[WIP] Adding functionality to read fits files into dictionaries.

[christinahedges]

The fits products downloaded by lksearch have various formats and units. We are building a more generic framework to hold and work with data like this.

To interface between the fits files and the new framework, we need a standard way to turn fits files into python objects we can parse.

I'm opening this WIP to show how I think we could do this. The function get_data_from_hdulist will:

• Open any fits file
• Store the header information as a dictionary
• Store the column/data information as a dictionary
• Store the WCS information as a dictionary
• Resolve conflicting information by trusting the first data extension if there are any duplicate columns or header keywords with conflicting information
• Optionally will store the data with the correct units.

The idea is that this converts any input fits file from the myriad TESS/Kepler/K2 data products (e.g. SPOC, TESS-SPOC, QLP, Eleanor, K2SFF, Everest, TESS-Cut) into something fairly easy to parse.

This does not do any of the checking to see if e.g. there is a flux column or to select which should be the "default" flux column in the event that there is more than one with different names.

This isn't designed to be merged [yet]. This might not be the final home for this functionality.

from lksearch.io import get_data_from_fits_file
from lksearch import KeplerSearch
sr = KeplerSearch('KIC 8462852')
path = sr.timeseries[0].download(quiet=True).loc[0, 'Local Path']
cards, cols, wcs = get_data_from_fits_file(path, units=False)