The NumPy array: a structure for efficient numerical computation
arXiv:1102.1523 · doi:10.1109/MCSE.2011.37
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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- A Deficit of Massive White Dwarfs in Gaia Astrometric Binaries
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- Water UV-shielding in the terrestrial planet-forming zone: Implications for carbon dioxide emission
- TOI-1408: Discovery and Photodynamical Modeling of a Small Inner Companion to a Hot Jupiter Revealed by TTVs
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