What advantages MATLAB has over SCILAB and vice versa?

I can't get into the nitty-gritty details, as I haven't used SCILAB extensively.

I can't get into the nitty-gritty details, as I haven't used SCILAB extensively. But from a bird's eye view, MATLAB is a very polished software, with decades of development behind it. And a price to match.It has a huge array of specialized packages, good support, a reasonably well designed UI, and it's generally user-friendly enough for non-computer engineers to work with.

It's also very common in the industry, so it's not a bad thing to have on your resume. But if you don't have very complex needs (which I suspect, given the use I made of MATLAB during my undergrad years) and you don't need the robustness and polish of a professional package, SCILAB will probably meet your needs. And since it's based on the MATLAB language, what you'll learn can be transferred later on if your needs change, or you find yourself working in an environment where MATLAB is the default.

Scilab is to MATLAB as OpenOffice is to MS Office. That is to say, it's a not-quite-a-clone, and it's not as polished. You do get most of the functionality of MATLAB, and the price is much more agreeable.

That said, if you want a free/open pretend MATLAB, I personally prefer Octave, since the syntax is closer to MATLAB's. If you aren't bothered about MATLAB compatibility, then check out the statistics language/environment R, which is delightful.

Matlab is the de-facto industrial standard, is ready now and here, and has a big firm behind to push it. Scilab has been for long time the open source alternative, but honestly it never appealed me. I think that or they never belived enough on the project, or that you need too much money to make a valid product of this kind.

And it is a real pity, since we desperately need a good open source alternative, because being open source is the only way to be very efficient on different platform: actually matlab is very good at prototyping small-medium programs, but since it is closed source, it's very difficult to scale it up, to supercomputers for example, requiring often a complete rewrite of the code. Sage might be the third way, it has a lot of potential, and I would bet on it. Check it.It doesn't reinvent the wheel like Scilab did, but take existing software and merge it in a new program.

It is based on python which gained a lot of momentum in the computing world, since it has shown to be both easy enough to quick prototype, and versatile enough to run on exotic platforma like supercomputers or GPGPU. @ MatlabDoug It is feasible in small-medium environment, but on very big task the flexibility of open source is invaluable. Starting from low-level tool like open-mpi that allows you to finely tune your applications, through higher-level framework like PETSc that lift a lot of work from your shoulders, to java and python implementations that let you concentrate on the algorithms forgetting about many of the headaches of the lower level languages.

But the real proof is that an astonishing majority of the top500 supercompunters prefers open source alternatives.

Mathworks. Com/products/parallel-computing – MatlabDoug Feb 10 '10 at 16:35 @MatlabDoug I answered ;) – Mascarpone Feb 10 '10 at 20:31.

I cant really gove you an answer,but what I can give you is a way to a solution, that is you have to find the anglde that you relate to or peaks your interest. A good paper is one that people get drawn into because it reaches them ln some way.As for me WW11 to me, I think of the holocaust and the effect it had on the survivors, their families and those who stood by and did nothing until it was too late.