Announcing Astropy v0.2: The First Release of the Community Built Astronomy Python Package

by Tom April 10, 2013

A little over a year ago, I wrote about the Astropy project. The aim of the project is to co-ordinate the Python code development efforts in Astronomy so as to be able to present users with a coherent set of tools to perform their work. On February 20th, we released the first public version, Astropy […]

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Python in Latex with Sympy

by Jessica Lu January 30, 2013

The final output for scientific research is typically a paper published in a scientific journal. There may be electronic versions of figures and tables that accompany the paper. However, the links between the input data (e.g. images, spectra, time series), the analysis (e.g. code, databases), and the output paper (LaTeX, EPS figures) is often weak. Everyone has […]


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Remote display in python? [Ask Astrobetter]

by Jane December 31, 2012

The question:  “How can I remotely display python graphics windows?” The backstory:  I’m gotten used to the nifty interactive graphics of matplotlib in ipython.  But here it is New Year’s Eve and I’m working from home.  I need to ssh in to my desktop, run python, and remotely display the python graphics windows to my […]


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Filtergraph: A Web-based Data Visualization Application

by Guest October 15, 2012

Dan Burger is a Computer Science graduate student at Vanderbilt University. He has been working with the Astroinformatics Group on how to dynamically handle and visualize large volumes of data. Datasets. If you work in astronomy, chances are you have them. They are hardly the romantic vision that you had when you decided to go into […]


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Learning Python – The Interactive Way

by Jessica Lu June 18, 2012

One of the nice things about programming in python is that it is free, relatively easy to use, and there is lots of support and development online. One of the downsides is that there is not a standard python package to install… you have to know about all the interesting add-on bits to get maximum […]


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Python Installation and Ecosystem Tutorial

by Guest April 11, 2012

This is a guest post from Tom Aldcroft. Tom is an astrophysicist working at the Harvard-Smithsonian Center for Astrophysics in Cambridge MA. In addition to science research he has responsibilities supporting mission operations for the Chandra X-ray Observatory. In both areas he uses Python on a daily basis and will gladly tell you about his […]


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Bayesian Inference in Python

by Jessica Lu February 24, 2012

Observational astronomers don’t simply present images or spectra, we analyze the data and use it to support or contradict physical models. A key aspect of data analysis is understanding the certainty of claims that are made. Thus using statistics is a fundamental part of observational astronomy. Statistical inference is one method of drawing conclusions, and establishing […]


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Astropy website/logo design competition

by Tom February 6, 2012

Last Monday, I wrote about the Astropy project, and mentioned various ways of contributing to the project code and documentation. We’ve now launched a competition to design the website and logo for Astropy, with a prize for the winning entry, so if you’re looking for a fun way to contribute to Astropy, this is your […]


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The Astropy Project: A core Python package for Astronomy

by Tom January 30, 2012

In June 2011, the announcement of a new Python package for Astronomy on the astropy mailing list prompted a long thread that started as a criticism of the proliferation of independently-developed Astronomy Python packages but quickly became the start of a common effort to develop a single core package for Astronomy. Many hundreds of emails, […]


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[Link] Statistics with Python

by Jessica Lu September 30, 2011

Astronomers rely on statistical analysis all the time. The Python programming language has some excellent add-on packages for statistics. But sometimes the documentation isn’t as helpful in “real-world” scenarios. Prasanth Nair has posted a very nice tutorial on Simple Statistics with Python over at his blog. I highly recommend it for new users of python […]


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