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Cookbook and random fixes

lightcurver will absolutely fail you a lot. Sorry, astronomical data is just too messy and such is life. Here I will add example situations and how to fix them.

Some of my images were imported, but cannot be plate solved due to low quality

High airmass observations, clouds, tracking problems ... If you have such images and are confident that you will not be able to extract value from them, you can remove them from consideration by flagging them in the database: 

'UPDATE frames SET comment='cannot be plate solved', eliminated = 1 WHERE plate_solved=0;'

I manually plate solved my images after importation, how can I make my pipeline aware of this?

If my plate solving step failed you, and if you managed to add a WCS yourself to the fits files in your frames directory, then you will need to manually run the process storing the footprints in the database and checking that your region of interest is in the frame. Here is how you might do that, with your current directory set to your working directory. 

import os
os.environ['LIGHTCURVER_CONFIG'] = "/path/to/config.yaml"
from pathlib import Path
from astropy.io import fits
from astropy.wcs import WCS

from lightcurver.processes.plate_solving import post_plate_solve_steps
from lightcurver.structure.user_config import get_user_config
from lightcurver.structure.database import execute_sqlite_query
from lightcurver.processes.frame_star_assignment import populate_stars_in_frames

user_config = get_user_config()

solved = Path('frames').glob('*.fits')

for s in solved:
    s = str(s)
    if 'sources.fits' in s:
        # this is a table of sources, skip
        continue
    wcs = WCS(fits.getheader(s))
    if not wcs.is_celestial:
        # this one wasn't solved then
        continue
    frame_id = execute_sqlite_query('select id from frames where image_relpath = ?', 
                                    params=(s,), is_select=True)[0][0]

    try:
       post_plate_solve_steps(frame_path=s, user_config=user_config, frame_id=frame_id)
    except AssertionError:
         # already inserted
        pass

    execute_sqlite_query(query="UPDATE frames SET plate_solved = ? WHERE id = ?",
                         params=(1, frame_id), is_select=False)

# now that we know what our footprints are, populate the table telling us which frame has which star.
populate_stars_in_frames()

The sources were not correctly found by sep, how to re-run that part only after changing the config?

import os
os.environ['LIGHTCURVER_CONFIG'] = "/path/to/config.yaml"

from lightcurver.pipeline.task_wrappers import source_extract_all_images

source_extract_all_images()
You can also pass a list of strings to source_extract_all_images, filtering on the frames table of the database, for instance: 
source_extract_all_images(['plate_solved = 0'])