Applying operations to whole sets of values simultaneously
In computer science, array programming refers to solutions that allow the application of operations to an entire set of values at once. Such solutions are commonly used in scientific and engineering settings.
Modern programming languages that support array programming (also known as vector or multidimensional languages) have been engineered specifically to generalize operations on scalars to apply transparently to vectors, matrices, and higher-dimensional arrays. These include APL, J, Fortran, MATLAB, Analytica, Octave, R, Cilk Plus, Julia, Perl Data Language (PDL). In these languages, an operation that operates on entire arrays can be called a vectorized operation,[1] 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] to find array programming language one-liners that require several pages of object-oriented code.
^Stéfan van der Walt; S. Chris Colbert & Gaël Varoquaux (2011). "The NumPy array: a structure for efficient numerical computation". Computing in Science and Engineering. 13 (2). IEEE: 22–30. arXiv:1102.1523. Bibcode:2011CSE....13b..22V. doi:10.1109/mcse.2011.37. S2CID 16907816.
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