This has been around for a while. However, it's clear to most people now that Python/Scipy is a better solution, rather than simply trying to copy Matlab. Python as a language is far, far better than Matlab. And the ecosystem has matured a lot, to the point that for many research algorithms, the Python offering is superior to the Matlab one.
It is interesting to note that ESI, the company that is sponsoring Scilab development, has recently hired the lead Octave developer too:<p><a href="http://lists.gnu.org/archive/html/octave-maintainers/2017-09/msg00053.html" rel="nofollow">http://lists.gnu.org/archive/html/octave-maintainers/2017-09...</a><p>This follows up on this story:<p><a href="https://news.ycombinator.com/item?id=13603575" rel="nofollow">https://news.ycombinator.com/item?id=13603575</a><p>Furthermore, reports of the death of Matlab (in favour of Python) have been greatly, <i>greatly</i> exaggerated.
It's not immediately clear from the homepage how this is different from Octave.<p><a href="https://www.gnu.org/software/octave/" rel="nofollow">https://www.gnu.org/software/octave/</a>
I’m a long term Matlab user who now enjoys using Python. Students still like to stick to Matlab because of its pretty simple IDE and decent documentation. The various Python IDEs like Canopy and PyCharm are too often complicated for engineering students who just want the simplicity of Matlab’s Workspace to get whatever problem they have solved.
Scilab is ancient; I was using it in grad school. They also made a decision at one point to make it just slightly incompatible with Matlab, which was probably a mistake. Octave is actually better at this point; they've managed to reproduce the best of Matlab's UI, which was always quite good.<p>While I rarely develop things in Matlab, it is worth noticing that it is a very elegant way of expressing linear algebra and numeric oriented programs. Python is a vastly more useful language, but numerics are an afterthought, and expressing numerics is abominable in Python. When I'm looking up how to implement some classic numerics algorithm, the Matlab way is usually concise and its vector oriented operations are usually the right way to express it in any interpreted language, as it keeps you in Lapack-land (remember, Matlab's origins were a repl for Eispack/Linpack).
As we are comparing to MATLAB.<p>I'm wondering why there is no comment about the toolboxes in MATLAB. Several standard toolboxes are the main reasons, that I'm still staying in MATLAB.
I thought that Scilab was well known. I used it in the uni during my degree in Maths.<p>I prefer Matlab, but Scilab is still pretty decent. I haven't tried Octave, so I can't compare the two of them.
How does this compare to Octave? (<a href="https://www.gnu.org/software/octave/" rel="nofollow">https://www.gnu.org/software/octave/</a>)
I am surprised that Julia hasn't been mentioned yet. It is the language/program that I normally use when I don't want or for some reason cannot use MATLAB. Many times I don't want to start MATLAB because of how ling that process takes on my computer, especially for easy tasks. I definitely recommend checking out Julia.<p>Main website: <a href="https://julialang.org/" rel="nofollow">https://julialang.org/</a>
Cloud: <a href="https://www.juliabox.com/" rel="nofollow">https://www.juliabox.com/</a>
"Batteries included" IDE: <a href="https://juliacomputing.com/products/juliapro" rel="nofollow">https://juliacomputing.com/products/juliapro</a>
As soon as you ask me for a name,email, DNA sample, etc for a download...you lose. Python doesn't do that. Which is why it is kicking Scilab, Matlabs et al arse.