The sequel to clusterview. Built around the point and cluster structure of the kmeans project, aims to improve upon the design and structural weakness of clusterview and add many interesting interactive ways to explore kmeans.
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1008 B

TODO:

  • Port over and improve clusterview and it's opengl stuff. It should use k-means point and cluster, as well as the math library from kmeans (add a test to dist). Additionally, the point and cluster of the clusterview should inherit from k-means point and cluster so that it can use the algorithm correctly. All other aspects of point and cluster in the clusterview program can be kept.
  • Extract and improve the overall structure of clusterview so that globals are not used unless absolutely necessary.
  • Turn kmeans into a python package and import it here.
  • Remove old clusterview buttons, keep the status window side and saving feature. Add new buttons for weighted and unweighted clustering.
  • Add a property to the point called weight, which is set when you click edit point. It will give a popup that allows you to specify a point weight.
  • Use kmeans to do the stuff.
  • Weighted cluster mean is rendered as a hollow circle and unweighted k-means mean is a x.