I am developing a high-performance interactive visualization package in Python based on PyOpenGL (http://rossant.github.com/galry/
). It is primarily meant to be used as a framework for developing complex interactive GUIs (in QT) that deal with very large amounts of data (tens of millions of points). But it may also be used, like matplotlib, as a high-level interactive library to plot and visualize data.
The low-level interface is mostly done at this point (the code is still in an experimental stage though), and I'm now focusing on my current research project which is to write a scientific GUI based on this interface. However, I think people (including myself!) may be interested in a matplotlib-like high-level interface. I was first thinking about writing such an interface from scratch, by implementing a very small fraction of the matplotlib interface (basic commands like figure(), plot(), subplot(), show(), etc.). One could then quickly visualize huge datasets with the same commands than matplotlib.
Another solution would be to write a matplotlib backend based on this library. I am not familar enough with the internals of matplotlib to know how complicated it could be. I may do it myself, but it would probably take a long time since it is currently not my highest priority. I would be glad if someone experienced in writing backends was interested in working on it. Actually I could do everything that is specific to my library, which already provides commands to plot points, lines, textures, etc. The canvas is based on QT and may be similar to what is already implemented in the QT backend.
Of course, it would already be great if only the most basic plotting features were available in the backend. A first step could be for example to have a simplistic example "plot(x, sin(x))" working (with interactive navigation).
I am looking forward to your feedback.