ten computer codes that transformed science

In a “Feature” article of 21 January 2021, Nature goes over a poll on “software tools that have had a big impact on the world of science”. Among those,

the Fortran compiler (1957), which is one of the first symbolic languages, developed by IBM. This is the first computer language I learned (in 1982) and one of the two (with SAS) I ever coded on punch cards for the massive computers of INSEE. I quickly and enthusiastically switched to Pascal (and the Apple IIe) the year after and despite an attempt at moving to C, I alas kept the Pascal programming style in my subsequent C codes (until I gave up in the early 2000’s!). Moving to R full time, even though I had been using Splus since a Unix version was produced. Interestingly, a later survey of Nature readers put R at the top of the list of what should have been included!, incidentally including Monte Carlo algorithms into the list (and I did not vote in that poll!),

the fast Fourier transform (1965), co-introduced by John Tukey, but which I never ever used (or at least knowingly!),

arXiv (1991), which was started as an emailed preprint list by Paul Ginsparg at Los Alamos, getting the current name by 1998, and where I only started publishing (or arXiving) in 2007, perhaps because it then sounded difficult to submit a preprint there, perhaps because having a worldwide preprint server sounded more like bother (esp. since we had then to publish our preprints on the local servers) than revolution, perhaps because of a vague worry of being overtaken by others… Anyway, I now see arXiv as the primary outlet for publishing papers, with the possible added features of arXiv-backed journals and Peer Community validations,

the IPython Notebook (2011), by Fernando Pérez, which started by 259 lines of Python code, and turned into Jupyter in 2014. I know nothing about this, but I can relate to the relevance of the project when thinking about Rmarkdown, which I find more and more to be a great way to work on collaborative projects and to teach. And for producing reproducible research. (I do remember writing once a paper in Sweave, but not which one…!)

GG Day in Rouen

[Notice: This post is fairly “local” in that it is about a long-time friend being celebrated by his university. Nice poster though and an opportunity to stress his essential contributions to the maths department there!]

Next June, I will spend the day in Rouen for a conference celebrating the career and dedication of Gérard Grancher to mathematics and the maths department there. (When I got invited I had not realised I was to give the research talk of the day!) Gérard Granger is a CNRS engineer and a statistician who is indissociable from the maths department in Rouen, where he spent his whole career, now getting quite close to [mandatory] retirement! I am very happy to take part in this celebration as Gérard has always been an essential component of the department there, driving the computer structure, reorganising the library, disseminating the fun of doing maths to high schools around and to the general public, and always a major presence in the department,  whom I met when I started my PhD there (!) Working on the local computers in Pascal and typing my thesis with scientific word (!!)

Extending R

As I was previously unaware of this book coming up, my surprise and excitement were both extreme when I received it from CRC Press a few weeks ago! John Chambers, one of the fathers of S, precursor of R, had just published a book about extending R. It covers some reflections of the author on programming and the story of R (Parts 2 and 1),  and then focus on object-oriented programming (Part 3) and the interfaces from R to other languages (Part 4). While this is “only” a programming book, and thus not strictly appealing to statisticians, reading one of the original actors’ thoughts on the past, present, and future of R is simply fantastic!!! And John Chambers is definitely not calling to simply start over and build something better, as Ross Ihaka did in this [most read] post a few years ago. (It is also great to see the names of friends appearing at times, like Julie, Luke, and Duncan!)

“I wrote most of the original software for S3 methods, which were useful for their application, in the early 1990s.”

In the (hi)story part, Chambers delves into the details of the evolution of S at Bells Labs, as described in his [first]  “blue book” (which I kept on my shelf until very recently, next to the “white book“!) and of the occurrence of R in the mid-1990s. I find those sections fascinating maybe the more because I am somewhat of a contemporary, having first learned Fortran (and Pascal) in the mid-1980’s, before moving in the early 1990s to C (that I mostly coded as translated Pascal!), S-plus and eventually R, in conjunction with a (forced) migration from Unix to Linux, as my local computer managers abandoned Unix and mainframe in favour of some virtual Windows machines. And as I started running R on laptops with the help of friends more skilled than I (again keeping some of the early R manuals on my shelf until recently). Maybe one of the most surprising things about those reminiscences is that the very first version of R was dated Feb 29, 2000! Not because of Feb 29, 2000 (which, as Chambers points out, is the first use of the third-order correction to the Gregorian calendar, although I would have thought 1600 was the first one), but because I would have thought it appeared earlier, in conjunction with my first Linux laptop, but this memory is alas getting too vague!

As indicated above, the book is mostly about programming, which means in my case that some sections are definitely beyond my reach! For instance, reading “the onus is on the person writing the calling function to avoid using a reference object as the argument to an existing function that expects a named list” is not immediately clear… Nonetheless, most sections are readable [at my level] and enlightening about the mottoes “everything that exists is an object” and “everything that happens is a function” repeated throughout.  (And about my psycho-rigid ways of translating Pascal into every other language!) I obviously learned about new commands and notions, like the difference between

x <- 3

and

x <<- 3

(but I was disappointed to learn that the number of <‘s was not related with the depth or height of the allocation!) In particular, I found the part about replacement fascinating, explaining how a command like

diag(x)[i] = 3

could modify x directly. (While definitely worth reading, the chapter on R packages could have benefited from more details. But as Chambers points out there are whole books about this.) Overall, I am afraid the book will not improve my (limited) way of programming in R but I definitely recommend it to anyone even moderately skilled in the language.

Dennis Ritchie 1941-2011

I just got the “news” that Dennis Ritchie died, although this happened on October 12… The announcement was surprisingly missing from my information channels and certainly got little media coverage, compared with Steve Jobs‘ demise. (I did miss the obituaries in the New York Times and in the Guardian. The Economist has the most appropriate heading, printf(“goodbye, Dennis”); !!!) Still, Dennis Ritchie contributed to computer science to extents comparable to Steve Jobs’, if on a lesser commercial plane: he is a founding father of both the C language and the Unix operating system. I remember spending many days perusing over his reference book, The C programming language, co-written with Brian Kernighan. (I kept trying programming in C until Olivier Cappé kindly pointed out to me that I was merely translating my Pascal vision into C code, missing most of the appeal of the language!) And, of course, I also remember discovering Unix when arriving at Purdue as a logical and much more modern operating system: just tfour years after programming principal components on punched card and in SAS, this was a real shock! I took a few evening classes at Purdue run by the Computer Department and I still carry around the Purdue University UNIX Pocket Guide. Although I hardly ever use it, it is there on the first shelf on top of my desk… As is The C programming language even though I have not opened it in years!

So we (geeks, computer users, Linuxians, R users, …) owe a lot to Dennis Ritchie and it is quite sad both that he passed away by himself and that his enormous contribution was not better acknowledged. Thus, indeed,

for (i=0; i<ULONG_LONG_MAX; i++)
    printf("thanks a lot, Dennis")

The great’08 Pascal challenge

In order to make advances in the processing of their datasets and experiments, and in the understanding of the fundamental parameters driving the general relativity model, cosmologists are lauching a competition called the great’08 challenge through the Pascal European network. Details about the challenge are available on an arXiv:0802.1214 document, the model being clearly defined from a statistical point of view as a combination of lensing shear (the phenomenon of interest) and of various (=three) convolution noises that make the analysis so challenging, and the date being a collection of images of galaxies. The fundamental problem is to identify a 2d-linear distortion applied to all images within a certain region of the space, up (or down) to a precision of 0.003, the distortion being identified by an isotonic assumption over the un-distrorted images. The solution must be efficient too in that it is to be tested on 27 million galaxies! A standard MCMC mixture analysis on each galaxy is thus unlikely to converge before the challenge is over, next April. I think the challenge is worth considering by statistical teams, even though this represents a considerable involvement over the next six months….