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Dakota
Version 6.22
Explore and Predict with Confidence
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The Python class constructs a surrogate via python and has it ready for Dakota use. More...
Public Member Functions | |
| Python (const std::string &module_and_class_name) | |
| Constructor that sets moduleAndClassName and does not build. More... | |
| Python (const MatrixXd &samples, const MatrixXd &response, const std::string &module_and_class_name) | |
| Constructor sets moduleAndClassName and builds the python surrogate. More... | |
| ~Python () | |
| Default destructor. | |
| void | default_options () override |
| Construct and populate the defaultConfigOptions. | |
| virtual bool | diagnostics_available () override |
| void | build (const MatrixXd &samples, const MatrixXd &response) override |
| Build the python surrogate using specified build data. More... | |
| VectorXd | value (const MatrixXd &eval_points) override |
| Evaluate the scalar python surrogate at a set of prediction points. More... | |
| VectorXd | values (const MatrixXd &eval_points) override |
| Evaluate the field python surrogate at a set of prediction points. More... | |
| MatrixXd | gradient (const MatrixXd &eval_points) override |
| Evaluate the gradient of the python scalar surrogate at a set of prediction points. More... | |
| MatrixXd | hessian (const MatrixXd &eval_point) override |
| Evaluate the Hessian of the python scalar surrogate at a single point. More... | |
| std::shared_ptr< Surrogate > | clone () const override |
| clone derived Surrogate class for use in cross-validation | |
Public Member Functions inherited from Surrogate | |
| Surrogate () | |
| Constructor that uses defaultConfigOptions and does not build. | |
| Surrogate (const ParameterList ¶m_list) | |
| Constructor that sets configOptions but does not build. More... | |
| Surrogate (const MatrixXd &samples, const MatrixXd &response, const ParameterList ¶m_list) | |
| Constructor for the Surrogate that sets configOptions and builds the surrogate (does nothing in the base class). More... | |
| virtual | ~Surrogate () |
| Default destructor. | |
| MatrixXd | gradients (const MatrixXd &eval_points) |
| Evaluate the gradient of the field Surrogate at a set of prediction points. More... | |
| virtual MatrixXd | hessians (const MatrixXd &eval_point) |
| Evaluate the Hessian of the field Surrogate at a set of prediction points. More... | |
| void | variable_labels (const std::vector< std::string > &var_labels) |
| Set the variable/feature names. More... | |
| const std::vector< std::string > & | variable_labels () const |
| Get the (possibly empty) variable/feature names. More... | |
| void | response_labels (const std::vector< std::string > &resp_labels) |
| Set the response/QoI names. More... | |
| const std::vector< std::string > & | response_labels () const |
| Get the (possibly empty) response/QoI names. More... | |
| void | set_options (const ParameterList &options) |
| Set the Surrogate's configOptions. More... | |
| void | get_options (ParameterList &options) |
| Get the Surrogate's configOptions. More... | |
| void | print_options () |
| Print the Surrogate's configOptions. | |
| VectorXd | evaluate_metrics (const StringArray &mnames, const MatrixXd &points, const MatrixXd &ref_values) |
| Evalute metrics at specified points (within surrogates) | |
| VectorXd | cross_validate (const MatrixXd &samples, const MatrixXd &response, const StringArray &mnames, const int num_folds=5, const int seed=20) |
| Perform K-folds cross-validation (within surrogates) | |
| template<typename DerivedSurr > | |
| void | save (const DerivedSurr &surr_out, const std::string &outfile, const bool binary) |
| Serialize a derived (i.e. non-base) surrogate model. More... | |
| template<typename DerivedSurr > | |
| void | load (const std::string &infile, const bool binary, DerivedSurr &surr_in) |
| Load a derived (i.e. non-base) surrogate model. More... | |
Private Member Functions | |
| void | initialize_python () |
| Initialize python interpreter and callback module. | |
Private Attributes | |
| std::string | moduleAndClassName |
| Name of python callback module file. | |
| bool | ownPython |
| true if this class created the interpreter instance | |
| bool | pyModuleActive |
| true if python callback module is valid | |
| py::object | pySurrogate |
| python Surrogate class | |
| bool | isField |
| flag for field-based surrogates | |
| int | verbosity |
| Verbosity level. | |
Additional Inherited Members | |
Static Public Member Functions inherited from Surrogate | |
| template<typename SurrHandle > | |
| static void | save (const SurrHandle &surr_out, const std::string &outfile, const bool binary) |
| serialize Surrogate to file (typically through shared_ptr<Surrogate>, but Derived& or Derived* okay too) | |
| template<typename SurrHandle > | |
| static void | load (const std::string &infile, const bool binary, SurrHandle &surr_in) |
| serialize Surrogate from file (typically through shared_ptr<Surrogate>, but Derived& or Derived* okay too) | |
| static std::shared_ptr< Surrogate > | load (const std::string &infile, const bool binary) |
| serialize Surrogate from file through pointer to base class (must have been saved via same data type) | |
Public Attributes inherited from Surrogate | |
| util::DataScaler | dataScaler |
| DataScaler class for a Surrogate's build samples. | |
| double | responseOffset = 0. |
| Response offset. | |
| double | responseScaleFactor = 1. |
| Response scale factor. | |
Protected Attributes inherited from Surrogate | |
| int | numSamples |
| Number of samples in the Surrogate's build samples. | |
| int | numVariables |
| Number of features/variables in the Surrogate's build samples. | |
| std::vector< std::string > | variableLabels |
| Names of the variables/features; need not be populated. | |
| int | numQOI |
| Number of quantities of interest predicted by the surrogate. For scalar-valued surrogates numQOI = 1. | |
| std::vector< std::string > | responseLabels |
| Names of the responses/QoIs; need not be populated. | |
| ParameterList | defaultConfigOptions |
| Default Key/value options to configure the surrogate. | |
| ParameterList | configOptions |
| Key/value options to configure the surrogate - will override defaultConfigOptions. | |
| Python | ( | const std::string & | module_and_class_name | ) |
Constructor that sets moduleAndClassName and does not build.
| [in] | module_and_class_name | Name of python module file containing callback functions |
References Python::initialize_python().
| Python | ( | const MatrixXd & | samples, |
| const MatrixXd & | response, | ||
| const std::string & | module_and_class_name | ||
| ) |
Constructor sets moduleAndClassName and builds the python surrogate.
| [in] | samples | Matrix of data for surrogate construction - (num_samples by num_features) |
| [in] | response | Vector of targets for surrogate construction - (num_samples by num_qoi = 1; only 1 response is supported currently). |
| [in] | module_and_class_name | Name of python module file containing callback functions |
References Python::build(), and Python::initialize_python().
Build the python surrogate using specified build data.
| [in] | samples | Matrix of data for surrogate construction - (num_samples by num_features) |
| [in] | response | Vector of targets for surrogate construction - (num_samples by num_qoi = 1; only 1 response is supported currently). |
Implements Surrogate.
References Surrogate::configOptions, Python::isField, Python::moduleAndClassName, Python::pyModuleActive, Python::pySurrogate, and Python::verbosity.
Referenced by Python::Python().
Evaluate the scalar python surrogate at a set of prediction points.
| [in] | eval_points | Matrix of prediction points - (num_pts by num_features). |
Reimplemented from Surrogate.
References Python::pyModuleActive, and Python::pySurrogate.
Evaluate the field python surrogate at a set of prediction points.
| [in] | eval_points | Matrix of prediction points - (num_pts by num_features). |
Reimplemented from Surrogate.
References Python::pyModuleActive, and Python::pySurrogate.
Evaluate the gradient of the python scalar surrogate at a set of prediction points.
| [in] | eval_points | Coordinates of the prediction points - (num_pts by num_features). |
Reimplemented from Surrogate.
References Python::moduleAndClassName, Python::pyModuleActive, and Python::pySurrogate.
Evaluate the Hessian of the python scalar surrogate at a single point.
| [in] | eval_point | Coordinates of the prediction point - (1 by num_features). |
Reimplemented from Surrogate.
References Python::moduleAndClassName, Python::pyModuleActive, and Python::pySurrogate.