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.
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.
Based on the "Data Visualization" category.
Alternatively, view GR alternatives based on common mentions on social networks and blogs.
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[MIT license](LICENSE.md) GitHub tag PyPI version DOI
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).
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 Grünberg Institute at Forschunsgzentrum Jülich. 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.
To install GR and try it using Python, Julia or C, please see the corresponding documentation:
You can find more information about GR on the GR home page.
If you want to improve GR, please read the contribution guide for a few notes on how to report issues or submit changes.
If you have any questions about GR or run into any issues setting up or running GR, please open an issue on GitHub, either in this repo or in the repo for the language binding you are using (Python, Julia, Ruby).
*Note that all licence references and agreements mentioned in the GR README section above
are relevant to that project's source code only.
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