Hi there. I have recently finished a class on multiphysics simulation, using Matlab, FlexPDE, and AnSys, to simulate everything from porewater movements to vibration to thermomechanics to electrodynamics to fluid mechanics and turbulence. Each of the above tools are beautifully useful, extremely flexible, and can plot really nicely. I am trying to figure out if I can focus on Julia as a tool for Numerical Multiphysics design within a full computer language -- I want this kind of flexible power, lets say even just FlexPDE or PDETools in Matlab what book or package should I be learning? What if ..read more

In a base module, the code @ = 1 fails. What other symbols or glyphs are reserved in Julia? Can I get a complete list? Is "@" defined in Core? Or is it part of the language of Julia (like "if")? submitted by /u/stvaccount [visit reddit] [comments ..read more

I have the following code: using LinearAlgebra *(A::Matrix, B::Matrix) = begin println("matrix multiplication") C = Matrix{Float64}(undef, size(A, 1), size(B,2)) mul!(C, A, B) end mat = [1 2; 3 4] mat * mat It works! But is there any more idiomatic way to reference the original multiplication? My workaround is to use "mul!" but I would like to call instead of "mul!" the original * that I am overriding. submitted by /u/stvaccount [visit reddit] [comments ..read more

Best book recommendation for someone learning coming from an R/Python background? Special focus on functional programming, structs and vector operations would be great. TIA! submitted by /u/seg006 [visit reddit] [comments ..read more

submitted by /u/ChrisRackauckas [visit reddit] [comments ..read more

I do a lot of constrained optimization and have used the trust region reflective algorithm in matlab and python but haven't been able to find it for julia. Does anyone know whether it might be included anytime soon since I'm not knowledgeable enough to write it myself? submitted by /u/red1tterr [visit reddit] [comments ..read more

Hi, everyone. ​ I had write by myself an penalty method with ForwardDiff, and i need to compare with an already implemented method. I know that MATLAB has the fmincon function, which is used to allow minimization with non-linear restrictions. However, i didn't found something relatable in Julia. ChatGPT suggested something like NLopt, but i was unable to use it together with ForwardDiff. ​ Does anyone knows how to council both or if there's already a more friendly (plug-and-play) alternative else than NLopt? submitted by /u/Jan_van_Rosenhout [visit reddit] [comments ..read more

I've recently begun exploring real-time streaming data, primarily using PyFlink. Given Flink's close integration with JVM-based systems, I'm curious about alternatives that leverage Julia. Are there any Julia tools or libraries for working with Kafka that offer capabilities similar to Flink for real-time stream analysis? Considering Julia's performance and ease of development, it seems like a potentially great fit for this domain. submitted by /u/USMCamp0811 [visit reddit] [comments ..read more

Hi guys, do you have any julia projects where you compare them with python projects. I would like to know the performance of Julia. Also i would like to know in what kind of projects Julia is so much better submitted by /u/pussydestroyerSPY [visit reddit] [comments ..read more

I'm learning Julia and I noticed that I could use the function isodd to check if a number is odd. In Python, for example, one could simply use the fast bitwise and n&1 to check if n is odd, so I was curious about what is the implementation of isodd in Julia. So, if n is a Number, it is converted to a Real and then checks if the remainder when divided by 2 is not zero. Which already seems to be inefficient? Going back again to the Python example, I feel that n%2!=0 is slower than n&1. https://preview.redd.it/oyrjswdm29xc1.png?width=452&format=png&auto=webp&s=d189cccfd7e2258 ..read more