Class EditionDistance

    • Method Detail

      • distance

        public double distance​(Comparison inProgress,
                               EObject a,
                               EObject b)
        Return the distance between two EObjects. When the two objects should considered as completely different the implementation is expected to return Double.MAX_VALUE.
        Specified by:
        distance in interface ProximityEObjectMatcher.DistanceFunction
        Parameters:
        inProgress - the comparison being processed right now. This might be used for the distance to retrieve other matches for instance.
        a - first object.
        b - second object.
        Returns:
        the distance between the two EObjects or Double.MAX_VALUE when the objects are considered too different to be the same.
      • areIdentic

        public boolean areIdentic​(Comparison inProgress,
                                  EObject a,
                                  EObject b)
        Check that two objects are equals from the distance function point of view (distance should be 0) You should prefer this method when you just want to check objects are not equals enabling the distance to stop sooner.
        Specified by:
        areIdentic in interface ProximityEObjectMatcher.DistanceFunction
        Parameters:
        inProgress - the comparison being processed right now. This might be used for the distance to retrieve other matches for instance.
        a - first object.
        b - second object.
        Returns:
        true of the two objects are equals, false otherwise.
      • builder

        public static EditionDistance.Builder builder()
        Create a new builder to instantiate and configure an EditionDistance.
        Returns:
        a configuration builder.
      • getThresholdAmount

        public double getThresholdAmount​(EObject eObj)
      • getThresholdRatio

        protected double getThresholdRatio​(int nbFeatures)
        return a ratio to apply on the amount of maximum un-similarity amount depending on the number of features which are considered.
        Parameters:
        nbFeatures - the nb of features which should be considerd to compute the amount.
        Returns:
        a ratio to appli on the amount of maximum un-similarity amount depending on the number of features which are considered.