Open giovp opened 1 year ago
I agree, we need to unify the types we use for elements, it's too heterogenous at the moment.
Wow maybe we have the perfect solution! And this applies also for polygons! https://github.com/geopandas/dask-geopandas
I think GeoDataFrame
(with dask) would be the best solution because we consider also Squares
as Shapes
.
I like the idea a lot but maybe it's also overkill for the moment? the shapes and polygons are in the order of 10-100_000 for the current datasets so plain geopandas might be enough?
I agree, from the performance point of view it may be overkill, but there is another implication of backing vs non-backing that we may be interested. If backing implies that when we modify something in-memory this is also modified in the disk (like it happens with h5py
), then it would be desirable that all the elements are backed. Otherwise for certain elements (currently the table behaves like this), we need to rewrite the whole table so that the changes are reflected to the disk storage.
We have to test how the objects behave. Keeping track of that in this other issue: https://github.com/scverse/spatialdata/issues/126.
Not sure why I closed this 👀 It's still open, and duplicate of this (I remembered this discussion but couldn't find this issue anymore). https://github.com/scverse/spatialdata/issues/359
right now the Shapes model is an anndata. We are just saving the coordinates in
adata.obsm["spatial"]
and the metadata inuns
. I feel this is overkill and we don't really have plans to extend this spec further (but we did discuss to potentially move it to geodataframe or as points -> dask dataframes). I'd suggest by release to convert Shapes toGeoDataFarme
orDaskDataFrame
@scverse/spatialdata