PSFMachine

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.

Installation

pip install git+https://github.com/SSDataLab/psfmachine.git

Example use

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.