[pymvpa] Announcement: PyMVPA 2.0.0

[Yaroslav Halchenko]

Dear PyMVPA-ers,

We would like to "close" this lengthy thread of RCs by announcing the
availability of PyMVPA 2.0.0.  It provides mvpa2 module so you all could
happily have stable but old 0.4.x series (providing mvpa module) and new
API-incompatible version co-installed on the same system.  We are yet to adapt
some fixes from 2.0.0 for 0.4.x and release bugfix 0.4.8 (within a week or
two).

Fresh PyMVPA 2.0.0 is available from 
GIT:         https://github.com/PyMVPA/PyMVPA
NeuroDebian: http://neuro.debian.net/pkgs/python-mvpa2.html
and official Debian sid.

python-mvpa-snapshot packages (carrying outdated 0.6.0~rc4) were removed from
NeuroDebian archive.  Just install python-mvpa2 and adjust your import
statement(s) to import mvpa2 instead.

Here is the changelog for the release including few release candidates I
think we have not explicitly announced.  You might prefer to browse
online at http://www.pymvpa.org/changelog.html :


 * 2.0.0 (Mon, Dec 19 2011)
   This release aggregates all the changes occurred between official releases in 0.4 series and various snapshot releases (in 0.5 and 0.6 series). To get better overview of high level changes see release notes for 0.5 and 0.6 as well as summaries of release candidates below
      + Fixes (23 BF commits)
           o significance level in the right tail was fixed to include the value tested – otherwise resulted in optimistic bias (or absurdly high significance in improbable case if all estimates having the same value)
           o compatible with the upcoming IPython 0.12 and renamed sklearn (Fixes #57)
           o do not double-train slave classifiers while assessing sensitivities (Fixes #53)
      + Enhancements (30 ENH + 3 NF commits)
           o resolving voting ties in kNN based on mean distance, and randomly in SMLR
           o kNN‘s ca.estimates now contains dictionaries with votes for each class
           o consistent zscoring in Hyperalignment
 * 2.0.0~rc5 (Wed, Oct 19 2011)                   
      + Major: to allow easy co-existence of stable PyMVPA 0.4.x, 0.6 development mvpa module was renamed into mod:mvpa2.
      + Fixes
           o compatible with the new Shogun 1.x series
           o compatible with the new h5py 2.x series
           o mvpa-prep-fmri – various compatibility fixes and smoke testing
           o deepcopying SummaryStatistics during __add__
      + Enhancements
           o tutorial uses mvpa2.tutorial_suite now
           o better suppression of R warnings when needed
           o internal attributes of many classes were exposed as properties
           o more unification of __repr__ for many classes
 * 0.6.0~rc4 (Wed, Jun 14 2011)                           
      + Fixes
           o Finished transition to nibabel conventions in plot_lightbox
           o Addressed matplotlib.hist API change
           o Various adjustments in the tests batteries (nibabel 1.1.0 compatibility, etc)
      + New functionality
           o Explicit new argument flatten to from_wizard – default behavior changed if mapper was provided as well
      + Enhancements
           o Elaborated __str__ and __repr__ for some Classifiers and Measures

Happy holidays!

On Wed, 13 Apr 2011, Yaroslav Halchenko wrote:

> Dear PyMVPA-ers,

> Fresh 0.6.0 RC3 is available from GIT / NeuroDebian repositories.

> RC3 addresses few issues and shortcomings discovered since RC2 and
> provides additional functionality which was already mentioned  a few
> times on different occasions on the mailing list.

> N.B. 0.4.7 Debian packages were  updated as well to absorb few little
>   fixes concerning compatibility with recent libsvm and scipy 0.9.0.  They
>   were uploaded to Debian and NeuroDebian backports.

> Here is a complete ChangeLog for 0.6.0 RC3 from
> http://www.pymvpa.org/changelog.html

> * 0.6.0~rc3 (Thu, Apr 12 2011)

>   * Fixes

>     - Bugfixes regarding the interaction of FlattenMapper and
>       BoxcarMapper that affected event-related analyses.
>     - `Splitter` now handles attribute value `None` for splitting
>       properly.
>     - `GNBSearchlight` handling of  ``roi_ids``.
>     - More robust detection of mod:`scikits.learn` and :mod:`nipy`
>       externals.

>   * New functionality

>     - Added a `Repeater` node to yield a dataset multiple times and
>       `Sifter` node to exclude some datasets. Consequently, the
>       "nosplitting" mode of `Splitter` got removed at the same time.
>     - :file:`tools/niils` -- little tool to list details
>       (dimensionality, scaling, etc) of the files in nibabel-supported formats.

>   * Enhancements

>     - Numerous documentation fixes.
>     - Various improvements and increased flexibility of null distribution
>       estimation of Measures.
>     - All attribute are now reported in sorted order when printing a dataset.
>     - `fmri_dataset` now also stores the input image type.
>     - `Crossvalidation` can now take a custom `Splitter` instance. Moreover, the
>       default splitter of CrossValidation is more robust in terms of number and
>       type of created splits for common usage patterns (i.e. together with
>       partitioners).
>     - `CrossValidation` takes any custom Node as ``errorfx`` argument.
>     - `ConfusionMatrix` can now be used as an ``errorfx`` in Crossvalidation.
>     - ``LOE(ACC): Linear Order Effect in ACC`` was added to
>       `ConfusionMatrix` to detect trends in performances across
>       splits.
>     - A `Node`\ s postproc is now accessible as a property.
>     - `RepeatedMeasure` has a new 'concat_as' argument that allows results to be
>       concatenated along the feature axis. The default behavior, stacking as
>       multiple samples, is unchanged.
>     - `Searchlight` now has the ability to mark the center/seed of an ROI in
>       with a feature attribute in the generated datasets.
>     - ``debug`` takes ``args`` parameter for delayed string
>       comprehensions.  It should reduce run-time impact of ``debug()``
>       calls in regular, non ``-O`` mode of Python operation.
>     - String summaries and representations (provided by ``__str__``
>       and ``__repr__``) were made more exhaustive and more coherent.
>       Additional properties to access initial constructor arguments
>       were added to variety of classes.


>   Also adapts changes from 0.4.6 and 0.4.7 (see corresponding
>   changelogs).

-- 
=------------------------------------------------------------------=
Keep in touch                                     www.onerussian.com
Yaroslav Halchenko                 www.ohloh.net/accounts/yarikoptic
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