Photometric Classification of Astronomical Transients and Variables With Biased Spectroscopic Samples
Avocado is a general photometric classification code that is designed to produce classifications of arbitrary astronomical transients and variable objects. This code is designed from the ground up to address the problem of biased spectroscopic samples. It does so by generating many lightcurves from each object in the original spectroscopic sample at a variety of redshifts and with many different observing conditions. The "augmented" samples of lightcurves that are generated are much more representative of the full datasets than the original spectroscopic samples.
The original codebase of avocado was developed for and won the 2018 Kaggle PLAsTiCC challenge. A description of the algorithms used for this challenge can be found on the kaggle forum. This analysis can be replicated using the latest version of avocado following the steps in the documentation.
Instructions on how to install and use avocado can be found on the avocado readthedocs page.
