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#julialang

4 posts4 participants0 posts today

I'm sure someone has already invented a #python wiper that gets rid of all stray python installations, venvs and package managers. After two versions of poetry, a conda episode (better say: accident), a switch to uv, inconsistent use of pip, pipx and python installs via #homebrew, and installs via miniconda that #julialang and #quarto sneaked up on me, there is absolutely no way to make any path to anything work in any virtual environment and I need a new laptop. So what's the python wiper called?

New article published today in the Computers & Chemical Engineering journal: *A multi-agent system for hybrid optimization*. This paper is based on the work presented last year at the European Symposium on Computer Aided Process Engineering (ESCAPE 34) conference.

One key lesson I took away from this work: how easy it is to write efficient and effective multiprocessing code in Julia. And how much fun it is actually. 🙂

#MultiAgentSystem #Agents #Optimization #HybridOptimization #ProcessSystemsEngineering #CAPE #PSE #JuliaLang

doi.org/10.1016/j.compchemeng.

So, the Roller Derby World Cup happened from 3-6 July in Innsbruck, Austria. Our hosts Fearless Bruisers Innsbruck were extremely hard working, and from the 1st to the 7th (including set up + teardown time) we worked with 6 THOs, 2 THAs, 2 THPs and three GTOs (and 9 officiating crews, dozens of announcers and photographers, and a host of volunteers, along with our streaming tech friends at Real-Time Events) to make the world's largest Roller Derby event in history happen.

Despite this record-breaking scale over 5 tracks and 80 games, each of our 48 teams only played 3⅓ games on average. In order to make it possible to effectively run the equivalent of a qualifier, "group stage" and elimination all in just 4 days - with 6 teams entirely new to Derby! - we needed to use a tiny bit of statistics.

The advantage of the stats is that we can present you with a considerably richer "final result" than most sporting events would - estimating not just final ratings but also our errors on those ratings.

Code for this graph is open to the public at codeberg.org/aoanla/RDWC2025 (the game data needed will be uploaded very soon).

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
Continued thread

Evaluating of simple #additivemanufacturing cost function metrics (build height, footprint area, support volume, overhang area, ... ). The model is rotated and all metrics are computed, next the sphere is "painted" to show the magnitude of that metric for that orientation (sum of the lengths of the black lines as estimate of support material use). This way the sphere provides a nice summary visualisation of which orientations are best e.g. in terms of minimising support material use.

When someone says: "There's this great dynamically-typed programming language with a useful and expressive type system, powerful macros and multiple-dispatch that solves the 'two language problem' (meaning that you can quickly and comfortably write a prototype in the language but then also write the fast production version in the same language), that has roots in academia but with uptake in industry, a great interactive coding experience in the REPL (including the ability to show you the assembly code for any function!) and [an] excellent compiler[s]" you don't know if they're talking about #CommonLisp or #JuliaLang until they choose either the plural or singular for the word "compiler"! 😛

Just a bunny rotating according to a uniform set of directions on the sphere. The bunny is colored towards the "overhang" angle with respect to the ground. The black area on the ground is the projection of the bunny onto the ground (a bit like a shadow). This is a simple toy simulation that computes some metrics relevant to the simulation of 3D printing preparation.

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

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.