PRF photometry with Kepler
Check out the documentation. Check out the paper
PSFMachine is an open source Python tool for creating models of instrument effective Point Spread Functions (ePSFs), a.k.a Pixel Response Functions (PRFs). These models are then used to fit a scene in a stack of astronomical images. PSFMachine is able to quickly derive photometry from stacks of Kepler images and separate crowded sources.
pip install psfmachine
Below is an example script that shows how to use PSFMachine. Depending on the speed or your computer fitting this sort of model will probably take ~10 minutes to build 200 light curves. You can speed this up by changing some of the input parameters.
import psfmachine as psf
import lightkurve as lk
tpfs = lk.search_targetpixelfile('Kepler-16', mission='Kepler', quarter=12, radius=1000, limit=200, cadence='long').download_all(quality_bitmask=None)
machine = psf.TPFMachine.from_TPFs(tpfs, n_r_knots=10, n_phi_knots=12)
machine.fit_lightcurves()Funding for this project is provided by NASA ROSES grant number 80NSSC20K0874.