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Gammapy-based pipeline for easy joint analysis of different gamma-ray datasets

Project description

asgardpy Build Status codecov DOI PyPI OpenSSF Best Practices gammapy astropy

Analysis Software for GAmma-Ray Data in Python

'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 v1.1 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

Pipeline development

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.

Examples with Data

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 v1.1 Introduction and then run the scripts/download_asgardpy_data.sh script to add separate Fermi-LAT dataset for the usecase of the pipeline.

Examples of usage of asgardpy is shown in jupyter notebooks in notebooks/.

Cite

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 Template

Pipeline generated based on the template by python-package-template with additional standards being followed -

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