https://github.com/rndev2017/exoboost

Using radial velocity data to identify exoplanet companions
https://github.com/rndev2017/exoboost

ai astronomy astrophysics astropy boosted-trees classification classifier-model exoplanet-data exoplanets machine-learning ml nasa python radial-velocity-data science xgboost

Last synced: about 1 year ago
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Using radial velocity data to identify exoplanet companions

• Host: GitHub
• URL: https://github.com/rndev2017/exoboost
• Owner: rndev2017
• License: mit
• Created: 2019-10-26T23:03:09.000Z (over 6 years ago)
• Default Branch: master
• Last Pushed: 2023-03-06T14:03:04.000Z (about 3 years ago)
• Last Synced: 2024-01-29T04:39:46.244Z (about 2 years ago)
• Topics: ai, astronomy, astrophysics, astropy, boosted-trees, classification, classifier-model, exoplanet-data, exoplanets, machine-learning, ml, nasa, python, radial-velocity-data, science, xgboost
• Language: Python
• Homepage:
• Size: 21.5 MB
• Stars: 3
• Watchers: 1
• Forks: 0
• Open Issues: 9
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# ExoBoost

[![made-with-python](https://img.shields.io/badge/Made%20with-Python-1f425f.svg)](https://www.python.org/)

[![Maintenance](https://img.shields.io/badge/Maintained%3F-no-red.svg)](https://github.com/rndev2017/ExoBoost/graphs/commit-activity)

![astropy](http://img.shields.io/badge/powered%20by-AstroPy-orange.svg?style=flat)

[![nasa](https://img.shields.io/badge/powered%20by-NASA%20Exoplanet%20Archive-blue)](https://exoplanetarchive.ipac.caltech.edu/)


Using existing radial velocity data to identify exoplanet companions with XGBoost 


### Code Author

Rohan S. Nagavardhan: [@rndev2017](https://github.com/rndev2017) 


### Directories

[src/](https://github.com/rndev2017/ExoBoost/tree/master/src)

- contains the XGBoost Classifier

- contains the script used to label my data set

- contains the `Star` class

    - plot Radial Velocity Plots

    - plot phased Radial Velocity Plots

    - plot periodograms

    - fit phased radial velocity curves

[plots/](https://github.com/rndev2017/ExoBoost/tree/master/plots)

- contains images that are relavent to the model

- contains images that are relavent to the exoplanet data

[sim/](https://github.com/rndev2017/ExoBoost/tree/master/sim)

- contains code for creating synthetic radial velocity data

[data/](https://github.com/rndev2017/ExoBoost/tree/master/data)

- contains the data used to train the XGBoost Classifier

- formatted in `.csv` format

## Dependencies

- XGBoost ([instructions](https://xgboost.readthedocs.io/en/latest/build.html#python-package-installation))

- Pandas ([instructions](https://pandas.pydata.org/pandas-docs/stable/install.html))

- NumPy ([instructions](https://scipy.org/install.html))

- SciPy ([instructions](https://scipy.org/install.html))

- Astropy ([instructions](https://www.astropy.org/))

- Matplotlib ([instructions](https://matplotlib.org/users/installing.html))

- Scikit-Learn - ([instructions](https://scikit-learn.org/stable/install.html))

- Seaborn - ([instructions](https://seaborn.pydata.org/installing.html))

- Astroquery - ([instructions](https://astroquery.readthedocs.io/en/latest/#installation))

# Future Plans

I have been given the oppurtunity to present this work at [LISEF](https://www.lisef.org/) and various science research fairs in the near future as part of my science research class. Additionally, I am considering submitting this work to a journal for publication. As for the project itself, I will be working on improving the model by creating a simulated dataset to add to the existing dataset of real exoplanet data. Furthermore, I am thinking about using a transfer learning approach by repurposing [AstroNet](https://github.com/google-research/exoplanet-ml) for exoplanet companion identification with radial velocity. Keep following this directory for updates on this project.