Scientific computing advice needed

AI Thread Summary
Advice on science-related software for budding physicists emphasizes the importance of focusing on widely used tools in professional settings. Open-source options like Octave, R, and gnuplot are highlighted as accessible choices for users with budget constraints. While Octave and gnuplot are already familiar to some users, there is a recognition of their limitations, particularly in error analysis capabilities. The discussion acknowledges that software preferences vary significantly based on individual needs and specific fields of application. Notable commercial software includes Mathematica, Matlab, and Maple, but the emphasis remains on free alternatives due to financial limitations. Programming languages such as C and Fortran are also mentioned, with the understanding that learning one language can facilitate the acquisition of others. Scilab is suggested as another viable option for scientific computing. Overall, the consensus is to prioritize tools that are prevalent in real-world applications while considering personal comfort and budget.
freemind
Hello folks,

I'm a budding physicist who needs advice on science-related software that's used in The Real World (TM). I've recently had a look at Octave, Maxima, matplotlib (python plotting), gnuplot, Ocaml and "The R environment for statistical computing". Problem is, I can't make up my mind on which to learn. Given my goldfish-like memory, familiarising myself with the syntax of all those applications/languages is quite unfeasible.
Hence, I'd like to know what some of the professionals use at work, so I can focus on those instead of all - worse yet, focus on only some of them which don't find much usage outside their respective developer communities. I'm completely an open-source user (would like to be a contributor as well), due to my non-existent budget - and I'd rather not obtain proprietary commercial software by illegal means. Please feel free to post other languages/apps as well.

Thanks.

P.S: I've been using Octave and gnuplot (with a little bit of maxima) for my university lab-reports so far. I'm relatively comfy with those, but I do find the lack of error-analysis capabilities to be a hindrance.
 
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I think the variety of software people use in the 'real world' is about as varied as the number of people using them and where the software is being used. you'll likely get different answers from everybody who responds.

That said, the big ones are probably Mathematica, Matlab and Maple. Personally, I go with the free/open source alternatives since I have no budget for software (no budget for much of anything really). My tools of choice are
[*]programming: C, Fortran, PHP, shell
[*]Math: Octave, FreeMat
[*]Statistics: R
[*]Productivity: Excel, Word, OpenOffice, LaTeX
[*]Graphing: Excel

As far as programming goes, once you've learned how to program in one language, learning other languages is usually just a matter of learning the syntax. The programming principles remain the same.
 
Thanks for the insight imabug. I guess I'm on the right track in terms of software and languages. I really didn't realize that there would be a large variation (I thought MATLAB and C would be the only major ones).
 
hi,
There are somethings like scilab. Good for use.
 
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