Ivory v1.7 is here! This release is all about hashtags. It's set to slowly roll out over the next few days, but you can force download it now from our App Store page:
#SimulatedUniverses
two clusters of galaxies form and merge into a larger one; here we track both the evolving gas density (left) as well as the relativistic electron content injected by all their galaxies (right).
Other "new" nice renderings of the growth of simulated clusters of galaxies by my former student Matteo Angelinelli, who kindly left all these gems in an hard disc!
During the holidays, i.e. from the 23rd to the 7th, I will not work.
I'd like to continue playing with the #julialang and some #pytorch but it's really for pleasure.
I will read some stuff about brains and perception but it'll be Ed Yong's "An Immense World", and perhaps McCulloch and Ashby.
Also, I'm finishing Dune.
If you too have the "privilege" of taking a break, what are you up to?
Still playing with #julialang. Here's Switzerland in triangles.
@jonocarroll I get a lot of small dark triangles with some images which persist even if I set npts to a high value (5000) and refine as true or false. Any ideas? Thanks again for the package! I'm enjoying seeing what it produces.
(1/6)This time of the year ☃️...Statistical Rethinking 2024 ❤️❤️❤️
This has become a tradition. Like previous Decembers, this week, the 2024 edition of the Statistical Rethinking course was announced. If you are looking to learn Bayesian statistics, I highly recommend checking it out.
🎂It's my birthday!🎂
To celebrate, I'm... Working to build a friendly, diverse #DataScience community at https://r4ds.io, just like I do every day! It'd make my day if you supported our efforts at https://r4ds.io/donate !
Here‘s another interesting #julialang, #python, #rstats comparison: „count the number of vowels in a string“. #julia uses an anonymous function as an argument to count(), #python iterates over the string using list comprehension, #rstats does the same but in a vectorized way
Pretty happy with my solution to part 2. Realised it's easier to just replace 'J' with '' and then add the count of '' to the highest counted card in the hand.
Bulk of the work is defining appropriate types so that sorting hands by rank is easy, and parsing the input. Mostly that's done by counting how many of each card is present and mapping to a hand type. Fun little problem.
Today's swirling electrons:
initially located in the halos of galaxies, finally accreted and mixing in a cluster undergoing a merger, and leading to the formation of a (mega) radio halo.
ENZO simulation + #JuliaLang processing, visualisation with SAO Ds9
STL files give each triangle their own coordinates set. So none of the triangles actually share nodes. So step one, after importing such a mesh, is to merge the nodes. This animation shows vertex normal based "inflation", the left is unmerged, the right is merged.
I've established I can use the AT Protocol API to post to #bluesky from #JuliaLang or #python I tried to re-post a Mastodon toot, but received this error message:
"Invalid app.bsky.feed.post record: Record/text must not be longer than 300 graphemes"
The Mathematical Engineering of Deep Learning is a new book by Benoit Liquet, Sarat Moka, and Yoni Nazarathy.
As its name implies, it focuses on the mathematical engineering of #deeplearning and covers topics such as:
✅ Foundation of machine learning and deep learning
✅ Optimization algorithms
✅ Convolutional neural networks
✅ Transformers
✅ Generative models
✅ Diffusion models
Idk, managing to actually dispatch the parallel tasks of my #Julialang code to the cores of Leonardo at CINECA (currently 4th HPC machine in the world), by calling the slurm task manager with ClusterManagers.jl (👉 https://github.com/JuliaParallel/ClusterManagers.jl) feels very good.
My routine is not meant to scale on more than 32 cores at the moment; however it means that I should be able to effectively use Julia also for massive parallel postprocessing on the computing nodes.
👍 @julialang #astrodon#astronomy
I love graphs from dynamical systems theory and analytical mechanics.
I love those curves in phase space etc.
That makes me want to understand them better.
I have discovered the book "Structure and Interpretation of Classical Mechanics", that teaches mathematical physics and the #programminglanguage#scheme but it looks quite annoying to work in Scheme with my 💻.
So, are there similar books/courses/resources with similar means to an end? Maybe in easier to use programming languages? Like #julialang#julialanguage
@rml yeah, I don't think I can go through the book SICM without coding in Scheme or similar... But I was curious also about other things, see for example "Nonlinear Dynamics" (Datseris, Parlitz) with #julialang.
This would probably be easier for me, coming from Python over all else, and with some experience in R and MATLAB from the bioengineering years. Also, I want to study Julia regardless.
But I understand I could use Clojure in JupyterLab/Notebooks, and if running Clojure+SICMUtils reading SICM is actually all I need, I might go for it.
If instead I need to learn lots of other basics in the programming language and installing all tools, I must postpone it to god knows when :/
Do you have any suggestions or tips? Consider I know nothing beyond the names I quoted
@julialang
Optimization.jl has many options for automatic differentiation, such as AutoZygote() and AutoEnzyme().
They are very useful, but are there any pros and cons for each option?