An easy way to boost performance (optional)

[MaceKuailv]

This is an optional recommendation as part of the review for the joss paper openjournals/joss-reviews#7873
Feel free to close this if you don't want to implement this.

It seems like most of the function is based on numpy, except for the calculation of great_circle distance using geopy, which means you could compile most of your functions using numba decorator. Actually, it is not too hard to rewrite great_circle using just numpy.

[cassidymwagner]

Thank you for this suggestion! We are exploring a future shift of FluidSF from numpy to xarray/dask. We have seen some really nice performance boosts in the early stages of this process, not to mention the convenience of using xarray datasets. It looks like Numba can be easily used with xarray, so we will keep this in mind for the next version of FluidSF!

[MaceKuailv]

Wow, I didn't know about this development with dask and numba! Glad you are thinking about the next step already.

I will keep this issue open so that I can be notified by, but this won't hinder your publishing of the joss paper.