mne-tools/mne-python — pull request #191 by dengemann (2012-11-14 17:02:37+00:00)
Title: ENH: RandomizedPCA and FastICA

I'm happy I found a way to preserve the current API, feedback is welcome.

- Integrated PCA station into the ICA workflow as performed bye mne.artifacts.ICA
- The user may giva a maximum numer of components and further select the ultimate number of components passed to ICA via explained variance criteria.
- On picking sources the user may select a proportion of the disposed PCA copomponents to be re-appended before undoing the whitening. This is done by the arg prop_unused. This allows to control the trade off between denoising data for better ICA performance and preserving original data as much as possible apart from the artifact.
- updated tests and examples
- minor changes.
- self.mixing is now self._mixing
- self._fastica is now self._fastica
- NEW attr: self._pca