I am going through the process of creating my first video on youtube. This will probably be a series about thermodynamic modelling, which is a subject I am interested in. The question is: should I make it in matlab (which is easier for me and very fast) or in python (which is way too slow for anything serious but which more people know)? People of QOTO, what are your thoughts on the subject?
#STEM #help #question #thermodynamics #programming #matlab #python
@nwerneck
Matlab is fast enough for the most part, to be honest... Are there good nonlinear optimization libraries for julia? I remember trying like 1.0 version, wasn't exactly smooth.
@nwerneck
This sounds interesting, thanks for info! I decided to stick with octave for my next project, but Julia looks like something worth learning.
@zpartacoos
It is true, but I'm more interested in native features, to be honest. Also, lack of semicolons triggers me :D
Plus for every package there is a syntax to learn, which kinda makes it troublesome. I am considering Julia, as @nic@nwerneck pointed out, it is an option. I might go full out nerdiness and code in pure c/c++, though...
@academicalnerd I'll also be posting videos soon btw. Mostly about the intersection between computer science, mathematics and neuroscience. I'm thinking of using Python first for the ease of explanation and teaching basics of programming, then Haskell for more of the pure mathematics and Rust for the computationally heavy tasks as I feel there is no need for C/C++ due to memory safety. If you are interested it might be nice to share content on this thread once it's published.
@zpartacoos
Yeah, would be nice. I think I'll opt for Octave for now since it's a decent replacement for matlab. And my love for c/c++ is mostly irrational because it's the first language I learned and keep using to this day.
@academicalnerd I'm curious if this is actually the case. People have this believe that Python is a turtle (true for native python) but most scientific python packages can even be faster than Matlab since they're written in C and use Python's Foreign Function Interface (FFI). So, if you're doing linear algebra with Python and use a package like Numpy you'd see similar speeds to native C code...