issues: 413589315

Code Sample, a copy-pastable example if possible

I try to load the following dataset over opendap with the pydap engine. It only works if I do decode_times=False

python url = 'http://aims3.llnl.gov/thredds/dodsC/css03_data/CMIP6/CMIP/NOAA-GFDL/GFDL-AM4/amip/r1i1p1f1/Amon/ta/gr1/v20180807/ta_Amon_GFDL-AM4_amip_r1i1p1f1_gr1_198001-201412.nc' ds = xr.open_dataset(url, decode_times=False, engine='pydap') xr.decode_times(ds)

raises ```

---

IndexError Traceback (most recent call last) <ipython-input-52-df985a95e29e> in <module>() 1 #ds.time_bnds.load() ----> 2 xr.decode_cf(ds)

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/conventions.py in decode_cf(obj, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables) 459 vars, attrs, coord_names = decode_cf_variables( 460 vars, attrs, concat_characters, mask_and_scale, decode_times, --> 461 decode_coords, drop_variables=drop_variables) 462 ds = Dataset(vars, attrs=attrs) 463 ds = ds.set_coords(coord_names.union(extra_coords).intersection(vars))

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/conventions.py in decode_cf_variables(variables, attributes, concat_characters, mask_and_scale, decode_times, decode_coords, drop_variables) 392 k, v, concat_characters=concat_characters, 393 mask_and_scale=mask_and_scale, decode_times=decode_times, --> 394 stack_char_dim=stack_char_dim) 395 if decode_coords: 396 var_attrs = new_vars[k].attrs

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/conventions.py in decode_cf_variable(name, var, concat_characters, mask_and_scale, decode_times, decode_endianness, stack_char_dim) 298 for coder in [times.CFTimedeltaCoder(), 299 times.CFDatetimeCoder()]: --> 300 var = coder.decode(var, name=name) 301 302 dimensions, data, attributes, encoding = (

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/coding/times.py in decode(self, variable, name) 410 units = pop_to(attrs, encoding, 'units') 411 calendar = pop_to(attrs, encoding, 'calendar') --> 412 dtype = _decode_cf_datetime_dtype(data, units, calendar) 413 transform = partial( 414 decode_cf_datetime, units=units, calendar=calendar)

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/coding/times.py in _decode_cf_datetime_dtype(data, units, calendar) 116 values = indexing.ImplicitToExplicitIndexingAdapter( 117 indexing.as_indexable(data)) --> 118 example_value = np.concatenate([first_n_items(values, 1) or [0], 119 last_item(values) or [0]]) 120

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/core/formatting.py in first_n_items(array, n_desired) 94 from_end=False) 95 array = array[indexer] ---> 96 return np.asarray(array).flat[:n_desired] 97 98

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/numpy/core/numeric.py in asarray(a, dtype, order) 529 530 """ --> 531 return array(a, dtype, copy=False, order=order) 532 533

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/core/indexing.py in array(self, dtype) 630 631 def array(self, dtype=None): --> 632 self._ensure_cached() 633 return np.asarray(self.array, dtype=dtype) 634

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/core/indexing.py in _ensure_cached(self) 627 def _ensure_cached(self): 628 if not isinstance(self.array, NumpyIndexingAdapter): --> 629 self.array = NumpyIndexingAdapter(np.asarray(self.array)) 630 631 def array(self, dtype=None):

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/numpy/core/numeric.py in asarray(a, dtype, order) 529 530 """ --> 531 return array(a, dtype, copy=False, order=order) 532 533

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/core/indexing.py in array(self, dtype) 608 609 def array(self, dtype=None): --> 610 return np.asarray(self.array, dtype=dtype) 611 612 def getitem(self, key):

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/numpy/core/numeric.py in asarray(a, dtype, order) 529 530 """ --> 531 return array(a, dtype, copy=False, order=order) 532 533

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/core/indexing.py in array(self, dtype) 514 def array(self, dtype=None): 515 array = as_indexable(self.array) --> 516 return np.asarray(array[self.key], dtype=None) 517 518 def transpose(self, order):

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/conventions.py in getitem(self, key) 43 44 def getitem(self, key): ---> 45 return np.asarray(self.array[key], dtype=self.dtype) 46 47

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/numpy/core/numeric.py in asarray(a, dtype, order) 529 530 """ --> 531 return array(a, dtype, copy=False, order=order) 532 533

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/core/indexing.py in array(self, dtype) 514 def array(self, dtype=None): 515 array = as_indexable(self.array) --> 516 return np.asarray(array[self.key], dtype=None) 517 518 def transpose(self, order):

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/backends/pydap_.py in getitem(self, key) 24 def getitem(self, key): 25 return indexing.explicit_indexing_adapter( ---> 26 key, self.shape, indexing.IndexingSupport.BASIC, self._getitem) 27 28 def _getitem(self, key):

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/core/indexing.py in explicit_indexing_adapter(key, shape, indexing_support, raw_indexing_method) 785 if numpy_indices.tuple: 786 # index the loaded np.ndarray --> 787 result = NumpyIndexingAdapter(np.asarray(result))[numpy_indices] 788 return result 789

~/miniconda3/envs/geo_scipy/lib/python3.6/site-packages/xarray/core/indexing.py in getitem(self, key) 1174 def getitem(self, key): 1175 array, key = self._indexing_array_and_key(key) -> 1176 return array[key] 1177 1178 def setitem(self, key, value):

IndexError: too many indices for array ```

Strangely, I can overcome the error by first explicitly loading (or dropping) the time_bnds variable: python ds.time_bnds.load() xr.decode_cf(ds)

I wish this would work without the .load() step. I think it has something to do with the many layers of array wrappers involved in lazy opening. The problem does not occur with the netcdf4 engine.

I know this is a very obscure problem, but I thought I would open an issue to document.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 3.6.8 |Anaconda, Inc.| (default, Dec 29 2018, 19:04:46) [GCC 4.2.1 Compatible Clang 4.0.1 (tags/RELEASE_401/final)] python-bits: 64 OS: Darwin OS-release: 16.7.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: en_US.UTF-8 libhdf5: 1.10.4 libnetcdf: 4.6.2 xarray: 0.11.3 pandas: 0.23.4 numpy: 1.13.1 scipy: 0.19.1 netCDF4: 1.4.2 pydap: installed h5netcdf: None h5py: None Nio: None zarr: 2.2.1.dev126+dirty cftime: 1.0.3.4 PseudonetCDF: None rasterio: None cfgrib: None iris: None bottleneck: 1.2.1 cyordereddict: None dask: 0.20.2 distributed: 1.24.2 matplotlib: 2.1.0 cartopy: 0.15.1 seaborn: 0.8.1 setuptools: 40.6.2 pip: 18.1 conda: None pytest: 4.0.0 IPython: 6.1.0 sphinx: 1.6.5