PRF photometry with Kepler
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.