RAPID

RAPID (Real-time Automated Photometric IDentification) can classify multiband photometric light curves into several different transient classes. It uses a deep recurrent neural network to produce time-varying classifications.

Contents:

• Installation
  • Using pip
  • From Source
  • Dependencies
  • Platforms
• Usage
  • Classify Light curves
  • Train your own classifier with your own data
• Example
• API
  • Classify light curves
  • Plot classifications
  • Train your own classifier
  • Full Documentation

Contribute

• Issue Tracker: https://github.com/daniel-muthukrishna/astrorapid/issues
• Source Code: https://github.com/daniel-muthukrishna/astrorapid

Support

If you are having issues, please let us know by submitting a GitHub issue at https://github.com/daniel-muthukrishna/astrorapid/issues

License

The project is licensed under the MIT license.

Citation

You can cite the following paper for this work: https://ui.adsabs.harvard.edu/abs/2019arXiv190400014M/abstract

Author

Daniel Muthukrishna http://www.danielmuthukrishna.com