django weekend Cardiff - 7-9th Feb 2014

Python in Astronomy
Dr Haley Gomez
@astrofairy

thanks to Edward Gomez (@zemogle)...
astronomy then

© Copyright California Institute of Technology
astronomy now

very hot
gas

cold gas
how do we store this?

FITS format
•

first successful cross-platform way to share
astronomical data

•

contains metadata...
the problem
Big Data and Rich Data

survey astronomy
How do we prepare the
astronomy community?
why python?
•
•
•
•
•
•

open source, cross platform
easy to learn
communicates with Fortran and C++
many different packag...
.units/.constants
.coordinates
.time
.table/ .ascii
.fits
.wcs

.modelling
.ndata
.convolution
.stats
.cosmology

montage,...
astropy ‘core’
package:
Only has Numpy as non-optional dependency
Well tested, documented code
Community consensus for inc...
e.g. astropy.units
e.g. combine images of an object
e.g. bringing things together
machine learning

signal
?
http://www.astropy.org
http://aplpy.github.io/

This research made use of Astropy, a community-developed core
Python packa...
Python in Astronomy
Python in Astronomy
Python in Astronomy
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Python in Astronomy

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Talk given at Django weekend Cardiff @Djangoweekendcardiff

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Python in Astronomy

  1. 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. 2. astronomy then © Copyright California Institute of Technology
  3. 3. astronomy now very hot gas cold gas
  4. 4. how do we store this? FITS format • first successful cross-platform way to share astronomical data • contains metadata which can be read • long term data storage
  5. 5. the problem Big Data and Rich Data survey astronomy
  6. 6. How do we prepare the astronomy community?
  7. 7. why python? • • • • • • open source, cross platform easy to learn communicates with Fortran and C++ many different packages cooperative sharing blurred lines reproducability
  8. 8. .units/.constants .coordinates .time .table/ .ascii .fits .wcs .modelling .ndata .convolution .stats .cosmology montage, APLpy, astroML Thomas Robitaille, Perry Greenfield, Erik Tollerud
  9. 9. 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
  10. 10. e.g. astropy.units
  11. 11. e.g. combine images of an object
  12. 12. e.g. bringing things together
  13. 13. machine learning signal ?
  14. 14. 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)

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