Change tests of casting an interval range index from float to int to reflect current behaviour
This is to address an issue I came across in PR #38697 where there is a test, `test_subtype_integer_errors`, in pandas/tests/indexes/interval/test_astype.py marked as failing because it is not raising `ValueErrors` when casting an interval range index from float to int. My reading of #15832 is that it is unnecessary to raise a `ValueError` in this case.

As I wrote in the comments to #38697:

The question is, as a user of pandas, if you had an interval range such as [(0.0, 0.25], (0.25, 0.5], (0.5, 0.75], (0.75, 1.0], (1.0, 1.25], (1.25, 1.5], (1.5, 1.75], (1.75, 2.0], (2.0, 2.25], (2.25, 2.5]], and you cast it to int, what would you want or expect? The old (failing) version of the test said you expect a ValueError. I am saying you expect [(0, 0], (0, 0], (0, 0], (0, 1], (1, 1], (1, 1], (1, 1], (1, 2], (2, 2], (2, 2]] which, as I said, looks not that useful as an IntervalIndex, but is not wrong either.

So what I plan to do is delete two `pytest.raises` calls in `test_subtype_integer_errors` but also add a test to ensure that casting an interval range from float to int works as expected.


> 
> Your logic makes sense to me, but I'd defer to someone with more experience on how we handle `IntervalIndex`. 
> 
> If being removed from this test, we definitely want to make sure this specific casting behavior is being tested somewhere.  To keep this pr simple and easier to merge, I'd suggest reverting modification of this test, then making a followup pr to clean up this test and add tests for any untested casting behavior.
> 
> _Originally posted by @mzeitlin11 in https://github.com/pandas-dev/pandas/pull/38697#discussion_r549023944_
