CTLearn: Deep Learning for IACT Event Reconstruction
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 R1/DL0/DL1 data from CTAO (Cherenkov Telescope Array Observatory), FACT, H.E.S.S., LST-1, MAGIC, and VERITAS telescopes reduced by ctapipe and processed by DL1DataHandler.
Code, feature requests, bug reports, pull requests: https://github.com/ctlearn-project/ctlearn
Documentation: https://ctlearn.readthedocs.io
License: BSD-3
Installation for users
Installation
First, create and activate a fresh conda environment:
mamba create -n ctlearn -c conda-forge python==3.12 llvmlite
conda activate ctlearnThe lastest version fo this package can be installed as a pip package:
pip install ctlearnSee the documentation for further information like installation instructions for the IT-cluster, installation instructions for developers, package usage, and dependencies among other topics.
Citing this software
Please cite the corresponding version using the DOIs from Zenodo if this software package is used to produce results for any publication.
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Release files for CTLearn 0.10.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| ctlearn-0.10.4.tar.gz | 1.2 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| ctlearn-0.10.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.2 MB
Release files / ctlearn-0.10.4.tar.gz
| Download URL | ctlearn-0.10.4.tar.gz |
|---|---|
| Size | 1.2 MB |
| Tags | Source |
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| Size | 82.5 kB |
| Tags | Python 3 |
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