VisPy: interactive scientific visualization in Python
Main website: http://vispy.org, Build Status, Appveyor Status, Coverage Status, Zenodo Link, ----
VisPy is a high-performance interactive 2D/3D data visualization
library. VisPy leverages the computational power of modern Graphics
Processing Units (GPUs) through the OpenGL library to display very
large datasets. Applications of VisPy include:
- High-quality interactive scientific plots with millions of points.
- Direct visualization of real-time data.
- Fast interactive visualization of 3D models (meshes, volume
rendering). - OpenGL visualization demos.
- Scientific GUIs with fast, scalable visualization widgets (
Qt <http://www.qt.io>__ or
IPython notebook <http://ipython.org/notebook.html>__ with WebGL).
Announcements
- Release! Version 0.6.4, December 13, 2019
- Release! Version 0.6.3, November 27, 2019
- Release! Version 0.6.2, November 4, 2019
- Release! Version 0.6.1, July 28, 2019
- Release! Version 0.6.0, July 11, 2019
- Release! Version 0.5.3, March 28, 2018
- Release! Version 0.5.2, December 11, 2017
- Release! Version 0.5.1, November 4, 2017
- Release! Version 0.5, October 24, 2017
- Release! Version 0.4, May 22, 2015
VisPy tutorial in the IPython Cookbook <https://github.com/ipython-books/cookbook-code/blob/master/featured/06_vispy.ipynb>__- Release! Version 0.3, August 29, 2014
- EuroSciPy 2014: talk at Saturday 30, and sprint at Sunday 31, August 2014
Article in Linux Magazine, French Edition <https://github.com/vispy/linuxmag-article>__, July 2014- GSoC 2014:
two GSoC students are currently working on VisPy under the PSF umbrella <https://github.com/vispy/vispy/wiki/Project.%20GSoC-2014>__ - Release!, Version 0.2.1 04-11-2013
- Presentation at BI forum, Budapest, 6 November 2013
- Presentation at Euroscipy, Belgium, August 2013
- EuroSciPy Sprint, Belgium, August 2013
- Release! Version 0.1.0 14-08-2013
Using VisPy
VisPy is a young library under heavy development at this time. It
targets two categories of users:
- Users knowing OpenGL, or willing to learn OpenGL, who want to
create beautiful and fast interactive 2D/3D visualizations in Python
as easily as possible. - Scientists without any knowledge of OpenGL, who are seeking a
high-level, high-performance plotting toolkit.
If you're in the first category, you can already start using VisPy.
VisPy offers a Pythonic, NumPy-aware, user-friendly interface for OpenGL
ES 2.0 called gloo. You can focus on writing your GLSL code instead
of dealing with the complicated OpenGL API - VisPy takes care of that
automatically for you.
If you're in the second category, we're starting to build experimental
high-level plotting interfaces. Notably, VisPy now ships a very basic
and experimental OpenGL backend for matplotlib.
Installation
Please follow the detailed
installation instructions <http://vispy.org/installation.html>_
on the VisPy website.
Structure of VisPy
Currently, the main subpackages are:
-
app: integrates an event system and offers a unified interface on
top of many window backends (Qt4, wx, glfw, IPython notebook
with/without WebGL, and others). Relatively stable API. -
gloo: a Pythonic, object-oriented interface to OpenGL. Relatively
stable API. -
scene: this is the system underlying our upcoming high level
visualization interfaces. Under heavy development and still
experimental, it contains several modules.- Visuals are graphical abstractions representing 2D shapes, 3D
meshes, text, etc. - Transforms implement 2D/3D transformations implemented on both
CPU and GPU. - Shaders implements a shader composition system for plumbing
together snippets of GLSL code. - The scene graph tracks all objects within a transformation
graph.
- Visuals are graphical abstractions representing 2D shapes, 3D
-
plot: high-level plotting interfaces.
The API of all public interfaces are subject to change in the future,
although app and gloo are relatively stable at this point.
Genesis
VisPy began when four developers with their own visualization libraries
decided to team up:
Luke Campagnola <http://luke.campagnola.me/>__ with PyQtGraph <http://www.pyqtgraph.org/>,
Almar Klein <http://www.almarklein.org/> with Visvis <https://github.com/almarklein/visvis>,
Cyrille Rossant <http://cyrille.rossant.net> with Galry <https://github.com/rossant/galry>,
Nicolas Rougier <http://www.loria.fr/~rougier/index.html> with Glumpy <https://github.com/rougier/Glumpy>__.
Now VisPy looks to build on the expertise of these developers and the
broader open-source community to build a high-performance OpenGL library.
External links
User mailing list <https://groups.google.com/forum/#!forum/vispy>__Dev mailing list <https://groups.google.com/forum/#!forum/vispy-dev>__Dev chat room <https://gitter.im/vispy/vispy>__Wiki <http://github.com/vispy/vispy/wiki>__Gallery <http://vispy.org/gallery.html>__Documentation <http://vispy.readthedocs.org>__
.., Build Status, image:: https://travis-ci.org/vispy/vispy.svg?branch=master
:target: https://travis-ci.org/vispy/vispy
.., Appveyor Status, image:: https://ci.appveyor.com/api/projects/status/v09sc8ua4ju2ngyy/branch/master?svg=true
:target: https://ci.appveyor.com/project/vispy/vispy/branch/master
.., Coverage Status, image:: https://img.shields.io/coveralls/vispy/vispy/master.svg
:target: https://coveralls.io/r/vispy/vispy?branch=master
.., Zenodo Link, image:: https://zenodo.org/badge/5822/vispy/vispy.svg
:target: http://dx.doi.org/10.5281/zenodo.17869
