/astropy-workshop

Materials for Astropy Workshops

Primary LanguageJupyter NotebookBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

Python and Astropy for Astronomical Data Analysis

Workshop at the 245th Meeting of the AAS in National Harbor, MD, USA

  • DATE: TBD
  • TIME: TBD
  • LOCATION: TBD

PRE-WORKSHOP SETUP

Please be sure your laptop is properly configured before the workshop by following the installation and setup instructions.

Warning: Installation and setup could take as long as one hour depending on your current configuration and internet speeds. DO NOT WAIT UNTIL THE DAY OF THE WORKSHOP.

If you have any trouble, we will have facilitators on-site as early as 8:30 AM local time who can help you in person.

As an alternative, a workshop session can be run on mybinder.org via this link: Binder

Schedule

Time (PT) Topic Presenter/Instructor
9:00 - 9:10am Install and config help, if needed Brett Morris (@bmorris3)
9:10 - 9:20am Intro to Astropy and Code of Conduct Kelle Cruz (@kelle)
9:20 - 9:45am Astropy Units, Quantities, and Constants
9:45 - 10:15am Intro to Object Oriented Programming (OOP)
10:15 - 10:30am BREAK
10:30 - 11:00am Coordinates
11:00 - 11:30pm Astropy Tables
11:30 – 12:00pm I/O: FITS and ASCII
12:00 - 1:30pm LUNCH
1:30 - 2:00pm Specutils
2:00 - 2:30pm Photutils
2:30 - 3:00pm BREAK
3:00 - 3:20pm Explore together time
3:20 - 3:40pm Uncertainty
3:40 - 4:00pm Astropy Communities & Contributing to Astropy
4:00 - 5:30pm Explore together time

Additional Helpers

TBD

Description

This workshop covers the use of Python tools for astronomical data analysis and visualization, with the focus primarily on UV, Optical, and IR data. Data analysis tools for JWST are being written in Python and distributed as part of Astropy, a community developed Python library for astronomy, and its affiliated packages.

The workshop goals introduce you to the variety of tools which are already available inside the Astropy library as well as provide ample hands-on time during which you’ll be able to explore the science analysis capabilities which the greater Python environment and community provide.

We plan on accomplishing this with brief overview talks on the main tools followed by extended instructor guided tutorials where you’ll be able to try them out for yourself and ask questions in the company of expert users and developers.

Some basic Python experience is highly recommended to be able to effectively participate in the exercises, but those without Python experience will still get much useful information about the capabilities for data analysis in Python and perhaps pick up some pointers on where they can get started learning more scientific Python and integrating it into their work flow.

If you would like to get a head start with the tools we will be concentrating on you can check out their documentation on readthedocs:

Problems or Questions?

We encourage you to submit any problems or questions you have to this repository issue tracker by choosing the "Question from workshop participant" issue template.

Past Workshops

Materials from past workshops can be found in other branches on this repo and in the past-astropy-workshops repo.