Rethinking ``to_flat_index`` on flat ``Index``
With reference to #22866, and to a comment I made ( https://github.com/pandas-dev/pandas/pull/22866#issuecomment-437700886 ) which I thought was paranoid and maybe is not.

Three considerations:
1. ``to_flat_index`` is the only method (the only operation in pandas, actually) I can think of which gives a different result when called on a flat ``Index`` and when called on an equivalent 1-level ``MultiIndex``: you obtain the ``Index`` itself (each item being assumingly a scalar) in the first case and an ``Index`` of length 1 tuples in the second case
2. if one needs, for any reason, an ``Index`` of length-one scalar, there is no simple way to obtain it. Or if you prefer: if we add some ``sep`` or analogous arguments (e.g. ``fmt``) to ``to_flat_index``, then it is not going to work on a flat ``Index`` (at least with the current implementation). In general, ``to_flat_index`` is a method which makes sense also because it can be combined with, for instance ``.map``. When doing so, it is good to know for sure that the arguments received by the callable are always tuples.
3. ``Index.to_flat_index()`` as it is now is idempotent and pretty useless: it makes sense for compatibility... but then compatibility is a priority!

These all lead me to conclude: shouldn't ``pd.Index.to_flat_index()`` return an ``Index`` of length-1 tuples?

@WillAyd 

#### Code Sample, a copy-pastable example if possible

```python
In [2]: pd.Index([1, 2, 3,]).to_flat_index()
Out[2]: Int64Index([1, 2, 3], dtype='int64')

In [3]: pd.MultiIndex.from_arrays([pd.Index([1, 2, 3,])]).to_flat_index()
Out[3]: Index([(1,), (2,), (3,)], dtype='object')
```

#### Expected Output

``Out[2]`` should be equal to ``Out[3]``

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit: 454ecfc61891be610fbb586a7d946eb61b87f32d
python: 3.5.3.final.0
python-bits: 64
OS: Linux
OS-release: 4.9.0-8-amd64
machine: x86_64
processor: 
byteorder: little
LC_ALL: None
LANG: it_IT.UTF-8
LOCALE: it_IT.UTF-8

pandas: 0.24.0.dev0+995.g454ecfc61
pytest: 3.5.0
pip: 9.0.1
setuptools: 39.2.0
Cython: 0.28.4
numpy: 1.14.3
scipy: 0.19.0
pyarrow: None
xarray: None
IPython: 6.2.1
sphinx: 1.5.6
patsy: 0.5.0
dateutil: 2.7.3
pytz: 2018.4
blosc: None
bottleneck: 1.2.0dev
tables: 3.3.0
numexpr: 2.6.1
feather: 0.3.1
matplotlib: 2.2.2.post1634.dev0+ge8120cf6d
openpyxl: 2.3.0
xlrd: 1.0.0
xlwt: 1.3.0
xlsxwriter: 0.9.6
lxml: 4.1.1
bs4: 4.5.3
html5lib: 0.999999999
sqlalchemy: 1.0.15
pymysql: None
psycopg2: None
jinja2: 2.10
s3fs: None
fastparquet: None
pandas_gbq: None
pandas_datareader: 0.2.1
gcsfs: None

</details>
