issue_comments

That sounds reasonable to me. I don't necessarily expect all of the xarray goodness to work with those files, but I do expect them to open without error.

@rabernat While I agree that they're (somewhat) confusing files, I think you're missing two things:

1. netCDF doesn't enforce naming on dimensions and variables. Full stop. The only naming netCDF will care about is any conflict with an internal reserved name (I'm not sure that those even exist for anything besides attributes.) IMO that's a good thing, but more importantly it's not the netCDF library's job to enforce any of it.

2. CF is an attribute convention. This also means that the conventions say absolutely nothing about naming of variables and dimensions.

IMO, xarray is being overly pedantic here. XArray states that it adopts the Common Data Model (CDM); netCDF-java and the CDM were the tools used to generate the failing examples above.

@rabernat For the groups NetCDF files I had in mind the NASA L1B data files for the satellite instrument VIIRS onboard Suomi-NPP and NOAA-20 satellites. You can see an example file here.

The summary of the ncdump is:

``` netcdf VNP02IMG.A2018008.0000.001.2018061001540 { dimensions: number_of_scans = 202 ; number_of_lines = 6464 ; number_of_pixels = 6400 ; number_of_LUT_values = 65536 ;

... lots of global attributes ...

group: scan_line_attributes { variables: double scan_start_time(number_of_scans) ; scan_start_time:long_name = "Scan start time (TAI93)" ; scan_start_time:units = "seconds" ; scan_start_time:_FillValue = -999.9 ; scan_start_time:valid_min = 0. ; scan_start_time:valid_max = 2000000000. ; ... lots of other variables in this group ...

group: observation_data { variables: ushort I04(number_of_lines, number_of_pixels) ; I04:long_name = "I-band 04 earth view radiance" ; I04:units = "Watts/meter^2/steradian/micrometer" ; I04:_FillValue = 65535US ; I04:valid_min = 0US ; I04:valid_max = 65527US ; I04:scale_factor = 6.104354e-05f ; I04:add_offset = 0.0016703f ; I04:flag_values = 65532US, 65533US, 65534US ; I04:flag_meanings = "Missing_EV Bowtie_Deleted Cal_Fail" ;

```

When I first started out with xarray I assumed I would be able to do something like:

import xarray as xr nc = xr.open_dataset('VNP02IMG.A2018008.0000.001.2018061001540.nc') band_data = nc['observation_data/I04']

Which I can't do, but can do with the python netcdf4 library:

``` In [7]: from netCDF4 import Dataset

In [8]: nc = Dataset('VNP02IMG.A2018008.0000.001.2018061001540.nc')

In [9]: nc['observation_data/I04'] Out[9]: <class 'netCDF4._netCDF4.Variable'> ```

I understand that I can provide the group keyword to open_dataset but then I have to open the file twice if I want to get the global attributes. So any interface I had set up in my code to pass around one object with all of the file contents won't work. That isn't xarray's fault and shouldn't necessarily be something xarray has to solve, but it is a type of NetCDF4 file that is valid and can't be read "perfectly" with xarray.

I found this problem too long ago (see #457). Back then the workaround we implemented is to exclude the offending variable ("siglay" or "isobaric" in the examples above) with the "drop_variables" optional argument. Of course this is not great if you want to actually use the values in the variable you are dropping.

I personally don't like the notion of a "two dimensional coordinate", I find it confusing. However this kind of netCDFs are common, so fully supporting them in xarray would be nice. But I don't know how. Maybe just renaming the variable instead of dropping it with a "rename_variables"? This is the only thing that comes to my mind.

This is mentioned elsewhere (can't find the issue right now) and may be out of scope for this issue but I'm going to say it anyway: opening a NetCDF file with groups was not as easy as I wanted it to be when first starting out with xarray.

Here's a sample CDL for a file: ``` netcdf temp { dimensions: profile = 1 ; station = 1 ; isobaric = 31 ; station_name_strlen = 10 ; station_description_strlen = 33 ; variables: float isobaric(station, profile, isobaric) ; isobaric:standard_name = "isobaric" ; isobaric:long_name = "isobaric" ; isobaric:units = "Pa" ; isobaric:positive = "down" ; isobaric:axis = "Z" ; float Geopotential_height_isobaric(station, profile, isobaric) ; Geopotential_height_isobaric:standard_name = "Geopotential_height_isobaric" ; Geopotential_height_isobaric:long_name = "Geopotential_height_isobaric" ; Geopotential_height_isobaric:units = "gpm" ; Geopotential_height_isobaric:coordinates = "time longitude latitude isobaric" ; char station_name(station, station_name_strlen) ; station_name:long_name = "station name" ; station_name:cf_role = "timeseries_id" ; char station_description(station, station_description_strlen) ; station_description:long_name = "station description" ; station_description:standard_name = "platform_name" ; double latitude(station) ; latitude:units = "degrees_north" ; latitude:long_name = "profile latitude" ; double longitude(station) ; longitude:units = "degrees_east" ; longitude:long_name = "profile longitude" ; double time(station, profile) ; time:units = "Hour since 2018-08-15T12:00:00Z" ; time:calendar = "proleptic_gregorian" ; time:standard_name = "time" ; time:long_name = "GRIB forecast or observation time" ;

// global attributes: :Conventions = "CDM-Extended-CF" ; :history = "Written by CFPointWriter" ; :title = "Extract Points data from Grid file /data/ldm/pub/native/grid/NCEP/GFS/Global_0p5deg/GFS_Global_0p5deg_20180815_1200.grib2.ncx3#LatLon_361X720-p25S-180p0E" ; :featureType = "timeSeriesProfile" ; :time_coverage_start = "2018-08-15T18:00:00Z" ; :time_coverage_end = "2018-08-15T18:00:00Z" ; :geospatial_lat_min = 39.9995 ; :geospatial_lat_max = 40.0005 ; :geospatial_lon_min = -105.0005 ; :geospatial_lon_max = -104.9995 ; } which gives:pytb

MissingDimensionsError Traceback (most recent call last) <ipython-input-10-d6f8d8651b9f> in <module>() 4 query.add_lonlat().accept('netcdf4') 5 nc = ncss.get_data(query) ----> 6 xr.open_dataset(NetCDF4DataStore(nc))

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/backends/api.py in open_dataset(filename_or_obj, group, decode_cf, mask_and_scale, decode_times, autoclose, concat_characters, decode_coords, engine, chunks, lock, cache, drop_variables, backend_kwargs) 352 store = backends.ScipyDataStore(filename_or_obj) 353 --> 354 return maybe_decode_store(store) 355 356

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/backends/api.py in maybe_decode_store(store, lock) 256 store, mask_and_scale=mask_and_scale, decode_times=decode_times, 257 concat_characters=concat_characters, decode_coords=decode_coords, --> 258 drop_variables=drop_variables) 259 260 _protect_dataset_variables_inplace(ds, cache)

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables) 428 vars, attrs, concat_characters, mask_and_scale, decode_times, 429 decode_coords, drop_variables=drop_variables) --> 430 ds = Dataset(vars, attrs=attrs) 431 ds = ds.set_coords(coord_names.union(extra_coords).intersection(vars)) 432 ds._file_obj = file_obj

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/dataset.py in init(self, data_vars, coords, attrs, compat) 363 coords = {} 364 if data_vars is not None or coords is not None: --> 365 self._set_init_vars_and_dims(data_vars, coords, compat) 366 if attrs is not None: 367 self.attrs = attrs

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/dataset.py in _set_init_vars_and_dims(self, data_vars, coords, compat) 381 382 variables, coord_names, dims = merge_data_and_coords( --> 383 data_vars, coords, compat=compat) 384 385 self._variables = variables

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in merge_data_and_coords(data, coords, compat, join) 363 indexes = dict(extract_indexes(coords)) 364 return merge_core(objs, compat, join, explicit_coords=explicit_coords, --> 365 indexes=indexes) 366 367

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in merge_core(objs, compat, join, priority_arg, explicit_coords, indexes) 433 coerced = coerce_pandas_values(objs) 434 aligned = deep_align(coerced, join=join, copy=False, indexes=indexes) --> 435 expanded = expand_variable_dicts(aligned) 436 437 coord_names, noncoord_names = determine_coords(coerced)

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in expand_variable_dicts(list_of_variable_dicts) 209 var_dicts.append(coords) 210 --> 211 var = as_variable(var, name=name) 212 sanitized_vars[name] = var 213

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/variable.py in as_variable(obj, name) 112 'dimensions %r. xarray disallows such variables because they ' 113 'conflict with the coordinates used to label ' --> 114 'dimensions.' % (name, obj.dims)) 115 obj = obj.to_index_variable() 116

MissingDimensionsError: 'isobaric' has more than 1-dimension and the same name as one of its dimensions ('station', 'profile', 'isobaric'). xarray disallows such variables because they conflict with the coordinates used to label dimensions. ```

python import xarray as xr xr.open_dataset('http://thredds.ucar.edu/thredds/dodsC/grib/NCEP/GFS/Global_0p5deg/TwoD')

```pytb

MissingDimensionsError Traceback (most recent call last) <ipython-input-6-e2a87d803d99> in <module>() ----> 1 xr.open_dataset(gfs_cat.datasets[0].access_urls['OPENDAP'])

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/backends/api.py in open_dataset(filename_or_obj, group, decode_cf, mask_and_scale, decode_times, autoclose, concat_characters, decode_coords, engine, chunks, lock, cache, drop_variables, backend_kwargs) 344 lock = _default_lock(filename_or_obj, engine) 345 with close_on_error(store): --> 346 return maybe_decode_store(store, lock) 347 else: 348 if engine is not None and engine != 'scipy':

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/backends/api.py in maybe_decode_store(store, lock) 256 store, mask_and_scale=mask_and_scale, decode_times=decode_times, 257 concat_characters=concat_characters, decode_coords=decode_coords, --> 258 drop_variables=drop_variables) 259 260 _protect_dataset_variables_inplace(ds, cache)

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables) 428 vars, attrs, concat_characters, mask_and_scale, decode_times, 429 decode_coords, drop_variables=drop_variables) --> 430 ds = Dataset(vars, attrs=attrs) 431 ds = ds.set_coords(coord_names.union(extra_coords).intersection(vars)) 432 ds._file_obj = file_obj

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/dataset.py in init(self, data_vars, coords, attrs, compat) 363 coords = {} 364 if data_vars is not None or coords is not None: --> 365 self._set_init_vars_and_dims(data_vars, coords, compat) 366 if attrs is not None: 367 self.attrs = attrs

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/dataset.py in _set_init_vars_and_dims(self, data_vars, coords, compat) 381 382 variables, coord_names, dims = merge_data_and_coords( --> 383 data_vars, coords, compat=compat) 384 385 self._variables = variables

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in merge_data_and_coords(data, coords, compat, join) 363 indexes = dict(extract_indexes(coords)) 364 return merge_core(objs, compat, join, explicit_coords=explicit_coords, --> 365 indexes=indexes) 366 367

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in merge_core(objs, compat, join, priority_arg, explicit_coords, indexes) 433 coerced = coerce_pandas_values(objs) 434 aligned = deep_align(coerced, join=join, copy=False, indexes=indexes) --> 435 expanded = expand_variable_dicts(aligned) 436 437 coord_names, noncoord_names = determine_coords(coerced)

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/merge.py in expand_variable_dicts(list_of_variable_dicts) 209 var_dicts.append(coords) 210 --> 211 var = as_variable(var, name=name) 212 sanitized_vars[name] = var 213

~/miniconda3/envs/py36/lib/python3.6/site-packages/xarray/core/variable.py in as_variable(obj, name) 112 'dimensions %r. xarray disallows such variables because they ' 113 'conflict with the coordinates used to label ' --> 114 'dimensions.' % (name, obj.dims)) 115 obj = obj.to_index_variable() 116

MissingDimensionsError: 'time' has more than 1-dimension and the same name as one of its dimensions ('reftime', 'time'). xarray disallows such variables because they conflict with the coordinates used to label dimensions. ```

I believe the last one in the notebook below is already fixed and the first two are mentioned above but here is a data point:

http://nbviewer.jupyter.org/gist/ocefpaf/1bf3b86359c459c89d44a81d3129f967