Body class for model specification data. More...
Public Attributes | |
String | idModel |
string identifier for the model specification data set (from the id_model specification in ModelIndControl) | |
String | modelType |
model type selection: single, surrogate, or nested (from the model type specification in ModelIndControl) | |
String | variablesPointer |
string pointer to the variables specification to be used by this model (from the variables_pointer specification in ModelIndControl) | |
String | interfacePointer |
string pointer to the interface specification to be used by this model (from the interface_pointer specification in ModelSingle and the optional_interface_pointer specification in ModelNested) | |
String | responsesPointer |
string pointer to the responses specification to be used by this model (from the responses_pointer specification in ModelIndControl) | |
String | subMethodPointer |
pointer to a sub-iterator used for global approximations (from the dace_method_pointer specification in ModelSurrG) or by nested models (from the sub_method_pointer specification in ModelNested) | |
IntSet | surrogateFnIndices |
array specifying the response function set that is approximated | |
String | surrogateType |
the selected surrogate type: local_taylor, multipoint_tana, global_(neural_network,mars,orthogonal_polynomial,gaussian, polynomial,kriging), or hierarchical | |
String | truthModelPointer |
pointer to the model specification for constructing the truth model used in building local, multipoint, and hierarchical approximations (from the actual_model_pointer specification in ModelSurrL and ModelSurrMP and the high_fidelity_model_pointer specification in ModelSurrH) | |
String | lowFidelityModelPointer |
pointer to the low fidelity model specification used in hierarchical approximations (from the low_fidelity_model_pointer specification in ModelSurrH) | |
int | pointsTotal |
user-specified lower bound on total points with which to build the model (if reuse_points < pointsTotal, new samples will make up the difference) | |
bool | pointsMinimum |
use the surrogate-specific minimum allowable points to build the model | |
bool | pointsRecommended |
use the surrogate-specific recommended number of points to build the model | |
String | approxPointReuse |
sample reuse selection for building global approximations: none, all, region, or file (from the reuse_samples specification in ModelSurrG) | |
String | approxPointReuseFile |
the file name for the "file" setting for the reuse_samples specification in ModelSurrG | |
String | approxCorrectionType |
correction type for global and hierarchical approximations: additive or multiplicative (from the correction specification in ModelSurrG and ModelSurrH) | |
short | approxCorrectionOrder |
correction order for global and hierarchical approximations: 0, 1, or 2 (from the correction specification in ModelSurrG and ModelSurrH) | |
bool | approxDerivUsageFlag |
flags the use of derivatives in building global approximations (from the use_derivatives specification in ModelSurrG) | |
short | polynomialOrder |
scalar integer indicating the order of the polynomial approximation (1=linear, 2=quadratic, 3=cubic; from the polynomial specification in ModelSurrG) | |
RealVector | krigingCorrelations |
vector of correlations used in building a kriging approximation (from the correlations specification in ModelSurrG) | |
String | krigingOptMethod |
optimization method to use in finding optimal correlation parameters: none, sampling, local, global | |
short | krigingMaxTrials |
maximum number of trials in optimization of kriging correlations | |
RealVector | krigingMaxCorrelations |
upper bound on kriging correlation vector | |
RealVector | krigingMinCorrelations |
lower bound on kriging correlation vector | |
short | mlsPolyOrder |
polynomial order for moving least squares approximation | |
short | mlsWeightFunction |
weight function for moving least squares approximation | |
short | rbfBases |
bases for radial basis function approximation | |
short | rbfMaxPts |
maximum number of points for radial basis function approximation | |
short | rbfMaxSubsets |
maximum number of subsets for radial basis function approximation | |
short | rbfMinPartition |
minimum partition for radial basis function approximation | |
short | marsMaxBases |
maximum number of bases for MARS approximation | |
String | marsInterpolation |
interpolation type for MARS approximation | |
short | annRandomWeight |
random weight for artificial neural network approximation | |
short | annNodes |
number of nodes for artificial neural network approximation | |
Real | annRange |
range for artificial neural network approximation | |
String | trendOrder |
scalar integer indicating the order of the Gaussian process mean (0= constant, 1=linear, 2=quadratic, 3=cubic); from the gaussian_process specification in ModelSurrG) | |
bool | pointSelection |
flag indicating the use of point selection in the Gaussian process | |
StringArray | diagMetrics |
List of diagnostic metrics the user requests to assess the goodness of fit for a surrogate model. | |
String | optionalInterfRespPointer |
string pointer to the responses specification used by the optional interface in nested models (from the optional_interface_responses_pointer specification in ModelNested) | |
StringArray | primaryVarMaps |
the primary variable mappings used in nested models for identifying the lower level variable targets for inserting top level variable values (from the primary_variable_mapping specification in ModelNested) | |
StringArray | secondaryVarMaps |
the secondary variable mappings used in nested models for identifying the (distribution) parameter targets within the lower level variables for inserting top level variable values (from the secondary_variable_mapping specification in ModelNested) | |
RealVector | primaryRespCoeffs |
the primary response mapping matrix used in nested models for weighting contributions from the sub-iterator responses in the top level (objective) functions (from the primary_response_mapping specification in ModelNested) | |
RealVector | secondaryRespCoeffs |
the secondary response mapping matrix used in nested models for weighting contributions from the sub-iterator responses in the top level (constraint) functions (from the secondary_response_mapping specification in ModelNested) | |
Private Member Functions | |
DataModelRep () | |
constructor | |
~DataModelRep () | |
destructor | |
void | write (std::ostream &s) const |
write a DataModelRep object to an std::ostream | |
void | read (MPIUnpackBuffer &s) |
read a DataModelRep object from a packed MPI buffer | |
void | write (MPIPackBuffer &s) const |
write a DataModelRep object to a packed MPI buffer | |
Private Attributes | |
int | referenceCount |
number of handle objects sharing this dataModelRep | |
Friends | |
class | DataModel |
the handle class can access attributes of the body class directly |
Body class for model specification data.
The DataModelRep class is used to contain the data from a model keyword specification. Default values are managed in the DataModelRep constructor. Data is public to avoid maintaining set/get functions, but is still encapsulated within ProblemDescDB since ProblemDescDB::dataModelList is private (a similar approach is used with SurrogateDataPoint objects contained in Dakota::Approximation).