8000 Fixed bug in serializing datetime scalars by shoyer · Pull Request #454 · pydata/xarray · GitHub
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Fixed bug in serializing datetime scalars #454

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Merged
merged 1 commit into from
Jul 6, 2015
Merged

Fixed bug in serializing datetime scalars #454

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1 change: 1 addition & 0 deletions doc/whats-new.rst
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Original file line number Diff line number Diff line change
Expand Up @@ -29,6 +29,7 @@ Bug fixes

- :py:func:`~xray.open_dataset` and :py:func:`~xray.open_mfdataset` support
supplying chunks as a single integer.
- Fixed a bug in serializing scalar datetime variable to netCDF.

v0.5.1 (15 June 2015)
---------------------
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4 changes: 2 additions & 2 deletions xray/conventions.py
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Expand Up @@ -181,7 +181,7 @@ def infer_datetime_units(dates):
'hours', 'minutes' or 'seconds' (the first one that can evenly divide all
unique time deltas in `dates`)
"""
dates = pd.to_datetime(np.asarray(dates), box=False)
dates = pd.to_datetime(np.asarray(dates).ravel(), box=False)
unique_timedeltas = np.unique(np.diff(dates[pd.notnull(dates)]))
units = _infer_time_units_from_diff(unique_timedeltas)
return '%s since %s' % (units, pd.Timestamp(dates[0]))
Expand All @@ -192,7 +192,7 @@ def infer_timedelta_units(deltas):
{'days', 'hours', 'minutes' 'seconds'} (the first one that can evenly
divide all unique time deltas in `deltas`)
"""
deltas = pd.to_timedelta(np.asarray(deltas), box=False)
deltas = pd.to_timedelta(np.asarray(deltas).ravel(), box=False)
unique_timedeltas = np.unique(deltas[pd.notnull(deltas)])
units = _infer_time_units_from_diff(unique_timedeltas)
return units
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4 changes: 2 additions & 2 deletions xray/test/test_backends.py
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Expand Up @@ -184,13 +184,13 @@ def test_roundtrip_string_data(self):

def test_roundtrip_datetime_data(self):
times = pd.to_datetime(['2000-01-01', '2000-01-02', 'NaT'])
expected = Dataset({'t': ('t', times)})
expected = Dataset({'t': ('t', times), 't0': times[0]})
with self.roundtrip(expected) as actual:
self.assertDatasetIdentical(expected, actual)

def test_roundtrip_timedelta_data(self):
time_deltas = pd.to_timedelta(['1h', '2h', 'NaT'])
expected = Dataset({'td': ('td', time_deltas)})
expected = Dataset({'td': ('td', time_deltas), 'td0': time_deltas[0]})
with self.roundtrip(expected) as actual:
self.assertDatasetIdentical(expected, actual)

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