Week 13: Weekly Check-In (#7) - Last Check-In

Published: 08/26/2019

1. What did you do this week?

As described in my previous post, I spent last week doing some smaller corrections on my Pull Requests. The biggest amount of work was dedicated to allowing fast and memory saving computation to the tfr_stockwell function, the last function where I haven't implemented this yet. Principally, most of this went similar to the other functions, i.e. I had to create an alternative function which computes stuff separately for lists of SourceEstimate objects, and is capable of handling input from generator objects. However, the tricky and time consuming part was again to make sure the data fields were completely equal.
Another step last week was to change the examples I created, from one example to three example that cover the diffferent TFR functions and SourceEstimate types which can be processed equally.
Finally I did some smaller commits, correcting some stuff that my reviewers mentioned could be made better.

2. What is coming up next?

Well, as my project is finished now, and all of the important functional stuff has been implemented, I will only spend my time working on review corrections, in order to get everything merged into master.
Concerning the extended plotting that I mentioned over the last blog posts, I will probably do a bigger independent PR, that can enhance plotting functionality and modularity.

3. Did you get stuck anywhere?

Yes. As I already mentioned I first had problems with making the data fields completely equivalent, when implementing a time/memory saving version of tfr_stockwell.
But probably even more annoying (because I didn't expect it) was trying to erase Errors when submitting the freshly made examples. I rewrote the exampels first to a MNE-testing dataset which contained real neurophysiological data. Then, when submitting it, noticed that my version of the testing data was outdated (the respective dataset has been revised for another MNE-Python GSoC project running this summer). So I had to adapt the respective file paths again, which would've been no problem at all, if one of the files that I needed for one of my examples (a trans.fif file) wouldn't have been removed from the dataset. So this resulted in trying various solutions to make things work again, until I finally decided to change the example and make it run on a different dataset, where all needed files were accessible.
So next time I'll be using testing data, I'll definitely will make sure to update my testing data folder first.

So this was the last regular report on my GSoC project, and I hope that you've found it an interesting thing to read. As you might have noticed from reading, I've definitely learned alot of things during the project (probably a consequence of doing a lot of mistakes during the project), but I'm glad that I could really notably enhance my coding skills during this summer.
From now (and after having all the stuff from the project entirely merged), I will still try to stay involved in MNE, so I hope that this won't be the last thing that you'll hear from me.

Finally I want to say thanks to everyone who participated in this Google Summer of Code project with me - from my mentors to all reviewers to the people from the Salzburg Brain Dynamics lab to finally you, the reader of my blog.
Thank's to everyone and have a good time - hopefully profiting from my works on MNE-Python this Google Summer of Code ;).