Low-level data processing pipeline software for CTA (the Cherenkov Telescope Array)
This is code is a prototype data processing framework and is under rapid development. It is not recommended for production use unless you are an expert or developer!
- Code: https://github.com/cta-observatory/ctapipe
- Docs: https://ctapipe.readthedocs.io/
- Slack: Contact Karl Kosack for invite
If you use this software for a publication, please cite the Zenodo Record for the specific version you are using and our latest publication.
You can find all ctapipe Zenodo records here: List of ctapipe Records on Zenodo.
There is also a Zenodo DOI always pointing to the latest version: 
At this point, our latest publication is the 2021 ICRS proceeding, which you can cite using this bibtex entry:
@inproceedings{ctapipe-icrc-2021,
author = {Nöthe, Maximilian and Kosack, Karl and Nickel, Lukas and Peresano, Michele},
title = {Prototype Open Event Reconstruction Pipeline for the Cherenkov Telescope Array},
doi = {10.22323/1.395.0744},
booktitle = {Proceedings, 37th International Cosmic Ray Conference},
year=2021,
volume={395},
number={744},
location={Berlin, Germany},
}
ctapipe and its dependencies may be installed using the Anaconda or Miniconda package system. We recommend creating a conda virtual environment first, to isolate the installed version and dependencies from your master environment (this is optional).
The following command will set up a conda virtual environment, add the necessary package channels, and install ctapipe specified version and its dependencies:
CTAPIPE_VER=0.17.0 wget https://raw.githubusercontent.com/cta-observatory/ctapipe/v$CTAPIPE_VER/environment.yml conda env create -n cta -f environment.yml conda activate cta conda install -c conda-forge ctapipe=$CTAPIPE_VER
Note: this environment contains many useful packages that are not strictly requirements of ctapipe.
To get only ctapipe and its direct dependencies, just do conda install -c conda-forge ctapipe[=<version>] in an environment
of your choice.
Note: If you encounter long Solving environment times with conda, try using mamba (https://github.com/mamba-org/mamba) instead.
The file environment.yml can be found in this repo. Note this is pre-alpha software and is not yet stable enough for end-users (expect large API changes until the first stable 1.0 release).
Developers should follow the development install instructions found in the documentation.