Dr. Haley Gomez gave a presentation on using Python in astronomy. Python is well-suited for astronomy as it is open source, cross-platform, easy to learn, and has many astronomy packages. The Astropy package in particular provides core functions for astronomy work, including units, coordinates, time handling, and FITS file support. Machine learning techniques also show promise for addressing challenges in processing large astronomical datasets.

1. django weekend Cardiff - 7-9th Feb 2014
Python in Astronomy
Dr Haley Gomez
@astrofairy
thanks to Edward Gomez (@zemogle) and Thomas Robitaille (@astrofrog)

2. astronomy then
© Copyright California Institute of Technology

3. astronomy now
very hot
gas
cold gas

4. how do we store this?
FITS format
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first successful cross-platform way to share
astronomical data
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contains metadata which can be read
•
long term data storage

5. the problem
Big Data and Rich Data
survey astronomy

6. How do we prepare the
astronomy community?

8. why python?
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•
•
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open source, cross platform
easy to learn
communicates with Fortran and C++
many different packages
cooperative sharing
blurred lines
reproducability

11. .units/.constants
.coordinates
.time
.table/ .ascii
.fits
.wcs
.modelling
.ndata
.convolution
.stats
.cosmology
montage, APLpy,
astroML
Thomas Robitaille, Perry Greenfield, Erik Tollerud

12. astropy ‘core’
package:
Only has Numpy as non-optional dependency
Well tested, documented code
Community consensus for inclusion
Cross platform and easy to install
Python 3 compatible

13. e.g. astropy.units

14. e.g. combine images of an object

15. e.g. bringing things together

16. machine learning
signal
?

17. http://www.astropy.org
http://aplpy.github.io/
This research made use of Astropy, a community-developed core
Python package for Astronomy (Astropy Collaboration, 2013)