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coords = _load_netcdf_1d_coords(riods.tags())
_parse_driver_tags(riods=riods, attrs=attrs, coords=coords)
for coord in coords:
if f"NETCDF_DIM_{coord}" in attrs:
coord_name = coord
attrs.pop(f"NETCDF_DIM_{coord}")
break
else:
coord_name = "band"
coords[coord_name] = np.asarray(riods.indexes)
# Get geospatial coordinates
transform = _rio_transform(riods)
if parse_coordinates and transform.is_rectilinear:
# 1d coordinates
coords.update(affine_to_coords(riods.transform, riods.width, riods.height))
elif parse_coordinates:
# 2d coordinates
warnings.warn(
"The file coordinates' transformation isn't "
"rectilinear: xarray won't parse the coordinates "
"in this case. Set `parse_coordinates=False` to "
"suppress this warning.",
RuntimeWarning,
stacklevel=3,
)
unsigned = False
encoding = {}
if mask_and_scale and "_Unsigned" in attrs:
unsigned = variables.pop_to(attrs, encoding, "_Unsigned") == "true"