The following classes can be run without parameters to generate a sample data set and 
run the reference Dirichlet Process Clustering implementation over them:

DisplayDirichlet - generates 1000 samples from three, symmetric distributions. This is the same 
    data set that is used by the following clustering programs. It displays the points on a screen
    and superimposes the model parameters that were used to generate the points. You can edit the
    generateSamples() method to change the sample points used by these programs.
  * DisplayNDirichlet - clusters the above sample points using the NormalModelDistribution
  * DisplaySNDirichlet - clusters the above sample points using the SampledNormalDistribution
  * DisplayASNDirichlet - clusters the above sample points using the AsymmetricSampledNormalDistribution
  * Display2dASNDirichlet - clusters a set of asymmetric sample points (generated by DisplayDirichlet's
    generate2dSamples() method) using the AsymmetricSampledNormalDistribution.
  * NOTE: each of these programs displays the sample points and then superimposes all of the clusters
    from each iteration. The last iteration's clusters are in bold red and the previous several are 
    colored (orange, yellow, green, blue, magenta) in order after which all earlier clusters are in
    light grey. This helps to visualize how the clusters converge upon a solution over multiple
    iterations.
  * NOTE: by changing the UncommonDistributions.init(...) call in DisplayDirichlet, you can get
    different behaviors. Removing the initialization altogether will use a random seed for each run.
    
DisplayOutputState - this program can be run after any of the SampledNormalDistribution M/R Dirichlet test 
  cases in TestMapReduce. It draws the points and the resulting clusters from the output directory in 
  a manner similar to the above. By changing the initialization seed in TestMapReduce you can get 
  different data points.
DisplayASNOutputState - similar to above but uses the AsymmetricSampledNormalDistribution.

  
    