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# Nicolas P. Rougier - Modern and Interactive Scientific Visualization

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 mostly focused
on the generation of static publication-ready figures rather 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.

Vispy is a new high-performance interactive 2D/3D data visualization library
that leverages the computational power of modern Graphics Processing Units
(GPUs) in order to offer both fast and high quality scientific visualization
using the Python language and modern OpenGL (shaders). Our primary goal is not
to make publication quality plots -- even if we expect high quality using
modern and dedicated GPU techniques such as dashed lines, curves, markers,
arrows, interpolations -- but rather to get a sense of the data by visualizing it
interactively. The nature of the data can be anything: real-time signals, maps,
high-dimensional points, surfaces, volumes, images, textures, etc.

Main sites: [vispy](http://vispy.org) & [glumpy](http://glumpy.github.io).


[[Slides|XDC-2014-rougier.pdf]]