Difference between revisions of "Python"

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** [http://www.esrf.eu/UsersAndScience/Publications/Highlights/2012/et/et3 Official site.]
 
** [http://www.esrf.eu/UsersAndScience/Publications/Highlights/2012/et/et3 Official site.]
 
** [https://github.com/kif/pyFAI Source code.]
 
** [https://github.com/kif/pyFAI Source code.]
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* '''High-performance Python for crystallographic computing'''
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** A. Boulle and J. Kieffer [http://scripts.iucr.org/cgi-bin/paper?gj5229 High-performance Python for crystallographic computing] ''J. Appl. Cryst.'' '''2019''', 52 [https://doi.org/10.1107/S1600576719008471 doi: 10.1107/S1600576719008471]

Revision as of 07:32, 25 July 2019

Python is a powerful and flexible programming language. It is increasingly used in scientific software packages, because it has a large number of libraries that are extremely useful in numerical and scientific computing. For instance:

  • numpy: Also known as numerical python, this package allows for efficient handling of vectors, arrays, matrices, and associated computations.
  • matplotlib: Plotting library that can generate graphs of datasets, including area images. Publication-quality images are possible with some effort.
  • scipy: A large collection of computational tools relevant to scientific data.
  • Python Image Library (PIL): A library that allows opening, converting, and editing image files including the TIFF files frequently output by x-ray area detectors in scattering instruments.


See Also

Hints about Python usage

Official Site

Packages for Scattering