Ensure decoding as datetime64[ns]

Pandas seems to have trouble constructing multi-indices when it's given
datetime64 arrays which don't have ns precision. The current version of
decode_cf_datetime will give datetime arrays with the default precision, which
is us. Hence, when coupled with the dtype restoring wrapper from PR #54, the
`to_series()` and `to_dataframe()` methods were broken when using decoded
datetimes.

Author: shoyer

src/xray/utils.py

@@ -135,7 +135,8 @@ def decode_cf_datetime(num_dates, units, calendar=None):
             or max_date > datetime(2262, 4, 11)):
         dates = nc4.num2date(num_dates, units, calendar)
     else:
-        # we can safely use np.datetime64
+        # we can safely use np.datetime64 with nanosecond precision (pandas
+        # likes ns precision so it can directly make DatetimeIndex objects)
         if min_num == max_num:
             # we can't safely divide by max_num - min_num
             dates = np.repeat(np.datetime64(min_date), num_dates.size)
@@ -156,8 +157,8 @@ def decode_cf_datetime(num_dates, units, calendar=None):
             denominator = max_num - min_num
             dates = (time_delta * numerator / denominator
                      + np.datetime64(min_date))
-        # restore original shape
-        dates = dates.reshape(num_dates.shape)
+        # restore original shape and ensure dates are given in ns
+        dates = dates.reshape(num_dates.shape).astype('M8[ns]')
     return dates
 
 

test/test_utils.py

@@ -89,7 +89,17 @@ def test_cf_datetime(self):
             for calendar in ['standard', 'gregorian', 'proleptic_gregorian']:
                 expected = nc4.num2date(num_dates, units, calendar)
                 actual = utils.decode_cf_datetime(num_dates, units, calendar)
-                self.assertArrayEqual(expected, actual)
+                if (isinstance(actual, np.ndarray)
+                        and np.issubdtype(actual.dtype, np.datetime64)):
+                    self.assertEqual(actual.dtype, np.dtype('M8[ns]'))
+                    # For some reason, numpy 1.8 does not compare ns precision
+                    # datetime64 arrays as equal to arrays of datetime objects,
+                    # but it works for us precision. Thus, convert to us
+                    # precision for the actual array equal comparison...
+                    actual_cmp = actual.astype('M8[us]')
+                else:
+                    actual_cmp = actual
+                self.assertArrayEqual(expected, actual_cmp)
                 encoded, _, _ = utils.encode_cf_datetime(actual, units, calendar)
                 self.assertArrayEqual(num_dates, np.around(encoded))
                 if (hasattr(num_dates, 'ndim') and num_dates.ndim == 1