«Թվային մեթոդներ»–ի խմբագրումների տարբերություն

==Ծրագրային ապահովում==

 

 

There are several popular numerical computing applications such as [[MATLAB]], [[TK Solver]], [[S-PLUS]], and [[IDL (programming language)|IDL]] as well as free and open source alternatives such as [[FreeMat]], [[Scilab]], [[GNU Octave]] (similar to Matlab), and [[IT++]] (a C++ library). There are also programming languages such as [[R (programming language)|R]] (similar to S-PLUS) and [[Python (programming language)|Python]] with libraries such as [[NumPy]], [[SciPy]] and [[SymPy]]. Performance varies widely: while vector and matrix operations are usually fast, scalar loops may vary in speed by more than an order of magnitude.<ref>[http://www.sciviews.org/benchmark/ Speed comparison of various number crunching packages] {{webarchive |url=https://web.archive.org/web/20061005024002/http://www.sciviews.org/benchmark/ |date=5 October 2006 }}</ref><ref>[http://www.scientificweb.com/ncrunch/ncrunch5.pdf Comparison of mathematical programs for data analysis] {{Webarchive|url=http://arquivo.pt/wayback/20160518062220/http://www.scientificweb.com/ncrunch/ncrunch5.pdf |date=18 May 2016 }} Stefan Steinhaus, ScientificWeb.com</ref>