No research this morning. Had flu-like symptoms from midnight to 2:00 or so and slept in. Considering how bad I felt last night, I’m pleasantly surprised to feel good enough to get into work at 9:00.

I did take the Superpedestrian wheel out (yes, as I was getting sick) for my 18 mile hilly loop. It took around an hour and performed really well. It just flattens hills, while behaving like a normal bike at all other times.

Google Says Its Job Is to Promote Climate Change Conspiracy Theories

9:00 – 4:00 BRC

• My fix from yesterday doesn’t work on Aaron’s machine. Verified that it works on any of my cmd-line interfaces. Weird.
• Testing to see if my Excel has been fixed. Nope.
• More work on getting Python imports to behave. All written up here.
• Got the data sheets working with the plots: 

  plt.imshow(df, extent=[3, points/3, 0.9, 0.1], aspect='auto', cmap=plt.cm.get_cmap("hot"))
  plt.colorbar()

   This took a while to figure out. The X, Y arrays are used to create the mesh. The df.as_matrix() contains the Z values. Just make sure that row size and column size match!

  fig = plt.figure()
  ax = Axes3D(fig)
  X = co.get_min_cluster_array()
  Y = co.get_eps_array()
  X, Y = np.meshgrid(X, Y)
  Z = df.as_matrix()
  ax.plot_surface(X, Y, Z, cmap=plt.cm.get_cmap("hot"))
  plt.show()

• Next is to save the best cluster run with its EPS and cluster size
• Wound up just using the number of clusters for now. That seems to be a better fitness test. Also, I discovered that all Dataframes are references, so it’s important to make a deep copy if you’re trying to keep the best one around! Here are the best results so far: