Package edu.uci.ics.jung.algorithms.scoring

Class AbstractIterativeScorer<V,​E,​T>

  • All Implemented Interfaces:
    VertexScorer<V,​T>, IterativeContext
    Direct Known Subclasses:
    AbstractIterativeScorerWithPriors, VoltageScorer
    public abstract class AbstractIterativeScorer<V,​E,​T>
extends java.lang.Object
implements IterativeContext, VertexScorer<V,​T>
    An abstract class for algorithms that assign scores to vertices based on iterative methods. Generally, any (concrete) subclass will function by creating an instance, and then either calling evaluate (if the user wants to iterate until the algorithms is 'done') or repeatedly call step (if the user wants to observe the values at each step).

    • Field Summary

      Fields 
      Modifier and Type Field Description
      private boolean accept_disconnected_graph
      A flag representing whether this instance tolerates disconnected graphs.
      private java.util.Map<V,​T> current_values
      The map in which the current values are stored.
      protected com.google.common.base.Function<VEPair<V,​E>,​? extends java.lang.Number> edge_weights
      The edge weights used by this algorithm.
      protected Hypergraph<V,​E> graph
      The graph on which the calculations are to be made.
      protected boolean hyperedges_are_self_loops  
      protected double max_delta
      The largest change seen so far among all vertex scores.
      protected int max_iterations
      Maximum number of iterations to use before terminating.
      private java.util.Map<V,​T> output
      The map in which the output values are stored.
      protected boolean output_reversed
      Indicates whether the output and current values are in a 'swapped' state.
      protected double tolerance
      Minimum change from one step to the next; if all changes are ≤ tolerance, no further updates will occur.
      protected int total_iterations
      The total number of iterations used so far.

    • Method Summary

      All Methods Instance Methods Abstract Methods Concrete Methods 
      Modifier and Type Method Description
      void acceptDisconnectedGraph​(boolean accept)
      Specifies whether this instance should accept vertices with no outgoing edges.
      protected void afterStep()  
      protected void collectDisappearingPotential​(V v)
      Collects the 'potential' from v (its current value) if it has no outgoing edges; this can then be redistributed among the other vertices as a means of normalization.
      boolean done()
      Returns true if the total number of iterations is greater than or equal to max_iterations or if the maximum value change observed is less than tolerance.
      void evaluate()
      Steps through this scoring algorithm until a termination condition is reached.
      protected int getAdjustedIncidentCount​(E e)
      Returns the effective number of vertices incident to this edge.
      protected T getCurrentValue​(V v)
      Gets the current value for this vertex
      protected java.lang.Number getEdgeWeight​(V v, E e)
      Gets the edge weight for e in the context of its (incident) vertex v.
      com.google.common.base.Function<VEPair<V,​E>,​? extends java.lang.Number> getEdgeWeights()
      Returns the Function that this instance uses to associate edge weights with each edge.
      int getIterations()
      Returns the number of iterations that this instance has used so far.
      int getMaxIterations()
      Returns the maximum number of iterations that this instance will use.
      protected T getOutputValue​(V v)
      Gets the output value for this vertex.
      double getTolerance()
      Gets the size of the largest change (difference between the current and previous values) for any vertex that can be tolerated.
      T getVertexScore​(V v)  
      protected void initialize()
      Initializes the internal state for this instance.
      boolean isDisconnectedGraphOK()
      Returns true if this instance accepts vertices with no outgoing edges, and false otherwise.
      protected void setCurrentValue​(V v, T value)
      Sets the current value for this vertex.
      void setEdgeWeights​(com.google.common.base.Function<? super E,​? extends java.lang.Number> edge_weights)
      Sets the Function that this instance uses to associate edge weights with each edge
      void setHyperedgesAreSelfLoops​(boolean arg)
      Specifies whether hyperedges are to be treated as self-loops.
      void setMaxIterations​(int max_iterations)
      Sets the maximum number of times that evaluate will call step.
      protected void setOutputValue​(V v, T value)
      Sets the output value for this vertex.
      void setTolerance​(double tolerance)
      Sets the size of the largest change (difference between the current and previous values) for any vertex that can be tolerated.
      void step()
      Performs one step of this algorithm; updates the state (value) for each vertex.
      protected void swapOutputForCurrent()  
      protected abstract double update​(V v)
      Updates the value for v.
      protected void updateMaxDelta​(V v, double diff)  

      • Methods inherited from class java.lang.Object

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

    • Field Detail

      • max_iterations

        protected int max_iterations
        Maximum number of iterations to use before terminating. Defaults to 100.

      • tolerance

        protected double tolerance
        Minimum change from one step to the next; if all changes are ≤ tolerance, no further updates will occur. Defaults to 0.001.

      • graph

        protected Hypergraph<V,​E> graph
        The graph on which the calculations are to be made.

      • total_iterations

        protected int total_iterations
        The total number of iterations used so far.

      • edge_weights

        protected com.google.common.base.Function<VEPair<V,​E>,​? extends java.lang.Number> edge_weights
        The edge weights used by this algorithm.

      • output_reversed

        protected boolean output_reversed
        Indicates whether the output and current values are in a 'swapped' state. Intended for internal use only.

      • output

        private java.util.Map<V,​T> output
        The map in which the output values are stored.

      • current_values

        private java.util.Map<V,​T> current_values
        The map in which the current values are stored.

      • accept_disconnected_graph

        private boolean accept_disconnected_graph
        A flag representing whether this instance tolerates disconnected graphs. Instances that do not accept disconnected graphs may have unexpected behavior on disconnected graphs; they are not guaranteed to do an explicit check. Defaults to true.

      • hyperedges_are_self_loops

        protected boolean hyperedges_are_self_loops

      • max_delta

        protected double max_delta
        The largest change seen so far among all vertex scores.

    • Constructor Detail

      • AbstractIterativeScorer

        public AbstractIterativeScorer​(Hypergraph<V,​E> g,
                               com.google.common.base.Function<? super E,​? extends java.lang.Number> edge_weights)
        Creates an instance for the specified graph and edge weights.
        Parameters:
        g - the graph for which the instance is to be created
        edge_weights - the edge weights for this instance

      • AbstractIterativeScorer

        public AbstractIterativeScorer​(Hypergraph<V,​E> g)
        Creates an instance for the specified graph g. NOTE: This constructor does not set the internal edge_weights variable. If this variable is used by the subclass which invoked this constructor, it must be initialized by that subclass.
        Parameters:
        g - the graph for which the instance is to be created

    • Method Detail

      • setOutputValue

        protected void setOutputValue​(V v,
                              T value)
        Sets the output value for this vertex.
        Parameters:
        v - the vertex whose output value is to be set
        value - the value to set

      • getOutputValue

        protected T getOutputValue​(V v)
        Gets the output value for this vertex.
        Parameters:
        v - the vertex whose output value is to be retrieved
        Returns:
        the output value for this vertex

      • getCurrentValue

        protected T getCurrentValue​(V v)
        Gets the current value for this vertex
        Parameters:
        v - the vertex whose current value is to be retrieved
        Returns:
        the current value for this vertex

      • setCurrentValue

        protected void setCurrentValue​(V v,
                               T value)
        Sets the current value for this vertex.
        Parameters:
        v - the vertex whose current value is to be set
        value - the current value to set

      • initialize

        protected void initialize()
        Initializes the internal state for this instance.

      • evaluate

        public void evaluate()
        Steps through this scoring algorithm until a termination condition is reached.

      • done

        public boolean done()
        Returns true if the total number of iterations is greater than or equal to max_iterations or if the maximum value change observed is less than tolerance.
        Specified by:
        done in interface IterativeContext
        Returns:
        true if this iterative process is finished, and false otherwise.

      • step

        public void step()
        Performs one step of this algorithm; updates the state (value) for each vertex.
        Specified by:
        step in interface IterativeContext

      • swapOutputForCurrent

        protected void swapOutputForCurrent()

      • update

        protected abstract double update​(V v)
        Updates the value for v.
        Parameters:
        v - the vertex whose value is to be updated
        Returns:
        the updated value

      • updateMaxDelta

        protected void updateMaxDelta​(V v,
                              double diff)

      • afterStep

        protected void afterStep()

      • getVertexScore

        public T getVertexScore​(V v)
        Specified by:
        getVertexScore in interface VertexScorer<V,​E>
        Parameters:
        v - the vertex whose score is requested
        Returns:
        the algorithm's score for this vertex

      • getMaxIterations

        public int getMaxIterations()
        Returns the maximum number of iterations that this instance will use.
        Returns:
        the maximum number of iterations that evaluate will use prior to terminating

      • getIterations

        public int getIterations()
        Returns the number of iterations that this instance has used so far.
        Returns:
        the number of iterations that this instance has used so far

      • setMaxIterations

        public void setMaxIterations​(int max_iterations)
        Sets the maximum number of times that evaluate will call step.
        Parameters:
        max_iterations - the maximum

      • getTolerance

        public double getTolerance()
        Gets the size of the largest change (difference between the current and previous values) for any vertex that can be tolerated. Once all changes are less than this value, evaluate will terminate.
        Returns:
        the size of the largest change that evaluate() will permit

      • setTolerance

        public void setTolerance​(double tolerance)
        Sets the size of the largest change (difference between the current and previous values) for any vertex that can be tolerated.
        Parameters:
        tolerance - the size of the largest change that evaluate() will permit

      • getEdgeWeights

        public com.google.common.base.Function<VEPair<V,​E>,​? extends java.lang.Number> getEdgeWeights()
        Returns the Function that this instance uses to associate edge weights with each edge.
        Returns:
        the Function that associates an edge weight with each edge

      • setEdgeWeights

        public void setEdgeWeights​(com.google.common.base.Function<? super E,​? extends java.lang.Number> edge_weights)
        Sets the Function that this instance uses to associate edge weights with each edge
        Parameters:
        edge_weights - the Function to use to associate an edge weight with each edge
        See Also:
        UniformDegreeWeight

      • getEdgeWeight

        protected java.lang.Number getEdgeWeight​(V v,
                                         E e)
        Gets the edge weight for e in the context of its (incident) vertex v.
        Parameters:
        v - the vertex incident to e as a context in which the edge weight is to be calculated
        e - the edge whose weight is to be returned
        Returns:
        the edge weight for e in the context of its (incident) vertex v

      • collectDisappearingPotential

        protected void collectDisappearingPotential​(V v)
        Collects the 'potential' from v (its current value) if it has no outgoing edges; this can then be redistributed among the other vertices as a means of normalization.
        Parameters:
        v - the vertex whose potential is being collected

      • acceptDisconnectedGraph

        public void acceptDisconnectedGraph​(boolean accept)
        Specifies whether this instance should accept vertices with no outgoing edges.
        Parameters:
        accept - true if this instance should accept vertices with no outgoing edges, false otherwise

      • isDisconnectedGraphOK

        public boolean isDisconnectedGraphOK()
        Returns true if this instance accepts vertices with no outgoing edges, and false otherwise.
        Returns:
        true if this instance accepts vertices with no outgoing edges, otherwise false

      • setHyperedgesAreSelfLoops

        public void setHyperedgesAreSelfLoops​(boolean arg)
        Specifies whether hyperedges are to be treated as self-loops. If they are, then potential will flow along a hyperedge a vertex to itself, just as it does to all other vertices incident to that hyperedge.
        Parameters:
        arg - if true, hyperedges are treated as self-loops

      • getAdjustedIncidentCount

        protected int getAdjustedIncidentCount​(E e)
        Returns the effective number of vertices incident to this edge. If the graph is a binary relation or if hyperedges are treated as self-loops, the value returned is graph.getIncidentCount(e); otherwise it is graph.getIncidentCount(e) - 1.
        Parameters:
        e - the edge whose incident edge count is requested
        Returns:
        the edge count, adjusted based on how hyperedges are treated