machenslab / dPCA

An implementation of demixed Principal Component Analysis (a supervised linear dimensionality reduction technique)

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Merging components before fitting

pkollias opened this issue · comments

I am wondering if I can use the code to merge effects and fit on the combined marginalization. Similar to what the paper describes describing a marginalization main effect (sensory) and its interaction with time in a single component.
I have been trying to use the join parameter but have stumbled on a couple of issues. Also I am not sure if the fact that the _marginalize method calls the parameter generator method with join=False by default