'User-friendly' configuration-centred pipeline built over Gammapy to allow for easy simultaneous analysis of various datasets of different formats.
Example: 3D Fermi-LAT (with various source models in the Region of Interest stored in XML file) + 1D energy-dependent directional cuts MAGIC/LST [PointSkyRegion geometry for ON region] + 1D global directional cut VERITAS [CircleSkyRegion geometry for ON region].
Follow the documentation at https://asgardpy.readthedocs.io/en/latest/ for the main functionality of this pipeline. Follow the Gammapy v1.2 documentation for understanding the core Gammapy objects.
The various Data Levels used here follow the descriptions suggested by GADF v0.3 and CTAO Data Model.
For requiring support only for Gammapy v1.1, one may follow the latest Hotfix release v0.4.4 which benefits from the correct usage of getting EBL-deabsorbed data products as included in v0.5.0. This can be done by using
git fetch --tags
git switch -c tags/v0.4.4
For creating a conda environment, for this Hotfix release, one can use
conda env create -f environment_0.4.4.yml
and in general, for the latest release,
conda env create -f environment.yml
This method was included after v0.5.0, and for earlier (<v0.4.4) releases, one can simply use the gammapy conda environment and install asgardpy on top of it.
The pipeline was developed with first testing with Fermi-LAT (enrico and fermipy) files and LST-1 (cta-lstchain) DL3 files (with energy-dependent and global directional cuts) for point-like sources. The pipeline can be further expanded to support more types of DL3 files of gamma-ray instruments.
An example of configuration file that can be used with asgardpy can be found at asgardpy/config/template.yaml
For working with some public data to check the pipeline functionality, one should first download the public dataset available with Gammapy as indicated in Gammapy v1.2 Introduction and then run the scripts/download_asgardpy_data.sh script to add datasets for the full usage of the pipeline.
Examples of usage of Asgardpy is shown in jupyter notebooks.
If you use Asgardpy in a publication, please cite the exact version you used from Zenodo Cite as https://doi.org/10.5281/zenodo.8106369
Pipeline generated based on the template by python-package-template with additional standards being followed -
FAQs
Gammapy-based pipeline for easy joint analysis of different gamma-ray datasets
We found that asgardpy demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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