VisPy: interactive scientific visualization in Python
Main website: http://vispy.org
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 or IPython notebook with WebGL).
Announcements
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
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, July 2014
GSoC 2014: two GSoC students are currently working on VisPy under the PSF umbrella
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
VisPy runs on Python 2.7+ and Python 3.3+ and depends on NumPy. You also need a backend (PyQt4/PySide, PyQt5/PySide2, glfw, pyglet, SDL, or wx).
PyQt5/PySide2 should be considered more experimental than PyQt4/PySide.
VisPy can be installed either via pip:
` pip install vispy `
or within the Anaconda Python distribution. Anaconda provides a convenient package management system. Installing VisPy can then easily be achieved by adding conda-forge to the channels with:
` conda config --add channels conda-forge `
Once the conda-forge channel has been enabled, vispy can be installed with:
` conda install vispy `
Development Installation
As VisPy is under heavy development at this time, we highly recommend developers to use the development version on Github (master branch). You need to clone the repository and install VisPy with python setup.py install.
As a one-liner, assuming git is installed:
git clone --recurse-submodules https://github.com/vispy/vispy.git && cd vispy && python setup.py install --user
This will automatically install the latest version of vispy.
If you already have vispy cloned, you may need to update the git submodules to make sure you have the newest code:
git pull git submodule update --init --recursive
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.
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 with PyQtGraph, Almar Klein with Visvis, Cyrille Rossant with Galry, Nicolas Rougier with 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
Release files for vispy 0.6.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| vispy-0.6.2.tar.gz | 13.3 MB | Details |
Built distributions (wheels)
| File | Reset | |||
|---|---|---|---|---|
| vispy-0.6.2-cp37-cp37m-win_amd64.whl | CPython 3.7 | CPython 3.7 pymalloc | Windows x86-64 | Details |
| vispy-0.6.2-cp37-cp37m-win32.whl | CPython 3.7 | CPython 3.7 pymalloc | Windows x86-32 | Details |
| vispy-0.6.2-cp37-cp37m-manylinux1_x86_64.whl | CPython 3.7 | CPython 3.7 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| vispy-0.6.2-cp37-cp37m-manylinux1_i686.whl | CPython 3.7 | CPython 3.7 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| vispy-0.6.2-cp37-cp37m-macosx_10_6_intel.whl | CPython 3.7 | CPython 3.7 pymalloc | macOS 10.6+ Intel (x86-64, i386) | Details |
| vispy-0.6.2-cp36-cp36m-win_amd64.whl | CPython 3.6 | CPython 3.6 pymalloc | Windows x86-64 | Details |
| vispy-0.6.2-cp36-cp36m-win32.whl | CPython 3.6 | CPython 3.6 pymalloc | Windows x86-32 | Details |
| vispy-0.6.2-cp36-cp36m-manylinux1_x86_64.whl | CPython 3.6 | CPython 3.6 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| vispy-0.6.2-cp36-cp36m-manylinux1_i686.whl | CPython 3.6 | CPython 3.6 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| vispy-0.6.2-cp36-cp36m-macosx_10_6_intel.whl | CPython 3.6 | CPython 3.6 pymalloc | macOS 10.6+ Intel (x86-64, i386) | Details |
| vispy-0.6.2-cp35-cp35m-win_amd64.whl | CPython 3.5 | CPython 3.5 pymalloc | Windows x86-64 | Details |
| vispy-0.6.2-cp35-cp35m-win32.whl | CPython 3.5 | CPython 3.5 pymalloc | Windows x86-32 | Details |
| vispy-0.6.2-cp35-cp35m-manylinux1_x86_64.whl | CPython 3.5 | CPython 3.5 pymalloc | Linux glibc 2.5+ x86-64 | Details |
| vispy-0.6.2-cp35-cp35m-manylinux1_i686.whl | CPython 3.5 | CPython 3.5 pymalloc | Linux glibc 2.5+ x86-32 | Details |
| vispy-0.6.2-cp35-cp35m-macosx_10_6_intel.whl | CPython 3.5 | CPython 3.5 pymalloc | macOS 10.6+ Intel (x86-64, i386) | Details |
Total release size: 46.7 MB
Release files / vispy-0.6.2.tar.gz
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Release files / vispy-0.6.2-cp37-cp37m-win_amd64.whl
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Release files / vispy-0.6.2-cp37-cp37m-win32.whl
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Release files / vispy-0.6.2-cp37-cp37m-manylinux1_x86_64.whl
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Release files / vispy-0.6.2-cp37-cp37m-manylinux1_i686.whl
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Release files / vispy-0.6.2-cp37-cp37m-macosx_10_6_intel.whl
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Release files / vispy-0.6.2-cp36-cp36m-win_amd64.whl
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Release files / vispy-0.6.2-cp36-cp36m-win32.whl
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Release files / vispy-0.6.2-cp36-cp36m-manylinux1_x86_64.whl
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Release files / vispy-0.6.2-cp36-cp36m-manylinux1_i686.whl
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Release files / vispy-0.6.2-cp36-cp36m-macosx_10_6_intel.whl
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Release files / vispy-0.6.2-cp35-cp35m-win_amd64.whl
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Release files / vispy-0.6.2-cp35-cp35m-win32.whl
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Release files / vispy-0.6.2-cp35-cp35m-manylinux1_x86_64.whl
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Release files / vispy-0.6.2-cp35-cp35m-manylinux1_i686.whl
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Release files / vispy-0.6.2-cp35-cp35m-macosx_10_6_intel.whl
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