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Astropy tutorials at the University of Bern, 28 Oct 2019
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00-Install_and_Setup
01-IntroCoC
02-PythonIntro
03-UnitsQuantities updating presentations Oct 24, 2019
04-Coordinates
05-FITS
06-Tables
07-Models
08-WCS Clarify some of the language in the final exercises of the WCS tutorial. Dec 31, 2018
09-Photutils
09b-Specutils
10-WrapUp
11-Extras
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README.md Update README.md Oct 24, 2019
SETUP.md
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README.md

Using Python and Astropy for Astronomical Data Analysis

Workshop at Universitat Bern

DATE: Monday, October 28, 2019

TIME: 10:00-16:00

LOCATION: G6, Room -108

PRE-WORKSHOP SETUP

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

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

Schedule

Time Topic
9:00 - 10:00 Install and config
10:00 - 10:45 Intake Survey, Introduction to Python
10:45 - 11:00 Coffee break
11:00 - 11:30 Astropy Units, Quantities, and Constants
11:30 - 12:00 Coordinates
12:00 - 13:00 LUNCH
13:00 - 13:30 I/O: FITS and ASCII
13:30 - 14:00 Astropy Tables
14:00 - 14:30 Coffee break
14:30 - 15:00 Contributing to Astropy
15:00 - 15:30 Extras
15:30 - 16:00 Q&A, Outgoing Survey

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:

Past Workshops

Materials from other astropy workshops can be found here: https://github.com/astropy/astropy-workshop

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