{"action":"closed","issue":{"url":"https://api.github.com/repos/pydata/pandas/issues/14345","repository_url":"https://api.github.com/repos/pydata/pandas","labels_url":"https://api.github.com/repos/pydata/pandas/issues/14345/labels{/name}","comments_url":"https://api.github.com/repos/pydata/pandas/issues/14345/comments","events_url":"https://api.github.com/repos/pydata/pandas/issues/14345/events","html_url":"https://github.com/pydata/pandas/issues/14345","id":180925247,"number":14345,"title":"TST: failing test at tseries/tests/test_base.py TestDatetimeIndexOps 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A small, complete example of the issue\r\n\r\n```python\r\n======================================================================\r\nFAIL: test_nat (pandas.tseries.tests.test_base.TestDatetimeIndexOps)\r\n----------------------------------------------------------------------\r\nTraceback (most recent call last):\r\n  File \"/home/matt/pandas-mattrijk/pandas/tseries/tests/test_base.py\", line 878, in test_nat\r\n    tm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.int64))\r\n  File \"/home/matt/pandas-mattrijk/pandas/util/testing.py\", line 1084, in assert_numpy_array_equal\r\n    assert_attr_equal('dtype', left, right, obj=obj)\r\n  File \"/home/matt/pandas-mattrijk/pandas/util/testing.py\", line 878, in assert_attr_equal\r\n    left_attr, right_attr)\r\n  File \"/home/matt/pandas-mattrijk/pandas/util/testing.py\", line 1019, in raise_assert_detail\r\n    raise AssertionError(msg)\r\nAssertionError: numpy array are different\r\n\r\nAttribute \"dtype\" are different\r\n[left]:  int32\r\n[right]: int64\r\n\r\n----------------------------------------------------------------------\r\nRan 92 tests in 3.580s\r\n\r\nFAILED (failures=1)\r\n\r\n\r\nProcess finished with exit code 0\r\n\r\n```\r\n\r\n#### Expected Output\r\n# failing test\r\nidx = pd.DatetimeIndex(['2011-01-01', '2011-01-02'], tz=tz)\r\ntm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.int64))\r\n\r\nidx = pd.DatetimeIndex(['2011-01-01', 'NaT'], tz=tz)\r\ntm.assert_numpy_array_equal(idx._nan_idxs, np.array([1], dtype=np.int64))\r\n\r\n# test passes\r\ntm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.int32))\r\n\r\n\r\n\r\nIn Ipython on 32bit the values look fine.\r\n\r\nIn [3]: idx = pd.DatetimeIndex(['2016-01-01', 'NaT'], tz=None)\r\n\r\nIn [4]: idx.dtype\r\nOut[4]: dtype('<M8[ns]')\r\n\r\nIn [5]: idx._nan_idxs\r\nOut[5]: array([], dtype=int64)\r\n\r\nIn [6]: arry = np.array([], dtype=np.int64)\r\n\r\nIn [7]: arry\r\nOut[7]: array([], dtype=int64) \r\n\r\nIn [8]: import pandas.util.testing as tm\r\n\r\nIn [9]: tm.assert_numpy_array_equal(idx._nan_idxs, arry))\r\nOut[9]: True\r\n\r\n\r\nThis fixes it but I think theres more going on.\r\n\r\nimport platform\r\nif platform.architecture()[0] == '32bit':\r\n    tm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.int32))\r\nelse:\r\n    tm.assert_numpy_array_equal(idx._nan_idxs, np.array([], dtype=np.int64))\r\n\r\n#### Output of ``pd.show_versions()``\r\n\r\n<details>\r\nINSTALLED VERSIONS\r\n------------------\r\ncommit: None\r\npython: 2.7.12.final.0\r\npython-bits: 32\r\nOS: Linux\r\nOS-release: 3.13.0-92-generic\r\nmachine: i686\r\nprocessor: i686\r\nbyteorder: little\r\nLC_ALL: None\r\nLANG: en_US.UTF-8\r\nLOCALE: None.None\r\n\r\npandas: 0.19.0\r\nnose: 1.3.7\r\npip: 8.1.2\r\nsetuptools: 27.2.0\r\nCython: 0.24.1\r\nnumpy: 1.11.1\r\nscipy: 0.18.1\r\nstatsmodels: None\r\nxarray: None\r\nIPython: 5.1.0\r\nsphinx: 1.4.6\r\npatsy: 0.4.1\r\ndateutil: 2.5.3\r\npytz: 2016.6.1\r\nblosc: None\r\nbottleneck: 1.1.0\r\ntables: 3.2.3.1\r\nnumexpr: 2.6.1\r\nmatplotlib: 1.5.3\r\nopenpyxl: 2.4.0\r\nxlrd: 1.0.0\r\nxlwt: 1.1.2\r\nxlsxwriter: 0.9.3\r\nlxml: 3.6.4\r\nbs4: 4.3.2\r\nhtml5lib: 0.999\r\nhttplib2: None\r\napiclient: None\r\nsqlalchemy: 1.0.13\r\npymysql: 0.7.6.None\r\npsycopg2: None\r\njinja2: 2.8\r\nboto: None\r\npandas_datareader: 0.2.1\r\n\r\n\r\n\r\n</details>\r\n"}}
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