Skip to content
The (Exoplanet Detection Identifier) EDI-Vetter is the rock'n roll love child of Terra and RoboVetter, optimized to vet K2 transit signals.
Python Fortran IDL C
Branch: master
Clone or download
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Type Name Latest commit message Commit time
Failed to load latest commit information.


This is a program meant identify false positive transit signal in the K2 data set. This program has been simplified to test single transiting planet signals. Systems with multiple signals require additional testing, which will be made available in a later iteration.


Getting Started

These instructions will get you a copy of the project up and running on your local machine for research, development, and testing purposes. EDI-Vetter was written in Python 3.4


Several python packages are required to run this software. Here are a few: Pandas, Numpy, emcee, scipy, lmfit, batman, astropy

EDI-Vetter currently relies on several features provided by the Terra software package. We have included a copy in this repositories, but remind users to cite appropriately.

Running EDI-Vetter in Python

Here we provide a quick example using the light curve of K2-138.

Begin by opening Python in the appropriate directory.

$ python

Now import the necessary packages

>>> import pandas as pd
>>> import EDI_Vetter

Import the light curve file

>>> lc=pd.read_csv("K2_138.csv")

Now you can set up the EDI-Vetter parameters object with the appropriate transit signal parameters

>>> params=EDI_Vetter.parameters(per=8.26144,  t0=2907.6451,  radRatio=0.0349,  tdur=0.128,  lc=lc)

It is essential that EDI-Vetter re-fits the light curve to measure changes from the transit detection.

>>> params=EDI_Vetter.MCfit(params)

Now you can run all of the vetting metrics on the signal

>>> params=EDI_Vetter.Go(params,delta_mag=10,delta_dist=1000, photoAp=41)
You can’t perform that action at this time.