semvec/pypi-packages huggingface dataset:
vetting 0.3.1
Simple, stand-alone vetting tools for transiting signals in Keper, K2 and TESS data
License: MIT
Requires Python: <4.0,>=3.7
Keywords: NASA, Kepler, K2, TESS, Astronomy

# vetting

**`vetting` contains simple, stand-alone Python tools for vetting transiting signals in NASA's Kepler, K2 and TESS data. `vetting` requires an installation of Python 3.8 or higher.**

[![pypi](https://img.shields.io/pypi/v/vetting)](https://pypi.org/project/vetting/)
![pytest](https://github.com/ssdatalab/vetting/workflows/pytest/badge.svg)
[![paper](https://img.shields.io/badge/RNAAS-read%20the%20paper-blue)](https://iopscience.iop.org/article/10.3847/2515-5172/ac376a)

## Installation

You can install `vetting` by executing the following in a terminal

```
pip install vetting
```

### Centroid testing

An example of a simple test is shown below.

![Example of simple centroid test](https://github.com/SSDataLab/vetting/raw/main/demo.png)

Here a significant offset is detected in the centroid of false positive KOI-608 during transit. The p-value for the points during transit being drawn from the same distribution as the points out of transit is low, (there is a less than 1% chance these are drawn from the same distribution). To recreate this example you can use the following script:

```python
import lightkurve as lk
from vetting import centroid_test

tpf = lk.search_targetpixelfile('KOI-608', mission='Kepler', quarter=10).download()
period, t0, dur = 25.3368592, 192.91552, 8.85/24
r = centroid_test(tpf, period, t0, dur, aperture_mask='pipeline', plot=False)
```