I kept my twtr account for a while because brands I occasionally reach out to were still exclusively there. It’s now no longer the case so I put the account down for real :)
@hasnep@ayo The regex for Nix was [^a-z:]nix so it was filtering out Unix. I've changed it to [^(a-z|\.|\*):]nix[^Craft] to remove some of the worst false positives.
I've also added #julia, thank you for the suggestions!
Should I teach bash, fish, or Nushell to data scientists who want to go beyond the basics of shell scripting? There seems to be a clear spectrum from "ubiquitous but m'gawd" to "this is the future but m'gawd in a different way".
#Julia#Julialang@julialang
I have a question:
I am using HDF5.jl to open an hdf5 file; the file is organised in >100 datasets, written by the creator in a rather unpredictable way.
How do I automatically open all
datasets in the sequence, without knowing their name beforehand? (with the final goal of recreating a single long array, by appending the content of each dataset - this I know how to do).
thanks in advance
You'll be working with another reviewer to read and run the code, make sure it fills a basic checklist which usually only takes a few hours, and beyond that whatever youd like to focus on. Both of these are collaborative review processes where the goal is to help these packages be usable, well documented, and maintainable for the overall health of free scientific software.
Its fun, I promise! Happy to answer questions and boosts welcome.
Edit: feel free to volunteer as a reply here, DM me, or commenting on those issues! Anyone is welcome! Some experience with the language required, but other than that I can coach you through the rest.
February's TIOBE index has #Fortran as the 11th most popular language, marking its 12th consecutive month in the top 20, beating languages like #Rust, #R, #MATLAB and #Julia. About time to do away with that "Fortran is ancient/dead/obsolete" myth?
#astronomy#astrodon
Well, folks...I think this is it. today something odd or terrible is going to happen, and the omen is that I just coded that stuff from scratch in #Julia
...and it just worked, giving me results in the right units, at the first attempt.
How have I not made this connection before??? #rstats' S3 dispatch mechanism is strikingly similar to #rust's trait system (provided your mental model is sufficiently flexible and can compare function call vs method, that distinction perhaps being the reason I hadn't).
But it no longer feels so. Maybe it was a case of "you have to move fast to fix things" and as incumbents raise their game the window of opportunity closes. The vast investment in established stacks incentivises patching the most egregious weaknesses.
One exception seems #golang, which found a network niche
I'm very impressed by first impressions of https://marimo.io/ - a brand new open source Python notebook implementation, a bit like Jupyter but with reactive cells as seen in https://observablehq.com/ - which means any edits you make to values or code (or a UI element) in a cell cause all dependent cells to update automatically
Fantastic first run experience too: "pipx install marimo" and then "marimo tutorial intro"
@simon just played with it and there’s a few rough edged outside of the tutorials but overall this is awesome. I’ve been waiting for something like Pluto from #julia to come to python
Just read the news that HBO Max is cancelling Julia, just as the show was really getting good.
Why not... it's critically acclaimed, has incredibly reviews with both critics and the audience, a 96% on Rotten Tomatoes. That makes all the sense in the world for HBO to cancel it.
I made some cards with DataFrames.jl and Luxor.jl. In previous years I used to calculate the data using Astro libraries, but recently I discovered that NASA supply all the relevant data in CSV format. 😂
Hey I am baer,
a student from germany (currently in my finals) with great interest in #science and #computerscience . This includes #linux and #foss.
I can (more or less) write #rust code and I am looking into #julia and #uiua.
Other things I enjoy are #photograpgy and riding my bike (#lifebehindbars ).
If you want to contact me look at my website pls.
Have a great day
🍪
Para calcular la integral definida usando esa función, tenemos que definir algo parecido a linspace:
def linspace(start,stop,count):
return [x*(stop-start)/(count-1)+start for x in range(0,count)]
from math import pi, sin
x = linspace(0,pi,7)
y = [sin(y) for y in x]
print(simp_int(x,y))
El resultado es 2.0008631896735363, un 0.04% más que el valor real.