BUG: Rank on Rolling window not correct when using FixedForwardWindowIndexer

[jenko]

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• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd

df = pd.DataFrame({"X":[9,3,4,5,1,2,8,7,6,10,11]})
window_size = 5
indexer = pd.api.indexers.FixedForwardWindowIndexer(window_size=window_size)
df.rolling(window=indexer).rank(ascending=False)

      X
0   5.0
1   4.0
2   1.0
3   2.0
4   3.0
5   1.0
6   1.0
7   NaN
8   NaN
9   NaN
10  NaN

Issue Description

Ranking a rolling window using FixedForwardWindowIndexer yields incorrect results.

Expected Behavior

  X

0 1.0 # based on the window [9,3,4,5,1], 9 is ranked 1st w/ascending = False
1 3.0 # based on the window [3,4,5,1,2], 3 is ranked 3rd
2 3.0 # based on the window [4,5,1,2,8], 4 is ranked 3rd
3 3.0 # etc
4 5.0
5 5.0
6 3.0
7 NaN
8 NaN
9 NaN
10 NaN

Installed Versions

INSTALLED VERSIONS

commit : 8dab54d
python : 3.10.6.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.79.1-microsoft-standard-WSL2
Version : #1 SMP Wed Nov 23 01:01:46 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8

pandas : 1.5.2
numpy : 1.23.4
pytz : 2022.6
dateutil : 2.8.2
setuptools : 59.6.0
pip : 22.3.1
Cython : None
pytest : 7.2.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : None
pandas_datareader: None
bs4 : None
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.6.2
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.9.3
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None
tzdata : None

[gsiano]

This looks like it is computing the rank on the right-most value in each window. You get the same results if you do

df.X.rolling(window=indexer).apply(lambda x: x.rank(ascending=False).iloc[-1])