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timothydmorton / VESPA

Validation of Exoplanet Signals using a Probabilistic Algorithm--- calculating false positive probabilities for transit signals
MIT License
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Note: Current recommendation is to retire VESPA in favor of TRICERATOPS (https://github.com/stevengiacalone/triceratops); see research note posted at https://iopscience.iop.org/article/10.3847/2515-5172/acd9a6 for more details.

VESPA

.. image:: https://travis-ci.com/timothydmorton/VESPA.svg?branch=master :target: https://travis-ci.com/timothydmorton/VESPA

Validation of Exoplanet Signals using a Probabilistic Algorithm--- calculating false positive probabilities for transit signals

For usage and more info, check out the documentation <http://vespa.rtfd.org>_.

Installation

To install, you can get the most recently released version from PyPI::

pip install vespa [--user]

Or you can clone the repository::

git clone https://github.com/timothydmorton/vespa.git
cd vespa
python setup.py install [--user]

The --user argument may be necessary if you don't have root privileges.

Depends on typical scientific packages (e.g. numpy, scipy, pandas), as well as isochrones <http://github.com/timothydmorton/isochrones>, and (in several corners of the code), another package of mine called simpledist <http://github.com/timothydmorton/simpledist>. All dependencies should get resolved upon install, though this has only been tested under the anaconda Python distribution, which has all the scientific stuff already well-organized.

For best results, it is also recommended to have MultiNest and pymultinest installed. Without this, emcee will be used for stellar modeling, but the MulitNest results are a bit more trustworthy given the often multi-modal nature of stellar model fitting.

Basic Usage

The simplest way to run an FPP calculation straight out of the box is as follows.

  1. Make a text file containing the transit photometry in three columns: t_from_midtransit [days], flux [relative, where out-of-transit is normalized to unity], and flux_err. The file should not have a header row (no titles); and can be either whitespace or comma-delimited (will be ingested by np.loadtxt).

  2. Make a star.ini file that contains the observed properties of the target star (photometric and/or spectroscopic, whatever is available)::

    #provide spectroscopic properties if available
    #Teff = 3503, 80  #value, uncertainty
    #feh = 0.09, 0.09
    #logg = 4.89, 0.1

#observed magnitudes of target star
# If uncertainty provided, will be used to fit StarModel
    J = 9.763, 0.03
    H = 9.135, 0.03
    K = 8.899, 0.02
    Kepler = 12.473

  3. Make a fpp.ini file containing the following information::

        name = k2oi #anything
    ra = 11:30:14.510 #can be decimal form too
    dec = +07:35:18.21

    period = 32.988 #days
    rprs = 0.0534   #Rp/Rstar best estimate
    photfile = lc_k2oi.csv #contains transit photometry

[constraints]
maxrad = 12  # aperture radius [arcsec]
secthresh = 1e-4 # Maximum allowed depth of potential secondary eclipse

  4. Run the following from the command line (from within the same folder that has star.ini and fpp.ini)::

    $ calcfpp

Or, if you put the files in a folder called mycandidate, then you can run calcfpp mycandidate::

This will run the calculation for you, creating result files, diagnostic plots, etc. It should take 20-30 minutes. If you want to do a shorter version to test, you can try calcfpp -n 1000 (the default is 20000). The first time you run it though, about half the time is doing the stellar modeling, so it will still take a few minutes.

Attribution

If you use this code, please cite both the paper and the code.

Paper citation::

@ARTICLE{2012ApJ...761....6M,
author = {{Morton}, T.~D.},
title = "{An Efficient Automated Validation Procedure for Exoplanet Transit Candidates}",
journal = {\apj},
archivePrefix = "arXiv",
eprint = {1206.1568},
primaryClass = "astro-ph.EP",
keywords = {planetary systems, stars: statistics },
year = 2012,
month = dec,
volume = 761,
eid = {6},
pages = {6},
doi = {10.1088/0004-637X/761/1/6},
adsurl = {http://adsabs.harvard.edu/abs/2012ApJ...761....6M},
adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

code::

@MISC{2015ascl.soft03011M,
   author = {{Morton}, T.~D.},
    title = "{VESPA: False positive probabilities calculator}",
howpublished = {Astrophysics Source Code Library},
     year = 2015,
    month = mar,
archivePrefix = "ascl",
   eprint = {1503.011},
   adsurl = {http://adsabs.harvard.edu/abs/2015ascl.soft03011M},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}