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I use it often. Even after 20 years of using numeric/numarray/numpy, I still feel more productive in Octave and Matlab. Mostly time series analysis, signal pr
by paijiut 6y ago
I use it often. Even after 20 years of using numeric/numarray/numpy, I still feel more productive in Octave and Matlab. Mostly time series analysis, signal processing, image analysis. Occasional modeling and simulation work. I think for me it’s that octave does it’s job well and doesn’t try to do other things. Python grates on me occasionally since it’s libraries seem to lack focus and try to be too much for too broad of an audience. I like focused, simple tools. I do use Python, but not as my sole tool. I don’t understand he mindset that one tool/language should do everything. Easier for me to learn many languages than one language and have to learn many independently designed libraries.
- _0ffh 6y agoI wonder how much of this is due to the availability of the dot-operator syntax beside the extensive libraries and the easy extensibility (just create a new function in the Matlab search path and Bob's your uncle - no further installation or registration rituals needed).
- billfruit 6y agoMatlab never feels a particularly elegant system to me, and most Matlab codebases I have seen are huge messes, with not much structuring and organization. In that respect I prefer python, that it naturally seems to lead to saner manner of organizing code, and also being very helpful in massaging/parsing/reformatting data into forms more amenable to processing.
- marmaduke 6y ago> Matlab codebases I have seen are huge messes I can confirm this, but, Conway's Law suggest that this reflects more the user group that the language. Matlab provides all the typical suspects for structuring codebases (packages, classes, functions, globals, etc) but look what users do with it. This suggests simply that research groups " communication structure"s are huge messes.