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https://github.com/sciapp/gr

GR framework: a graphics library for visualisation applications
https://github.com/sciapp/gr

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GR framework: a graphics library for visualisation applications

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README 

        
GR - a universal framework for visualization applications

=========================================================



[![MIT license](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE.md)

[![GitHub tag](https://img.shields.io/github/tag/jheinen/gr.svg)](https://github.com/jheinen/gr/releases)

[![PyPI version](https://img.shields.io/pypi/v/gr.svg)](https://pypi.python.org/pypi/gr)

[![DOI](https://zenodo.org/badge/17747322.svg)](https://zenodo.org/badge/latestdoi/17747322)



*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](http://matplotlib.org) and significantly improve

the performance of existing Matplotlib or PyPlot applications written

in Python or Julia, respectively.

In [this](http://gr-framework.org/tutorials/matplotlib.html) 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](http://ipython.org) and

[Jupyter](https://jupyter.org). An interesting example can be found

[here](http://pgi-jcns.fz-juelich.de/pub/doc/700K_460.html).



## Installation and Getting Started



To install *GR* and try it using *Python*, *Julia* or *C*, please see the corresponding documentation:



- [Python package gr](https://gr-framework.org/python.html)

- [Julia package GR](https://gr-framework.org/julia.html)

- [C library GR](https://gr-framework.org/c.html)

- [Ruby package GR](https://github.com/red-data-tools/GR.rb)



## Documentation



You can find more information about *GR* on the [GR home page](http://gr-framework.org).



## Contributing



If you want to improve *GR*, please read the [contribution guide](https://github.com/sciapp/gr/blob/develop/CONTRIBUTING.md) for a few notes on how to report issues or submit changes.



## Support



If you have any questions about *GR* or run into any issues setting up or running GR, please [open an issue on GitHub](https://github.com/sciapp/gr/issues/new), either in this repo or in the repo for the language binding you are using ([Python](https://github.com/sciapp/python-gr/issues/new), [Julia](https://github.com/jheinen/GR.jl/issues/new), [Ruby](https://github.com/red-data-tools/GR.rb/issues/new)).