Indexing/Slicing tz-aware TimeSeries fails when using datetime
The following code should clarify the problem:

``` python
import pandas
import pytz
index = pandas.date_range(start='2012-12-24 16:00', end='2012-12-24 18:00', freq='H', tz='Europe/Berlin')
ts = pandas.TimeSeries(index=index, data=index.hour)
time_pandas = pandas.Timestamp('2012-12-24 17:00', tz='Europe/Berlin')
time_datetime = datetime.datetime(2012,12,24,17,00, tzinfo=pytz.timezone('Europe/Berlin'))
time_pandas == time_datetime
ts[time_pandas] == ts[time_datetime]
```

While the two time stamps are equal, using them as an index on the TimeSeries results in different values. The same is true for slicing.

When using a tz-aware datetime for indexing/slicing, pandas seems to remove the timezone and interprete the time stamp as UTC.
