python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy Class Reference

Inheritance diagram for python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy:

Public Member Functions
	__init__ (self, refnums=0, epsilon=1e-6, level=0, deg=2)
	estimate (self, vol, grid, alpha, f, U, T, dd)

Public Attributes
	level

Constructor & Destructor Documentation

__init__()

python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__init__	(		self,
			refnums = 0,
			epsilon = 1e-6,
			level = 0,
			deg = 2
	)

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__, python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__epsilon, python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__init__(), and python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__refnums.

Referenced by python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__init__().

Member Function Documentation

estimate()

python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.estimate	(		self,
			vol,
			grid,
			alpha,
			f,
			U,
			T,
			dd
	)

Extraction of the expectation the given sg function
interpolating the product of function value and pdf.

\int\limits_{[0, 1]^d} v(x) dy

where v(x) := u(x) q(x)

References python.learner.LearnerBuilder.LearnerBuilder.GridDescriptor.__deg, python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__deg, python.uq.learner.builder.GridDescriptor.GridDescriptor.__deg, python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__epsilon, python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__extractPDFforMomentEstimation(), python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.__refnums, f, sgpp::base::HashGridPoint.level, sgpp::combigrid::FullGrid.level, sgpp::combigrid::OperationPoleHierarchisationGeneral::HierarchisationGeneralSLE.level, python.learner.folding.FilesFoldingPolicy.FilesFoldingPolicy.level, python.learner.folding.FoldingPolicy.FoldingPolicy.level, python.learner.folding.RandomFoldingPolicy.RandomFoldingPolicy.level, python.learner.folding.SequentialFoldingPolicy.SequentialFoldingPolicy.level, python.learner.folding.StratifiedFoldingPolicy.StratifiedFoldingPolicy.level, python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.level, python.uq.learner.builder.GridDescriptor.GridDescriptor.level, python.uq.learner.builder.RegressorSpecificationDescriptor.FoldingDescriptor.level, python.uq.learner.SimulationLearner.SimulationLearner.level, python.uq.manager.ASGCStatistics.ASGCStatistics.level, python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.level, sgpp::datadriven::AlgorithmAdaBoostBase.level, sgpp::datadriven::CombiScheme.level, sgpp::datadriven::LevelIndexPair.level, sgpp::datadriven::OperationMultiEvalModMaskStreaming.level, sgpp::datadriven::OperationMultiEvalStreamingBSplineOCL< T >.level, sgpp::datadriven::OperationMultiEvalStreamingModOCLFastMultiPlatform< T >.level, sgpp::datadriven::OperationMultiEvalStreamingModOCLMaskMultiPlatform< T >.level, sgpp::datadriven::OperationMultiEvalStreamingModOCLUnified< T >.level, sgpp::datadriven::StreamingOCLMultiPlatform::OperationMultiEvalStreamingOCLMultiPlatform< T >.level, sgpp::datadriven::SubspaceNodeCombined.level, and sgpp::datadriven::SubspaceNodeSimple.level.

Member Data Documentation

level

python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.level

Referenced by python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.__eq__(), python.learner.folding.FoldingPolicy.FoldingPolicy.__next__(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.contains(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.containsDimx(), python.uq.learner.builder.GridDescriptor.GridDescriptor.createGrid(), python.uq.estimators.MarginalIntegralStrategy.MarginalIntegralStrategy.estimate(), python.uq.learner.builder.GridDescriptor.GridDescriptor.fromGrid(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.getLevelIndex(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.getMaxLevel(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.overlap(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.overlapDimx(), python.uq.operations.forcePositivity.localFullGridSearch.LocalFullGrid.transformToReferenceGrid(), python.uq.manager.ASGCStatistics.ASGCStatistics.updateResults(), python.uq.learner.builder.GridDescriptor.GridDescriptor.withLevel(), and python.uq.learner.builder.RegressorSpecificationDescriptor.FoldingDescriptor.withLevel().

---

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

• datadriven/python/uq/estimators/MarginalIntegralStrategy.py