dave-vkostov 2.1

DISCOVERY AND VETTING of EXOPLANETS

dave™

Discovery And Vetting of Exoplanets™

Summary

This repository implements a pipeline to find and vet planets planets using data from NASA K2 and TESS missions.

The pipeline performs the following steps:

1. Create a subset of targets for testing
2. Light Curve Genertion/CoTrend -- remove instrumental effects e.g. PDC light curves Dan Foreman-Mackey's method
3. Detrend/Search for planets -- BLS
4. Fitting a planetary model
5. Produce vetting Metrics
6. Output useful data products

Installation and Requirements

Please consider installing DAVE in a new environment (with Python 3.6/3.7, gnuplot installation may be a problem with 3.8) as you'll need to pip install the following packages before proceeding: astropy, metric_learn, sklearn ,pyfits, astroquery, conda install gnuplot (from command line: conda install -c conda-forge gnuplot ), PyGnuplot, parmap, bls, clipboard, lpproj, numba and eleanor. After having installed all the dependencies, please pip install dave-vkostov. Now you only need one last thing: go to the dave directory, open the tessPipeline directory and open the vet_tess_.py script. Here you will see some (3 or 4) lines of code with the path of my machine. Replace them with your path to the dave dir. Thanks for installing.

Example use for TESS

from python:

from dave.tessPipeline import vet_tess_
detrendType = "tess_2min"
clip = vet_tess_.runOneDv(detrendType, 2, 307210830, 1, 3.690613, 1356.2038, 1863, 1.27)
outfile = "tmp.txt"
export_ = vet_tess_.runExport(clip,outfile_)

where input for runOneDv is: Sector, TIC ID, Planet Number, Period, BTJD, Transit Depth [ppm], Transit Duration [hours].

Currently supported "detrendType" are "tess_2min" and "eleanor", where "tess_2min" refers to the SPOC short-cadence data, and "eleanor" refers to eleanor-generated FFI lightcurves