issues: 322591813

Code Sample, a copy-pastable example if possible

``` In [1]: from itertools import product

In [2]: import numpy as np

In [3]: import xarray as xr

In [4]: from cftime import DatetimeNoLeap

In [5]: dates = [DatetimeNoLeap(year, month, 1) for year, month in product(range ...: (1, 3), range(1, 13))]

In [6]: with xr.set_options(enable_cftimeindex=True): ...: da = xr.DataArray(np.arange(24), coords=[dates], dims=['time'], name='foo') ...:

In [7]: da.to_netcdf('test.nc')

TypeError Traceback (most recent call last) <ipython-input-7-306dbf0ba669> in <module>() ----> 1 da.to_netcdf('test.nc')

/Users/spencerclark/xarray-dev/xarray/xarray/core/dataarray.pyc in to_netcdf(self, args, kwargs) 1514 dataset = self.to_dataset() 1515 -> 1516 return dataset.to_netcdf(args, **kwargs) 1517 1518 def to_dict(self):

/Users/spencerclark/xarray-dev/xarray/xarray/core/dataset.pyc in to_netcdf(self, path, mode, format, group, engine, encoding, unlimited_dims) 1143 return to_netcdf(self, path, mode, format=format, group=group, 1144 engine=engine, encoding=encoding, -> 1145 unlimited_dims=unlimited_dims) 1146 1147 def to_zarr(self, store=None, mode='w-', synchronizer=None, group=None,

/Users/spencerclark/xarray-dev/xarray/xarray/backends/api.pyc in to_netcdf(dataset, path_or_file, mode, format, group, engine, writer, encoding, unlimited_dims) 681 try: 682 dataset.dump_to_store(store, sync=sync, encoding=encoding, --> 683 unlimited_dims=unlimited_dims) 684 if path_or_file is None: 685 return target.getvalue()

/Users/spencerclark/xarray-dev/xarray/xarray/core/dataset.pyc in dump_to_store(self, store, encoder, sync, encoding, unlimited_dims) 1073 1074 store.store(variables, attrs, check_encoding, -> 1075 unlimited_dims=unlimited_dims) 1076 if sync: 1077 store.sync()

/Users/spencerclark/xarray-dev/xarray/xarray/backends/common.pyc in store(self, variables, attributes, check_encoding_set, unlimited_dims) 356 """ 357 --> 358 variables, attributes = self.encode(variables, attributes) 359 360 self.set_attributes(attributes)

/Users/spencerclark/xarray-dev/xarray/xarray/backends/common.pyc in encode(self, variables, attributes) 441 # All NetCDF files get CF encoded by default, without this attempting 442 # to write times, for example, would fail. --> 443 variables, attributes = cf_encoder(variables, attributes) 444 variables = OrderedDict([(k, self.encode_variable(v)) 445 for k, v in variables.items()])

/Users/spencerclark/xarray-dev/xarray/xarray/conventions.pyc in cf_encoder(variables, attributes) 575 """ 576 new_vars = OrderedDict((k, encode_cf_variable(v, name=k)) --> 577 for k, v in iteritems(variables)) 578 return new_vars, attributes

python2/cyordereddict/_cyordereddict.pyx in cyordereddict._cyordereddict.OrderedDict.init (python2/cyordereddict/_cyordereddict.c:1225)()

//anaconda/envs/xarray-dev/lib/python2.7/_abcoll.pyc in update(args, *kwds) 569 self[key] = other[key] 570 else: --> 571 for key, value in other: 572 self[key] = value 573 for key, value in kwds.items():

/Users/spencerclark/xarray-dev/xarray/xarray/conventions.pyc in <genexpr>((k, v)) 575 """ 576 new_vars = OrderedDict((k, encode_cf_variable(v, name=k)) --> 577 for k, v in iteritems(variables)) 578 return new_vars, attributes

/Users/spencerclark/xarray-dev/xarray/xarray/conventions.pyc in encode_cf_variable(var, needs_copy, name) 232 variables.CFMaskCoder(), 233 variables.UnsignedIntegerCoder()]: --> 234 var = coder.encode(var, name=name) 235 236 # TODO(shoyer): convert all of these to use coders, too:

/Users/spencerclark/xarray-dev/xarray/xarray/coding/times.pyc in encode(self, variable, name) 384 data, 385 encoding.pop('units', None), --> 386 encoding.pop('calendar', None)) 387 safe_setitem(attrs, 'units', units, name=name) 388 safe_setitem(attrs, 'calendar', calendar, name=name)

/Users/spencerclark/xarray-dev/xarray/xarray/coding/times.pyc in encode_cf_datetime(dates, units, calendar) 338 339 if units is None: --> 340 units = infer_datetime_units(dates) 341 else: 342 units = _cleanup_netcdf_time_units(units)

/Users/spencerclark/xarray-dev/xarray/xarray/coding/times.pyc in infer_datetime_units(dates) 254 reference_date = dates[0] if len(dates) > 0 else '1970-01-01' 255 reference_date = format_cftime_datetime(reference_date) --> 256 unique_timedeltas = np.unique(np.diff(dates)).astype('timedelta64[ns]') 257 units = _infer_time_units_from_diff(unique_timedeltas) 258 return '%s since %s' % (units, reference_date)

TypeError: Cannot cast datetime.timedelta object from metadata [Y] to [ns] according to the rule 'same_kind' ```

Problem description

This seems to be an edge case that was not covered in the tests I added in #1252. Strangely if I cast the result of np.unique(np.diff(dates)) as an array before converting to 'timedelta64[ns]' objects things work: ``` In [9]: np.unique(np.diff(dates)).astype('timedelta64[ns]')

---

TypeError Traceback (most recent call last) <ipython-input-9-5d53452b676f> in <module>() ----> 1 np.unique(np.diff(dates)).astype('timedelta64[ns]')

TypeError: Cannot cast datetime.timedelta object from metadata [Y] to [ns] according to the rule 'same_kind'

In [10]: np.array(np.unique(np.diff(dates))).astype('timedelta64[ns]') Out[10]: array([2419200000000000, 2592000000000000, 2678400000000000], dtype='timedelta64[ns]') ``` Might anyone have any ideas as to what the underlying issue is? The fix could be as simple as that, but I don't understand why that makes a difference.

Expected Output

da.to_netcdf('test.nc') should succeed without an error.

Output of xr.show_versions()

INSTALLED VERSIONS ------------------ commit: None python: 2.7.14.final.0 python-bits: 64 OS: Darwin OS-release: 17.4.0 machine: x86_64 processor: i386 byteorder: little LC_ALL: None LANG: en_US.UTF-8 LOCALE: None.None xarray: 0.8.2+dev641.g7302d7e pandas: 0.22.0 numpy: 1.13.1 scipy: 0.19.1 netCDF4: 1.3.1 h5netcdf: None h5py: 2.7.1 Nio: None zarr: 2.2.0 bottleneck: None cyordereddict: 1.0.0 dask: 0.17.1 distributed: 1.21.3 matplotlib: 2.2.2 cartopy: None seaborn: 0.8.1 setuptools: 38.4.0 pip: 9.0.1 conda: None pytest: 3.3.2 IPython: 5.5.0 sphinx: 1.7.1