AK_SSAlgorithm

class otak.AK_SSAlgorithm(event, n_SS, n_DoE, sim_budget, basis, cov_model, proposal_range=1.0, target_proba=0.5, cv_target=0.05, criterion=2, verbose=False)

Class implementing AK SS algorithm

Event

ThresholdEvent based on composite vector of input variables on limit state function

N_SS

integer, number of SS samples

N_DoE

integer, number of samples in initial Kriging DoE

Sim_budget

integer, total simulation budget available

Basis

basis of kriging model

Cov_model

covariance model of kriging

Proposal_range

proposal range of SubsetSampling

Target_proba

targetProbability of SubsetSampling

Cv_target

target coefficient of variation

U_criterion

float, threshold value for u criterion

Verbose

verbosity parameter

Methods

compute_U(my_krig, list_id_evaluated)	Function computing the infill criterion
compute_proba()	Function computing failure probability using AK-SS
getCoefficientOfVariation()	Accessor to coefficient of variation
getDoE()	Accessor to the Design of Experiments, openturns.Sample
getEventSamples()	Accessor to Event samples, openturns.Sample
getFailureProbability()	Accessor to failure probability
getKrigingModel()	Accessor to Kriging model, openturns.KrigingResult
getSimBudget()	Accessor to the simulation budget

__init__(event, n_SS, n_DoE, sim_budget, basis, cov_model, proposal_range=1.0, target_proba=0.5, cv_target=0.05, criterion=2, verbose=False)

compute_U(my_krig, list_id_evaluated)

Function computing the infill criterion

My_krig

Kriging model openturns.KrigingResult

List_id_evaluated

list of evaluated openturns.Sample

compute_proba()

Function computing failure probability using AK-SS

getCoefficientOfVariation()

Accessor to coefficient of variation

getDoE()

Accessor to the Design of Experiments, openturns.Sample

getEventSamples()

Accessor to Event samples, openturns.Sample

getFailureProbability()

Accessor to failure probability

getKrigingModel()

Accessor to Kriging model, openturns.KrigingResult

getSimBudget()

Accessor to the simulation budget