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Dakota
Version 6.2
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The primary namespace for DAKOTA. More...
Classes | |
class | ApplicationInterface |
Derived class within the interface class hierarchy for supporting interfaces to simulation codes. 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 | COLINApplication |
class | COLINOptimizer |
Wrapper class for optimizers defined using COLIN. More... | |
class | CollabHybridMetaIterator |
Meta-iterator for hybrid iteration using multiple collaborating optimization and nonlinear least squares methods. More... | |
class | GetLongOpt |
GetLongOpt is a general command line utility from S. Manoharan (Advanced Computer Research Institute, Lyon, France). 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 | FileReadException |
base class for Dakota file read exceptions (to allow catching both tabular and general file truncation issues) More... | |
class | TabularDataTruncated |
exception thrown when data read truncated More... | |
class | ResultsFileError |
exception throw for other results file read error More... | |
class | FunctionEvalFailure |
exception class for function evaluation failures More... | |
struct | BaseConstructor |
Dummy struct for overloading letter-envelope constructors. More... | |
struct | NoDBBaseConstructor |
Dummy struct for overloading constructors used in on-the-fly instantiations without ProblemDescDB support. More... | |
struct | LightWtBaseConstructor |
Dummy struct for overloading constructors used in on-the-fly Model instantiations. More... | |
class | ActiveSet |
Container class for active set tracking information. Contains the active set request vector and the derivative variables vector. More... | |
class | Analyzer |
Base class for NonD, DACE, and ParamStudy branches of the iterator hierarchy. More... | |
class | Approximation |
Base class for the approximation class hierarchy. More... | |
class | Constraints |
Base class for the variable constraints class hierarchy. More... | |
class | Environment |
Base class for the environment class hierarchy. 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 | Interface |
Base class for the interface class hierarchy. More... | |
class | Iterator |
Base class for the iterator class hierarchy. More... | |
class | LeastSq |
Base class for the nonlinear least squares branch of the iterator hierarchy. More... | |
class | Minimizer |
Base class for the optimizer and least squares branches of the iterator hierarchy. More... | |
class | Model |
Base class for the model class hierarchy. More... | |
class | NonD |
Base class for all nondetermistic iterators (the DAKOTA/UQ branch). More... | |
class | Optimizer |
Base class for the optimizer branch of the iterator hierarchy. More... | |
class | PStudyDACE |
Base class for managing common aspects of parameter studies and design of experiments methods. More... | |
class | Response |
Container class for response functions and their derivatives. Response provides the enveloper base class. More... | |
class | Variables |
Base class for the variables class hierarchy. More... | |
class | Verification |
Base class for managing common aspects of verification studies. More... | |
class | DataEnvironmentRep |
Body class for environment specification data. More... | |
class | DataEnvironment |
Handle class for environment specification data. 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 | DataMethodRep |
Body class for method specification data. More... | |
class | DataMethod |
Handle class for method specification data. More... | |
class | DataModelRep |
Body class for model specification data. More... | |
class | DataModel |
Handle class for model specification data. More... | |
class | DataResponsesRep |
Body class for responses specification data. More... | |
class | DataResponses |
Handle class for responses specification data. More... | |
class | DataVariablesRep |
Body class for variables specification data. More... | |
class | DataVariables |
Handle class for variables specification data. More... | |
class | DDACEDesignCompExp |
Wrapper class for the DDACE design of experiments library. 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 | DOTOptimizer |
Wrapper class for the DOT optimization library. More... | |
class | EffGlobalMinimizer |
Implementation of Efficient Global Optimization/Least Squares algorithms. More... | |
class | EfficientSubspaceMethod |
Efficient Subspace Method (ESM), as proposed by Hany S. Abdel-Khalik. More... | |
class | EmbedHybridMetaIterator |
Meta-iterator for closely-coupled hybrid iteration, typically involving the embedding of local search methods within global search methods. 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 | 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 | GaussProcApproximation |
Derived approximation class for Gaussian Process implementation. More... | |
class | GridApplicInterface |
Derived application interface class which spawns simulation codes using grid services such as Condor or Globus. More... | |
class | HierarchSurrModel |
Derived model class within the surrogate model branch for managing hierarchical surrogates (models of varying fidelity). 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 | LibraryEnvironment |
Environment corresponding to execution as an embedded library. More... | |
class | MatlabInterface |
class | MetaIterator |
Base class for meta-iterators. 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 | 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 | NestedModel |
Derived model class which performs a complete sub-iterator execution within every evaluation of the model. More... | |
struct | Var_rcheck |
structure for verifying bounds and initial point for real-valued vars More... | |
struct | Var_icheck |
structure for verifying bounds and initial point for string-valued vars More... | |
struct | VLreal |
structure for validating real uncertain variable labels, bounds, values More... | |
struct | VLint |
structure for validating integer uncertain variable labels, bounds, values More... | |
struct | VLstr |
structure for validating string uncertain variable labels, bounds, values 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 | NLPQLPOptimizer |
Wrapper class for the NLPQLP optimization library, Version 2.0. More... | |
class | NLSSOLLeastSq |
Wrapper class for the NLSSOL nonlinear least squares library. More... | |
class | NomadOptimizer |
Wrapper class for NOMAD Optimizer. 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 | NonDCalibration |
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 | NonDExpansion |
Base class for polynomial chaos expansions (PCE) and stochastic collocation (SC) 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 | NonDIncremLHSSampling |
Performs icremental LHS 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 | 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 | QuesoJointPdf |
Dakota specialization of QUESO generic joint PDF. More... | |
class | QuesoVectorRV |
Dakota specialization of QUESO vector-valued random variable. 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 | NonDSampling |
Base class for common code between NonDLHSSampling, NonDIncremLHSSampling, and NonDAdaptImpSampling. 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 | NonlinearCGOptimizer |
class | NPSOLOptimizer |
Wrapper class for the NPSOL optimization library. More... | |
class | OptDartsOptimizer |
Wrapper class for OptDarts Optimizer. More... | |
class | OutputWriter |
class | ConsoleRedirector |
class | RestartWriter |
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 | ParallelLevel |
Container class for the data associated with a single level of communicator partitioning. More... | |
class | ParallelConfiguration |
Container class for a set of ParallelLevel list iterators that collectively identify a particular multilevel parallel configuration. 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... | |
class | PecosApproximation |
Derived approximation class for global basis polynomials. 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... | |
struct | partial_prp_hash |
wrapper to delegate to the ParamResponsePair hash_value function More... | |
struct | partial_prp_equality |
predicate for comparing ONLY the interfaceId and Vars attributes of PRPair More... | |
class | PSUADEDesignCompExp |
Wrapper class for the PSUADE library. More... | |
class | PythonInterface |
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 | 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 | ResultsDBAny |
class | ResultsID |
Get a globally unique 1-based execution number for a given iterator name (combination of methodName and methodID) for use in results DB. Each Iterator::run() call creates or increments this count for its string identifier. More... | |
class | ResultsNames |
List of valid names for iterator results. More... | |
class | ResultsManager |
Results manager for iterator final data. More... | |
class | ResultsEntry |
Class to manage in-core vs. file database lookups. More... | |
class | RichExtrapVerification |
Class for Richardson extrapolation for code and solution verification. 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 | SharedPecosApproxData |
Derived approximation class for global basis polynomials. More... | |
class | SharedResponseDataRep |
The representation of a SharedResponseData instance. This representation, or body, may be shared by multiple SharedResponseData handle instances. More... | |
class | SharedResponseData |
Container class encapsulating variables data that can be shared among a set of Response instances. More... | |
class | SharedSurfpackApproxData |
Derived approximation class for Surfpack approximation classes. Interface between Surfpack and Dakota. More... | |
class | SharedVariablesDataRep |
The representation of a SharedVariablesData instance. This representation, or body, may be shared by multiple SharedVariablesData handle instances. More... | |
class | SharedVariablesData |
Container class encapsulating variables data that can be shared among a set of Variables instances. More... | |
class | SimulationResponse |
Container class for response functions and their derivatives. SimulationResponse provides the body class. More... | |
class | SingleModel |
Derived model class which utilizes a single interface to map variables into responses. More... | |
class | SNLLBase |
Base class for OPT++ optimization and least squares methods. More... | |
class | SNLLLeastSq |
Wrapper class for the OPT++ optimization library. More... | |
class | SNLLOptimizer |
Wrapper class for the OPT++ optimization library. More... | |
class | SOLBase |
Base class for Stanford SOL software. More... | |
class | SpawnApplicInterface |
Derived application interface class which spawns simulation codes using spawnvp. More... | |
class | SurfpackApproximation |
Derived approximation class for Surfpack approximation classes. Interface between Surfpack and Dakota. More... | |
class | SurrBasedGlobalMinimizer |
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 | SysCallApplicInterface |
Derived application interface class which spawns simulation codes using system calls. 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 | TrackerHTTP |
TrackerHTTP: a usage tracking module that uses HTTP/HTTPS via the curl library. More... | |
class | UsageTracker |
Lightweight class to manage conditionally active Curl-based HTTP tracker via PIMPL. More... | |
class | VPSApproximation |
Derived approximation class for VPS implementation. 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 | WorkdirHelper |
Typedefs | |
typedef double | Real |
typedef std::string | String |
typedef Teuchos::SerialDenseVector < int, Real > | RealVector |
typedef Teuchos::SerialDenseMatrix < int, Real > | RealMatrix |
typedef Teuchos::SerialSymDenseMatrix < int, Real > | RealSymMatrix |
typedef Teuchos::SerialDenseVector < int, int > | IntVector |
typedef Teuchos::SerialDenseMatrix < int, int > | IntMatrix |
typedef std::deque< bool > | BoolDeque |
typedef boost::dynamic_bitset < unsigned long > | BitArray |
typedef std::vector< BoolDeque > | BoolDequeArray |
typedef std::vector< Real > | RealArray |
typedef std::vector< RealArray > | Real2DArray |
typedef std::vector< int > | IntArray |
typedef std::vector< IntArray > | Int2DArray |
typedef std::vector< short > | ShortArray |
typedef std::vector< unsigned short > | UShortArray |
typedef std::vector< UShortArray > | UShort2DArray |
typedef std::vector < UShort2DArray > | UShort3DArray |
typedef std::vector< size_t > | SizetArray |
typedef std::vector< SizetArray > | Sizet2DArray |
typedef std::vector< String > | StringArray |
typedef std::vector< StringArray > | String2DArray |
typedef boost::multi_array_types::index_range | idx_range |
typedef boost::multi_array < String, 1 > | StringMultiArray |
typedef boost::multi_array < String, 2 > | StringMulti2DArray |
typedef StringMultiArray::array_view < 1 >::type | StringMultiArrayView |
typedef StringMultiArray::const_array_view < 1 >::type | StringMultiArrayConstView |
typedef boost::multi_array < unsigned short, 1 > | UShortMultiArray |
typedef UShortMultiArray::array_view < 1 >::type | UShortMultiArrayView |
typedef UShortMultiArray::const_array_view < 1 >::type | UShortMultiArrayConstView |
typedef boost::multi_array < size_t, 1 > | SizetMultiArray |
typedef SizetMultiArray::array_view < 1 >::type | SizetMultiArrayView |
typedef SizetMultiArray::const_array_view < 1 >::type | SizetMultiArrayConstView |
typedef boost::multi_array < Real, 1 > | RealMultiArray |
typedef boost::multi_array < Real, 2 > | RealMulti2DArray |
typedef boost::multi_array < Real, 3 > | RealMulti3DArray |
typedef std::vector< RealVector > | RealVectorArray |
typedef std::vector < RealVectorArray > | RealVector2DArray |
typedef std::vector< RealMatrix > | RealMatrixArray |
typedef std::vector < RealSymMatrix > | RealSymMatrixArray |
typedef std::vector< IntVector > | IntVectorArray |
typedef std::vector< Variables > | VariablesArray |
typedef std::vector< Response > | ResponseArray |
typedef std::vector < ParamResponsePair > | PRPArray |
typedef std::vector< PRPArray > | PRP2DArray |
typedef std::vector< Model > | ModelArray |
typedef std::vector< Iterator > | IteratorArray |
typedef std::vector < RealMultiArray > | BoostMAArray |
typedef std::vector < RealMulti2DArray > | BoostMA2DArray |
typedef std::vector < RealMulti3DArray > | BoostMA3DArray |
typedef std::list< bool > | BoolList |
typedef std::list< int > | IntList |
typedef std::list< size_t > | SizetList |
typedef std::list< Real > | RealList |
typedef std::list< RealVector > | RealVectorList |
typedef std::list< String > | StringList |
typedef std::list< Variables > | VariablesList |
typedef std::list< Interface > | InterfaceList |
typedef std::list< Response > | ResponseList |
typedef std::list< Model > | ModelList |
typedef std::list< Iterator > | IteratorList |
typedef std::pair< int, int > | IntIntPair |
typedef std::pair< size_t, int > | SizetIntPair |
typedef std::pair< int, String > | IntStringPair |
typedef std::pair< Real, Real > | RealRealPair |
typedef std::pair< int, Response > | IntResponsePair |
typedef std::set< Real > | RealSet |
typedef std::set< int > | IntSet |
typedef std::set< String > | StringSet |
typedef std::set< unsigned short > | UShortSet |
typedef std::set< size_t > | SizetSet |
typedef std::vector< RealSet > | RealSetArray |
typedef std::vector< IntSet > | IntSetArray |
typedef std::vector< StringSet > | StringSetArray |
typedef std::vector< UShortSet > | UShortSetArray |
typedef std::map< int, int > | IntIntMap |
typedef std::map< int, short > | IntShortMap |
typedef std::map< int, short > | IntSizetMap |
typedef std::map< int, Real > | IntRealMap |
typedef std::map< Real, Real > | RealRealMap |
typedef std::map< String, Real > | StringRealMap |
typedef std::vector< IntRealMap > | IntRealMapArray |
typedef std::vector< RealRealMap > | RealRealMapArray |
typedef std::vector < StringRealMap > | StringRealMapArray |
typedef std::map< int, RealVector > | IntRealVectorMap |
typedef std::map< int, RealMatrix > | IntRealMatrixMap |
typedef std::map< int, ActiveSet > | IntActiveSetMap |
typedef std::map< int, Variables > | IntVariablesMap |
typedef std::map< int, Response > | IntResponseMap |
typedef std::map< IntArray, size_t > | IntArraySizetMap |
typedef std::map< IntIntPair, Real > | IntIntPairRealMap |
typedef std::map< RealRealPair, Real > | RealRealPairRealMap |
typedef std::vector < IntIntPairRealMap > | IntIntPairRealMapArray |
typedef std::vector < RealRealPairRealMap > | RealRealPairRealMapArray |
typedef std::multimap < RealRealPair, ParamResponsePair > | RealPairPRPMultiMap |
typedef IntList::iterator | ILIter |
typedef IntList::const_iterator | ILCIter |
typedef SizetList::iterator | StLIter |
typedef SizetList::const_iterator | StLCIter |
typedef RealList::iterator | RLIter |
typedef RealList::const_iterator | RLCIter |
typedef RealVectorList::iterator | RVLIter |
typedef RealVectorList::const_iterator | RVLCIter |
typedef StringList::iterator | StringLIter |
typedef StringList::const_iterator | StringLCIter |
typedef VariablesList::iterator | VarsLIter |
typedef InterfaceList::iterator | InterfLIter |
typedef ResponseList::iterator | RespLIter |
typedef ModelList::iterator | ModelLIter |
typedef ModelList::reverse_iterator | ModelLRevIter |
typedef IteratorList::iterator | IterLIter |
typedef std::list < ParallelLevel >::iterator | ParLevLIter |
typedef std::list < ParallelConfiguration > ::iterator | ParConfigLIter |
typedef IntSet::iterator | ISIter |
typedef IntSet::const_iterator | ISCIter |
typedef StringSet::iterator | SSIter |
typedef StringSet::const_iterator | SSCIter |
typedef RealSet::iterator | RSIter |
typedef RealSet::const_iterator | RSCIter |
typedef IntIntMap::iterator | IntIntMIter |
typedef IntIntMap::const_iterator | IntIntMCIter |
typedef IntShortMap::iterator | IntShMIter |
typedef IntShortMap::const_iterator | IntShMCIter |
typedef IntRealMap::iterator | IRMIter |
typedef IntRealMap::const_iterator | IRMCIter |
typedef StringRealMap::iterator | SRMIter |
typedef StringRealMap::const_iterator | SRMCIter |
typedef RealRealMap::iterator | RRMIter |
typedef RealRealMap::const_iterator | RRMCIter |
typedef IntIntPairRealMap::iterator | IIPRMIter |
typedef IntIntPairRealMap::const_iterator | IIPRMCIter |
typedef RealRealPairRealMap::iterator | RRPRMIter |
typedef RealRealPairRealMap::const_iterator | RRPRMCIter |
typedef IntRealVectorMap::iterator | IntRDVMIter |
typedef IntRealVectorMap::const_iterator | IntRDVMCIter |
typedef IntActiveSetMap::iterator | IntASMIter |
typedef IntVariablesMap::iterator | IntVarsMIter |
typedef IntVariablesMap::const_iterator | IntVarsMCIter |
typedef IntResponseMap::iterator | IntRespMIter |
typedef IntResponseMap::const_iterator | IntRespMCIter |
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 void(* | dl_find_optimum_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. | |
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. | |
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 } |
enum | { METHOD_ERROR = -7, MODEL_ERROR = -6, IO_ERROR = -5, INTERFACE_ERROR = -4, CONSTRUCT_ERROR = -3, PARSE_ERROR = -2, OTHER_ERROR = -1 } |
enum for Dakota abort reasons; using negative numbers to avoid clash with signal codes 1--64 in signum.h | |
enum | { ABORT_EXITS, ABORT_THROWS } |
enum for dakota abort behaviors | |
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 } |
options for tabular columns | |
enum | { DEFAULT_INTERFACE = 0, APPROX_INTERFACE, FORK_INTERFACE = PROCESS_INTERFACE_BIT, SYSTEM_INTERFACE, GRID_INTERFACE, TEST_INTERFACE = DIRECT_INTERFACE_BIT, MATLAB_INTERFACE, PYTHON_INTERFACE, SCILAB_INTERFACE } |
special values for interface type | |
enum | { SYNCHRONOUS_INTERFACE, ASYNCHRONOUS_INTERFACE } |
interface synchronization types | |
enum | { OBJECTIVE, INEQUALITY_CONSTRAINT, EQUALITY_CONSTRAINT } |
define algebraic function types | |
enum | { DEFAULT_METHOD = 0, HYBRID = (META_BIT | PARALLEL_BIT), PARETO_SET, MULTI_START, BRANCH_AND_BOUND, 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, POLYNOMIAL_CHAOS, STOCH_COLLOCATION, CUBATURE_INTEGRATION, SPARSE_GRID_INTEGRATION, QUADRATURE_INTEGRATION, BAYES_CALIBRATION, GPAIS, POF_DARTS, EFFICIENT_SUBSPACE, IMPORTANCE_SAMPLING, ADAPTIVE_SAMPLING, RANDOM_SAMPLING, LOCAL_INTERVAL_EST, LOCAL_EVIDENCE, GLOBAL_INTERVAL_EST, GLOBAL_EVIDENCE, SURROGATE_BASED_LOCAL = (MINIMIZER_BIT | SURRBASED_BIT), 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, GENIE_OPT_DARTS, GENIE_DIRECT, 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, DL_SOLVER } |
enum | { SUBMETHOD_DEFAULT = 0, SUBMETHOD_COLLABORATIVE, SUBMETHOD_EMBEDDED, SUBMETHOD_SEQUENTIAL, SUBMETHOD_LHS, SUBMETHOD_RANDOM, SUBMETHOD_INCREMENTAL_LHS, SUBMETHOD_INCREMENTAL_RANDOM, SUBMETHOD_BOX_BEHNKEN, SUBMETHOD_CENTRAL_COMPOSITE, SUBMETHOD_GRID, SUBMETHOD_OA_LHS, SUBMETHOD_OAS, SUBMETHOD_DREAM, SUBMETHOD_GPMSA, SUBMETHOD_QUESO, SUBMETHOD_NIP, SUBMETHOD_SQP, SUBMETHOD_EA, SUBMETHOD_EGO, SUBMETHOD_SBO, SUBMETHOD_CONVERGE_ORDER, SUBMETHOD_CONVERGE_QOI, SUBMETHOD_ESTIMATE_ORDER } |
Sub-methods, including sampling, inference algorithm, opt algorithm types. More... | |
enum | { SILENT_OUTPUT, QUIET_OUTPUT, NORMAL_OUTPUT, VERBOSE_OUTPUT, DEBUG_OUTPUT } |
enum | { DEFAULT_SCHEDULING, MASTER_SCHEDULING, PEER_SCHEDULING, PEER_DYNAMIC_SCHEDULING, PEER_STATIC_SCHEDULING, DYNAMIC_SCHEDULING, STATIC_SCHEDULING } |
enum | { DEFAULT_CONFIG, PUSH_DOWN, PUSH_UP } |
enum | { STD_NORMAL_U, STD_UNIFORM_U, ASKEY_U, EXTENDED_U } |
enum | { DEFAULT_COVARIANCE, NO_COVARIANCE, DIAGONAL_COVARIANCE, FULL_COVARIANCE } |
enum | { NO_INT_REFINE = 0, IS, AIS, MMAIS } |
enum | { PROBABILITIES, RELIABILITIES, GEN_RELIABILITIES } |
enum | { COMPONENT = 0, SYSTEM_SERIES, SYSTEM_PARALLEL } |
enum | { CUMULATIVE, COMPLEMENTARY } |
enum | { DEFAULT_LS = 0, SVD_LS, EQ_CON_LS } |
enum | { NO_EMULATOR, PCE_EMULATOR, SC_EMULATOR, GP_EMULATOR, KRIGING_EMULATOR, VPS_EMULATOR } |
enum | { IGNORE_RANKS, SET_RANKS, GET_RANKS, SET_GET_RANKS } |
enum | { UNCERTAIN, UNCERTAIN_UNIFORM, ALEATORY_UNCERTAIN, ALEATORY_UNCERTAIN_UNIFORM, EPISTEMIC_UNCERTAIN, EPISTEMIC_UNCERTAIN_UNIFORM, ACTIVE, ACTIVE_UNIFORM, ALL, ALL_UNIFORM } |
enum | { MV = 0, AMV_X, AMV_U, AMV_PLUS_X, AMV_PLUS_U, TANA_X, TANA_U, NO_APPROX, EGRA_X, EGRA_U } |
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 | { SCALE_NONE, SCALE_VALUE, SCALE_LOG } |
enum | { CDV, LINEAR, NONLIN, FN_LSQ } |
enum | { DISALLOW, TARGET, BOUNDS } |
enum | { DEFAULT_POINTS, MINIMUM_POINTS, RECOMMENDED_POINTS, TOTAL_POINTS } |
define special values for pointsManagement | |
enum | { NO_SURROGATE = 0, UNCORRECTED_SURROGATE, AUTO_CORRECTED_SURROGATE, BYPASS_SURROGATE, MODEL_DISCREPANCY } |
define special values for SurrogateModel::responseMode | |
enum | { NO_CORRECTION = 0, ADDITIVE_CORRECTION, MULTIPLICATIVE_CORRECTION, COMBINED_CORRECTION } |
define special values for approxCorrectionType | |
enum | { BASE_RESPONSE = 0, SIMULATION_RESPONSE, EXPERIMENT_RESPONSE } |
special values for derived Response type | |
enum | { GENERIC_FNS = 0, OBJECTIVE_FNS, CALIB_TERMS } |
values for primary response types | |
enum | { DEFAULT_DOMAIN = 0, RELAXED_DOMAIN, MIXED_DOMAIN } |
enum | { DEFAULT_VIEW = 0, ALL_VIEW, DESIGN_VIEW, UNCERTAIN_VIEW, ALEATORY_UNCERTAIN_VIEW, EPISTEMIC_UNCERTAIN_VIEW, STATE_VIEW } |
enum | { EMPTY = 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 } |
enum | { CONTINUOUS_DESIGN = 1, 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 } |
enum | { 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 } |
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_Fs, VAR_P1, VAR_P2, VAR_P3, VAR_B, VAR_D, VAR_H, VAR_F0, VAR_d, VAR_MForm } |
enumeration of possible variable types (to index to names) | |
enum | driver_t { NO_DRIVER = 0, CANTILEVER_BEAM, MOD_CANTILEVER_BEAM, CYLINDER_HEAD, EXTENDED_ROSENBROCK, GENERALIZED_ROSENBROCK, LF_ROSENBROCK, MF_ROSENBROCK, ROSENBROCK, 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, HERBIE, SMOOTH_HERBIE, SHUBERT, SALINAS, MODELCENTER, GENZ, DAMPED_OSCILLATOR } |
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 | { SETUP_MODEL, SETUP_USERFUNC } |
enum | { 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 } |
enum | { DAUIVar_poisson = 0, DAUIVar_binomial = 1, DAUIVar_negative_binomial = 2, DAUIVar_geometric = 3, DAUIVar_hypergeometric = 4, DAUIVar_histogram_point_int = 5, DAUIVar_Nkinds = 6 } |
enum | { DAUSVar_histogram_point_str = 0, DAUSVar_Nkinds = 1 } |
enum | { DAURVar_histogram_point_real = 0, DAURVar_Nkinds = 1 } |
enum | { CEUVar_interval = 0, CEUVar_Nkinds = 1 } |
enum | { DEUIVar_interval = 0, DEUIVar_set_int = 1, DEUIVar_Nkinds = 2 } |
enum | { DEUSVar_set_str = 0, DEUSVar_Nkinds = 1 } |
enum | { DEURVar_set_real = 0, DEURVar_Nkinds = 1 } |
enum | { 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 | { NUM_UNC_REAL_CONT = 4 } |
number of real-valued uncertain contiguous containers | |
enum | { NUM_UNC_INT_CONT = 2 } |
number of int-valued uncertain contiguous containers | |
enum | { NUM_UNC_STR_CONT = 2 } |
number of string-valued uncertain contiguous containers | |
enum | { FULL_TENSOR, FILTERED_TENSOR, RANDOM_TENSOR } |
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 | EvalType { NLFEvaluator, CONEvaluator } |
enumeration for the type of evaluator function | |
enum | { TH_SILENT_OUTPUT, TH_QUIET_OUTPUT, TH_NORMAL_OUTPUT, TH_VERBOSE_OUTPUT, TH_DEBUG_OUTPUT } |
enum | { DIR_CLEAN, DIR_PERSIST, DIR_ERROR } |
define directory creation options | |
enum | { FILEOP_SILENT, FILEOP_WARN, FILEOP_ERROR } |
enum indicating action on failed file operation | |
Functions | |
CommandShell & | flush (CommandShell &shell) |
convenient shell manipulator function to "flush" the shell | |
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, RealVectorArray &config_vars) |
void | read_config_vars_singlefile (const std::string &basename, int num_expts, int ncv, RealVectorArray &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) |
void | copy_data (const RealMatrix &rmat, RealVectorArray &rvarray) |
file reader for VECTOR and MATRIX covariance data | |
void | copy_data (const RealVectorArray &rvarray, RealMatrix &rmat) |
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 | |
bool | operator== (const SizetArray &sa, SizetMultiArrayConstView smav) |
equality operator for SizetArray and SizetMultiArrayConstView | |
bool | operator!= (const StringMultiArrayView &sma1, const StringMultiArray &sma2) |
inequality operator for StringMultiArray view vs. container | |
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. | |
bool | operator== (const IntArray &dia1, const IntArray &dia2) |
equality operator for IntArray | |
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 | |
bool | operator!= (const SizetArray &sa, SizetMultiArrayConstView smav) |
inequality operator for StringArray | |
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(). | |
void | copy_row_vector (const RealMatrix &m, RealMatrix::ordinalType i, std::vector< Real > &row) |
Copies a row of a Teuchos_SerialDenseMatrix<int,Real> to std::vector<Real> | |
template<typename T > | |
void | copy_data (const std::vector< T > &vec, T *ptr, const size_t ptr_len) |
copy Array<T> to T* | |
template<typename T > | |
void | copy_data (const T *ptr, const size_t ptr_len, std::vector< T > &vec) |
copy T* to Array<T> | |
template<typename OrdinalType1 , typename OrdinalType2 , typename ScalarType > | |
void | copy_data (const std::vector< Teuchos::SerialDenseVector< OrdinalType1, ScalarType > > &va, ScalarType *ptr, const OrdinalType2 ptr_len, const String &ptr_type) |
copy Array<Teuchos::SerialDenseVector<OT,ST> > to ST* | |
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> | |
template<typename T > | |
void | copy_data (const std::list< T > &dl, std::vector< T > &da) |
copy std::list<T> to std::vector<T> | |
template<typename T > | |
void | copy_data (const std::list< T > &dl, std::vector< std::vector< T > > &d2a, size_t num_a, size_t a_len) |
copy std::list<T> to std::vector<std::vector<T> > | |
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) | |
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) | |
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 of a vector view is needed) | |
template<typename OrdinalType , typename ScalarType > | |
void | copy_data (const Teuchos::SerialDenseVector< OrdinalType, ScalarType > &sdv, std::vector< ScalarType > &da) |
copy Teuchos::SerialDenseVector<OrdinalType, ScalarType> to std::vector<ScalarType> | |
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> | |
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> | |
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> | |
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<> > | |
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 | |
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 | |
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 | |
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 | |
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> | |
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> | |
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> | |
template<typename T > | |
void | copy_data_partial (const std::vector< T > &da1, size_t start_index1, size_t num_items, std::vector< T > &da2, size_t start_index2) |
copy portion of first Array<T> to portion of second Array<T> | |
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 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 ContainerType > | |
size_t | find_index (const ContainerType &c, const typename ContainerType::value_type &search_data) |
generic find_index (inactive) | |
template<typename MultiArrayType , typename DakArrayType > | |
void | copy_data (const MultiArrayType &ma, DakArrayType &da) |
generic copy (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 | |
void | copy_data (SizetMultiArrayConstView ma, SizetArray &da) |
copy boost::multi_array view to Array | |
void | copy_data (StringMultiArrayConstView ma, StringArray &da) |
copy boost::multi_array view to Array | |
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 DakContainerType > | |
bool | contains (const DakContainerType &v, const typename DakContainerType::value_type &val) |
return true if the item val appears in container v | |
void | abort_handler (int code) |
global function which handles serial or parallel aborts | |
void | abort_throw_or_exit (int code) |
throw or exit depending on abort_mode | |
void | register_signal_handlers () |
Tie various signal handlers to Dakota's abort_handler function. | |
void | mpi_debug_hold () |
Global function to hold Dakota processes to help with MPI debugging. | |
template<typename T > | |
T | abort_handler_t (int code) |
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) |
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 | |
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 | |
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 | |
bool | operator!= (const Model &m1, const Model &m2) |
inequality operator for Envelope is true if different letter instance | |
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 | |
std::string | re_match (const std::string &token, const boost::regex &re) |
Global utility function to ease migration from CtelRegExp to Boost.Regex. | |
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 | |
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 | |
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 | |
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 | |
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 | |
static 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_find_optimum_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. | |
bool | get_positive_definite_covariance_from_hessian (const RealSymMatrix &hessian, RealMatrix &covariance) |
Compute the covariance C of a hessian matrix H, i.e, C=inv(H) The hessian is enforced to be positive definite by setting any negative eigenvalues to zero. The state of eigenvalue truncation is returned. | |
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. | |
void | copy_residuals (const RealVector &fn_vals, RealMatrix &fn_grad, const RealSymMatrixArray &fn_hess, size_t offset, size_t num_fns, Response &response) |
Copy a field into a response object. | |
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) |
template<typename T > | |
string | asstring (const T &val) |
Creates a string from the argument val using an ostringstream. | |
PACKBUF (int, MPI_INT) PACKBUF(u_int | |
MPI_UNSIGNED | PACKBUF (long, MPI_LONG) PACKBUF(u_long |
MPI_UNSIGNED MPI_UNSIGNED_LONG | PACKBUF (short, MPI_SHORT) PACKBUF(u_short |
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_SHORT | PACKBUF (char, MPI_CHAR) PACKBUF(u_char |
MPI_UNSIGNED MPI_UNSIGNED_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 (short, MPI_SHORT) UNPACKBUF(u_short |
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_SHORT | UNPACKBUF (char, MPI_CHAR) UNPACKBUF(u_char |
MPI_UNSIGNED MPI_UNSIGNED_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 (short, MPI_SHORT) PACKSIZE(u_short |
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_SHORT | PACKSIZE (char, MPI_CHAR) PACKSIZE(u_char |
MPI_UNSIGNED MPI_UNSIGNED_LONG MPI_UNSIGNED_SHORT MPI_UNSIGNED_CHAR | PACKSIZE (double, MPI_DOUBLE) PACKSIZE(float |
MPI_UNSIGNED MPI_UNSIGNED_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 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, 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 | |
template<class ContainerT > | |
void | container_read (ContainerT &c, MPIUnpackBuffer &s) |
Read a generic container (vector<T>, list<T>) from MPIUnpackBuffer, s. | |
template<class ContainerT > | |
void | container_write (const ContainerT &c, MPIPackBuffer &s) |
Write a generic container to MPIPackBuffer, s. | |
template<typename Block , typename Allocator > | |
MPIPackBuffer & | operator<< (MPIPackBuffer &s, const boost::dynamic_bitset< Block, Allocator > &bs) |
stream insertion for BitArray | |
template<typename Block , typename Allocator > | |
MPIUnpackBuffer & | operator>> (MPIUnpackBuffer &s, boost::dynamic_bitset< Block, Allocator > &bs) |
stream extraction for BitArray | |
template<class ContainerT > | |
MPIUnpackBuffer & | operator>> (MPIUnpackBuffer &s, ContainerT &data) |
global MPIUnpackBuffer extraction operator for generic container | |
template<class ContainerT > | |
MPIPackBuffer & | operator<< (MPIPackBuffer &s, const ContainerT &data) |
global MPIPackBuffer insertion operator for generic container | |
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 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) |
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_type | MP2s (interfaceSynchronization, ASYNCHRONOUS_INTERFACE) |
static Iface_mp_type | MP2s (interfaceSynchronization, SYNCHRONOUS_INTERFACE) |
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, MATLAB_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 String | MP_ (algebraicMappings) |
static String | MP_ (idInterface) |
static String | MP_ (inputFilter) |
static String | MP_ (outputFilter) |
static String | MP_ (parametersFile) |
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_ (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_ (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_penalty) |
static Method_mp_lit | MP2 (batchSelectionType, topology) |
static Method_mp_lit | MP2 (batchSelectionType, constant_liar) |
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 (evalSynchronize, blocking) |
static Method_mp_lit | MP2 (evalSynchronize, nonblocking) |
static Method_mp_lit | MP2 (expansionSampleType, incremental_lhs) |
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 (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_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_ (initStepLength) |
static Real | MP_ (initTRRadius) |
static Real | MP_ (likelihoodScale) |
static Real | MP_ (lineSearchTolerance) |
static Real | MP_ (localBalanceParam) |
static Real | MP_ (maxBoxSize) |
static Real | MP_ (maxStep) |
static Real | MP_ (minBoxSize) |
static Real | MP_ (mutationRate) |
static Real | MP_ (mutationScale) |
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_ (stepLenToBoundary) |
static Real | MP_ (surrBasedLocalTRContract) |
static Real | MP_ (surrBasedLocalTRContractTrigger) |
static Real | MP_ (surrBasedLocalTRExpand) |
static Real | MP_ (surrBasedLocalTRExpandTrigger) |
static Real | MP_ (surrBasedLocalTRInitSize) |
static Real | MP_ (surrBasedLocalTRMinSize) |
static Real | MP_ (threshDelta) |
static Real | MP_ (threshStepLength) |
static Real | MP_ (vbdDropTolerance) |
static Real | MP_ (volBoxSize) |
static Real | MP_ (vns) |
static Real | MP_ (xConvTol) |
static RealVector | MP_ (anisoDimPref) |
static RealVector | MP_ (concurrentParameterSets) |
static RealVector | MP_ (finalPoint) |
static RealVector | MP_ (linearEqConstraintCoeffs) |
static RealVector | MP_ (linearEqScales) |
static RealVector | MP_ (linearEqTargets) |
static RealVector | MP_ (linearIneqConstraintCoeffs) |
static RealVector | MP_ (linearIneqLowerBnds) |
static RealVector | MP_ (linearIneqUpperBnds) |
static RealVector | MP_ (linearIneqScales) |
static RealVector | MP_ (listOfPoints) |
static RealVector | MP_ (proposalCovData) |
static RealVector | MP_ (regressionNoiseTol) |
static RealVector | MP_ (stepVector) |
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_ (softConvLimit) |
static unsigned short | MP_ (vbdOrder) |
static SizetArray | MP_ (collocationPoints) |
static SizetArray | MP_ (expansionSamples) |
static UShortArray | MP_ (expansionOrder) |
static UShortArray | MP_ (quadratureOrder) |
static UShortArray | MP_ (sparseGridLevel) |
static UShortArray | MP_ (tensorGridOrder) |
static UShortArray | MP_ (varPartitions) |
static String | MP_ (approxExportFile) |
static String | MP_ (approxImportFile) |
static String | MP_ (betaSolverName) |
static String | MP_ (displayFormat) |
static String | MP_ (expansionExportFile) |
static String | MP_ (expansionImportFile) |
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_ (logFile) |
static String | MP_ (modelPointer) |
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_ (linearEqScaleTypes) |
static StringArray | MP_ (linearIneqScaleTypes) |
static StringArray | MP_ (miscOptions) |
static bool | MP_ (adaptPosteriorRefine) |
static bool | MP_ (approxImportActive) |
static bool | MP_ (backfillFlag) |
static bool | MP_ (calibrateSigmaFlag) |
static bool | MP_ (constantPenalty) |
static bool | MP_ (crossValidation) |
static bool | MP_ (expansionFlag) |
static bool | MP_ (fixedSeedFlag) |
static bool | MP_ (fixedSequenceFlag) |
static bool | MP_ (latinizeFlag) |
static bool | MP_ (logitTransform) |
static bool | MP_ (mainEffectsFlag) |
static bool | MP_ (methodScaling) |
static bool | MP_ (methodUseDerivsFlag) |
static bool | MP_ (mutationAdaptive) |
static bool | MP_ (normalizedCoeffs) |
static bool | MP_ (printPopFlag) |
static bool | MP_ (pstudyFileActive) |
static bool | MP_ (randomizeOrderFlag) |
static bool | MP_ (regressDiag) |
static bool | MP_ (showAllEval) |
static bool | MP_ (showMiscOptions) |
static bool | MP_ (speculativeFlag) |
static bool | MP_ (standardizedSpace) |
static bool | MP_ (tensorGridFlag) |
static bool | MP_ (surrBasedGlobalReplacePts) |
static bool | MP_ (surrBasedLocalLayerBypass) |
static bool | MP_ (vbdFlag) |
static bool | MP_ (volQualityFlag) |
static short | MP_ (expansionType) |
static short | MP_ (nestingOverride) |
static short | MP_ (refinementType) |
static int | MP_ (batchSize) |
static int | MP_ (concurrentRandomJobs) |
static int | MP_ (contractAfterFail) |
static int | MP_ (covarianceType) |
static int | MP_ (crossoverChainPairs) |
static int | MP_ (emulatorOrder) |
static int | MP_ (emulatorSamples) |
static int | MP_ (expandAfterSuccess) |
static int | MP_ (iteratorServers) |
static int | MP_ (jumpStep) |
static int | MP_ (maxFunctionEvaluations) |
static int | MP_ (maxIterations) |
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_ (previousSamples) |
static int | MP_ (procsPerIterator) |
static int | MP_ (proposalCovUpdates) |
static int | MP_ (randomSeed) |
static int | MP_ (refineSamples) |
static int | MP_ (searchSchemeSize) |
static int | MP_ (totalPatternSize) |
static int | MP_ (verifyLevel) |
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 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, GP_EMULATOR) |
static Method_mp_type | MP2s (emulatorType, KRIGING_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 | 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 (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 | MP2p (nestingOverride, NESTED) |
static Method_mp_type | MP2p (nestingOverride, NON_NESTED) |
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 (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 | 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_utype | MP2s (approxExportFormat, TABULAR_NONE) |
static Method_mp_utype | MP2s (approxExportFormat, TABULAR_HEADER) |
static Method_mp_utype | MP2s (approxExportFormat, TABULAR_EVAL_ID) |
static Method_mp_utype | MP2s (approxExportFormat, TABULAR_IFACE_ID) |
static Method_mp_utype | MP2s (approxExportFormat, TABULAR_ANNOTATED) |
static Method_mp_utype | MP2s (approxImportFormat, TABULAR_NONE) |
static Method_mp_utype | MP2s (approxImportFormat, TABULAR_HEADER) |
static Method_mp_utype | MP2s (approxImportFormat, TABULAR_EVAL_ID) |
static Method_mp_utype | MP2s (approxImportFormat, TABULAR_IFACE_ID) |
static Method_mp_utype | MP2s (approxImportFormat, 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, ASYNCH_PATTERN_SEARCH) |
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, 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, 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, NL2SOL) |
static Method_mp_utype | MP2s (methodName, NLPQL_SQP) |
static Method_mp_utype | MP2s (methodName, NLSSOL_SQP) |
static Method_mp_utype | MP2s (methodName, ADAPTIVE_SAMPLING) |
static Method_mp_utype | MP2s (methodName, BAYES_CALIBRATION) |
static Method_mp_utype | MP2s (methodName, EFFICIENT_SUBSPACE) |
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, POF_DARTS) |
static Method_mp_utype | MP2s (methodName, POLYNOMIAL_CHAOS) |
static Method_mp_utype | MP2s (methodName, RANDOM_SAMPLING) |
static Method_mp_utype | MP2s (methodName, STOCH_COLLOCATION) |
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 (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 (reliabilitySearchType, AMV_PLUS_U) |
static Method_mp_utype | MP2s (reliabilitySearchType, AMV_PLUS_X) |
static Method_mp_utype | MP2s (reliabilitySearchType, AMV_U) |
static Method_mp_utype | MP2s (reliabilitySearchType, AMV_X) |
static Method_mp_utype | MP2s (reliabilitySearchType, EGRA_U) |
static Method_mp_utype | MP2s (reliabilitySearchType, EGRA_X) |
static Method_mp_utype | MP2s (reliabilitySearchType, NO_APPROX) |
static Method_mp_utype | MP2s (reliabilitySearchType, TANA_U) |
static Method_mp_utype | MP2s (reliabilitySearchType, TANA_X) |
static Method_mp_utype | MP2s (sampleType, SUBMETHOD_INCREMENTAL_LHS) |
static Method_mp_utype | MP2s (sampleType, SUBMETHOD_INCREMENTAL_RANDOM) |
static Method_mp_utype | MP2s (sampleType, SUBMETHOD_LHS) |
static Method_mp_utype | MP2s (sampleType, SUBMETHOD_RANDOM) |
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_DREAM) |
static Method_mp_utype | MP2s (subMethod, SUBMETHOD_GPMSA) |
static Method_mp_utype | MP2s (subMethod, SUBMETHOD_QUESO) |
static Method_mp_utype | MP2s (subMethod, SUBMETHOD_NIP) |
static Method_mp_utype | MP2s (subMethod, SUBMETHOD_SQP) |
static Method_mp_utype | MP2s (subMethod, SUBMETHOD_EA) |
static Method_mp_utype | MP2s (subMethod, SUBMETHOD_EGO) |
static Method_mp_utype | MP2s (subMethod, SUBMETHOD_SBO) |
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 IntSet | 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, nested) |
static Model_mp_lit | MP2 (modelType, single) |
static Model_mp_lit | MP2 (modelType, surrogate) |
static Model_mp_lit | MP2 (surrogateType, hierarchical) |
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_tana) |
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 (subMethodScheduling, PEER_SCHEDULING) |
static Model_mp_utype | MP2s (approxChallengeFormat, TABULAR_NONE) |
static Model_mp_utype | MP2s (approxChallengeFormat, TABULAR_HEADER) |
static Model_mp_utype | MP2s (approxChallengeFormat, TABULAR_EVAL_ID) |
static Model_mp_utype | MP2s (approxChallengeFormat, TABULAR_IFACE_ID) |
static Model_mp_utype | MP2s (approxChallengeFormat, TABULAR_ANNOTATED) |
static Real | MP_ (annRange) |
static Real | MP_ (discontGradThresh) |
static Real | MP_ (discontJumpThresh) |
static Real | MP_ (krigingNugget) |
static Real | MP_ (percentFold) |
static RealVector | MP_ (krigingCorrelations) |
static RealVector | MP_ (primaryRespCoeffs) |
static RealVector | MP_ (secondaryRespCoeffs) |
static String | MP_ (approxChallengeFile) |
static String | MP_ (approxExportModelFile) |
static String | MP_ (decompCellType) |
static String | MP_ (idModel) |
static String | MP_ (interfacePointer) |
static String | MP_ (krigingOptMethod) |
static String | MP_ (lowFidelityModelPointer) |
static String | MP_ (optionalInterfRespPointer) |
static String | MP_ (responsesPointer) |
static String | MP_ (truthModelPointer) |
static String | MP_ (variablesPointer) |
static StringArray | MP_ (primaryVarMaps) |
static StringArray | MP_ (secondaryVarMaps) |
static StringArray | MP_ (diagMetrics) |
static bool | MP_ (approxChallengeActive) |
static bool | MP_ (crossValidateFlag) |
static bool | MP_ (decompDiscontDetect) |
static bool | MP_ (hierarchicalTags) |
static bool | MP_ (modelUseDerivsFlag) |
static bool | MP_ (piecewiseDecomp) |
static bool | MP_ (pointSelection) |
static bool | MP_ (pressFlag) |
static short | MP_ (annNodes) |
static short | MP_ (annRandomWeight) |
static short | MP_ (krigingFindNugget) |
static short | MP_ (krigingMaxTrials) |
static short | MP_ (marsMaxBases) |
static short | MP_ (mlsPolyOrder) |
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_ (numFolds) |
static int | MP_ (pointsTotal) |
static int | MP_ (subMethodProcs) |
static int | MP_ (subMethodServers) |
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_ (coordList) |
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_ (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_ (coordDataFileName) |
static String | MP_ (scalarDataFileName) |
static String | MP_ (idResponses) |
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) |
static Env_mp_utype | MP2s (preRunOutputFormat, TABULAR_IFACE_ID) |
static Env_mp_utype | MP2s (preRunOutputFormat, TABULAR_ANNOTATED) |
static Env_mp_utype | MP2s (tabularFormat, TABULAR_NONE) |
static Env_mp_utype | MP2s (tabularFormat, TABULAR_HEADER) |
static Env_mp_utype | MP2s (tabularFormat, TABULAR_EVAL_ID) |
static Env_mp_utype | MP2s (tabularFormat, TABULAR_IFACE_ID) |
static Env_mp_utype | MP2s (tabularFormat, TABULAR_ANNOTATED) |
static String | MP_ (errorFile) |
static String | MP_ (outputFile) |
static String | MP_ (postRunInput) |
static String | MP_ (postRunOutput) |
static String | MP_ (preRunInput) |
static String | MP_ (preRunOutput) |
static String | MP_ (readRestart) |
static String | MP_ (resultsOutputFile) |
static String | MP_ (runInput) |
static String | MP_ (runOutput) |
static String | MP_ (tabularDataFile) |
static String | MP_ (topMethodPointer) |
static String | MP_ (writeRestart) |
static bool | MP_ (checkFlag) |
static bool | MP_ (graphicsFlag) |
static bool | MP_ (postRunFlag) |
static bool | MP_ (preRunFlag) |
static bool | MP_ (resultsOutputFlag) |
static bool | MP_ (runFlag) |
static bool | MP_ (tabularDataFlag) |
static int | MP_ (outputPrecision) |
static int | MP_ (stopRestart) |
static size_t | MP_ (numBetaUncVars) |
static size_t | MP_ (numBinomialUncVars) |
static size_t | MP_ (numContinuousDesVars) |
static size_t | MP_ (numContinuousIntervalUncVars) |
static size_t | MP_ (numContinuousStateVars) |
static size_t | MP_ (numDiscreteDesRangeVars) |
static size_t | MP_ (numDiscreteDesSetIntVars) |
static size_t | MP_ (numDiscreteDesSetStrVars) |
static size_t | MP_ (numDiscreteDesSetRealVars) |
static size_t | MP_ (numDiscreteIntervalUncVars) |
static size_t | MP_ (numDiscreteStateRangeVars) |
static size_t | MP_ (numDiscreteStateSetIntVars) |
static size_t | MP_ (numDiscreteStateSetStrVars) |
static size_t | MP_ (numDiscreteStateSetRealVars) |
static size_t | MP_ (numDiscreteUncSetIntVars) |
static size_t | MP_ (numDiscreteUncSetStrVars) |
static size_t | MP_ (numDiscreteUncSetRealVars) |
static size_t | MP_ (numExponentialUncVars) |
static size_t | MP_ (numFrechetUncVars) |
static size_t | MP_ (numGammaUncVars) |
static size_t | MP_ (numGeometricUncVars) |
static size_t | MP_ (numGumbelUncVars) |
static size_t | MP_ (numHistogramBinUncVars) |
static size_t | MP_ (numHistogramPtIntUncVars) |
static size_t | MP_ (numHistogramPtStrUncVars) |
static size_t | MP_ (numHistogramPtRealUncVars) |
static size_t | MP_ (numHyperGeomUncVars) |
static size_t | MP_ (numLognormalUncVars) |
static size_t | MP_ (numLoguniformUncVars) |
static size_t | MP_ (numNegBinomialUncVars) |
static size_t | MP_ (numNormalUncVars) |
static size_t | MP_ (numPoissonUncVars) |
static size_t | MP_ (numTriangularUncVars) |
static size_t | MP_ (numUniformUncVars) |
static size_t | MP_ (numWeibullUncVars) |
static IntVector | VP_ (ddsi) |
static IntVector | VP_ (DIlb) |
static IntVector | MP_ (discreteDesignRangeLowerBnds) |
static IntVector | MP_ (discreteDesignRangeUpperBnds) |
static IntVector | MP_ (discreteDesignRangeVars) |
static IntVector | MP_ (discreteDesignSetIntVars) |
static IntVector | MP_ (discreteIntervalUncVars) |
static IntVector | MP_ (discreteStateRangeLowerBnds) |
static IntVector | MP_ (discreteStateRangeUpperBnds) |
static IntVector | MP_ (discreteStateRangeVars) |
static IntVector | MP_ (discreteStateSetIntVars) |
static IntVector | MP_ (discreteUncSetIntVars) |
static IntVector | VP_ (DIub) |
static IntVector | MP_ (histogramPointIntUncVars) |
static IntVector | VP_ (hpia) |
static IntVector | VP_ (dssi) |
static IntVector | VP_ (ddsia) |
static IntVector | VP_ (ddssa) |
static IntVector | VP_ (ddsra) |
static IntVector | VP_ (dusi) |
static IntArray | VP_ (nddsi) |
static IntArray | VP_ (nddss) |
static IntArray | VP_ (nddsr) |
static IntArray | VP_ (ndssi) |
static IntArray | VP_ (ndsss) |
static IntArray | VP_ (ndssr) |
static IntArray | VP_ (ndusi) |
static IntArray | VP_ (nduss) |
static IntArray | VP_ (ndusr) |
static IntArray | VP_ (nhbp) |
static IntArray | VP_ (nhpip) |
static IntArray | VP_ (nhpsp) |
static IntArray | VP_ (nhprp) |
static IntArray | VP_ (nCI) |
static IntArray | VP_ (nDI) |
static RealVector | MP_ (betaUncLowerBnds) |
static RealVector | MP_ (betaUncUpperBnds) |
static RealVector | MP_ (betaUncVars) |
static RealVector | MP_ (binomialUncProbPerTrial) |
static RealVector | MP_ (continuousDesignLowerBnds) |
static RealVector | MP_ (continuousDesignUpperBnds) |
static RealVector | MP_ (continuousDesignVars) |
static RealVector | MP_ (continuousDesignScales) |
static RealVector | MP_ (continuousIntervalUncVars) |
static RealVector | MP_ (continuousStateLowerBnds) |
static RealVector | MP_ (continuousStateUpperBnds) |
static RealVector | MP_ (continuousStateVars) |
static RealVector | MP_ (discreteDesignSetRealVars) |
static RealVector | MP_ (discreteStateSetRealVars) |
static RealVector | MP_ (discreteUncSetRealVars) |
static RealVector | MP_ (frechetUncBetas) |
static RealVector | MP_ (frechetUncVars) |
static RealVector | MP_ (geometricUncProbPerTrial) |
static RealVector | MP_ (gumbelUncBetas) |
static RealVector | MP_ (gumbelUncVars) |
static RealVector | MP_ (histogramBinUncVars) |
static RealVector | MP_ (histogramPointRealUncVars) |
static RealVector | MP_ (negBinomialUncProbPerTrial) |
static RealVector | MP_ (normalUncLowerBnds) |
static RealVector | MP_ (normalUncMeans) |
static RealVector | MP_ (normalUncUpperBnds) |
static RealVector | MP_ (normalUncVars) |
static RealVector | MP_ (triangularUncModes) |
static RealVector | MP_ (triangularUncVars) |
static RealVector | MP_ (uniformUncVars) |
static RealVector | MP_ (weibullUncVars) |
static RealVector | VP_ (ddsr) |
static RealVector | VP_ (dssr) |
static RealVector | VP_ (dusr) |
static RealVector | VP_ (CIlb) |
static RealVector | VP_ (CIub) |
static RealVector | VP_ (CIp) |
static RealVector | VP_ (DIp) |
static RealVector | VP_ (DSIp) |
static RealVector | VP_ (DSSp) |
static RealVector | VP_ (DSRp) |
static RealVector | VP_ (hba) |
static RealVector | VP_ (hbo) |
static RealVector | VP_ (hbc) |
static RealVector | VP_ (hpic) |
static RealVector | VP_ (hpsc) |
static RealVector | VP_ (hpra) |
static RealVector | VP_ (hprc) |
static RealVector | VP_ (ucm) |
static String | MP_ (idVariables) |
static StringArray | MP_ (continuousDesignLabels) |
static StringArray | MP_ (continuousDesignScaleTypes) |
static StringArray | MP_ (continuousStateLabels) |
static StringArray | MP_ (discreteDesignRangeLabels) |
static StringArray | MP_ (discreteDesignSetIntLabels) |
static StringArray | MP_ (discreteDesignSetStrLabels) |
static StringArray | MP_ (discreteDesignSetRealLabels) |
static StringArray | MP_ (discreteStateRangeLabels) |
static StringArray | MP_ (discreteStateSetIntLabels) |
static StringArray | MP_ (discreteStateSetStrLabels) |
static StringArray | MP_ (discreteStateSetRealLabels) |
static StringArray | MP_ (discreteDesignSetStrVars) |
static StringArray | MP_ (discreteUncSetStrVars) |
static StringArray | MP_ (discreteStateSetStrVars) |
static StringArray | MP_ (histogramPointStrUncVars) |
static StringArray | VP_ (hpsa) |
static StringArray | VP_ (ddss) |
static StringArray | VP_ (duss) |
static StringArray | VP_ (dsss) |
static BitArray | MP_ (discreteDesignSetIntCat) |
static BitArray | MP_ (discreteDesignSetRealCat) |
static BitArray | MP_ (discreteStateSetIntCat) |
static BitArray | MP_ (discreteStateSetRealCat) |
static BitArray | MP_ (discreteUncSetIntCat) |
static BitArray | MP_ (discreteUncSetRealCat) |
static Var_brv | MP2s (betaUncAlphas, 0.) |
static Var_brv | MP2s (betaUncBetas, 0.) |
static Var_brv | MP2s (exponentialUncBetas, 0.) |
static Var_brv | MP2s (exponentialUncVars, 0.) |
static Var_brv | MP2s (frechetUncAlphas, 2.) |
static Var_brv | MP2s (gammaUncAlphas, 0.) |
static Var_brv | MP2s (gammaUncBetas, 0.) |
static Var_brv | MP2s (gammaUncVars, 0.) |
static Var_brv | MP2s (gumbelUncAlphas, 0.) |
static Var_brv | MP2s (lognormalUncErrFacts, 1.) |
static Var_brv | MP2s (lognormalUncLambdas, 0.) |
static Var_brv | MP2s (lognormalUncLowerBnds, 0.) |
static Var_brv | MP2s (lognormalUncMeans, 0.) |
static Var_brv | MP2s (lognormalUncStdDevs, 0.) |
static Var_brv | MP2s (lognormalUncUpperBnds, std::numeric_limits< Real >::infinity()) |
static Var_brv | MP2s (lognormalUncVars, 0.) |
static Var_brv | MP2s (lognormalUncZetas, 0.) |
static Var_brv | MP2s (loguniformUncLowerBnds, 0.) |
static Var_brv | MP2s (loguniformUncUpperBnds, std::numeric_limits< Real >::infinity()) |
static Var_brv | MP2s (loguniformUncVars, 0.) |
static Var_brv | MP2s (normalUncStdDevs, 0.) |
static Var_brv | MP2s (poissonUncLambdas, 0.) |
static Var_brv | MP2s (triangularUncLowerBnds,-std::numeric_limits< Real >::infinity()) |
static Var_brv | MP2s (triangularUncUpperBnds, std::numeric_limits< Real >::infinity()) |
static Var_brv | MP2s (uniformUncLowerBnds,-std::numeric_limits< Real >::infinity()) |
static Var_brv | MP2s (uniformUncUpperBnds, std::numeric_limits< Real >::infinity()) |
static Var_brv | MP2s (weibullUncAlphas, 0.) |
static Var_brv | MP2s (weibullUncBetas, 0.) |
static Var_biv | MP2s (binomialUncNumTrials, 0) |
static Var_biv | MP2s (binomialUncVars, 0) |
static Var_biv | MP2s (geometricUncVars, 0) |
static Var_biv | MP2s (hyperGeomUncNumDrawn, 0) |
static Var_biv | MP2s (hyperGeomUncSelectedPop, 0) |
static Var_biv | MP2s (hyperGeomUncTotalPop, 0) |
static Var_biv | MP2s (hyperGeomUncVars, 0) |
static Var_biv | MP2s (negBinomialUncNumTrials, 0) |
static Var_biv | MP2s (negBinomialUncVars, 0) |
static Var_biv | MP2s (poissonUncVars, 0) |
static Var_mp_type | Vtype (varsDomain, MIXED_DOMAIN) |
static Var_mp_type | Vtype (varsDomain, RELAXED_DOMAIN) |
static Var_mp_type | Vtype (varsView, ALL_VIEW) |
static Var_mp_type | Vtype (varsView, DESIGN_VIEW) |
static Var_mp_type | Vtype (varsView, UNCERTAIN_VIEW) |
static Var_mp_type | Vtype (varsView, ALEATORY_UNCERTAIN_VIEW) |
static Var_mp_type | Vtype (varsView, EPISTEMIC_UNCERTAIN_VIEW) |
static Var_mp_type | Vtype (varsView, STATE_VIEW) |
template<class ContainerT > | |
void | flatten_num_array (const std::vector< ContainerT > &input_array, IntArray **pia) |
Free convenience function that flatten sizes of an array of std containers; takes an array of containers and returns an IntArray containing the sizes of each container in the input array. Note: Did not specialize for vector<RealVector> as no current use cases. | |
void | dn2f_ (int *n, int *p, Real *x, Calcrj, int *iv, int *liv, int *lv, Real *v, int *ui, void *ur, Vf) |
void | dn2fb_ (int *n, int *p, Real *x, Real *b, Calcrj, int *iv, int *liv, int *lv, Real *v, int *ui, void *ur, Vf) |
void | dn2g_ (int *n, int *p, Real *x, Calcrj, Calcrj, int *iv, int *liv, int *lv, Real *v, int *ui, void *ur, Vf) |
void | dn2gb_ (int *n, int *p, Real *x, Real *b, Calcrj, Calcrj, int *iv, int *liv, int *lv, Real *v, int *ui, void *ur, Vf) |
void | divset_ (int *, int *, int *, int *, Real *) |
double | dr7mdc_ (int *) |
static void | Rswapchk (Nl2Misc *q) |
static int | hasnaninf (const double *d, int n) |
NLPQLPOptimizer * | new_NLPQLPOptimizer (ProblemDescDB &problem_db) |
NLPQLPOptimizer * | new_NLPQLPOptimizer (Model &model) |
NLPQLPOptimizer * | new_NLPQLPOptimizer (ProblemDescDB &problem_db, Model &model) |
NPSOLOptimizer * | new_NPSOLOptimizer (ProblemDescDB &problem_db) |
NPSOLOptimizer * | new_NPSOLOptimizer1 (Model &model) |
NPSOLOptimizer * | new_NPSOLOptimizer2 (Model &model, const int &derivative_level, const Real &conv_tol) |
NPSOLOptimizer * | new_NPSOLOptimizer3 (const RealVector &initial_point, const RealVector &var_lower_bnds, const RealVector &var_upper_bnds, const RealMatrix &lin_ineq_coeffs, const RealVector &lin_ineq_lower_bnds, const RealVector &lin_ineq_upper_bnds, const RealMatrix &lin_eq_coeffs, const RealVector &lin_eq_targets, const RealVector &nonlin_ineq_lower_bnds, const RealVector &nonlin_ineq_upper_bnds, const RealVector &nonlin_eq_targets, void(*user_obj_eval)(int &, int &, double *, double &, double *, int &), void(*user_con_eval)(int &, int &, int &, int &, int *, double *, double *, double *, int &), const int &derivative_level, const Real &conv_tol) |
NPSOLOptimizer * | new_NPSOLOptimizer (ProblemDescDB &problem_db, Model &model) |
NPSOLOptimizer * | new_NPSOLOptimizer (Model &model) |
NPSOLOptimizer * | new_NPSOLOptimizer (Model &model, const int &, const Real &) |
NPSOLOptimizer * | new_NPSOLOptimizer (const RealVector &initial_point, const RealVector &var_lower_bnds, const RealVector &var_upper_bnds, const RealMatrix &lin_ineq_coeffs, const RealVector &lin_ineq_lower_bnds, const RealVector &lin_ineq_upper_bnds, const RealMatrix &lin_eq_coeffs, const RealVector &lin_eq_targets, const RealVector &nonlin_ineq_lower_bnds, const RealVector &nonlin_ineq_upper_bnds, const RealVector &nonlin_eq_targets, void(*user_obj_eval)(int &, int &, double *, double &, double *, int &), void(*user_con_eval)(int &, int &, int &, int &, int *, double *, double *, double *, int &), const int &derivative_level, const Real &conv_tol) |
void | start_dakota_heartbeat (int) |
void | dak_sigcatch (int sig) |
MPIUnpackBuffer & | operator>> (MPIUnpackBuffer &s, ParallelLevel &pl) |
MPIUnpackBuffer extraction operator for ParallelLevel. Calls read(MPIUnpackBuffer&). | |
MPIPackBuffer & | operator<< (MPIPackBuffer &s, const ParallelLevel &pl) |
MPIPackBuffer insertion operator for ParallelLevel. Calls write(MPIPackBuffer&). | |
std::istream & | operator>> (std::istream &s, ParamResponsePair &pair) |
std::istream extraction operator for ParamResponsePair | |
std::ostream & | operator<< (std::ostream &s, const ParamResponsePair &pair) |
std::ostream insertion operator for ParamResponsePair | |
MPIUnpackBuffer & | operator>> (MPIUnpackBuffer &s, ParamResponsePair &pair) |
MPIUnpackBuffer extraction operator for ParamResponsePair. | |
MPIPackBuffer & | operator<< (MPIPackBuffer &s, const ParamResponsePair &pair) |
MPIPackBuffer insertion operator for ParamResponsePair. | |
bool | operator== (const ParamResponsePair &pair1, const ParamResponsePair &pair2) |
equality operator for ParamResponsePair | |
bool | operator!= (const ParamResponsePair &pair1, const ParamResponsePair &pair2) |
inequality operator for ParamResponsePair | |
static void * | binsearch (void *kw, size_t kwsize, size_t n, const char *key) |
static const char * | Begins (const String &entry_name, const char *s) |
static void | Bad_name (String entry_name, const char *where) |
static void | Locked_db () |
static void | Null_rep (const char *who) |
static void | Null_rep1 (const char *who) |
MPIUnpackBuffer & | operator>> (MPIUnpackBuffer &s, ProgramOptions &progopt) |
MPIUnpackBuffer extraction operator. | |
MPIPackBuffer & | operator<< (MPIPackBuffer &s, const ProgramOptions &progopt) |
MPIPackBuffer insertion operator. | |
bool | set_compare (const ParamResponsePair &database_pr, const ActiveSet &search_set) |
search function for a particular ParamResponsePair within a PRPList based on ActiveSet content (request vector and derivative variables vector) | |
bool | id_vars_exact_compare (const ParamResponsePair &database_pr, const ParamResponsePair &search_pr) |
search function for a particular ParamResponsePair within a PRPMultiIndex | |
std::size_t | hash_value (const ParamResponsePair &prp) |
hash_value for ParamResponsePairs stored in a PRPMultiIndex | |
PRPCacheHIter | hashedCacheBegin (PRPCache &prp_cache) |
hashed definition of cache begin | |
PRPCacheHIter | hashedCacheEnd (PRPCache &prp_cache) |
hashed definition of cache end | |
PRPQueueHIter | hashedQueueBegin (PRPQueue &prp_queue) |
hashed definition of queue begin | |
PRPQueueHIter | hashedQueueEnd (PRPQueue &prp_queue) |
hashed definition of queue end | |
PRPCacheHIter | lookup_by_val (PRPMultiIndexCache &prp_cache, const ParamResponsePair &search_pr) |
find a ParamResponsePair based on the interface id, variables, and ActiveSet search data within search_pr. | |
PRPCacheHIter | lookup_by_val (PRPMultiIndexCache &prp_cache, const String &search_interface_id, const Variables &search_vars, const ActiveSet &search_set) |
find a ParamResponsePair within a PRPMultiIndexCache based on the interface id, variables, and ActiveSet search data | |
PRPCacheOIter | lookup_by_nearby_val (PRPMultiIndexCache &prp_cache, const String &search_interface_id, const Variables &search_vars, const ActiveSet &search_set, Real tol) |
PRPCacheOIter | lookup_by_ids (PRPMultiIndexCache &prp_cache, const IntStringPair &search_ids) |
find a ParamResponsePair within a PRPMultiIndexCache based on search_ids (i.e. std::pair<eval_id,interface_id>) search data | |
PRPCacheOIter | lookup_by_ids (PRPMultiIndexCache &prp_cache, const IntStringPair &search_ids, const ParamResponsePair &search_pr) |
PRPQueueHIter | lookup_by_val (PRPMultiIndexQueue &prp_queue, const ParamResponsePair &search_pr) |
find a ParamResponsePair based on the interface id, variables, and ActiveSet search data within search_pr. | |
PRPQueueHIter | lookup_by_val (PRPMultiIndexQueue &prp_queue, const String &search_interface_id, const Variables &search_vars, const ActiveSet &search_set) |
find a ParamResponsePair within a PRPMultiIndexQueue based on interface id, variables, and ActiveSet search data | |
PRPQueueOIter | lookup_by_eval_id (PRPMultiIndexQueue &prp_queue, int search_id) |
find a ParamResponsePair within a PRPMultiIndexQueue based on search_id (i.e. integer eval_id) search data | |
void | print_usage (std::ostream &s) |
print restart utility help message | |
void | print_restart (StringArray pos_args, String print_dest) |
print a restart file | |
void | print_restart_pdb (StringArray pos_args, String print_dest) |
print a restart file (PDB format) | |
void | print_restart_tabular (StringArray pos_args, String print_dest, unsigned short tabular_format) |
print a restart file (tabular format) | |
void | read_neutral (StringArray pos_args) |
read a restart file (neutral file format) | |
void | repair_restart (StringArray pos_args, String identifier_type) |
repair a restart file by removing corrupted evaluations | |
void | concatenate_restart (StringArray pos_args) |
concatenate multiple restart files | |
static HANDLE * | wait_setup (std::map< pid_t, int > *M, size_t *pn) |
static int | wait_for_one (size_t n, HANDLE *h, int req1, size_t *pi) |
int | salinas_main (int argc, char *argv[], MPI_Comm *comm) |
subroutine interface to SALINAS simulation code | |
std::string | get_cwd_str () |
std::vector< std::string > | get_pathext () |
bool | contains (const bfs::path &dir_path, const std::string &file_name, boost::filesystem::path &complete_filepath) |
Variables | |
PRPCache | data_pairs |
contains all parameter/response pairs. | |
short | abort_mode = ABORT_EXITS |
by default Dakota exits or calls MPI_Abort on errors | |
std::ostream * | dakota_cout = &std::cout |
DAKOTA stdout initially points to < std::cout, but may be redirected to a tagged ofstream if there are < concurrent iterators. | |
std::ostream * | dakota_cerr = &std::cerr |
DAKOTA stderr initially points to < std::cerr, but may be redirected to a tagged ofstream if there are < concurrent iterators. | |
ResultsManager | iterator_results_db |
Global results database for iterator results. | |
int | write_precision = 10 |
used in ostream data output functions < (restart_util.cpp overrides default value) | |
MPIManager | dummy_mpi_mgr |
dummy MPIManager for ref initialization | |
ProgramOptions | dummy_prg_opt |
dummy ProgramOptions for ref initialization | |
OutputManager | dummy_out_mgr |
dummy OutputManager for ref initialization | |
ParallelLibrary | dummy_lib |
dummy ParallelLibrary for ref initialization | |
ProblemDescDB | dummy_db |
dummy ProblemDescDB for ref initialization | |
int | mc_ptr_int = 0 |
global pointer for ModelCenter API | |
int | dc_ptr_int = 0 |
global pointer for ModelCenter eval DB | |
ProblemDescDB * | Dak_pddb |
set by ProblemDescDB, for use in parsing | |
const size_t | _NPOS = ~(size_t)0 |
special value returned by index() when entry not found | |
Interface | dummy_interface |
dummy Interface object used for mandatory < reference initialization or default virtual < function return by reference when a real < Interface instance is unavailable | |
Model | dummy_model |
dummy Model object used for mandatory reference < initialization or default virtual function < return by reference when a real Model instance < is unavailable | |
Iterator | dummy_iterator |
dummy Iterator object used for mandatory < reference initialization or default virtual < function return by reference when a real < Iterator instance is unavailable | |
Dakota_funcs * | DF |
Dakota_funcs | DakFuncs0 |
const char * | FIELD_NAMES [] |
const int | NUMBER_OF_FIELDS = 23 |
static const int | MPI_COMM_WORLD = 1 |
static const int | MPI_COMM_NULL = 0 |
static const int | MPI_ANY_TAG = -1 |
static void * | MPI_REQUEST_NULL = NULL |
static GuiKeyWord | kw_1 [3] |
static GuiKeyWord | kw_2 [3] |
static GuiKeyWord | kw_3 [2] |
static GuiKeyWord | kw_4 [3] |
static GuiKeyWord | kw_5 [3] |
static GuiKeyWord | kw_6 [2] |
static GuiKeyWord | kw_7 [1] |
static GuiKeyWord | kw_8 [1] |
static GuiKeyWord | kw_9 [2] |
static GuiKeyWord | kw_10 [3] |
static GuiKeyWord | kw_11 [5] |
static GuiKeyWord | kw_12 [15] |
static GuiKeyWord | kw_13 [1] |
static GuiKeyWord | kw_14 [4] |
static GuiKeyWord | kw_15 [1] |
static GuiKeyWord | kw_16 [4] |
static GuiKeyWord | kw_17 [1] |
static GuiKeyWord | kw_18 [8] |
static GuiKeyWord | kw_19 [9] |
static GuiKeyWord | kw_20 [12] |
static GuiKeyWord | kw_21 [2] |
static GuiKeyWord | kw_22 [2] |
static GuiKeyWord | kw_23 [3] |
static GuiKeyWord | kw_24 [2] |
static GuiKeyWord | kw_25 [2] |
static GuiKeyWord | kw_26 [9] |
static GuiKeyWord | kw_27 [2] |
static GuiKeyWord | kw_28 [1] |
static GuiKeyWord | kw_29 [1] |
static GuiKeyWord | kw_30 [2] |
static GuiKeyWord | kw_31 [4] |
static GuiKeyWord | kw_32 [3] |
static GuiKeyWord | kw_33 [3] |
static GuiKeyWord | kw_34 [3] |
static GuiKeyWord | kw_35 [3] |
static GuiKeyWord | kw_36 [4] |
static GuiKeyWord | kw_37 [2] |
static GuiKeyWord | kw_38 [3] |
static GuiKeyWord | kw_39 [2] |
static GuiKeyWord | kw_40 [15] |
static GuiKeyWord | kw_41 [7] |
static GuiKeyWord | kw_42 [2] |
static GuiKeyWord | kw_43 [19] |
static GuiKeyWord | kw_44 [3] |
static GuiKeyWord | kw_45 [3] |
static GuiKeyWord | kw_46 [3] |
static GuiKeyWord | kw_47 [4] |
static GuiKeyWord | kw_48 [6] |
static GuiKeyWord | kw_49 [2] |
static GuiKeyWord | kw_50 [2] |
static GuiKeyWord | kw_51 [1] |
static GuiKeyWord | kw_52 [5] |
static GuiKeyWord | kw_53 [6] |
static GuiKeyWord | kw_54 [1] |
static GuiKeyWord | kw_55 [2] |
static GuiKeyWord | kw_56 [2] |
static GuiKeyWord | kw_57 [4] |
static GuiKeyWord | kw_58 [2] |
static GuiKeyWord | kw_59 [3] |
static GuiKeyWord | kw_60 [3] |
static GuiKeyWord | kw_61 [3] |
static GuiKeyWord | kw_62 [4] |
static GuiKeyWord | kw_63 [10] |
static GuiKeyWord | kw_64 [3] |
static GuiKeyWord | kw_65 [3] |
static GuiKeyWord | kw_66 [3] |
static GuiKeyWord | kw_67 [4] |
static GuiKeyWord | kw_68 [6] |
static GuiKeyWord | kw_69 [2] |
static GuiKeyWord | kw_70 [2] |
static GuiKeyWord | kw_71 [1] |
static GuiKeyWord | kw_72 [5] |
static GuiKeyWord | kw_73 [9] |
static GuiKeyWord | kw_74 [9] |
static GuiKeyWord | kw_75 [4] |
static GuiKeyWord | kw_76 [7] |
static GuiKeyWord | kw_77 [8] |
static GuiKeyWord | kw_78 [2] |
static GuiKeyWord | kw_79 [12] |
static GuiKeyWord | kw_80 [3] |
static GuiKeyWord | kw_81 [2] |
static GuiKeyWord | kw_82 [3] |
static GuiKeyWord | kw_83 [2] |
static GuiKeyWord | kw_84 [5] |
static GuiKeyWord | kw_85 [4] |
static GuiKeyWord | kw_86 [15] |
static GuiKeyWord | kw_87 [3] |
static GuiKeyWord | kw_88 [2] |
static GuiKeyWord | kw_89 [2] |
static GuiKeyWord | kw_90 [18] |
static GuiKeyWord | kw_91 [14] |
static GuiKeyWord | kw_92 [12] |
static GuiKeyWord | kw_93 [10] |
static GuiKeyWord | kw_94 [1] |
static GuiKeyWord | kw_95 [15] |
static GuiKeyWord | kw_96 [15] |
static GuiKeyWord | kw_97 [3] |
static GuiKeyWord | kw_98 [3] |
static GuiKeyWord | kw_99 [2] |
static GuiKeyWord | kw_100 [3] |
static GuiKeyWord | kw_101 [4] |
static GuiKeyWord | kw_102 [7] |
static GuiKeyWord | kw_103 [9] |
static GuiKeyWord | kw_104 [3] |
static GuiKeyWord | kw_105 [1] |
static GuiKeyWord | kw_106 [9] |
static GuiKeyWord | kw_107 [1] |
static GuiKeyWord | kw_108 [11] |
static GuiKeyWord | kw_109 [3] |
static GuiKeyWord | kw_110 [3] |
static GuiKeyWord | kw_111 [3] |
static GuiKeyWord | kw_112 [4] |
static GuiKeyWord | kw_113 [2] |
static GuiKeyWord | kw_114 [3] |
static GuiKeyWord | kw_115 [2] |
static GuiKeyWord | kw_116 [11] |
static GuiKeyWord | kw_117 [2] |
static GuiKeyWord | kw_118 [2] |
static GuiKeyWord | kw_119 [3] |
static GuiKeyWord | kw_120 [2] |
static GuiKeyWord | kw_121 [3] |
static GuiKeyWord | kw_122 [3] |
static GuiKeyWord | kw_123 [2] |
static GuiKeyWord | kw_124 [3] |
static GuiKeyWord | kw_125 [4] |
static GuiKeyWord | kw_126 [5] |
static GuiKeyWord | kw_127 [12] |
static GuiKeyWord | kw_128 [2] |
static GuiKeyWord | kw_129 [3] |
static GuiKeyWord | kw_130 [3] |
static GuiKeyWord | kw_131 [2] |
static GuiKeyWord | kw_132 [3] |
static GuiKeyWord | kw_133 [4] |
static GuiKeyWord | kw_134 [5] |
static GuiKeyWord | kw_135 [8] |
static GuiKeyWord | kw_136 [2] |
static GuiKeyWord | kw_137 [1] |
static GuiKeyWord | kw_138 [1] |
static GuiKeyWord | kw_139 [3] |
static GuiKeyWord | kw_140 [3] |
static GuiKeyWord | kw_141 [3] |
static GuiKeyWord | kw_142 [4] |
static GuiKeyWord | kw_143 [2] |
static GuiKeyWord | kw_144 [3] |
static GuiKeyWord | kw_145 [2] |
static GuiKeyWord | kw_146 [2] |
static GuiKeyWord | kw_147 [16] |
static GuiKeyWord | kw_148 [2] |
static GuiKeyWord | kw_149 [1] |
static GuiKeyWord | kw_150 [2] |
static GuiKeyWord | kw_151 [1] |
static GuiKeyWord | kw_152 [1] |
static GuiKeyWord | kw_153 [5] |
static GuiKeyWord | kw_154 [1] |
static GuiKeyWord | kw_155 [2] |
static GuiKeyWord | kw_156 [8] |
static GuiKeyWord | kw_157 [2] |
static GuiKeyWord | kw_158 [3] |
static GuiKeyWord | kw_159 [2] |
static GuiKeyWord | kw_160 [12] |
static GuiKeyWord | kw_161 [3] |
static GuiKeyWord | kw_162 [4] |
static GuiKeyWord | kw_163 [3] |
static GuiKeyWord | kw_164 [2] |
static GuiKeyWord | kw_165 [1] |
static GuiKeyWord | kw_166 [1] |
static GuiKeyWord | kw_167 [2] |
static GuiKeyWord | kw_168 [3] |
static GuiKeyWord | kw_169 [2] |
static GuiKeyWord | kw_170 [7] |
static GuiKeyWord | kw_171 [3] |
static GuiKeyWord | kw_172 [5] |
static GuiKeyWord | kw_173 [4] |
static GuiKeyWord | kw_174 [10] |
static GuiKeyWord | kw_175 [1] |
static GuiKeyWord | kw_176 [2] |
static GuiKeyWord | kw_177 [4] |
static GuiKeyWord | kw_178 [2] |
static GuiKeyWord | kw_179 [7] |
static GuiKeyWord | kw_180 [17] |
static GuiKeyWord | kw_181 [2] |
static GuiKeyWord | kw_182 [5] |
static GuiKeyWord | kw_183 [3] |
static GuiKeyWord | kw_184 [1] |
static GuiKeyWord | kw_185 [6] |
static GuiKeyWord | kw_186 [3] |
static GuiKeyWord | kw_187 [2] |
static GuiKeyWord | kw_188 [1] |
static GuiKeyWord | kw_189 [3] |
static GuiKeyWord | kw_190 [1] |
static GuiKeyWord | kw_191 [2] |
static GuiKeyWord | kw_192 [4] |
static GuiKeyWord | kw_193 [22] |
static GuiKeyWord | kw_194 [1] |
static GuiKeyWord | kw_195 [1] |
static GuiKeyWord | kw_196 [7] |
static GuiKeyWord | kw_197 [2] |
static GuiKeyWord | kw_198 [5] |
static GuiKeyWord | kw_199 [10] |
static GuiKeyWord | kw_200 [2] |
static GuiKeyWord | kw_201 [2] |
static GuiKeyWord | kw_202 [3] |
static GuiKeyWord | kw_203 [2] |
static GuiKeyWord | kw_204 [10] |
static GuiKeyWord | kw_205 [1] |
static GuiKeyWord | kw_206 [2] |
static GuiKeyWord | kw_207 [4] |
static GuiKeyWord | kw_208 [2] |
static GuiKeyWord | kw_209 [3] |
static GuiKeyWord | kw_210 [4] |
static GuiKeyWord | kw_211 [2] |
static GuiKeyWord | kw_212 [3] |
static GuiKeyWord | kw_213 [1] |
static GuiKeyWord | kw_214 [1] |
static GuiKeyWord | kw_215 [2] |
static GuiKeyWord | kw_216 [2] |
static GuiKeyWord | kw_217 [1] |
static GuiKeyWord | kw_218 [17] |
static GuiKeyWord | kw_219 [3] |
static GuiKeyWord | kw_220 [6] |
static GuiKeyWord | kw_221 [3] |
static GuiKeyWord | kw_222 [3] |
static GuiKeyWord | kw_223 [6] |
static GuiKeyWord | kw_224 [3] |
static GuiKeyWord | kw_225 [2] |
static GuiKeyWord | kw_226 [4] |
static GuiKeyWord | kw_227 [3] |
static GuiKeyWord | kw_228 [2] |
static GuiKeyWord | kw_229 [5] |
static GuiKeyWord | kw_230 [2] |
static GuiKeyWord | kw_231 [30] |
static GuiKeyWord | kw_232 [1] |
static GuiKeyWord | kw_233 [4] |
static GuiKeyWord | kw_234 [1] |
static GuiKeyWord | kw_235 [13] |
static GuiKeyWord | kw_236 [3] |
static GuiKeyWord | kw_237 [3] |
static GuiKeyWord | kw_238 [2] |
static GuiKeyWord | kw_239 [3] |
static GuiKeyWord | kw_240 [2] |
static GuiKeyWord | kw_241 [2] |
static GuiKeyWord | kw_242 [4] |
static GuiKeyWord | kw_243 [2] |
static GuiKeyWord | kw_244 [4] |
static GuiKeyWord | kw_245 [2] |
static GuiKeyWord | kw_246 [28] |
static GuiKeyWord | kw_247 [2] |
static GuiKeyWord | kw_248 [13] |
static GuiKeyWord | kw_249 [12] |
static GuiKeyWord | kw_250 [11] |
static GuiKeyWord | kw_251 [3] |
static GuiKeyWord | kw_252 [4] |
static GuiKeyWord | kw_253 [16] |
static GuiKeyWord | kw_254 [5] |
static GuiKeyWord | kw_255 [2] |
static GuiKeyWord | kw_256 [1] |
static GuiKeyWord | kw_257 [10] |
static GuiKeyWord | kw_258 [4] |
static GuiKeyWord | kw_259 [5] |
static GuiKeyWord | kw_260 [2] |
static GuiKeyWord | kw_261 [2] |
static GuiKeyWord | kw_262 [2] |
static GuiKeyWord | kw_263 [2] |
static GuiKeyWord | kw_264 [4] |
static GuiKeyWord | kw_265 [20] |
static GuiKeyWord | kw_266 [15] |
static GuiKeyWord | kw_267 [7] |
static GuiKeyWord | kw_268 [2] |
static GuiKeyWord | kw_269 [7] |
static GuiKeyWord | kw_270 [1] |
static GuiKeyWord | kw_271 [4] |
static GuiKeyWord | kw_272 [6] |
static GuiKeyWord | kw_273 [13] |
static GuiKeyWord | kw_274 [4] |
static GuiKeyWord | kw_275 [90] |
static GuiKeyWord | kw_276 [1] |
static GuiKeyWord | kw_277 [2] |
static GuiKeyWord | kw_278 [7] |
static GuiKeyWord | kw_279 [2] |
static GuiKeyWord | kw_280 [1] |
static GuiKeyWord | kw_281 [3] |
static GuiKeyWord | kw_282 [4] |
static GuiKeyWord | kw_283 [6] |
static GuiKeyWord | kw_284 [2] |
static GuiKeyWord | kw_285 [2] |
static GuiKeyWord | kw_286 [3] |
static GuiKeyWord | kw_287 [3] |
static GuiKeyWord | kw_288 [3] |
static GuiKeyWord | kw_289 [2] |
static GuiKeyWord | kw_290 [4] |
static GuiKeyWord | kw_291 [7] |
static GuiKeyWord | kw_292 [2] |
static GuiKeyWord | kw_293 [3] |
static GuiKeyWord | kw_294 [4] |
static GuiKeyWord | kw_295 [2] |
static GuiKeyWord | kw_296 [3] |
static GuiKeyWord | kw_297 [3] |
static GuiKeyWord | kw_298 [5] |
static GuiKeyWord | kw_299 [2] |
static GuiKeyWord | kw_300 [3] |
static GuiKeyWord | kw_301 [4] |
static GuiKeyWord | kw_302 [5] |
static GuiKeyWord | kw_303 [3] |
static GuiKeyWord | kw_304 [23] |
static GuiKeyWord | kw_305 [6] |
static GuiKeyWord | kw_306 [3] |
static GuiKeyWord | kw_307 [2] |
static GuiKeyWord | kw_308 [2] |
static GuiKeyWord | kw_309 [5] |
static GuiKeyWord | kw_310 [7] |
static GuiKeyWord | kw_311 [2] |
static GuiKeyWord | kw_312 [3] |
static GuiKeyWord | kw_313 [6] |
static GuiKeyWord | kw_314 [2] |
static GuiKeyWord | kw_315 [6] |
static GuiKeyWord | kw_316 [4] |
static GuiKeyWord | kw_317 [6] |
static GuiKeyWord | kw_318 [8] |
static GuiKeyWord | kw_319 [18] |
static GuiKeyWord | kw_320 [4] |
static GuiKeyWord | kw_321 [10] |
static GuiKeyWord | kw_322 [2] |
static GuiKeyWord | kw_323 [1] |
static GuiKeyWord | kw_324 [2] |
static GuiKeyWord | kw_325 [8] |
static GuiKeyWord | kw_326 [4] |
static GuiKeyWord | kw_327 [6] |
static GuiKeyWord | kw_328 [8] |
static GuiKeyWord | kw_329 [15] |
static GuiKeyWord | kw_330 [4] |
static GuiKeyWord | kw_331 [4] |
static GuiKeyWord | kw_332 [8] |
static GuiKeyWord | kw_333 [7] |
static GuiKeyWord | kw_334 [1] |
static GuiKeyWord | kw_335 [2] |
static GuiKeyWord | kw_336 [19] |
static GuiKeyWord | kw_337 [6] |
static GuiKeyWord | kw_338 [11] |
static GuiKeyWord | kw_339 [5] |
static GuiKeyWord | kw_340 [12] |
static GuiKeyWord | kw_341 [10] |
static GuiKeyWord | kw_342 [8] |
static GuiKeyWord | kw_343 [8] |
static GuiKeyWord | kw_344 [1] |
static GuiKeyWord | kw_345 [7] |
static GuiKeyWord | kw_346 [1] |
static GuiKeyWord | kw_347 [7] |
static GuiKeyWord | kw_348 [7] |
static GuiKeyWord | kw_349 [3] |
static GuiKeyWord | kw_350 [9] |
static GuiKeyWord | kw_351 [8] |
static GuiKeyWord | kw_352 [7] |
static GuiKeyWord | kw_353 [7] |
static GuiKeyWord | kw_354 [6] |
static GuiKeyWord | kw_355 [3] |
static GuiKeyWord | kw_356 [9] |
static GuiKeyWord | kw_357 [9] |
static GuiKeyWord | kw_358 [8] |
static GuiKeyWord | kw_359 [3] |
static GuiKeyWord | kw_360 [5] |
static GuiKeyWord | kw_361 [7] |
static GuiKeyWord | kw_362 [7] |
static GuiKeyWord | kw_363 [4] |
static GuiKeyWord | kw_364 [7] |
static GuiKeyWord | kw_365 [11] |
static GuiKeyWord | kw_366 [6] |
static GuiKeyWord | kw_367 [6] |
static GuiKeyWord | kw_368 [6] |
static GuiKeyWord | kw_369 [3] |
static GuiKeyWord | kw_370 [5] |
static GuiKeyWord | kw_371 [2] |
static GuiKeyWord | kw_372 [4] |
static GuiKeyWord | kw_373 [11] |
static GuiKeyWord | kw_374 [7] |
static GuiKeyWord | kw_375 [5] |
static GuiKeyWord | kw_376 [11] |
static GuiKeyWord | kw_377 [3] |
static GuiKeyWord | kw_378 [9] |
static GuiKeyWord | kw_379 [7] |
static GuiKeyWord | kw_380 [7] |
static GuiKeyWord | kw_381 [34] |
static GuiKeyWord | kw_382 [6] |
static KeyWord | kw_383 [6] |
static KeyWord | kw_384 [6] |
static KeyWord | kw_385 [6] |
static KeyWord | kw_386 [3] |
static KeyWord | kw_387 [5] |
static KeyWord | kw_388 [2] |
static KeyWord | kw_389 [4] |
static KeyWord | kw_390 [11] |
static KeyWord | kw_391 [7] |
static KeyWord | kw_392 [5] |
static KeyWord | kw_393 [11] |
static KeyWord | kw_394 [3] |
static KeyWord | kw_395 [9] |
static KeyWord | kw_396 [7] |
static KeyWord | kw_397 [7] |
static KeyWord | kw_398 [34] |
static KeyWord | kw_399 [6] |
FILE * | nidrin |
const size_t | NIDR_MAX_ERROR_LEN = 8192 |
maximum error length is roughly 100 lines at 80 char; using fixed error length instead of investing in converting to vsnprintf (C++11) | |
static const char * | aln_scaletypes [] = { "auto", "log", "none", 0 } |
static Var_uinfo | CAUVLbl [CAUVar_Nkinds] |
static Var_uinfo | DAUIVLbl [DAUIVar_Nkinds] |
static Var_uinfo | DAUSVLbl [DAUSVar_Nkinds] |
static Var_uinfo | DAURVLbl [DAURVar_Nkinds] |
static Var_uinfo | CEUVLbl [CEUVar_Nkinds] |
static Var_uinfo | DEUIVLbl [DEUIVar_Nkinds] |
static Var_uinfo | DEUSVLbl [DEUSVar_Nkinds] |
static Var_uinfo | DEURVLbl [DEURVar_Nkinds] |
static Var_uinfo | DiscSetLbl [DiscSetVar_Nkinds] |
static VarLabelChk | DesignAndStateLabelsCheck [] |
Variables label array designations for design and state. All non-uncertain variables need to be in this array. Used in check_variables_node to check lengths and make_variable_defaults to build labels. | |
static VLreal | VLUncertainReal [NUM_UNC_REAL_CONT] |
Variables labels/bounds/values check array for real-valued uncertain variables; one array entry per contiguous container. These associate the individual variables given by, e.g., CAUVLbl, with the contiguous container in which they are stored. | |
static VLint | VLUncertainInt [NUM_UNC_INT_CONT] |
Variables labels/bounds/values check array for integer-valued uncertain variables; one array entry per contiguous container. These associate the individual variables given by, e.g., DAUIVLbl, with the contiguous container in which they are stored. | |
static VLstr | VLUncertainStr [NUM_UNC_STR_CONT] |
Variables labels/bounds/values check array for string-valued uncertain variables; one array entry per contiguous container. These associate the individual variables given by, e.g., DAUSVLbl, with the contiguous container in which they are stored. | |
static int | VLR_aleatory [NUM_UNC_REAL_CONT] = { 1, 0, 1, 0 } |
which uncertain real check array containers are aleatory (true = 1) | |
static int | VLI_aleatory [NUM_UNC_INT_CONT] = { 1, 0 } |
which uncertain integer check array containers are aleatory (true = 1) | |
static int | VLS_aleatory [NUM_UNC_STR_CONT] = { 1, 0 } |
which uncertain string check array containers are aleatory (true = 1) | |
static Var_check | var_mp_check_cv [] |
static Var_check | var_mp_check_dset [] |
static Var_check | var_mp_check_cau [] |
static Var_check | var_mp_check_daui [] |
static Var_check | var_mp_check_daus [] |
static Var_check | var_mp_check_daur [] |
static Var_check | var_mp_check_ceu [] |
static Var_check | var_mp_check_deui [] |
static Var_check | var_mp_check_deus [] |
static Var_check | var_mp_check_deur [] |
static Var_rcheck | var_mp_cbound [] |
This is used within check_variables_node(): Var_RealBoundIPCheck() is applied to validate bounds and initial points. | |
static Var_icheck | var_mp_drange [] |
This is used in check_variables_node(): Var_IntBoundIPCheck() is applied to validate bounds and initial points, and in make_variable_defaults(): Vgen_* is called to infer bounds. | |
static time_t | start_time |
const char * | SCI_FIELD_NAMES [] |
const int | SCI_NUMBER_OF_FIELDS = 26 |
const int | LARGE_SCALE = 100 |
a (perhaps arbitrary) definition of large scale; choose a large-scale algorithm if numVars >= LARGE_SCALE | |
const double | POW_VAL = 1.0 |
offset used text_book exponent: 1.0 is nominal, 1.4 used for B&B testing |
The primary namespace for DAKOTA.
The Dakota namespace encapsulates the core classes of the DAKOTA framework and prevents name clashes with third-party libraries from methods and packages. The C++ source files defining these core classes reside in Dakota/src as *.[ch]pp.
Work directory TODO
Doc: we will search for drivers in PATH, workdir (.), RUNDIR
Remove legacy utilities (once concepts migrated)
Allowed FOO=zorch and would set that in the environment; could allow separate env var specification; otherwise likely remove
TESTING NEEDS
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.
For a global cache, both evaluation and interface id's are used for tagging ParamResponsePair records.
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.
For a local queue, interface id's are expected to be consistent, such that evaluation id's are sufficient for tracking particular evaluations.
anonymous enum |
CommandShell & flush | ( | CommandShell & | shell | ) |
convenient shell manipulator function to "flush" the shell
global convenience function for manipulating the shell; invokes the class member flush function.
References CommandShell::flush().
Referenced by abort_handler(), ProcessHandleApplicInterface::create_evaluation_process(), TestDriverInterface::salinas(), SysCallApplicInterface::spawn_analysis_to_shell(), SysCallApplicInterface::spawn_evaluation_to_shell(), SysCallApplicInterface::spawn_input_filter_to_shell(), SysCallApplicInterface::spawn_output_filter_to_shell(), ParallelLibrary::split_communicator_dedicated_master(), and ParallelLibrary::split_communicator_peer_partition().
void register_signal_handlers | ( | ) |
Tie various signal handlers to Dakota's abort_handler function.
Global function to register signal handlers at top-level.
References abort_handler().
Referenced by main().
void mpi_debug_hold | ( | ) |
T Dakota::abort_handler_t | ( | int | code | ) |
Templatized abort_handler_t method that allows for convenient return from methods that otherwise have no sensible return from error clauses. Usage: MyType& method() { return abort_handler<MyType&>(-1); }
References abort_handler().
bool Dakota::operator!= | ( | const ActiveSet & | set1, |
const ActiveSet & | set2 | ||
) | [inline] |
inequality operator for ActiveSet
inequality operator
bool Dakota::operator== | ( | const Model & | m1, |
const Model & | m2 | ||
) | [inline] |
equality operator for Envelope is true if same letter instance
equality operator (detect same letter instance)
References Model::modelRep.
bool Dakota::operator!= | ( | const Model & | m1, |
const Model & | m2 | ||
) | [inline] |
inequality operator for Envelope is true if different letter instance
inequality operator (detect different letter instances)
References Model::modelRep.
bool Dakota::operator!= | ( | const Response & | resp1, |
const Response & | resp2 | ||
) | [inline] |
inequality operator for Response
inequality operator
bool Dakota::operator!= | ( | const Variables & | vars1, |
const Variables & | vars2 | ||
) | [inline] |
inequality operator for Variables
strict inequality operator
void Dakota::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 | ||
) | [inline] |
free function to write Variables data vectors in input spec ordering
written for arbitrary types, but typical use will be ScalarType1 = Real, ScalarType2 = int, ScalarType3 = string, and ScalarType4 = int or Real.
Referenced by ParamStudy::pre_run().
void Dakota::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 | ||
) | [inline] |
free function to write Variables data vectors in input spec ordering
written for arbitrary types, but typical use will be ScalarType1 = Real, ScalarType2 = int, ScalarType3 = string, and ScalarType4 = int or Real.
void symmetric_eigenvalue_decomposition | ( | const RealSymMatrix & | matrix, |
RealVector & | eigenvalues, | ||
RealMatrix & | eigenvectors | ||
) |
Computes the eigenvalues and, optionally, eigenvectors of a real symmetric matrix A.
Eigenvalues are returned in ascending order.
References symmetric_eigenvalue_decomposition().
Referenced by get_positive_definite_covariance_from_hessian(), and symmetric_eigenvalue_decomposition().
Real Dakota::getdist | ( | const RealVector & | x1, |
const RealVector & | x2 | ||
) |
Gets the Euclidean distance between x1 and x2
Referenced by mindist(), and mindistindx().
Real Dakota::mindist | ( | const RealVector & | x, |
const RealMatrix & | xset, | ||
int | except | ||
) |
Real Dakota::mindistindx | ( | const RealVector & | x, |
const RealMatrix & | xset, | ||
const IntArray & | indx | ||
) |
Gets the min distance between x and points in the set xset defined by the nindx values in indx.
References getdist().
Referenced by GaussProcApproximation::pointsel_add_sel().
Real Dakota::getRmax | ( | const RealMatrix & | xset | ) |
Gets the maximum of the min distance between each point and the rest of the set.
References mindist().
Referenced by GaussProcApproximation::pointsel_add_sel().
int Dakota::start_grid_computing | ( | char * | analysis_driver_script, |
char * | params_file, | ||
char * | results_file | ||
) |
sample function prototype for launching grid computing
int Dakota::stop_grid_computing | ( | ) |
sample function prototype for terminating grid computing
int Dakota::perform_analysis | ( | char * | iteration_num | ) |
sample function prototype for submitting a grid evaluation
string Dakota::asstring | ( | const T & | val | ) |
Creates a string from the argument val using an ostringstream.
This only gets used in this file and is only ever called with ints so no error checking is in place.
val | The value of type T to convert to a string. |
Referenced by JEGAOptimizer::LoadTheConstraints().
void start_dakota_heartbeat | ( | int | seconds | ) |
Heartbeat function provided by dakota_filesystem_utils; pass output interval in seconds, or -1 to use $DAKOTA_HEARTBEAT
Referenced by OutputManager::OutputManager().
bool Dakota::operator== | ( | const ParamResponsePair & | pair1, |
const ParamResponsePair & | pair2 | ||
) | [inline] |
equality operator for ParamResponsePair
equality operator
References ParamResponsePair::evalInterfaceIds, ParamResponsePair::prpResponse, and ParamResponsePair::prpVariables.
bool Dakota::operator!= | ( | const ParamResponsePair & | pair1, |
const ParamResponsePair & | pair2 | ||
) | [inline] |
inequality operator for ParamResponsePair
inequality operator
bool Dakota::set_compare | ( | const ParamResponsePair & | database_pr, |
const ActiveSet & | search_set | ||
) | [inline] |
search function for a particular ParamResponsePair within a PRPList based on ActiveSet content (request vector and derivative variables vector)
a global function to compare the ActiveSet of a particular database_pr (presumed to be in the global history list) with a passed in ActiveSet (search_set).
References ParamResponsePair::active_set(), ActiveSet::derivative_vector(), and ActiveSet::request_vector().
Referenced by lookup_by_val().
bool Dakota::id_vars_exact_compare | ( | const ParamResponsePair & | database_pr, |
const ParamResponsePair & | search_pr | ||
) | [inline] |
search function for a particular ParamResponsePair within a PRPMultiIndex
a global function to compare the interface id and variables of a particular database_pr (presumed to be in the global history list) with a passed in key of interface id and variables provided by search_pr.
References ParamResponsePair::interface_id(), and ParamResponsePair::variables().
Referenced by partial_prp_equality::operator()().
PRPCacheHIter Dakota::lookup_by_val | ( | PRPMultiIndexCache & | prp_cache, |
const ParamResponsePair & | search_pr | ||
) | [inline] |
find a ParamResponsePair based on the interface id, variables, and ActiveSet search data within search_pr.
Lookup occurs in two steps: (1) PRPMultiIndexCache lookup based on strict equality in interface id and variables, and (2) set_compare() post-processing based on ActiveSet subset logic.
References ParamResponsePair::active_set(), and set_compare().
Referenced by Model::db_lookup(), ApplicationInterface::duplication_detect(), SurrBasedLocalMinimizer::find_center_approx(), Minimizer::local_recast_retrieve(), lookup_by_val(), SNLLLeastSq::post_run(), SurrBasedMinimizer::print_results(), LeastSq::print_results(), Optimizer::print_results(), DiscrepancyCorrection::search_db(), and NonDLocalReliability::update_mpp_search_data().
PRPQueueHIter Dakota::lookup_by_val | ( | PRPMultiIndexQueue & | prp_queue, |
const ParamResponsePair & | search_pr | ||
) | [inline] |
find a ParamResponsePair based on the interface id, variables, and ActiveSet search data within search_pr.
Lookup occurs in two steps: (1) PRPMultiIndexQueue lookup based on strict equality in interface id and variables, and (2) set_compare() post-processing based on ActiveSet subset logic.
References ParamResponsePair::active_set(), and set_compare().
void print_restart | ( | StringArray | pos_args, |
String | print_dest | ||
) |
print a restart file
Usage: "dakota_restart_util print dakota.rst"
"dakota_restart_util to_neutral dakota.rst dakota.neu"
Prints all evals. in full precision to either stdout or a neutral file. The former is useful for ensuring that duplicate detection is successful in a restarted run (e.g., starting a new method from the previous best), and the latter is used for translating binary files between platforms.
References abort_handler(), ParamResponsePair::eval_id(), ParamResponsePair::write_annotated(), and write_precision.
Referenced by main().
void print_restart_pdb | ( | StringArray | pos_args, |
String | print_dest | ||
) |
print a restart file (PDB format)
Usage: "dakota_restart_util to_pdb dakota.rst dakota.pdb"
Unrolls all data associated with a particular tag for all evaluations and then writes this data in a tabular format (e.g., to a PDB database or MATLAB/TECPLOT data file).
References abort_handler(), Variables::continuous_variables(), Variables::discrete_int_variables(), Variables::discrete_real_variables(), and Response::function_values().
Referenced by main().
void print_restart_tabular | ( | StringArray | pos_args, |
String | print_dest, | ||
unsigned short | tabular_format | ||
) |
print a restart file (tabular format)
Usage: "dakota_restart_util to_tabular dakota.rst dakota.txt"
Unrolls all data associated with a particular tag for all evaluations and then writes this data in a tabular format (e.g., to a PDB database or MATLAB/TECPLOT data file).
References abort_handler(), Variables::acv(), Variables::adiv(), Variables::adrv(), Variables::adsv(), Variables::all_continuous_variable_labels(), Variables::all_discrete_int_variable_labels(), Variables::all_discrete_real_variable_labels(), Variables::all_discrete_string_variable_labels(), Response::function_labels(), ParamResponsePair::interface_id(), ParamResponsePair::response(), ParamResponsePair::variables(), ParamResponsePair::write_tabular(), and ParamResponsePair::write_tabular_labels().
Referenced by main().
void read_neutral | ( | StringArray | pos_args | ) |
read a restart file (neutral file format)
Usage: "dakota_restart_util from_neutral dakota.neu dakota.rst"
Reads evaluations from a neutral file. This is used for translating binary files between platforms.
References abort_handler(), and ParamResponsePair::read_annotated().
Referenced by main().
void repair_restart | ( | StringArray | pos_args, |
String | identifier_type | ||
) |
repair a restart file by removing corrupted evaluations
Usage: "dakota_restart_util remove 0.0 dakota_old.rst dakota_new.rst"
"dakota_restart_util remove_ids 2 7 13 dakota_old.rst
dakota_new.rst"
Repairs a restart file by removing corrupted evaluations. The identifier for evaluation removal can be either a double precision number (all evaluations having a matching response function value are removed) or a list of integers (all evaluations with matching evaluation ids are removed).
References abort_handler(), Response::active_set_request_vector(), contains(), ParamResponsePair::eval_id(), Response::function_values(), and ParamResponsePair::response().
Referenced by main().
void concatenate_restart | ( | StringArray | pos_args | ) |
concatenate multiple restart files
Usage: "dakota_restart_util cat dakota_1.rst ... dakota_n.rst dakota_new.rst"
Combines multiple restart files into a single restart database.
References abort_handler().
Referenced by main().
std::vector<std::string> Dakota::get_pathext | ( | ) |
Utility function for executable file search algorithms
Referenced by WorkdirHelper::which().
bool Dakota::contains | ( | const bfs::path & | dir_path, |
const std::string & | file_name, | ||
boost::filesystem::path & | complete_filepath | ||
) | [inline] |
Utility function for "which" sets complete_filepath from dir_path/file_name combo
short abort_mode = ABORT_EXITS |
by default Dakota exits or calls MPI_Abort on errors
whether dakota exits/aborts or throws on errors
Referenced by abort_throw_or_exit(), Environment::exit_mode(), and PythonInterface::python_run().
Dakota_funcs DakFuncs0 |
{ fprintf, abort_handler, dlsolver_option, continuous_lower_bounds1, continuous_upper_bounds1, nonlinear_ineq_constraint_lower_bounds1, nonlinear_ineq_constraint_upper_bounds1, nonlinear_eq_constraint_targets1, linear_ineq_constraint_lower_bounds1, linear_ineq_constraint_upper_bounds1, linear_eq_constraint_targets1, linear_ineq_constraint_coeffs1, linear_eq_constraint_coeffs1, ComputeResponses1, GetFuncs1, GetGrads1, GetContVars1, SetBestContVars1, SetBestDiscVars1, SetBestRespFns1, Get_Real1, Get_Int1, Get_Bool1 }
const char* FIELD_NAMES[] |
{ "numFns", "numVars", "numACV", "numADIV", "numADRV", "numDerivVars", "xC", "xDI", "xDR", "xCLabels", "xDILabels", "xDRLabels", "directFnASV", "directFnDVV", "fnFlag", "gradFlag", "hessFlag", "fnVals", "fnGrads", "fnHessians", "fnLabels", "failure", "currEvalId" }
fields to pass to Matlab in Dakota structure
Referenced by MatlabInterface::matlab_engine_run(), and MatlabInterface::MatlabInterface().
const int NUMBER_OF_FIELDS = 23 |
number of fields in above structure
Referenced by MatlabInterface::matlab_engine_run(), and MatlabInterface::MatlabInterface().
static KeyWord kw_1 [static] |
{ {"eval_id",8,0,2,0,49}, {"header",8,0,1,0,47}, {"interface_id",8,0,3,0,51} }
1480 distinct keywords (plus 205 aliases)
static KeyWord kw_2 [static] |
{ {"annotated",8,0,1,0,43}, {"custom_annotated",8,3,1,0,45,kw_1}, {"freeform",8,0,1,0,53} }
static KeyWord kw_3 [static] |
{ {"input",11,3,1,0,41,kw_2}, {"output",11,0,2,0,55} }
static KeyWord kw_4 [static] |
{ {"eval_id",8,0,2,0,27}, {"header",8,0,1,0,25}, {"interface_id",8,0,3,0,29} }
static KeyWord kw_5 [static] |
{ {"annotated",8,0,1,0,21}, {"custom_annotated",8,3,1,0,23,kw_4}, {"freeform",8,0,1,0,31} }
static KeyWord kw_6 [static] |
{ {"input",11,0,1,0,17}, {"output",11,3,2,0,19,kw_5} }
static KeyWord kw_7 [static] |
{
{"stop_restart",0x29,0,1,0,11}
}
static KeyWord kw_8 [static] |
{ {"results_output_file",11,0,1,0,79,0,0.,0.,0.,0,"{File name for results output} EnvCommands.html#EnvOutput"} }
static KeyWord kw_9 [static] |
{ {"input",11,0,1,0,35}, {"output",11,0,2,0,37} }
static KeyWord kw_10 [static] |
{ {"eval_id",8,0,2,0,69}, {"header",8,0,1,0,67}, {"interface_id",8,0,3,0,71} }
static KeyWord kw_11 [static] |
{ {"annotated",8,0,2,0,63}, {"custom_annotated",8,3,2,0,65,kw_10}, {"freeform",8,0,2,0,73}, {"tabular_data_file",11,0,1,0,61}, {"tabular_graphics_file",3,0,1,0,60} }
static KeyWord kw_12 [static] |
{ {"check",8,0,1,0,3}, {"error_file",11,0,3,0,7}, {"graphics",8,0,9,0,57,0,0.,0.,0.,0,"{Graphics flag} EnvCommands.html#EnvOutput"}, {"method_pointer",3,0,13,0,80}, {"output_file",11,0,2,0,5}, {"output_precision",0x29,0,11,0,75,0,0.,0.,0.,0,"{Numeric output precision} EnvCommands.html#EnvOutput"}, {"post_run",8,2,8,0,39,kw_3}, {"pre_run",8,2,6,0,15,kw_6}, {"read_restart",11,1,4,0,9,kw_7}, {"results_output",8,1,12,0,77,kw_8,0.,0.,0.,0,"{Enable results output} EnvCommands.html#EnvOutput"}, {"run",8,2,7,0,33,kw_9}, {"tabular_data",8,5,10,0,59,kw_11}, {"tabular_graphics_data",0,5,10,0,58,kw_11}, {"top_method_pointer",11,0,13,0,81,0,0.,0.,0.,0,"{Method pointer} EnvCommands.html#EnvMethPtr"}, {"write_restart",11,0,5,0,13} }
static KeyWord kw_13 [static] |
{
{"cache_tolerance",10,0,1,0,2697}
}
static KeyWord kw_14 [static] |
{ {"active_set_vector",8,0,1,0,2691}, {"evaluation_cache",8,0,2,0,2693}, {"restart_file",8,0,4,0,2699}, {"strict_cache_equality",8,1,3,0,2695,kw_13} }
static KeyWord kw_15 [static] |
{ {"processors_per_analysis",0x19,0,1,0,2667,0,0.,0.,0.,0,"{Number of processors per analysis server} InterfCommands.html#InterfApplicDF"} }
static KeyWord kw_16 [static] |
{ {"abort",8,0,1,1,2681,0,0.,0.,0.,0,"@[CHOOSE failure mitigation]"}, {"continuation",8,0,1,1,2687}, {"recover",14,0,1,1,2685}, {"retry",9,0,1,1,2683} }
static KeyWord kw_17 [static] |
{ {"numpy",8,0,1,0,2673,0,0.,0.,0.,0,"{Python NumPy dataflow} InterfCommands.html#InterfApplicMSP"} }
static KeyWord kw_18 [static] |
{ {"copy_files",15,0,5,0,2661,0,0.,0.,0.,0,"{copy files} InterfCommands.html#InterfApplicF"}, {"dir_save",0,0,3,0,2656}, {"dir_tag",0,0,2,0,2654}, {"directory_save",8,0,3,0,2657,0,0.,0.,0.,0,"{Save work directory} InterfCommands.html#InterfApplicF"}, {"directory_tag",8,0,2,0,2655,0,0.,0.,0.,0,"{Tag work directory} InterfCommands.html#InterfApplicF"}, {"link_files",15,0,4,0,2659,0,0.,0.,0.,0,"{link files} InterfCommands.html#InterfApplicF"}, {"named",11,0,1,0,2653,0,0.,0.,0.,0,"{Name of work directory} InterfCommands.html#InterfApplicF"}, {"replace",8,0,6,0,2663} }
static KeyWord kw_19 [static] |
{ {"allow_existing_results",8,0,3,0,2641,0,0.,0.,0.,0,"{Allow existing results files} InterfCommands.html#InterfApplicF"}, {"aprepro",8,0,5,0,2645,0,0.,0.,0.,0,"{Aprepro parameters file format} InterfCommands.html#InterfApplicF"}, {"dprepro",0,0,5,0,2644}, {"file_save",8,0,7,0,2649,0,0.,0.,0.,0,"{Parameters and results file saving} InterfCommands.html#InterfApplicF"}, {"file_tag",8,0,6,0,2647,0,0.,0.,0.,0,"{Parameters and results file tagging} InterfCommands.html#InterfApplicF"}, {"parameters_file",11,0,1,0,2637,0,0.,0.,0.,0,"{Parameters file name} InterfCommands.html#InterfApplicF"}, {"results_file",11,0,2,0,2639,0,0.,0.,0.,0,"{Results file name} InterfCommands.html#InterfApplicF"}, {"verbatim",8,0,4,0,2643,0,0.,0.,0.,0,"{Verbatim driver/filter invocation syntax} InterfCommands.html#InterfApplicF"}, {"work_directory",8,8,8,0,2651,kw_18,0.,0.,0.,0,"{Create work directory} InterfCommands.html#InterfApplicF"} }
static KeyWord kw_20 [static] |
{ {"analysis_components",15,0,1,0,2627,0,0.,0.,0.,0,"{Additional identifiers for use by the analysis_drivers} InterfCommands.html#InterfApplic"}, {"deactivate",8,4,6,0,2689,kw_14,0.,0.,0.,0,"{Feature deactivation} InterfCommands.html#InterfApplic"}, {"direct",8,1,4,1,2665,kw_15,0.,0.,0.,0,"[CHOOSE interface type]{Direct function interface } InterfCommands.html#InterfApplicDF"}, {"failure_capture",8,4,5,0,2679,kw_16,0.,0.,0.,0,"{Failure capturing} InterfCommands.html#InterfApplic"}, {"fork",8,9,4,1,2635,kw_19,0.,0.,0.,0,"@{Fork interface } InterfCommands.html#InterfApplicF"}, {"grid",8,0,4,1,2677,0,0.,0.,0.,0,"{Grid interface } InterfCommands.html#InterfApplicG"}, {"input_filter",11,0,2,0,2629,0,0.,0.,0.,0,"{Input filter} InterfCommands.html#InterfApplic"}, {"matlab",8,0,4,1,2669,0,0.,0.,0.,0,"{Matlab interface } InterfCommands.html#InterfApplicMSP"}, {"output_filter",11,0,3,0,2631,0,0.,0.,0.,0,"{Output filter} InterfCommands.html#InterfApplic"}, {"python",8,1,4,1,2671,kw_17,0.,0.,0.,0,"{Python interface } InterfCommands.html#InterfApplicMSP"}, {"scilab",8,0,4,1,2675,0,0.,0.,0.,0,"{Scilab interface } InterfCommands.html#InterfApplicMSP"}, {"system",8,9,4,1,2633,kw_19} }
static KeyWord kw_21 [static] |
{ {"master",8,0,1,1,2731}, {"peer",8,0,1,1,2733} }
static KeyWord kw_22 [static] |
{ {"dynamic",8,0,1,1,2707}, {"static",8,0,1,1,2709} }
static KeyWord kw_23 [static] |
{ {"analysis_concurrency",0x19,0,3,0,2711,0,0.,0.,0.,0,"{Asynchronous analysis concurrency} InterfCommands.html#InterfIndControl"}, {"evaluation_concurrency",0x19,0,1,0,2703,0,0.,0.,0.,0,"{Asynchronous evaluation concurrency} InterfCommands.html#InterfIndControl"}, {"local_evaluation_scheduling",8,2,2,0,2705,kw_22,0.,0.,0.,0,"{Local evaluation scheduling} InterfCommands.html#InterfIndControl"} }
static KeyWord kw_24 [static] |
{ {"dynamic",8,0,1,1,2721}, {"static",8,0,1,1,2723} }
static KeyWord kw_25 [static] |
{ {"master",8,0,1,1,2717}, {"peer",8,2,1,1,2719,kw_24,0.,0.,0.,0,"{Peer scheduling of evaluations} InterfCommands.html#InterfIndControl"} }
static KeyWord kw_26 [static] |
{ {"algebraic_mappings",11,0,2,0,2623,0,0.,0.,0.,0,"{Algebraic mappings file} InterfCommands.html#InterfAlgebraic"}, {"analysis_drivers",15,12,3,0,2625,kw_20,0.,0.,0.,0,"{Analysis drivers} InterfCommands.html#InterfApplic"}, {"analysis_scheduling",8,2,9,0,2729,kw_21,0.,0.,0.,0,"{Message passing configuration for scheduling of analyses} InterfCommands.html#InterfIndControl"}, {"analysis_servers",0x19,0,8,0,2727,0,0.,0.,0.,0,"{Number of analysis servers} InterfCommands.html#InterfIndControl"}, {"asynchronous",8,3,4,0,2701,kw_23,0.,0.,0.,0,"{Asynchronous interface usage} InterfCommands.html#InterfIndControl"}, {"evaluation_scheduling",8,2,6,0,2715,kw_25,0.,0.,0.,0,"{Message passing configuration for scheduling of evaluations} InterfCommands.html#InterfIndControl"}, {"evaluation_servers",0x19,0,5,0,2713,0,0.,0.,0.,0,"{Number of evaluation servers} InterfCommands.html#InterfIndControl"}, {"id_interface",11,0,1,0,2621,0,0.,0.,0.,0,"{Interface set identifier} InterfCommands.html#InterfIndControl"}, {"processors_per_evaluation",0x19,0,7,0,2725,0,0.,0.,0.,0,"{Number of processors per evaluation server} InterfCommands.html#InterfIndControl"} }
static KeyWord kw_27 [static] |
{ {"complementary",8,0,1,1,1311}, {"cumulative",8,0,1,1,1309} }
static KeyWord kw_28 [static] |
{ {"num_gen_reliability_levels",13,0,1,0,1319,0,0.,0.,0.,0,"{Number of generalized reliability levels} MethodCommands.html#MethodNonD"} }
static KeyWord kw_29 [static] |
{ {"num_probability_levels",13,0,1,0,1315,0,0.,0.,0.,0,"{Number of probability levels} MethodCommands.html#MethodNonD"} }
static KeyWord kw_30 [static] |
{ {"mt19937",8,0,1,1,1323}, {"rnum2",8,0,1,1,1325} }
static KeyWord kw_31 [static] |
{ {"constant_liar",8,0,1,1,1159}, {"distance_penalty",8,0,1,1,1155}, {"naive",8,0,1,1,1153}, {"topology",8,0,1,1,1157} }
static KeyWord kw_32 [static] |
{ {"eval_id",8,0,2,0,1187}, {"header",8,0,1,0,1185}, {"interface_id",8,0,3,0,1189} }
static KeyWord kw_33 [static] |
{ {"annotated",8,0,1,0,1181}, {"custom_annotated",8,3,1,0,1183,kw_32}, {"freeform",8,0,1,0,1191} }
static KeyWord kw_34 [static] |
{ {"distance",8,0,1,1,1147}, {"gradient",8,0,1,1,1149}, {"predicted_variance",8,0,1,1,1145} }
static KeyWord kw_35 [static] |
{ {"eval_id",8,0,2,0,1171}, {"header",8,0,1,0,1169}, {"interface_id",8,0,3,0,1173} }
static KeyWord kw_36 [static] |
{ {"active_only",8,0,2,0,1177}, {"annotated",8,0,1,0,1165}, {"custom_annotated",8,3,1,0,1167,kw_35}, {"freeform",8,0,1,0,1175} }
static KeyWord kw_37 [static] |
{ {"parallel",8,0,1,1,1207}, {"series",8,0,1,1,1205} }
static KeyWord kw_38 [static] |
{ {"gen_reliabilities",8,0,1,1,1201}, {"probabilities",8,0,1,1,1199}, {"system",8,2,2,0,1203,kw_37} }
static KeyWord kw_39 [static] |
{ {"compute",8,3,2,0,1197,kw_38}, {"num_response_levels",13,0,1,0,1195} }
static KeyWord kw_40 [static] |
{ {"batch_selection",8,4,3,0,1151,kw_31,0.,0.,0.,0,"{Batch selection strategy} MethodCommands.html#MethodNonDAdaptive"}, {"batch_size",9,0,4,0,1161,0,0.,0.,0.,0,"{Batch size (number of points added each iteration)} MethodCommands.html#MethodNonDAdaptive"}, {"distribution",8,2,12,0,1307,kw_27,0.,0.,0.,0,"{Distribution type} MethodCommands.html#MethodNonD"}, {"emulator_samples",9,0,1,0,1141,0,0.,0.,0.,0,"{Number of samples on the emulator to generate a new true sample each iteration} MethodCommands.html#MethodNonDAdaptive"}, {"export_points_file",11,3,6,0,1179,kw_33,0.,0.,0.,0,"{File name for exporting approximation-based samples from evaluating the GP} MethodCommands.html#MethodNonDAdaptive"}, {"fitness_metric",8,3,2,0,1143,kw_34,0.,0.,0.,0,"{Fitness metric} MethodCommands.html#MethodNonDAdaptive"}, {"gen_reliability_levels",14,1,14,0,1317,kw_28,0.,0.,0.,0,"{Generalized reliability levels} MethodCommands.html#MethodNonD"}, {"import_points_file",11,4,5,0,1163,kw_36,0.,0.,0.,0,"{File name for points to be imported as the basis for the initial GP} MethodCommands.html#MethodNonDAdaptive"}, {"misc_options",15,0,8,0,1209}, {"model_pointer",11,0,9,0,1905}, {"probability_levels",14,1,13,0,1313,kw_29,0.,0.,0.,0,"{Probability levels} MethodCommands.html#MethodNonD"}, {"response_levels",14,2,7,0,1193,kw_39}, {"rng",8,2,15,0,1321,kw_30,0.,0.,0.,0,"{Random number generator} MethodCommands.html#MethodNonDMC"}, {"samples",9,0,10,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,11,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"} }
static KeyWord kw_41 [static] |
{ {"merit1",8,0,1,1,371,0,0.,0.,0.,0,"[CHOOSE merit function]"}, {"merit1_smooth",8,0,1,1,373}, {"merit2",8,0,1,1,375}, {"merit2_smooth",8,0,1,1,377,0,0.,0.,0.,0,"@"}, {"merit2_squared",8,0,1,1,379}, {"merit_max",8,0,1,1,367}, {"merit_max_smooth",8,0,1,1,369} }
static KeyWord kw_42 [static] |
{ {"blocking",8,0,1,1,361,0,0.,0.,0.,0,"[CHOOSE synchronization]"}, {"nonblocking",8,0,1,1,363,0,0.,0.,0.,0,"@"} }
static KeyWord kw_43 [static] |
{ {"constraint_penalty",10,0,7,0,381,0,0.,0.,0.,0,"{Constraint penalty} MethodCommands.html#MethodAPPSDC"}, {"contraction_factor",10,0,2,0,353,0,0.,0.,0.,0,"{Pattern contraction factor} MethodCommands.html#MethodAPPSDC"}, {"initial_delta",10,0,1,0,351,0,0.,0.,0.,0,"{Initial offset value} MethodCommands.html#MethodAPPSDC"}, {"linear_equality_constraint_matrix",14,0,15,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,17,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,18,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,16,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,10,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,11,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,13,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,14,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,12,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"merit_function",8,7,6,0,365,kw_41,0.,0.,0.,0,"{Merit function} MethodCommands.html#MethodAPPSDC"}, {"model_pointer",11,0,9,0,1905}, {"smoothing_factor",10,0,8,0,383,0,0.,0.,0.,0,"{Smoothing factor} MethodCommands.html#MethodAPPSDC"}, {"solution_accuracy",2,0,4,0,356}, {"solution_target",10,0,4,0,357,0,0.,0.,0.,0,"{Solution target} MethodCommands.html#MethodAPPSDC"}, {"synchronization",8,2,5,0,359,kw_42,0.,0.,0.,0,"{Evaluation synchronization} MethodCommands.html#MethodAPPSDC"}, {"threshold_delta",10,0,3,0,355,0,0.,0.,0.,0,"{Threshold for offset values} MethodCommands.html#MethodAPPSDC"} }
static KeyWord kw_44 [static] |
{ {"eval_id",8,0,2,0,1563}, {"header",8,0,1,0,1561}, {"interface_id",8,0,3,0,1565} }
static KeyWord kw_45 [static] |
{ {"annotated",8,0,1,0,1557}, {"custom_annotated",8,3,1,0,1559,kw_44}, {"freeform",8,0,1,0,1567} }
static KeyWord kw_46 [static] |
{ {"eval_id",8,0,2,0,1547}, {"header",8,0,1,0,1545}, {"interface_id",8,0,3,0,1549} }
static KeyWord kw_47 [static] |
{ {"active_only",8,0,2,0,1553}, {"annotated",8,0,1,0,1541}, {"custom_annotated",8,3,1,0,1543,kw_46}, {"freeform",8,0,1,0,1551} }
static KeyWord kw_48 [static] |
{ {"dakota",8,0,1,1,1533}, {"emulator_samples",9,0,2,0,1535}, {"export_points_file",11,3,5,0,1555,kw_45}, {"import_points_file",11,4,4,0,1539,kw_47}, {"posterior_adaptive",8,0,3,0,1537}, {"surfpack",8,0,1,1,1531} }
static KeyWord kw_49 [static] |
{ {"collocation_ratio",10,0,1,1,1575}, {"posterior_adaptive",8,0,2,0,1577} }
static KeyWord kw_50 [static] |
{ {"expansion_order",13,2,1,1,1573,kw_49}, {"sparse_grid_level",13,0,1,1,1571} }
static KeyWord kw_51 [static] |
{
{"sparse_grid_level",13,0,1,1,1581}
}
static KeyWord kw_52 [static] |
{ {"gaussian_process",8,6,1,1,1529,kw_48}, {"kriging",0,6,1,1,1528,kw_48}, {"pce",8,2,1,1,1569,kw_50}, {"sc",8,1,1,1,1579,kw_51}, {"use_derivatives",8,0,2,0,1583} }
static KeyWord kw_53 [static] |
{ {"chains",0x29,0,1,0,1517,0,3.,0.,0.,0,"{Number of chains} MethodCommands.html#MethodNonDBayesCalib"}, {"crossover_chain_pairs",0x29,0,3,0,1521,0,0.,0.,0.,0,"{Number of chain pairs used in crossover } MethodCommands.html#MethodNonDBayesCalib"}, {"emulator",8,5,6,0,1527,kw_52}, {"gr_threshold",0x1a,0,4,0,1523,0,0.,0.,0.,0,"{Gelman-Rubin Threshold for convergence} MethodCommands.html#MethodNonDBayesCalib"}, {"jump_step",0x29,0,5,0,1525,0,0.,0.,0.,0,"{Jump-Step } MethodCommands.html#MethodNonDBayesCalib"}, {"num_cr",0x29,0,2,0,1519,0,1.,0.,0.,0,"{Number of candidate points used in burn-in adaptation} MethodCommands.html#MethodNonDBayesCalib"} }
static KeyWord kw_54 [static] |
{
{"proposal_updates",9,0,1,0,1499}
}
static KeyWord kw_55 [static] |
{ {"diagonal",8,0,1,1,1511}, {"matrix",8,0,1,1,1513} }
static KeyWord kw_56 [static] |
{ {"diagonal",8,0,1,1,1505}, {"matrix",8,0,1,1,1507} }
static KeyWord kw_57 [static] |
{ {"derivatives",8,1,1,1,1497,kw_54}, {"filename",11,2,1,1,1509,kw_55}, {"prior",8,0,1,1,1501}, {"values",14,2,1,1,1503,kw_56} }
static KeyWord kw_58 [static] |
{ {"mt19937",8,0,1,1,1491}, {"rnum2",8,0,1,1,1493} }
static KeyWord kw_59 [static] |
{ {"eval_id",8,0,2,0,1473}, {"header",8,0,1,0,1471}, {"interface_id",8,0,3,0,1475} }
static KeyWord kw_60 [static] |
{ {"annotated",8,0,1,0,1467}, {"custom_annotated",8,3,1,0,1469,kw_59}, {"freeform",8,0,1,0,1477} }
static KeyWord kw_61 [static] |
{ {"eval_id",8,0,2,0,1457}, {"header",8,0,1,0,1455}, {"interface_id",8,0,3,0,1459} }
static KeyWord kw_62 [static] |
{ {"active_only",8,0,2,0,1463}, {"annotated",8,0,1,0,1451}, {"custom_annotated",8,3,1,0,1453,kw_61}, {"freeform",8,0,1,0,1461} }
static KeyWord kw_63 [static] |
{ {"adaptive_metropolis",8,0,4,0,1483}, {"delayed_rejection",8,0,4,0,1481}, {"dram",8,0,4,0,1479}, {"emulator_samples",9,0,1,1,1447}, {"export_points_file",11,3,3,0,1465,kw_60}, {"import_points_file",11,4,2,0,1449,kw_62}, {"metropolis_hastings",8,0,4,0,1485}, {"multilevel",8,0,4,0,1487}, {"proposal_covariance",8,4,6,0,1495,kw_57}, {"rng",8,2,5,0,1489,kw_58,0.,0.,0.,0,"{Random seed generator} MethodCommands.html#MethodNonDBayesCalib"} }
static KeyWord kw_64 [static] |
{ {"eval_id",8,0,2,0,1421}, {"header",8,0,1,0,1419}, {"interface_id",8,0,3,0,1423} }
static KeyWord kw_65 [static] |
{ {"annotated",8,0,1,0,1415}, {"custom_annotated",8,3,1,0,1417,kw_64}, {"freeform",8,0,1,0,1425} }
static KeyWord kw_66 [static] |
{ {"eval_id",8,0,2,0,1405}, {"header",8,0,1,0,1403}, {"interface_id",8,0,3,0,1407} }
static KeyWord kw_67 [static] |
{ {"active_only",8,0,2,0,1411}, {"annotated",8,0,1,0,1399}, {"custom_annotated",8,3,1,0,1401,kw_66}, {"freeform",8,0,1,0,1409} }
static KeyWord kw_68 [static] |
{ {"dakota",8,0,1,1,1391}, {"emulator_samples",9,0,2,0,1393}, {"export_points_file",11,3,5,0,1413,kw_65}, {"import_points_file",11,4,4,0,1397,kw_67}, {"posterior_adaptive",8,0,3,0,1395}, {"surfpack",8,0,1,1,1389} }
static KeyWord kw_69 [static] |
{ {"collocation_ratio",10,0,1,1,1433}, {"posterior_adaptive",8,0,2,0,1435} }
static KeyWord kw_70 [static] |
{ {"expansion_order",13,2,1,1,1431,kw_69}, {"sparse_grid_level",13,0,1,1,1429} }
static KeyWord kw_71 [static] |
{
{"sparse_grid_level",13,0,1,1,1439}
}
static KeyWord kw_72 [static] |
{ {"gaussian_process",8,6,1,1,1387,kw_68}, {"kriging",0,6,1,1,1386,kw_68}, {"pce",8,2,1,1,1427,kw_70}, {"sc",8,1,1,1,1437,kw_71}, {"use_derivatives",8,0,2,0,1441} }
static KeyWord kw_73 [static] |
{ {"adaptive_metropolis",8,0,3,0,1483}, {"delayed_rejection",8,0,3,0,1481}, {"dram",8,0,3,0,1479}, {"emulator",8,5,1,0,1385,kw_72}, {"logit_transform",8,0,2,0,1443}, {"metropolis_hastings",8,0,3,0,1485}, {"multilevel",8,0,3,0,1487}, {"proposal_covariance",8,4,5,0,1495,kw_57}, {"rng",8,2,4,0,1489,kw_58,0.,0.,0.,0,"{Random seed generator} MethodCommands.html#MethodNonDBayesCalib"} }
static KeyWord kw_74 [static] |
{ {"calibrate_sigma",8,0,4,0,1589,0,0.,0.,0.,0,"{Calibrate sigma flag} MethodCommands.html#MethodNonDBayesCalib"}, {"dream",8,6,1,1,1515,kw_53}, {"gpmsa",8,10,1,1,1445,kw_63}, {"likelihood_scale",10,0,3,0,1587,0,0.,0.,0.,0,"{Likelihood scale factor} MethodCommands.html#MethodNonDBayesCalib"}, {"model_pointer",11,0,5,0,1905}, {"queso",8,9,1,1,1383,kw_73}, {"samples",9,0,6,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,7,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"}, {"standardized_space",8,0,2,0,1585} }
static KeyWord kw_75 [static] |
{ {"deltas_per_variable",5,0,2,2,1888}, {"model_pointer",11,0,3,0,1905}, {"step_vector",14,0,1,1,1887,0,0.,0.,0.,0,"{Step vector} MethodCommands.html#MethodPSCPS"}, {"steps_per_variable",13,0,2,2,1889,0,0.,0.,0.,0,"{Number of steps per variable} MethodCommands.html#MethodPSCPS"} }
static KeyWord kw_76 [static] |
{ {"beta_solver_name",11,0,1,1,671}, {"misc_options",15,0,6,0,679,0,0.,0.,0.,0,"{Specify miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"model_pointer",11,0,2,0,1905}, {"seed",0x19,0,4,0,675,0,0.,0.,0.,0,"{Random seed for stochastic pattern search} MethodCommands.html#MethodSCOLIBPS"}, {"show_misc_options",8,0,5,0,677,0,0.,0.,0.,0,"{Show miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"solution_accuracy",2,0,3,0,672}, {"solution_target",10,0,3,0,673,0,0.,0.,0.,0,"{Desired solution target} MethodCommands.html#MethodSCOLIBDC"} }
static KeyWord kw_77 [static] |
{ {"initial_delta",10,0,6,0,589,0,0.,0.,0.,0,"{Initial offset value} MethodCommands.html#MethodSCOLIBPS"}, {"misc_options",15,0,5,0,679,0,0.,0.,0.,0,"{Specify miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"model_pointer",11,0,1,0,1905}, {"seed",0x19,0,3,0,675,0,0.,0.,0.,0,"{Random seed for stochastic pattern search} MethodCommands.html#MethodSCOLIBPS"}, {"show_misc_options",8,0,4,0,677,0,0.,0.,0.,0,"{Show miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"solution_accuracy",2,0,2,0,672}, {"solution_target",10,0,2,0,673,0,0.,0.,0.,0,"{Desired solution target} MethodCommands.html#MethodSCOLIBDC"}, {"threshold_delta",10,0,7,0,591,0,0.,0.,0.,0,"{Threshold for offset values} MethodCommands.html#MethodSCOLIBPS"} }
static KeyWord kw_78 [static] |
{ {"all_dimensions",8,0,1,1,599}, {"major_dimension",8,0,1,1,597} }
static KeyWord kw_79 [static] |
{ {"constraint_penalty",10,0,6,0,609,0,0.,0.,0.,0,"{Constraint penalty} MethodCommands.html#MethodSCOLIBDIR"}, {"division",8,2,1,0,595,kw_78,0.,0.,0.,0,"{Box subdivision approach} MethodCommands.html#MethodSCOLIBDIR"}, {"global_balance_parameter",10,0,2,0,601,0,0.,0.,0.,0,"{Global search balancing parameter} MethodCommands.html#MethodSCOLIBDIR"}, {"local_balance_parameter",10,0,3,0,603,0,0.,0.,0.,0,"{Local search balancing parameter} MethodCommands.html#MethodSCOLIBDIR"}, {"max_boxsize_limit",10,0,4,0,605,0,0.,0.,0.,0,"{Maximum boxsize limit} MethodCommands.html#MethodSCOLIBDIR"}, {"min_boxsize_limit",10,0,5,0,607,0,0.,0.,0.,0,"{Minimum boxsize limit} MethodCommands.html#MethodSCOLIBDIR"}, {"misc_options",15,0,11,0,679,0,0.,0.,0.,0,"{Specify miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"model_pointer",11,0,7,0,1905}, {"seed",0x19,0,9,0,675,0,0.,0.,0.,0,"{Random seed for stochastic pattern search} MethodCommands.html#MethodSCOLIBPS"}, {"show_misc_options",8,0,10,0,677,0,0.,0.,0.,0,"{Show miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"solution_accuracy",2,0,8,0,672}, {"solution_target",10,0,8,0,673,0,0.,0.,0.,0,"{Desired solution target} MethodCommands.html#MethodSCOLIBDC"} }
static KeyWord kw_80 [static] |
{ {"blend",8,0,1,1,645}, {"two_point",8,0,1,1,643}, {"uniform",8,0,1,1,647} }
static KeyWord kw_81 [static] |
{ {"linear_rank",8,0,1,1,625}, {"merit_function",8,0,1,1,627} }
static KeyWord kw_82 [static] |
{ {"flat_file",11,0,1,1,621}, {"simple_random",8,0,1,1,617}, {"unique_random",8,0,1,1,619} }
static KeyWord kw_83 [static] |
{ {"mutation_range",9,0,2,0,663,0,0.,0.,0.,0,"{Mutation range} MethodCommands.html#MethodSCOLIBEA"}, {"mutation_scale",10,0,1,0,661,0,0.,0.,0.,0,"{Mutation scale} MethodCommands.html#MethodSCOLIBEA"} }
static KeyWord kw_84 [static] |
{ {"non_adaptive",8,0,2,0,665,0,0.,0.,0.,0,"{Non-adaptive mutation flag} MethodCommands.html#MethodSCOLIBEA"}, {"offset_cauchy",8,2,1,1,657,kw_83}, {"offset_normal",8,2,1,1,655,kw_83}, {"offset_uniform",8,2,1,1,659,kw_83}, {"replace_uniform",8,0,1,1,653} }
static KeyWord kw_85 [static] |
{ {"chc",9,0,1,1,633,0,0.,0.,0.,0,"{CHC replacement type} MethodCommands.html#MethodSCOLIBEA"}, {"elitist",9,0,1,1,635,0,0.,0.,0.,0,"{Elitist replacement type} MethodCommands.html#MethodSCOLIBEA"}, {"new_solutions_generated",9,0,2,0,637,0,0.,0.,0.,0,"{New solutions generated} MethodCommands.html#MethodSCOLIBEA"}, {"random",9,0,1,1,631,0,0.,0.,0.,0,"{Random replacement type} MethodCommands.html#MethodSCOLIBEA"} }
static KeyWord kw_86 [static] |
{ {"constraint_penalty",10,0,9,0,667}, {"crossover_rate",10,0,5,0,639,0,0.,0.,0.,0,"{Crossover rate} MethodCommands.html#MethodSCOLIBEA"}, {"crossover_type",8,3,6,0,641,kw_80,0.,0.,0.,0,"{Crossover type} MethodCommands.html#MethodSCOLIBEA"}, {"fitness_type",8,2,3,0,623,kw_81,0.,0.,0.,0,"{Fitness type} MethodCommands.html#MethodSCOLIBEA"}, {"initialization_type",8,3,2,0,615,kw_82,0.,0.,0.,0,"{Initialization type} MethodCommands.html#MethodSCOLIBEA"}, {"misc_options",15,0,14,0,679,0,0.,0.,0.,0,"{Specify miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"model_pointer",11,0,10,0,1905}, {"mutation_rate",10,0,7,0,649,0,0.,0.,0.,0,"{Mutation rate} MethodCommands.html#MethodSCOLIBEA"}, {"mutation_type",8,5,8,0,651,kw_84,0.,0.,0.,0,"{Mutation type} MethodCommands.html#MethodSCOLIBEA"}, {"population_size",0x19,0,1,0,613,0,0.,0.,0.,0,"{Number of population members} MethodCommands.html#MethodSCOLIBEA"}, {"replacement_type",8,4,4,0,629,kw_85,0.,0.,0.,0,"{Replacement type} MethodCommands.html#MethodSCOLIBEA"}, {"seed",0x19,0,12,0,675,0,0.,0.,0.,0,"{Random seed for stochastic pattern search} MethodCommands.html#MethodSCOLIBPS"}, {"show_misc_options",8,0,13,0,677,0,0.,0.,0.,0,"{Show miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"solution_accuracy",2,0,11,0,672}, {"solution_target",10,0,11,0,673,0,0.,0.,0.,0,"{Desired solution target} MethodCommands.html#MethodSCOLIBDC"} }
static KeyWord kw_87 [static] |
{ {"adaptive_pattern",8,0,1,1,563}, {"basic_pattern",8,0,1,1,565}, {"multi_step",8,0,1,1,561} }
static KeyWord kw_88 [static] |
{ {"coordinate",8,0,1,1,551}, {"simplex",8,0,1,1,553} }
static KeyWord kw_89 [static] |
{ {"blocking",8,0,1,1,569}, {"nonblocking",8,0,1,1,571} }
static KeyWord kw_90 [static] |
{ {"constant_penalty",8,0,1,0,543,0,0.,0.,0.,0,"{Control of dynamic penalty} MethodCommands.html#MethodSCOLIBPS"}, {"constraint_penalty",10,0,17,0,585,0,0.,0.,0.,0,"{Constraint penalty} MethodCommands.html#MethodSCOLIBPS"}, {"contraction_factor",10,0,16,0,583,0,0.,0.,0.,0,"{Pattern contraction factor} MethodCommands.html#MethodSCOLIBPS"}, {"expand_after_success",9,0,3,0,547,0,0.,0.,0.,0,"{Number of consecutive improvements before expansion} MethodCommands.html#MethodSCOLIBPS"}, {"exploratory_moves",8,3,7,0,559,kw_87,0.,0.,0.,0,"{Exploratory moves selection} MethodCommands.html#MethodSCOLIBPS"}, {"initial_delta",10,0,14,0,589,0,0.,0.,0.,0,"{Initial offset value} MethodCommands.html#MethodSCOLIBPS"}, {"misc_options",15,0,13,0,679,0,0.,0.,0.,0,"{Specify miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"model_pointer",11,0,9,0,1905}, {"no_expansion",8,0,2,0,545,0,0.,0.,0.,0,"{No expansion flag} MethodCommands.html#MethodSCOLIBPS"}, {"pattern_basis",8,2,4,0,549,kw_88,0.,0.,0.,0,"{Pattern basis selection} MethodCommands.html#MethodSCOLIBPS"}, {"seed",0x19,0,11,0,675,0,0.,0.,0.,0,"{Random seed for stochastic pattern search} MethodCommands.html#MethodSCOLIBPS"}, {"show_misc_options",8,0,12,0,677,0,0.,0.,0.,0,"{Show miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"solution_accuracy",2,0,10,0,672}, {"solution_target",10,0,10,0,673,0,0.,0.,0.,0,"{Desired solution target} MethodCommands.html#MethodSCOLIBDC"}, {"stochastic",8,0,5,0,555,0,0.,0.,0.,0,"{Stochastic pattern search} MethodCommands.html#MethodSCOLIBPS"}, {"synchronization",8,2,8,0,567,kw_89,0.,0.,0.,0,"{Evaluation synchronization} MethodCommands.html#MethodSCOLIBPS"}, {"threshold_delta",10,0,15,0,591,0,0.,0.,0.,0,"{Threshold for offset values} MethodCommands.html#MethodSCOLIBPS"}, {"total_pattern_size",9,0,6,0,557,0,0.,0.,0.,0,"{Total number of points in pattern} MethodCommands.html#MethodSCOLIBPS"} }
static KeyWord kw_91 [static] |
{ {"constant_penalty",8,0,4,0,581,0,0.,0.,0.,0,"{Control of dynamic penalty} MethodCommands.html#MethodSCOLIBSW"}, {"constraint_penalty",10,0,13,0,585,0,0.,0.,0.,0,"{Constraint penalty} MethodCommands.html#MethodSCOLIBPS"}, {"contract_after_failure",9,0,1,0,575,0,0.,0.,0.,0,"{Number of consecutive failures before contraction} MethodCommands.html#MethodSCOLIBSW"}, {"contraction_factor",10,0,12,0,583,0,0.,0.,0.,0,"{Pattern contraction factor} MethodCommands.html#MethodSCOLIBPS"}, {"expand_after_success",9,0,3,0,579,0,0.,0.,0.,0,"{Number of consecutive improvements before expansion} MethodCommands.html#MethodSCOLIBSW"}, {"initial_delta",10,0,10,0,589,0,0.,0.,0.,0,"{Initial offset value} MethodCommands.html#MethodSCOLIBPS"}, {"misc_options",15,0,9,0,679,0,0.,0.,0.,0,"{Specify miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"model_pointer",11,0,5,0,1905}, {"no_expansion",8,0,2,0,577,0,0.,0.,0.,0,"{No expansion flag} MethodCommands.html#MethodSCOLIBSW"}, {"seed",0x19,0,7,0,675,0,0.,0.,0.,0,"{Random seed for stochastic pattern search} MethodCommands.html#MethodSCOLIBPS"}, {"show_misc_options",8,0,8,0,677,0,0.,0.,0.,0,"{Show miscellaneous options} MethodCommands.html#MethodSCOLIBDC"}, {"solution_accuracy",2,0,6,0,672}, {"solution_target",10,0,6,0,673,0,0.,0.,0.,0,"{Desired solution target} MethodCommands.html#MethodSCOLIBDC"}, {"threshold_delta",10,0,11,0,591,0,0.,0.,0.,0,"{Threshold for offset values} MethodCommands.html#MethodSCOLIBPS"} }
static KeyWord kw_92 [static] |
{ {"frcg",8,0,1,1,285}, {"linear_equality_constraint_matrix",14,0,8,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,10,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,11,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,9,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,3,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,4,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,6,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,7,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,5,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"mfd",8,0,1,1,287}, {"model_pointer",11,0,2,0,1905} }
static KeyWord kw_93 [static] |
{ {"linear_equality_constraint_matrix",14,0,7,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,9,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,10,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,8,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,2,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,3,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,5,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,6,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,4,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"model_pointer",11,0,1,0,1905} }
static KeyWord kw_94 [static] |
{
{"drop_tolerance",10,0,1,0,1613}
}
static KeyWord kw_95 [static] |
{ {"box_behnken",8,0,1,1,1603,0,0.,0.,0.,0,"[CHOOSE DACE type]"}, {"central_composite",8,0,1,1,1605}, {"fixed_seed",8,0,5,0,1615,0,0.,0.,0.,0,"{Fixed seed flag} MethodCommands.html#MethodDDACE"}, {"grid",8,0,1,1,1593}, {"lhs",8,0,1,1,1599}, {"main_effects",8,0,2,0,1607,0,0.,0.,0.,0,"{Main effects} MethodCommands.html#MethodDDACE"}, {"model_pointer",11,0,7,0,1905}, {"oa_lhs",8,0,1,1,1601}, {"oas",8,0,1,1,1597}, {"quality_metrics",8,0,3,0,1609,0,0.,0.,0.,0,"{Quality metrics} MethodCommands.html#MethodDDACE"}, {"random",8,0,1,1,1595}, {"samples",9,0,8,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,9,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"}, {"symbols",9,0,6,0,1617,0,0.,0.,0.,0,"{Number of symbols} MethodCommands.html#MethodDDACE"}, {"variance_based_decomp",8,1,4,0,1611,kw_94,0.,0.,0.,0,"{Variance based decomposition} MethodCommands.html#MethodDDACE"} }
static KeyWord kw_96 [static] |
{ {"bfgs",8,0,1,1,273}, {"frcg",8,0,1,1,269}, {"linear_equality_constraint_matrix",14,0,8,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,10,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,11,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,9,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,3,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,4,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,6,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,7,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,5,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"mmfd",8,0,1,1,271}, {"model_pointer",11,0,2,0,1905}, {"slp",8,0,1,1,275}, {"sqp",8,0,1,1,277} }
static KeyWord kw_97 [static] |
{ {"eval_id",8,0,2,0,753}, {"header",8,0,1,0,751}, {"interface_id",8,0,3,0,755} }
static KeyWord kw_98 [static] |
{ {"annotated",8,0,1,0,747}, {"custom_annotated",8,3,1,0,749,kw_97}, {"freeform",8,0,1,0,757} }
static KeyWord kw_99 [static] |
{ {"dakota",8,0,1,1,725}, {"surfpack",8,0,1,1,723} }
static KeyWord kw_100 [static] |
{ {"eval_id",8,0,2,0,737}, {"header",8,0,1,0,735}, {"interface_id",8,0,3,0,739} }
static KeyWord kw_101 [static] |
{ {"active_only",8,0,2,0,743}, {"annotated",8,0,1,0,731}, {"custom_annotated",8,3,1,0,733,kw_100}, {"freeform",8,0,1,0,741} }
static KeyWord kw_102 [static] |
{ {"export_points_file",11,3,4,0,745,kw_98,0.,0.,0.,0,"{File name for exporting approximation-based samples from evaluating the GP} MethodCommands.html#MethodEG"}, {"gaussian_process",8,2,1,0,721,kw_99,0.,0.,0.,0,"{GP selection} MethodCommands.html#MethodEG"}, {"import_points_file",11,4,3,0,729,kw_101,0.,0.,0.,0,"{File name for points to be imported as the basis for the initial GP} MethodCommands.html#MethodEG"}, {"kriging",0,2,1,0,720,kw_99}, {"model_pointer",11,0,6,0,1905}, {"seed",0x19,0,5,0,759,0,0.,0.,0.,0,"{Random seed} MethodCommands.html#MethodEG"}, {"use_derivatives",8,0,2,0,727,0,0.,0.,0.,0,"{Derivative usage} MethodCommands.html#MethodEG"} }
static KeyWord kw_103 [static] |
{ {"batch_size",9,0,2,0,1241}, {"distribution",8,2,6,0,1307,kw_27,0.,0.,0.,0,"{Distribution type} MethodCommands.html#MethodNonD"}, {"emulator_samples",9,0,1,0,1239}, {"gen_reliability_levels",14,1,8,0,1317,kw_28,0.,0.,0.,0,"{Generalized reliability levels} MethodCommands.html#MethodNonD"}, {"model_pointer",11,0,3,0,1905}, {"probability_levels",14,1,7,0,1313,kw_29,0.,0.,0.,0,"{Probability levels} MethodCommands.html#MethodNonD"}, {"rng",8,2,9,0,1321,kw_30,0.,0.,0.,0,"{Random number generator} MethodCommands.html#MethodNonDMC"}, {"samples",9,0,4,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,5,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"} }
static KeyWord kw_104 [static] |
{ {"grid",8,0,1,1,1633,0,0.,0.,0.,0,"[CHOOSE trial type]"}, {"halton",8,0,1,1,1635}, {"random",8,0,1,1,1637,0,0.,0.,0.,0,"@"} }
static KeyWord kw_105 [static] |
{
{"drop_tolerance",10,0,1,0,1627}
}
static KeyWord kw_106 [static] |
{ {"fixed_seed",8,0,4,0,1629,0,0.,0.,0.,0,"{Fixed seed flag} MethodCommands.html#MethodFSUDACE"}, {"latinize",8,0,1,0,1621,0,0.,0.,0.,0,"{Latinization of samples} MethodCommands.html#MethodFSUDACE"}, {"model_pointer",11,0,7,0,1905}, {"num_trials",9,0,6,0,1639,0,0.,0.,0.,0,"{Number of trials } MethodCommands.html#MethodFSUDACE"}, {"quality_metrics",8,0,2,0,1623,0,0.,0.,0.,0,"{Quality metrics} MethodCommands.html#MethodFSUDACE"}, {"samples",9,0,8,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,9,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"}, {"trial_type",8,3,5,0,1631,kw_104,0.,0.,0.,0,"{Trial type} MethodCommands.html#MethodFSUDACE"}, {"variance_based_decomp",8,1,3,0,1625,kw_105,0.,0.,0.,0,"{Variance based decomposition} MethodCommands.html#MethodFSUDACE"} }
static KeyWord kw_107 [static] |
{
{"drop_tolerance",10,0,1,0,1845}
}
static KeyWord kw_108 [static] |
{ {"fixed_sequence",8,0,6,0,1849,0,0.,0.,0.,0,"{Fixed sequence flag} MethodCommands.html#MethodFSUDACE"}, {"halton",8,0,1,1,1835,0,0.,0.,0.,0,"[CHOOSE sequence type]"}, {"hammersley",8,0,1,1,1837}, {"latinize",8,0,2,0,1839,0,0.,0.,0.,0,"{Latinization of samples} MethodCommands.html#MethodFSUDACE"}, {"model_pointer",11,0,10,0,1905}, {"prime_base",13,0,9,0,1855,0,0.,0.,0.,0,"{Prime bases for sequences} MethodCommands.html#MethodFSUDACE"}, {"quality_metrics",8,0,3,0,1841,0,0.,0.,0.,0,"{Quality metrics} MethodCommands.html#MethodFSUDACE"}, {"samples",9,0,5,0,1847,0,0.,0.,0.,0,"{Number of samples taken in the MCMC sampling} MethodCommands.html#MethodNonDBayesCalib"}, {"sequence_leap",13,0,8,0,1853,0,0.,0.,0.,0,"{Sequence leaping indices} MethodCommands.html#MethodFSUDACE"}, {"sequence_start",13,0,7,0,1851,0,0.,0.,0.,0,"{Sequence starting indices} MethodCommands.html#MethodFSUDACE"}, {"variance_based_decomp",8,1,4,0,1843,kw_107,0.,0.,0.,0,"{Variance based decomposition} MethodCommands.html#MethodFSUDACE"} }
static KeyWord kw_109 [static] |
{ {"eval_id",8,0,2,0,1117}, {"header",8,0,1,0,1115}, {"interface_id",8,0,3,0,1119} }
static KeyWord kw_110 [static] |
{ {"annotated",8,0,1,0,1111}, {"custom_annotated",8,3,1,0,1113,kw_109}, {"freeform",8,0,1,0,1121} }
static KeyWord kw_111 [static] |
{ {"eval_id",8,0,2,0,1101}, {"header",8,0,1,0,1099}, {"interface_id",8,0,3,0,1103} }
static KeyWord kw_112 [static] |
{ {"active_only",8,0,2,0,1107}, {"annotated",8,0,1,0,1095}, {"custom_annotated",8,3,1,0,1097,kw_111}, {"freeform",8,0,1,0,1105} }
static KeyWord kw_113 [static] |
{ {"parallel",8,0,1,1,1137}, {"series",8,0,1,1,1135} }
static KeyWord kw_114 [static] |
{ {"gen_reliabilities",8,0,1,1,1131}, {"probabilities",8,0,1,1,1129}, {"system",8,2,2,0,1133,kw_113} }
static KeyWord kw_115 [static] |
{ {"compute",8,3,2,0,1127,kw_114}, {"num_response_levels",13,0,1,0,1125} }
static KeyWord kw_116 [static] |
{ {"distribution",8,2,8,0,1307,kw_27,0.,0.,0.,0,"{Distribution type} MethodCommands.html#MethodNonD"}, {"emulator_samples",9,0,1,0,1091}, {"export_points_file",11,3,3,0,1109,kw_110,0.,0.,0.,0,"{File name for exporting approximation-based samples from evaluating the emulator} MethodCommands.html#MethodNonDBayesCalib"}, {"gen_reliability_levels",14,1,10,0,1317,kw_28,0.,0.,0.,0,"{Generalized reliability levels} MethodCommands.html#MethodNonD"}, {"import_points_file",11,4,2,0,1093,kw_112,0.,0.,0.,0,"{File name for points to be imported as the basis for the initial emulator} MethodCommands.html#MethodNonDBayesCalib"}, {"model_pointer",11,0,5,0,1905}, {"probability_levels",14,1,9,0,1313,kw_29,0.,0.,0.,0,"{Probability levels} MethodCommands.html#MethodNonD"}, {"response_levels",14,2,4,0,1123,kw_115}, {"rng",8,2,11,0,1321,kw_30,0.,0.,0.,0,"{Random number generator} MethodCommands.html#MethodNonDMC"}, {"samples",9,0,6,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,7,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"} }
static KeyWord kw_117 [static] |
{ {"model_pointer",11,0,2,0,1905}, {"seed",0x19,0,1,0,717,0,0.,0.,0.,0,"{Random seed} MethodCommands.html#MethodNonDMC"} }
static KeyWord kw_118 [static] |
{ {"parallel",8,0,1,1,1305}, {"series",8,0,1,1,1303} }
static KeyWord kw_119 [static] |
{ {"gen_reliabilities",8,0,1,1,1299}, {"probabilities",8,0,1,1,1297}, {"system",8,2,2,0,1301,kw_118} }
static KeyWord kw_120 [static] |
{ {"compute",8,3,2,0,1295,kw_119}, {"num_response_levels",13,0,1,0,1293} }
static KeyWord kw_121 [static] |
{ {"eval_id",8,0,2,0,1281}, {"header",8,0,1,0,1279}, {"interface_id",8,0,3,0,1283} }
static KeyWord kw_122 [static] |
{ {"annotated",8,0,1,0,1275}, {"custom_annotated",8,3,1,0,1277,kw_121}, {"freeform",8,0,1,0,1285} }
static KeyWord kw_123 [static] |
{ {"dakota",8,0,1,1,1253}, {"surfpack",8,0,1,1,1251} }
static KeyWord kw_124 [static] |
{ {"eval_id",8,0,2,0,1265}, {"header",8,0,1,0,1263}, {"interface_id",8,0,3,0,1267} }
static KeyWord kw_125 [static] |
{ {"active_only",8,0,2,0,1271}, {"annotated",8,0,1,0,1259}, {"custom_annotated",8,3,1,0,1261,kw_124}, {"freeform",8,0,1,0,1269} }
static KeyWord kw_126 [static] |
{ {"export_points_file",11,3,4,0,1273,kw_122}, {"gaussian_process",8,2,1,0,1249,kw_123}, {"import_points_file",11,4,3,0,1257,kw_125,0.,0.,0.,0,"{File containing points to evaluate} MethodCommands.html#MethodPSLPS"}, {"kriging",0,2,1,0,1248,kw_123}, {"use_derivatives",8,0,2,0,1255} }
static KeyWord kw_127 [static] |
{ {"distribution",8,2,6,0,1307,kw_27,0.,0.,0.,0,"{Distribution type} MethodCommands.html#MethodNonD"}, {"ea",8,0,1,0,1287}, {"ego",8,5,1,0,1247,kw_126}, {"gen_reliability_levels",14,1,8,0,1317,kw_28,0.,0.,0.,0,"{Generalized reliability levels} MethodCommands.html#MethodNonD"}, {"lhs",8,0,1,0,1289}, {"model_pointer",11,0,3,0,1905}, {"probability_levels",14,1,7,0,1313,kw_29,0.,0.,0.,0,"{Probability levels} MethodCommands.html#MethodNonD"}, {"response_levels",14,2,2,0,1291,kw_120}, {"rng",8,2,9,0,1321,kw_30,0.,0.,0.,0,"{Random number generator} MethodCommands.html#MethodNonDMC"}, {"samples",9,0,4,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"sbo",8,5,1,0,1245,kw_126}, {"seed",0x19,0,5,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"} }
static KeyWord kw_128 [static] |
{ {"mt19937",8,0,1,1,1377}, {"rnum2",8,0,1,1,1379} }
static KeyWord kw_129 [static] |
{ {"eval_id",8,0,2,0,1365}, {"header",8,0,1,0,1363}, {"interface_id",8,0,3,0,1367} }
static KeyWord kw_130 [static] |
{ {"annotated",8,0,1,0,1359}, {"custom_annotated",8,3,1,0,1361,kw_129}, {"freeform",8,0,1,0,1369} }
static KeyWord kw_131 [static] |
{ {"dakota",8,0,1,1,1337}, {"surfpack",8,0,1,1,1335} }
static KeyWord kw_132 [static] |
{ {"eval_id",8,0,2,0,1349}, {"header",8,0,1,0,1347}, {"interface_id",8,0,3,0,1351} }
static KeyWord kw_133 [static] |
{ {"active_only",8,0,2,0,1355}, {"annotated",8,0,1,0,1343}, {"custom_annotated",8,3,1,0,1345,kw_132}, {"freeform",8,0,1,0,1353} }
static KeyWord kw_134 [static] |
{ {"export_points_file",11,3,4,0,1357,kw_130,0.,0.,0.,0,"{File name for exporting approximation-based samples from evaluating the GP} MethodCommands.html#MethodNonDGlobalIntervalEst"}, {"gaussian_process",8,2,1,0,1333,kw_131,0.,0.,0.,0,"{EGO GP selection} MethodCommands.html#MethodNonDGlobalIntervalEst"}, {"import_points_file",11,4,3,0,1341,kw_133,0.,0.,0.,0,"{File name for points to be imported as the basis for the initial GP} MethodCommands.html#MethodNonDGlobalIntervalEst"}, {"kriging",0,2,1,0,1332,kw_131}, {"use_derivatives",8,0,2,0,1339,0,0.,0.,0.,0,"{Derivative usage} MethodCommands.html#MethodNonDGlobalIntervalEst"} }
static KeyWord kw_135 [static] |
{ {"ea",8,0,1,0,1371}, {"ego",8,5,1,0,1331,kw_134}, {"lhs",8,0,1,0,1373}, {"model_pointer",11,0,3,0,1905}, {"rng",8,2,2,0,1375,kw_128,0.,0.,0.,0,"{Random seed generator} MethodCommands.html#MethodNonDGlobalIntervalEst"}, {"samples",9,0,4,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"sbo",8,5,1,0,1329,kw_134}, {"seed",0x19,0,5,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"} }
static KeyWord kw_136 [static] |
{ {"complementary",8,0,1,1,1823}, {"cumulative",8,0,1,1,1821} }
static KeyWord kw_137 [static] |
{
{"num_gen_reliability_levels",13,0,1,0,1831}
}
static KeyWord kw_138 [static] |
{
{"num_probability_levels",13,0,1,0,1827}
}
static KeyWord kw_139 [static] |
{ {"eval_id",8,0,2,0,1787}, {"header",8,0,1,0,1785}, {"interface_id",8,0,3,0,1789} }
static KeyWord kw_140 [static] |
{ {"annotated",8,0,1,0,1781}, {"custom_annotated",8,3,1,0,1783,kw_139}, {"freeform",8,0,1,0,1791} }
static KeyWord kw_141 [static] |
{ {"eval_id",8,0,2,0,1771}, {"header",8,0,1,0,1769}, {"interface_id",8,0,3,0,1773} }
static KeyWord kw_142 [static] |
{ {"active_only",8,0,2,0,1777}, {"annotated",8,0,1,0,1765}, {"custom_annotated",8,3,1,0,1767,kw_141}, {"freeform",8,0,1,0,1775} }
static KeyWord kw_143 [static] |
{ {"parallel",8,0,1,1,1817}, {"series",8,0,1,1,1815} }
static KeyWord kw_144 [static] |
{ {"gen_reliabilities",8,0,1,1,1811}, {"probabilities",8,0,1,1,1809}, {"system",8,2,2,0,1813,kw_143} }
static KeyWord kw_145 [static] |
{ {"compute",8,3,2,0,1807,kw_144}, {"num_response_levels",13,0,1,0,1805} }
static KeyWord kw_146 [static] |
{ {"mt19937",8,0,1,1,1799}, {"rnum2",8,0,1,1,1801} }
static KeyWord kw_147 [static] |
{ {"dakota",8,0,2,0,1761}, {"distribution",8,2,10,0,1819,kw_136}, {"export_points_file",11,3,4,0,1779,kw_140,0.,0.,0.,0,"{File name for exporting approximation-based samples from evaluating the GP} MethodCommands.html#MethodNonDGlobalRel"}, {"gen_reliability_levels",14,1,12,0,1829,kw_137}, {"import_points_file",11,4,3,0,1763,kw_142,0.,0.,0.,0,"{File name for points to be imported as the basis for the initial GP} MethodCommands.html#MethodNonDGlobalRel"}, {"model_pointer",11,0,9,0,1905}, {"probability_levels",14,1,11,0,1825,kw_138}, {"response_levels",14,2,8,0,1803,kw_145}, {"rng",8,2,7,0,1797,kw_146}, {"seed",0x19,0,6,0,1795,0,0.,0.,0.,0,"{Random seed for initial GP construction} MethodCommands.html#MethodNonDGlobalRel"}, {"surfpack",8,0,2,0,1759}, {"u_gaussian_process",8,0,1,1,1757}, {"u_kriging",0,0,1,1,1756}, {"use_derivatives",8,0,5,0,1793,0,0.,0.,0.,0,"{Derivative usage} MethodCommands.html#MethodNonDGlobalRel"}, {"x_gaussian_process",8,0,1,1,1755}, {"x_kriging",0,0,1,1,1754} }
static KeyWord kw_148 [static] |
{ {"master",8,0,1,1,179}, {"peer",8,0,1,1,181} }
static KeyWord kw_149 [static] |
{ {"model_pointer_list",11,0,1,0,143,0,0.,0.,0.,0,"{List of model pointers} MethodCommands.html#MethodMetaHybrid"} }
static KeyWord kw_150 [static] |
{ {"method_name_list",15,1,1,1,141,kw_149,0.,0.,0.,0,"{List of method names} MethodCommands.html#MethodMetaHybrid"}, {"method_pointer_list",15,0,1,1,145,0,0.,0.,0.,0,"{List of method pointers} MethodCommands.html#MethodMetaHybrid"} }
static KeyWord kw_151 [static] |
{ {"global_model_pointer",11,0,1,0,127,0,0.,0.,0.,0,"{Pointer to the global model specification} MethodCommands.html#MethodMetaHybrid"} }
static KeyWord kw_152 [static] |
{ {"local_model_pointer",11,0,1,0,133,0,0.,0.,0.,0,"{Pointer to the local model specification} MethodCommands.html#MethodMetaHybrid"} }
static KeyWord kw_153 [static] |
{ {"global_method_name",11,1,1,1,125,kw_151,0.,0.,0.,0,"{Name of the global method} MethodCommands.html#MethodMetaHybrid"}, {"global_method_pointer",11,0,1,1,129,0,0.,0.,0.,0,"{Pointer to the global method specification} MethodCommands.html#MethodMetaHybrid"}, {"local_method_name",11,1,2,2,131,kw_152,0.,0.,0.,0,"{Name of the local method} MethodCommands.html#MethodMetaHybrid"}, {"local_method_pointer",11,0,2,2,135,0,0.,0.,0.,0,"{Pointer to the local method specification} MethodCommands.html#MethodMetaHybrid"}, {"local_search_probability",10,0,3,0,137,0,0.,0.,0.,0,"{Probability of executing local searches} MethodCommands.html#MethodMetaHybrid"} }
static KeyWord kw_154 [static] |
{ {"model_pointer_list",11,0,1,0,119,0,0.,0.,0.,0,"{List of model pointers} MethodCommands.html#MethodMetaHybrid"} }
static KeyWord kw_155 [static] |
{ {"method_name_list",15,1,1,1,117,kw_154,0.,0.,0.,0,"{List of method names} MethodCommands.html#MethodMetaHybrid"}, {"method_pointer_list",15,0,1,1,121,0,0.,0.,0.,0,"{List of method pointers} MethodCommands.html#MethodMetaHybrid"} }
static KeyWord kw_156 [static] |
{ {"collaborative",8,2,1,1,139,kw_150,0.,0.,0.,0,"{Collaborative hybrid} MethodCommands.html#MethodMetaHybrid"}, {"coupled",0,5,1,1,122,kw_153}, {"embedded",8,5,1,1,123,kw_153,0.,0.,0.,0,"{Embedded hybrid} MethodCommands.html#MethodMetaHybrid"}, {"iterator_scheduling",8,2,3,0,177,kw_148,0.,0.,0.,0,"{Message passing configuration for scheduling of iterator jobs} MethodCommands.html#MethodMeta"}, {"iterator_servers",0x19,0,2,0,175,0,0.,0.,0.,0,"{Number of iterator servers} MethodCommands.html#MethodMeta"}, {"processors_per_iterator",0x19,0,4,0,183,0,0.,0.,0.,0,"{Number of processors per iterator server} MethodCommands.html#MethodMeta"}, {"sequential",8,2,1,1,115,kw_155,0.,0.,0.,0,"{Sequential hybrid} MethodCommands.html#MethodMetaHybrid"}, {"uncoupled",0,2,1,1,114,kw_155} }
static KeyWord kw_157 [static] |
{ {"parallel",8,0,1,1,1087}, {"series",8,0,1,1,1085} }
static KeyWord kw_158 [static] |
{ {"gen_reliabilities",8,0,1,1,1081}, {"probabilities",8,0,1,1,1079}, {"system",8,2,2,0,1083,kw_157} }
static KeyWord kw_159 [static] |
{ {"compute",8,3,2,0,1077,kw_158}, {"num_response_levels",13,0,1,0,1075} }
static KeyWord kw_160 [static] |
{ {"adapt_import",8,0,1,1,1067}, {"distribution",8,2,7,0,1307,kw_27,0.,0.,0.,0,"{Distribution type} MethodCommands.html#MethodNonD"}, {"gen_reliability_levels",14,1,9,0,1317,kw_28,0.,0.,0.,0,"{Generalized reliability levels} MethodCommands.html#MethodNonD"}, {"import",8,0,1,1,1065}, {"mm_adapt_import",8,0,1,1,1069}, {"model_pointer",11,0,4,0,1905}, {"probability_levels",14,1,8,0,1313,kw_29,0.,0.,0.,0,"{Probability levels} MethodCommands.html#MethodNonD"}, {"refinement_samples",9,0,2,0,1071}, {"response_levels",14,2,3,0,1073,kw_159}, {"rng",8,2,10,0,1321,kw_30,0.,0.,0.,0,"{Random number generator} MethodCommands.html#MethodNonDMC"}, {"samples",9,0,5,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,6,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"} }
static KeyWord kw_161 [static] |
{ {"eval_id",8,0,2,0,1877}, {"header",8,0,1,0,1875}, {"interface_id",8,0,3,0,1879} }
static KeyWord kw_162 [static] |
{ {"active_only",8,0,2,0,1883}, {"annotated",8,0,1,0,1871}, {"custom_annotated",8,3,1,0,1873,kw_161}, {"freeform",8,0,1,0,1881} }
static KeyWord kw_163 [static] |
{ {"import_points_file",11,4,1,1,1869,kw_162}, {"list_of_points",14,0,1,1,1867,0,0.,0.,0.,0,"{List of points to evaluate} MethodCommands.html#MethodPSLPS"}, {"model_pointer",11,0,2,0,1905} }
static KeyWord kw_164 [static] |
{ {"complementary",8,0,1,1,1683}, {"cumulative",8,0,1,1,1681} }
static KeyWord kw_165 [static] |
{
{"num_gen_reliability_levels",13,0,1,0,1677}
}
static KeyWord kw_166 [static] |
{
{"num_probability_levels",13,0,1,0,1673}
}
static KeyWord kw_167 [static] |
{ {"parallel",8,0,1,1,1669}, {"series",8,0,1,1,1667} }
static KeyWord kw_168 [static] |
{ {"gen_reliabilities",8,0,1,1,1663}, {"probabilities",8,0,1,1,1661}, {"system",8,2,2,0,1665,kw_167} }
static KeyWord kw_169 [static] |
{ {"compute",8,3,2,0,1659,kw_168}, {"num_response_levels",13,0,1,0,1657} }
static KeyWord kw_170 [static] |
{ {"distribution",8,2,5,0,1679,kw_164}, {"gen_reliability_levels",14,1,4,0,1675,kw_165}, {"model_pointer",11,0,6,0,1905}, {"nip",8,0,1,0,1653}, {"probability_levels",14,1,3,0,1671,kw_166}, {"response_levels",14,2,2,0,1655,kw_169}, {"sqp",8,0,1,0,1651} }
static KeyWord kw_171 [static] |
{ {"model_pointer",11,0,2,0,1905}, {"nip",8,0,1,0,1689}, {"sqp",8,0,1,0,1687} }
static KeyWord kw_172 [static] |
{ {"adapt_import",8,0,1,1,1723}, {"import",8,0,1,1,1721}, {"mm_adapt_import",8,0,1,1,1725}, {"refinement_samples",9,0,2,0,1727}, {"seed",0x19,0,3,0,1729,0,0.,0.,0.,0,"{Random seed} MethodCommands.html#MethodNonDBayesCalib"} }
static KeyWord kw_173 [static] |
{ {"first_order",8,0,1,1,1715}, {"probability_refinement",8,5,2,0,1719,kw_172}, {"sample_refinement",0,5,2,0,1718,kw_172}, {"second_order",8,0,1,1,1717} }
static KeyWord kw_174 [static] |
{ {"integration",8,4,3,0,1713,kw_173,0.,0.,0.,0,"{Integration method} MethodCommands.html#MethodNonDLocalRel"}, {"nip",8,0,2,0,1711}, {"no_approx",8,0,1,1,1707}, {"sqp",8,0,2,0,1709}, {"u_taylor_mean",8,0,1,1,1697}, {"u_taylor_mpp",8,0,1,1,1701}, {"u_two_point",8,0,1,1,1705}, {"x_taylor_mean",8,0,1,1,1695}, {"x_taylor_mpp",8,0,1,1,1699}, {"x_two_point",8,0,1,1,1703} }
static KeyWord kw_175 [static] |
{
{"num_reliability_levels",13,0,1,0,1751}
}
static KeyWord kw_176 [static] |
{ {"parallel",8,0,1,1,1747}, {"series",8,0,1,1,1745} }
static KeyWord kw_177 [static] |
{ {"gen_reliabilities",8,0,1,1,1741}, {"probabilities",8,0,1,1,1737}, {"reliabilities",8,0,1,1,1739}, {"system",8,2,2,0,1743,kw_176} }
static KeyWord kw_178 [static] |
{ {"compute",8,4,2,0,1735,kw_177}, {"num_response_levels",13,0,1,0,1733} }
static KeyWord kw_179 [static] |
{ {"distribution",8,2,5,0,1819,kw_136}, {"gen_reliability_levels",14,1,7,0,1829,kw_137}, {"model_pointer",11,0,4,0,1905}, {"mpp_search",8,10,1,0,1693,kw_174,0.,0.,0.,0,"{MPP search type} MethodCommands.html#MethodNonDLocalRel"}, {"probability_levels",14,1,6,0,1825,kw_138}, {"reliability_levels",14,1,3,0,1749,kw_175}, {"response_levels",14,2,2,0,1731,kw_178} }
static KeyWord kw_180 [static] |
{ {"display_all_evaluations",8,0,7,0,399,0,0.,0.,0.,0,"{Display NOMAD evaluations} MethodCommands.html#MethodNOMADDC"}, {"display_format",11,0,4,0,393}, {"function_precision",10,0,1,0,387,0,0.,0.,0.,0,"{Function Evaluation Precision} MethodCommands.html#MethodNOMADDC"}, {"history_file",11,0,3,0,391,0,0.,0.,0.,0,"{NOMAD History File} MethodCommands.html#MethodNOMADDC"}, {"linear_equality_constraint_matrix",14,0,14,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,16,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,17,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,15,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,9,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,10,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,12,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,13,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,11,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"model_pointer",11,0,8,0,1905}, {"neighbor_order",0x19,0,6,0,397}, {"seed",0x19,0,2,0,389,0,0.,0.,0.,0,"{Random Seed} MethodCommands.html#MethodNOMADDC"}, {"variable_neighborhood_search",10,0,5,0,395} }
static KeyWord kw_181 [static] |
{ {"num_offspring",0x19,0,2,0,501,0,0.,0.,0.,0,"{Number of offspring in random shuffle crossover} MethodCommands.html#MethodJEGADC"}, {"num_parents",0x19,0,1,0,499,0,0.,0.,0.,0,"{Number of parents in random shuffle crossover} MethodCommands.html#MethodJEGADC"} }
static KeyWord kw_182 [static] |
{ {"crossover_rate",10,0,2,0,503,0,0.,0.,0.,0,"{Crossover rate} MethodCommands.html#MethodJEGADC"}, {"multi_point_binary",9,0,1,1,491,0,0.,0.,0.,0,"{Multi point binary crossover} MethodCommands.html#MethodJEGADC"}, {"multi_point_parameterized_binary",9,0,1,1,493,0,0.,0.,0.,0,"{Multi point parameterized binary crossover} MethodCommands.html#MethodJEGADC"}, {"multi_point_real",9,0,1,1,495,0,0.,0.,0.,0,"{Multi point real crossover} MethodCommands.html#MethodJEGADC"}, {"shuffle_random",8,2,1,1,497,kw_181,0.,0.,0.,0,"{Random shuffle crossover} MethodCommands.html#MethodJEGADC"} }
static KeyWord kw_183 [static] |
{ {"flat_file",11,0,1,1,487}, {"simple_random",8,0,1,1,483}, {"unique_random",8,0,1,1,485} }
static KeyWord kw_184 [static] |
{ {"mutation_scale",10,0,1,0,517,0,0.,0.,0.,0,"{Mutation scale} MethodCommands.html#MethodJEGADC"} }
static KeyWord kw_185 [static] |
{ {"bit_random",8,0,1,1,507}, {"mutation_rate",10,0,2,0,519,0,0.,0.,0.,0,"{Mutation rate} MethodCommands.html#MethodJEGADC"}, {"offset_cauchy",8,1,1,1,513,kw_184}, {"offset_normal",8,1,1,1,511,kw_184}, {"offset_uniform",8,1,1,1,515,kw_184}, {"replace_uniform",8,0,1,1,509} }
static KeyWord kw_186 [static] |
{ {"metric_tracker",8,0,1,1,433,0,0.,0.,0.,0,"{Convergence type} MethodCommands.html#MethodJEGAMOGA"}, {"num_generations",0x29,0,3,0,437,0,0.,0.,0.,0,"{Number generations for metric_tracker converger} MethodCommands.html#MethodJEGAMOGA"}, {"percent_change",10,0,2,0,435,0,0.,0.,0.,0,"{Percent change limit for metric_tracker converger} MethodCommands.html#MethodJEGAMOGA"} }
static KeyWord kw_187 [static] |
{ {"domination_count",8,0,1,1,407}, {"layer_rank",8,0,1,1,405} }
static KeyWord kw_188 [static] |
{ {"num_designs",0x29,0,1,0,429,0,2.,0.,0.,0,"{Number designs to keep for max_designs nicher} MethodCommands.html#MethodJEGAMOGA"} }
static KeyWord kw_189 [static] |
{ {"distance",14,0,1,1,425}, {"max_designs",14,1,1,1,427,kw_188}, {"radial",14,0,1,1,423} }
static KeyWord kw_190 [static] |
{ {"orthogonal_distance",14,0,1,1,441,0,0.,0.,0.,0,"{Post_processor distance} MethodCommands.html#MethodJEGAMOGA"} }
static KeyWord kw_191 [static] |
{ {"shrinkage_fraction",10,0,1,0,419}, {"shrinkage_percentage",2,0,1,0,418} }
static KeyWord kw_192 [static] |
{ {"below_limit",10,2,1,1,417,kw_191,0.,0.,0.,0,"{Below limit selection} MethodCommands.html#MethodJEGADC"}, {"elitist",8,0,1,1,411}, {"roulette_wheel",8,0,1,1,413}, {"unique_roulette_wheel",8,0,1,1,415} }
static KeyWord kw_193 [static] |
{ {"convergence_type",8,3,4,0,431,kw_186}, {"crossover_type",8,5,20,0,489,kw_182,0.,0.,0.,0,"{Crossover type} MethodCommands.html#MethodJEGADC"}, {"fitness_type",8,2,1,0,403,kw_187,0.,0.,0.,0,"{Fitness type} MethodCommands.html#MethodJEGAMOGA"}, {"initialization_type",8,3,19,0,481,kw_183,0.,0.,0.,0,"{Initialization type} MethodCommands.html#MethodJEGADC"}, {"linear_equality_constraint_matrix",14,0,12,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,14,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,15,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,13,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,7,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,8,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,10,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,11,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,9,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"log_file",11,0,17,0,477,0,0.,0.,0.,0,"{Log file} MethodCommands.html#MethodJEGADC"}, {"model_pointer",11,0,6,0,1905}, {"mutation_type",8,6,21,0,505,kw_185,0.,0.,0.,0,"{Mutation type} MethodCommands.html#MethodJEGADC"}, {"niching_type",8,3,3,0,421,kw_189,0.,0.,0.,0,"{Niche pressure type} MethodCommands.html#MethodJEGAMOGA"}, {"population_size",0x29,0,16,0,475,0,0.,0.,0.,0,"{Number of population members} MethodCommands.html#MethodJEGADC"}, {"postprocessor_type",8,1,5,0,439,kw_190,0.,0.,0.,0,"{Post_processor type} MethodCommands.html#MethodJEGAMOGA"}, {"print_each_pop",8,0,18,0,479,0,0.,0.,0.,0,"{Population output} MethodCommands.html#MethodJEGADC"}, {"replacement_type",8,4,2,0,409,kw_192,0.,0.,0.,0,"{Replacement type} MethodCommands.html#MethodJEGAMOGA"}, {"seed",0x19,0,22,0,521,0,0.,0.,0.,0,"{Random seed} MethodCommands.html#MethodJEGADC"} }
static KeyWord kw_194 [static] |
{ {"model_pointer",11,0,1,0,151,0,0.,0.,0.,0,"{Model pointer} MethodCommands.html#MethodMeta"} }
static KeyWord kw_195 [static] |
{ {"seed",9,0,1,0,157,0,0.,0.,0.,0,"{Seed for random starting points} MethodCommands.html#MethodMetaMultiStart"} }
static KeyWord kw_196 [static] |
{ {"iterator_scheduling",8,2,5,0,177,kw_148,0.,0.,0.,0,"{Message passing configuration for scheduling of iterator jobs} MethodCommands.html#MethodMeta"}, {"iterator_servers",0x19,0,4,0,175,0,0.,0.,0.,0,"{Number of iterator servers} MethodCommands.html#MethodMeta"}, {"method_name",11,1,1,1,149,kw_194,0.,0.,0.,0,"{Identification of a sub-method by name (no separate specification block)} MethodCommands.html#MethodMeta"}, {"method_pointer",11,0,1,1,153,0,0.,0.,0.,0,"{Identification of a sub-method by pointer to a separate specification block} MethodCommands.html#MethodMeta"}, {"processors_per_iterator",0x19,0,6,0,183,0,0.,0.,0.,0,"{Number of processors per iterator server} MethodCommands.html#MethodMeta"}, {"random_starts",9,1,2,0,155,kw_195,0.,0.,0.,0,"{Number of random starting points} MethodCommands.html#MethodMetaMultiStart"}, {"starting_points",14,0,3,0,159,0,0.,0.,0.,0,"{List of user-specified starting points} MethodCommands.html#MethodMetaMultiStart"} }
static KeyWord kw_197 [static] |
{ {"model_pointer",11,0,2,0,1905}, {"partitions",13,0,1,1,1893,0,0.,0.,0.,0,"{Partitions per variable} MethodCommands.html#MethodPSMPS"} }
static KeyWord kw_198 [static] |
{ {"min_boxsize_limit",10,0,2,0,709,0,0.,0.,0.,0,"{Min boxsize limit} MethodCommands.html#MethodNCSUDC"}, {"model_pointer",11,0,4,0,1905}, {"solution_accuracy",2,0,1,0,706}, {"solution_target",10,0,1,0,707,0,0.,0.,0.,0,"{Solution Target } MethodCommands.html#MethodNCSUDC"}, {"volume_boxsize_limit",10,0,3,0,711,0,0.,0.,0.,0,"{Volume boxsize limit} MethodCommands.html#MethodNCSUDC"} }
static KeyWord kw_199 [static] |
{ {"absolute_conv_tol",10,0,2,0,685,0,0.,0.,0.,0,"{Absolute function convergence tolerance} MethodCommands.html#MethodLSNL2SOL"}, {"covariance",9,0,8,0,697,0,0.,0.,0.,0,"{Covariance post-processing} MethodCommands.html#MethodLSNL2SOL"}, {"false_conv_tol",10,0,6,0,693,0,0.,0.,0.,0,"{False convergence tolerance} MethodCommands.html#MethodLSNL2SOL"}, {"function_precision",10,0,1,0,683,0,0.,0.,0.,0,"{Relative precision in least squares terms} MethodCommands.html#MethodLSNL2SOL"}, {"initial_trust_radius",10,0,7,0,695,0,0.,0.,0.,0,"{Initial trust region radius} MethodCommands.html#MethodLSNL2SOL"}, {"model_pointer",11,0,10,0,1905}, {"regression_diagnostics",8,0,9,0,699,0,0.,0.,0.,0,"{Regression diagnostics post-processing} MethodCommands.html#MethodLSNL2SOL"}, {"singular_conv_tol",10,0,4,0,689,0,0.,0.,0.,0,"{Singular convergence tolerance} MethodCommands.html#MethodLSNL2SOL"}, {"singular_radius",10,0,5,0,691,0,0.,0.,0.,0,"{Step limit for sctol} MethodCommands.html#MethodLSNL2SOL"}, {"x_conv_tol",10,0,3,0,687,0,0.,0.,0.,0,"{Convergence tolerance for change in parameter vector} MethodCommands.html#MethodLSNL2SOL"} }
static KeyWord kw_200 [static] |
{ {"global",8,0,1,1,1217}, {"local",8,0,1,1,1215} }
static KeyWord kw_201 [static] |
{ {"parallel",8,0,1,1,1235}, {"series",8,0,1,1,1233} }
static KeyWord kw_202 [static] |
{ {"gen_reliabilities",8,0,1,1,1229}, {"probabilities",8,0,1,1,1227}, {"system",8,2,2,0,1231,kw_201} }
static KeyWord kw_203 [static] |
{ {"compute",8,3,2,0,1225,kw_202}, {"num_response_levels",13,0,1,0,1223} }
static KeyWord kw_204 [static] |
{ {"distribution",8,2,7,0,1307,kw_27,0.,0.,0.,0,"{Distribution type} MethodCommands.html#MethodNonD"}, {"emulator_samples",9,0,2,0,1219}, {"gen_reliability_levels",14,1,9,0,1317,kw_28,0.,0.,0.,0,"{Generalized reliability levels} MethodCommands.html#MethodNonD"}, {"lipschitz",8,2,1,0,1213,kw_200}, {"model_pointer",11,0,4,0,1905}, {"probability_levels",14,1,8,0,1313,kw_29,0.,0.,0.,0,"{Probability levels} MethodCommands.html#MethodNonD"}, {"response_levels",14,2,3,0,1221,kw_203}, {"rng",8,2,10,0,1321,kw_30,0.,0.,0.,0,"{Random number generator} MethodCommands.html#MethodNonDMC"}, {"samples",9,0,5,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,6,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"} }
static KeyWord kw_205 [static] |
{ {"num_reliability_levels",13,0,1,0,1043,0,0.,0.,0.,0,"{Number of reliability levels} MethodCommands.html#MethodNonD"} }
static KeyWord kw_206 [static] |
{ {"parallel",8,0,1,1,1061}, {"series",8,0,1,1,1059} }
static KeyWord kw_207 [static] |
{ {"gen_reliabilities",8,0,1,1,1055}, {"probabilities",8,0,1,1,1051}, {"reliabilities",8,0,1,1,1053}, {"system",8,2,2,0,1057,kw_206} }
static KeyWord kw_208 [static] |
{ {"compute",8,4,2,0,1049,kw_207,0.,0.,0.,0,"{Target statistics for response levels} MethodCommands.html#MethodNonD"}, {"num_response_levels",13,0,1,0,1047,0,0.,0.,0.,0,"{Number of response levels} MethodCommands.html#MethodNonD"} }
static KeyWord kw_209 [static] |
{ {"eval_id",8,0,2,0,875}, {"header",8,0,1,0,873}, {"interface_id",8,0,3,0,877} }
static KeyWord kw_210 [static] |
{ {"active_only",8,0,2,0,881}, {"annotated",8,0,1,0,869}, {"custom_annotated",8,3,1,0,871,kw_209}, {"freeform",8,0,1,0,879} }
static KeyWord kw_211 [static] |
{ {"advancements",9,0,1,0,807}, {"soft_convergence_limit",9,0,2,0,809} }
static KeyWord kw_212 [static] |
{ {"adapted",8,2,1,1,805,kw_211}, {"tensor_product",8,0,1,1,801}, {"total_order",8,0,1,1,803} }
static KeyWord kw_213 [static] |
{
{"noise_tolerance",14,0,1,0,831}
}
static KeyWord kw_214 [static] |
{
{"noise_tolerance",14,0,1,0,835}
}
static KeyWord kw_215 [static] |
{ {"l2_penalty",10,0,2,0,841,0,0.,0.,0.,0,"{l2_penalty used for elastic net modification of LASSO} MethodCommands.html#MethodNonDPCE"}, {"noise_tolerance",14,0,1,0,839} }
static KeyWord kw_216 [static] |
{ {"equality_constrained",8,0,1,0,821}, {"svd",8,0,1,0,819} }
static KeyWord kw_217 [static] |
{
{"noise_tolerance",14,0,1,0,825}
}
static KeyWord kw_218 [static] |
{ {"basis_pursuit",8,0,2,0,827,0,0.,0.,0.,0,"{L1 minimization via Basis Pursuit (BP)} MethodCommands.html#MethodNonDPCE"}, {"basis_pursuit_denoising",8,1,2,0,829,kw_213,0.,0.,0.,0,"{L1 minimization via Basis Pursuit DeNoising (BPDN)} MethodCommands.html#MethodNonDPCE"}, {"bp",0,0,2,0,826}, {"bpdn",0,1,2,0,828,kw_213}, {"cross_validation",8,0,3,0,843,0,0.,0.,0.,0,"{Specify whether to use cross validation} MethodCommands.html#MethodNonDPCE"}, {"lars",0,1,2,0,832,kw_214}, {"lasso",0,2,2,0,836,kw_215}, {"least_absolute_shrinkage",8,2,2,0,837,kw_215,0.,0.,0.,0,"{L1 minimization via Least Absolute Shrinkage Operator (LASSO)} MethodCommands.html#MethodNonDPCE"}, {"least_angle_regression",8,1,2,0,833,kw_214,0.,0.,0.,0,"{L1 minimization via Least Angle Regression (LARS)} MethodCommands.html#MethodNonDPCE"}, {"least_squares",8,2,2,0,817,kw_216,0.,0.,0.,0,"{Least squares regression} MethodCommands.html#MethodNonDPCE"}, {"omp",0,1,2,0,822,kw_217}, {"orthogonal_matching_pursuit",8,1,2,0,823,kw_217,0.,0.,0.,0,"{L1 minimization via Orthogonal Matching Pursuit (OMP)} MethodCommands.html#MethodNonDPCE"}, {"ratio_order",10,0,1,0,815,0,0.,0.,0.,0,"{Order of collocation oversampling relationship} MethodCommands.html#MethodNonDPCE"}, {"reuse_points",8,0,6,0,849}, {"reuse_samples",0,0,6,0,848}, {"tensor_grid",8,0,5,0,847}, {"use_derivatives",8,0,4,0,845} }
static KeyWord kw_219 [static] |
{ {"incremental_lhs",8,0,2,0,855,0,0.,0.,0.,0,"{Use incremental LHS for expansion_samples} MethodCommands.html#MethodNonDPCE"}, {"reuse_points",8,0,1,0,853}, {"reuse_samples",0,0,1,0,852} }
static KeyWord kw_220 [static] |
{ {"basis_type",8,3,2,0,799,kw_212}, {"collocation_points",13,17,3,1,811,kw_218,0.,0.,0.,0,"{Number collocation points to estimate coeffs} MethodCommands.html#MethodNonDPCE"}, {"collocation_ratio",10,17,3,1,813,kw_218,0.,0.,0.,0,"{Collocation point oversampling ratio to estimate coeffs} MethodCommands.html#MethodNonDPCE"}, {"dimension_preference",14,0,1,0,797}, {"expansion_samples",13,3,3,1,851,kw_219,0.,0.,0.,0,"{Number simulation samples to estimate coeffs} MethodCommands.html#MethodNonDPCE"}, {"import_points_file",11,4,4,0,867,kw_210,0.,0.,0.,0,"{File name for points to be imported for forming a PCE (unstructured grid assumed)} MethodCommands.html#MethodNonDPCE"} }
static KeyWord kw_221 [static] |
{ {"eval_id",8,0,2,0,921}, {"header",8,0,1,0,919}, {"interface_id",8,0,3,0,923} }
static KeyWord kw_222 [static] |
{ {"annotated",8,0,1,0,915}, {"custom_annotated",8,3,1,0,917,kw_221}, {"freeform",8,0,1,0,925} }
static KeyWord kw_223 [static] |
{ {"collocation_points",13,0,1,1,859}, {"cross_validation",8,0,2,0,861}, {"import_points_file",11,4,5,0,867,kw_210,0.,0.,0.,0,"{File name for points to be imported for forming a PCE (unstructured grid assumed)} MethodCommands.html#MethodNonDPCE"}, {"reuse_points",8,0,4,0,865}, {"reuse_samples",0,0,4,0,864}, {"tensor_grid",13,0,3,0,863} }
static KeyWord kw_224 [static] |
{ {"decay",8,0,1,1,771}, {"generalized",8,0,1,1,773}, {"sobol",8,0,1,1,769} }
static KeyWord kw_225 [static] |
{ {"dimension_adaptive",8,3,1,1,767,kw_224}, {"uniform",8,0,1,1,765} }
static KeyWord kw_226 [static] |
{ {"adapt_import",8,0,1,1,907}, {"import",8,0,1,1,905}, {"mm_adapt_import",8,0,1,1,909}, {"refinement_samples",9,0,2,0,911,0,0.,0.,0.,0,"{Refinement samples} MethodCommands.html#MethodNonDLocalRel"} }
static KeyWord kw_227 [static] |
{ {"dimension_preference",14,0,1,0,787,0,0.,0.,0.,0,"{Dimension preference for anisotropic tensor and sparse grids} MethodCommands.html#MethodNonDPCE"}, {"nested",8,0,2,0,789}, {"non_nested",8,0,2,0,791} }
static KeyWord kw_228 [static] |
{ {"lhs",8,0,1,1,899}, {"random",8,0,1,1,901} }
static KeyWord kw_229 [static] |
{ {"dimension_preference",14,0,2,0,787,0,0.,0.,0.,0,"{Dimension preference for anisotropic tensor and sparse grids} MethodCommands.html#MethodNonDPCE"}, {"nested",8,0,3,0,789}, {"non_nested",8,0,3,0,791}, {"restricted",8,0,1,0,783}, {"unrestricted",8,0,1,0,785} }
static KeyWord kw_230 [static] |
{ {"drop_tolerance",10,0,2,0,889,0,0.,0.,0.,0,"{VBD tolerance for omitting small indices} MethodCommands.html#MethodNonDMC"}, {"interaction_order",0x19,0,1,0,887,0,0.,0.,0.,0,"{Restriction of order of VBD interations} MethodCommands.html#MethodNonDPCE"} }
static KeyWord kw_232 [static] |
{ {"previous_samples",9,0,1,1,1031,0,0.,0.,0.,0,"{Previous samples for incremental approaches} MethodCommands.html#MethodNonDMC"} }
static KeyWord kw_233 [static] |
{ {"incremental_lhs",8,1,1,1,1027,kw_232}, {"incremental_random",8,1,1,1,1029,kw_232}, {"lhs",8,0,1,1,1025}, {"random",8,0,1,1,1023} }
static KeyWord kw_234 [static] |
{
{"drop_tolerance",10,0,1,0,1035}
}
static KeyWord kw_235 [static] |
{ {"backfill",8,0,3,0,1037}, {"distribution",8,2,7,0,1307,kw_27,0.,0.,0.,0,"{Distribution type} MethodCommands.html#MethodNonD"}, {"fixed_seed",8,0,13,0,1039,0,0.,0.,0.,0,"{Fixed seed flag} MethodCommands.html#MethodNonDMC"}, {"gen_reliability_levels",14,1,9,0,1317,kw_28,0.,0.,0.,0,"{Generalized reliability levels} MethodCommands.html#MethodNonD"}, {"model_pointer",11,0,4,0,1905}, {"probability_levels",14,1,8,0,1313,kw_29,0.,0.,0.,0,"{Probability levels} MethodCommands.html#MethodNonD"}, {"reliability_levels",14,1,11,0,1041,kw_205,0.,0.,0.,0,"{Reliability levels} MethodCommands.html#MethodNonD"}, {"response_levels",14,2,12,0,1045,kw_208,0.,0.,0.,0,"{Response levels} MethodCommands.html#MethodNonD"}, {"rng",8,2,10,0,1321,kw_30,0.,0.,0.,0,"{Random number generator} MethodCommands.html#MethodNonDMC"}, {"sample_type",8,4,1,0,1021,kw_233}, {"samples",9,0,5,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,6,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"}, {"variance_based_decomp",8,1,2,0,1033,kw_234} }
static KeyWord kw_236 [static] |
{ {"eval_id",8,0,2,0,1013}, {"header",8,0,1,0,1011}, {"interface_id",8,0,3,0,1015} }
static KeyWord kw_237 [static] |
{ {"annotated",8,0,1,0,1007}, {"custom_annotated",8,3,1,0,1009,kw_236}, {"freeform",8,0,1,0,1017} }
static KeyWord kw_238 [static] |
{ {"generalized",8,0,1,1,949}, {"sobol",8,0,1,1,947} }
static KeyWord kw_239 [static] |
{ {"dimension_adaptive",8,2,1,1,945,kw_238}, {"local_adaptive",8,0,1,1,951}, {"uniform",8,0,1,1,943} }
static KeyWord kw_240 [static] |
{ {"generalized",8,0,1,1,939}, {"sobol",8,0,1,1,937} }
static KeyWord kw_241 [static] |
{ {"dimension_adaptive",8,2,1,1,935,kw_240}, {"uniform",8,0,1,1,933} }
static KeyWord kw_242 [static] |
{ {"adapt_import",8,0,1,1,999}, {"import",8,0,1,1,997}, {"mm_adapt_import",8,0,1,1,1001}, {"refinement_samples",9,0,2,0,1003} }
static KeyWord kw_243 [static] |
{ {"lhs",8,0,1,1,991}, {"random",8,0,1,1,993} }
static KeyWord kw_244 [static] |
{ {"hierarchical",8,0,2,0,969}, {"nodal",8,0,2,0,967}, {"restricted",8,0,1,0,963}, {"unrestricted",8,0,1,0,965} }
static KeyWord kw_245 [static] |
{ {"drop_tolerance",10,0,2,0,983,0,0.,0.,0.,0,"{VBD tolerance for omitting small indices} MethodCommands.html#MethodNonDSC"}, {"interaction_order",0x19,0,1,0,981,0,0.,0.,0.,0,"{Restriction of order of VBD interations} MethodCommands.html#MethodNonDSC"} }
static KeyWord kw_246 [static] |
{ {"askey",8,0,2,0,955}, {"diagonal_covariance",8,0,8,0,985}, {"dimension_preference",14,0,4,0,971,0,0.,0.,0.,0,"{Dimension preference for anisotropic tensor and sparse grids} MethodCommands.html#MethodNonDSC"}, {"distribution",8,2,15,0,1307,kw_27,0.,0.,0.,0,"{Distribution type} MethodCommands.html#MethodNonD"}, {"export_points_file",11,3,11,0,1005,kw_237,0.,0.,0.,0,"{File name for exporting approximation-based samples from evaluating the interpolant} MethodCommands.html#MethodNonDSC"}, {"fixed_seed",8,0,21,0,1039,0,0.,0.,0.,0,"{Fixed seed flag} MethodCommands.html#MethodNonDMC"}, {"full_covariance",8,0,8,0,987}, {"gen_reliability_levels",14,1,17,0,1317,kw_28,0.,0.,0.,0,"{Generalized reliability levels} MethodCommands.html#MethodNonD"}, {"h_refinement",8,3,1,0,941,kw_239}, {"model_pointer",11,0,12,0,1905}, {"nested",8,0,6,0,975}, {"non_nested",8,0,6,0,977}, {"p_refinement",8,2,1,0,931,kw_241}, {"piecewise",8,0,2,0,953}, {"probability_levels",14,1,16,0,1313,kw_29,0.,0.,0.,0,"{Probability levels} MethodCommands.html#MethodNonD"}, {"probability_refinement",8,4,10,0,995,kw_242}, {"quadrature_order",13,0,3,1,959,0,0.,0.,0.,0,"{Quadrature order for collocation points} MethodCommands.html#MethodNonDSC"}, {"reliability_levels",14,1,19,0,1041,kw_205,0.,0.,0.,0,"{Reliability levels} MethodCommands.html#MethodNonD"}, {"response_levels",14,2,20,0,1045,kw_208,0.,0.,0.,0,"{Response levels} MethodCommands.html#MethodNonD"}, {"rng",8,2,18,0,1321,kw_30,0.,0.,0.,0,"{Random number generator} MethodCommands.html#MethodNonDMC"}, {"sample_refinement",0,4,10,0,994,kw_242}, {"sample_type",8,2,9,0,989,kw_243}, {"samples",9,0,13,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,14,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"}, {"sparse_grid_level",13,4,3,1,961,kw_244,0.,0.,0.,0,"{Sparse grid level for collocation points} MethodCommands.html#MethodNonDSC"}, {"use_derivatives",8,0,5,0,973,0,0.,0.,0.,0,"{Derivative enhancement flag} MethodCommands.html#MethodNonDSC"}, {"variance_based_decomp",8,2,7,0,979,kw_245,0.,0.,0.,0,"{Variance-based decomposition (VBD)} MethodCommands.html#MethodNonDSC"}, {"wiener",8,0,2,0,957} }
static KeyWord kw_247 [static] |
{ {"misc_options",15,0,1,0,703}, {"model_pointer",11,0,2,0,1905} }
static KeyWord kw_248 [static] |
{ {"function_precision",10,0,12,0,303,0,0.,0.,0.,0,"{Function precision} MethodCommands.html#MethodNPSOLDC"}, {"linear_equality_constraint_matrix",14,0,7,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,9,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,10,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,8,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,2,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,3,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,5,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,6,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,4,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"linesearch_tolerance",10,0,13,0,305,0,0.,0.,0.,0,"{Line search tolerance} MethodCommands.html#MethodNPSOLDC"}, {"model_pointer",11,0,1,0,1905}, {"verify_level",9,0,11,0,301,0,0.,0.,0.,0,"{Gradient verification level} MethodCommands.html#MethodNPSOLDC"} }
static KeyWord kw_249 [static] |
{ {"gradient_tolerance",10,0,12,0,343}, {"linear_equality_constraint_matrix",14,0,7,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,9,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,10,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,8,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,2,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,3,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,5,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,6,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,4,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"max_step",10,0,11,0,341}, {"model_pointer",11,0,1,0,1905} }
static KeyWord kw_250 [static] |
{ {"linear_equality_constraint_matrix",14,0,8,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,10,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,11,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,9,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,3,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,4,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,6,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,7,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,5,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"model_pointer",11,0,2,0,1905}, {"search_scheme_size",9,0,1,0,347} }
static KeyWord kw_251 [static] |
{ {"argaez_tapia",8,0,1,1,333}, {"el_bakry",8,0,1,1,331}, {"van_shanno",8,0,1,1,335} }
static KeyWord kw_252 [static] |
{ {"gradient_based_line_search",8,0,1,1,323,0,0.,0.,0.,0,"[CHOOSE line search type]"}, {"tr_pds",8,0,1,1,327}, {"trust_region",8,0,1,1,325}, {"value_based_line_search",8,0,1,1,321} }
static KeyWord kw_253 [static] |
{ {"centering_parameter",10,0,4,0,339}, {"gradient_tolerance",10,0,16,0,343}, {"linear_equality_constraint_matrix",14,0,11,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,13,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,14,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,12,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,6,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,7,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,9,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,10,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,8,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"max_step",10,0,15,0,341}, {"merit_function",8,3,2,0,329,kw_251}, {"model_pointer",11,0,5,0,1905}, {"search_method",8,4,1,0,319,kw_252}, {"steplength_to_boundary",10,0,3,0,337} }
static KeyWord kw_254 [static] |
{ {"debug",8,0,1,1,89,0,0.,0.,0.,0,"[CHOOSE output level]"}, {"normal",8,0,1,1,93}, {"quiet",8,0,1,1,95}, {"silent",8,0,1,1,97}, {"verbose",8,0,1,1,91} }
static KeyWord kw_255 [static] |
{ {"model_pointer",11,0,1,0,165,0,0.,0.,0.,0,"{Identification of model by pointer} MethodCommands.html#MethodMetaMultiStart"}, {"opt_model_pointer",3,0,1,0,164} }
static KeyWord kw_256 [static] |
{ {"seed",9,0,1,0,171,0,0.,0.,0.,0,"{Seed for random weighting sets} MethodCommands.html#MethodMetaParetoSet"} }
static KeyWord kw_257 [static] |
{ {"iterator_scheduling",8,2,5,0,177,kw_148,0.,0.,0.,0,"{Message passing configuration for scheduling of iterator jobs} MethodCommands.html#MethodMeta"}, {"iterator_servers",0x19,0,4,0,175,0,0.,0.,0.,0,"{Number of iterator servers} MethodCommands.html#MethodMeta"}, {"method_name",11,2,1,1,163,kw_255,0.,0.,0.,0,"{Identification of sub-iterator by name} MethodCommands.html#MethodMetaMultiStart"}, {"method_pointer",11,0,1,1,167,0,0.,0.,0.,0,"{Identification of sub-iterator by pointer} MethodCommands.html#MethodMetaMultiStart"}, {"multi_objective_weight_sets",6,0,3,0,172}, {"opt_method_name",3,2,1,1,162,kw_255}, {"opt_method_pointer",3,0,1,1,166}, {"processors_per_iterator",0x19,0,6,0,183,0,0.,0.,0.,0,"{Number of processors per iterator server} MethodCommands.html#MethodMeta"}, {"random_weight_sets",9,1,2,0,169,kw_256,0.,0.,0.,0,"{Number of random weighting sets} MethodCommands.html#MethodMetaParetoSet"}, {"weight_sets",14,0,3,0,173,0,0.,0.,0.,0,"{List of user-specified weighting sets} MethodCommands.html#MethodMetaParetoSet"} }
static KeyWord kw_258 [static] |
{ {"model_pointer",11,0,2,0,1905}, {"partitions",13,0,1,0,1643,0,0.,0.,0.,0,"{Number of partitions} MethodCommands.html#MethodPSUADE"}, {"samples",9,0,3,0,1645,0,0.,0.,0.,0,"{Number of samples} MethodCommands.html#MethodNonDMC"}, {"seed",0x19,0,4,0,1647,0,0.,0.,0.,0,"{Refinement seed} MethodCommands.html#MethodNonDLocalRel"} }
static KeyWord kw_259 [static] |
{ {"converge_order",8,0,1,1,1899}, {"converge_qoi",8,0,1,1,1901}, {"estimate_order",8,0,1,1,1897}, {"model_pointer",11,0,3,0,1905}, {"refinement_rate",10,0,2,0,1903,0,0.,0.,0.,0,"{Refinement rate} MethodCommands.html#MethodSolnRichardson"} }
static KeyWord kw_260 [static] |
{ {"num_generations",0x29,0,2,0,473}, {"percent_change",10,0,1,0,471} }
static KeyWord kw_261 [static] |
{ {"num_generations",0x29,0,2,0,467,0,0.,0.,0.,0,"{Number of generations (for convergence test) } MethodCommands.html#MethodJEGASOGA"}, {"percent_change",10,0,1,0,465,0,0.,0.,0.,0,"{Percent change in fitness} MethodCommands.html#MethodJEGASOGA"} }
static KeyWord kw_262 [static] |
{ {"average_fitness_tracker",8,2,1,1,469,kw_260}, {"best_fitness_tracker",8,2,1,1,463,kw_261} }
static KeyWord kw_263 [static] |
{ {"constraint_penalty",10,0,2,0,449,0,0.,0.,0.,0,"{Constraint penalty in merit function} MethodCommands.html#MethodJEGASOGA"}, {"merit_function",8,0,1,1,447} }
static KeyWord kw_264 [static] |
{ {"elitist",8,0,1,1,453}, {"favor_feasible",8,0,1,1,455}, {"roulette_wheel",8,0,1,1,457}, {"unique_roulette_wheel",8,0,1,1,459} }
static KeyWord kw_265 [static] |
{ {"convergence_type",8,2,3,0,461,kw_262,0.,0.,0.,0,"{Convergence type} MethodCommands.html#MethodJEGASOGA"}, {"crossover_type",8,5,18,0,489,kw_182,0.,0.,0.,0,"{Crossover type} MethodCommands.html#MethodJEGADC"}, {"fitness_type",8,2,1,0,445,kw_263,0.,0.,0.,0,"{Fitness type} MethodCommands.html#MethodJEGASOGA"}, {"initialization_type",8,3,17,0,481,kw_183,0.,0.,0.,0,"{Initialization type} MethodCommands.html#MethodJEGADC"}, {"linear_equality_constraint_matrix",14,0,10,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,12,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,13,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,11,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,5,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,6,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,8,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,9,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,7,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"log_file",11,0,15,0,477,0,0.,0.,0.,0,"{Log file} MethodCommands.html#MethodJEGADC"}, {"model_pointer",11,0,4,0,1905}, {"mutation_type",8,6,19,0,505,kw_185,0.,0.,0.,0,"{Mutation type} MethodCommands.html#MethodJEGADC"}, {"population_size",0x29,0,14,0,475,0,0.,0.,0.,0,"{Number of population members} MethodCommands.html#MethodJEGADC"}, {"print_each_pop",8,0,16,0,479,0,0.,0.,0.,0,"{Population output} MethodCommands.html#MethodJEGADC"}, {"replacement_type",8,4,2,0,451,kw_264,0.,0.,0.,0,"{Replacement type} MethodCommands.html#MethodJEGASOGA"}, {"seed",0x19,0,20,0,521,0,0.,0.,0.,0,"{Random seed} MethodCommands.html#MethodJEGADC"} }
static KeyWord kw_266 [static] |
{ {"function_precision",10,0,13,0,303,0,0.,0.,0.,0,"{Function precision} MethodCommands.html#MethodNPSOLDC"}, {"linear_equality_constraint_matrix",14,0,8,0,533,0,0.,0.,0.,0,"{Linear equality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_equality_scale_types",15,0,10,0,537,0,0.,0.,0.,0,"{Linear equality scaling types} MethodCommands.html#MethodMin"}, {"linear_equality_scales",14,0,11,0,539,0,0.,0.,0.,0,"{Linear equality scales} MethodCommands.html#MethodMin"}, {"linear_equality_targets",14,0,9,0,535,0,0.,0.,0.,0,"{Linear equality targets} MethodCommands.html#MethodMin"}, {"linear_inequality_constraint_matrix",14,0,3,0,523,0,0.,0.,0.,0,"{Linear inequality coefficient matrix} MethodCommands.html#MethodMin"}, {"linear_inequality_lower_bounds",14,0,4,0,525,0,0.,0.,0.,0,"{Linear inequality lower bounds} MethodCommands.html#MethodMin"}, {"linear_inequality_scale_types",15,0,6,0,529,0,0.,0.,0.,0,"{Linear inequality scaling types} MethodCommands.html#MethodMin"}, {"linear_inequality_scales",14,0,7,0,531,0,0.,0.,0.,0,"{Linear inequality scales} MethodCommands.html#MethodMin"}, {"linear_inequality_upper_bounds",14,0,5,0,527,0,0.,0.,0.,0,"{Linear inequality upper bounds} MethodCommands.html#MethodMin"}, {"linesearch_tolerance",10,0,14,0,305,0,0.,0.,0.,0,"{Line search tolerance} MethodCommands.html#MethodNPSOLDC"}, {"model_pointer",11,0,2,0,1905}, {"nlssol",8,0,1,1,299}, {"npsol",8,0,1,1,297}, {"verify_level",9,0,12,0,301,0,0.,0.,0.,0,"{Gradient verification level} MethodCommands.html#MethodNPSOLDC"} }
static KeyWord kw_267 [static] |
{ {"approx_method_name",3,0,1,1,250}, {"approx_method_pointer",3,0,1,1,248}, {"approx_model_pointer",3,0,2,2,252}, {"method_name",11,0,1,1,251}, {"method_pointer",11,0,1,1,249}, {"model_pointer",11,0,2,2,253}, {"replace_points",8,0,3,0,255,0,0.,0.,0.,0,"{Replace points used in surrogate construction with best points from previous iteration} MethodCommands.html#MethodSBG"} }
static KeyWord kw_268 [static] |
{ {"filter",8,0,1,1,241,0,0.,0.,0.,0,"@[CHOOSE acceptance logic]"}, {"tr_ratio",8,0,1,1,239} }
static KeyWord kw_269 [static] |
{ {"augmented_lagrangian_objective",8,0,1,1,217,0,0.,0.,0.,0,"[CHOOSE objective formulation]"}, {"lagrangian_objective",8,0,1,1,219}, {"linearized_constraints",8,0,2,2,223,0,0.,0.,0.,0,"[CHOOSE constraint formulation]"}, {"no_constraints",8,0,2,2,225}, {"original_constraints",8,0,2,2,221,0,0.,0.,0.,0,"@"}, {"original_primary",8,0,1,1,213,0,0.,0.,0.,0,"@"}, {"single_objective",8,0,1,1,215} }
static KeyWord kw_270 [static] |
{
{"homotopy",8,0,1,1,245}
}
static KeyWord kw_271 [static] |
{ {"adaptive_penalty_merit",8,0,1,1,231,0,0.,0.,0.,0,"[CHOOSE merit function]"}, {"augmented_lagrangian_merit",8,0,1,1,235,0,0.,0.,0.,0,"@"}, {"lagrangian_merit",8,0,1,1,233}, {"penalty_merit",8,0,1,1,229} }
static KeyWord kw_272 [static] |
{ {"contract_threshold",10,0,3,0,203,0,0.,0.,0.,0,"{Shrink trust region if trust region ratio is below this value} MethodCommands.html#MethodSBL"}, {"contraction_factor",10,0,5,0,207,0,0.,0.,0.,0,"{Trust region contraction factor} MethodCommands.html#MethodSBL"}, {"expand_threshold",10,0,4,0,205,0,0.,0.,0.,0,"{Expand trust region if trust region ratio is above this value} MethodCommands.html#MethodSBL"}, {"expansion_factor",10,0,6,0,209,0,0.,0.,0.,0,"{Trust region expansion factor} MethodCommands.html#MethodSBL"}, {"initial_size",10,0,1,0,199,0,0.,0.,0.,0,"{Trust region initial size (relative to bounds)} MethodCommands.html#MethodSBL"}, {"minimum_size",10,0,2,0,201,0,0.,0.,0.,0,"{Trust region minimum size} MethodCommands.html#MethodSBL"} }
static KeyWord kw_273 [static] |
{ {"acceptance_logic",8,2,8,0,237,kw_268,0.,0.,0.,0,"{SBL iterate acceptance logic} MethodCommands.html#MethodSBL"}, {"approx_method_name",3,0,1,1,188}, {"approx_method_pointer",3,0,1,1,186}, {"approx_model_pointer",3,0,2,2,190}, {"approx_subproblem",8,7,6,0,211,kw_269,0.,0.,0.,0,"{Approximate subproblem formulation} MethodCommands.html#MethodSBL"}, {"constraint_relax",8,1,9,0,243,kw_270,0.,0.,0.,0,"{SBL constraint relaxation method for infeasible iterates} MethodCommands.html#MethodSBL"}, {"merit_function",8,4,7,0,227,kw_271,0.,0.,0.,0,"{SBL merit function} MethodCommands.html#MethodSBL"}, {"method_name",11,0,1,1,189,0,0.,0.,0.,0,"{Identification of minimizer by name} MethodCommands.html#MethodMetaParetoSet"}, {"method_pointer",11,0,1,1,187,0,0.,0.,0.,0,"{Identification of minimizer by pointer} MethodCommands.html#MethodMetaParetoSet"}, {"model_pointer",11,0,2,2,191,0,0.,0.,0.,0,"{Identification of model by pointer} MethodCommands.html#MethodMetaParetoSet"}, {"soft_convergence_limit",9,0,3,0,193,0,0.,0.,0.,0,"{Soft convergence limit for SBL iterations} MethodCommands.html#MethodSBL"}, {"trust_region",8,6,5,0,197,kw_272,0.,0.,0.,0,"{Trust region group specification} MethodCommands.html#MethodSBL"}, {"truth_surrogate_bypass",8,0,4,0,195,0,0.,0.,0.,0,"{Flag for bypassing lower level surrogates in truth verifications} MethodCommands.html#MethodSBL"} }
static KeyWord kw_274 [static] |
{ {"final_point",14,0,1,1,1859,0,0.,0.,0.,0,"[CHOOSE final pt or increment]{Termination point of vector} MethodCommands.html#MethodPSVPS"}, {"model_pointer",11,0,3,0,1905}, {"num_steps",9,0,2,2,1863,0,0.,0.,0.,0,"{Number of steps along vector} MethodCommands.html#MethodPSVPS"}, {"step_vector",14,0,1,1,1861,0,0.,0.,0.,0,"{Step vector} MethodCommands.html#MethodPSVPS"} }
static KeyWord kw_276 [static] |
{ {"optional_interface_responses_pointer",11,0,1,0,2153,0,0.,0.,0.,0,"{Responses pointer for nested model optional interfaces} ModelCommands.html#ModelNested"} }
static KeyWord kw_277 [static] |
{ {"master",8,0,1,1,2161}, {"peer",8,0,1,1,2163} }
static KeyWord kw_278 [static] |
{ {"iterator_scheduling",8,2,2,0,2159,kw_277}, {"iterator_servers",0x19,0,1,0,2157}, {"primary_response_mapping",14,0,6,0,2171,0,0.,0.,0.,0,"{Primary response mappings for nested models} ModelCommands.html#ModelNested"}, {"primary_variable_mapping",15,0,4,0,2167,0,0.,0.,0.,0,"{Primary variable mappings for nested models} ModelCommands.html#ModelNested"}, {"processors_per_iterator",0x19,0,3,0,2165}, {"secondary_response_mapping",14,0,7,0,2173,0,0.,0.,0.,0,"{Secondary response mappings for nested models} ModelCommands.html#ModelNested"}, {"secondary_variable_mapping",15,0,5,0,2169,0,0.,0.,0.,0,"{Secondary variable mappings for nested models} ModelCommands.html#ModelNested"} }
static KeyWord kw_279 [static] |
{ {"optional_interface_pointer",11,1,1,0,2151,kw_276,0.,0.,0.,0,"{Optional interface set pointer} ModelCommands.html#ModelNested"}, {"sub_method_pointer",11,7,2,1,2155,kw_278,0.,0.,0.,0,"{Sub-method pointer for nested models} ModelCommands.html#ModelNested"} }
static KeyWord kw_280 [static] |
{ {"interface_pointer",11,0,1,0,1919,0,0.,0.,0.,0,"{Interface set pointer} ModelCommands.html#ModelSingle"} }
static KeyWord kw_281 [static] |
{ {"eval_id",8,0,2,0,2111}, {"header",8,0,1,0,2109}, {"interface_id",8,0,3,0,2113} }
static KeyWord kw_282 [static] |
{ {"active_only",8,0,2,0,2117}, {"annotated",8,0,1,0,2105}, {"custom_annotated",8,3,1,0,2107,kw_281}, {"freeform",8,0,1,0,2115} }
static KeyWord kw_283 [static] |
{ {"additive",8,0,2,2,2087,0,0.,0.,0.,0,"[CHOOSE correction type]"}, {"combined",8,0,2,2,2091}, {"first_order",8,0,1,1,2083,0,0.,0.,0.,0,"[CHOOSE correction order]"}, {"multiplicative",8,0,2,2,2089}, {"second_order",8,0,1,1,2085}, {"zeroth_order",8,0,1,1,2081} }
static KeyWord kw_284 [static] |
{ {"folds",9,0,1,0,2097,0,0.,0.,0.,0,"{Number cross validation folds} ModelCommands.html#ModelSurrG"}, {"percent",10,0,1,0,2099,0,0.,0.,0.,0,"{Percent points per CV fold} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_285 [static] |
{ {"cross_validation",8,2,1,0,2095,kw_284,0.,0.,0.,0,"{Perform cross validation} ModelCommands.html#ModelSurrG"}, {"press",8,0,2,0,2101,0,0.,0.,0.,0,"{Perform PRESS cross validation} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_286 [static] |
{ {"eval_id",8,0,2,0,2071}, {"header",8,0,1,0,2069}, {"interface_id",8,0,3,0,2073} }
static KeyWord kw_287 [static] |
{ {"annotated",8,0,1,0,2065}, {"custom_annotated",8,3,1,0,2067,kw_286}, {"freeform",8,0,1,0,2075} }
static KeyWord kw_288 [static] |
{ {"constant",8,0,1,1,1935}, {"linear",8,0,1,1,1937}, {"reduced_quadratic",8,0,1,1,1939} }
static KeyWord kw_289 [static] |
{ {"point_selection",8,0,1,0,1931,0,0.,0.,0.,0,"{GP point selection} ModelCommands.html#ModelSurrG"}, {"trend",8,3,2,0,1933,kw_288,0.,0.,0.,0,"{GP trend function} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_290 [static] |
{ {"constant",8,0,1,1,1945}, {"linear",8,0,1,1,1947}, {"quadratic",8,0,1,1,1951}, {"reduced_quadratic",8,0,1,1,1949} }
static KeyWord kw_291 [static] |
{ {"correlation_lengths",14,0,5,0,1961,0,0.,0.,0.,0,"{Surfpack GP correlation lengths} ModelCommands.html#ModelSurrG"}, {"export_model_file",11,0,6,0,1963}, {"find_nugget",9,0,4,0,1959,0,0.,0.,0.,0,"{Surfpack finds the optimal nugget } ModelCommands.html#ModelSurrG"}, {"max_trials",0x19,0,3,0,1955,0,0.,0.,0.,0,"{Surfpack GP maximum trials} ModelCommands.html#ModelSurrG"}, {"nugget",0x1a,0,4,0,1957,0,0.,0.,0.,0,"{Surfpack user-specified nugget } ModelCommands.html#ModelSurrG"}, {"optimization_method",11,0,2,0,1953,0,0.,0.,0.,0,"{Surfpack GP optimization method} ModelCommands.html#ModelSurrG"}, {"trend",8,4,1,0,1943,kw_290,0.,0.,0.,0,"{Surfpack GP trend function} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_292 [static] |
{ {"dakota",8,2,1,1,1929,kw_289}, {"surfpack",8,7,1,1,1941,kw_291} }
static KeyWord kw_293 [static] |
{ {"eval_id",8,0,2,0,2055}, {"header",8,0,1,0,2053}, {"interface_id",8,0,3,0,2057} }
static KeyWord kw_294 [static] |
{ {"active_only",8,0,2,0,2061}, {"annotated",8,0,1,0,2049,0,0.,0.,0.,0,"{Challenge file in annotated format} ModelCommands.html#ModelSurrG"}, {"custom_annotated",8,3,1,0,2051,kw_293}, {"freeform",8,0,1,0,2059,0,0.,0.,0.,0,"{Challenge file in freeform format} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_295 [static] |
{ {"cubic",8,0,1,1,1973}, {"linear",8,0,1,1,1971} }
static KeyWord kw_296 [static] |
{ {"export_model_file",11,0,3,0,1975}, {"interpolation",8,2,2,0,1969,kw_295,0.,0.,0.,0,"{MARS interpolation} ModelCommands.html#ModelSurrG"}, {"max_bases",9,0,1,0,1967,0,0.,0.,0.,0,"{MARS maximum bases} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_297 [static] |
{ {"export_model_file",11,0,3,0,1983}, {"poly_order",9,0,1,0,1979,0,0.,0.,0.,0,"{MLS polynomial order} ModelCommands.html#ModelSurrG"}, {"weight_function",9,0,2,0,1981,0,0.,0.,0.,0,"{MLS weight function} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_298 [static] |
{ {"export_model_file",11,0,4,0,1993}, {"max_nodes",9,0,1,0,1987}, {"nodes",1,0,1,0,1986}, {"random_weight",9,0,3,0,1991,0,0.,0.,0.,0,"{ANN random weight} ModelCommands.html#ModelSurrG"}, {"range",10,0,2,0,1989,0,0.,0.,0.,0,"{ANN range} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_299 [static] |
{ {"gradient_threshold",10,0,1,1,2027}, {"jump_threshold",10,0,1,1,2025} }
static KeyWord kw_300 [static] |
{ {"cell_type",11,0,1,0,2019}, {"discontinuity_detection",8,2,3,0,2023,kw_299}, {"support_layers",9,0,2,0,2021} }
static KeyWord kw_301 [static] |
{ {"cubic",8,0,1,1,2013,0,0.,0.,0.,0,"[CHOOSE polynomial order]"}, {"export_model_file",11,0,2,0,2015}, {"linear",8,0,1,1,2009}, {"quadratic",8,0,1,1,2011} }
static KeyWord kw_302 [static] |
{ {"bases",9,0,1,0,1997,0,0.,0.,0.,0,"{RBF number of bases} ModelCommands.html#ModelSurrG"}, {"export_model_file",11,0,5,0,2005}, {"max_pts",9,0,2,0,1999,0,0.,0.,0.,0,"{RBF maximum points} ModelCommands.html#ModelSurrG"}, {"max_subsets",9,0,4,0,2003}, {"min_partition",9,0,3,0,2001,0,0.,0.,0.,0,"{RBF minimum partitions} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_303 [static] |
{ {"all",8,0,1,1,2041}, {"none",8,0,1,1,2045}, {"region",8,0,1,1,2043} }
static KeyWord kw_304 [static] |
{ {"actual_model_pointer",11,0,4,0,2037,0,0.,0.,0.,0,"{Pointer to the truth model specification} ModelCommands.html#ModelSurrMP"}, {"challenge_points_file",11,4,11,0,2103,kw_282,0.,0.,0.,0,"{Challenge file for surrogate metrics} ModelCommands.html#ModelSurrG"}, {"correction",8,6,9,0,2079,kw_283,0.,0.,0.,0,"{Surrogate correction approach} ModelCommands.html#ModelSurrG"}, {"dace_method_pointer",11,0,4,0,2035,0,0.,0.,0.,0,"{Design of experiments method pointer} ModelCommands.html#ModelSurrG"}, {"diagnostics",7,2,10,0,2092,kw_285}, {"export_points_file",11,3,7,0,2063,kw_287,0.,0.,0.,0,"{File export of global approximation-based sample results} ModelCommands.html#ModelSurrG"}, {"gaussian_process",8,2,1,1,1927,kw_292,0.,0.,0.,0,"[CHOOSE surrogate type]{Dakota Gaussian process} ModelCommands.html#ModelSurrG"}, {"import_points_file",11,4,6,0,2047,kw_294,0.,0.,0.,0,"{File import of samples for global approximation builds} ModelCommands.html#ModelSurrG"}, {"kriging",0,2,1,1,1926,kw_292}, {"mars",8,3,1,1,1965,kw_296,0.,0.,0.,0,"{Multivariate adaptive regression splines} ModelCommands.html#ModelSurrG"}, {"metrics",15,2,10,0,2093,kw_285,0.,0.,0.,0,"{Compute surrogate diagnostics} ModelCommands.html#ModelSurrG"}, {"minimum_points",8,0,3,0,2031}, {"moving_least_squares",8,3,1,1,1977,kw_297,0.,0.,0.,0,"{Moving least squares} ModelCommands.html#ModelSurrG"}, {"neural_network",8,5,1,1,1985,kw_298,0.,0.,0.,0,"{Artificial neural network} ModelCommands.html#ModelSurrG"}, {"piecewise_decomposition",8,3,2,0,2017,kw_300}, {"polynomial",8,4,1,1,2007,kw_301,0.,0.,0.,0,"{Polynomial} ModelCommands.html#ModelSurrG"}, {"radial_basis",8,5,1,1,1995,kw_302}, {"recommended_points",8,0,3,0,2033}, {"reuse_points",8,3,5,0,2039,kw_303}, {"reuse_samples",0,3,5,0,2038,kw_303}, {"samples_file",3,4,6,0,2046,kw_294}, {"total_points",9,0,3,0,2029}, {"use_derivatives",8,0,8,0,2077,0,0.,0.,0.,0,"{Surfpack GP gradient enhancement} ModelCommands.html#ModelSurrG"} }
static KeyWord kw_305 [static] |
{ {"additive",8,0,2,2,2143,0,0.,0.,0.,0,"[CHOOSE correction type]"}, {"combined",8,0,2,2,2147}, {"first_order",8,0,1,1,2139,0,0.,0.,0.,0,"[CHOOSE correction order]"}, {"multiplicative",8,0,2,2,2145}, {"second_order",8,0,1,1,2141}, {"zeroth_order",8,0,1,1,2137} }
static KeyWord kw_306 [static] |
{ {"correction",8,6,3,3,2135,kw_305,0.,0.,0.,0,"{Surrogate correction approach} ModelCommands.html#ModelSurrH"}, {"high_fidelity_model_pointer",11,0,2,2,2133,0,0.,0.,0.,0,"{Pointer to the high fidelity model specification} ModelCommands.html#ModelSurrH"}, {"low_fidelity_model_pointer",11,0,1,1,2131,0,0.,0.,0.,0,"{Pointer to the low fidelity model specification} ModelCommands.html#ModelSurrH"} }
static KeyWord kw_307 [static] |
{ {"actual_model_pointer",11,0,2,2,2127,0,0.,0.,0.,0,"{Pointer to the truth model specification} ModelCommands.html#ModelSurrL"}, {"taylor_series",8,0,1,1,2125,0,0.,0.,0.,0,"{Taylor series local approximation } ModelCommands.html#ModelSurrL"} }
static KeyWord kw_308 [static] |
{ {"actual_model_pointer",11,0,2,2,2127,0,0.,0.,0.,0,"{Pointer to the truth model specification} ModelCommands.html#ModelSurrL"}, {"tana",8,0,1,1,2121,0,0.,0.,0.,0,"{Two-point adaptive nonlinear approximation } ModelCommands.html#ModelSurrMP"} }
static KeyWord kw_309 [static] |
{ {"global",8,23,2,1,1925,kw_304,0.,0.,0.,0,"[CHOOSE surrogate category]{Global approximations } ModelCommands.html#ModelSurrG"}, {"hierarchical",8,3,2,1,2129,kw_306,0.,0.,0.,0,"{Hierarchical approximation } ModelCommands.html#ModelSurrH"}, {"id_surrogates",13,0,1,0,1923,0,0.,0.,0.,0,"{Surrogate response ids} ModelCommands.html#ModelSurrogate"}, {"local",8,2,2,1,2123,kw_307,0.,0.,0.,0,"{Local approximation} ModelCommands.html#ModelSurrL"}, {"multipoint",8,2,2,1,2119,kw_308,0.,0.,0.,0,"{Multipoint approximation} ModelCommands.html#ModelSurrMP"} }
static KeyWord kw_310 [static] |
{ {"hierarchical_tagging",8,0,4,0,1915,0,0.,0.,0.,0,"{Hierarchical evaluation tags} ModelCommands.html#ModelIndControl"}, {"id_model",11,0,1,0,1909,0,0.,0.,0.,0,"{Model set identifier} ModelCommands.html#ModelIndControl"}, {"nested",8,2,5,1,2149,kw_279,0.,0.,0.,0,"[CHOOSE model type]"}, {"responses_pointer",11,0,3,0,1913,0,0.,0.,0.,0,"{Responses set pointer} ModelCommands.html#ModelIndControl"}, {"single",8,1,5,1,1917,kw_280,0.,0.,0.,0,"@"}, {"surrogate",8,5,5,1,1921,kw_309}, {"variables_pointer",11,0,2,0,1911,0,0.,0.,0.,0,"{Variables set pointer} ModelCommands.html#ModelIndControl"} }
static KeyWord kw_311 [static] |
{ {"exp_id",8,0,2,0,2817}, {"header",8,0,1,0,2815} }
static KeyWord kw_312 [static] |
{ {"annotated",8,0,1,0,2811,0,0.,0.,0.,0,"{Data file in annotated format} RespCommands.html#RespFnLS"}, {"custom_annotated",8,2,1,0,2813,kw_311}, {"freeform",8,0,1,0,2819,0,0.,0.,0.,0,"{Data file in freeform format} RespCommands.html#RespFnLS"} }
static KeyWord kw_313 [static] |
{ {"interpolate",8,0,5,0,2821}, {"num_config_variables",0x29,0,2,0,2805,0,0.,0.,0.,0,"{Configuration variable columns in file} RespCommands.html#RespFnLS"}, {"num_experiments",0x29,0,1,0,2803,0,0.,0.,0.,0,"{Experiments in file} RespCommands.html#RespFnLS"}, {"read_field_coordinates",8,0,6,0,2823}, {"scalar_data_file",11,3,4,0,2809,kw_312}, {"variance_type",0x80f,0,3,0,2807,0,0.,0.,0.,0,0,0,"field_calibration_terms"} }
static KeyWord kw_314 [static] |
{ {"exp_id",8,0,2,0,2833}, {"header",8,0,1,0,2831} }
static KeyWord kw_315 [static] |
{ {"annotated",8,0,1,0,2827}, {"custom_annotated",8,2,1,0,2829,kw_314}, {"freeform",8,0,1,0,2835}, {"num_config_variables",0x29,0,3,0,2839}, {"num_experiments",0x29,0,2,0,2837}, {"variance_type",0x80f,0,4,0,2841,0,0.,0.,0.,0,0,0,"calibration_terms"} }
static KeyWord kw_316 [static] |
{ {"coordinate_data_file",11,0,3,0,2793}, {"coordinate_list",14,0,3,0,2791}, {"lengths",13,0,1,1,2787,0,0.,0.,0.,0,0,0,"calibration_terms"}, {"num_coordinates_per_field",13,0,2,0,2789} }
static KeyWord kw_317 [static] |
{ {"nonlinear_equality_scale_types",0x807,0,2,0,2856,0,0.,0.,0.,0,0,0,"nonlinear_equality_constraints"}, {"nonlinear_equality_scales",0x806,0,3,0,2858,0,0.,0.,0.,0,0,0,"nonlinear_equality_constraints"}, {"nonlinear_equality_targets",6,0,1,0,2854,0,0.,0.,0.,0,0,0,"nonlinear_equality_constraints"}, {"scale_types",0x80f,0,2,0,2857,0,0.,0.,0.,0,0,0,"nonlinear_equality_constraints"}, {"scales",0x80e,0,3,0,2859,0,0.,0.,0.,0,0,0,"nonlinear_equality_constraints"}, {"targets",14,0,1,0,2855,0,0.,0.,0.,0,"{Nonlinear equality targets} RespCommands.html#RespFnLS",0,"nonlinear_equality_constraints"} }
static KeyWord kw_318 [static] |
{ {"lower_bounds",14,0,1,0,2845,0,0.,0.,0.,0,"{Nonlinear inequality lower bounds} RespCommands.html#RespFnLS",0,"nonlinear_inequality_constraints"}, {"nonlinear_inequality_lower_bounds",6,0,1,0,2844,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"nonlinear_inequality_scale_types",0x807,0,3,0,2848,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"nonlinear_inequality_scales",0x806,0,4,0,2850,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"nonlinear_inequality_upper_bounds",6,0,2,0,2846,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"scale_types",0x80f,0,3,0,2849,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"scales",0x80e,0,4,0,2851,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"upper_bounds",14,0,2,0,2847,0,0.,0.,0.,0,"{Nonlinear inequality upper bounds} RespCommands.html#RespFnLS",0,"nonlinear_inequality_constraints"} }
static KeyWord kw_319 [static] |
{ {"calibration_data",8,6,6,0,2801,kw_313}, {"calibration_data_file",11,6,6,0,2825,kw_315,0.,0.,0.,0,"{Calibration data file name} RespCommands.html#RespFnLS"}, {"calibration_term_scale_types",0x807,0,3,0,2794,0,0.,0.,0.,0,0,0,"calibration_terms"}, {"calibration_term_scales",0x806,0,4,0,2796,0,0.,0.,0.,0,0,0,"calibration_terms"}, {"calibration_weights",6,0,5,0,2798,0,0.,0.,0.,0,0,0,"calibration_terms"}, {"field_calibration_terms",0x29,4,2,0,2785,kw_316}, {"least_squares_data_file",3,6,6,0,2824,kw_315}, {"least_squares_term_scale_types",0x807,0,3,0,2794,0,0.,0.,0.,0,0,0,"calibration_terms"}, {"least_squares_term_scales",0x806,0,4,0,2796,0,0.,0.,0.,0,0,0,"calibration_terms"}, {"least_squares_weights",6,0,5,0,2798,0,0.,0.,0.,0,0,0,"calibration_terms"}, {"nonlinear_equality_constraints",0x29,6,8,0,2853,kw_317,0.,0.,0.,0,"{Number of nonlinear equality constraints} RespCommands.html#RespFnLS"}, {"nonlinear_inequality_constraints",0x29,8,7,0,2843,kw_318,0.,0.,0.,0,"{Number of nonlinear inequality constraints} RespCommands.html#RespFnLS"}, {"num_nonlinear_equality_constraints",0x21,6,8,0,2852,kw_317}, {"num_nonlinear_inequality_constraints",0x21,8,7,0,2842,kw_318}, {"primary_scale_types",0x80f,0,3,0,2795,0,0.,0.,0.,0,"{Calibration scaling types} RespCommands.html#RespFnLS",0,"calibration_terms"}, {"primary_scales",0x80e,0,4,0,2797,0,0.,0.,0.,0,"{Calibration scales} RespCommands.html#RespFnLS",0,"calibration_terms"}, {"scalar_calibration_terms",0x29,0,1,0,2783}, {"weights",14,0,5,0,2799,0,0.,0.,0.,0,"{Calibration term weights} RespCommands.html#RespFnLS",0,"calibration_terms"} }
static KeyWord kw_320 [static] |
{ {"absolute",8,0,2,0,2895}, {"bounds",8,0,2,0,2897}, {"ignore_bounds",8,0,1,0,2891,0,0.,0.,0.,0,"{Ignore variable bounds} RespCommands.html#RespGradMixed"}, {"relative",8,0,2,0,2893} }
static KeyWord kw_321 [static] |
{ {"central",8,0,6,0,2905,0,0.,0.,0.,0,"[CHOOSE difference interval]"}, {"dakota",8,4,4,0,2889,kw_320,0.,0.,0.,0,"@[CHOOSE gradient source]{Interval scaling type} RespCommands.html#RespGradNum"}, {"fd_gradient_step_size",6,0,7,0,2906}, {"fd_step_size",14,0,7,0,2907,0,0.,0.,0.,0,"{Finite difference step size} RespCommands.html#RespGradMixed"}, {"forward",8,0,6,0,2903,0,0.,0.,0.,0,"@"}, {"id_analytic_gradients",13,0,2,2,2883,0,0.,0.,0.,0,"{Analytic derivatives function list} RespCommands.html#RespGradMixed"}, {"id_numerical_gradients",13,0,1,1,2881,0,0.,0.,0.,0,"{Numerical derivatives function list} RespCommands.html#RespGradMixed"}, {"interval_type",8,0,5,0,2901,0,0.,0.,0.,0,"{Interval type} RespCommands.html#RespGradNum"}, {"method_source",8,0,3,0,2887,0,0.,0.,0.,0,"{Method source} RespCommands.html#RespGradNum"}, {"vendor",8,0,4,0,2899} }
static KeyWord kw_322 [static] |
{ {"fd_hessian_step_size",6,0,1,0,2938}, {"fd_step_size",14,0,1,0,2939,0,0.,0.,0.,0,"{Finite difference step size} RespCommands.html#RespHessMixed"} }
static KeyWord kw_323 [static] |
{ {"damped",8,0,1,0,2955,0,0.,0.,0.,0,"{Numerical safeguarding of BFGS update} RespCommands.html#RespHessMixed"} }
static KeyWord kw_324 [static] |
{ {"bfgs",8,1,1,1,2953,kw_323,0.,0.,0.,0,"[CHOOSE Hessian approx.]"}, {"sr1",8,0,1,1,2957} }
static KeyWord kw_325 [static] |
{ {"absolute",8,0,2,0,2943}, {"bounds",8,0,2,0,2945}, {"central",8,0,3,0,2949,0,0.,0.,0.,0,"[CHOOSE difference interval]"}, {"forward",8,0,3,0,2947,0,0.,0.,0.,0,"@"}, {"id_analytic_hessians",13,0,5,0,2959,0,0.,0.,0.,0,"{Analytic Hessians function list} RespCommands.html#RespHessMixed"}, {"id_numerical_hessians",13,2,1,0,2937,kw_322,0.,0.,0.,0,"{Numerical Hessians function list} RespCommands.html#RespHessMixed"}, {"id_quasi_hessians",13,2,4,0,2951,kw_324,0.,0.,0.,0,"{Quasi Hessians function list} RespCommands.html#RespHessMixed"}, {"relative",8,0,2,0,2941} }
static KeyWord kw_326 [static] |
{ {"coordinate_data_file",11,0,3,0,2779}, {"coordinate_list",14,0,3,0,2777}, {"lengths",13,0,1,1,2773}, {"num_coordinates_per_field",13,0,2,0,2775} }
static KeyWord kw_327 [static] |
{ {"nonlinear_equality_scale_types",0x807,0,2,0,2764,0,0.,0.,0.,0,0,0,"nonlinear_equality_constraints"}, {"nonlinear_equality_scales",0x806,0,3,0,2766,0,0.,0.,0.,0,0,0,"nonlinear_equality_constraints"}, {"nonlinear_equality_targets",6,0,1,0,2762,0,0.,0.,0.,0,0,0,"nonlinear_equality_constraints"}, {"scale_types",0x80f,0,2,0,2765,0,0.,0.,0.,0,"{Nonlinear scaling types (for inequalities or equalities)} RespCommands.html#RespFnLS",0,"nonlinear_equality_constraints"}, {"scales",0x80e,0,3,0,2767,0,0.,0.,0.,0,"{Nonlinear scales (for inequalities or equalities)} RespCommands.html#RespFnLS",0,"nonlinear_equality_constraints"}, {"targets",14,0,1,0,2763,0,0.,0.,0.,0,"{Nonlinear equality constraint targets} RespCommands.html#RespFnOpt",0,"nonlinear_equality_constraints"} }
static KeyWord kw_328 [static] |
{ {"lower_bounds",14,0,1,0,2753,0,0.,0.,0.,0,"{Nonlinear inequality constraint lower bounds} RespCommands.html#RespFnOpt",0,"nonlinear_inequality_constraints"}, {"nonlinear_inequality_lower_bounds",6,0,1,0,2752,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"nonlinear_inequality_scale_types",0x807,0,3,0,2756,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"nonlinear_inequality_scales",0x806,0,4,0,2758,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"nonlinear_inequality_upper_bounds",6,0,2,0,2754,0,0.,0.,0.,0,0,0,"nonlinear_inequality_constraints"}, {"scale_types",0x80f,0,3,0,2757,0,0.,0.,0.,0,"{Nonlinear constraint scaling types (for inequalities or equalities)} RespCommands.html#RespFnOpt",0,"nonlinear_inequality_constraints"}, {"scales",0x80e,0,4,0,2759,0,0.,0.,0.,0,"{Nonlinear constraint scales (for inequalities or equalities)} RespCommands.html#RespFnOpt",0,"nonlinear_inequality_constraints"}, {"upper_bounds",14,0,2,0,2755,0,0.,0.,0.,0,"{Nonlinear inequality constraint upper bounds} RespCommands.html#RespFnOpt",0,"nonlinear_inequality_constraints"} }
static KeyWord kw_329 [static] |
{ {"field_objectives",0x29,4,8,0,2771,kw_326}, {"multi_objective_weights",6,0,4,0,2748,0,0.,0.,0.,0,0,0,"objective_functions"}, {"nonlinear_equality_constraints",0x29,6,6,0,2761,kw_327,0.,0.,0.,0,"{Number of nonlinear equality constraints} RespCommands.html#RespFnOpt"}, {"nonlinear_inequality_constraints",0x29,8,5,0,2751,kw_328,0.,0.,0.,0,"{Number of nonlinear inequality constraints} RespCommands.html#RespFnOpt"}, {"num_field_objectives",0x21,4,8,0,2770,kw_326}, {"num_nonlinear_equality_constraints",0x21,6,6,0,2760,kw_327}, {"num_nonlinear_inequality_constraints",0x21,8,5,0,2750,kw_328}, {"num_scalar_objectives",0x21,0,7,0,2768}, {"objective_function_scale_types",0x807,0,2,0,2744,0,0.,0.,0.,0,0,0,"objective_functions"}, {"objective_function_scales",0x806,0,3,0,2746,0,0.,0.,0.,0,0,0,"objective_functions"}, {"primary_scale_types",0x80f,0,2,0,2745,0,0.,0.,0.,0,"{Objective function scaling types} RespCommands.html#RespFnOpt",0,"objective_functions"}, {"primary_scales",0x80e,0,3,0,2747,0,0.,0.,0.,0,"{Objective function scales} RespCommands.html#RespFnOpt",0,"objective_functions"}, {"scalar_objectives",0x29,0,7,0,2769}, {"sense",0x80f,0,1,0,2743,0,0.,0.,0.,0,"{Optimization sense} RespCommands.html#RespFnOpt",0,"objective_functions"}, {"weights",14,0,4,0,2749,0,0.,0.,0.,0,"{Multi-objective weightings} RespCommands.html#RespFnOpt",0,"objective_functions"} }
static KeyWord kw_330 [static] |
{ {"coordinate_data_file",11,0,3,0,2873}, {"coordinate_list",14,0,3,0,2871}, {"lengths",13,0,1,1,2867}, {"num_coordinates_per_field",13,0,2,0,2869} }
static KeyWord kw_331 [static] |
{ {"field_responses",0x29,4,2,0,2865,kw_330}, {"num_field_responses",0x21,4,2,0,2864,kw_330}, {"num_scalar_responses",0x21,0,1,0,2862}, {"scalar_responses",0x29,0,1,0,2863} }
static KeyWord kw_332 [static] |
{ {"central",8,0,6,0,2905,0,0.,0.,0.,0,"[CHOOSE difference interval]"}, {"dakota",8,4,4,0,2889,kw_320,0.,0.,0.,0,"@[CHOOSE gradient source]{Interval scaling type} RespCommands.html#RespGradNum"}, {"fd_gradient_step_size",6,0,7,0,2906}, {"fd_step_size",14,0,7,0,2907,0,0.,0.,0.,0,"{Finite difference step size} RespCommands.html#RespGradMixed"}, {"forward",8,0,6,0,2903,0,0.,0.,0.,0,"@"}, {"interval_type",8,0,5,0,2901,0,0.,0.,0.,0,"{Interval type} RespCommands.html#RespGradNum"}, {"method_source",8,0,3,0,2887,0,0.,0.,0.,0,"{Method source} RespCommands.html#RespGradNum"}, {"vendor",8,0,4,0,2899} }
static KeyWord kw_333 [static] |
{ {"absolute",8,0,2,0,2917}, {"bounds",8,0,2,0,2919}, {"central",8,0,3,0,2923,0,0.,0.,0.,0,"[CHOOSE difference interval]"}, {"fd_hessian_step_size",6,0,1,0,2912}, {"fd_step_size",14,0,1,0,2913,0,0.,0.,0.,0,"{Finite difference step size} RespCommands.html#RespHessNum"}, {"forward",8,0,3,0,2921,0,0.,0.,0.,0,"@"}, {"relative",8,0,2,0,2915} }
static KeyWord kw_334 [static] |
{ {"damped",8,0,1,0,2929,0,0.,0.,0.,0,"{Numerical safeguarding of BFGS update} RespCommands.html#RespHessQuasi"} }
static KeyWord kw_335 [static] |
{ {"bfgs",8,1,1,1,2927,kw_334,0.,0.,0.,0,"[CHOOSE Hessian approx.]"}, {"sr1",8,0,1,1,2931} }
static KeyWord kw_336 [static] |
{ {"analytic_gradients",8,0,4,2,2877,0,0.,0.,0.,0,"[CHOOSE gradient type]"}, {"analytic_hessians",8,0,5,3,2933,0,0.,0.,0.,0,"[CHOOSE Hessian type]"}, {"calibration_terms",0x29,18,3,1,2781,kw_319,0.,0.,0.,0,"{{Calibration (Least squares)} Number of calibration terms} RespCommands.html#RespFnLS"}, {"descriptors",15,0,2,0,2739,0,0.,0.,0.,0,"{Response labels} RespCommands.html#RespLabels"}, {"id_responses",11,0,1,0,2737,0,0.,0.,0.,0,"{Responses set identifier} RespCommands.html#RespSetId"}, {"least_squares_terms",0x21,18,3,1,2780,kw_319}, {"mixed_gradients",8,10,4,2,2879,kw_321,0.,0.,0.,0,"{Mixed gradients} RespCommands.html#RespGradMixed"}, {"mixed_hessians",8,8,5,3,2935,kw_325,0.,0.,0.,0,"{Mixed Hessians} RespCommands.html#RespHessMixed"}, {"no_gradients",8,0,4,2,2875,0,0.,0.,0.,0,"@"}, {"no_hessians",8,0,5,3,2909,0,0.,0.,0.,0,"@"}, {"num_least_squares_terms",0x21,18,3,1,2780,kw_319}, {"num_objective_functions",0x21,15,3,1,2740,kw_329}, {"num_response_functions",0x21,4,3,1,2860,kw_331}, {"numerical_gradients",8,8,4,2,2885,kw_332,0.,0.,0.,0,"{Numerical gradients} RespCommands.html#RespGradNum"}, {"numerical_hessians",8,7,5,3,2911,kw_333,0.,0.,0.,0,"{Numerical Hessians} RespCommands.html#RespHessNum"}, {"objective_functions",0x29,15,3,1,2741,kw_329,0.,0.,0.,0,"{{Optimization} Number of objective functions} RespCommands.html#RespFnOpt"}, {"quasi_hessians",8,2,5,3,2925,kw_335,0.,0.,0.,0,"{Quasi Hessians} RespCommands.html#RespHessQuasi"}, {"response_descriptors",7,0,2,0,2738}, {"response_functions",0x29,4,3,1,2861,kw_331,0.,0.,0.,0,"{{Generic responses} Number of response functions} RespCommands.html#RespFnGen"} }
static KeyWord kw_337 [static] |
{ {"aleatory",8,0,1,1,2187}, {"all",8,0,1,1,2181}, {"design",8,0,1,1,2183}, {"epistemic",8,0,1,1,2189}, {"state",8,0,1,1,2191}, {"uncertain",8,0,1,1,2185} }
static KeyWord kw_338 [static] |
{ {"alphas",14,0,1,1,2339,0,0.,0.,0.,0,"{beta uncertain alphas} VarCommands.html#VarCAUV_Beta",0,"beta_uncertain"}, {"betas",14,0,2,2,2341,0,0.,0.,0.,0,"{beta uncertain betas} VarCommands.html#VarCAUV_Beta",0,"beta_uncertain"}, {"buv_alphas",6,0,1,1,2338,0,0.,0.,0.,0,0,0,"beta_uncertain"}, {"buv_betas",6,0,2,2,2340,0,0.,0.,0.,0,0,0,"beta_uncertain"}, {"buv_descriptors",7,0,6,0,2348,0,0.,0.,0.,0,0,0,"beta_uncertain"}, {"buv_lower_bounds",6,0,3,3,2342,0,0.,0.,0.,0,0,0,"beta_uncertain"}, {"buv_upper_bounds",6,0,4,4,2344,0,0.,0.,0.,0,0,0,"beta_uncertain"}, {"descriptors",15,0,6,0,2349,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Gamma",0,"beta_uncertain"}, {"initial_point",14,0,5,0,2347,0,0.,0.,0.,0,0,0,"beta_uncertain"}, {"lower_bounds",14,0,3,3,2343,0,0.,0.,0.,0,"{Distribution lower bounds} VarCommands.html#VarCAUV_Beta",0,"beta_uncertain"}, {"upper_bounds",14,0,4,4,2345,0,0.,0.,0.,0,"{Distribution upper bounds} VarCommands.html#VarCAUV_Beta",0,"beta_uncertain"} }
static KeyWord kw_339 [static] |
{ {"descriptors",15,0,4,0,2421,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDAUV_Negative_Binomial",0,"binomial_uncertain"}, {"initial_point",13,0,3,0,2419,0,0.,0.,0.,0,0,0,"binomial_uncertain"}, {"num_trials",13,0,2,2,2417,0,0.,0.,0.,0,"{binomial uncertain num_trials} VarCommands.html#VarDAUV_Binomial",0,"binomial_uncertain"}, {"prob_per_trial",6,0,1,1,2414,0,0.,0.,0.,0,0,0,"binomial_uncertain"}, {"probability_per_trial",14,0,1,1,2415,0,0.,0.,0.,0,0,0,"binomial_uncertain"} }
static KeyWord kw_340 [static] |
{ {"cdv_descriptors",7,0,6,0,2208,0,0.,0.,0.,0,0,0,"continuous_design"}, {"cdv_initial_point",6,0,1,0,2198,0,0.,0.,0.,0,0,0,"continuous_design"}, {"cdv_lower_bounds",6,0,2,0,2200,0,0.,0.,0.,0,0,0,"continuous_design"}, {"cdv_scale_types",0x807,0,4,0,2204,0,0.,0.,0.,0,0,0,"continuous_design"}, {"cdv_scales",0x806,0,5,0,2206,0,0.,0.,0.,0,0,0,"continuous_design"}, {"cdv_upper_bounds",6,0,3,0,2202,0,0.,0.,0.,0,0,0,"continuous_design"}, {"descriptors",15,0,6,0,2209,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCDV",0,"continuous_design"}, {"initial_point",14,0,1,0,2199,0,0.,0.,0.,0,"{Initial point} VarCommands.html#VarCDV",0,"continuous_design"}, {"lower_bounds",14,0,2,0,2201,0,0.,0.,0.,0,"{Lower bounds} VarCommands.html#VarCDV",0,"continuous_design"}, {"scale_types",0x80f,0,4,0,2205,0,0.,0.,0.,0,"{Scaling types} VarCommands.html#VarCDV",0,"continuous_design"}, {"scales",0x80e,0,5,0,2207,0,0.,0.,0.,0,"{Scales} VarCommands.html#VarCDV",0,"continuous_design"}, {"upper_bounds",14,0,3,0,2203,0,0.,0.,0.,0,"{Upper bounds} VarCommands.html#VarCDV",0,"continuous_design"} }
static KeyWord kw_341 [static] |
{ {"descriptors",15,0,6,0,2505,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDUSRV",0,"continuous_interval_uncertain"}, {"initial_point",14,0,5,0,2503,0,0.,0.,0.,0,0,0,"continuous_interval_uncertain"}, {"interval_probabilities",14,0,2,0,2497,0,0.,0.,0.,0,"{basic probability assignments per continuous interval} VarCommands.html#VarCEUV_Interval"}, {"interval_probs",6,0,2,0,2496}, {"iuv_descriptors",7,0,6,0,2504,0,0.,0.,0.,0,0,0,"continuous_interval_uncertain"}, {"iuv_interval_probs",6,0,2,0,2496}, {"iuv_num_intervals",5,0,1,0,2494,0,0.,0.,0.,0,0,0,"continuous_interval_uncertain"}, {"lower_bounds",14,0,3,1,2499,0,0.,0.,0.,0,"{lower bounds of continuous intervals} VarCommands.html#VarCEUV_Interval"}, {"num_intervals",13,0,1,0,2495,0,0.,0.,0.,0,"{number of intervals defined for each continuous interval variable} VarCommands.html#VarCEUV_Interval",0,"continuous_interval_uncertain"}, {"upper_bounds",14,0,4,2,2501,0,0.,0.,0.,0,"{upper bounds of continuous intervals} VarCommands.html#VarCEUV_Interval"} }
static KeyWord kw_342 [static] |
{ {"csv_descriptors",7,0,4,0,2570,0,0.,0.,0.,0,0,0,"continuous_state"}, {"csv_initial_state",6,0,1,0,2564,0,0.,0.,0.,0,0,0,"continuous_state"}, {"csv_lower_bounds",6,0,2,0,2566,0,0.,0.,0.,0,0,0,"continuous_state"}, {"csv_upper_bounds",6,0,3,0,2568,0,0.,0.,0.,0,0,0,"continuous_state"}, {"descriptors",15,0,4,0,2571,0,0.,0.,0.,0,0,0,"continuous_state"}, {"initial_state",14,0,1,0,2565,0,0.,0.,0.,0,"{Initial states} VarCommands.html#VarCSV",0,"continuous_state"}, {"lower_bounds",14,0,2,0,2567,0,0.,0.,0.,0,"{Lower bounds} VarCommands.html#VarCSV",0,"continuous_state"}, {"upper_bounds",14,0,3,0,2569,0,0.,0.,0.,0,"{Upper bounds} VarCommands.html#VarCSV",0,"continuous_state"} }
static KeyWord kw_343 [static] |
{ {"ddv_descriptors",7,0,4,0,2218,0,0.,0.,0.,0,0,0,"discrete_design_range"}, {"ddv_initial_point",5,0,1,0,2212,0,0.,0.,0.,0,0,0,"discrete_design_range"}, {"ddv_lower_bounds",5,0,2,0,2214,0,0.,0.,0.,0,0,0,"discrete_design_range"}, {"ddv_upper_bounds",5,0,3,0,2216,0,0.,0.,0.,0,0,0,"discrete_design_range"}, {"descriptors",15,0,4,0,2219,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDDRIV",0,"discrete_design_range"}, {"initial_point",13,0,1,0,2213,0,0.,0.,0.,0,"{Initial point} VarCommands.html#VarDDRIV",0,"discrete_design_range"}, {"lower_bounds",13,0,2,0,2215,0,0.,0.,0.,0,"{Lower bounds} VarCommands.html#VarDDRIV",0,"discrete_design_range"}, {"upper_bounds",13,0,3,0,2217,0,0.,0.,0.,0,"{Upper bounds} VarCommands.html#VarDDRIV",0,"discrete_design_range"} }
static KeyWord kw_344 [static] |
{
{"adjacency_matrix",13,0,1,0,2231}
}
static KeyWord kw_345 [static] |
{ {"categorical",15,1,3,0,2229,kw_344,0.,0.,0.,0,0,0,"integer"}, {"descriptors",15,0,5,0,2235,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDDSIV",0,"integer"}, {"elements",13,0,2,1,2227}, {"elements_per_variable",0x80d,0,1,0,2225,0,0.,0.,0.,0,0,0,"integer"}, {"initial_point",13,0,4,0,2233,0,0.,0.,0.,0,"{Initial point} VarCommands.html#VarDDSIV",0,"integer"}, {"num_set_values",0x805,0,1,0,2224,0,0.,0.,0.,0,0,0,"integer"}, {"set_values",5,0,2,1,2226} }
static KeyWord kw_346 [static] |
{
{"adjacency_matrix",13,0,1,0,2257}
}
static KeyWord kw_347 [static] |
{ {"categorical",15,1,3,0,2255,kw_346,0.,0.,0.,0,0,0,"integer"}, {"descriptors",15,0,5,0,2261,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Normal",0,"real"}, {"elements",14,0,2,1,2253}, {"elements_per_variable",0x80d,0,1,0,2251,0,0.,0.,0.,0,0,0,"real"}, {"initial_point",14,0,4,0,2259,0,0.,0.,0.,0,0,0,"real"}, {"num_set_values",0x805,0,1,0,2250,0,0.,0.,0.,0,0,0,"real"}, {"set_values",6,0,2,1,2252} }
static KeyWord kw_348 [static] |
{ {"adjacency_matrix",13,0,3,0,2243}, {"descriptors",15,0,5,0,2247,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDDSRV",0,"string"}, {"elements",15,0,2,1,2241}, {"elements_per_variable",0x80d,0,1,0,2239,0,0.,0.,0.,0,0,0,"string"}, {"initial_point",15,0,4,0,2245,0,0.,0.,0.,0,"{Initial point} VarCommands.html#VarDDSRV",0,"string"}, {"num_set_values",0x805,0,1,0,2238,0,0.,0.,0.,0,0,0,"string"}, {"set_values",7,0,2,1,2240} }
static KeyWord kw_349 [static] |
{ {"integer",0x19,7,1,0,2223,kw_345}, {"real",0x19,7,3,0,2249,kw_347}, {"string",0x19,7,2,0,2237,kw_348} }
static KeyWord kw_350 [static] |
{ {"descriptors",15,0,6,0,2519,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCSV",0,"discrete_interval_uncertain"}, {"initial_point",13,0,5,0,2517,0,0.,0.,0.,0,0,0,"discrete_interval_uncertain"}, {"interval_probabilities",14,0,2,0,2511,0,0.,0.,0.,0,"{Basic probability assignments per interval} VarCommands.html#VarDIUV"}, {"interval_probs",6,0,2,0,2510}, {"lower_bounds",13,0,3,1,2513,0,0.,0.,0.,0,"{Lower bounds} VarCommands.html#VarDIUV"}, {"num_intervals",13,0,1,0,2509,0,0.,0.,0.,0,"{Number of intervals defined for each interval variable} VarCommands.html#VarDIUV",0,"discrete_interval_uncertain"}, {"range_probabilities",6,0,2,0,2510}, {"range_probs",6,0,2,0,2510}, {"upper_bounds",13,0,4,2,2515,0,0.,0.,0.,0,"{Upper bounds} VarCommands.html#VarDIUV"} }
static KeyWord kw_351 [static] |
{ {"descriptors",15,0,4,0,2581,0,0.,0.,0.,0,0,0,"discrete_state_range"}, {"dsv_descriptors",7,0,4,0,2580,0,0.,0.,0.,0,0,0,"discrete_state_range"}, {"dsv_initial_state",5,0,1,0,2574,0,0.,0.,0.,0,0,0,"discrete_state_range"}, {"dsv_lower_bounds",5,0,2,0,2576,0,0.,0.,0.,0,0,0,"discrete_state_range"}, {"dsv_upper_bounds",5,0,3,0,2578,0,0.,0.,0.,0,0,0,"discrete_state_range"}, {"initial_state",13,0,1,0,2575,0,0.,0.,0.,0,"{Initial states} VarCommands.html#VarDSRIV",0,"discrete_state_range"}, {"lower_bounds",13,0,2,0,2577,0,0.,0.,0.,0,"{Lower bounds} VarCommands.html#VarDSRIV",0,"discrete_state_range"}, {"upper_bounds",13,0,3,0,2579,0,0.,0.,0.,0,"{Upper bounds} VarCommands.html#VarDSRIV",0,"discrete_state_range"} }
static KeyWord kw_352 [static] |
{ {"categorical",15,0,3,0,2591,0,0.,0.,0.,0,0,0,"integer"}, {"descriptors",15,0,5,0,2595,0,0.,0.,0.,0,0,0,"integer"}, {"elements",13,0,2,1,2589}, {"elements_per_variable",0x80d,0,1,0,2587,0,0.,0.,0.,0,0,0,"integer"}, {"initial_state",13,0,4,0,2593,0,0.,0.,0.,0,"{Initial state} VarCommands.html#VarDSSIV",0,"integer"}, {"num_set_values",0x805,0,1,0,2586,0,0.,0.,0.,0,0,0,"integer"}, {"set_values",5,0,2,1,2588} }
static KeyWord kw_353 [static] |
{ {"categorical",15,0,3,0,2613,0,0.,0.,0.,0,0,0,"integer"}, {"descriptors",15,0,5,0,2617,0,0.,0.,0.,0,0,0,"real"}, {"elements",14,0,2,1,2611}, {"elements_per_variable",0x80d,0,1,0,2609,0,0.,0.,0.,0,0,0,"real"}, {"initial_state",14,0,4,0,2615,0,0.,0.,0.,0,0,0,"real"}, {"num_set_values",0x805,0,1,0,2608,0,0.,0.,0.,0,0,0,"real"}, {"set_values",6,0,2,1,2610} }
static KeyWord kw_354 [static] |
{ {"descriptors",15,0,4,0,2605,0,0.,0.,0.,0,0,0,"string"}, {"elements",15,0,2,1,2601}, {"elements_per_variable",0x80d,0,1,0,2599,0,0.,0.,0.,0,0,0,"string"}, {"initial_state",15,0,3,0,2603,0,0.,0.,0.,0,"{Initial state} VarCommands.html#VarDSSRV",0,"string"}, {"num_set_values",0x805,0,1,0,2598,0,0.,0.,0.,0,0,0,"string"}, {"set_values",7,0,2,1,2600} }
static KeyWord kw_355 [static] |
{ {"integer",0x19,7,1,0,2585,kw_352}, {"real",0x19,7,3,0,2607,kw_353}, {"string",0x19,6,2,0,2597,kw_354} }
static KeyWord kw_356 [static] |
{ {"categorical",15,0,4,0,2531,0,0.,0.,0.,0,0,0,"integer"}, {"descriptors",15,0,6,0,2535,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDSRIV",0,"integer"}, {"elements",13,0,2,1,2527}, {"elements_per_variable",13,0,1,0,2525,0,0.,0.,0.,0,0,0,"integer"}, {"initial_point",13,0,5,0,2533,0,0.,0.,0.,0,0,0,"integer"}, {"num_set_values",5,0,1,0,2524,0,0.,0.,0.,0,0,0,"integer"}, {"set_probabilities",14,0,3,0,2529,0,0.,0.,0.,0,"{Probabilities for each set member} VarCommands.html#VarDUSIV"}, {"set_probs",6,0,3,0,2528}, {"set_values",5,0,2,1,2526} }
static KeyWord kw_357 [static] |
{ {"categorical",15,0,4,0,2557,0,0.,0.,0.,0,0,0,"real"}, {"descriptors",15,0,6,0,2561,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDSSRV",0,"real"}, {"elements",14,0,2,1,2553}, {"elements_per_variable",13,0,1,0,2551,0,0.,0.,0.,0,0,0,"real"}, {"initial_point",14,0,5,0,2559,0,0.,0.,0.,0,0,0,"real"}, {"num_set_values",5,0,1,0,2550,0,0.,0.,0.,0,0,0,"real"}, {"set_probabilities",14,0,3,0,2555}, {"set_probs",6,0,3,0,2554}, {"set_values",6,0,2,1,2552} }
static KeyWord kw_358 [static] |
{ {"descriptors",15,0,5,0,2547,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDSSIV",0,"string"}, {"elements",15,0,2,1,2541}, {"elements_per_variable",13,0,1,0,2539,0,0.,0.,0.,0,0,0,"string"}, {"initial_point",15,0,4,0,2545,0,0.,0.,0.,0,0,0,"string"}, {"num_set_values",5,0,1,0,2538,0,0.,0.,0.,0,0,0,"string"}, {"set_probabilities",14,0,3,0,2543,0,0.,0.,0.,0,"{Probabilities for each set member} VarCommands.html#VarDUSRV"}, {"set_probs",6,0,3,0,2542}, {"set_values",7,0,2,1,2540} }
static KeyWord kw_359 [static] |
{ {"integer",0x19,9,1,0,2523,kw_356}, {"real",0x19,9,3,0,2549,kw_357}, {"string",0x19,8,2,0,2537,kw_358} }
static KeyWord kw_360 [static] |
{ {"betas",14,0,1,1,2331,0,0.,0.,0.,0,"{exponential uncertain betas} VarCommands.html#VarCAUV_Exponential",0,"exponential_uncertain"}, {"descriptors",15,0,3,0,2335,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Beta",0,"exponential_uncertain"}, {"euv_betas",6,0,1,1,2330,0,0.,0.,0.,0,0,0,"exponential_uncertain"}, {"euv_descriptors",7,0,3,0,2334,0,0.,0.,0.,0,0,0,"exponential_uncertain"}, {"initial_point",14,0,2,0,2333,0,0.,0.,0.,0,0,0,"exponential_uncertain"} }
static KeyWord kw_361 [static] |
{ {"alphas",14,0,1,1,2373,0,0.,0.,0.,0,"{frechet uncertain alphas} VarCommands.html#VarCAUV_Frechet",0,"frechet_uncertain"}, {"betas",14,0,2,2,2375,0,0.,0.,0.,0,"{frechet uncertain betas} VarCommands.html#VarCAUV_Frechet",0,"frechet_uncertain"}, {"descriptors",15,0,4,0,2379,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Weibull",0,"frechet_uncertain"}, {"fuv_alphas",6,0,1,1,2372,0,0.,0.,0.,0,0,0,"frechet_uncertain"}, {"fuv_betas",6,0,2,2,2374,0,0.,0.,0.,0,0,0,"frechet_uncertain"}, {"fuv_descriptors",7,0,4,0,2378,0,0.,0.,0.,0,0,0,"frechet_uncertain"}, {"initial_point",14,0,3,0,2377,0,0.,0.,0.,0,0,0,"frechet_uncertain"} }
static KeyWord kw_362 [static] |
{ {"alphas",14,0,1,1,2353,0,0.,0.,0.,0,"{gamma uncertain alphas} VarCommands.html#VarCAUV_Gamma",0,"gamma_uncertain"}, {"betas",14,0,2,2,2355,0,0.,0.,0.,0,"{gamma uncertain betas} VarCommands.html#VarCAUV_Gamma",0,"gamma_uncertain"}, {"descriptors",15,0,4,0,2359,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Gumbel",0,"gamma_uncertain"}, {"gauv_alphas",6,0,1,1,2352,0,0.,0.,0.,0,0,0,"gamma_uncertain"}, {"gauv_betas",6,0,2,2,2354,0,0.,0.,0.,0,0,0,"gamma_uncertain"}, {"gauv_descriptors",7,0,4,0,2358,0,0.,0.,0.,0,0,0,"gamma_uncertain"}, {"initial_point",14,0,3,0,2357,0,0.,0.,0.,0,0,0,"gamma_uncertain"} }
static KeyWord kw_363 [static] |
{ {"descriptors",15,0,3,0,2439,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDAUV_Hypergeometric",0,"geometric_uncertain"}, {"initial_point",13,0,2,0,2437,0,0.,0.,0.,0,0,0,"geometric_uncertain"}, {"prob_per_trial",6,0,1,1,2434,0,0.,0.,0.,0,0,0,"geometric_uncertain"}, {"probability_per_trial",14,0,1,1,2435,0,0.,0.,0.,0,0,0,"geometric_uncertain"} }
static KeyWord kw_364 [static] |
{ {"alphas",14,0,1,1,2363,0,0.,0.,0.,0,"{gumbel uncertain alphas} VarCommands.html#VarCAUV_Gumbel",0,"gumbel_uncertain"}, {"betas",14,0,2,2,2365,0,0.,0.,0.,0,"{gumbel uncertain betas} VarCommands.html#VarCAUV_Gumbel",0,"gumbel_uncertain"}, {"descriptors",15,0,4,0,2369,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Frechet",0,"gumbel_uncertain"}, {"guuv_alphas",6,0,1,1,2362,0,0.,0.,0.,0,0,0,"gumbel_uncertain"}, {"guuv_betas",6,0,2,2,2364,0,0.,0.,0.,0,0,0,"gumbel_uncertain"}, {"guuv_descriptors",7,0,4,0,2368,0,0.,0.,0.,0,0,0,"gumbel_uncertain"}, {"initial_point",14,0,3,0,2367,0,0.,0.,0.,0,0,0,"gumbel_uncertain"} }
static KeyWord kw_365 [static] |
{ {"abscissas",14,0,2,1,2395,0,0.,0.,0.,0,"{sets of abscissas for bin-based histogram variables} VarCommands.html#VarCAUV_Bin_Histogram"}, {"counts",14,0,3,2,2399,0,0.,0.,0.,0,"{sets of counts for bin-based histogram variables} VarCommands.html#VarCAUV_Bin_Histogram"}, {"descriptors",15,0,5,0,2403,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDAUV_Poisson",0,"histogram_bin_uncertain"}, {"huv_bin_abscissas",6,0,2,1,2394}, {"huv_bin_counts",6,0,3,2,2398}, {"huv_bin_descriptors",7,0,5,0,2402,0,0.,0.,0.,0,0,0,"histogram_bin_uncertain"}, {"huv_bin_ordinates",6,0,3,2,2396}, {"initial_point",14,0,4,0,2401,0,0.,0.,0.,0,0,0,"histogram_bin_uncertain"}, {"num_pairs",5,0,1,0,2392,0,0.,0.,0.,0,0,0,"histogram_bin_uncertain"}, {"ordinates",14,0,3,2,2397,0,0.,0.,0.,0,"{sets of ordinates for bin-based histogram variables} VarCommands.html#VarCAUV_Bin_Histogram"}, {"pairs_per_variable",13,0,1,0,2393,0,0.,0.,0.,0,0,0,"histogram_bin_uncertain"} }
static KeyWord kw_366 [static] |
{ {"abscissas",13,0,2,1,2459,0,0.,0.,0.,0,"{sets of abscissas for point-based histogram variables} VarCommands.html#VarDAUV_Point_Histogram"}, {"counts",14,0,3,2,2461,0,0.,0.,0.,0,"{sets of counts for point-based histogram variables} VarCommands.html#VarDAUV_Point_Histogram"}, {"descriptors",15,0,5,0,2465,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCEUV_Interval",0,"integer"}, {"initial_point",13,0,4,0,2463,0,0.,0.,0.,0,0,0,"integer"}, {"num_pairs",5,0,1,0,2456,0,0.,0.,0.,0,0,0,"integer"}, {"pairs_per_variable",13,0,1,0,2457,0,0.,0.,0.,0,0,0,"integer"} }
static KeyWord kw_367 [static] |
{ {"abscissas",14,0,2,1,2483}, {"counts",14,0,3,2,2485}, {"descriptors",15,0,5,0,2489,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDUSIV",0,"real"}, {"initial_point",14,0,4,0,2487,0,0.,0.,0.,0,0,0,"real"}, {"num_pairs",5,0,1,0,2480,0,0.,0.,0.,0,0,0,"real"}, {"pairs_per_variable",13,0,1,0,2481,0,0.,0.,0.,0,0,0,"real"} }
static KeyWord kw_368 [static] |
{ {"abscissas",15,0,2,1,2471}, {"counts",14,0,3,2,2473}, {"descriptors",15,0,5,0,2477,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDIUV",0,"string"}, {"initial_point",15,0,4,0,2475,0,0.,0.,0.,0,0,0,"string"}, {"num_pairs",5,0,1,0,2468,0,0.,0.,0.,0,0,0,"string"}, {"pairs_per_variable",13,0,1,0,2469,0,0.,0.,0.,0,0,0,"string"} }
static KeyWord kw_369 [static] |
{ {"integer",0x19,6,1,0,2455,kw_366}, {"real",0x19,6,3,0,2479,kw_367}, {"string",0x19,6,2,0,2467,kw_368} }
static KeyWord kw_370 [static] |
{ {"descriptors",15,0,5,0,2451,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDAUV_Point_Histogram",0,"hypergeometric_uncertain"}, {"initial_point",13,0,4,0,2449,0,0.,0.,0.,0,0,0,"hypergeometric_uncertain"}, {"num_drawn",13,0,3,3,2447,0,0.,0.,0.,0,"{hypergeometric uncertain num_drawn } VarCommands.html#VarDAUV_Hypergeometric",0,"hypergeometric_uncertain"}, {"selected_population",13,0,2,2,2445,0,0.,0.,0.,0,"{hypergeometric uncertain selected_population} VarCommands.html#VarDAUV_Hypergeometric",0,"hypergeometric_uncertain"}, {"total_population",13,0,1,1,2443,0,0.,0.,0.,0,"{hypergeometric uncertain total_population} VarCommands.html#VarDAUV_Hypergeometric",0,"hypergeometric_uncertain"} }
static KeyWord kw_371 [static] |
{ {"lnuv_zetas",6,0,1,1,2280,0,0.,0.,0.,0,0,0,"lognormal_uncertain"}, {"zetas",14,0,1,1,2281,0,0.,0.,0.,0,"{lognormal uncertain zetas} VarCommands.html#VarCAUV_Lognormal",0,"lognormal_uncertain"} }
static KeyWord kw_372 [static] |
{ {"error_factors",14,0,1,1,2287,0,0.,0.,0.,0,"[CHOOSE variance spec.]{lognormal uncertain error factors} VarCommands.html#VarCAUV_Lognormal",0,"lognormal_uncertain"}, {"lnuv_error_factors",6,0,1,1,2286,0,0.,0.,0.,0,0,0,"lognormal_uncertain"}, {"lnuv_std_deviations",6,0,1,1,2284,0,0.,0.,0.,0,0,0,"lognormal_uncertain"}, {"std_deviations",14,0,1,1,2285,0,0.,0.,0.,0,"@{lognormal uncertain standard deviations} VarCommands.html#VarCAUV_Lognormal",0,"lognormal_uncertain"} }
static KeyWord kw_373 [static] |
{ {"descriptors",15,0,5,0,2295,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Uniform",0,"lognormal_uncertain"}, {"initial_point",14,0,4,0,2293,0,0.,0.,0.,0,0,0,"lognormal_uncertain"}, {"lambdas",14,2,1,1,2279,kw_371,0.,0.,0.,0,"[CHOOSE characterization]{lognormal uncertain lambdas} VarCommands.html#VarCAUV_Lognormal",0,"lognormal_uncertain"}, {"lnuv_descriptors",7,0,5,0,2294,0,0.,0.,0.,0,0,0,"lognormal_uncertain"}, {"lnuv_lambdas",6,2,1,1,2278,kw_371,0.,0.,0.,0,0,0,"lognormal_uncertain"}, {"lnuv_lower_bounds",6,0,2,0,2288,0,0.,0.,0.,0,0,0,"lognormal_uncertain"}, {"lnuv_means",6,4,1,1,2282,kw_372,0.,0.,0.,0,0,0,"lognormal_uncertain"}, {"lnuv_upper_bounds",6,0,3,0,2290,0,0.,0.,0.,0,0,0,"lognormal_uncertain"}, {"lower_bounds",14,0,2,0,2289,0,0.,0.,0.,0,"{Distribution lower bounds} VarCommands.html#VarCAUV_Lognormal",0,"lognormal_uncertain"}, {"means",14,4,1,1,2283,kw_372,0.,0.,0.,0,"@{lognormal uncertain means} VarCommands.html#VarCAUV_Lognormal",0,"lognormal_uncertain"}, {"upper_bounds",14,0,3,0,2291,0,0.,0.,0.,0,"{Distribution upper bounds} VarCommands.html#VarCAUV_Lognormal",0,"lognormal_uncertain"} }
static KeyWord kw_374 [static] |
{ {"descriptors",15,0,4,0,2315,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Triangular",0,"loguniform_uncertain"}, {"initial_point",14,0,3,0,2313,0,0.,0.,0.,0,0,0,"loguniform_uncertain"}, {"lower_bounds",14,0,1,1,2309,0,0.,0.,0.,0,"{Distribution lower bounds} VarCommands.html#VarCAUV_Loguniform",0,"loguniform_uncertain"}, {"luuv_descriptors",7,0,4,0,2314,0,0.,0.,0.,0,0,0,"loguniform_uncertain"}, {"luuv_lower_bounds",6,0,1,1,2308,0,0.,0.,0.,0,0,0,"loguniform_uncertain"}, {"luuv_upper_bounds",6,0,2,2,2310,0,0.,0.,0.,0,0,0,"loguniform_uncertain"}, {"upper_bounds",14,0,2,2,2311,0,0.,0.,0.,0,"{Distribution upper bounds} VarCommands.html#VarCAUV_Loguniform",0,"loguniform_uncertain"} }
static KeyWord kw_375 [static] |
{ {"descriptors",15,0,4,0,2431,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDAUV_Geometric",0,"negative_binomial_uncertain"}, {"initial_point",13,0,3,0,2429,0,0.,0.,0.,0,0,0,"negative_binomial_uncertain"}, {"num_trials",13,0,2,2,2427,0,0.,0.,0.,0,"{negative binomial uncertain success num_trials} VarCommands.html#VarDAUV_Negative_Binomial",0,"negative_binomial_uncertain"}, {"prob_per_trial",6,0,1,1,2424,0,0.,0.,0.,0,0,0,"negative_binomial_uncertain"}, {"probability_per_trial",14,0,1,1,2425,0,0.,0.,0.,0,0,0,"negative_binomial_uncertain"} }
static KeyWord kw_376 [static] |
{ {"descriptors",15,0,6,0,2275,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Lognormal",0,"normal_uncertain"}, {"initial_point",14,0,5,0,2273,0,0.,0.,0.,0,0,0,"normal_uncertain"}, {"lower_bounds",14,0,3,0,2269,0,0.,0.,0.,0,"{Distribution lower bounds} VarCommands.html#VarCAUV_Normal",0,"normal_uncertain"}, {"means",14,0,1,1,2265,0,0.,0.,0.,0,"{normal uncertain means} VarCommands.html#VarCAUV_Normal",0,"normal_uncertain"}, {"nuv_descriptors",7,0,6,0,2274,0,0.,0.,0.,0,0,0,"normal_uncertain"}, {"nuv_lower_bounds",6,0,3,0,2268,0,0.,0.,0.,0,0,0,"normal_uncertain"}, {"nuv_means",6,0,1,1,2264,0,0.,0.,0.,0,0,0,"normal_uncertain"}, {"nuv_std_deviations",6,0,2,2,2266,0,0.,0.,0.,0,0,0,"normal_uncertain"}, {"nuv_upper_bounds",6,0,4,0,2270,0,0.,0.,0.,0,0,0,"normal_uncertain"}, {"std_deviations",14,0,2,2,2267,0,0.,0.,0.,0,"{normal uncertain standard deviations} VarCommands.html#VarCAUV_Normal",0,"normal_uncertain"}, {"upper_bounds",14,0,4,0,2271,0,0.,0.,0.,0,"{Distribution upper bounds} VarCommands.html#VarCAUV_Normal",0,"normal_uncertain"} }
static KeyWord kw_377 [static] |
{ {"descriptors",15,0,3,0,2411,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarDAUV_Binomial",0,"poisson_uncertain"}, {"initial_point",13,0,2,0,2409,0,0.,0.,0.,0,0,0,"poisson_uncertain"}, {"lambdas",14,0,1,1,2407,0,0.,0.,0.,0,"{poisson uncertain lambdas} VarCommands.html#VarDAUV_Poisson",0,"poisson_uncertain"} }
static KeyWord kw_378 [static] |
{ {"descriptors",15,0,5,0,2327,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Exponential",0,"triangular_uncertain"}, {"initial_point",14,0,4,0,2325,0,0.,0.,0.,0,0,0,"triangular_uncertain"}, {"lower_bounds",14,0,2,2,2321,0,0.,0.,0.,0,"{Distribution lower bounds} VarCommands.html#VarCAUV_Triangular",0,"triangular_uncertain"}, {"modes",14,0,1,1,2319,0,0.,0.,0.,0,"{triangular uncertain modes} VarCommands.html#VarCAUV_Triangular",0,"triangular_uncertain"}, {"tuv_descriptors",7,0,5,0,2326,0,0.,0.,0.,0,0,0,"triangular_uncertain"}, {"tuv_lower_bounds",6,0,2,2,2320,0,0.,0.,0.,0,0,0,"triangular_uncertain"}, {"tuv_modes",6,0,1,1,2318,0,0.,0.,0.,0,0,0,"triangular_uncertain"}, {"tuv_upper_bounds",6,0,3,3,2322,0,0.,0.,0.,0,0,0,"triangular_uncertain"}, {"upper_bounds",14,0,3,3,2323,0,0.,0.,0.,0,"{Distribution upper bounds} VarCommands.html#VarCAUV_Triangular",0,"triangular_uncertain"} }
static KeyWord kw_379 [static] |
{ {"descriptors",15,0,4,0,2305,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Loguniform",0,"uniform_uncertain"}, {"initial_point",14,0,3,0,2303,0,0.,0.,0.,0,0,0,"uniform_uncertain"}, {"lower_bounds",14,0,1,1,2299,0,0.,0.,0.,0,"{Distribution lower bounds} VarCommands.html#VarCAUV_Uniform",0,"uniform_uncertain"}, {"upper_bounds",14,0,2,2,2301,0,0.,0.,0.,0,"{Distribution upper bounds} VarCommands.html#VarCAUV_Uniform",0,"uniform_uncertain"}, {"uuv_descriptors",7,0,4,0,2304,0,0.,0.,0.,0,0,0,"uniform_uncertain"}, {"uuv_lower_bounds",6,0,1,1,2298,0,0.,0.,0.,0,0,0,"uniform_uncertain"}, {"uuv_upper_bounds",6,0,2,2,2300,0,0.,0.,0.,0,0,0,"uniform_uncertain"} }
static KeyWord kw_380 [static] |
{ {"alphas",14,0,1,1,2383,0,0.,0.,0.,0,"{weibull uncertain alphas} VarCommands.html#VarCAUV_Weibull",0,"weibull_uncertain"}, {"betas",14,0,2,2,2385,0,0.,0.,0.,0,"{weibull uncertain betas} VarCommands.html#VarCAUV_Weibull",0,"weibull_uncertain"}, {"descriptors",15,0,4,0,2389,0,0.,0.,0.,0,"{Descriptors} VarCommands.html#VarCAUV_Bin_Histogram",0,"weibull_uncertain"}, {"initial_point",14,0,3,0,2387,0,0.,0.,0.,0,0,0,"weibull_uncertain"}, {"wuv_alphas",6,0,1,1,2382,0,0.,0.,0.,0,0,0,"weibull_uncertain"}, {"wuv_betas",6,0,2,2,2384,0,0.,0.,0.,0,0,0,"weibull_uncertain"}, {"wuv_descriptors",7,0,4,0,2388,0,0.,0.,0.,0,0,0,"weibull_uncertain"} }
static KeyWord kw_382 [static] |
{ {"environment",0x108,15,1,1,1,kw_12,0.,0.,0.,0,"{Environment} The environment specifies the top level technique which will govern the management of iterators and models in the solution of the problem of interest. EnvCommands.html"}, {"interface",0x308,9,5,5,2619,kw_26,0.,0.,0.,0,"{Interface} An interface specifies how function evaluations will be performed in order to map a set of parameters into a set of responses. InterfCommands.html"}, {"method",0x308,90,2,2,83,kw_275,0.,0.,0.,0,"{Method} A method specifies the name and controls of an iterative procedure, e.g., a sensitivity analysis, uncertainty quantification, or optimization method. MethodCommands.html"}, {"model",8,7,3,3,1907,kw_310,0.,0.,0.,0,"{Model} A model consists of a model type and maps specified variables through an interface to generate responses. ModelCommands.html"}, {"responses",0x308,19,6,6,2735,kw_336,0.,0.,0.,0,"{Responses} A responses object specifies the data that can be returned to DAKOTA through the interface after the completion of a function evaluation. RespCommands.html"}, {"variables",0x308,34,4,4,2175,kw_381,0.,0.,0.,0,"{Variables} A variables object specifies the parameter set to be iterated by a particular method. VarCommands.html"} }
KeyWord kw_383[6] [static] |
{ {"abscissas",13,0,2,1,0,0.,0.,0,N_vam(newivec,Var_Info_hpia)}, {"counts",14,0,3,2,0,0.,0.,0,N_vam(newrvec,Var_Info_hpic)}, {"descriptors",15,0,5,0,0,0.,0.,0,N_vae(dauilbl,DAUIVar_histogram_point_int)}, {"initial_point",13,0,4,0,0,0.,0.,0,N_vam(ivec,histogramPointIntUncVars)}, {"num_pairs",5,0,1,0,0,0.,0.,1,N_vam(newiarray,Var_Info_nhpip)}, {"pairs_per_variable",13,0,1,0,0,0.,0.,0,N_vam(newiarray,Var_Info_nhpip)} }
KeyWord kw_384[6] [static] |
{ {"abscissas",14,0,2,1,0,0.,0.,0,N_vam(newrvec,Var_Info_hpra)}, {"counts",14,0,3,2,0,0.,0.,0,N_vam(newrvec,Var_Info_hprc)}, {"descriptors",15,0,5,0,0,0.,0.,0,N_vae(daurlbl,DAURVar_histogram_point_real)}, {"initial_point",14,0,4,0,0,0.,0.,0,N_vam(rvec,histogramPointRealUncVars)}, {"num_pairs",5,0,1,0,0,0.,0.,1,N_vam(newiarray,Var_Info_nhprp)}, {"pairs_per_variable",13,0,1,0,0,0.,0.,0,N_vam(newiarray,Var_Info_nhprp)} }
KeyWord kw_385[6] [static] |
{ {"abscissas",15,0,2,1,0,0.,0.,0,N_vam(newsarray,Var_Info_hpsa)}, {"counts",14,0,3,2,0,0.,0.,0,N_vam(newrvec,Var_Info_hpsc)}, {"descriptors",15,0,5,0,0,0.,0.,0,N_vae(dauslbl,DAUSVar_histogram_point_str)}, {"initial_point",15,0,4,0,0,0.,0.,0,N_vam(strL,histogramPointStrUncVars)}, {"num_pairs",5,0,1,0,0,0.,0.,1,N_vam(newiarray,Var_Info_nhpsp)}, {"pairs_per_variable",13,0,1,0,0,0.,0.,0,N_vam(newiarray,Var_Info_nhpsp)} }
KeyWord kw_386[3] [static] |
{ {"integer",0x19,6,1,0,kw_383,0.,0.,0,N_vam(pintz,numHistogramPtIntUncVars)}, {"real",0x19,6,3,0,kw_384,0.,0.,0,N_vam(pintz,numHistogramPtRealUncVars)}, {"string",0x19,6,2,0,kw_385,0.,0.,0,N_vam(pintz,numHistogramPtStrUncVars)} }
KeyWord kw_387[5] [static] |
{ {"descriptors",15,0,5,0,0,0.,0.,0,N_vae(dauilbl,DAUIVar_hypergeometric)}, {"initial_point",13,0,4,0,0,0.,0.,0,N_vam(IntLb,hyperGeomUncVars)}, {"num_drawn",13,0,3,3,0,0.,0.,0,N_vam(IntLb,hyperGeomUncNumDrawn)}, {"selected_population",13,0,2,2,0,0.,0.,0,N_vam(IntLb,hyperGeomUncSelectedPop)}, {"total_population",13,0,1,1,0,0.,0.,0,N_vam(IntLb,hyperGeomUncTotalPop)} }
KeyWord kw_388[2] [static] |
{ {"lnuv_zetas",6,0,1,1,0,0.,0.,1,N_vam(RealLb,lognormalUncZetas)}, {"zetas",14,0,1,1,0,0.,0.,0,N_vam(RealLb,lognormalUncZetas)} }
KeyWord kw_389[4] [static] |
{ {"error_factors",14,0,1,1,0,0.,0.,0,N_vam(RealLb,lognormalUncErrFacts)}, {"lnuv_error_factors",6,0,1,1,0,0.,0.,-1,N_vam(RealLb,lognormalUncErrFacts)}, {"lnuv_std_deviations",6,0,1,1,0,0.,0.,1,N_vam(RealLb,lognormalUncStdDevs)}, {"std_deviations",14,0,1,1,0,0.,0.,0,N_vam(RealLb,lognormalUncStdDevs)} }
KeyWord kw_390[11] [static] |
{ {"descriptors",15,0,5,0,0,0.,0.,0,N_vae(caulbl,CAUVar_lognormal)}, {"initial_point",14,0,4,0,0,0.,0.,0,N_vam(RealLb,lognormalUncVars)}, {"lambdas",14,2,1,1,kw_388,0.,0.,0,N_vam(rvec,lognormalUncLambdas)}, {"lnuv_descriptors",7,0,5,0,0,0.,0.,-3,N_vae(caulbl,CAUVar_lognormal)}, {"lnuv_lambdas",6,2,1,1,kw_388,0.,0.,-2,N_vam(rvec,lognormalUncLambdas)}, {"lnuv_lower_bounds",6,0,2,0,0,0.,0.,3,N_vam(RealLb,lognormalUncLowerBnds)}, {"lnuv_means",6,4,1,1,kw_389,0.,0.,3,N_vam(RealLb,lognormalUncMeans)}, {"lnuv_upper_bounds",6,0,3,0,0,0.,0.,3,N_vam(RealUb,lognormalUncUpperBnds)}, {"lower_bounds",14,0,2,0,0,0.,0.,0,N_vam(RealLb,lognormalUncLowerBnds)}, {"means",14,4,1,1,kw_389,0.,0.,0,N_vam(RealLb,lognormalUncMeans)}, {"upper_bounds",14,0,3,0,0,0.,0.,0,N_vam(RealUb,lognormalUncUpperBnds)} }
KeyWord kw_391[7] [static] |
{ {"descriptors",15,0,4,0,0,0.,0.,0,N_vae(caulbl,CAUVar_loguniform)}, {"initial_point",14,0,3,0,0,0.,0.,0,N_vam(RealLb,loguniformUncVars)}, {"lower_bounds",14,0,1,1,0,0.,0.,0,N_vam(RealLb,loguniformUncLowerBnds)}, {"luuv_descriptors",7,0,4,0,0,0.,0.,-3,N_vae(caulbl,CAUVar_loguniform)}, {"luuv_lower_bounds",6,0,1,1,0,0.,0.,-2,N_vam(RealLb,loguniformUncLowerBnds)}, {"luuv_upper_bounds",6,0,2,2,0,0.,0.,1,N_vam(RealUb,loguniformUncUpperBnds)}, {"upper_bounds",14,0,2,2,0,0.,0.,0,N_vam(RealUb,loguniformUncUpperBnds)} }
KeyWord kw_392[5] [static] |
{ {"descriptors",15,0,4,0,0,0.,0.,0,N_vae(dauilbl,DAUIVar_negative_binomial)}, {"initial_point",13,0,3,0,0,0.,0.,0,N_vam(IntLb,negBinomialUncVars)}, {"num_trials",13,0,2,2,0,0.,0.,0,N_vam(IntLb,negBinomialUncNumTrials)}, {"prob_per_trial",6,0,1,1,0,0.,0.,1,N_vam(rvec,negBinomialUncProbPerTrial)}, {"probability_per_trial",14,0,1,1,0,0.,0.,0,N_vam(rvec,negBinomialUncProbPerTrial)} }
KeyWord kw_393[11] [static] |
{ {"descriptors",15,0,6,0,0,0.,0.,0,N_vae(caulbl,CAUVar_normal)}, {"initial_point",14,0,5,0,0,0.,0.,0,N_vam(rvec,normalUncVars)}, {"lower_bounds",14,0,3,0,0,0.,0.,0,N_vam(rvec,normalUncLowerBnds)}, {"means",14,0,1,1,0,0.,0.,0,N_vam(rvec,normalUncMeans)}, {"nuv_descriptors",7,0,6,0,0,0.,0.,-4,N_vae(caulbl,CAUVar_normal)}, {"nuv_lower_bounds",6,0,3,0,0,0.,0.,-3,N_vam(rvec,normalUncLowerBnds)}, {"nuv_means",6,0,1,1,0,0.,0.,-3,N_vam(rvec,normalUncMeans)}, {"nuv_std_deviations",6,0,2,2,0,0.,0.,2,N_vam(RealLb,normalUncStdDevs)}, {"nuv_upper_bounds",6,0,4,0,0,0.,0.,2,N_vam(rvec,normalUncUpperBnds)}, {"std_deviations",14,0,2,2,0,0.,0.,0,N_vam(RealLb,normalUncStdDevs)}, {"upper_bounds",14,0,4,0,0,0.,0.,0,N_vam(rvec,normalUncUpperBnds)} }
KeyWord kw_394[3] [static] |
{ {"descriptors",15,0,3,0,0,0.,0.,0,N_vae(dauilbl,DAUIVar_poisson)}, {"initial_point",13,0,2,0,0,0.,0.,0,N_vam(IntLb,poissonUncVars)}, {"lambdas",14,0,1,1,0,0.,0.,0,N_vam(RealLb,poissonUncLambdas)} }
KeyWord kw_395[9] [static] |
{ {"descriptors",15,0,5,0,0,0.,0.,0,N_vae(caulbl,CAUVar_triangular)}, {"initial_point",14,0,4,0,0,0.,0.,0,N_vam(rvec,triangularUncVars)}, {"lower_bounds",14,0,2,2,0,0.,0.,0,N_vam(RealLb,triangularUncLowerBnds)}, {"modes",14,0,1,1,0,0.,0.,0,N_vam(rvec,triangularUncModes)}, {"tuv_descriptors",7,0,5,0,0,0.,0.,-4,N_vae(caulbl,CAUVar_triangular)}, {"tuv_lower_bounds",6,0,2,2,0,0.,0.,-3,N_vam(RealLb,triangularUncLowerBnds)}, {"tuv_modes",6,0,1,1,0,0.,0.,-3,N_vam(rvec,triangularUncModes)}, {"tuv_upper_bounds",6,0,3,3,0,0.,0.,1,N_vam(RealUb,triangularUncUpperBnds)}, {"upper_bounds",14,0,3,3,0,0.,0.,0,N_vam(RealUb,triangularUncUpperBnds)} }
KeyWord kw_396[7] [static] |
{ {"descriptors",15,0,4,0,0,0.,0.,0,N_vae(caulbl,CAUVar_uniform)}, {"initial_point",14,0,3,0,0,0.,0.,0,N_vam(rvec,uniformUncVars)}, {"lower_bounds",14,0,1,1,0,0.,0.,0,N_vam(RealLb,uniformUncLowerBnds)}, {"upper_bounds",14,0,2,2,0,0.,0.,0,N_vam(RealUb,uniformUncUpperBnds)}, {"uuv_descriptors",7,0,4,0,0,0.,0.,-4,N_vae(caulbl,CAUVar_uniform)}, {"uuv_lower_bounds",6,0,1,1,0,0.,0.,-3,N_vam(RealLb,uniformUncLowerBnds)}, {"uuv_upper_bounds",6,0,2,2,0,0.,0.,-3,N_vam(RealUb,uniformUncUpperBnds)} }
KeyWord kw_397[7] [static] |
{ {"alphas",14,0,1,1,0,0.,0.,0,N_vam(RealLb,weibullUncAlphas)}, {"betas",14,0,2,2,0,0.,0.,0,N_vam(RealLb,weibullUncBetas)}, {"descriptors",15,0,4,0,0,0.,0.,0,N_vae(caulbl,CAUVar_weibull)}, {"initial_point",14,0,3,0,0,0.,0.,0,N_vam(RealLb,weibullUncVars)}, {"wuv_alphas",6,0,1,1,0,0.,0.,-4,N_vam(RealLb,weibullUncAlphas)}, {"wuv_betas",6,0,2,2,0,0.,0.,-4,N_vam(RealLb,weibullUncBetas)}, {"wuv_descriptors",7,0,4,0,0,0.,0.,-4,N_vae(caulbl,CAUVar_weibull)} }
KeyWord kw_399[6] [static] |
{ {"environment",0x108,15,1,1,kw_12,0.,0.,0,NIDRProblemDescDB::env_start}, {"interface",0x308,9,5,5,kw_26,0.,0.,0,N_ifm3(start,0,stop)}, {"method",0x308,90,2,2,kw_291,0.,0.,0,N_mdm3(start,0,stop)}, {"model",8,7,3,3,kw_327,0.,0.,0,N_mom3(start,0,stop)}, {"responses",0x308,19,6,6,kw_353,0.,0.,0,N_rem3(start,0,stop)}, {"variables",0x308,34,4,4,kw_398,0.,0.,0,N_vam3(start,0,stop)} }
Var_uinfo CAUVLbl[CAUVar_Nkinds] [static] |
{ VarLabelInfo(nuv_, NormalUnc), VarLabelInfo(lnuv_, LognormalUnc), VarLabelInfo(uuv_, UniformUnc), VarLabelInfo(luuv_, LoguniformUnc), VarLabelInfo(tuv_, TriangularUnc), VarLabelInfo(euv_, ExponentialUnc), VarLabelInfo(beuv_, BetaUnc), VarLabelInfo(gauv_, GammaUnc), VarLabelInfo(guuv_, GumbelUnc), VarLabelInfo(fuv_, FrechetUnc), VarLabelInfo(wuv_, WeibullUnc), VarLabelInfo(hbuv_, HistogramBinUnc) }
Var_uinfo DAUIVLbl[DAUIVar_Nkinds] [static] |
{ VarLabelInfo(puv_, PoissonUnc), VarLabelInfo(biuv_, BinomialUnc), VarLabelInfo(nbuv_, NegBinomialUnc), VarLabelInfo(geuv_, GeometricUnc), VarLabelInfo(hguv_, HyperGeomUnc), VarLabelInfo(hpiuv_, HistogramPtIntUnc) }
Var_uinfo DAUSVLbl[DAUSVar_Nkinds] [static] |
{ VarLabelInfo(hpsuv_, HistogramPtStrUnc) }
Var_uinfo DAURVLbl[DAURVar_Nkinds] [static] |
{ VarLabelInfo(hpruv_, HistogramPtRealUnc) }
Var_uinfo CEUVLbl[CEUVar_Nkinds] [static] |
{ VarLabelInfo(ciuv_, ContinuousIntervalUnc) }
Var_uinfo DEUIVLbl[DEUIVar_Nkinds] [static] |
{ VarLabelInfo(diuv_, DiscreteIntervalUnc), VarLabelInfo(dusiv_, DiscreteUncSetInt) }
Var_uinfo DEUSVLbl[DEUSVar_Nkinds] [static] |
{ VarLabelInfo(dussv_, DiscreteUncSetStr) }
Var_uinfo DEURVLbl[DEURVar_Nkinds] [static] |
{ VarLabelInfo(dusrv_, DiscreteUncSetReal) }
Var_uinfo DiscSetLbl[DiscSetVar_Nkinds] [static] |
{ VarLabelInfo(ddsiv_, DiscreteDesSetInt), VarLabelInfo(ddssv_, DiscreteDesSetStr), VarLabelInfo(ddsrv_, DiscreteDesSetReal), VarLabelInfo(dssiv_, DiscreteStateSetInt), VarLabelInfo(dsssv_, DiscreteStateSetStr), VarLabelInfo(dssrv_, DiscreteStateSetReal) }
VarLabelChk DesignAndStateLabelsCheck[] [static] |
{ { AVI numContinuousDesVars, AVI continuousDesignLabels, "cdv_", "cdv_descriptors" }, { AVI numDiscreteDesRangeVars, AVI discreteDesignRangeLabels, "ddriv_", "ddriv_descriptors" }, { AVI numDiscreteDesSetIntVars, AVI discreteDesignSetIntLabels, "ddsiv_", "ddsiv_descriptors" }, { AVI numDiscreteDesSetStrVars, AVI discreteDesignSetStrLabels, "ddssv_", "ddssv_descriptors" }, { AVI numDiscreteDesSetRealVars, AVI discreteDesignSetRealLabels, "ddsrv_", "ddsrv_descriptors" }, { AVI numContinuousStateVars, AVI continuousStateLabels, "csv_", "csv_descriptors" }, { AVI numDiscreteStateRangeVars, AVI discreteStateRangeLabels, "dsriv_", "dsriv_descriptors" }, { AVI numDiscreteStateSetIntVars, AVI discreteStateSetIntLabels, "dssiv_", "dssiv_descriptors" }, { AVI numDiscreteStateSetStrVars, AVI discreteStateSetStrLabels, "dsssv_", "dsssv_descriptors" }, { AVI numDiscreteStateSetRealVars, AVI discreteStateSetRealLabels, "dssrv_", "dssrv_descriptors" }, { AVI numContinuousDesVars, AVI continuousDesignScaleTypes, 0, "cdv_scale_types" } }
Variables label array designations for design and state. All non-uncertain variables need to be in this array. Used in check_variables_node to check lengths and make_variable_defaults to build labels.
Referenced by NIDRProblemDescDB::check_variables_node(), and NIDRProblemDescDB::make_variable_defaults().
VLreal VLUncertainReal[NUM_UNC_REAL_CONT] [static] |
{ {CAUVar_Nkinds, AVI CAUv, CAUVLbl, DVR continuousAleatoryUncLabels, DVR continuousAleatoryUncLowerBnds, DVR continuousAleatoryUncUpperBnds, DVR continuousAleatoryUncVars}, {CEUVar_Nkinds, AVI CEUv, CEUVLbl, DVR continuousEpistemicUncLabels, DVR continuousEpistemicUncLowerBnds, DVR continuousEpistemicUncUpperBnds, DVR continuousEpistemicUncVars}, {DAURVar_Nkinds, AVI DAURv, DAURVLbl, DVR discreteRealAleatoryUncLabels, DVR discreteRealAleatoryUncLowerBnds, DVR discreteRealAleatoryUncUpperBnds, DVR discreteRealAleatoryUncVars}, {DEURVar_Nkinds, AVI DEURv, DEURVLbl, DVR discreteRealEpistemicUncLabels, DVR discreteRealEpistemicUncLowerBnds, DVR discreteRealEpistemicUncUpperBnds, DVR discreteRealEpistemicUncVars}}
Variables labels/bounds/values check array for real-valued uncertain variables; one array entry per contiguous container. These associate the individual variables given by, e.g., CAUVLbl, with the contiguous container in which they are stored.
Referenced by NIDRProblemDescDB::check_variables_node(), and NIDRProblemDescDB::make_variable_defaults().
VLint VLUncertainInt[NUM_UNC_INT_CONT] [static] |
{ {DAUIVar_Nkinds, AVI DAUIv, DAUIVLbl, DVR discreteIntAleatoryUncLabels, DVR discreteIntAleatoryUncLowerBnds, DVR discreteIntAleatoryUncUpperBnds, DVR discreteIntAleatoryUncVars}, {DEUIVar_Nkinds, AVI DEUIv, DEUIVLbl, DVR discreteIntEpistemicUncLabels, DVR discreteIntEpistemicUncLowerBnds, DVR discreteIntEpistemicUncUpperBnds, DVR discreteIntEpistemicUncVars}}
Variables labels/bounds/values check array for integer-valued uncertain variables; one array entry per contiguous container. These associate the individual variables given by, e.g., DAUIVLbl, with the contiguous container in which they are stored.
Referenced by NIDRProblemDescDB::check_variables_node(), and NIDRProblemDescDB::make_variable_defaults().
VLstr VLUncertainStr[NUM_UNC_STR_CONT] [static] |
{ {DAUSVar_Nkinds, AVI DAUSv, DAUSVLbl, DVR discreteStrAleatoryUncLabels, DVR discreteStrAleatoryUncLowerBnds, DVR discreteStrAleatoryUncUpperBnds, DVR discreteStrAleatoryUncVars}, {DEUSVar_Nkinds, AVI DEUSv, DEUSVLbl, DVR discreteStrEpistemicUncLabels, DVR discreteStrEpistemicUncLowerBnds, DVR discreteStrEpistemicUncUpperBnds, DVR discreteStrEpistemicUncVars}}
Variables labels/bounds/values check array for string-valued uncertain variables; one array entry per contiguous container. These associate the individual variables given by, e.g., DAUSVLbl, with the contiguous container in which they are stored.
Referenced by NIDRProblemDescDB::check_variables_node(), and NIDRProblemDescDB::make_variable_defaults().
Var_check var_mp_check_cv[] [static] |
{ Vchk_3(continuous_design,ContinuousDes), Vchk_3(continuous_state,ContinuousState) }
Var_check var_mp_check_dset[] [static] |
{ Vchk_3(discrete_design_set_integer,DiscreteDesSetInt), Vchk_3(discrete_design_set_string,DiscreteDesSetStr), Vchk_3(discrete_design_set_real,DiscreteDesSetReal), Vchk_3(discrete_state_set_integer,DiscreteStateSetInt), Vchk_3(discrete_state_set_string,DiscreteStateSetStr), Vchk_3(discrete_state_set_real,DiscreteStateSetReal) }
Var_check var_mp_check_cau[] [static] |
{ Vchk_3(normal_uncertain,NormalUnc), Vchk_3(lognormal_uncertain,LognormalUnc), Vchk_3(uniform_uncertain,UniformUnc), Vchk_3(loguniform_uncertain,LoguniformUnc), Vchk_3(triangular_uncertain,TriangularUnc), Vchk_3(exponential_uncertain,ExponentialUnc), Vchk_3(beta_uncertain,BetaUnc), Vchk_3(gamma_uncertain,GammaUnc), Vchk_3(gumbel_uncertain,GumbelUnc), Vchk_3(frechet_uncertain,FrechetUnc), Vchk_3(weibull_uncertain,WeibullUnc), Vchk_3(histogram_bin_uncertain,HistogramBinUnc) }
Var_check var_mp_check_daui[] [static] |
{ Vchk_3(poisson_uncertain,PoissonUnc), Vchk_3(binomial_uncertain,BinomialUnc), Vchk_3(negative_binomial_uncertain,NegBinomialUnc), Vchk_3(geometric_uncertain,GeometricUnc), Vchk_3(hypergeometric_uncertain,HyperGeomUnc), Vchk_3(histogram_point_int_uncertain,HistogramPtIntUnc) }
Var_check var_mp_check_daus[] [static] |
{ Vchk_3(histogram_point_str_uncertain,HistogramPtStrUnc) }
Var_check var_mp_check_daur[] [static] |
{ Vchk_3(histogram_point_real_uncertain,HistogramPtRealUnc) }
Var_check var_mp_check_ceu[] [static] |
{ Vchk_3(continuous_interval_uncertain,ContinuousIntervalUnc) }
Var_check var_mp_check_deui[] [static] |
{ Vchk_3(discrete_interval_uncertain,DiscreteIntervalUnc), Vchk_3(discrete_uncertain_set_integer,DiscreteUncSetInt) }
Var_check var_mp_check_deus[] [static] |
{ Vchk_3(discrete_uncertain_set_string,DiscreteUncSetStr) }
Var_check var_mp_check_deur[] [static] |
{ Vchk_3(discrete_uncertain_set_real,DiscreteUncSetReal) }
Var_rcheck var_mp_cbound[] [static] |
{ Vchk_7(continuous_design,ContinuousDes,continuousDesign), Vchk_7(continuous_state,ContinuousState,continuousState), Vchk_5(normal_uncertain,NormalUnc,normalUnc), Vchk_5(lognormal_uncertain,LognormalUnc,lognormalUnc), Vchk_5(uniform_uncertain,UniformUnc,uniformUnc), Vchk_5(loguniform_uncertain,LoguniformUnc,loguniformUnc), Vchk_5(triangular_uncertain,TriangularUnc,triangularUnc), Vchk_5(beta_uncertain,BetaUnc,betaUnc) }
This is used within check_variables_node(): Var_RealBoundIPCheck() is applied to validate bounds and initial points.
Referenced by NIDRProblemDescDB::check_variables_node().
Var_icheck var_mp_drange[] [static] |
{ Vchk_7(discrete_design_range,DiscreteDesRange,discreteDesignRange), Vchk_7(discrete_state_range,DiscreteStateRange,discreteStateRange) }
This is used in check_variables_node(): Var_IntBoundIPCheck() is applied to validate bounds and initial points, and in make_variable_defaults(): Vgen_* is called to infer bounds.
Referenced by NIDRProblemDescDB::check_variables_node(), and NIDRProblemDescDB::make_variable_defaults().
const char* SCI_FIELD_NAMES[] |
{ "dakota_type", "numFns", "numVars", "numACV", "numADIV", "numADRV", "numDerivVars", "xC", "xDI", "xDR", "xCLabels", "xDILabels", "xDRLabels", "directFnASV", "directFnASM", "directFnDVV", "directFnDVV_bool", "fnFlag", "gradFlag", "hessFlag", "fnVals", "fnGrads", "fnHessians", "fnLabels", "failure", "currEvalId" }
fields to pass to Scilab in Dakota structure
Referenced by ScilabInterface::scilab_engine_run().
const int SCI_NUMBER_OF_FIELDS = 26 |
number of fields in above structure
Referenced by ScilabInterface::scilab_engine_run().