Closed aladinor closed 2 months ago
Hi @aladinor - have you checked that this behaviour is actually different from what xr.open_dataset
will do for one dataset? Because the aim here should be compliance with that behaviour, and clarity as to what options should be passed if you want different behaviour (e.g. passing chunks={}
).
Hi @TomNicholas. This is a really good question. So the main thing that I found out is that xarray.open_dataset
has its default parameters. Thus, when passing the **kwargs
dictionary from datatree.open_datatree
to xarray.open_dataset
, it will overwrite all the default parameters and set them None
. At least in the test I performed, if none of those default arguments were passed, xr.open_dataset
would behave as I mentioned in #328. I think that If we want to keep xr.open_dataset
, all the parameters should be passed within the **kwargs
dictionary or try to find a way to not overwrite the default args in xr.open_dataset
. I could not find a way to do that without retyping/passing all of them from datatree.open_datatree
to xr.open_dataset
. That's why I felt using xr.open_zarr
was more convenient. However, I will recheck it using one dataset
Hi @TomNicholas. This could be a reproducible example for you to check.
import xarray as xr
import datatree
import numpy as np
import pandas as pd
def main():
data = 283 + 5 * np.random.randn(5, 3, 4)
times = pd.date_range("2018-01-01", periods=5)
lons = np.linspace(-120, -90, 4)
lats = np.linspace(25, 55, 3)
temp = xr.DataArray(data, coords=[times, lats, lons], dims=["time", "lat", "lon"]).chunk({'time': 1,
'lat': -1,
'lon': -1})
ds = xr.Dataset(data_vars={'Temp': temp})
ds2 = xr.Dataset(data_vars={'Temp_C': temp - 273.15}).chunk({'time': 1, 'lat': 1, 'lon': 1})
dtree = datatree.DataTree(data=ds)
datatree.DataTree(ds2, parent=dtree, name='set2')
print(dtree.Temp.chunksizes)
print(dtree.set2.Temp_C.chunksizes)
path_zarr = "test.zarr"
dtree.to_zarr(path_zarr)
dtree_back = datatree.open_datatree(path_zarr, engine='zarr')
print(dtree_back.Temp.chunksizes)
print(dtree_back.set2.Temp_C.chunksizes)
...
if __name__ == "__main__":
main()
And the output
Frozen({'time': (1, 1, 1, 1, 1), 'lat': (3,), 'lon': (4,)})
Frozen({'time': (1, 1, 1, 1, 1), 'lat': (1, 1, 1), 'lon': (1, 1, 1, 1)})
Frozen({})
Frozen({})
The expected output without passing any parameters to open_datatree
should be to keep the same chunk sizes. However, it didn't.
Let me know your thoughts.
Hi @TomNicholas. I looked again at xr.open_dataset
documentation and I found this
In order to reproduce the default behavior of xr.open_zarr(...) use xr.open_dataset(..., engine='zarr', chunks={}). chunks='auto' will use dask auto chunking taking into account the engine preferred chunks. See dask chunking for more details.
I think based on I will close this issue and the PR. Thanks for your time!
Description
HI everyone,
I have been working on creating a datatree with multiple datasets containing weather radar data, as shown here. The ultimate purpose is to store data in Analysis-Ready Cloud-Optimized format (Zarr).
When reading data back using the
datatree.open_datatree
method, it loads the data as it was stored, but the issue is that allXarray.DataArrays
within the tree are rechunked into one singlechunk
along all dimensions.Then, the tree output looks like,![WhatsApp Image 2024-04-03 at 12 09 05 PM](https://github.com/xarray-contrib/datatree/assets/18624932/42cf9893-8458-4f33-bb7d-92cb35f5c922)
Digging around this issue, I found out that the
xarray.open_dataset
default variables, such aschunks
anddecode_cf
, are set toNone
. Therefore, when passing an emptykwargs
dictionary, all variables will be set to None.https://github.com/xarray-contrib/datatree/blob/0afaa6cc1d6800987d8b9c37a604dc0a8c68aeaa/datatree/io.py#L88
Possible Solution
I think this can be resolved by using
xarray.open_zarr
instead of usingxarray.open_dataset
method in #L88Please let me know your thoughts.