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mne-tools
Misleading parameter description in `fit_transform` method of `CSP` and `SPoC`
Proposed documentation enhancement
CSP and SPoC classes of the decoding module both have a fit, transform, and fit_transform method, which require passing in 3D data of shape (n_epochs, n_channels, n_times). The docstrings for fit and transform are customised for each class, describing the shape of the data properly.
However, the fit_transform method uses the docstring from the TransformerMixin class, which only refers to data as needing shape (n_samples, n_features). The inconsistent description of the parameters could lead to confusion in how to use the classes, e.g.: https://mne.discourse.group/t/spoc-with-fit-transform-x-must-have-at-least-3-dimensions/9147.
This could be avoided by having a docstring for fit_transform that is specific for the data shapes expected by the CSP and SPoC classes.
The SSD class also uses the default fit_transform docstring, but in this case it does accept 2D arrays as data. It's slightly less misleading here, but perhaps also worth changing.
What do others think?
