Package es.uam.eps.ir.relison.diffusion.metrics.features.global

Class FeatureGlobalEntropy<U extends java.io.Serializable,​I extends java.io.Serializable,​F>

java.lang.Object
es.uam.eps.ir.relison.diffusion.metrics.AbstractGlobalSimulationMetric<U,​I,​F>
es.uam.eps.ir.relison.diffusion.metrics.features.AbstractFeatureGlobalSimulationMetric<U,​I,​F>
es.uam.eps.ir.relison.diffusion.metrics.features.global.FeatureGlobalEntropy<U,​I,​F>
Type Parameters:
U - type of the users.
I - type of the information pieces.
F - type of the user / information pieces features.
All Implemented Interfaces:
GlobalSimulationMetric<U,​I,​F>, SimulationMetric<U,​I,​F>
public class FeatureGlobalEntropy<U extends java.io.Serializable,​I extends java.io.Serializable,​F>
extends AbstractFeatureGlobalSimulationMetric<U,​I,​F>
Metric that computes the entropy over the number of times each feature has been received. If we use information pieces features (i.e. hashtags) the (user, feature) value counts the number of times that the user has received information pieces using that feature. In case we use user features, it is just how many times the user has received information from users with that feature.

  • Field Summary

    Fields 
    Modifier and Type Field Description
    private static java.lang.String ENTROPY
    Name fixed value
    private double sum
    The total number of features that have reached the different users.
    private boolean unique
    Indicates if a piece of information is considered once (or each time it appears if false).
    private java.util.Map<F,​java.lang.Double> values
    Times each parameter has been received.

    Fields inherited from class es.uam.eps.ir.relison.diffusion.metrics.AbstractGlobalSimulationMetric

    data, initialized

  • Constructor Summary

    Constructors 
    Constructor Description
    FeatureGlobalEntropy​(java.lang.String feature, boolean userFeat, boolean unique)
    Constructor.

  • Method Summary

    Modifier and Type Method Description
    double calculate()
    Calculates the metric for the current state of the simulation.
    void clear()
    Resets the metric.
    protected void initialize()
    Initializes all the variables needed for computing and updating the values of the metric.
    protected void updateInfoFeature​(Iteration<U,​I,​F> iteration)
    Updates the necessary variables to compute a metric, in case the feature values we are using belong to the information pieces received by the users in the network.
    protected void updateUserFeature​(Iteration<U,​I,​F> iteration)
    Updates the necessary variables to compute a metric, in case the feature values we are using belongs to the creators of the information pieces received by the users in the network.

    Methods inherited from class es.uam.eps.ir.relison.diffusion.metrics.features.AbstractFeatureGlobalSimulationMetric

    getFeature, update, usesUserFeatures

    Methods inherited from class es.uam.eps.ir.relison.diffusion.metrics.AbstractGlobalSimulationMetric

    getName, initialize, isInitialized

    Methods inherited from class java.lang.Object

    clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

    Methods inherited from interface es.uam.eps.ir.relison.diffusion.metrics.SimulationMetric

    calculate, initialize

  • Field Details

    • ENTROPY

      private static final java.lang.String ENTROPY
      Name fixed value
      See Also:
      Constant Field Values

    • values

      private final java.util.Map<F,​java.lang.Double> values
      Times each parameter has been received.

    • sum

      private double sum
      The total number of features that have reached the different users.

    • unique

      private final boolean unique
      Indicates if a piece of information is considered once (or each time it appears if false).

  • Constructor Details

    • FeatureGlobalEntropy

      public FeatureGlobalEntropy​(java.lang.String feature, boolean userFeat, boolean unique)
      Constructor.
      Parameters:
      userFeat - true if we are using a user feature, false if we are using an information piece feature.
      feature - the name of the feature.
      unique - true if a piece of information is considered once, false if it is considered each time it appears.

  • Method Details