I think that this touches on another problem as well - which assumptions can those writing interpolators make about the fieldsets that they're working work? This mentions the dimensionality, but there's other things (riffing off the top of my head):
- Dimensionality in the case of 2D etc fields
- Types of the underlying arrays (dask, numpy, cupy etc)
- Units
Since you've written a bunch of interpolators already, what do you think about this @erikvansebille ? I don't think we have to have all the answers now, but if we don't - perhaps its worth setting up a tracking issue so that we can work towards this
Originally posted by @VeckoTheGecko in #2590
alongside response from @erikvansebille
Yes, all of these are good points. And a fourth one is land-value (see also #2451).
As for Dimensionality, I thought that we always assumed fields to be 4D (time, depth, lat, lon) in Parcels? So writers of interpolators can be confident that the order is that way?
As for the array-type; perhaps we can declare a generalised array operation, that then links to the same array package that the rest of Parcels?
As for units, that is up to the user - until we have something like support for pint; but that is for a later version...)
Originally posted by @VeckoTheGecko in #2590
alongside response from @erikvansebille