Lyra analysis

Hi guys,
Here is some code that I've developed for the LYRA team to help in the analysis of LYRA data.  It enables python users to easily access information about artifacts and remove them from data.
The principle new functions are:
(1) extract_lytaf_events() which reads information about instrumental effects etc. from the LYRA Time Annotation database files (LYTAF) into a numpy recarray.  This deprecates get_lytaf_events() which does something similar but only accesses the Pointing and Positioning LYTAF database.  extract_lytaf_events() can access all four LYTAF databases.  I've added a Deprecated warning to get_lytaf_events() and also altered split_series_using_lytaf() so that it uses this new function without changing functionality.
(2) remove_lyra_artifacts() which removes periods corresponding to artifacts listed in the LYTAF files from user input time and irradiance arrays. Exactly which artifacts are to be removed can be controlled by the user.
To help with testing, I've also added some simulated LYTAF database files to sunpy/data/test/

I look forward to your comments and suggestions :)
yep, do this:

```python
columns = lyralc.columns
channels = [np.asanyarray(lyralc.data[col] for col in columns]
```
Then call out to `_remove_lyra_artifacts` then you can reconstruct the dataframe:
```python
data = dict((col, channels[i]) for i, col in enumerate(columns))
```