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CTLearn: Deep Learning for IACT Event Reconstruction

DOI Latest Release Continuos Integration CTLearn Logo

CTLearn is a package under active development to run deep learning models to analyze data from all major current and future arrays of imaging atmospheric Cherenkov telescopes (IACTs). CTLearn can load DL1 data from CTA (Cherenkov Telescope Array), FACT, H.E.S.S., MAGIC, and VERITAS telescopes processed by ctapipe or DL1DataHandler.

Installation for users

Download and install Anaconda, or, for a minimal installation, Miniconda.

The following command will set up a conda virtual environment, add the necessary package channels, and install CTLearn specified version and its dependencies:

conda env create -n [ENVIRONMENT_NAME] -f environment.yml
conda activate [ENVIRONMENT_NAME]
pip install ctlearn==$CTLEARN_VER
ctlearn -h

This should automatically install all dependencies (NOTE: this may take some time, as by default MKL is included as a dependency of NumPy and it is very large).

See the documentation for further information like installation instructions for developers, package usage, and dependencies among other topics.

Citing this software

Please cite the corresponding version using the DOIs below if this software package is used to produce results for any publication:

  • 0.7.0 : zendoi070


Ari Brill Bryan Kim Tjark Miener Daniel Nieto
Ari Brill Bryan Kim Tjark Miener Daniel Nieto


Qi Feng Ruben Lopez-Coto
Qi Feng Ruben Lopez-Coto


Jaime Sevilla Héctor Rueda Juan Redondo Pizarro LucaRomanato Sahil Yadav Sergio García Heredia
Jaime Sevilla Héctor Rueda Juan Redondo Pizarro Luca Romanato Sahil Yadav Sergio García Heredia