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Having spent a lifetime in both science and engineering departments, I can safely say that the persistent use of Matlab is almost entirely because of entrenchment: the professors learned Matlab, they don't have time/energy/interest to learn a better alternative, and so they use it in their teaching, and the next generation carries the leaden baton onwards. Syntax has very little to do with it; runtime speed has little to do with it; development speed is why it was adopted in parallel with system languages in the first place.

The OP's argument is weakened a little by their Python, which could be simpler (here X is now a 3x1 column "vector"):

   X = np.array([[1, 2, 3]]).T
   Y = np.array([[1, 2, 3],
                 [4, 5, 6],
                 [7, 8, 9]])
   Z = Y @ X
   np.hstack((X, X))
which is almost as readable as the Matlab (and let's not forget those semi-colons and ellipses are awkward too).

The OP mentions "Licensing Pain" without citing the high price of a Matlab license: the issues they mention are real (license server not behaving; shared license not available), but the true problem is that in many parts of the world, the money just isn't there. So people use cracked licenses instead.

As a professor, it makes me wildly uncomfortable to see my colleagues inculcate in the next generation of engineers a lifetime dependence on an expensive, closed-source, commercial product. Free alternatives like Octave and RunMat are nice, but niche: in that respect, I wish the RunMat project the best of luck. I very much hope they don't get targeted by MathWorks lawyers.


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