Re:JupyterLab is ready for users
by bitL on Tuesday February 20, 2018 @09:53AM
(#16420709)
That's all nice but you go to real-world space/robotics/drones etc. shops and they all use Matlab or similar for their scientific computation and validation and treat Jupyter stack as a toy. Similar to telling a photographer to use Linux because there is GIMP and that should be enough for them.
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Re:JupyterLab is ready for users
by neuromantik8086 on Tuesday February 20, 2018 @12:27PM
(#16422065)
I think a better analogy would be how large swathes of the population use Windows for everyday computation and treat Linux as a toy, whereas individuals with more domain knowledge take Linux seriously and use it in production in a variety of environments (e.g., high frequency trading, web hosts, commerce sites, etc). Engineers may prefer MATLAB as a "serious" development environment, but most software developers find it to be seriously lacking. Most general purpose programming languages are far more powerful than MATLAB, but simply lack the toolboxes/convenience. Both of these points are nothing new and have been observed since the creation of MATLAB (indeed, the latter is the reason why MATLAB was created, since MATLAB is basically supposed to be a pretty face for FORTRAN).
Re:JupyterLab is ready for users
by _coveredInBees on Tuesday February 20, 2018 @12:25PM
(#16422039)
Yeah, I work at a startup where we specialize in signal processing + ML. We have a robust set of infrastructure in MATLAB (use our own ML libraries rather than MATLAB's libs) and try as we might, we haven't been able to switch altogether to Python (despite a number of us being fans of Python).
MATLAB has a TON of things that you don't get with Python + Numpy + Scipy. Complicated plots/graphics with interactivity are a pain point in Python compared to MATLAB. Similarly, the debugging capabilities in MATLAB are truly magical compared to a pretty terrible experience on the Python side of things. Even though we deploy software in Python, we are much faster prototyping in MATLAB and deploying finalized algorithms/software to Python than trying to do everything in Python from the get go. MATLAB's JIT is also pretty great and while Numba is pretty great, it still requires more work and can be brittle at times.
Have you tried bokeh for interactive visualizations? https://bokeh.pydata.org/en/latest/
You can really do photography on Linux nowadays though. Darktable and rawtherapee are shaping up nicely.
I am a pro photographer and still have to use Lightroom for proper color adjustments. I even had competitions with Darktable pros to see who can get a better picture and unfortunately Lightroom was outclassing them (and I hate Adobe's forced subscriptions). It still needs a lot of work to be cutting edge.
Can you share some specific weaknesses Darktable has? (I've never used either.)
But Matlab has much less restrictive terms when it comes to code, right?
And then there's LabView, used widely for lab and process automation, which really has no open-source or free alternative.