A set of Python notebooks created to demonstrate the use of services provided by HEASARC for high-energy astrophysics.
This repository contains tutorials for finding, accessing, and analyzing high-energy data from a variety of missions, as well as demonstrations of how to explore and access HEASARC-hosted catalogs, and employ various useful high-energy software tools.
Our tutorials are all written as 'markdown notebooks' (with file extension '.md'), an alternative to the standard '.ipynb' files typical of Jupyter and iPython notebooks.
These markdown notebooks can be viewed in the GitHub web interface, but unlike 'ipynb' files they cannot include any of the outputs you get by running the code cells.
As such, the recommended way to view and read the tutorials is to visit the HEASARC Tutorials website.
All demonstrations beyond the development stage are rendered on this website - the outputs of the code cells are shown as they would be in an executed 'ipynb' notebook.
You can also download an executed 'ipynb' version of any demonstration by clicking the download button in the top right corner of the rendered notebook.
An excellent option for you to run these demonstrations and to perform your own analyses (perhaps using the tutorials as a starting point) is to use NASA's new cloud computing platform, the Fornax Initiative.
NASA's astrophysics archives, IRSA, MAST, and HEASARC (us!) have jointly created this new resource, which is designed to enable the next generation of astrophysics research by bringing analyses 'closer' to our observation archives.
The Fornax Science Console is a Jupyter Lab interface (familiar to anyone who has used Jupyter notebooks before) running on Amazon Web Services (AWS). Various levels of computing resources can be requested. Analyses of very large samples (and very large data, such as from the upcoming Roman Observatory) are made more efficient by avoiding the need to download data to your local machine.
HEASARC provides several pre-configured software environments for high-energy data analysis (e.g., Chandra's CIAO package, Fermitools, and XMM's SAS) and more will be added in the future.
We are now accepting beta users, and you can sign up for a free account at the sign-up website.
HEASARC's tutorial notebooks are available on the Fornax Science Console in
the fornax-notebooks/heasarc-tutorials folder, in your home directory.
All these tutorials and demonstrations are stored and developed in this GitHub repository, so you, of course, have the usual GitHub options for getting local copies of the notebooks.
For instance, you could clone the latest version of the entire repository into a new 'resources' directory using these commands:
mkdir -p resource
cd resources
git clone https://github.com/HEASARC/heasarc-tutorials
Alternatively, if you want to download the 'production' versions of the tutorials, both as executed 'ipynb' files and as markdown notebooks, you could use:
mkdir -p resources
cd resources
git clone -b production-notebooks --single-branch https://github.com/HEASARC/heasarc-tutorials
A guide for the best ways to run these notebooks locally is coming soon!
This repository is maintained to help make the identification and use of high-energy observations more accessible to the astrophysics community, and we welcome any feedback on or contributions to this set of notebooks.
If you wish to create a new Jupyter notebook, please use the 'notebook_template.md' file as a starting point - any notebooks that do not follow this template when a pull request is submitted will need to be edited.
We also encourage the submission of any Jupyter notebooks from recent publications that you think are a good example of high-energy astrophysics analysis in a Python environment.
Please open an issue that briefly explains what your notebook does, why you think it should be included in this repository, and what the software requirements are, as well as attaching the notebook file. We may then decide to convert your notebook to the standard described by the template and include it in this resource.