Project containing the first steps on the TDE early photometric classification to be used within FINK, for ZTF and LSST data.

Git clone this directory Create virtual environment, and activate it. For instance:

conda create --name tdes python=3.10
conda activate tdes

In order to use the Rainbow fitting, we need to install the light-curve-python package, for which we previously need to install rust, with the following command:

curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh

Then, we can clone and pip install the light-curve-python package:

python3 -mpip install 'light-curve[full]'

Then, simply install this project with

pip install -e .

First, update the config.py file to match your preference. You need to update the paths.

The features can be extracted using the extract_features.py script, where you can manually specify on which data you want to perform the feature extraction. The script merge_csvs.py provides can be used to put all the extracted features in the same csv.

Then, you can use the python script in the anomaly detection folder, in order to run the SNAD_AAD method on the extracted features.