biVector forum

GA Tutorial Wishlist

I think it would be worthwhile to make a wishlist of code/blog tutorials for GA. Given many people want to work with these algebras from a range of different fields it would be great if people would post tutorials/problems they would like a GA treatment of/algorithm reference implementations they would like to see, then we can focus tutorial construction towards things people are interested in :smiley:

I’ll start, I would like to see:

Spacetime algebra EM tutorials with visualisation of fields

A tutorial and reference implementation of FABRIK with constraints

Anyone else got any other ideas?


There are at least three libraries coming out of this forum. It would be fantastic if we could try to make a unified documentation system that can have code examples with all of these libraries (sort of how Ganga’s autogenerated code already works, the user selects the code they want and then reads the tutorial). This could help resist fragmentation in the learning space.

The key members on this forum have done an amazing job presenting learning material to the community and this site does a very good job organizing it, but when it comes to code snippets and blog posts things are still a little spread around personal pages, source and forum posts.

I’m not the biggest fan of MATLAB, but I love the way that their documentation system works with explanation of theory alongside working code examples.

As to specific topics: I second some more IK material, perhaps with examples of common joint systems. Enki’s existing IK example is impressive and is a great demo for showing off the power of GA. It would be great to have a PGA3D version alongside the 2D version.

I’m interested in Fourier transforms in GA and applications for RGB image registration (I can’t remember where I saw an example, but it caught my eye).

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My website has a section for tutorials, I would be delighted if other people started contributing to that. Currently, I am working on some conputations for some problems related to EM, I will post that when ready.


Efficient Collision detection.