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      The NumPy array: a structure for efficient numerical computation

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          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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          Author and article information

          Journal
          08 February 2011
          10.1109/MCSE.2011.37
          1102.1523

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Computing in Science and Engineering 13, 2 (2011) 22-30
          cs.MS
          ccsd

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