[pymvpa] PyMVPA 0.3.1
michael.hanke at gmail.com
Sun Sep 14 18:18:00 UTC 2008
I'm glad to be able to announce another update of PyMVPA. The changelog
of 0.3.1 is:
* New manual section about feature selection with a focus on RFE.
Contributed by James M. Hughes.
* New dataset type `ChannelDataset` for data structured in channels. Might
be useful for data modalities like EEG and MEG. This dataset includes
support for common preprocessing steps like resampling and baseline
* Plotting of topographies on heads. Thanks to Ingo Fründ for contributing
this code. Additionally, a new example shows how to do such plots.
* New general purpose function for generating barplots and candlestick plots
with error bars (`plotBars()`).
* Dataset supports mapping of string labels onto numerical labels, removing
the need to perform this mapping manually in user code. 'clfs_examples.py'
is adjusted accordingly to demonstrate the new feature.
* New Classifier.summary() method to dump classifier settings.
* Improved and more flexible plotERPs().
* New I-RELIEF sensitivity analyzer.
* Added visualization of confusion matrices via `ConfusionMatrix.plot()`
inspired by Ingo Fründ.
* The PyMVPA version is now globally available in `mvpa.pymvpa_version`.
* BugFix: TuebingenMEG reader failed in some cases.
* Several improvements (docs and implementation) for building PyMVPA on
* New convenience accessor methods (`select()`, `where()` and
`__getitem__()`) for the `Dataset` base class.
* New `seed()` function to configure the random number generators from user
* Added reader for a MEG sensor locations format
* Initial model selection support for GRP (using openopt).
* And tons of minor bugfixes, additional tests and improved documentation.
Grab the source from the project website. Binary packages and installer
updates will follow during the next week.
GPG key: 1024D/3144BE0F Michael Hanke
More information about the Pkg-ExpPsy-PyMVPA