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posted by janrinok on Monday June 01 2015, @07:28PM   Printer-friendly
from the plot-this dept.

I wasn't aware of the GNU Octave project until I saw a post on Reddit that it had hit version 4.0.0. If you're not familiar with it either, here's a brief overview:

GNU Octave is a high-level interpreted language, primarily intended for numerical computations. It provides capabilities for the numerical solution of linear and nonlinear problems, and for performing other numerical experiments. It also provides extensive graphics capabilities for data visualization and manipulation.

So why is this exciting? Aside from a Windows installer for all you people too lazy to switch to GNU/Linux, it apparently finally got a GUI (kind of a must for "modern" software):

Octave 4.0 is a major new release with many new features, including a graphical user interface, support for classdef object-oriented programming, better compatibility with Matlab, and many new and improved functions.

You can also get the full list of user-visible changes here.

Share and enjoy!

 
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  • (Score: 3, Informative) by Anonymous Coward on Tuesday June 02 2015, @03:00PM

    by Anonymous Coward on Tuesday June 02 2015, @03:00PM (#191158)

    Scipy/Numpy/etc is really useful. However, the Julia syntax is much slicker for numerical tasks, since that was the original purpose. I've been using Julia for quite a bit of my own work. Since it can be nearly as fast as C, development is sped up by not having to write things in Fortran/C.

    Critically, there is a package, PyCall, to call Python code. To do a simple plot with matplotlib:

    using PyCall
    @pyimport matplotlib.pyplot as plt
    x=rand(10)
    y=rand(10)
    plt.plot(x,y)
    plt.show()

    You can barely tell the matplotlib parts are calling out to python. Lisp-style homoiconicity really allows for some pretty cool stuff.

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