A package of utilities for reading, and applying image processing to Cherenkov Telescope Array (CTA) R0/R1/DL0/DL1 data in a standardized format. Created primarily for testing machine learning image analysis techniques on IACT data.
Currently supports ctapipe v6.0.0 data format.
Previously named image-extractor (v0.1.0 - v0.6.0). Currently under development, intended for internal use only.
The following installation method (for Linux) is recommended:
To install dl1-data-handler as a conda package, first install Anaconda by following the instructions here: https://www.anaconda.com/distribution/.
The following command will set up a conda virtual environment, add the necessary package channels, and install dl1-data-handler specified version and its dependencies:
DL1DH_VER=0.12.0
wget https://raw.githubusercontent.com/cta-observatory/dl1-data-handler/v$DL1DH_VER/environment.yml
conda env create -n [ENVIRONMENT_NAME] -f environment.yml
conda activate [ENVIRONMENT_NAME]
conda install -c ctlearn-project dl1_data_handler=$DL1DH_VERThis 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).
The main dependencies are:
- PyTables >= 3.8
- NumPy >= 1.20.0
- ctapipe == 0.21.2
Also see setup.py.
The ImageMapper class transforms the hexagonal input pixels into a 2D Cartesian output image. The basic usage is demonstrated in the ImageMapper tutorial. It requires ctapipe-extra outside of the dl1-data-handler. See this publication for a detailed description: arXiv:1912.09898
- Cherenkov Telescope Array (CTA) - Homepage of the CTA Observatory
- CTLearn and GammaLearn - Repository of code for studies on applying deep learning to IACT analysis tasks. Maintained by groups at Columbia University, Universidad Complutense de Madrid, Barnard College (CTLearn) and LAPP (GammaLearn).
- ctapipe - Official documentation for the ctapipe analysis package (in development)