BUG: centered rolling on decreasing datetime-index inconsistency
### 

- [X] I have checked that this issue has not already been reported.

- [X] I have confirmed this bug exists on the [latest version](https://pandas.pydata.org/docs/whatsnew/index.html) of pandas.

- [X] I have confirmed this bug exists on the master branch of pandas.


### Reproducible Example

```python
import pandas as pd
import numpy as np

index = pd.date_range('2020', periods=4, freq='s')

inc = pd.Series([1,1,1,1], index=index).rolling('3s', center=True).sum()
dec = pd.Series([1,1,1,1], index=index[::-1]).rolling('3s', center=True).sum()

assert np.all(inc.values == dec.values)

>>> inc
2020-01-01 00:00:00    2.0
2020-01-01 00:00:01    3.0
2020-01-01 00:00:02    3.0
2020-01-01 00:00:03    2.0
Freq: S, dtype: float64

>>> dec
2020-01-01 00:00:03    NaN
2020-01-01 00:00:02    3.0
2020-01-01 00:00:01    3.0
2020-01-01 00:00:00    2.0
Freq: -1S, dtype: float64
```


### Issue Description

the first value is a `NaN` when rolling over a decreasing index with `center=True`, but it shouldnt. This happens for ever value of `closed`.  

AFAIK, this comes from the cython implementation of `calculate_valiable_window_bounds`. 

I prepared a MR for this. 



### Expected Behavior

no `NaN` as first value. 

### Installed Versions

<details>

INSTALLED VERSIONS
------------------
commit           : 73c68257545b5f8530b7044f56647bd2db92e2ba
python           : 3.9.5.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.4.0-88-generic
Version          : #99-Ubuntu SMP Thu Sep 23 17:29:00 UTC 2021
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : en_US.UTF-8
LOCALE           : en_US.UTF-8
pandas           : 1.3.3
numpy            : 1.20.3
pytz             : 2021.1
dateutil         : 2.8.2
pip              : 21.2.4
setuptools       : 57.0.0
Cython           : None
pytest           : 6.2.5
hypothesis       : 6.17.4
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : None
jinja2           : None
IPython          : None
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : None
fastparquet      : None
gcsfs            : None
matplotlib       : 3.4.3
numexpr          : None
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : 4.0.1
pyxlsb           : None
s3fs             : None
scipy            : 1.7.1
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : None
xlwt             : None
numba            : 0.54.0

</details>
