[Insight-developers] multi-label point sets

[M Stauffer -V-]

Hi Nick,

Brian and I have been discussing the new point set metrics and how to
use them with labels. We're thinking we'll want to have single point
sets containing multiple labels, and the metrics will evaluate using the
labels. Presumably we'll store the label information in the point set
data.

One need is to be able to perform neighbor searches constrained by
label, and probabilistic searches e.g. for the expectation-based and
jensen point set metrics. Currently the PointsLocator is used within the
point set metric to find N nearest neighbors, which creates a k-d tree
representation of the point set during pre-processing. 

Do we add per-label search directly to the point sets, presumably by
adding a new k-d tree type? Perhaps creating one that does probabilistic
neighbor searching as well? Or do we pre-process the user-supplied point
sets into individual point sets for each label, and then just use the
exciting point locator methods on those?

Do we create a separate LabeledPointSet class that knows how to do these
things, and require that the point set metrics take this type?

What do you think?

-M