DatetimeIndex with a frequency greater than dates range now returns only one value
There's a different behavior between 0.16.0 and 0.17.0 on a DatetimeIndex creation with a frequency greater than the dates range:

``` python
import pandas as pd
pd.DatetimeIndex(start=pd.Timestamp('2015-04-15'), end=pd.Timestamp('2015-04-18'), freq='7D')
```

With previous versions I had a DatetimeIndex of length 2: `[2015-04-15, 2015-04-22]`.

With 0.17.0 I get an index with only one value: `['2015-04-15']`.

Is it a bug/regression? Is there a way to reproduce the previous behavior?

Here are the the results of `pd.show_versions()`:
- 0.16.0

```
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.10.final.0
python-bits: 32
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 60 Stepping 3, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.16.0
nose: 1.3.7
Cython: 0.23.4
numpy: 1.10.1
scipy: 0.16.0
statsmodels: 0.6.1
IPython: 4.0.0
sphinx: 1.3.1
patsy: 0.4.0
dateutil: 2.4.1
pytz: 2015.7
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.4.4
matplotlib: 1.4.3
openpyxl: 2.2.6
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.7.7
lxml: 3.4.4
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.9
pymysql: None
psycopg2: None
```
- 0.17.0

```
INSTALLED VERSIONS
------------------
commit: None
python: 2.7.10.final.0
python-bits: 32
OS: Windows
OS-release: 7
machine: AMD64
processor: Intel64 Family 6 Model 58 Stepping 9, GenuineIntel
byteorder: little
LC_ALL: None
LANG: None

pandas: 0.17.0
nose: 1.3.7
pip: 7.1.2
setuptools: 18.4
Cython: 0.23.4
numpy: 1.10.1
scipy: 0.16.0
statsmodels: 0.6.1
IPython: 4.0.0
sphinx: 1.3.1
patsy: 0.4.0
dateutil: 2.4.1
pytz: 2015.7
blosc: None
bottleneck: 1.0.0
tables: 3.2.2
numexpr: 2.4.4
matplotlib: 1.4.3
openpyxl: 2.2.6
xlrd: 0.9.4
xlwt: 1.0.0
xlsxwriter: 0.7.7
lxml: 3.4.4
bs4: 4.4.1
html5lib: None
httplib2: None
apiclient: None
sqlalchemy: 1.0.9
pymysql: None
psycopg2: None
```
