ERR: DatetimeIndex creation inconsistencies between list and ndarray
Setting invalid freq against ndarray(dtype=int) should raise `ValueError`.

```
import numpy as np
import pandas as pd

pd.DatetimeIndex(np.array([pd.Timestamp('2011-01-01').value, pd.Timestamp('2011-01-03').value]), freq='D')
# ValueError: Inferred frequency None from passed dates does not conform to passed frequency D
```

There seems to be 2 issues:
### 1.  invalid frequency may set if `data` is list

```
pd.DatetimeIndex([pd.Timestamp('2011-01-01').value, pd.Timestamp('2011-01-03').value], freq='D')
# DatetimeIndex(['2011-01-01', '2011-01-03'], dtype='datetime64[ns]', freq='D')
```
### 2. ndarray `data` may raise unclear error message

```
pd.DatetimeIndex(np.array([pd.tslib.iNaT, pd.Timestamp('2011-01-01').value]), freq='D')
# ValueError: NaTType does not support time
```
