This evening Michael looked at an apple I was eating and said something that sounded awfully like, “What’s that?” Chao-Jen and I both looked at him and then each other, both surprised. I looked back at Michael, pointed at the apple, and said, “Apple.” Almost immediately, he responded, “Apple.”

He said it a few more times, clearly referring to the apple, although it did become “bapple” a couple times.

Amazing.

He has said other words (including “owl” when looking at one of his sippy cups), but this seemed much more interactive.

I have done additional work on the Delaunay triangulation that I mentioned in the previous post. The code is less messy, has tests, and is now packaged.

My code needs to compute the convex hull in order to start the Delaunay triangulation. Since that is sort of interesting in itself (and may be needed on its own in the future), I pulled out the convex hull generation into its own class. The computation proceeds using Graham scan. Here’s an example (created with ‘conhull -s 50 -n 20′):

You can see that’s correct, but visually, it’s not too interesting. For fun, I added the ability to generate nested convex hulls. The next image was created with ‘conhull -s 50 -n 500 –num-hulls all –no-plot-points’:

With more points (‘conhull -s 50 -n 1000 –num-hulls all –no-plot-points’):

The package is here.

I spent a little time implementing Delaunay triangulation for learning. I am going to do a little more work on it, but here’s an example of its output.

The code is still a mess, and will be updated, but you can find it here. You need Python with matplotlib to run the code.