LeastSq Class Reference

Base class for the nonlinear least squares branch of the iterator hierarchy. More...

Inheritance diagram for LeastSq:

Protected Member Functions
	LeastSq (std::shared_ptr< TraitsBase > traits)
	default constructor
	LeastSq (ProblemDescDB &problem_db, Model &model, std::shared_ptr< TraitsBase > traits)
	standard constructor More...
	LeastSq (unsigned short method_name, Model &model, std::shared_ptr< TraitsBase > traits)
	alternate "on the fly" constructor
	~LeastSq ()
	destructor
void	initialize_run ()
void	post_run (std::ostream &s)
void	finalize_run ()
	utility function to perform common operations following post_run(); deallocation and resetting of instance pointers More...
void	print_results (std::ostream &s, short results_state=FINAL_RESULTS)
void	get_confidence_intervals (const Variables &native_vars, const Response &iter_resp)
	Calculate confidence intervals on estimated parameters. More...
Protected Member Functions inherited from Minimizer
	Minimizer (std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	default constructor
	Minimizer (ProblemDescDB &problem_db, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	standard constructor More...
	Minimizer (unsigned short method_name, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	alternate constructor for "on the fly" instantiations
	Minimizer (unsigned short method_name, size_t num_lin_ineq, size_t num_lin_eq, size_t num_nln_ineq, size_t num_nln_eq, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	alternate constructor for "on the fly" instantiations
	~Minimizer ()
	destructor
void	update_from_model (const Model &model)
	set inherited data attributes based on extractions from incoming model
void	initialize_run ()
	utility function to perform common operations prior to pre_run(); typically memory initialization; setting of instance pointers More...
void	post_run (std::ostream &s)
	post-run portion of run (optional); verbose to print results; re-implemented by Iterators that can read all Variables/Responses and perform final analysis phase in a standalone way More...
void	finalize_run ()
	utility function to perform common operations following post_run(); deallocation and resetting of instance pointers More...
const Model &	algorithm_space_model () const
Model	original_model (unsigned short recasts_left=0) const
	Return a shallow copy of the original model this Iterator was originally passed, optionally leaving recasts_left on top of it.
void	data_transform_model ()
	Wrap iteratedModel in a RecastModel that subtracts provided observed data from the primary response functions (variables and secondary responses are unchanged) More...
void	scale_model ()
	Wrap iteratedModel in a RecastModel that performs variable and/or response scaling. More...
Real	objective (const RealVector &fn_vals, const BoolDeque &max_sense, const RealVector &primary_wts) const
	compute a composite objective value from one or more primary functions More...
Real	objective (const RealVector &fn_vals, size_t num_fns, const BoolDeque &max_sense, const RealVector &primary_wts) const
	compute a composite objective with specified number of source primary functions, instead of userPrimaryFns More...
void	objective_gradient (const RealVector &fn_vals, const RealMatrix &fn_grads, const BoolDeque &max_sense, const RealVector &primary_wts, RealVector &obj_grad) const
	compute the gradient of the composite objective function
void	objective_gradient (const RealVector &fn_vals, size_t num_fns, const RealMatrix &fn_grads, const BoolDeque &max_sense, const RealVector &primary_wts, RealVector &obj_grad) const
	compute the gradient of the composite objective function More...
void	objective_hessian (const RealVector &fn_vals, const RealMatrix &fn_grads, const RealSymMatrixArray &fn_hessians, const BoolDeque &max_sense, const RealVector &primary_wts, RealSymMatrix &obj_hess) const
	compute the Hessian of the composite objective function
void	objective_hessian (const RealVector &fn_vals, size_t num_fns, const RealMatrix &fn_grads, const RealSymMatrixArray &fn_hessians, const BoolDeque &max_sense, const RealVector &primary_wts, RealSymMatrix &obj_hess) const
	compute the Hessian of the composite objective function More...
void	archive_best_variables (const bool active_only=false) const
	archive best variables for the index'th final solution
void	archive_best_objective_functions () const
	archive the index'th set of objective functions
void	archive_best_constraints () const
	archive the index'th set of constraints
void	archive_best_residuals () const
	Archive residuals when calibration terms are used.
void	resize_best_vars_array (size_t newsize)
	Safely resize the best variables array to newsize taking into account the envelope-letter design pattern and any recasting. More...
void	resize_best_resp_array (size_t newsize)
	Safely resize the best response array to newsize taking into account the envelope-letter design pattern and any recasting. More...
void	local_recast_retrieve (const Variables &vars, Response &response) const
	infers MOO/NLS solution from the solution of a single-objective optimizer More...
Protected Member Functions inherited from Iterator
	Iterator (BaseConstructor, ProblemDescDB &problem_db, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	constructor initializes the base class part of letter classes (BaseConstructor overloading avoids infinite recursion in the derived class constructors - Coplien, p. 139) More...
	Iterator (NoDBBaseConstructor, unsigned short method_name, Model &model, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	alternate constructor for base iterator classes constructed on the fly More...
	Iterator (NoDBBaseConstructor, unsigned short method_name, std::shared_ptr< TraitsBase > traits=std::shared_ptr< TraitsBase >(new TraitsBase()))
	alternate constructor for base iterator classes constructed on the fly More...
virtual void	derived_init_communicators (ParLevLIter pl_iter)
	derived class contributions to initializing the communicators associated with this Iterator instance
virtual const VariablesArray &	initial_points () const
	gets the multiple initial points for this iterator. This will only be meaningful after a call to initial_points mutator.
StrStrSizet	run_identifier () const
	get the unique run identifier based on method name, id, and number of executions
void	initialize_model_graphics (Model &model, int iterator_server_id)
	helper function that encapsulates initialization operations, modular on incoming Model instance More...
void	export_final_surrogates (Model &data_fit_surr_model)
	export final surrogates generated, e.g., GP in EGO and friends More...

Protected Attributes
size_t	numLeastSqTerms
	number of least squares terms
LeastSq *	prevLSqInstance
	pointer containing previous value of leastSqInstance
bool	weightFlag
	flag indicating whether weighted least squares is active
RealVector	confBoundsLower
	lower bounds for confidence intervals on calibration parameters
RealVector	confBoundsUpper
	upper bounds for confidence intervals on calibration parameters
RealVector	bestIterPriFns
	storage for iterator best primary functions (which shouldn't be stored in bestResponseArray when there are transformations)
bool	retrievedIterPriFns
	whether final primary iterator space functions have been retrieved (possibly by a derived class)
Protected Attributes inherited from Minimizer
size_t	numFunctions
	number of response functions
size_t	numContinuousVars
	number of active continuous vars
size_t	numDiscreteIntVars
	number of active discrete integer vars
size_t	numDiscreteStringVars
	number of active discrete string vars
size_t	numDiscreteRealVars
	number of active discrete real vars
Real	constraintTol
	optimizer/least squares constraint tolerance
Real	bigRealBoundSize
	cutoff value for inequality constraint and continuous variable bounds
int	bigIntBoundSize
	cutoff value for discrete variable bounds
size_t	numNonlinearIneqConstraints
	number of nonlinear inequality constraints
size_t	numNonlinearEqConstraints
	number of nonlinear equality constraints
size_t	numLinearIneqConstraints
	number of linear inequality constraints
size_t	numLinearEqConstraints
	number of linear equality constraints
size_t	numNonlinearConstraints
	total number of nonlinear constraints
size_t	numLinearConstraints
	total number of linear constraints
size_t	numConstraints
	total number of linear and nonlinear constraints
bool	optimizationFlag
	flag for use where optimization and NLS must be distinguished
size_t	numUserPrimaryFns
	number of objective functions or least squares terms in the inbound model; always initialize at Minimizer, even if overridden later
size_t	numIterPrimaryFns
	number of objective functions or least squares terms in iterator's view, after transformations; always initialize at Minimizer, even if overridden later
bool	boundConstraintFlag
	convenience flag for denoting the presence of user-specified bound constraints. Used for method selection and error checking.
bool	speculativeFlag
	flag for speculative gradient evaluations
bool	calibrationDataFlag
	flag indicating whether user-supplied calibration data is active
ExperimentData	expData
	Container for experimental data to which to calibrate model using least squares or other formulations which minimize SSE.
size_t	numExperiments
	number of experiments
size_t	numTotalCalibTerms
	number of total calibration terms (sum over experiments of number of experimental data per experiment, including field data)
Model	dataTransformModel
	Shallow copy of the data transformation model, when present (cached in case further wrapped by other transformations)
bool	scaleFlag
	whether Iterator-level scaling is active
Model	scalingModel
	Shallow copy of the scaling transformation model, when present (cached in case further wrapped by other transformations)
Minimizer *	prevMinInstance
	pointer containing previous value of minimizerInstance
bool	vendorNumericalGradFlag
	convenience flag for gradient_type == numerical && method_source == vendor
std::shared_ptr< TPLDataTransfer >	dataTransferHandler
	Emerging helper class for handling data transfers to/from Dakota and the underlying TPL.
Protected Attributes inherited from Iterator
ProblemDescDB &	probDescDB
	class member reference to the problem description database More...
ParallelLibrary &	parallelLib
	class member reference to the parallel library
ParConfigLIter	methodPCIter
	the active ParallelConfiguration used by this Iterator instance
Model	iteratedModel
	the model to be iterated (for iterators and meta-iterators employing a single model instance)
size_t	myModelLayers
	number of Models locally (in Iterator or derived classes) wrapped around the initially passed in Model
unsigned short	methodName
	name of the iterator (the user's method spec)
Real	convergenceTol
	iteration convergence tolerance
size_t	maxIterations
	maximum number of iterations for the method
size_t	maxFunctionEvals
	maximum number of fn evaluations for the method
int	maxEvalConcurrency
	maximum number of concurrent model evaluations More...
ActiveSet	activeSet
	the response data requirements on each function evaluation
size_t	numFinalSolutions
	number of solutions to retain in best variables/response arrays
VariablesArray	bestVariablesArray
	collection of N best solution variables found during the study; always in context of Model originally passed to the Iterator (any in-flight Recasts must be undone)
ResponseArray	bestResponseArray
	collection of N best solution responses found during the study; always in context of Model originally passed to the Iterator (any in-flight Recasts must be undone)
bool	subIteratorFlag
	flag indicating if this Iterator is a sub-iterator (NestedModel::subIterator or DataFitSurrModel::daceIterator)
short	outputLevel
	output verbosity level: {SILENT,QUIET,NORMAL,VERBOSE,DEBUG}_OUTPUT
bool	summaryOutputFlag
	flag for summary output (evaluation stats, final results); default true, but false for on-the-fly (helper) iterators and sub-iterator use cases
ResultsManager &	resultsDB
	reference to the global iterator results database
EvaluationStore &	evaluationsDB
	reference to the global evaluation database
EvaluationsDBState	evaluationsDBState
	State of evaluations DB for this iterator.
ResultsNames	resultsNames
	valid names for iterator results
std::shared_ptr< TraitsBase >	methodTraits
	pointer that retains shared ownership of a TraitsBase object, or child thereof
bool	topLevel
	Whether this is the top level iterator.
bool	exportSurrogate = false
	whether to export final surrogates
String	surrExportPrefix
	base filename for exported surrogates
unsigned short	surrExportFormat = NO_MODEL_FORMAT
	(bitwise) format(s) to export

Static Protected Attributes
static LeastSq *	leastSqInstance
	pointer to LeastSq instance used in static member functions
Static Protected Attributes inherited from Minimizer
static Minimizer *	minimizerInstance
	pointer to Minimizer used in static member functions

Private Member Functions
void	weight_model ()
	Wrap iteratedModel in a RecastModel that weights the residuals. More...
void	archive_best_results ()
	top-level archival method

Additional Inherited Members
Public Member Functions inherited from Minimizer
void	constraint_tolerance (Real constr_tol)
	set the method constraint tolerance (constraintTol)
Real	constraint_tolerance () const
	return the method constraint tolerance (constraintTol)
std::shared_ptr< TPLDataTransfer >	get_data_transfer_helper () const
bool	resize ()
	reinitializes iterator based on new variable size
Static Public Member Functions inherited from Minimizer
static Real	sum_squared_residuals (size_t num_pri_fns, const RealVector &residuals, const RealVector &weights)
	return weighted sum of squared residuals
static void	print_residuals (size_t num_terms, const RealVector &best_terms, const RealVector &weights, size_t num_best, size_t best_index, std::ostream &s)
	print num_terms residuals and misfit for final results
static void	print_model_resp (size_t num_pri_fns, const RealVector &best_fns, size_t num_best, size_t best_index, std::ostream &s)
	print the original user model resp in the case of data transformations
Static Protected Member Functions inherited from Iterator
static void	gnewton_set_recast (const Variables &recast_vars, const ActiveSet &recast_set, ActiveSet &sub_model_set)
	conversion of request vector values for the Gauss-Newton Hessian approximation More...

Detailed Description

Base class for the nonlinear least squares branch of the iterator hierarchy.

The LeastSq class provides common data and functionality for least squares solvers (including NL2OL, NLSSOLLeastSq, and SNLLLeastSq.

Constructor & Destructor Documentation

LeastSq ( ProblemDescDB &  problem_db, Model &  model, std::shared_ptr< TraitsBase >  traits  )

protected

standard constructor

This constructor extracts the inherited data for the least squares branch and performs sanity checking on gradient and constraint settings.

References Dakota::abort_handler(), Iterator::bestVariablesArray, Minimizer::calibrationDataFlag, Variables::copy(), Model::current_variables(), Minimizer::data_transform_model(), Iterator::iteratedModel, Iterator::methodName, LeastSq::numLeastSqTerms, Minimizer::numTotalCalibTerms, Minimizer::optimizationFlag, Model::primary_fn_type(), Minimizer::scale_model(), Minimizer::scaleFlag, LeastSq::weight_model(), and LeastSq::weightFlag.

Member Function Documentation

void initialize_run ( )

protectedvirtual

This function should be invoked (or reimplemented) by any derived implementations of initialize_run() (which would otherwise hide it).

Reimplemented from Iterator.

Reimplemented in SNLLLeastSq.

References LeastSq::bestIterPriFns, Minimizer::initialize_run(), Iterator::iteratedModel, LeastSq::leastSqInstance, Iterator::myModelLayers, LeastSq::prevLSqInstance, LeastSq::retrievedIterPriFns, and Model::update_from_subordinate_model().

Referenced by SNLLLeastSq::initialize_run().

void post_run ( std::ostream &  s)

protectedvirtual

Implements portions of post_run specific to LeastSq for scaling back to native variables and functions. This function should be invoked (or reimplemented) by any derived implementations of post_run() (which would otherwise hide it).

Reimplemented from Iterator.

References Dakota::abort_handler(), Iterator::activeSet, LeastSq::bestIterPriFns, Iterator::bestResponseArray, Iterator::bestVariablesArray, Minimizer::calibrationDataFlag, Variables::continuous_variables(), Model::continuous_variables(), Response::copy(), Variables::copy(), Dakota::copy_data_partial(), Model::current_response(), Model::db_lookup(), Model::evaluate(), Response::function_gradients(), Response::function_values(), Response::function_values_view(), LeastSq::get_confidence_intervals(), Iterator::iteratedModel, Model::model_rep(), Minimizer::numContinuousVars, LeastSq::numLeastSqTerms, Minimizer::numNonlinearConstraints, Minimizer::numUserPrimaryFns, Minimizer::original_model(), Iterator::outputLevel, Minimizer::post_run(), ActiveSet::request_value(), ActiveSet::request_values(), ActiveSet::request_vector(), LeastSq::retrievedIterPriFns, Minimizer::scaleFlag, Minimizer::scalingModel, Minimizer::vendorNumericalGradFlag, and LeastSq::weightFlag.

void finalize_run ( )

inlineprotectedvirtual

utility function to perform common operations following post_run(); deallocation and resetting of instance pointers

Optional: perform finalization phases of run sequence, like deallocating memory and resetting instance pointers. Commonly used in sub-iterator executions. This is a virtual function; when re-implementing, a derived class must call its nearest parent's finalize_run(), typically after performing its own implementation steps.

Reimplemented from Iterator.

Reimplemented in SNLLLeastSq.

References Minimizer::finalize_run(), LeastSq::leastSqInstance, and LeastSq::prevLSqInstance.

Referenced by SNLLLeastSq::finalize_run().

void print_results ( std::ostream &  s, short  results_state = FINAL_RESULTS  )

protectedvirtual

Redefines default iterator results printing to include nonlinear least squares results (residual terms and constraints).

Reimplemented from Iterator.

References Iterator::activeSet, Iterator::bestResponseArray, Iterator::bestVariablesArray, Minimizer::calibrationDataFlag, LeastSq::confBoundsLower, LeastSq::confBoundsUpper, Model::continuous_variable_labels(), Dakota::data_pairs, Minimizer::dataTransformModel, Minimizer::expData, Model::interface_id(), Iterator::iteratedModel, Dakota::lookup_by_val(), Model::model_rep(), ExperimentData::num_config_vars(), ExperimentData::num_experiments(), Minimizer::numContinuousVars, Minimizer::numNonlinearConstraints, Minimizer::numUserPrimaryFns, Minimizer::original_model(), DataTransformModel::print_best_responses(), Minimizer::print_residuals(), ActiveSet::request_values(), Model::response_size(), Minimizer::scaleFlag, LeastSq::weightFlag, Variables::write(), and Dakota::write_precision.

void get_confidence_intervals ( const Variables &  native_vars, const Response &  iter_resp  )

protected

Calculate confidence intervals on estimated parameters.

Calculate individual confidence intervals for each parameter, based on a linear approximation of the nonlinear model. native_cv are needed for transformations and final reporting. iter_resp must contain the final differenced, scaled, weighted residuals and gradients.

References LeastSq::confBoundsLower, LeastSq::confBoundsUpper, Variables::continuous_variables(), Response::copy(), Response::function_gradients_view(), Response::function_values(), Model::model_rep(), Minimizer::numContinuousVars, LeastSq::numLeastSqTerms, ScalingModel::response_modify_s2n(), Minimizer::scaleFlag, Minimizer::scalingModel, and Minimizer::vendorNumericalGradFlag.

Referenced by LeastSq::post_run().

void weight_model ( )

private

Wrap iteratedModel in a RecastModel that weights the residuals.

Setup Recast for weighting model. The weighting transformation doesn't resize, and makes no vars, active set or secondary mapping. All indices are one-to-one mapped (no change in counts).

References Dakota::abort_handler(), Model::assign_rep(), Iterator::iteratedModel, Iterator::myModelLayers, Iterator::outputLevel, and Model::primary_response_fn_weights().

Referenced by LeastSq::LeastSq().

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

• DakotaLeastSq.hpp
• DakotaLeastSq.cpp