Metadata-Version: 2.1
Name: autoeap
Version: 0.1.0
Summary: Automated version of Extended Aperture Photometry developed for K2 RR Lyrae stars.
Home-page: https://github.com/zabop/autoeap/
Author: Pal Szabo
Author-email: ps738@cam.ac.uk
License: UNKNOWN
Description: [![Image](https://img.shields.io/badge/tutorials-%E2%9C%93-blue.svg)](https://github.com/zabop/autoeap/tree/master/examples)
        [![Image](https://img.shields.io/badge/arXiv-1909.00446-blue.svg)](https://arxiv.org/abs/1909.00446)
        
        # 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](https://ui.adsabs.harvard.edu/abs/2019ApJS..244...32P/abstract).
        A short summary of automatization is published [here](https://ui.adsabs.harvard.edu/abs/2020arXiv200908786P/abstract).
        
        ## Installation
        
        To install the package, use:
        
        ```bash
        pip install git+https://github.com/zabop/autoeap
        ```
        if you fail, try instead:
        ```bash
        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.](https://github.com/zabop/autoeap/blob/master/examples/ktwo212466080-c17_lpd-targ.fits)
        Then, after starting Python, you can do:
        
        ```python
        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:
        
        ```python
        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:
        ```python
        import matplotlib.pyplot as plt
        plt.figure(figsize=(10,5))
        plt.scatter(time,flux,marker='+',c='r')
        plt.show()
        ```
        ![example scatter plot2](https://raw.githubusercontent.com/zabop/autoeap/master/docs/ktwo212466080-c17_raw.png)
        
        The details of the workflow is described in [docs](https://github.com/zabop/autoeap/tree/master/docs).
        
        You can find Google Colab friendly tutorial [in the examples](https://github.com/zabop/autoeap/tree/master/examples).
        
        ### Apply K2 Systematics Correction (K2SC)
        If you want to apply K2SC correction for your freshly made raw-photometry, first you should install [K2SC](https://github.com/OxES/k2sc). AutoEAP is based on that package, so if you find K2SC useful, please cite [Aigrain et al.,2016,MNRAS,459,2408](https://ui.adsabs.harvard.edu/abs/2016MNRAS.459.2408A/abstract).
        
        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:
        ```python
        import autoeap
        time, flux, flux_err = autoeap.createlightcurve(yourtpf,apply_K2SC=True)
        ```
        
        The result is quite delightful:
        ```python
        import matplotlib.pyplot as plt
        plt.figure(figsize=(10,5))
        plt.scatter(time,flux,marker='+',c='r')
        plt.show()
        ```
        ![k2sc result](https://raw.githubusercontent.com/zabop/autoeap/master/docs/ktwo212466080-c17_k2sc.png)
        
        ### 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:
        ```python
        import autoeap
        time, flux, flux_err = autoeap.createlightcurve(yourtpf,remove_spline=True)
        ```
        
        Or do this to remove a spline from the K2SC light curve:
        ```python
        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.](https://keplerscience.arc.nasa.gov/k2-approved-programs.html)
        
        The data we have already created have been uploaded to our [webpage](https://konkoly.hu/KIK/data_en.html).
        
        ## Contributing
        Feel free to open PR / Issue, or contact me [here](https://twitter.com/palszab) or [here](ps738@cam.ac.uk).
        
        ## Citing
        If you find this code useful, please cite [Plachy et al.,2019,ApJS,244,32](https://ui.adsabs.harvard.edu/abs/2019ApJS..244...32P/abstract), 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.
        
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