-
Notifications
You must be signed in to change notification settings - Fork 1
Home
Don Sheehy edited this page Dec 3, 2020
·
2 revisions
There are many cases where one would like to compute with metric spaces. This library is designed to be lightweight and versatile.
The primary design goals are:
-
It should handle both Euclidean metrics (via numpy) and those defined by a provided distance function.
-
It should interface seamlessly with net-tree, cover tree, and greedy tree code among others.
-
It should have support for data collection like counting distances computed.
-
It should handle the caching of distances. See Caching
-
It should be able to use approximate distances.
-
It should support alternative distance comparison methods.
-
It should cache upper and lower bounds on distances in settings where distance comparison suffices.