Array programming: Difference between revisions

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In [[computer science]], '''array programming''' refers to solutions which allow the application of operations to an entire set of values at once. Such solutions are commonly used in [[computational science|scientific]] and [[engineering]] settings.

Modern programming languages that support array programming (also known as [[vector (computing)|vector]] or '''multidimensional''' languages) have been engineered specifically to generalize operations on [[scalar (computing)|scalar]]s to apply transparently to [[vector (geometric)|vector]]s, [[matrix (mathematics)|matrices]], and higher-dimensional arrays. These include [[APL (programming language)|APL]], [[J (programming language)|J]], [[Fortran 90]], [[MATLAB]], [[Analytica (software)|Analytica]], [[TK Solver]] (as lists), [[GNU Octave|Octave]], [[R (programming language)|R]], [[Cilk Plus]], [[Julia (programming language)|Julia]], [[Perl Data Language|Perl Data Language (PDL)]], and the [[NumPy]] extension to [[Python (programming language)|Python]]. In these languages, an operation that operates on entire arrays can be called a ''vectorized'' operation,<ref>{{cite journal |title=The NumPy array: a structure for efficient numerical computation |author=Stéfan van der Walt |author2=S. Chris Colbert |author3=Gaël Varoquaux |name-list-style=amp |journal=Computing in Science and Engineering |volume=13 |issue=2 |pages=22–30 |publisher=IEEE |year=2011 |doi=10.1109/mcse.2011.37|bibcode=2011CSE....13b..22V |arxiv=1102.1523 |s2cid=16907816 }}</ref> regardless of whether it is executed on a [[vector processor]], which implements vector instructions. Array programming primitives concisely express broad ideas about data manipulation. The level of concision can be dramatic in certain cases: it is not uncommon{{Example needed|date=September 2021}} to find array programming language [[one-liner program|one-liners]] that require several pages of object-oriented code.

==Concepts of array==

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==Languages==

The canonical examples of array programming languages are [[Fortran]], [[APL (programming language)|APL]], and [[J (programming language)|J]]. Others include: [[A+ (programming language)|A+]], [[Analytica (software)|Analytica]], [[Chapel (programming language)|Chapel]], [[IDL (programming language)|IDL]], [[Julia (programming language)|Julia]], [[K (programming language)|K]], Klong, [[Q (programming language from Kx Systems)|Q]], [[MATLAB]], [[NumPy]], [[GNU Octave]], [[Perl Data Language|PDL]], [[R (programming language)|R]], [[S-Lang (programming language)|S-Lang]], [[SAC programming language|SAC]], [[Nial programming language|Nial]], [[ZPL (programming language)|ZPL]] and [[TI-BASIC]].

===Scalar languages===

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==Third-party libraries==

The use of specialized and efficient libraries to provide more terse abstractions is also common in other programming languages. In [[C++]] several linear algebra libraries exploit the language's ability to [[operator overloading|overload operators]]. In some cases a very terse abstraction in those languages is explicitly influenced by the array programming paradigm, as the [[NumPy]] extension library to [[Python (programming language)|Python]], [[Armadillo (C++ library)|Armadillo]] and [[Blitz++]] libraries do.<ref>{{cite web |title= Reference for Armadillo 1.1.8. Examples of Matlab/Octave syntax and conceptually corresponding Armadillo syntax. |url= http://arma.sourceforge.net/docs.html#syntax |access-date= 2011-03-19}}</ref><ref>{{cite web |title= Blitz++ User's Guide. 3. Array Expressions. |url= http://www.oonumerics.org/blitz/docs/blitz_3.html#SEC80 |access-date= 2011-03-19 |archive-url= https://web.archive.org/web/20110323013142/http://www.oonumerics.org/blitz/docs/blitz_3.html#SEC80 |archive-date= 2011-03-23 |url-status= dead }}</ref>

==See also==