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Comment by kyzyl | Hacker News Reader

I'm curious... is the matlabbing that happens at your work related to the simulink/realtime/control parts of matlab? Based on the other things you've said it sounds to me like that might be the case. Obviously I might be wrong.

In any case, I've found that those parts of matlab can actually be used pretty effectively. I think the reason is that, even though matlab as a language is pretty crappy (IMO), these domains aren't actually dominated by programming languages. Take for example industrial control. It's extremely common to use PLC's, PAC's or FPGAs. These tools are, like simulink, largely operated via proprietary graphical environments.

Essentially, I agree with your points for uses of matlab where you don't write much custom code, and/or where your custom code is very insulated from the 'real world' and even from the rest of the system.

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We don't use simulink or anything like that - we just use the typical linear algebra stuff: Markov chains, finding eigenvalues, solving linear systems, etc.

try python. it is much more powerful in almost every sense. And it is not easy to write crappy code in python.

Last I looked, vector and matrix handling was extremely clunky and tacked on in Python.

You would probably use NumPy, which even has a page for people used to Matlab: http://wiki.scipy.org/NumPy_for_Matlab_Users

Can you be more specific?

I'm not the parent commenter but I've used matlab extensively and found Numpy clunky in comparison.

All I ever did in matlab involved matrices (usually differential equations with matrix coefficients and other things of that nature) and matrices are super easy to use in MATLAB:

    A = [1 2 3
        4 5 6];

    A = [1 2 3; 4 5 6];

I can input A just like that and it works, try out the python syntax:

    A = array([[1,2,3],[4,5,6]])

And it just goes on from there.

Even if you're doing complicated operations because matrices are the essential building blocks of MATLAB it is easy to use, not so much in python.

I tried building my FEA (finite element analysis) project in python after i finished programming it in matlab it and found it to frustrating to continue.

Matlab has a terse syntax for 2D matrices. Try creating 3D, 4D and 5D matrices, and the syntax is suddenly completely different.

I've seen abominable code written in python from academics.

ya ya, its possible but hard :D

It's very easy to write crappy code in python. And that's why I love it - it doesn't try to protect the programmer from themselves, instead it lets you do what you want (for better or worse). Compared to languages like java...

And that's the thing with Matlab, it does the math part really well

Maybe R and Numpy are getting better, but try to invert a matrix, find and eigenvalue, find the solution to a polynomial, fit an equation, etc Not to mention the most advanced things outside Matlab

You mean like this? http://docs.scipy.org/doc/numpy/reference/routines.linalg.ht...

Yes, as I said, it's getting better.

Simulink is a whole different world inside Matlab as well

Here's something that doesn't look like it's covered by NumPy 100% http://www.mathworks.de/de/help/signal/ug/iir-filter-design....

> Here's something

Yeah that's exactly the kind of stuff I meant when I was talking about pulse coding and such. Although the last time I had to do some filtering stuff I did manage to use python+scipy, but yeah it hasn't progressed as far as matlab in a lot of those niche engineering areas yet.

Well, matlab--ahem, matrix lab--does certain bits of math quite well. But I would say that R/numpy are most than just 'getting better'. They literally do every thing you just mentioned, and typically their implementations go beyond matlab's.

Where I've found matlab to still be ahead is in the area of domain specific engineering. For example, if you want to manually pulse code a signal using some specific modulation scheme, matlab has a tool for just that. In python you still have to manually write a bit, interface it to the fitting routine, and convolve it across your signal.

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