Array programming: Difference between revisions

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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]], Mata, [[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)]], [[Wolfram Language]], 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 |last-author-amp=yes |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 }}</ref> regardless of whether it is executed on a [[vector processor]] (which implements vector instructions) or not.

Array programming primitives concisely express broad ideas about data manipulation. The level of concision can be dramatic in certain cases: it is not uncommon to find array programming language [[one-liner program|one-liners]] that require more than a couple of pages of Javaobject-oriented code.<ref>{{cite web|url=http://www.cs.nyu.edu/~michaels/screencasts/Java_vs_K/Java_vs_K.html|title=Java and K|author=Michael Schidlowsky|accessdate=2008-01-23}}</ref>

==Concepts of array==