dont use verify_integrity, push one more level of test into parametrize

pandas-dev · jorisvandenbossche · Nov 28, 2018 · Nov 19, 2018 · Nov 19, 2018 · Nov 19, 2018
commit dd7e87396fef2a30c7d6018c0fd305c1bdd5e0a0
diff --git a/pandas/core/arrays/timedeltas.py b/pandas/core/arrays/timedeltas.py
@@ -134,12 +134,11 @@ def _simple_new(cls, values, freq=None, dtype=_TD_DTYPE):
         return result
 
     def __new__(cls, values, freq=None, dtype=_TD_DTYPE, copy=False):
-        verify_integrity = True
 
         freq, freq_infer = dtl.maybe_infer_freq(freq)
 
-        values, inferred_freq = sequence_to_td64ns(values, copy=copy,
-                                                   unit=None)
+        values, inferred_freq = sequence_to_td64ns(
+            values, copy=copy, unit=None)
         if inferred_freq is not None:
             if freq is not None and freq != inferred_freq:
                 raise ValueError('Inferred frequency {inferred} from passed '
@@ -150,11 +149,10 @@ def __new__(cls, values, freq=None, dtype=_TD_DTYPE, copy=False):
             elif freq_infer:
                 freq = inferred_freq
                 freq_infer = False
-            verify_integrity = False
 
         result = cls._simple_new(values, freq=freq)
         # check that we are matching freqs
-        if verify_integrity and len(result) > 0:
+        if inferred_freq is None and len(result) > 0:
             if freq is not None and not freq_infer:
                 cls._validate_frequency(result, freq)
 

diff --git a/pandas/tests/arithmetic/test_datetime64.py b/pandas/tests/arithmetic/test_datetime64.py
@@ -1125,10 +1125,25 @@ def test_dt64arr_add_sub_relativedelta_offsets(self, box_with_array):
         'Easter', ('DateOffset', {'day': 4}),
         ('DateOffset', {'month': 5})])
     @pytest.mark.parametrize('normalize', [True, False])
+    @pytest.mark.parametrize('n', [0, 5])
     def test_dt64arr_add_sub_DateOffsets(self, box_with_array,
-                                         normalize, cls_and_kwargs):
+                                         n, normalize, cls_and_kwargs):
         # GH#10699
-        # assert these are equal on a piecewise basis
+        # assert vectorized operation matches pointwise operations
+
+        if isinstance(cls_and_kwargs, tuple):
+            # If cls_name param is a tuple, then 2nd entry is kwargs for
+            # the offset constructor
+            cls_name, kwargs = cls_and_kwargs
+        else:
+            cls_name = cls_and_kwargs
+            kwargs = {}
+
+        if n == 0 and cls_name in ['WeekOfMonth', 'LastWeekOfMonth',
+                                   'FY5253Quarter', 'FY5253']:
+            # passing n = 0 is invalid for these offset classes
+            return
+
         vec = DatetimeIndex([Timestamp('2000-01-05 00:15:00'),
                              Timestamp('2000-01-31 00:23:00'),
                              Timestamp('2000-01-01'),
@@ -1140,43 +1155,30 @@ def test_dt64arr_add_sub_DateOffsets(self, box_with_array,
         vec = tm.box_expected(vec, box_with_array)
         vec_items = vec.squeeze() if box_with_array is pd.DataFrame else vec
 
-        if isinstance(cls_and_kwargs, tuple):
-            # If cls_name param is a tuple, then 2nd entry is kwargs for
-            # the offset constructor
-            cls_name, kwargs = cls_and_kwargs
-        else:
-            cls_name = cls_and_kwargs
-            kwargs = {}
-
         offset_cls = getattr(pd.offsets, cls_name)
 
         with warnings.catch_warnings(record=True):
             # pandas.errors.PerformanceWarning: Non-vectorized DateOffset being
             # applied to Series or DatetimeIndex
             # we aren't testing that here, so ignore.
             warnings.simplefilter("ignore", PerformanceWarning)
-            for n in [0, 5]:
-                    if (cls_name in ['WeekOfMonth', 'LastWeekOfMonth',
-                                 'FY5253Quarter', 'FY5253'] and n == 0):
-                    # passing n = 0 is invalid for these offset classes
-                    continue
 
-                offset = offset_cls(n, normalize=normalize, **kwargs)
+            offset = offset_cls(n, normalize=normalize, **kwargs)
 
-                expected = DatetimeIndex([x + offset for x in vec_items])
-                expected = tm.box_expected(expected, box_with_array)
-                tm.assert_equal(expected, vec + offset)
+            expected = DatetimeIndex([x + offset for x in vec_items])
+            expected = tm.box_expected(expected, box_with_array)
+            tm.assert_equal(expected, vec + offset)
 
-                expected = DatetimeIndex([x - offset for x in vec_items])
-                expected = tm.box_expected(expected, box_with_array)
-                tm.assert_equal(expected, vec - offset)
+            expected = DatetimeIndex([x - offset for x in vec_items])
+            expected = tm.box_expected(expected, box_with_array)
+            tm.assert_equal(expected, vec - offset)
 
-                expected = DatetimeIndex([offset + x for x in vec_items])
-                expected = tm.box_expected(expected, box_with_array)
-                tm.assert_equal(expected, offset + vec)
+            expected = DatetimeIndex([offset + x for x in vec_items])
+            expected = tm.box_expected(expected, box_with_array)
+            tm.assert_equal(expected, offset + vec)
 
-                with pytest.raises(TypeError):
-                    offset - vec
+            with pytest.raises(TypeError):
+                offset - vec
 
     def test_dt64arr_add_sub_DateOffset(self, box_with_array):
         # GH#10699