Time flies.
It feels like yesterday that I joined DiRAC virtually and now that I look back, already a month and a half!
It has been a really amazing journey so far and I have learned a lot, wrote a lot of code and have worked with some really nice people.
The results of the first evaluation was declared on the 4th of July and yes, I successfully completed my first evaluation!
The second coding period is now officially halfway through. Since the end of the first coding period, I have been working on both the 1D Profile viewer and WCS autolinking. Since much has been discussed about the 1D Profile viewer of glue and now that it is finally working, let me take the opportunity to talk about the wcs-autolinking PR.
Problem statement: Originally the wcs-autolinking only worked for some cases, for example for the spatial axes but not for the temporal and wavelength axes in the scenario where the dimensions of the two wcs objects of the data cubes being matched up do not match. This is highly undesirable and needs generalizing while conforming to APE 14, where the issue of a shared Python interface for World Coordinate Systems is discussed.
The solution: So we rewrote the code. Most of the celestial code has been retained, with some new additions to add linking for the other dimensions. The code rewritten is as follows:
Hello! This blog marks the end of the first phase of Google Summer of Code. The journey so far has been challenging but also extremely rewarding. The knowledge gained as a by-product of the work I’ve been doing on my project so far is unbelievable, but more importantly has been a better, more pleasant experience compared to the traditional system of gaining knowledge by reading books and tutorials. In this blog, I will be summarising the work that I’ve been doing for the past 2 weeks, update the readers on my current position and give an idea of what lies ahead.
As I discussed in my previous blog, the work for the first two weeks mostly involved using Cython to translate the host code into something which could be compiled to provide better performance. More importantly, apart from the Cython part, I had to also start working on porting the kernels from their pure CUDA C form into something which Python/Cython could also understand. While the actual work to do so did not take long or came across as very challenging, the most difficult part in the whole process, undeniably, was to get the two, Cython and CuPy to talk to one another.
So after 4 weeks of planning and coding and debugging, the day came when I had to launch version 1.0 of the product!
The extension I built is now deployed in the DiRAC Jupyter Hub and is currently getting used by the astronomy community at DiRAC!
What you can do with my extension:
It has been a month since GSoC’s coding period started early in June 2020. Much has happened since then in the glue-solar project, and to sum it up I have been pretty much spending all my GSoC time working on a WCSAxes-enabled version the 1D Profile viewer for extracting 1D spectrum from data cubes using the pixel extracted in a 2D Image viewer. To be honest it has been very effort-intensive, though not necessarily time-intensive as I have previously feared. But the journey has been fun given my very supportive and friendly project mentors. To the layman and non-specialist what I have related regarding the project details probably sounds esoteric, which it is. With this realization I will split this and remaining GSoC blog posts into two halves: one pertaining to my personal struggles, and the other pertaining to the technical aspect of the work carried out thus far, in that order, so that that latter part can be conveniently skipped over (but I do encourage you to do read both sections in tandem so get a better understanding of the project :-p) Anyway, let me begin…
One personal “secret” I wish to reveal is that this is my last year as a PhD Candidate in Astrophysics at the University of Hong Kong (HKU). Not only that, since my Postgraduate Scholarship officially ran out in October 2019 and no other funding options are available, I have been holding down a job as a front-end developer for some parts of the weekdays to support my PhD studies. So far I have been trying to manage my time wisely and balancing my various duties and obligations as best as possible, but it has been a genuine struggle, especially in me trying to find enough time to sleep. To make matters worse I have a tendency to drift towards writing code than writing my thesis, though I am making progress in both. So I did hesitated to apply for GSoC for a 2nd time this year and was originally against the idea. But when I saw the project ideas available I changed my mind. Glue-solar is actually like a godsend for me; the project enabled me to not only further develop my self-discipline as a person, it also allowed me to learn from experts in the field working on open-source data visualization, and to grow from the experience. I thoroughly enjoyed interacted with my mentors, who have been very patient and helpful in offering me guidance (as well as friendship) throughout. If I have any advice I am allowed to offer anyone wanting to try out open-source software development through GSoC, and if GSoC does continue in the near future, I would recommend them to try out any of the OpenAstronomy projects. This is because OpenAstronomy is one (relatively) small but vibrant community of dedicated programmers, many of which scientists, that is welcoming to newcomers coming from a diverse background. And also, simply put, ASTRONOMY IS FUN! This is especially true for SunPy. I remember I started to contribute to open-source software as a relative novice with some bookish knowledge but not a lot of real-world experience back in around January 2019. My first contributions were to SunPy and Astropy. I remember I have read an article about how to get into GSoC in 2018 to learn about the program, though was not all that keen in getting into it at first. My first motivation to contribute was to give back to the community, because I had been using Python-based astronomy packages like Astropy for my PhD research. But at the urge of a mentor active in the Astropy community, I did apply. The GSoC project I worked on last year in 2019 was IRISpy, and my mentors were Dan Ryan and Laura Hayes. They were amazing as mentors, and were instrumental in my being able to complete the project successfully in the end of the program. I still miss my time spent with them on that project. IRISpy has officially changed its name to sunraster, which I was fortunate enough to help launch earlier this year in 2020. Basically when I was working on it as a GSoC project it was to provide additional functionalities for the analysis of observations from NASA’s Interface Region Imaging Spectrograph (IRIS) satellite which looks at UV emission from the solar chromosphere in particular. Now that scope has been extended to not just IRIS data, but data collected with similar instruments. This year I am using a lot of the code I have written for the IRISpy project for the current glue-solar project, which is kind of cool. As an icing to the cake, I get to work on data cubes for glue-solar, which is one of my favorite things in this world, a passion I have gained through my PhD research into integral field spectroscopy (IFS). For the present GSoC work I even get to work on 4D data cubes (ones with an extra time dimension), which has one more dimension than the IFS cubes I am so familiar with! So far it has been another incredible GSoC experience for me. All in all I have a feeling it will be a good one, and also a fruitful one.
So we (me and my mentors) have ventured away from focusing on glue-solar and have entered the glue “proper” territory as we put more time and effort towards modifying the 1D Profile viewer. By this I mean we have begun work on glue instead of glue-solar as was the case as described in my previous article where we have built a “SunPy Map” viewer. So I am well on my way to complete the task “modifying the existing glue 1D Profile viewer to provide sliders for extra dimensions (currently collapses)” soon, which is a significant part of the glue-solar project. Personally, I am really looking forward to working on the “adding support for pre-computed statistics in datasets / viewers” task, which I will surely make time to complete before end of August.
This fortnight, I worked around iterating over different designs for redesigning the Dataretriever Clients so that its implementation can be simpler and more general. Generalization here means the ability to inherit most of the methods from the base class itself; therefore minimizing a number of similar methods in the subclasses.
I got PR #4309 merged which solved an old Issue #556. A simple show() function in ~sunpy.net.base_client.BaseQueryResponse enabled QueryResponse objects for Dataretriever, VSO, and JSOC clients to specify the columns to be shown in the result.
This returns an ~astropy.table.Table instance, so table operations can also be easily performed on the result.
Firstly, I would like to apologize for not posting a blog for more than a month.
Secondly, I would again like to apologize as this blog is going to be astronomically jargon-heavy(pun intended).
Now before you decide to just watch the funny Joey video and go watch more Friends episodes; trust me after reading this 7 minute blog you will gain serious bragging rights. After which you can binge Friends to your heart’s content(I already got my popcorn bowl with me 😉).
There has never been a better time to help scientists understand the mysteries of the sun.
‘Sunspots’ and ‘solar storms’ are the feature of an ambitious project launched internationally by astrophysicists at Trinity College Dublin. Citizen scientists work as part of a global team to better understand sunspot and solar storm phenomena and their impacts on Earth. They do this by ‘rating’ the relative complexity of each sunspot image they see on the Sunspotter Web site, based on its size, shape and arrangement of ‘magnetic blobs’. Sunspotter is essentially a game of hot-or-not for sunspot data; citizen scientists are shown two images of sunspot groups and asked which is more complex. This is extremely useful in helping astronomers understand the physics of our star, the Sun.