BUG: support corr and cov functions for custom BaseIndexer rolling windows
- [X] closes #32865
- [X] reverts #33057
- [X] 2 tests added / 2 passed
- [X] passes `black pandas`
- [X] passes `git diff upstream/master -u -- "*.py" | flake8 --diff`
- [X] whatsnew entry

## Scope of PR
This is the final PR needed to solve #32865. It fixes `cov` and `corr` by passing the correct argument to `rolling` constructors if the functions are called with a custom `BaseIndexer` subclass. A separate test is added for `cov` and `corr` as the previous tests were single-variable and wouldn't work with two columns of data. I also propose we revert #33057.

## Details
The reason `cov` and `corr` didn't work was that we were passing `_get_window` results (usually, window width), instead of the `BaseIndexer` subclass to `rolling` constructors called inside the function. Passing `self.window` (when necessary) fixes the issue.

The new test asserts only against an explicit array, because shoehorning a comparison against `np.cov` an `np.corrcoef` is ugly (I've tried). Our `rolling.apply` isn't really suited to be called with bivariate statistics functions, and the necessary gymnastics didn't look good to me. I don't believe the minor benefit would be worth, but please say if you think coomparing against numpy is necessary.

Thanks to @mroeschke for implementing the `NotImplemented` error-raising behavior in #33057 . Now that all the functions are fixed, I propose we revert that commit.

## Background on the wider issue
We currently don't support several rolling window functions when building a rolling window object using a custom class descended from `pandas.api.indexers.Baseindexer`. The implementations were written with backward-looking windows in mind, and this led to these functions breaking.
Currently, using these functions returns a `NotImplemented` error thanks to #33057, but ideally we want to update the implementations, so that they will work without a performance hit. This is what I aim to do over a series of PRs.

## Perf notes
No changes to algorithms.