This repository contains code allowing reproducibility of results presented in Leoni et al., 2022, Astronomy & Astrophysics, Volume 663, id.A13, 10 pp.
We list below a general description of each script/notebook.
The data necessary to reproduce these results are available through zenodo.
-
actsnfink/sigmoid.py: functions related to the sigmoid feature extraction
-
actsnfink/classifier_sigmoid.py: functions related to filtering points on the rise and concatenation with extra features (SNR, npoints, chi2) with sigmoid fit parameters
-
actsnfink/early_sn_classifier.py: global functions for feature extraction and learning loop.
-
actsnfink/notebooks/mean_model.ipynb: Extract best performing model from a given query strategy, save pkl file and generate list of alerts used of training.
-
actsnfink/notebooks/0X with X \in [1,2,3,4,5,7]: Jupyter notebooks for reproducing the plots in Leoni et al., 2022
-
actsnfink/scripts/run_loop.py Example script on how to use this package.
-
LICENSE: MIT License
Create a virtual environment following these instructions. Source it and install the actsnclass package.
Then you can install the other dependencies using pip:
python3 -m pip install -r requirements.txt
Then you can install the functionalities of this package.
python setup.py install