1.0 road map

[KristofferC]

This was my very first package and looking at this with a set of more experienced eyes there are quite a few changes I want to make to APIs etc. Some of those will be somewhat breaking but I think it is worth it.

• use ArrayOfArrays for return value to reduce the number of allocated arrays #167
• Rethink the skip function. Right now it only takes a single index but it isn't really documented and it is unclear if this is the best API.
• Remove DataFreeTree: I don't see any use of this in JuliaHub and I am not really satisfied with its implementation.
• Ensure all public API is documented, nn lacking docstring #147
• Test benchmarks and have them run on CI
• Some public API for investigating the tree like bounding_box, isleaf etc?
• Consider multithreading
• Go through and triage open issues and PRs
• Remove the sorting kwargs, users can just sort themselves.
• Add knn! to be able to pass in a vector to be updated.
• Consider if "vectorized" functions of knn and inrange are needed or if user can just write the loop themselves if they want. Would remove the need for use ArrayOfArrays for return value to reduce the number of allocated arrays #167.
• Periodic versions of the trees?
• Better docs?

More to come

[KristofferC]

CC some people that I know use this package: @juliohm, @fredrikekre

[aplavin]

Wonder if there are any plans for adding multidimensional inrange search?
Implementation is very short:
https://github.com/JuliaAPlavin/FlexiJoins.jl/blob/00000000ca2fe5eace0b881caa8d2258ca6154ee/src/nearestneighbors.jl#L32-L52
#150

[aplavin]

Also, what about supporting arbitrary types, at least for BallTree? Stuff like strings or even custom objects can be useful with distance searches.
JuliaAPlavin/FlexiJoins.jl#8

[KristofferC]

Wonder if there are any plans for adding multidimensional inrange search?

Sounds like a good idea!

[KristofferC]

Also, what about supporting arbitrary types, at least for BallTree?

I don't think that should be too hard, we would "just" have to relax some assumptions of what types are used for the data etc.