autoeap 0.1.0

Automated version of Extended Aperture Photometry developed for K2 RR Lyrae stars.

autoEAP - Automated Extended Aperture Photometry, developed for high amplitude K2 variable stars

The details of Extended Aperture Photometry are published in Plachy et al.,2019,ApJS,244,32. A short summary of automatization is published here.

Installation

To install the package, use:

pip install git+https://github.com/zabop/autoeap

if you fail, try instead:

git clone https://github.com/zabop/autoeap
cd autoeap
python  setup.py install

Example usage

To create your own photomery, you'll need a Target Pixel File, such as this one. Then, after starting Python, you can do:

yourtpf = '/path/to/your/tpf/ktwo212466080-c17_lpd-targ.fits'
import autoeap
time, flux, flux_err = autoeap.createlightcurve(yourtpf)

Or if you want to let autoEAP download the TPF from MAST database, you can just provide a target name and a campaign number:

import autoeap
targetID = 'EPIC 212466080'
campaign = 17
time, flux, flux_err = autoeap.createlightcurve(targetID,campaign=campaign)

With this last line, you can create autoEAP photometry for any K2 variable star.

Plotting our results gives:

import matplotlib.pyplot as plt
plt.figure(figsize=(10,5))
plt.scatter(time,flux,marker='+',c='r')
plt.show()

The details of the workflow is described in docs.

You can find Google Colab friendly tutorial in the examples.

Apply K2 Systematics Correction (K2SC)

If you want to apply K2SC correction for your freshly made raw-photometry, first you should install K2SC. AutoEAP is based on that package, so if you find K2SC useful, please cite Aigrain et al.,2016,MNRAS,459,2408.

Installation:

git clone https://github.com/OxES/k2sc.git
cd k2sc
python setup.py install --user

And then without much hassle, you can use in python:

import autoeap
time, flux, flux_err = autoeap.createlightcurve(yourtpf,apply_K2SC=True)

The result is quite delightful:

import matplotlib.pyplot as plt
plt.figure(figsize=(10,5))
plt.scatter(time,flux,marker='+',c='r')
plt.show()

Apply spline correction

We have also built-in a method to remove trends using low-order splines. Just do to correct the raw light curve:

import autoeap
time, flux, flux_err = autoeap.createlightcurve(yourtpf,remove_spline=True)

Or do this to remove a spline from the K2SC light curve:

import autoeap
time, flux, flux_err = autoeap.createlightcurve(yourtpf,apply_K2SC=True,remove_spline=True)

Available options

• apply_K2SC If True, after the raw photomery, K2SC will be applied to remove systematics from the extracted light curve.
• remove_spline If True, after the raw photomery, a low-order spline will be fitted and removed from the extracted light curve. If apply_K2SC is also True, then this step will be done after the K2SC.
• save_lc If True, the final light curve will be save as a file.
• campaign If local TPF file is not found, it will be downloaded from MAST, but campaign number should be defined as well, if the target has been observed in more than one campaign.
• TH Threshold to segment each target in each TPF candence. Only used if targets cannot be separated normally. Default is 8.
• show_plots If True, all the plots will be displayed.
• save_plots If True, all the plots will be saved to a subdirectory.
• window_length The length of filter window for spline correction given in days. Applies only if remove_spline is True. Default is 20 days.

Data Access

We provide photometry for targets for the following Guest Observation Programs: GO12111,GO8037,GO13111,GO14058,GO6082,GO16058,GO18033,GO10037,GO15058,GO17033.

Slightly less than 2000 RRLs. See: K2 approved targets & programs.

The data we have already created have been uploaded to our webpage.

Contributing

Feel free to open PR / Issue, or contact me here or here.

Citing

If you find this code useful, please cite Plachy et al.,2019,ApJS,244,32, until the new paper is not ready. Here is the BibTeX source:

@ARTICLE{2019ApJS..244...32P,
       author = {{Plachy}, Emese and {Moln{\'a}r}, L{\'a}szl{\'o} and {B{\'o}di}, Attila and {Skarka}, Marek and {Szab{\'o}}, P{\'a}l and {Szab{\'o}}, R{\'o}bert and {Klagyivik}, P{\'e}ter and {S{\'o}dor}, {\'A}d{\'a}m and {Pope}, Benjamin J.~S.},
        title = "{Extended Aperture Photometry of K2 RR Lyrae stars}",
      journal = {\apjs},
     keywords = {RR Lyrae variable stars: 1410, Light curves (918, Space telescopes (1547, 1410, 918, 1547, Astrophysics - Instrumentation and Methods for Astrophysics, Astrophysics - Solar and Stellar Astrophysics},
         year = 2019,
        month = oct,
       volume = {244},
       number = {2},
          eid = {32},
        pages = {32},
          doi = {10.3847/1538-4365/ab4132},
archivePrefix = {arXiv},
       eprint = {1909.00446},
 primaryClass = {astro-ph.IM},
       adsurl = {https://ui.adsabs.harvard.edu/abs/2019ApJS..244...32P},
      adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

Acknowledgements

This project was made possible by the funding provided by the National Research, Development and Innovation Office of Hungary, funding granted under project 2018-2.1.7-UK_GYAK-2019-00009 and by the Lendület Program of the Hungarian Academy of Sciences, project No LP2018-7/2019.