Dear PyMVPA-ers, We are glad to announce the availability of a new release addressing a number of bugs and introducing new features and enhancements.
Sources: Tagged and pushed to http://github.com/PyMVPA/PyMVPA Tarballs available from https://github.com/PyMVPA/PyMVPA/tags Debian/Ubuntu: Available from the http://neuro.debian.net and was uploaded to Debian unstable (i.e. sid) Windows installer is available for Python 2.6 at https://github.com/PyMVPA/PyMVPA/downloads [although once again -- we recommend Windows/OSX users to have a look at http://neuro.debian.net/vm.html] Hopefully soon http://www.lfd.uci.edu/~gohlke/pythonlibs collection by Christoph Gohlke would get 2.1.0 as well Website: updated And here is what would you are getting with the upgrade: * 2.1.0 (Fri, June 29 2012) * Fixes - :func:`~mvpa2.misc.support.mask2slice` failed to convert an array of ``False`` values into ``slice(None, 0, None)`` (Fixes #56). - A number of fixes to the HDF5 IO code that ignored parts of an object's state when custom ``__reduce__()`` implementations were used (Fixes #42), and had problems storing metaclass types (Fixes #78). - Proper single quotes in documentation code snippets within PDFs. - Memory leak (model pointer) in LIBSVM bindings. * Enhancements - All searchlight implementations can now optionally store the IDs of all features for each generated ROI (conditional attr. ``roi_feature_ids``) - Add :func:`~mvpa2.misc.neighborhood.scatter_neighborhoods` to aid sparse sampling of spaces. - Add :class:`~mvpa2.clfs.transerror.ConfusionMatrixError` to compute confusion matrices with an error function interface (e.g. for ``CrossValidation(errorfx=...)``). This class existed for a long time, but was hidden in the unit tests. - Add :class:`~mvpa2.clfs.transerror.Confusion` to compute confusion matrices with a Node interface (e.g. for ``CrossValidation(postproc=...)``). This is useful if confusion matrices are necessary as an intermediate result and further processing with other nodes is desired. * New functionality - Add :class:`~mvpa2.clfs.transerror.BayesConfusionHypothesis` to perform Bayesian hypothesis testing of multi-class confusion statistics. This is useful to assess the likelihood of a particular (or all possible) grouping of classes being distinguishable. - Add :class:`~mvpa2.mappers.fxy.FxyMapper` to perform arbitrary computations involving two datasets. - Add :class:`~mvpa2.mappers.base.CombinedMapper` to run a dataset through a set of mappers and combine their outputs. - Add :class:`~mvpa2.measures.statsmodels_adaptor.UnivariateStatsModels` a wrapper for using models from the statsmodels_ package as a FeaturewiseMeasure. - Add :class:`~mvpa2.misc.dcov.dCOV` and :func:`~mvpa2.misc.dcov.dcorcoef` to quantify independence of (multivariate) signals. * API changes - Deprecating ``GLM`` that is now implemented with UnivariateStatsModels. This deprecated GLM class no longer supports the ``zstat`` calculation, and none of its previous conditional attributes are available anymore. Enjoy! -- =------------------------------------------------------------------= Yaroslav O. Halchenko Postdoctoral Fellow, Department of Psychological and Brain Sciences Dartmouth College, 419 Moore Hall, Hinman Box 6207, Hanover, NH 03755 Phone: +1 (603) 646-9834 Fax: +1 (603) 646-1419 WWW: http://www.linkedin.com/in/yarik _______________________________________________ Pkg-ExpPsy-PyMVPA mailing list [email protected] http://lists.alioth.debian.org/cgi-bin/mailman/listinfo/pkg-exppsy-pymvpa
