First, CTLearn installation is required. Installation can be carried out from source:

CTLEARN_VER=0.6.0
git clone https://github.com/ctlearn-project/ctlearn
cd ctlearn
conda env create -f environment-gpu.yml
conda activate ctlearn
pip install ctlearn==$CTLEARN_VER

Or simply:

CTLEARN_VER=0.6.0
mode=gpu
wget https://raw.githubusercontent.com/ctlearn-project/ctlearn/v$CTLEARN_VER/environment-$mode.yml
conda env create -n [ENVIRONMENT_NAME] -f environment-$mode.yml
conda activate [ENVIRONMENT_NAME]
pip install ctlearn==$CTLEARN_VER
ctlearn -h

Additionally, the following installation is necessary:

1. pip install tensorflow-addons
2. pip install --upgrade matplotlib
3. pip install wandb (afterwards run wandb login and log in)

First, update GANs.yml (and predictor.yml if no predefined model is used as a predictor). Possible labels are 'particletype', 'energy' and 'direction'. To train the models, simply run main.py and introduce the path to GANs.yml.