issues: 118525173

grab a copy of the file http://nh.id.au/data/ocean_vort.nc.gz, and gunzip it. It's a file with some ocean vorticity fields, from the MOM4 model. The ncdump -h ocean_vort.nc results don't look too odd to me.

If I run:

``` python import xray

ds = xray.open_dataset('ocean_vort.nc') ds ```

I get the following error:

``` python ValueError Traceback (most recent call last) /data/downloads/software/ipython/IPython/core/formatters.py in call(self, obj) 695 type_pprinters=self.type_printers, 696 deferred_pprinters=self.deferred_printers) --> 697 printer.pretty(obj) 698 printer.flush() 699 return stream.getvalue()

/data/downloads/software/ipython/IPython/lib/pretty.py in pretty(self, obj) 382 if callable(meth): 383 return meth(obj, self, cycle) --> 384 return _default_pprint(obj, self, cycle) 385 finally: 386 self.end_group()

/data/downloads/software/ipython/IPython/lib/pretty.py in default_pprint(obj, p, cycle) 502 if _safe_getattr(klass, '__repr__', None) not in _baseclass_reprs: 503 # A user-provided repr. Find newlines and replace them with p.break() --> 504 _repr_pprint(obj, p, cycle) 505 return 506 p.begin_group(1, '<')

/data/downloads/software/ipython/IPython/lib/pretty.py in repr_pprint(obj, p, cycle) 700 """A pprint that just redirects to the normal repr function.""" 701 # Find newlines and replace them with p.break() --> 702 output = repr(obj) 703 for idx,output_line in enumerate(output.splitlines()): 704 if idx:

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/dataset.py in repr(self) 885 886 def repr(self): --> 887 return formatting.dataset_repr(self) 888 889 @property

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/formatting.py in dataset_repr(ds) 271 272 summary.append(coords_repr(ds.coords, col_width=col_width)) --> 273 summary.append(vars_repr(ds.data_vars, col_width=col_width)) 274 if ds.attrs: 275 summary.append(attrs_repr(ds.attrs))

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/formatting.py in _mapping_repr(mapping, title, summarizer, col_width) 208 summary = ['%s:' % title] 209 if mapping: --> 210 summary += [summarizer(k, v, col_width) for k, v in mapping.items()] 211 else: 212 summary += [EMPTY_REPR]

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/formatting.py in <listcomp>(.0) 208 summary = ['%s:' % title] 209 if mapping: --> 210 summary += [summarizer(k, v, col_width) for k, v in mapping.items()] 211 else: 212 summary += [EMPTY_REPR]

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/formatting.py in summarize_var(name, var, col_width) 172 def summarize_var(name, var, col_width): 173 show_values = _not_remote(var) --> 174 return _summarize_var_or_coord(name, var, col_width, show_values) 175 176

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/formatting.py in _summarize_var_or_coord(name, var, col_width, show_values, marker, max_width) 154 front_str = first_col + dims_str + ('%s ' % var.dtype) 155 if show_values: --> 156 values_str = format_array_flat(var, max_width - len(front_str)) 157 else: 158 values_str = '...'

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/formatting.py in format_array_flat(items_ndarray, max_width) 130 # print at least one item 131 max_possibly_relevant = max(int(np.ceil(max_width / 2.0)), 1) --> 132 relevant_items = first_n_items(items_ndarray, max_possibly_relevant) 133 pprint_items = format_items(relevant_items) 134

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/formatting.py in first_n_items(x, n_desired) 54 indexer = _get_indexer_at_least_n_items(x.shape, n_desired) 55 x = x[indexer] ---> 56 return np.asarray(x).flat[:n_desired] 57 58

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/numpy/core/numeric.py in asarray(a, dtype, order) 472 473 """ --> 474 return array(a, dtype, copy=False, order=order) 475 476 def asanyarray(a, dtype=None, order=None):

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/common.py in array(self, dtype) 73 74 def array(self, dtype=None): ---> 75 return np.asarray(self.values, dtype=dtype) 76 77 def repr(self):

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/dataarray.py in values(self) 332 def values(self): 333 """The array's data as a numpy.ndarray""" --> 334 return self.variable.values 335 336 @values.setter

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/variable.py in values(self) 269 def values(self): 270 """The variable's data as a numpy.ndarray""" --> 271 return _as_array_or_item(self._data_cached()) 272 273 @values.setter

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/variable.py in _data_cached(self) 235 def _data_cached(self): 236 if not isinstance(self._data, np.ndarray): --> 237 self._data = np.asarray(self._data) 238 return self._data 239

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/numpy/core/numeric.py in asarray(a, dtype, order) 472 473 """ --> 474 return array(a, dtype, copy=False, order=order) 475 476 def asanyarray(a, dtype=None, order=None):

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/core/indexing.py in array(self, dtype) 292 def array(self, dtype=None): 293 array = orthogonally_indexable(self.array) --> 294 return np.asarray(array[self.key], dtype=None) 295 296 def getitem(self, key):

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/conventions.py in getitem(self, key) 416 417 def getitem(self, key): --> 418 return decode_cf_timedelta(self.array[key], units=self.units) 419 420

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/xray/conventions.py in decode_cf_timedelta(num_timedeltas, units) 166 num_timedeltas = _asarray_or_scalar(num_timedeltas) 167 units = _netcdf_to_numpy_timeunit(units) --> 168 result = pd.to_timedelta(num_timedeltas, unit=units, box=False) 169 # NaT is returned unboxed with wrong units; this should be fixed in pandas 170 if result.dtype != 'timedelta64[ns]':

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/pandas/util/decorators.py in wrapper(args, kwargs) 87 else: 88 kwargs[new_arg_name] = new_arg_value ---> 89 return func(args, **kwargs) 90 return wrapper 91 return _deprecate_kwarg

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/pandas/tseries/timedeltas.py in to_timedelta(arg, unit, box, errors, coerce) 64 return _convert_listlike(arg, box=box, unit=unit, name=arg.name) 65 elif is_list_like(arg): ---> 66 return _convert_listlike(arg, box=box, unit=unit) 67 68 # ...so it must be a scalar value. Return scalar.

/home/naught101/miniconda3/envs/science/lib/python3.4/site-packages/pandas/tseries/timedeltas.py in _convert_listlike(arg, box, unit, name) 47 value = arg.astype('timedelta64[{0}]'.format(unit)).astype('timedelta64[ns]', copy=False) 48 else: ---> 49 value = tslib.array_to_timedelta64(_ensure_object(arg), unit=unit, errors=errors) 50 value = value.astype('timedelta64[ns]', copy=False) 51

pandas/tslib.pyx in pandas.tslib.array_to_timedelta64 (pandas/tslib.c:47353)()

ValueError: Buffer has wrong number of dimensions (expected 1, got 2) ```

Any idea what might be causing that problem?