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Comment by CharlesW | Hacker News Reader

For anyone else who hadn't heard of Octave, it's an open source near-clone of the proprietary MATLAB: https://en.wikipedia.org/wiki/GNU_Octave

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"near clone" is a bit exaggerated. As much as I'm a free software zealot, I don't think Octave comes close to matlab yet (provided you do anything a bit more advanced than the practical of some courses)

See https://stackoverflow.com/questions/12084246/differences-bet...

I don’t think Matlab or Octave are great languages for software engineering. Actually, these languages are like example #1 of the difference between engineering software vs software engineering: they are excellent tools for writing, like, 10-100 line numerical experiments.

Anyone who runs up against a limitation of Octave has probably hit the point where they should consider switching, but not to Matlab or some other scripting language, but to Fortran or maybe Julia or something.

Therefore, I disagree with the accepted answer in that StackOverflow thread. The language is only good in the first place for short codes anyway, so fixing any little octave/matlab regionalisms is not a big deal. And, since it is a mathematical experiments, you should understand what every line of code does, so running the code without reading it is not really an option.

They are never meant for general software engineer but for numerical analysis/data analysis and engineering. In fact they are quite horrible for writing general software code -- the APIs for IO and HTTP requests are very lacking compared what you can find in other languages, for example.

I haven't found a better CLI calculator utility for writing more than one-liner numerical stuff with some plots than MATLAB and octave. They're fantastic.

Python is trash, by comparison.

You think MATLAB is better than (checks notes) a scripting language for writing one liners/throwaway code? Is that what you're saying here? Lol

>a scripting language for writing one liners/throwaway code

Just objectively not an accurate description of Python

1000% yes, because this kind of stuff is not oneliners and you don't want to throw it away.

You also don't have the rats nest that is python environment and package management.

> 10-100 line numerical experiments

There's plenty of satellites, rockets, re-entry vehicles whose guidance and control code were designed and written using MATLAB/Simulink and then "autocoded" to C using "MATLAB Coder".

While not my preferred way of doing things, it is popular for this purpose throughout the aerospace industry.

People who use MATLAB use it for the toolboxes.

The language itself is awful.

> The language itself is awful.

As a programming language freak, I must disagree... in what other programming language can you solve a linear system Ax=b in one line

    x = A\b

without any external libraries or imports, just with the base language?

I never used any official matlab "toolbox", but still love the language via the octave interpreter. It's so clean and straightforward!

> without any external libraries or imports

Why does this matter in the least? Like you must understand that this is a library call right? Like just put `import numpy as np` in your PYTHONSTARTUP and it's the exact same UX in python.

https://docs.python.org/3/using/cmdline.html#envvar-PYTHONST...

Well, in Julia, for one.

Also APL: b ⌹ A

GNU Maxima.

Not a general purpose one, but good enough.

Also, qalc from libqalculate for trivial stuff.

In Python you can use a library, then it is: x = np.linalg.solve(A, b). But yeah, Octave is nice, because it stays very symbolic.

In R, this is: x <- solve(A, b)

Matlab/Octave is great for numerical programs that perform within an order of magnitude of Fortran. If some things aren't fast enough, you can rewrite them in C or Fortran without too much trouble. If you're doing anything other than numerical computing, it's awful, and you should use a different language.

(Source: I did a PhD using a mixture of Octave for numerical stuff, Perl for text-processing and automation, and C++ for the parts that were too slow. Choose the right tool for the job.)

Modern Fortran is better all around. The compiler will check usage based on interface. It has a working and supported module system (unlike C++). A couple of openmp pragmas will parallelize it. Multidimensional dense arrays are first class objects. The compiler can emit code with array bounds checking. Keyword and optional arguments. Standardized C FFI. f2py inter-op with Python/numpy.

Most people encounter large FORTRAN IV or FORTRAN 77 heirloom codes, and assume that's what Fortran is like in 2025.

Early versions of Andrew Ng's ML MOOC used Octave, if you are looking for examples and exercises.

YouTube playlist: https://www.youtube.com/playlist?list=PLiPvV5TNogxIS4bHQVW4p...

Oh, the times when Coursera and Udacity were just starting... They were supposed to disrupt academia, it's a shame they never actually did.

There's a great recent book (Anne Trumbore's _The Teacher_in_The_Machine_) on using technology to "disrupt" education (starting much earlier than you would think, with mechanical devices in the early 20th century that could drill students with multiple choice questions, running through basically pre-computer MOOCS that used radio and then TV to broadcast lectures, various educational software, and finally MOOCs like Coursera and Udacity).

The real value of a degree unfortunately isnt the education it's the exclusivity of the program. When bootcamps realized this some started having more stringent admissions.

I was in one of those early cohorts that used Octave, one of the things the course had to deal with was that at the time (I don't know about now) Octave did not ship with an optimization function suitable for the coursework so we ended up using an implementation of `fmincg` provided along with the homework by the course staff. If you're following along with the lectures, you might need to track down that file, it's probably available somewhere.

Using Octave for a beginning ML class felt like the worst of both worlds - you got the awkward, ugly language of MATLAB without any of the upsides of MATLAB-the-product because it didn't have the GUI environment or the huge pile of toolbox functions. None of that is meant as criticism at Octave as a project, it's fine for what it is, it just ended up being more of a stumbling block for beginners than a booster in that specific context.

It’s nice to know that someone else suffered this pain. And that i bet on PGMs which really turned out to be the wrong horse…

ha! I took at least one PGM class myself. I had a difficult time with the material.

I did that with Octave too. I didn't mind the language much, but it wasn't great. I had significant experience with both coding and simple models when doing it, so I wasn't a beginner; I can see it being an additional hurdle for some people. What are they using now? Python?

Believe Andrew Ng's new course is all Python now, yeah. Amusingly enough another class that I took (Linear Algebra: Foundations to Frontiers) kinda did the opposite move - when I took it, it was all Python, but shortly after they transitioned to full-powered MATLAB with limited student licenses. Guess it makes sense given that LAFF was primarily about the math.

I used octave in place of matlab in undergrad numerical analysis course 15 years ago. The language was completely compatible for what we did.

I'm not a Matlab user, but from what I can tell, even if the language can be cloned, there's a lot more to Matlab: It's a GUI driven software suite, with a lot of pre-written apps that eliminate the need for coding in many cases.

It comes with vendor support and "official-ness" for lack of a better word.

Things are changing rapidly in this area but it wasn't very long ago that most people reacted to open-source software as something weird that shouldn't be trusted.

Scilab is another MATLAB clone, but emphasizes features rather than compatibility.

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