Python visualization framework
GR is a universal framework for cross-platform visualization applications. It offers developers a compact, portable and consistent graphics library for their programs. Applications range from publication quality 2D graphs to the representation of complex 3D scenes.
GR is essentially based on an implementation of a Graphical Kernel System (GKS) and OpenGL. As a self-contained system it can quickly and easily be integrated into existing applications (i.e. using the ctypes mechanism in Python or ccall in Julia).
The GR framework can be used in imperative programming systems or integrated into modern object-oriented systems, in particular those based on GUI toolkits. GR is characterized by its high interoperability and can be used with modern web technologies. The GR framework is especially suitable for real-time or signal processing environments.
GR was developed by the Scientific IT-Systems group at the Peter Gruenberg Institute at Forschunsgzentrum Juelich. The main development has been done by Josef Heinen who currently maintains the software, but there are other developers who currently make valuable contributions. Special thanks to Florian Rhiem (GR3] and Christian Felder (qtgr, setup.py).
Starting with release 0.6 GR can be used as a backend for Matplotlib and significantly improve the performance of existing Matplotlib or PyPlot applications written in Python or Julia, respectively. In this tutorial section you can find some examples.
Beginning with version 0.10.0 GR supports inline graphics which shows up in IPython’s Qt Console or interactive computing environments for Python and Julia, such as IPython and Jupyter. An interesting example can be found here.
For further information please refer to the GR home page.