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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

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. 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).

mkl 9y ago
> 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 This is a really strange statement to me. Python has much better syntax for vectorised operations than Matlab. I have written a great deal of both (Python by choice, Matlab when required to), and in my experience almost everything numerical is easier to express in Python. Numpy is in large part a thin wrapper over fast low-level libraries, but with an excellent well-designed interface, unlike the undesigned growth-by-accretion of Matlab.
- newen 9y ago
  I don't think you've worked a lot with numpy. Matrix indexing is a nightmare in numpy and the documentation for just it is 3 pages long.
  - mkl 9y ago
    I've worked a lot with numpy (hundreds to thousands of hours, depending exactly what you count). I've also worked with numerical arrays in several other languages, and of those I've tried I've found numpy the cleanest and simplest. What specifically do you see as nightmarish?

mkl 9y ago

> 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 This is a really strange statement to me. Python has much better syntax for vectorised operations than Matlab. I have written a great deal of both (Python by choice, Matlab when required to), and in my experience almost everything numerical is easier to express in Python. Numpy is in large part a thin wrapper over fast low-level libraries, but with an excellent well-designed interface, unlike the undesigned growth-by-accretion of Matlab.

newen 9y ago
I don't think you've worked a lot with numpy. Matrix indexing is a nightmare in numpy and the documentation for just it is 3 pages long.
- mkl 9y ago
  I've worked a lot with numpy (hundreds to thousands of hours, depending exactly what you count). I've also worked with numerical arrays in several other languages, and of those I've tried I've found numpy the cleanest and simplest. What specifically do you see as nightmarish?