NL2SOLLeastSq Class Reference

Wrapper class for the NL2SOL nonlinear least squares library. More...

Inheritance diagram for NL2SOLLeastSq:

Public Member Functions
	NL2SOLLeastSq (ProblemDescDB &problem_db, Model &model)
	standard constructor
	NL2SOLLeastSq (Model &model)
	alternate constructor
	~NL2SOLLeastSq ()
	destructor
void	core_run ()
	core portion of run; implemented by all derived classes and may include pre/post steps in lieu of separate pre/post More...

Static Private Member Functions
static void	calcr (int *np, int *pp, Real *x, int *nfp, Real *r, int *ui, void *ur, Vf vf)
	evaluator function for residual vector
static void	calcj (int *np, int *pp, Real *x, int *nfp, Real *J, int *ui, void *ur, Vf vf)
	evaluator function for residual Jacobian

Private Attributes
int	auxprt
	auxilary printing bits (see Dakota Ref Manual): sum of < 1 = x0prt (print initial guess) < 2 = solprt (print final solution) < 4 = statpr (print solution statistics) < 8 = parprt (print nondefault parameters) < 16 = dradpr (print bound constraint drops/adds) < debug/verbose/normal use default = 31 (everything), < quiet uses 3, silent uses 0.
int	outlev
	frequency of output summary lines in number of iterations < (debug/verbose/normal/quiet use default = 1, silent uses 0)
Real	dltfdj
	finite-diff step size for computing Jacobian approximation < (fd_gradient_step_size)
Real	delta0
	finite-diff step size for gradient differences for H < (a component of some covariance approximations, if desired) < (fd_hessian_step_size)
Real	dltfdc
	finite-diff step size for function differences for H < (fd_hessian_step_size)
int	mxfcal
	function-evaluation limit (max_function_evaluations)
int	mxiter
	iteration limit (max_iterations)
Real	rfctol
	relative fn convergence tolerance (convergence_tolerance)
Real	afctol
	absolute fn convergence tolerance (absolute_conv_tol)
Real	xctol
	x-convergence tolerance (x_conv_tol)
Real	sctol
	singular convergence tolerance (singular_conv_tol)
Real	lmaxs
	radius for singular-convergence test (singular_radius)
Real	xftol
	false-convergence tolerance (false_conv_tol)
int	covreq
	kind of covariance required (\c covariance): < 1 or -1 ==> sigma^2 H^-1 J^T J H^-1 < 2 or -2 ==> sigma^2 H^-1 < 3 or -3 ==> sigma^2 (J^T J)^-1 < 1 or 2 ==> use gradient diffs to estimate H < -1 or -2 ==> use function diffs to estimate H < default = 0 (no covariance)
int	rdreq
	whether to compute the regression diagnostic vector < (regression_diagnostics)
Real	fprec
	expected response function precision (function_precision)
Real	lmax0
	initial trust-region radius (initial_trust_radius)

Static Private Attributes
static NL2SOLLeastSq *	nl2solInstance
	pointer to the active object instance used within the static evaluator functions

Additional Inherited Members
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
Protected Member Functions inherited from LeastSq
	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...
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...
Protected Attributes inherited from LeastSq
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)
Static Protected Attributes inherited from LeastSq
static LeastSq *	leastSqInstance
	pointer to LeastSq instance used in static member functions

Detailed Description

Wrapper class for the NL2SOL nonlinear least squares library.

The NL2SOLLeastSq class provides a wrapper for NL2SOL (TOMS Algorithm 573), in the updated form of Port Library routines dn[fg][b ] from Bell Labs; see http://www.netlib.org/port/readme. The Fortran from Port has been turned into C by f2c. NL2SOL uses a function pointer approach for which passed functions must be either global functions or static member functions.

Member Function Documentation

void core_run ( )

virtual

core portion of run; implemented by all derived classes and may include pre/post steps in lieu of separate pre/post

Virtual run function for the iterator class hierarchy. All derived classes need to redefine it.

Details on the following subscript values appear in "Usage Summary for Selected Optimization Routines" by David M. Gay, Computing Science Technical Report No. 153, AT&T Bell Laboratories, 1990. http://netlib.bell-labs.com/cm/cs/cstr/153.ps.gz

Reimplemented from Iterator.

References NL2SOLLeastSq::afctol, NL2SOLLeastSq::auxprt, LeastSq::bestIterPriFns, Iterator::bestVariablesArray, Minimizer::boundConstraintFlag, NL2SOLLeastSq::calcj(), NL2SOLLeastSq::calcr(), Model::continuous_lower_bounds(), Model::continuous_upper_bounds(), Model::continuous_variables(), Dakota::copy_data(), NL2SOLLeastSq::covreq, NL2SOLLeastSq::delta0, NL2SOLLeastSq::dltfdc, NL2SOLLeastSq::dltfdj, NL2SOLLeastSq::fprec, Model::gradient_type(), Iterator::iteratedModel, NL2SOLLeastSq::lmax0, NL2SOLLeastSq::lmaxs, NL2SOLLeastSq::mxfcal, NL2SOLLeastSq::mxiter, NL2SOLLeastSq::nl2solInstance, Minimizer::numContinuousVars, LeastSq::numLeastSqTerms, NL2SOLLeastSq::outlev, NL2SOLLeastSq::rdreq, LeastSq::retrievedIterPriFns, NL2SOLLeastSq::rfctol, NL2SOLLeastSq::sctol, Minimizer::speculativeFlag, Minimizer::vendorNumericalGradFlag, NL2SOLLeastSq::xctol, and NL2SOLLeastSq::xftol.

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

• NL2SOLLeastSq.hpp
• NL2SOLLeastSq.cpp