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SG++-Doxygen-Documentation
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Public Member Functions | |
__init__ (self) | |
update (self, grid, v, gpi, params, *args, **kws) | |
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getKnowledgeType (self) | |
rank (self, grid, gp, alphas, params, t=0, *args, **kws) | |
Additional Inherited Members | |
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_dtype | |
_ranking | |
python.uq.refinement.RefinementStrategy.AnchoredWeightedL2OptRanking.__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.AnchoredWeightedL2OptRanking.__init__().
Referenced by python.uq.refinement.RefinementStrategy.AnchoredWeightedL2OptRanking.__init__().
python.uq.refinement.RefinementStrategy.AnchoredWeightedL2OptRanking.update | ( | self, | |
grid, | |||
v, | |||
gpi, | |||
params, | |||
* | args, | ||
** | kws | ||
) |
Compute ranking for variance estimation \argmax_{i \in \A} |v_i| \sqrt{E[\varphi_i^2]} @param grid: Grid grid @param v: numpy array coefficients
Reimplemented from python.uq.refinement.RefinementStrategy.Ranking.
Referenced by python.uq.refinement.RefinementStrategy.Ranking.rank(), and python.learner.LearnedKnowledge.LearnedKnowledge.setMemento().