Ok, it was not as straightforward as I initially thought either. Initially I just tried doing the example from the first post, where I just add the contents of fluid.labelset~ as an additional column in a fluid.dataset~. I managed to get all of that into a single dict, but couldn’t initially figure out how to munge them together from there. Got it in the end though.
Quite handy for visualizing. This is definitely a situation where you don’t want to use the linear perception maps as the differentiation is far less with those when looking at clusters. I also noticed that if you use HSL, the edges wrap around more obviously for visualizing clusters. (I’ll update fluid.datasetplot~ in the relevant thread).
4 clusters from kmeans (linear display):
4 clusters (previous hsl):
4 clusters (new hsl):
