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DataResponsesRep Class Reference

Body class for responses specification data. More...

List of all members.

Public Attributes

size_t numObjectiveFunctions
 number of objective functions (from the num_objective_functions specification in RespFnOpt)
size_t numNonlinearIneqConstraints
 number of nonlinear inequality constraints (from the num_nonlinear_inequality_constraints specification in RespFnOpt)
size_t numNonlinearEqConstraints
 number of nonlinear equality constraints (from the num_nonlinear_equality_constraints specification in RespFnOpt)
size_t numLeastSqTerms
 number of least squares terms (from the num_least_squares_terms specification in RespFnLS)
size_t numResponseFunctions
 number of generic response functions (from the num_response_functions specification in RespFnGen)
StringArray primaryRespFnScaleTypes
 vector of primary response function scaling types (from the objective_function_scale_types specification in RespFnOpt and the least_squares_term_scale_types specification in RespFnLS)
RealVector primaryRespFnScales
 vector of primary response function scaling factors (from the objective_function_scales specification in RespFnOpt and the least_squares_term_scales specification in RespFnLS)
RealVector primaryRespFnWeights
 vector of weightings for multiobjective optimization or weighted nonlinear least squares (from the multi_objective_weights specification in RespFnOpt and the least_squares_weights specification in RespFnLS)
String leastSqDataFile
 filename from which to read observation data to compute least squares residuals (from the least_squares_data_file specification in RespFnLS)
RealVector nonlinearIneqLowerBnds
 vector of nonlinear inequality constraint lower bounds (from the nonlinear_inequality_lower_bounds specification in RespFnOpt)
RealVector nonlinearIneqUpperBnds
 vector of nonlinear inequality constraint upper bounds (from the nonlinear_inequality_upper_bounds specification in RespFnOpt)
StringArray nonlinearIneqScaleTypes
 vector of nonlinear inequality constraint scaling types (from the nonlinear_inequality_scale_types specification in RespFnOpt)
RealVector nonlinearIneqScales
 vector of nonlinear inequality constraint scaling factors (from the nonlinear_inequality_scales specification in RespFnOpt)
RealVector nonlinearEqTargets
 vector of nonlinear equality constraint targets (from the nonlinear_equality_targets specification in RespFnOpt)
StringArray nonlinearEqScaleTypes
 vector of nonlinear equality constraint scaling types (from the nonlinear_equality_scale_types specification in RespFnOpt)
RealVector nonlinearEqScales
 vector of nonlinear equality constraint scaling factors (from the nonlinear_equality_scales specification in RespFnOpt)
String gradientType
 gradient type: none, numerical, analytic, or mixed (from the no_gradients, numerical_gradients, analytic_gradients, and mixed_gradients specifications in RespGrad)
String hessianType
 Hessian type: none, numerical, quasi, analytic, or mixed (from the no_hessians, numerical_hessians, quasi_hessians, analytic_hessians, and mixed_hessians specifications in RespHess)
bool ignoreBounds
 option to ignore bounds when doing finite differences (default is to honor bounds)
bool centralHess
 Temporary(?) option to use old 2nd-order diffs when computing finite-difference Hessians; default is forward differences.
String quasiHessianType
 quasi-Hessian type: bfgs, damped_bfgs, or sr1 (from the bfgs and sr1 specifications in RespHess)
String methodSource
 numerical gradient method source: dakota or vendor (from the method_source specification in RespGradNum and RespGradMixed)
String intervalType
 numerical gradient interval type: forward or central (from the interval_type specification in RespGradNum and RespGradMixed)
RealVector fdGradStepSize
 vector of finite difference step sizes for numerical gradients, one step size per active continuous variable, used in computing 1st-order forward or central differences (from the fd_gradient_step_size specification in RespGradNum and RespGradMixed)
RealVector fdHessStepSize
 vector of finite difference step sizes for numerical Hessians, one step size per active continuous variable, used in computing 1st-order gradient-based differences and 2nd-order function-based differences (from the fd_hessian_step_size specification in RespHessNum and RespHessMixed)
IntList idNumericalGrads
 mixed gradient numerical identifiers (from the id_numerical_gradients specification in RespGradMixed)
IntList idAnalyticGrads
 mixed gradient analytic identifiers (from the id_analytic_gradients specification in RespGradMixed)
IntList idNumericalHessians
 mixed Hessian numerical identifiers (from the id_numerical_hessians specification in RespHessMixed)
IntList idQuasiHessians
 mixed Hessian quasi identifiers (from the id_quasi_hessians specification in RespHessMixed)
IntList idAnalyticHessians
 mixed Hessian analytic identifiers (from the id_analytic_hessians specification in RespHessMixed)
String idResponses
 string identifier for the responses specification data set (from the id_responses specification in RespSetId)
StringArray responseLabels
 the response labels array (from the response_descriptors specification in RespLabels)

Private Member Functions

 DataResponsesRep ()
 constructor
 ~DataResponsesRep ()
 destructor
void write (std::ostream &s) const
 write a DataResponsesRep object to an std::ostream
void read (MPIUnpackBuffer &s)
 read a DataResponsesRep object from a packed MPI buffer
void write (MPIPackBuffer &s) const
 write a DataResponsesRep object to a packed MPI buffer

Private Attributes

int referenceCount
 number of handle objects sharing this dataResponsesRep

Friends

class DataResponses
 the handle class can access attributes of the body class directly

Detailed Description

Body class for responses specification data.

The DataResponsesRep class is used to contain the data from a responses keyword specification. Default values are managed in the DataResponsesRep constructor. Data is public to avoid maintaining set/get functions, but is still encapsulated within ProblemDescDB since ProblemDescDB::dataResponsesList is private (a similar approach is used with SurrogateDataPoint objects contained in Dakota::Approximation).


The documentation for this class was generated from the following files: