ValueError: Buffer has wrong number of dimensions (expected 1, got 2) #665
Description
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:
import xray
ds = xray.open_dataset('ocean_vort.nc')
dsI get the following error:
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?