High-performance interactive visualization in Python
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Latest commit 6201fa3 Mar 19, 2016 @rossant Bump version

README.md

Galry: high performance interactive visualization package in Python

This experimental project is now superseded by Vispy. Galry is no longer maintained.

Galry is a high performance interactive visualization package in Python based on OpenGL. It allows to interactively visualize very large plots (tens of millions of points) in real time, by using the graphics card as much as possible.

Galry's high-level interface is directly inspired by Matplotlib and Matlab. The low-level interface can be used to write complex interactive visualization GUIs with Qt that deal with large 2D/3D datasets.

Visualization capabilities of Galry are not restricted to plotting, and include textures, 3D meshes, graphs, shapes, etc. Custom shaders can also be written for advanced uses.

Click here to go to the FAQ.

Gallery

Multiple plots Multiple bar plots Dynamic fractal

Click here to see all screenshots and videos.

Installation

Installation procedure

  • Type in a terminal:

    $ pip install galry
    
  • In Python, type:

    from galry import *
    from numpy.random import randn
    plot(randn(3, 10000))
    show()
    
  • You should see three overlayed random signals. You can navigate with the mouse and the keyboard. Press H to see all available actions.

More details.

Requirements

  • Galry should work on any platform (Window/Linux/MacOS).

  • Mandatory dependencies include:

    • Python 2.7
    • Numpy
    • PyQt4 or PySide with the OpenGL bindings
    • PyOpenGL
    • matplotlib
  • Your graphics card drivers must be up-to-date and support OpenGL 2.1.

Galry is licensed under the BSD license.

Development version (expert users)

  • Clone the repository:

    git clone https://github.com/rossant/galry.git
    
  • Install Galry with pip so that external packages are automatically updated (like qtools which contains some Qt-related utility functions):

    pip install -r requirements.txt
    

Quick links

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