I’ve been working on another paper today and decided to update my previous xtable function (as described here) to use dplyr, as I want to fully get to grips with Hadley Wickham’s wonderful ecosystem of packages including dplyr (and its predecessor plyr), ggplot2 and tidyr (and its predecessor reshape2). I mentioned this before Christmas but have only got round to it now, which included a few hours of struggling with tidyr to make it do what I want!
I’ve recently decided to start using Sweave for producing my publications since I already use R for the data analysis side and LaTeX for the markup, so it seems natural to combine them. In a nutshell, Sweave lets you embed R output directly into your documents, allowing for a more organised workflow. You mark a section as containing R code, then run your analyses with your output, be it in the form of text, a table, or a chart, formatted directly into LaTeX markup.
I’ve never fully taught myself R, just dipped in and out when necessary. I’ve primarily used it for standard data analysis and visualisation, although I have been meaning to get to grips with one of the numerous available machine learning packages. Dealing with datasets tends to involve a lot of hacky manipulation until it’s in a useful format for your analysis. Initially I was just trying to use standard library functions, although once I came upon the essential reshape2 package and the ease with which you could convert your dataframe between wide and long formats I knew I was going to have to use a different approach.
In my last blog post I touched on the fact that I’m an extrinsically motivated learner, I need to be working towards a goal rather than learning for learning’s sake. Thus, in times where I’m not working towards a specific deliverable such as a report, or a publication, I can find it challenging to maintain focus and motivation and frequently end up bored. This also happens when I’ve been working on the same thing for a while (which is what is happening at the moment!
Thanks to a year long course I’m taking in Higher Education teaching I’ve been thinking a lot recently about the education I received, not only as an undergraduate but throughout my schooling. One issue that I keep coming back to is that I believe I’ve developed disadvantageous working habits due to the use of exams as the primary form of assessment in the UK education system. I’ve always excelled in exams, whereas with coursework I lack the discipline to stay focused without the tight time constraint of an exam.
Over the weekend I was wondering if there were any useful APIs out there for retrieving information about the weather for a given location. I was particularly interested in current weather but this post also applies to forecasting. I had a Google and found the OpenWeatherMap service which impressed me for several reasons: It is open - anyone can add a weather station to it providing they fulfill certain criteria It provides a lot of information related to the weather!
Last week on the 30th October the 7th annual York Doctoral Symposium took place. This is a 1 day Symposium run by post-graduate students from the Computer Science and Electronics departments at the University of York. It provides a fantastic opportunity for students to gain experience in writing papers or posters, giving presentations and network with other researchers in their field. Another key benefit of the symposium is that it gives experience in organizing and running a conference to the students who are on the organizing committee, a valuable skill to have for anyone pursuing an academic career.
After watching Peep Show recently I realised there just isn’t enough of it in my life. The writing is a particular highlight, with brilliant characters (that are somewhat relatable) and each episode is filled with hilarious quotes. If you haven’t seen it before I highly recommended checking it out on Netflix, which has all 8 seasons. Each season is only 6 episodes long so it won’t take long to watch them all.
This may not be very relevant to many people, but if you’re unsure of when to use the NIO classes, or are having problems interfacing with USB in Java then I hope it helps a little.
I was tasked with debugging an annoying error this week, where a position sensor connected to a laptop via USB froze approximately once every 70 attempts. The IO was performed in Java, accessing the USB port as though it were a local file and reading in data byte by byte using a BufferedInputStream.
The majority of my work is involved with machine learning using biologically inspired techniques, focusing on classification problems. I run my algorithms on benchmark datasets to test their validity and the effect of various parameters, and then these are used in real life medical applications. Trials can take a long time to prepare, and the data collection process can be somewhat challenging. The group I’m involved with researchs Neurodegenerative Diseases, particularly Parkinson’s Disease.