_EVAL_ID)
 
static Resp_mp_utype MP2s (scalarDataFormat, TABULAR_EXPER_ANNOT)
 
static Env_mp_utype MP2s (postRunInputFormat, TABULAR_NONE)
 
static Env_mp_utype MP2s (postRunInputFormat, TABULAR_HEADER)
 
static Env_mp_utype MP2s (postRunInputFormat, TABULAR_EVAL_ID)
 
static Env_mp_utype MP2s (postRunInputFormat, TABULAR_IFACE_ID)
 
static Env_mp_utype MP2s (postRunInputFormat, TABULAR_ANNOTATED)
 
static Env_mp_utype MP2s (preRunOutputFormat, TABULAR_NONE)
 
static Env_mp_utype MP2s (preRunOutputFormat, TABULAR_HEADER)
 
static Env_mp_utype MP2s (preRunOutputFormat, TABULAR_EVAL_ID)