VISPY, A Modern and Interactive Scientific Visualisation

Luke Campagnola 1 Almar Klein 2 Cyrille Rossant 3 Nicolas Rougier 4, *
* Auteur correspondant
4 Mnemosyne - Mnemonic Synergy
LaBRI - Laboratoire Bordelais de Recherche en Informatique, Inria Bordeaux - Sud-Ouest, IMN - Institut des Maladies Neurodégénératives [Bordeaux]
Abstract : Whereas the availability of data increases exponentially fast, the current visualization tools available today in Python do not scale gracefully to big data. The major plotting library in Python is Matplotlib and is more focused on the generation of static publication-ready figures than interactive visualization. These are really two different, and nearly orthogonal goals. For the former, high display quality is the major objective, whereas speed and reactivity is much more important for the latter. Matplotlib can be used for interactive visualization, but it has not been primarily designed for this. Consequently, the frame rate tends to be low on medium-size data sets, and million-points data sets can not be decently visualized in this way. Our goal is thus to create the foundations for the next-generation interactive visualization software in Python.
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Contributeur : Nicolas P. Rougier <>
Soumis le : jeudi 21 novembre 2013 - 18:46:16
Dernière modification le : jeudi 11 janvier 2018 - 06:24:26


  • HAL Id : hal-00907830, version 1



Luke Campagnola, Almar Klein, Cyrille Rossant, Nicolas Rougier. VISPY, A Modern and Interactive Scientific Visualisation. Euroscipy 2013, Aug 2013, Brusells, Belgium. 2013. 〈hal-00907830〉



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