# 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)
```
Raw data
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"description": "# vetting\n\n**`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.**\n\n[![pypi](https://img.shields.io/pypi/v/vetting)](https://pypi.org/project/vetting/)\n![pytest](https://github.com/ssdatalab/vetting/workflows/pytest/badge.svg)\n[![paper](https://img.shields.io/badge/RNAAS-read%20the%20paper-blue)](https://iopscience.iop.org/article/10.3847/2515-5172/ac376a)\n\n## Installation\n\nYou can install `vetting` by executing the following in a terminal\n\n```\npip install vetting\n```\n\n### Centroid testing\n\nAn example of a simple test is shown below.\n\n![Example of simple centroid test](https://github.com/SSDataLab/vetting/raw/main/demo.png)\n\nHere 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:\n\n```python\nimport lightkurve as lk\nfrom vetting import centroid_test\n\ntpf = lk.search_targetpixelfile('KOI-608', mission='Kepler', quarter=10).download()\nperiod, t0, dur = 25.3368592, 192.91552, 8.85/24\nr = centroid_test(tpf, period, t0, dur, aperture_mask='pipeline', plot=False)\n```\n",
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