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Mar 15, 2016


pymvpa2 Debian release 2.4.3-1
Mar 15, 2016


* 2.4.3 (Tue, 15 Mar 2016)
  * Fixes

    - Fixed memory leaking in libsvm bindings introduced in 2.4.2 (gh-443)
    - Avoid overriding parameters defined in subclasses with the ones from
      super class
    - Address freshish deprecations (warnings) in sklearn, scipy, etc
    - Workaround in the test for numpy's corrcoef issue resulting in corrcoef
      a bit outside of [-1, 1] range
Mar 8, 2016


pymvpa2 Debian release 2.4.2-1
Mar 8, 2016


* 2.4.2 (Tue, 8 Mar 2016)
  * Fixes

    - *Important:*
      Reverse mapping of some chained Flatten/StaticSelection mappers did not
      work correctly e.g. if you selected some features from already masked
      fmri_dataset. This could have resulted in incorrect cluster counts by
      :class:`~mvpa2.algorithms.group_clusterthr.GroupClusterThreshold`.  Please
      recreate your datasets and re-estimate GroupClusterThreshold if that was
      the case for you
    - ad-hoc searchlights (gnb, m1nn) can now operate with partitioners which
      leave some samples out of training and testing sets.  Also `splitter` argument
      was added to them for greater flexibility
    - Due to the bug in OpenfMRI datasets' TR within NIfTIs being hardcoded to
      wrong 1.0, so `scan_key.txt` will now be consulted if TR is 1 in the .nii*
    - Compatibility with :mod:`~numpy` 1.10 fixes
    - :class:`CachedQueryEngine` acquired .ids making it compatible with some
      ad-hoc searchlights
    - `FeatureSelection` acquired `__iadd__` fixing the incorrect behavior upon
      reverse after a sequence of feature selections

  * Deprecations/removal

    - `Hamster` is gone.

  * Enhancements

    - Bundled version of libsvm updated to 3.12.  Now includes maxiter
      setting which prevents infinite looping which can happen in some rare cases
    - A swarm of stylistic improvements ("is not", PEP8, etc) which should not
      affect functionality but could result in more robust operation
    - `CrossValidation` can now operate with a None generator (i.e. partitioner) using
      solely `Splitter` to generate a single split on original dataset.  Provides easier
      means for "cross-classification"
    - :class:`~mvpa2.measures.nnsearchlight.M1NNSearchlight` can now do classification
      based on correlation distance (just provide `dfx=one_minus_correlation` to kNN)
    - libsvm bindings for SVM were refactored to interface via svmc not _svmc interface,
      which made them also compatible with swig 3.x
    - :meth:`~mvpa2.base.dataset.AttrDataset.to_npz` and :meth:`~mvpa2.base.dataset.AttrDataset.from_npz`
      to interface Datasets through NumPy's npz files
    - Variety of PEP8 and other tune ups for more readable code
    - :class:`~mvpa.featsel.rfe.SplitRFE` can now work with static measures (e.g.
      `OneWayAnova`) and `BinaryFxFeaturewiseMeasure`.  So do feature selection
      with nested cross-validation without double-dipping!

  * New functionality

    - :class:`~mvpa2.generators.partition.FactorialPartitioner` for factorial designs
      to cross-validate across sub-ordinate category samples (more efficient/avoids
      previously recommend ChainMapper of NFoldPartitioner and Sifter)
Nov 18, 2015


pymvpa2 Debian release 2.4.1-1
Nov 18, 2015


* 2.4.1 (Wed, 18 Nov 2015)
  * New functionality

    - :class:`~mvpa.datasets.gifti` can write GIFTI files that contain both
      dataset samples and surface anatomy (vertices and faces). Such GIFTI
      files can be read by FreeSurfer.

  * Deprecations/removal

    - :file:`tools/niils` -- tool removed, since the functionality was moved into
      :mod:`nibabel` under the name `nib-ls`
    - Drop support for nibabel < 2.0.0

  * Enhancements

    - "Native" use of :mod:`~duecredit` to provide citations for PyMVPA itself
      and functionality/methods it implements.
    - Unified use of os.path.join as pathjoin.
    - :class:`~mvpa.mappers.procrustean.ProcrusteanMapper` computes reconstruction
      now more efficiently (just a transpose with proper scaling) in case of
      non-oblique transformations.

  * Refactorings/misc changes

    - :class:`~mvpa.mappers.procrustean.ProcrusteanMapper` now just returns transpose
      in reverse if transformation is non-oblique (instead of an explicit inverse).

  * Fixes

    - 2.4.0 was released with incorrect `__version__` (as 2.3.1)
    - Fixes to `ofmotionqc` command implementation
    - Variety of fixes for compatibility with recent matplotlib, python3
    - Fixes to SVDMapper in reverse when projection is not a matrix

Read release notes

Oct 25, 2015


pymvpa2 Debian release
Oct 14, 2015


"Tag"-release of PyMVPA for consistent deployment.
Proper 2.4.1 release to come
May 11, 2015


pymvpa2 Debian release 2.4.0-1
May 11, 2015


* 2.4.0 (Mon, 11 May 2015)
  * New functionality

    - Support for CoSMoMVPA ( in
      :mod:`~mvpa2.datasets.cosmo` providing dataset input/output
      (:meth:`~mvpa2.datasets.cosmo.cosmo_dataset` and
      :meth:`~mvpa2.datasets.cosmo.map2cosmo`) and neighborhood input
      (:class:`~mvpa2.datasets.cosmo.CosmoQueryEngine`). This allows for
      for running searchlights (:class:`mvpa2.datasets.cosmo.CosmoSearchlight`)
      on data from CoSMoMVPA (fMRI and MEEG).
    - :func:`~mvpa2.datasets.miscfx.remove_nonfinite_features` removes
      features with non-finite values, i.e. NaNs or Infs, for any sample.
    - :func:`~mvpa2.misc.stats.binomial_proportion_ci` for computing
      confidence intervals on proportions of Bernoulli trial outcomes.
    - New mapper for removing sample means from features.
    - New algorithm for statistical evaluation of clusters in accuracy maps
      of group-based searchlight classification analyses. This is essentially
      an improved implementation of Stelzer et al., NeuroImage, 2013.
    - New identity mapper. Does nothing, but goes were only mappers can go.
    - Simplified selection of samples/feature in a dataset. One can now
      specify sets of attribute values to define sample/feature subsets.
    - IO adaptor for OpenFMRI-formated datasets. Load arbitrary bits from such
      a dataset, or automatically build event-related dataset (optionally with
      NiPy-based HRF-modeling).  `tutorial_data_25mm` was converted to
      OpenFMRI layout and extended also with `1slice` flavor.
    - New command line command to generate a motion plot for an
      OpenFMRI-formated dataset.
    - New convenience functions for boxplots and outlier detection.
    - Reincarnated (similar functionality was removed for 2.0 release)
      convenience methods (
      :meth:`~mvpa2.base.collections.UniformLengthCollection.match` and
      to ease selecting parts of a dataset

  * Enhancements

    - :class:`~mvpa2.mappers.flatten.ProductFlattenMapper` accepts
      explicit names of factors in the constructor.
    - HollowSphere() can now, optionally, include the center feature.
    - :func:`~mvpa2.datasets.mri.fmri_dataset` no longer stores original copy
      of the NIfTI file header -- it converts it to `dict` representation to
      remain portable. Use :func:`~mvpa2.datasets.mri.strip_nibabel` to convert
      old datasets to new format if/when necessary.

  * Fixes

    - :class:`~mvpa2.algorithms.hyperalignment.Hyperalignment` with regularization
      (alpha != 1.0) was producing incorrect transformations because they were
      driven by offsets of the last subject.  Fixed by not "auto_train"ing
      regularization projection.
    - :func:`~mvpa2.misc.plot.lightbox.plot_lightbox` should take a
      slice index from the last dimension, not the leading one if no
      `slices` argument was provided.
    - Improved Python3k compatibility in :mod:`~mvpa2.base.state`,
      :mod:`~mvpa2.tests`, and :mod:`~mvpa2.clfs.stats` modules, and in
      libsvmlrc msvc building.
    - Partial fix for compatibility with ancient scipy on SPARC using

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