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paulcbogdan avatar paulcbogdan commented on May 31, 2024

Hi, to handle 164 ROIs, you will need to create a new dictionary for the idx_to_label parameter and an (n, 3)-sized list of lists/tuples for the coords parameter.

For instance, if the 0th ROI had the "FP" label (MNI coordinate: [0, 68, 6]) and the 1st ROI had the "IFG" label (coordinate: [44, 32, 0]), then your dictionary would start:

idx_to_label = {0: 'FP', 1: 'IFG'}
coords = [[0, 68, 6], [44, 32, 0]]

You would need to expand this for all 164 ROIs or so (i.e., make a dictionary of length 164 and a list of length 164). The first example in the README shows this process going up to 8 ROIs.

However, just a heads-up: The Harvard-Oxford atlas contains 69 labels for cortical and subcortical areas, right? If so, I'm not sure if you'd be able to fit them all neatly on the chord diagram (i.e., if you're plotting 69 segments, then each one would be tiny and there wouldn't be any space for the text).

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MohammadHosseinMaleki avatar MohammadHosseinMaleki commented on May 31, 2024

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paulcbogdan avatar paulcbogdan commented on May 31, 2024

Hi Mohammad, sorry for this much slower response! I think you should just pursue the dictionary route. This is certainly the easiest way to accomplish what you seem to be looking for.

I'm not sure what you mean by adapting the code to work with the atlas you are using. The only change that I could see would be adapting get_idx_to_label to accept a different atlas argument. It currently only has the yeo atlas setup for it. However, this could be changed to have other atlases built in. If you end up doing this and you want to incorporate another atlas in the code, please let me know. I would happily pull such a change, but I don't have time to work on something like this myself right now (particularly, as the dictionary route is always there, so this type of modification isn't essential).

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