ATL06 example in readme results in ValueError

[scottyhq]

Executing the code cells in the repository README results in a ValueError.

(earthaccess v0.5.2 running in AWS us-west-2 https://opensciencelab.asf.alaska.edu with netrc auth)

---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[4], line 3
      1 import xarray as xr
----> 3 ds = xr.open_mfdataset(earthaccess.open(results))

File ~/.local/envs/odc/lib/python3.10/site-packages/xarray/backends/api.py:1011, in open_mfdataset(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs)
    998     combined = _nested_combine(
    999         datasets,
   1000         concat_dims=concat_dim,
   (...)
   1006         combine_attrs=combine_attrs,
   1007     )
   1008 elif combine == "by_coords":
   1009     # Redo ordering from coordinates, ignoring how they were ordered
   1010     # previously
-> 1011     combined = combine_by_coords(
   1012         datasets,
   1013         compat=compat,
   1014         data_vars=data_vars,
   1015         coords=coords,
   1016         join=join,
   1017         combine_attrs=combine_attrs,
   1018     )
   1019 else:
   1020     raise ValueError(
   1021         "{} is an invalid option for the keyword argument"
   1022         " ``combine``".format(combine)
   1023     )

File ~/.local/envs/odc/lib/python3.10/site-packages/xarray/core/combine.py:976, in combine_by_coords(data_objects, compat, data_vars, coords, fill_value, join, combine_attrs, datasets)
    974     concatenated_grouped_by_data_vars = []
    975     for vars, datasets_with_same_vars in grouped_by_vars:
--> 976         concatenated = _combine_single_variable_hypercube(
    977             list(datasets_with_same_vars),
    978             fill_value=fill_value,
    979             data_vars=data_vars,
    980             coords=coords,
    981             compat=compat,
    982             join=join,
    983             combine_attrs=combine_attrs,
    984         )
    985         concatenated_grouped_by_data_vars.append(concatenated)
    987 return merge(
    988     concatenated_grouped_by_data_vars,
    989     compat=compat,
   (...)
    992     combine_attrs=combine_attrs,
    993 )

File ~/.local/envs/odc/lib/python3.10/site-packages/xarray/core/combine.py:623, in _combine_single_variable_hypercube(datasets, fill_value, data_vars, coords, compat, join, combine_attrs)
    617 if len(datasets) == 0:
    618     raise ValueError(
    619         "At least one Dataset is required to resolve variable names "
    620         "for combined hypercube."
    621     )
--> 623 combined_ids, concat_dims = _infer_concat_order_from_coords(list(datasets))
    625 if fill_value is None:
    626     # check that datasets form complete hypercube
    627     _check_shape_tile_ids(combined_ids)

File ~/.local/envs/odc/lib/python3.10/site-packages/xarray/core/combine.py:145, in _infer_concat_order_from_coords(datasets)
    140             tile_ids = [
    141                 tile_id + (position,) for tile_id, position in zip(tile_ids, order)
    142             ]
    144 if len(datasets) > 1 and not concat_dims:
--> 145     raise ValueError(
    146         "Could not find any dimension coordinates to use to "
    147         "order the datasets for concatenation"
    148     )
    150 combined_ids = dict(zip(tile_ids, datasets))
    152 return combined_ids, concat_dims

ValueError: Could not find any dimension coordinates to use to order the datasets for concatenation

[asteiker]

@scottyhq Thanks for submitting this Issue- great catch. This is due to us not specifying a group when attempting to open the granules (so that line is more generic for files that do not have a group structure, yet we've included ATL06 as the example). We can update with a group specified like in our latest ICESat-2 cloud tutorial (https://github.com/nsidc/NSIDC-Data-Tutorials/blob/main/notebooks/ICESat-2_Cloud_Access/nsidc_daac_uwg_cloud_access_tutorial.ipynb) and/or or update to a different dataset example without groups. What do you think would be most helpful @scottyhq ? I did just test an example group and this should fix the error:

ds = xr.open_mfdataset(earthaccess.open(results), group='/gt1l/land_ice_segments')

[scottyhq]

What do you think would be most helpful @scottyhq ?

Sorry for the delayed response @asteiker , the fix makes sense! I'd advocate for starting with a much simpler ds = xr.open_dataset(earthaccess.open(results[0]), group='/gt1l/land_ice_segments') single file example. Often the readme is a gateway for new users who want to quickly kick the tires. xr.open_mfdataset() is pretty advanced and slow if not opening local or cloud-optimized data.