Project 1 : Phase 1

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Project 1 Phase 1

• 22C021 CS II
• Data Structures

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Project 1 Plan

• Part I (for week 1)
• Turn the myListGraph class into a generic class.
• Implement clusteringCoefficient(v) and
  clusteringCoefficient( ).
• Add an additional data member to the myListGraph
  class called locations to keep track of an
  array of points.
• Add the constructor myListGraph(n, d, p) to
  myListGraph.

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Project 1 Plan

• Part II (for week 2)
• Implement the methods in the myListGraph class to
  compute average path length.
• Part II (for week 3)
• Run experiments, gather data, make plots, and
  write report.

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Making myListGraph Generic

• The Link class needs to be made generic to store
  values of type supplied by the user of class
• The LinkList class needs to be made generic to
  pass down values of correct type to Link
• The myListGraph class needs to be made generic to
  pass down values of correct type to LinkList.

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Making myListGraph Generic

• Correct way of instantiating arrays of Generic
  types
• theItems (AnyType) new Object newCapacity

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Code to Test Generic myListGraph

• Will soon be available on class webpage

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Clustering Coefficient Algorithm

• For a vertex V with n neighbors, there exist
• Q (n choose 2) n.(n 1) / 2 total
  pairs
• Find total number of pairs of neighbors that
  actually have connections, call this P
• Compute the clustering cofficient Cv for V as
• Cv P / Q
• The algorithm to find such pairs of connected
  nodes is similar to listTriangles from Assignment
  2

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Why do we need locations

• We need to know the locations of points within
  our square to find distances between them.
• This variable will store the location of ith
  vertex at index i in locations array.
• Computing distances between points
• Distance Sqrt ((x2 - x1)2 (y2 - y1)2)
• Review project 1 problem to see why distances
  between points is important

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Using Probability factor

• While generating a graph, probably factor p
  determines if we connect to another of our
  neighbors or to a non-neighbor
• To use this factor, generate a floating random
  number and compare it with p
• If the generated number is less than p, connect
  to a non-neighbor
• Otherwise, connect to your neighbor