This makes sense, though, because it isn't really a general purpose language for creating standalone programs. I mean, you can try that, but it is a bit awkward. The usecase is mostly "I've got some matrices and I want to try some things with them before writing a couple thousand lines of FORTRAN with a bunch of ugly BLAS calls."
Most programming languages are tools for making tools. Matlab is the tool itself.
I've seen scripts where you have to set up your matrices, manually put them in particular named variables, and run them through a script that was basically a bunch of matlab shell commands listed one after another. That's not scalable of course, but if elderly professors were willing to mess around with makefiles, dependencies, interfaces, and importing stuff then grad students would all find themselves unemployed.
Yes, if that tool were created, I bet it would be really popular. But it hasn't been. Python+Numpy+Scipy isn't it by virtue of the fact that we have to specify three different software packages, haha.
I've done tiny prototypes that I later turned into a nice little Python+Numpy+Scipy scripts, and the final Python version was much nicer, but writing it was still more like a couple hour project, compared to the real-time process of figuring out what I wanted, done in Octave.
It compares quite favorably. The nice thing is that most of Numpy and Octave functionality is already builtin to Julia (multidimensional matrices are first class as they are in Matlab/Octave). Julia performance is quite good and multiple dispatch is great for composing packages (once you get used to it).
Check out SciML, Julia's answer to scipy (https://sciml.ai/) and Flux Julia's answer to PyTorch/Tensorflow (https://fluxml.ai/). Are these projects as mature as their Python counterparts? To be honest, no they're not, but they are making pretty rapid progress.
I haven't tried it out. It seems really interesting, though. A guy in my group loved it, but he graduated. I haven't yet so I guess we can put at least one point on the board for Julia!
Most programming languages are tools for making tools. Matlab is the tool itself.
I've seen scripts where you have to set up your matrices, manually put them in particular named variables, and run them through a script that was basically a bunch of matlab shell commands listed one after another. That's not scalable of course, but if elderly professors were willing to mess around with makefiles, dependencies, interfaces, and importing stuff then grad students would all find themselves unemployed.