The article I found was “SunPy: Python for Solar Physicists”. You ask why Solar Physicists? Well, Physics to me is an incredibly challenging field and anything that can help to make research and discovery easier in this field is a very good thing. The article shows how SunPy, can help Physicists with their analysis of solar data. The article also shows how a Python code can help take huge quantities of data collected via solar satellites, and make the analysis of this data possible. As an example, “NASA’s Solar Dynamics Observatory (SDO) satellite records over 1 TB of data per day all of which is telemetered to the ground and available for analysis”: That’s data from only one satellite! But how do you take all the disparate data including different wavelengths, spatial scales, and those with high time cadence, and crunch all this data together? It seems, “SunPy is the data analysis toolkit which provides the necessary software for analyzing solar and heliospheric datasets in Python.” SunPy is a free and open-source code and this too is one of the positive aspects of complex code for complex tasks. This article was presented at the SciPy 2013 and here’s the link to the presentation:
The article itself is at: http://conference.scipy.org/proceedings/scipy2013/pdfs/mumford.pdf
The Python code allows you to analyze and then animate solar data. SunPy wants to provide a solid base of data types and a framework around which people can do science and I believe SunPy has succeeded. This Python code allows you to conduct awesome science using a modest amount of Python code.
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