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GNU Octave 6.1.0

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41–50 of 100 posts

Re: GNU Octave 6.1.0

#41

A general note that applies to some comments in this discussion, but to any discussion of Matlab on HN. Yes, Matlab is still used heavily, even for new code, and it will continue to be used for many years into the future. It doesn't really add much to the conversation to generalize from the small sample that is your slice of one industry/your employer/your inner circle of friends to conclude that Matlab is dead. Acco…

None of the comments right now really suggests Matlab is dead?

Re: GNU Octave 6.1.0

#43

When I left university and did not have access to MATLAB anymore, I spent many a nights hacking away at GNU Octave. I have fond memories of Octave. I thought Octave will be a valuable skill when I enter the industry but I could not have been more wrong. Does anyone still use Octave? Is it worth learning? What tools or languages would you recommend as alternatives to someone graduating from university today?

I worked at a university lab throughout undergrad and grad. I wrote a lot of MATLAB. I graduated and got a job as an engineer at a lab in another university. I write a lot of MATLAB.

Re: GNU Octave 6.1.0

#44
post #4

I've always preferred MATLAB to Python as the more engineer-friendly programming language. The interface was a plus as well. That being said, given the sheer amount of scientific libraries for Python and universities moving towards it as well, I'm wondering if the effort to maintain Octave is worth it. One use for it could definitely be running older MATLAB scripts that have deprecated language features. Those were a…

I spent the majority of my career porting MATLAB to C++. We charge about $70 an hour ($200 billable man-hour) to do it. It’s a slow and arduous process. Often times the features that are running in Matlab needs some C++ library that prevents the sort of speed increase that you hoped to gain out of the C++ port, so a C++ reimplementation of the toolbox needs to be developed anyway; this loosing the benefit of the “verified“ toolbox. Python, on the other hand can be improved for performance piece-wise through tools like cython and swig. Of course, both offer a C interface, but I prefer the python one to MEX files for a variety of reasons. Also, you don’t have to pay a license to use python. (Same library implementation problems)

Add a minimum, if the MATLAB folks would at least consider moving over to Octave we could illuminate some of the licensing fees, but... once performance matters, you’re still going to have to pay a full-time software engineer to port Octave code to make it performant.

Re: GNU Octave 6.1.0

#45
post #32
post #18

What value can Octave give me, relative to python?

A horror show mentally reconciling its one-based indexing with the zero-based indexing you're used to in Python. The use of a zero is admittedly a relatively new concept, and it may not catch on.

Not only that. Octave/Matlab indexes end at the last point. x = 0:20, ends at 20, not 19.

Re: GNU Octave 6.1.0

#46
post #39

I wish Octave the best of luck, but it faces an uphill battle against MATLAB (established engineering projects) and Python (new starts). The biggest issue with Octave for me is the slowness of its plotting compared to MATLAB. A major use case for me is visualizing large data sets. I can generate data using any backend (Python, C++, MATLAB, etc.) and want the ability to plot it, zoom in/out to a rectangle, filter to a…

Is Julia not the new player in that game?

Re: GNU Octave 6.1.0

#47
post #13

Is it worth learning Octave/Matlab for ML or Data analysis work? Does anyone use it outside the engineering/scientific research community? Since Andrew Ng teaches his ML course in it, I'm curious. However, I'm wondering if learning Julia or R will be better for my career. I mostly use Python/SQL at work as a data analyst.

Thanks for the replies. I did a course on Data Analysis from MIT and used R a bit there. I liked GGplot and RStudio. I don't think Python has anything close to those two. R was a bit harder to learn and I've already forgotten most of it, since I don't use it. I understand that it's based on Scheme and has roots in functional programming. I'm curious about Julia as it's being promoted as one of the fastest languages. I don't see a lot of value in that as I do most of my data intensive (in terabytes) work on pySpark on AWS clusters before I touch Pandas or any other BI tool. I couldn't use Julia on my laptop to do that! I guess sticking to R has more short term benefit as most courses on Statistics are heavily dependent on R. Julia will probably catch up soon.

Re: GNU Octave 6.1.0

#48
post #34

Could this project be threatened by Mathworks if SCOTUS rules that APIs themselves get copyright?

I don't think so. I imagine it would be very hard for Mathworks to claim copyright over mathematical functions and established terms such as "fft" or "rms".

On top of that, Octave isn't even in competition with MATLAB. The much higher performance and capabilities offered by MATLAB that aren't available in Octave (like C++ export including support for GPU acceleration) along with professional support are enough to keep the target audience from considering Octave over MATLAB.

Octave isn't encroaching on MATLAB sales, so I don't think such ruling would be an issue as I doubt that Mathworks would even consider legal action.

Even if they would for whatever bizarre reason, it'd be sufficient to just change the names and parameters of some functions - lots of work, sure but ultimately not too big an issue.

A script could be used to translate between the dialects and people using Octave over MATLAB would continue to do so, since their motivation for choosing Octave wouldn't change due to this.

At least that's what I think.

Re: GNU Octave 6.1.0

#49
post #2

Ask HN: Can GNU Octave be used as full MATLAB replacement?

In a similar sense that LibreCalc is a replacement for Excel.

Well, I don't think so. LibreCalc is much more competitive in terms of performance.

Octave doesn't even come close to MATLAB performance especially when dealing with large datasets and plots.

Re: GNU Octave 6.1.0

#50
post #39

I wish Octave the best of luck, but it faces an uphill battle against MATLAB (established engineering projects) and Python (new starts). The biggest issue with Octave for me is the slowness of its plotting compared to MATLAB. A major use case for me is visualizing large data sets. I can generate data using any backend (Python, C++, MATLAB, etc.) and want the ability to plot it, zoom in/out to a rectangle, filter to a…

Is Julia not the new player in that game?

Julia is a new player but probably still "too new" for most people (I say this as a Julia fan). Python is a pretty old language at this point, but the data sciencey eco system has only matured relatively recently (compared to the age of Matlab anyway).
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