mark_tests_working_on_intel
authorDebian Science Team <debian-science-maintainers@lists.alioth.debian.org>
Tue, 29 May 2018 13:50:59 +0000 (14:50 +0100)
committerGraham Inggs <ginggs@debian.org>
Tue, 29 May 2018 13:50:59 +0000 (14:50 +0100)
Last-Update Sat, 14 Oct 2017 19:42:59 +0200
Bug-Debian: https://bugs.debian.org/877419
Author: Graham Inggs <ginggs@debian.org>
Last-Update: 2018-04-11

Gbp-Pq: Name mark_tests_working_on_intel.patch

pandas/tests/dtypes/test_cast.py
pandas/tests/frame/test_analytics.py
pandas/tests/frame/test_indexing.py
pandas/tests/frame/test_operators.py
pandas/tests/groupby/test_aggregate.py
pandas/tests/indexes/timedeltas/test_ops.py
pandas/tests/series/test_constructors.py
pandas/tests/series/test_period.py
pandas/tests/test_algos.py
pandas/tests/test_resample.py

index 82a35fa711e8cd1d64cbb997101c76b53fe74cb2..491de261f02a61ac5b0b70201e8fbff069fe304b 100644 (file)
@@ -78,6 +78,7 @@ class TestMaybeDowncast(object):
             tm.assert_almost_equal(result, np.array([], dtype=np.int64))
             assert result.dtype == np.int64
 
+    @pytest.mark.intel
     def test_datetimelikes_nan(self):
         arr = np.array([1, 2, np.nan])
         exp = np.array([1, 2, np.datetime64('NaT')], dtype='datetime64[ns]')
index 97ab0deb50d503d6ad02e8a57a5261e6c5a2b28a..1d3453b0666d6da531b109fa1945ec9259287f43 100644 (file)
@@ -974,6 +974,7 @@ class TestDataFrameAnalytics(TestData):
         expected = pd.Series(result, index=['A', 'B'])
         tm.assert_series_equal(result, expected)
 
+    @pytest.mark.intel
     def test_sum_nanops_timedelta(self):
         # prod isn't defined on timedeltas
         idx = ['a', 'b', 'c']
index 78554d98ab5dfe8aefe10a2e5dd36360acdd3d42..49525f35c0c78130d4dbe453778154e6d48ef47c 100644 (file)
@@ -2649,6 +2649,7 @@ class TestDataFrameIndexing(TestData):
         result = a.where(do_not_replace, b)
         assert_frame_equal(result, expected)
 
+    @pytest.mark.intel
     def test_where_datetime(self):
 
         # GH 3311
index 986ba543141929a024cd8098cccc5f76819c35d7..bd524147fa7b94bc1ab9d7b0c43fda00921682e4 100644 (file)
@@ -177,6 +177,7 @@ class TestDataFrameOperators(TestData):
             df)), 'b': date_range('20100101', periods=len(df))})
         check(df, df2)
 
+    @pytest.mark.intel
     def test_timestamp_compare(self):
         # make sure we can compare Timestamps on the right AND left hand side
         # GH4982
index ad1a322fdaae93a8533c8ad6b0011d28e78a27af..d6abe1f3864d27e1b9bbd343426a3a369d8c5284 100644 (file)
@@ -131,6 +131,7 @@ class TestGroupByAggregate(object):
         grouped = df.groupby(df.index.month)
         list(grouped)
 
+    @pytest.mark.intel
     def test_agg_dict_parameter_cast_result_dtypes(self):
         # GH 12821
 
index 3cf56dc5115c2b1a7d51a039459d77512e67bc38..d59a6e421a3d8d18792efe137b50e6df67db6af5 100644 (file)
@@ -1104,6 +1104,7 @@ class TestTimedeltas(object):
             result = base - offset
             assert result == expected_sub
 
+    @pytest.mark.intel
     def test_timedelta_ops_with_missing_values(self):
         # setup
         s1 = pd.to_timedelta(Series(['00:00:01']))
index d2960860213494806d440f31770f1aac43ab2eb8..d28515d964f7aa89db357e555e337f4c8c036e9b 100644 (file)
@@ -786,6 +786,7 @@ class TestSeriesConstructors(TestData):
         series[2] = val
         assert isna(series[2])
 
+    @pytest.mark.intel
     def test_NaT_cast(self):
         # GH10747
         result = Series([np.nan]).astype('M8[ns]')
index e907b0edd5c6af91ceebf4f0b1dda922e2f1f67b..d2dc35b9333d73e471fd2ee477007d3b63946009 100644 (file)
@@ -94,6 +94,7 @@ class TestSeriesPeriod(object):
         series[2] = val
         assert isna(series[2])
 
+    @pytest.mark.intel
     def test_NaT_cast(self):
         result = Series([np.nan]).astype('period[D]')
         expected = Series([NaT])
index 240a7ad4b22f9c3a4ade101dfc6c8e46f69d8353..c4302509477b4f2c5f066a169def5094d5fc599d 100644 (file)
@@ -688,6 +688,7 @@ class TestValueCounts(object):
             expected = Series([2, 1, 1], index=[5., 10.3, np.nan])
             tm.assert_series_equal(result, expected)
 
+    @pytest.mark.intel
     def test_value_counts_normalized(self):
         # GH12558
         s = Series([1, 2, np.nan, np.nan, np.nan])
index 04e702644913fbcd99f189ceabe9be389c51cb58..5f4a3e9d50623fab3c2ed0c4d623318aaf8ec46b 100644 (file)
@@ -2204,6 +2204,7 @@ class TestDatetimeIndex(Base):
 
         assert_frame_equal(frame.resample('60s').mean(), frame_3s)
 
+    @pytest.mark.intel
     def test_resample_timedelta_values(self):
         # GH 13119
         # check that timedelta dtype is preserved when NaT values are
@@ -2221,6 +2222,7 @@ class TestDatetimeIndex(Base):
         res = df['time'].resample('2D').first()
         tm.assert_series_equal(res, exp)
 
+    @pytest.mark.intel
     def test_resample_datetime_values(self):
         # GH 13119
         # check that datetime dtype is preserved when NaT values are