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Title Lose Your Loops with Numpy
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Author(s) Gunter, Thoth Kenneth (speaker) (Northwestern University (US))
Corporate author(s) CERN. Geneva
Imprint 2016-05-30. - Streaming video.
Series (Developers@CERN Forum)
(2nd Developers@CERN Forum)
Lecture note on 2016-05-30T14:30:00
Subject category Developers@CERN Forum
Abstract Developing in python is fast. Computation, however, can often be another story. Or at least that is how it may seem. When working with arrays and numerical datasets one can subvert many of python’s computational limitations by utilizing numpy. Numpy is python’s standard matrix computation library. Many python users only use numpy to store and generate arrays, failing to utilize one of python’s most powerful computational tools. By leveraging numpy’s ufuncs, aggregation, broadcasting and slicing/masking/indexing functionality one can cut back on slow python loops and increase the speed of their programs by as much as 100x. This talk aims at teaching attendees how to use these tools through toy examples.
Copyright/License © 2016-2024 CERN
Submitted by jose.benito.gonzalez@cern.ch

 


 Record created 2016-05-31, last modified 2022-11-02


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