DatetimeIndex.to_period does not support multiple of frequencies
The code below is the simplest way I found to "snap" a DateTimeIndex to some "frequency" (is there any better way?). 
I would have expected the to_period method to work as flexibly as the resample method that accepts any rule (like 15T, 2H, ...) but the to_period method does not appear to handle properly multiples of frequencies (and neither raises an exception).
#### Code Sample, a copy-pastable example if possible

```
import pandas
import datetime
dt=pandas.date_range('2016-01-01 00:00','2016-01-01 05:00',freq='15T',closed="left")
print(dt.to_period('H').start_time) # snap to the hour : OK
print(dt.to_period('2H').start_time) # snap to even hours : not OK

```
#### Actual Output

```
DatetimeIndex(['2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 01:00:00', '2016-01-01 01:00:00',
               '2016-01-01 01:00:00', '2016-01-01 01:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 03:00:00', '2016-01-01 03:00:00',
               '2016-01-01 03:00:00', '2016-01-01 03:00:00',
               '2016-01-01 04:00:00', '2016-01-01 04:00:00',
               '2016-01-01 04:00:00', '2016-01-01 04:00:00'],
              dtype='datetime64[ns]', freq=None)
DatetimeIndex(['2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 01:00:00', '2016-01-01 01:00:00',
               '2016-01-01 01:00:00', '2016-01-01 01:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 03:00:00', '2016-01-01 03:00:00',
               '2016-01-01 03:00:00', '2016-01-01 03:00:00',
               '2016-01-01 04:00:00', '2016-01-01 04:00:00',
               '2016-01-01 04:00:00', '2016-01-01 04:00:00'],
              dtype='datetime64[ns]', freq=None)
```
#### Expected Output

```
DatetimeIndex(['2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 01:00:00', '2016-01-01 01:00:00',
               '2016-01-01 01:00:00', '2016-01-01 01:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 03:00:00', '2016-01-01 03:00:00',
               '2016-01-01 03:00:00', '2016-01-01 03:00:00',
               '2016-01-01 04:00:00', '2016-01-01 04:00:00',
               '2016-01-01 04:00:00', '2016-01-01 04:00:00'],
              dtype='datetime64[ns]', freq=None)
DatetimeIndex(['2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 00:00:00', '2016-01-01 00:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 02:00:00', '2016-01-01 02:00:00',
               '2016-01-01 04:00:00', '2016-01-01 04:00:00',
               '2016-01-01 04:00:00', '2016-01-01 04:00:00'],
              dtype='datetime64[ns]', freq=None)
```
#### output of `pd.show_versions()`

INSTALLED VERSIONS

commit: None
python: 3.5.2.final.0
python-bits: 32
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 61 Stepping 4, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.18.1
nose: None
pip: 8.1.2
setuptools: 23.0.0
Cython: None
numpy: 1.11.0
scipy: 0.17.1
statsmodels: None
xarray: None
IPython: 4.2.0
sphinx: None
patsy: None
dateutil: 2.5.3
pytz: 2016.4
blosc: None
bottleneck: None
tables: None
numexpr: 2.6.1
matplotlib: 1.5.1
openpyxl: 2.3.2
xlrd: 1.0.0
xlwt: None
xlsxwriter: 0.9.2
lxml: 3.6.0
bs4: None
html5lib: None
httplib2: 0.9.2
apiclient: None
sqlalchemy: 1.0.12
pymysql: None
psycopg2: 2.6.2 (dt dec pq3 ext)
jinja2: 2.8
boto: None
pandas_datareader: None
