How to support Matplotlib's gigantic API?

[nvaytet]

Supporting all of Matplotlib will never happen, it is too large.

But it would be good to find a way where we could support a lot of it without duplicating everything.
It would also be good if it could be done in a way (either patch mpl functions or use mpl under-the-hood) that would mean updates to the mpl API would automatically propagate here.

The way https://github.com/scipp/mplcanvas did this was by calling all methods on underlying mpl axes, and rendering with draw calls to a canvas.

In Matplotgl, we decided to clone the artists into their own implementation, because it meant that updating one line does not require re-drawing all the other lines on the plot, leading to significant performance gains.

[nvaytet]

One thing to think about is whether we would like matplotgl to exactly match the mpl API, or should it be a mpl-like library.

Having it be a mpl-like library could allow us to make useful additions, such as adding a set_xdata and set_ydata on the object returned by ax.scatter() to update the positions of the dots, instead of having to call set_offsets which has a somewhat obscure/unintuitive name and is also error-prone as the shape of the array that has to be passed can be a source of errors/annoyance.

[asteppke]

Thanks Neil for this project to make interactive plotting of much more convenient!

From a humble user perspective it would be advantageous if matplotgl would exactly match the mpl API. There are just so vast resources out there and if plots fail to run under matplotlib that would be a source of pain.

I can see that for some, very limited areas, such as animations or live changes to datasets matplotlib was not really designed for. Here extending the API slightly would be a possibility but please remain as compatible as possible. Ideally this would also include some slow 'fallback' where matplotgl is forwarding responsibility to matplotlib as you mentioned for more obscure features and accelerates or improves upon the 10% of functions that are commonly used.

Maybe some inspiration can also be obtained from https://github.com/mpld3/mpld3, which does not seem to be showing much activity anymore.