Palimpsest

Evolving notes, images and sounds by Luis Apiolaza

Page 18 of 64

I used to read

I used to read. A lot. All sorts of books, popular ones and some obscure ones; they were mostly novels, some poetry (in Spanish) were my usual fare. I read voraciously but with no target; I mean there was no “I have to read X books this year” just read and read. Years later I reduced my reading a lot, part of changing cities, countries, language, lifestyle.

Later came the idea of giving away books. It was too much hassle to keep so many books sitting on a shelf. Then I decided to buy much fewer books; some years I didn’t buy even one. Later there was much dog walking, which consumed a lot of my reading time and then I discovered audiobooks.

Initially, audiobooks felt very different, as usually my problem was “How do you pronounce this name? and now it was “How do you spell this name given the pronunciation?” It was harder to keep all the pieces in place, there was no going back to remind myself what was happening before. My solution, perhaps no ideal but practical, was to simplify stories. Lots of “who dunnit” but audiobooks were quite handy, with 8 to 15 hours for an unabbreviated story*.

Characters sound different from what they sound in my mind if I’m doing the reading. At the same time, it is going back to oral stories, which were the first stories for humanity. One big problem: the audiobook market is a dumpsterfire of a near monopoly, with a DRM heavy offer (Audible, an Amazon company). And I do not want to buy books or audiobooks so my solution is very simple: borrow audiobooks from my public library, which has a fairly large catalogue.

After a while one develops a taste for voice actors. My favourite, by far, is Seán Barrett who does an excellent Harry Hole in Joe Nesbø’s crime novels (here a Barrett interview about his voice acting work).

These “readings” are far from what I used to read, but they are very fun. How many of them? Quite a few, depending on time and books available. I often do not respect the order of book series, as I rarely have the patience to reserve the books and wait that they are in the right order.

Bookcase in my office. Mostly technical books.
Bookcase in my office. Mostly technical books, some of which I’ve given away.

*There are some exceptions, like Neal Stephenson’s Cryptonomicon which is 43 (!) hours.

Sense-checking data

Over the birdsite dumpster fire. Emily Harvey was asking:

do you know of any good guidelines/advice for what one should do to sense check and make sure they understand any data before using it?

I replied the following:

Typically, I might be very familiar with the type of data and its variables (if it is one of my trials) or chat/email multiple times with the owner of the dataset(s) so I can check that:

  • units and recorded values match. If units are mm, for example, the magnitudes should make sense in mm.
  • the order of assessments and experimental/sampling design match: people often get lost in trials or when doing data collection, recording the wrong sampling unit codes.
  • dates are OK. I prefer 2023-04-07; anyway, this is often a problem when dealing with Excel data.
  • if we are using environmental data that it matches my expectation about the site. Have found a few weather station problems doing that, where rainfall was too low (because there was a sensor failure).
  • the relationship between variables are OK. Example of problems: tall and too skinny trees, fat and short ones, suspicious (unless broken, etc), diameter under bark smaller than over bark, big etc.
  • levels of factor match planned levels (typically there are spelling mistakes and there are more levels). Same issue with locality names.
  • map coverage/orientation is OK (sometimes maps are sideways). Am I using the right projection?
  • joins retain the appropriate number of rows (I mean table joins using merge or left_join in R, etc).
  • Missing values! Are NA coded correctly or with zeros, negative numbers? Are they “random”?
  • If longitudinal data: are older observations larger (or do we get shrinking trees?)
  • etc

Of course these questions are dataset dependent and need to be adapted to each separate situation. Finally: Do results make any sense?

Jetsam 38: take away

People waiting for take away orders in a shop. Menus on the wall and an old-fashion video game in the left corner.
People waiting for take away orders in a shop, Christchurch, New Zealand.

Flotsam 16: new laptop

In my job I get a new laptop every 3 years or so; at least that is how it works with Apple laptops. You get a new one, together with Apple care, and it is depreciated during three years. Keeping computers for longer doesn’t make financial sense according to the bean counters. Coincidentally, it is roughly the time for the laptops to start falling apart, more likely by design.

On terms of features, I reached 1 TB SSD disk around 6 years ago (I don’t use half of that), 16 GB of RAM 3 years ago (I used to be quite comfortable with 8 GB of RAM 9 years ago or so. What I am trying to say is that spec-wise I’ve been OK for the last half decade, at least. The peak of my computing was a Macbook Air 13″ just before the appalling Macbook Pro 13″ butterfly keyboard fiasco. In 2020 I ordered a huge 16″ Macbook Pro, despite 13″ being my sweetspot for laptop size, because of covid 19. We didn’t know for how long we’d be working at home—which in NZ turned out to be not very long—so I ordered a larger screen and, gasp, a real ESC key (again). I don’t have much love for the 16″: too heavy, too noisy, meh battery life, got too hot, etc.

This time I went back to Macbook Pro 14″ because: real ESC key (ridiculous to mention this, but I was traumatised by the touch bar ESC), no touch bar (yay!), SD card slot (I like photography), HDMI connector (FINALLY!) so I can skip on one dongle, proper power connector. The screen notch looks funny, but it disappears from my mind when busy writing. Overall impression: solid, hefty, fast. It actually feels much faster than the 16″ with Intel processor.

I test a lot of software that I don’t end up using, R packages, etc. so I avoid moving my old setup to the new laptop, starting from scratch and avoid carrying over all the cruft accummulated over three years. Then it comes the unavoidable boring task of installing the software I need for my work (the university already install MS Office and other software that don’t use, like Endnote). I installed:

  • Homebrew: unix package manager*.
  • R and RStudio: R stuff (see below for packages)*.
  • Apple command line tools: compiler, etc.
  • MacTex: everything and the kitchen sink LaTeX for mac*.
  • Zotero (including Zotfile and Better Bibtex plugins)
  • Joplin: notetaking in markdown*
  • NetNewsWire: reading RSS feeds, free, synchronises across mac and ipad*.
  • Calibre: e-book management*.
  • Digikam: photo management*.
  • Rawtherapee: RAW photo processing*.
  • Visual Studio Code: free text editor, don’t think it is fully open source.
  • Neovim: text editor*.
  • pandoc: text transformer*.
  • asciidoctor: text transformer*.

All starred (*) items are Open Source Software.

I use numerous R packages, but when I start with a new computer I don’t compile a list of packages to import in the new machine (lots of cruft) but I add a few packages that I know I use often and then add when I need to. Included in this list:

  • tidyverse: so I get ggplot, dplyr, reader, etc*.
  • data.table: sometimes I use this for fread() and data management*.
  • asremlr: multivariate + spatial genetic analyses.
  • rjags: bayesian stuff*.
  • rstan: bayesian stuff*.

I still have to install “a few” things (like QGIS) but I’m getting there. I’ll update the post later once I have added more software.

Jetsam 37: ED

View of Emergency Department in Christchurch Hospital
View of Emergency Department in Christchurch Hospital
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