<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>the__alchemist</author><text>Another take: There&amp;#x27;s value in using a compiled language here. I&amp;#x27;m an amateur dabbling in computational chemistry, and my weapon of choice is Rust. (After starting using Python). Why:&lt;p&gt;&lt;pre&gt;&lt;code&gt;  - Fast, in an area where speed is important
  - Can be made faster for repetitive tasks by communicating with a GPU using Vulkan, CUDA etc
  - Can incorporate a GUI, and 3D graphics, which helps for exploring things visually, tweaking parameters, doing time simulations etc.
  - Can share. Ie, I showed my brother yesterday by sharing a 10Mb executable. Matlab has license complications and you need it installed. Sharing Python programs is a disaster. (Docker? Pip? Pyenv? Poetry? Virtualenv? System Python? System dependencies for the C and Fortran dependencies?)&lt;/code&gt;&lt;/pre&gt;</text><parent_chain><item><author>wwfn</author><text>Open science depends on open tools! Octave is such a good resource for otherwise walled off code (that doesn&amp;#x27;t use newer matlab features). But I&amp;#x27;m curious where octave is popular. Does anyone pick it over julia or python when starting a new project&amp;#x2F;research?&lt;p&gt;I also wish the state of science&amp;#x2F;engineering software shook out differently. There&amp;#x27;s plenty of money to pay Mathworks. Is there some kind of license like pay us if you&amp;#x27;re doing commercial work or publishing research on grants worth over $XXX, otherwise consider it open source?</text></item></parent_chain></comment><story><title>GNU Octave</title><url>https://octave.org/index</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>fluidcruft</author><text>I used to use it a lot, but the python libraries are much further ahead at this point. For my uses (essentially image processing and statistics) Octave is always playing catchup with Matlab but python is mostly at par or ahead of Matlab. With the exception of the parallel stuff... but that wasn&amp;#x27;t anything Octave had either. Eventually when I need performance again I&amp;#x27;ll see about figuring out how to migrate parts to Julia. One thing I like about the python things is there are some hints of IDL in there (I&amp;#x27;m a masochist and liked IDL... Matlab frustrates me at times). Matlab was great for slapping quick UIs together and making little tools, but Jupyter works well enough for that.&lt;p&gt;The 0 indexing in python does really and truly suck sometimes though.</text><parent_chain><item><author>wwfn</author><text>Open science depends on open tools! Octave is such a good resource for otherwise walled off code (that doesn&amp;#x27;t use newer matlab features). But I&amp;#x27;m curious where octave is popular. Does anyone pick it over julia or python when starting a new project&amp;#x2F;research?&lt;p&gt;I also wish the state of science&amp;#x2F;engineering software shook out differently. There&amp;#x27;s plenty of money to pay Mathworks. Is there some kind of license like pay us if you&amp;#x27;re doing commercial work or publishing research on grants worth over $XXX, otherwise consider it open source?</text></item></parent_chain></comment><story><title>GNU Octave</title><url>https://octave.org/index</url></story>