Jeremy R. Manning

We could use an index array that says which electrodes/locations came from which locations.

If you know the observed locations and the model locations, can't you determine the nearest neighbor locations? You'll need to store the threshold somewhere in the model object as well.

How about we store the original locations + data in the brain object, along with enough info to do the nearest neighbor calculations on the fly. For example, if we...

let's punt the precise implementation of this for now; we have a hacked version in place that: - plots observed (or rounded to observed) locations in black - plots reconstructed...

we'll need to explore this...it really depends on how the reconstructions look. we should probably at least try radii of 10 and 20.

The main components that take a lot of time in SuperEEG are: 1) reading stuff into memory from disk (i.e. disk I/O) 2) multiplying big matrices together TensorFlow could mainly...

Let's get the basic algorithm implemented nicely, and then we can see what it would take to port the relevant pieces to tensorflow...

Need tests for location objects...

Also need to update other object types to use Locations objects

That a great idea! I like it.