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#JuliaLang

4 posts4 participants0 posts today

Proud to say that last night before bed I suggested that fitting problems with our migration model might be fixed by switching to a local basis for a certain function. I described the use of compact radial basis functions, and by the time I woke up my student had implemented them in pure #Julialang and said that fits were now fast and seemed good quality. Its great to work with a student with that kind of talent, and a language that enables that kind of rapid exploration.

New post: jcarroll.com.au/2025/06/29/cou

What if you could just wave a magic wand over your R #rstats :rstats: code and have it transform into something that ran as fast as or faster than C? @t_kalinowski's {quickr} 'R to Fortran Transpiler' does that for you! #fortran

With bonus comparisons to #Rcpp #julialang :julia: and #rustlang :rust:

Updated to restrict to integers thanks to @toddixd

Irregularly Scheduled ProgrammingCounting Digits Quickly
More from Jonathan Carroll

I have started a new blog which will present musings on coding for my research in optimization and its application to industrial engineering problems. I code mostly in Julia and always using Emacs.

homepages.ucl.ac.uk/~ucecesf/b

I will post here when new blog posts are posted. I'm hoping to create an RSS feed for the blog in due course.

The blog is written in org mode in Emacs (of course 🙂).

(edited to add actual link 😜)

www.homepages.ucl.ac.ukOptimal configuration

#MathWorks server issues have persisted for days, affecting licensing and downloads. This highlights how dependent many academic workflows are on proprietary systems.

Consider alternatives that remain available regardless of vendor status:

🔹 Julia – built for numerical computing
🔹 Python – widely used, with strong scientific libraries

Both are open-source and resilient.

I often find myself having to explain stress derivation from hyperelastic formulations to research students. And I also have to explain the difference between constrained/coupled/uncoupled formulations a lot.

So I've been creating an #opensource educational resource on this here:
github.com/Kevin-Mattheus-Moer

It has now been extended with a #Pluto notebook showing the equations as well as a #Julialang numerical implementation.

I've also added the source for a fun companion presentation to show "the anatomy" of the Ogden hyperelastic formulation.