The problem is I think Octave missed its window. 20 years ago when I was in grad school, everybody was using Matlab and a competitive open source version would have been a killer app. I looked into Octave at the time, but it was basically a toy at that point. I looked into it recently, and it really has come a long way, and even has an official GUI similar to Matlab's, but these days Matlab is kind of fading out and R is what everybody seems to be using.
0 years ago when I was in grad school, everybody was still using Matlab. Ok, some used R and NumPy but 80% Matlab. Such a collection of sparse matrix routines (direct solve, iterative solve, preconditioning, eigensolvers, SVD) is very useful in applied sciences.
I did my uni ~10 years ago and I made a point of using Octave when everyone else was using Matlab. It worked just great for all the ODE and statistics exercises. Nobody else used it though.
And 10 years ago when I was in grad school (dropped out though), Python was on the rise with numpy and matplotlib. Coming from a programming background, it was an easy choice and I'm still using those today. They've got more usable for people with less programming experience with Jupyter notebooks etc.
Was briefly tempted by Octave, but it just didn't happen.
Or Python. I switched from Matlab to Python and Numpy and Matplotlib and Jupyter a few years ago and haven't looked back. They really are better in many ways.
20 years ago when I was in grad school I did use octave to do my research, and it was 'mostly fine'. (Also I discovered that a couple of the matlab toolboxes I needed were just .m files and there was no technical reason that I couldn't just copy them into a local directory for octave to find; I consider this no worse than 'morally iffy' considering that we had a matlab site license)
