Python spoilt me; returning to Matlab is hard

Using Python daily for more than three years as part of my scientific workflow and then abruptly returning to regular Matlab use has made me realise how much better Matlab could be and how evident its idiosyncrasies are. Conversely, while I was aware and noticed that Python makes things simple, it is Matlab’s comparative flaws that really made me come to appreciate just how much has been achieved in the past decade by the community in making Python an indispensable scientific tool.

An aim of this post is to recognize Python’s impressive convenience and versatility. Unfortunately, however, this post more naturally develops by taking the pessimistic approach of highlighting Matlab’s flaws. What follows are several minor, and a few major, annoyances that I’ve noticed on returning to Matlab.

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Benefits of an e-reader for academics

E-readers are no good for reading scientific papers.1 They’re grayscale, they’re too small, and flipping back and forth between pages takes time. That said, my e-reader has two key benefits for me as a scientist/academic. It provides a truly offline method to read content later and it lets me read books that are only available as PDFs.

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An example of how a given blog post looks on my e-reader

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Palatino and Source Sans Pro, the only fonts a scientist needs

The title of this post is both my subjective opinion and the TL;DR version of this post. If you’re interested in why I no longer bother with any other fonts, let me explain.

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Organise scripts and figures easily with Jupyter Notebooks

Keeping track of scripts used to generate figures is difficult. Before realising that Jupyter Notebooks could solve most of my problems, I would have directories with dozens of scripts with filenames of varying levels of ambiguity. Names that probably meant something to me at the time, but are hardly descriptive months or years later. Names like  ISW_plume_plots.m, new_ISW_model_plots.m, and plot_model_behaviour.m. A certain PhD comic springs to mind.

Regardless of whether its Python, R, Julia, Matlab, or pretty much any other type of code, Jupyter Notebooks solve the problem. For example, I use a single notebook to archive the code for all figures in a paper and, more importantly, I can associate each set of code with the figure it generates. Rather than trying to remember what file I want, I need only remember which figure I want. (I say archive because I much prefer to do the bulk of my exploratory analysis in an editor. Alternatively, JupyterLab may work better for you.)

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This is the best decade to be a grad student

Catching up on the literature is a daunting aspect of graduate studies. As a physical oceanographer, I regularly cite work from 30 to 40 years ago. In that time, and all the way back to the turn of the 20th century, the scientists before me got to answer all the low-hanging-fruit problems and write the papers that will be cited thousands of time. They leave behind the messy, complex, and esoteric questions for the current grad students. Surely, then, I would think the 60s or 70s or even earlier would have been the best time to be a grad student?

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Article titles are more important than your name

A webpage or CV with a list of publications serves two purposes. A useful one: to help readers discover papers related to one that interested them. And a less altruistic one: to say ‘Hey, look at how many publications I have’. These days, the latter is somewhat necessary, but shouldn’t overshadow the former. Furthermore, discovering related papers should be an easy task, but too often isn’t.

Too many publication lists that I come across these days obscure the title—surely the most important part of the citation—by bracketing it with the authors’ names and journal details. While this form is necessary for a reference list in a paper, it makes no sense in a CV or personal webpage.

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