Class WeightingSelector
java.lang.Object
eu.qualimaster.easy.extension.internal.WeightingSelector
- All Implemented Interfaces:
net.ssehub.easy.instantiation.core.model.vilTypes.IVilType
public class WeightingSelector
extends Object
implements net.ssehub.easy.instantiation.core.model.vilTypes.IVilType
A simple selection of the "best" alternative via weighted values/predictions.
- Author:
- Holger Eichelberger
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptionstatic StringweightingSelection(net.ssehub.easy.instantiation.core.model.vilTypes.Map<String, net.ssehub.easy.instantiation.core.model.vilTypes.Map<eu.qualimaster.observables.IObservable, Double>> predictions, net.ssehub.easy.instantiation.core.model.vilTypes.Map<eu.qualimaster.observables.IObservable, Double> weighting) Implements a simple weighting of mass predictions.static StringweightingSelection(net.ssehub.easy.instantiation.core.model.vilTypes.Map<String, net.ssehub.easy.instantiation.core.model.vilTypes.Map<eu.qualimaster.observables.IObservable, Double>> predictions, net.ssehub.easy.instantiation.core.model.vilTypes.Map<eu.qualimaster.observables.IObservable, Double> weighting, net.ssehub.easy.instantiation.core.model.vilTypes.Set<eu.qualimaster.observables.IObservable> costs) Implements a simple weighting of mass predictions.
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Constructor Details
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WeightingSelector
public WeightingSelector()
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Method Details
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weightingSelection
public static String weightingSelection(net.ssehub.easy.instantiation.core.model.vilTypes.Map<String, net.ssehub.easy.instantiation.core.model.vilTypes.Map<eu.qualimaster.observables.IObservable, Double>> predictions, net.ssehub.easy.instantiation.core.model.vilTypes.Map<eu.qualimaster.observables.IObservable, Double> weighting) Implements a simple weighting of mass predictions.- Parameters:
predictions- the predictions given as name-observable-prediction mapping, may be null, entries may be nullweighting- the weighting of the observables, negative weights invert the value by subtracting from the respective maximum- Returns:
- the "best" solution in terms of the name of the element with maximum average weighted sum
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weightingSelection
public static String weightingSelection(net.ssehub.easy.instantiation.core.model.vilTypes.Map<String, net.ssehub.easy.instantiation.core.model.vilTypes.Map<eu.qualimaster.observables.IObservable, Double>> predictions, net.ssehub.easy.instantiation.core.model.vilTypes.Map<eu.qualimaster.observables.IObservable, Double> weighting, net.ssehub.easy.instantiation.core.model.vilTypes.Set<eu.qualimaster.observables.IObservable> costs) Implements a simple weighting of mass predictions.- Parameters:
predictions- the predictions given as name-observable-prediction mapping, may be null, entries may be nullweighting- the weighting of the observables, negative weights invert the value by subtracting from the respective maximumcosts- observables to be treated as costs (implicit negative weights, may be null for none)- Returns:
- the "best" solution in terms of the name, the maximum average weighted value if no
costs, the maximum weighted sum ifcosts
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