[pymvpa] Announcement: 0.4.4 release (git/sources/Debian/Ubuntu/Windows/Fedora/SuSe/RedHat/CentOS)

[PyMVPA Team]

Dear PyMVPA users,

I am glad to announce that we are releasing 0.4.4 version of
PyMVPA.

So far we have:
  * pushed/tagged sources in git repository
    (git://git.debian.org/git/pkg-exppsy/pymvpa.git)
  * uploaded Debian packages into Debian/sid proper
    (should become available later on today)
  * uploaded Debian packages into http://neuro.debian.org
    repository for:
	+ Debian: lenny, squeeze
	+ Ubuntu: jaunty, karmic
	(http://neuro.debian.net/pkgs/python-mvpa.html)
  * source tarballs and windows installer available from
    usual location
    https://alioth.debian.org/frs/?group_id=30954
  * RPM-based GNU/Linux Distributions
	available from OpenSUSE Build Service. See
    http://pymvpa.org/installation.html#rpm-based-gnu-linux-distributions 

This is primarily a bugfix release, probably the last in 0.4 series since
development for 0.5 release is leaping forward -- please keep an eye on the
mailing list for the announcement of availability of snapshots of development
version.


Changelog for the release is:

  * New functionality (19 NF commits):

    - :class:`~mvpa.clfs.gnb.GNB` implements Gaussian Naïve Bayes
      Classifier.
    - :func:`~mvpa.misc.fsl.base.read_fsl_design` to read FSL FEAT design.fsf
      files (Contributed by Russell A. Poldrack).
    - :class:`~mvpa.datasets.miscfx.SequenceStats` to provide basic
      statistics on labels sequence (counter-balancing,
      autocorrelation).
    - New exceptions :class:`~mvpa.clfs.base.DegenerateInputError` and
      :class:`~mvpa.clfs.base.FailedToTrainError` to be thrown by
      classifiers primarily during training/testing.
    - Debug target `STATMC` to report on progress of Monte-Carlo
      sampling (during permutation testing).

  * Refactored (15 RF commits):

    - To get users prepared to 0.5 release, internally and in some
      examples/documentation, access to states and
      parameters is done via corresponding collections, not from the
      top level object (e.g. `clf.states.predictions` instead of
      soon-to-be-deprecated `clf.predictions`).  That should lead also
      to improved performance.
    - Adopted copy.py from python2.6 (support Ellipsis as well).

  * Fixed (38 BF commits):

    - GLM output does not depend on the enabled states any more.
    - Variety of docstrings fixed and/or improved.
    - Do not derive NaN scaling for SVM's C whenever data is
      degenerate (lead to never finishing SVM training).
    - :mod:`~mvpa.clfs.sg` :

      + KRR is optional now -- avoids crashing if KRR is not available.
      + tolerance to absent `set_precompute_matrix` in svmlight in
        recent shogun versions.
      + support for recent (present in 0.9.1) API change in exposing
        debug levels.

    - Python 2.4 compatibility issues: :class:`~mvpa.clfs.knn.kNN` and
      :class:`~mvpa.featsel.ifs.IFS`

Enjoy!
-- 
                                  .-.
=------------------------------   /v\  ----------------------------=
Keep in touch                    // \\     (yoh@|www.)onerussian.com
Yaroslav Halchenko              /(   )\               ICQ#: 60653192
                   Linux User    ^^-^^    [175555]


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