Recently, I migrated my personal website from Wordpress to Github Pages using Jekyll. After some trial and error, I managed to have everything up and running. However, Jekyll tagging (i.e., generating the pages that contain a collection of posts filtered by a tag) requires additional plugins which are not supported by Github Pages. Long Qian wrote a fantastic tutorial on how to implement this functionality with a Python script. Unfortunately, this still requires running the script, adding the files to the staging area, committing them, and pushing them to Github. That’s a lot of steps for every time that I want to add a new tag. Not only is it prone to errors, but let’s be honest: ain’t nobody got time for that.
Recently, I finished a personal project in which I analyzed the results of the “Who is your favorite Pokemon” survey. After that, I wanted to generate a more interactive visualization in which the user could choose a specific Pokemon and see its results. After pondering different options, I decided to do so in Bokeh because of a few reasons. First of all, you can generate your visualizations using Python only. Furthermore, it is very easy to incorporate Bokeh in Jupyter notebooks, which is great to generate a first version of the prototype. Lastly, a few colleagues of mine have used it for their projects at work and have been very happy with it.
For some strange reason, I stumbled with a paper that I had downloaded long time ago. It explains a simple algorithm for removing artifacts in ECG signal. Since I have a short time-off after the submission of my PhD thesis (yey!), I thought it would be cool to actually code the algorithm and give it a go.
Recently, I was going through my undergraduate lecture notes. I stumbled upon an exercise which I found interesting. The task consisted in implementing the algorithm proposed by Pei and Tseng, which uses vector projection to minimize the problem of transient values when applying an IIR notch filter to an ECG signal.