TST: Use intp as expected dtype in IntervalIndex indexing tests

[jschendel]

xref #23468 (comment): fixes some failing 32bit tests

[pep8speaks]

Hello @jschendel! Thanks for submitting the PR.

• There are no PEP8 issues in the file pandas/tests/indexes/interval/test_interval.py !

[codecov]

Codecov Report

Merging #23609 into master will not change coverage.
The diff coverage is n/a.

@@           Coverage Diff           @@
##           master   #23609   +/-   ##
=======================================
  Coverage   92.25%   92.25%           
=======================================
  Files         161      161           
  Lines       51260    51260           
=======================================
  Hits        47290    47290           
  Misses       3970     3970

Flag	Coverage Δ
#multiple	90.63% <ø> (ø)	⬆️
#single	42.33% <ø> (ø)	⬆️

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[jreback]

thanks

[jreback]

https://travis-ci.org/MacPython/pandas-wheels/jobs/453170919

it’s possible this ran before the merge or it’s still broken

[jschendel]

it’s possible this ran before the merge or it’s still broken

I think it ran before the merge. The expected in the failure message still has dtype='int64', which should have been changed to 'intp' if the merge had happened.

______ TestIntervalIndex.test_get_reindexer_datetimelike[datetime64[ns]] _______
self = 
arrays = (DatetimeIndex(['2018-01-01', '2018-01-02', '2018-01-03', '2018-01-04'], dtype='datetime64[ns]', freq='D'), DatetimeIndex(['2018-01-03', '2018-01-04', '2018-01-05', '2018-01-06'], dtype='datetime64[ns]', freq='D'))
    @pytest.mark.parametrize('arrays', [
        (date_range('20180101', periods=4), date_range('20180103', periods=4)),
        (date_range('20180101', periods=4, tz='US/Eastern'),
         date_range('20180103', periods=4, tz='US/Eastern')),
        (timedelta_range('0 days', periods=4),
         timedelta_range('2 days', periods=4))], ids=lambda x: str(x[0].dtype))
    def test_get_reindexer_datetimelike(self, arrays):
        # GH 20636
        index = IntervalIndex.from_arrays(*arrays)
        tuples = [(index[0].left, index[0].left + pd.Timedelta('12H')),
                  (index[-1].right - pd.Timedelta('12H'), index[-1].right)]
        target = IntervalIndex.from_tuples(tuples)
    
        result = index._get_reindexer(target)
        expected = np.array([0, 3], dtype='int64') 
>       tm.assert_numpy_array_equal(result, expected)
E       AssertionError: numpy array are different
E       
E       Attribute "dtype" are different
E       [left]:  int32
E       [right]: int64

[jreback]

https://travis-ci.org/MacPython/pandas-wheels/jobs/453459214

some more