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
Function computing failure probability using AK-SS
Accessor to coefficient of variation
getDoE
()Accessor to the Design of Experiments,
openturns.Sample
Accessor to Event samples,
openturns.Sample
Accessor to failure probability
Accessor to Kriging model,
openturns.KrigingResult
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