Here is my situation:
I am an AAVSO solar section observer and since January 2021 I have started a study project on the Sun for the 25th cycle which mainly consists of taking, every day and at the same time, an image of the Sun in SDO HMIIF format. 4K JPG and make an inventory of each sunspot, taking care to enter its coordinates in Latitude and Longitude, the Carrington rotation cycle as well as the region to which the spot belongs.
I was told that SunPy has procedures or routines that can automate or simplify my daily task as well as perform various statistical tests on my accumulated data such as a binomial test for a dichotomous variable with a 95% confidence interval.
I have no knowledge of Phyton language and would SunPy be a good solution in my case?
Do you have suggestions ?
I have a Windows 10 PC
Thanks in advance and have a nice day.
With SunPy you will be able to automate some of that process, e.g., downloading the image, extract and convert coordinates, etc. However, there some steps that need to be manual, or with some revision. For example, the sunspot detection can be automated (but I don’t think we have an algorithm that does that within SunPy), and so the “classification” of whether that sunspot belongs to a particular region or not. What SunPy can do is to visualise the information that exists already in the HEK.
For the rest of your analysis, as statistical tests, then there are many other python libraries that will probably help you on that (scipy.stats, statsmodels, pingouin).
So, in short, yes, Sunpy will help, but won’t provide all that you want. You will need to learn a bit of python to be able to use all the power provided by the scientific stack available.
If you don’t know any python and any programming language, then I’d suggest you start looking at the basics (the carpentries provides a good starting point). Then take a look at the different libraries and their user guides, tutorials, and examples. You can ask questions throughout all this journey in any of the places (here, [matrix] sunpy channel, or similarly for the other libraries).
Thank you very much for all these details. Certainly, this will help me greatly to assess the rest of the decisions that I have to make on this subject.
I greatly appreciate the hyperlinks you inserted in your answer as it will save me a lot of research time on the subject.
Have a nice day,