NonDAdaptImpSampling Class Reference

Class for the Adaptive Importance Sampling methods within DAKOTA. More...

Inheritance diagram for NonDAdaptImpSampling:

List of all members.

Public Member Functions
	NonDAdaptImpSampling (Model &model)
	constructors
	NonDAdaptImpSampling (Model &model, const String &sample_type, int samples, int seed, const String &rng, short is_type, bool cdf_flag, bool x_space_data, bool x_space_model, bool bounded_model)
	~NonDAdaptImpSampling ()
	destructor
void	quantify_uncertainty ()
	performs an adaptive importance sampling and returns probability of failure.
void	initialize (const RealVectorArray &initial_points, int resp_fn, const Real &initial_prob, const Real &failure_threshold)
	initializes data needed for importance sampling: an initial set of points around which to sample, a failure threshold, an initial probability to refine, and flags to control transformations
void	initialize (const RealVector &initial_point, int resp_fn, const Real &initial_prob, const Real &failure_threshold)
	initializes data needed for importance sampling: an initial point around which to sample, a failure threshold, an initial probability to refine, and flags to control transformations
const Real &	get_probability ()
	returns the probability calculated by the importance sampling
Private Member Functions
void	converge_cov ()
	iteratively generate samples and select representative points until coefficient of variation converges
void	converge_probability ()
	iteratively generate samples from final set of representative points until probability converges
void	select_init_rep_points (const RealVectorArray &samples)
	select representative points from initial set of samples
void	select_rep_points (const RealVectorArray &samples)
	select representative points from a set of samples
void	calculate_rep_weights ()
	calculate relative weights of representative points
void	generate_samples (RealVectorArray &samples)
	generate a set of samples based on multimodal sampling density
void	calculate_statistics (const RealVectorArray &samples, const size_t &total_sample_number, Real &probability_sum, Real &probability, bool cov_flag, Real &variance_sum, Real &coeff_of_variation)
	calculate the probability of exceeding the failure threshold and the coefficent of variation (if requested)
Private Attributes
short	importanceSamplingType
	integration type (is, ais, mmais) provided by input specification
bool	invertProb
	flag for inversion of probability values using 1.-p
size_t	numRepPoints
	the number of representative points around which to sample
size_t	respFn
	the response function in the model to be sampled
RealVectorArray	initPoints
	the original set of samples passed into the MMAIS routine
RealVectorArray	repPoints
	the set of representative points around which to sample
RealVector	repWeights
	the weight associated with each representative point
RealVector	designPoint
	design point at which uncertain space is being sampled
bool	transInitPoints
	flag to control if x->u transformation should be performed for initial points
bool	transPoints
	flag to control if u->x transformation should be performed before evaluation
bool	useModelBounds
	flag to control if the sampler should respect the model bounds
bool	initLHS
	flag to identify if initial points are generated from an LHS sample
Real	initProb
	the initial probability (from FORM or SORM)
Real	finalProb
	the final calculated probability (p)
Real	failThresh
	the failure threshold (z-bar) for the problem.

---

Detailed Description

Class for the Adaptive Importance Sampling methods within DAKOTA.

The NonDAdaptImpSampling implements the multi-modal adaptive importance sampling used for reliability calculations. (eventually we will want to broaden this). Need to add more detail to this description.

---

Constructor & Destructor Documentation

NonDAdaptImpSampling

(

Model &

model

)

constructors

standard constructor

This is the primary constructor. It accepts a Model reference.

References NonD::initialize_random_variables(), and NonDSampling::samplingVarsMode.

NonDAdaptImpSampling	(	Model &	model,
		const String &	sample_type,
		int	samples,
		int	seed,
		const String &	rng,
		short	is_type,
		bool	cdf_flag,
		bool	x_space_data,
		bool	x_space_model,
		bool	bounded_model
	)

This is an alternate constructor for instantiations on the fly using a Model but no ProblemDescDB.

References NonD::cdfFlag, and NonDSampling::samplingVarsMode.

---

Member Function Documentation

void initialize	(	const RealVectorArray &	initial_points,
		int	resp_fn,
		const Real &	initial_prob,
		const Real &	failure_threshold
	)

initializes data needed for importance sampling: an initial set of points around which to sample, a failure threshold, an initial probability to refine, and flags to control transformations

Initializes data using a set of starting points.

References NonDAdaptImpSampling::designPoint, NonDAdaptImpSampling::failThresh, NonDAdaptImpSampling::initPoints, NonDAdaptImpSampling::initProb, NonD::natafTransform, NonD::numContDesVars, Iterator::numContinuousVars, NonD::numUncertainVars, NonDAdaptImpSampling::respFn, and NonDAdaptImpSampling::transInitPoints.

Referenced by NonDExpansion::compute_statistics(), NonDGlobalReliability::importance_sampling(), NonDLocalReliability::probability(), and NonDAdaptImpSampling::quantify_uncertainty().

void initialize	(	const RealVector &	initial_point,
		int	resp_fn,
		const Real &	initial_prob,
		const Real &	failure_threshold
	)

initializes data needed for importance sampling: an initial point around which to sample, a failure threshold, an initial probability to refine, and flags to control transformations

Initializes data using only one starting point.

References NonDAdaptImpSampling::designPoint, NonDAdaptImpSampling::failThresh, NonDAdaptImpSampling::initPoints, NonDAdaptImpSampling::initProb, NonD::natafTransform, NonD::numContDesVars, Iterator::numContinuousVars, NonD::numUncertainVars, NonDAdaptImpSampling::respFn, and NonDAdaptImpSampling::transInitPoints.

---

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

• NonDAdaptImpSampling.H
• NonDAdaptImpSampling.C