mne-tools/mne-python — pull request #188 by dengemann (2012-11-13 18:24:32+00:00)
Title: API + ENH | DRAFT: Integrating RandomizedPCA with FastICA

This is the first draft in which I tried to find a remedy for the API issues described in #185 which ensue from integrating PCA and ICA.
To keep things as consistent a possible and only minmally change the API I choose class method approach for initializing from raw or epochs; it basically merges the init and the decomposition into one step. I integrated @agramfort 's max_n_components arg and at the same time the user can select the n_components via explained variance. Also note that with this approach we may fully control the PCA, e.g. jsut drop components for ICA but keep them for the final unmixing.
This isn't fully wokring yet but the API and the examples clearly expose the idea behind it. @agramfort @mluessi @Eric89GXL -- I would be happy to get some general feedback before putting further effort in cleaning up / testing.