Conflicting sizes for region and dataset when trying to create mask

Hi! I’ve been trying to create a mask for a dataset:

basins = regionmask.defined_regions.natural_earth.ocean_basins_50
mask = basins.mask(cmip6_compiled['CMIP.MPI-M.MPI-ESM1-2-HR.historical.Omon.gn'], lon_name='longitude', lat_name='latitude')

but this error appears:

ValueError                                Traceback (most recent call last)
/tmp/ipykernel_1285/730184074.py in <module>
      1 basins = regionmask.defined_regions.natural_earth.ocean_basins_50
----> 2 mask = basins.mask(cmip6_compiled['CMIP.MPI-M.MPI-ESM1-2-HR.historical.Omon.gn'], lon_name='longitude', lat_name='latitude')

/srv/conda/envs/notebook/lib/python3.9/site-packages/regionmask/core/regions.py in mask(self, lon_or_obj, lat, lon_name, lat_name, method, wrap_lon)
    282     ):
    283 
--> 284         return _mask_2D(
    285             outlines=self.polygons,
    286             lon_bounds=self.bounds_global[::2],

/srv/conda/envs/notebook/lib/python3.9/site-packages/regionmask/core/mask.py in _mask_2D(outlines, lon_bounds, numbers, lon_or_obj, lat, lon_name, lat_name, method, wrap_lon)
    198 ):
    199 
--> 200     mask = _mask(
    201         outlines=outlines,
    202         lon_bounds=lon_bounds,

/srv/conda/envs/notebook/lib/python3.9/site-packages/regionmask/core/mask.py in _mask(outlines, lon_bounds, numbers, lon_or_obj, lat, lon_name, lat_name, method, wrap_lon)
    183         )
    184 
--> 185     return mask_to_dataarray(mask, lon_or_obj, lat_orig, lon_name, lat_name)
    186 
    187 

/srv/conda/envs/notebook/lib/python3.9/site-packages/regionmask/core/mask.py in mask_to_dataarray(mask, lon_or_obj, lat, lon_name, lat_name)
    323         dims = ds.dims.keys()
    324 
--> 325     return ds.assign(region=(dims, mask)).region
    326 
    327 

/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/core/dataset.py in assign(self, variables, **variables_kwargs)
   5226         results = data._calc_assign_results(variables)
   5227         # ... and then assign
-> 5228         data.update(results)
   5229         return data
   5230 

/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/core/dataset.py in update(self, other)
   4206         Dataset.merge
   4207         """
-> 4208         merge_result = dataset_update_method(self, other)
   4209         return self._replace(inplace=True, **merge_result._asdict())
   4210 

/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/core/merge.py in dataset_update_method(dataset, other)
    982     # TODO: benbovy - flexible indexes: fix this (it only works with pandas indexes)
    983     indexes = {key: PandasIndex(dataset.coords[key]) for key in dataset.xindexes.keys()}
--> 984     return merge_core(
    985         [dataset, other],
    986         priority_arg=1,

/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/core/merge.py in merge_core(objects, compat, join, combine_attrs, priority_arg, explicit_coords, indexes, fill_value)
    638     assert_unique_multiindex_level_names(variables)
    639 
--> 640     dims = calculate_dimensions(variables)
    641 
    642     coord_names, noncoord_names = determine_coords(coerced)

/srv/conda/envs/notebook/lib/python3.9/site-packages/xarray/core/dataset.py in calculate_dimensions(variables)
    206                 last_used[dim] = k
    207             elif dims[dim] != size:
--> 208                 raise ValueError(
    209                     f"conflicting sizes for dimension {dim!r}: "
    210                     f"length {size} on {k!r} and length {dims[dim]} on {last_used!r}"

ValueError: conflicting sizes for dimension 'i': length 404 on 'region' and length 802 on {'i': 'i', 'j': 'j'}

I’m not sure, but maybe the i and j variables are getting switched? Here are the dimensions for the dataset:

xarray.Dataset
Dimensions: i: 802 j: 404 lev: 40 bnds: 2 member_id: 1 time: 1980 vertices: 4

And these are the package versions that I used:

regionmask='0.8.1.dev11+g3fab767'
xarray='0.19.0'

[mathause]

Thanks again for the error report - I am very happy I could fix this before releasing!

[mathause]

Let’s keep this open until I can fix it.