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ME-ICA / mapca

A Python implementation of the moving average principal components analysis methods from GIFT
GNU General Public License v2.0
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Documentation missing #42

Open eurunuela opened 2 years ago

eurunuela commented 2 years ago

I believe we should add a documentation page that clearly explains what the algorithm does.

I think it would make it easier to understand for users of tedana especially, as we receive some questions about it in Neurostars (see this post for example).

tsalo commented 2 years ago

:+1: on this. I really like the graph you put together for the post and think it would be good to add it (or something similar) to the documentation.

eurunuela commented 2 years ago

I'll try to go through the paper again and translate it into a step-by-step guide for the docs.

eurunuela commented 2 years ago

Hey @tsalo , I wanted to get your opinion on this: would it make more sense to have our docs written in a Jupyter Book rather than a readthedocs page?

Edit: thinking behind this would be that a Jupyter Book would make the "docs" interactive, which could help with understanding the method.

tsalo commented 2 years ago

I think an interactive walkthrough would be great, although I think a Jupyter Book might be overkill given how small mapca is. What about having our walkthrough as an example with a Binder link? Or multiple examples in a gallery.