Rolling sum (closed='left') with duplicate Timestamp indices. 
#### Code Sample, a copy-pastable example if possible

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

n = 5
t1 = pd.date_range('1/1/2011', periods=n, freq='H')
v1 = range(n)

t2 = pd.date_range('1/1/2011', periods=n, freq='H')
v2 = range(n, 2*n)

index = np.sort(np.hstack([t1.values, t2.values]))
data = np.sort(np.hstack([v1, v2]))
s = pd.Series(data=data, index=index)
print(s)
```
2011-01-01 00:00:00    0
2011-01-01 00:00:00    1
2011-01-01 01:00:00    2
2011-01-01 01:00:00    3
2011-01-01 02:00:00    4
2011-01-01 02:00:00    5
2011-01-01 03:00:00    6
2011-01-01 03:00:00    7
2011-01-01 04:00:00    8
2011-01-01 04:00:00    9



#### Unexpected behavior: rolling treats duplicate times as consecutive
```
four_hours = pd.Timedelta('4h')
g = s.rolling(four_hours,closed='left').sum()
print(g)
2011-01-01 00:00:00     NaN
2011-01-01 00:00:00     0.0
2011-01-01 01:00:00     1.0
2011-01-01 01:00:00     3.0
2011-01-01 02:00:00     6.0
2011-01-01 02:00:00    10.0
2011-01-01 03:00:00    15.0
2011-01-01 03:00:00    21.0
2011-01-01 04:00:00    28.0
2011-01-01 04:00:00    36.0
```


#### Problem description
Rolling treats duplicate times as consecutive rather than equal. 

#### Expected Output
```
gg = s.groupby(s.index).sum().rolling(four_hours, closed='left').sum()
ggg = pd.concat([gg, gg]).sort_index()
print(ggg)
```

```
2011-01-01 00:00:00     NaN
2011-01-01 00:00:00     NaN
2011-01-01 01:00:00     1.0
2011-01-01 01:00:00     1.0
2011-01-01 02:00:00     6.0
2011-01-01 02:00:00     6.0
2011-01-01 03:00:00    15.0
2011-01-01 03:00:00    15.0
2011-01-01 04:00:00    28.0
2011-01-01 04:00:00    28.0
```
#### Output of ``pd.show_versions()``

<details>

[paste the output of ``pd.show_versions()`` here below this line]

INSTALLED VERSIONS
------------------
commit: None
python: 2.7.13.final.0
python-bits: 64
OS: Darwin
OS-release: 17.5.0
machine: x86_64
processor: i386
byteorder: little
LC_ALL: None
LANG: None
LOCALE: None.None
pandas: 0.20.1
pytest: 3.4.0
pip: 9.0.3
setuptools: 36.6.0
Cython: None
numpy: 1.13.3
scipy: 0.19.0
xarray: 0.9.5
IPython: 5.5.0
sphinx: None
patsy: 0.4.1
dateutil: 2.6.1
pytz: 2017.3
blosc: None
bottleneck: None
tables: None
numexpr: None
feather: None
matplotlib: 2.1.0
openpyxl: None
xlrd: 1.0.0
xlwt: None
xlsxwriter: None
lxml: None
bs4: 4.6.0
html5lib: 0.9999999
sqlalchemy: None
pymysql: None
psycopg2: None
jinja2: 2.9.6
s3fs: 0.1.0
pandas_gbq: None
pandas_datareader: None
import sys; print('Python %s on %s' % (sys.version, sys.platform))