Inheritance diagram for python.uq.refinement.RefinementStrategy.MeanSquaredOptRanking:

Public Member Functions
	__init__ (self)

	update (self, grid, v, gpi, params, args, *kws)

Public Member Functions inherited from python.uq.refinement.RefinementStrategy.Ranking
	getKnowledgeType (self)

	rank (self, grid, gp, alphas, params, t=0, args, *kws)

Protected Attributes
	_bilinearForm

	_linearForm

Protected Attributes inherited from python.uq.refinement.RefinementStrategy.Ranking
	_dtype

	_ranking

Constructor & Destructor Documentation

◆ init()

python.uq.refinement.RefinementStrategy.MeanSquaredOptRanking.__init__ ( self )

Reimplemented from python.uq.refinement.RefinementStrategy.Ranking.

References python.controller.InfoToScreenRegressor.InfoToScreenRegressor.__class__, python.uq.estimators.AnalyticEstimationStrategy.AnalyticEstimationStrategy.__class__, python.uq.estimators.MarginalAnalyticEstimationStrategy.MarginalAnalyticEstimationStrategy.__class__, python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__class__, python.uq.learner.builder.SimulationLearnerBuilder.SimulationLearnerBuilder.__class__, python.uq.learner.Regressor.Regressor.__class__, python.uq.learner.SimulationLearnerSpecification.SimulationLearnerSpecification.__class__, python.uq.quadrature.bilinearform.DiscreteBilinearScipyQuadratureStrategy.DiscreteBilinearScipyQuadratureStrategy.__class__, python.uq.quadrature.bilinearform.PiecewiseConstantQuadratureStrategy.PiecewiseConstantQuadratureStrategy.__class__, python.uq.quadrature.bilinearform.SparseGridQuadratureStrategy.SparseGridQuadratureStrategy.__class__, python.uq.quadrature.bilinearform.UniformQuadratureStrategy.UniformQuadratureStrategy.__class__, python.uq.refinement.RefinementStrategy.AnchoredWeightedL2OptRanking.__class__, python.uq.refinement.RefinementStrategy.WeightedL2OptRanking.__class__, python.uq.refinement.RefinementStrategy.AnchoredExpectationValueOptRanking.__class__, python.uq.refinement.RefinementStrategy.ExpectationValueOptRanking.__class__, python.uq.refinement.RefinementStrategy.VarianceOptRanking.__class__, python.uq.refinement.RefinementStrategy.AnchoredVarianceOptRanking.__class__, python.uq.refinement.RefinementStrategy.MeanSquaredOptRanking.__class__, python.uq.refinement.RefinementStrategy.AnchoredMeanSquaredOptRanking.__class__, python.uq.refinement.RefinementStrategy.SquaredSurplusBFRanking.__class__, python.uq.refinement.RefinementStrategy.WeightedL2BFRanking.__class__, python.uq.refinement.RefinementStrategy.VarianceBFRanking.__class__, python.uq.refinement.RefinementStrategy.ExpectationValueBFRanking.__class__, python.uq.refinement.RefinementStrategy.LinearSurplusEstimationRanking.__class__, python.uq.refinement.RefinementStrategy.PredictiveRanking.__class__, python.uq.sampler.asgc.ASGCSampler.ASGCSampler.__class__, python.uq.sampler.MCSampler.MCSampler.__class__, and python.uq.refinement.RefinementStrategy.MeanSquaredOptRanking.__init__().

Referenced by python.uq.refinement.RefinementStrategy.MeanSquaredOptRanking.__init__().

Member Function Documentation

◆ update()

python.uq.refinement.RefinementStrategy.MeanSquaredOptRanking.update	(		self,
			grid,
			v,
			gpi,
			params,
		*	args,
		**	kws
	)

Compute ranking for variance estimation

\argmax_{i \in \A} | v_i (2 A_i v_i - v_i b_i) |

@param grid: Grid grid
@param v: numpy array coefficients
@param admissibleSet: AdmissibleSet

Reimplemented from python.uq.refinement.RefinementStrategy.Ranking.

References python.uq.refinement.RefinementStrategy.MeanSquaredOptRanking._bilinearForm, python.uq.refinement.RefinementStrategy.ExpectationValueOptRanking._linearForm, and python.uq.refinement.RefinementStrategy.MeanSquaredOptRanking._linearForm.

Referenced by python.uq.refinement.RefinementStrategy.Ranking.rank(), and python.learner.LearnedKnowledge.LearnedKnowledge.setMemento().