The NumPy array: a structure for efficient numerical computation

Abstract : In the Python world, NumPy arrays are the standard representation for numerical data. Here, we show how these arrays enable efficient implementation of numerical computations in a high-level language. Overall, three techniques are applied to improve performance: vectorizing calculations, avoiding copying data in memory, and minimizing operation counts. We first present the NumPy array structure, then show how to use it for efficient computation, and finally how to share array data with other libraries.
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Journal articles
Computing in Science and Engineering, Institute of Electrical and Electronics Engineers (IEEE), 2011, 13 (2), pp.22-30. <10.1109/MCSE.2011.37>


https://hal.inria.fr/inria-00564007
Contributor : Gaël Varoquaux <>
Submitted on : Monday, February 7, 2011 - 5:13:20 PM
Last modification on : Wednesday, June 19, 2013 - 3:12:05 PM

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Stefan Van Der Walt, S. Chris Colbert, Gaël Varoquaux. The NumPy array: a structure for efficient numerical computation. Computing in Science and Engineering, Institute of Electrical and Electronics Engineers (IEEE), 2011, 13 (2), pp.22-30. <10.1109/MCSE.2011.37>. <inria-00564007>

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