2.6.0

Primarily a bugfix release with some added new functionality. People contributed
code to the release: Matteo Visconti dOC, Yaroslav Halchenko, Nikolaas N. Oosterhof,
Feilong Ma, Christopher J. Markiewicz, Swaroop Guntupalli.

• IMPORTANT possibly backward-incompatible fixes
  • Dataset's :func:~mvpa2.base.dataset.vstack and :func:~mvpa2.base.dataset.hstack
    now by default would drop those feature or sample (fa, sa) attributes
    which do not have the same value across all datasets ("drop_nonunique").
    Previous behaviour was to update aggregated collections, so the attribute
    value of the last dataset would have been stored in the stacked dataset.
    Such behaviour could be brought back by fa="update" for vstack or
    similar value for sa="update" for hstack calls.
    If you find that some sa/fa you have relied on using in your code is no
    longer available after stacking, verify that you did intend to maintain the
    "last known" value, and adjust argument in stacking function to "update".
• Fixes
  • Fixed minor bug in computing ico linear divisions while working with surfaces
  • Handling of ref_ds in :class:~mvpa2.algorithms.searchlight_hyperalignment.SearchlightHyperalignment
  • Compatibility fixes for :mod:scipy 0.18.0 and :mod:nibabel 2.1.0.
• New functionality
  • pymvpa2 scatter command line and :mod:~mvpa2.misc.plot.scatter module to scatter plot
    datasets and nifti volumes, with coloring based on spatial location (see
    e.g. OHBM12 poster
    for an example, proper demo is coming)
• Enhancements
  • Allow for "4D" mri mask volumes with degenerate time dimension (e.g. coming
    from AFNI)
  • pymvpa2 ttest could operate now on h5save'd datasets
  • It is possible now to h5save trained Hyperalignment instances
  • :class:~mvpa2.generators.resampling.Balancer and
    :class:~mvpa2.generators.permutation.AttributePermutator now got rng
    argument to seed RNG. Please use an int as a seed specification if you
    want random selections/permutations be consistent across searchlights

2.5.0

• Fixes
  • Various python3 related small fixes
  • Minor fix allowing adhoc searchlights (e.g. gnbsearchlight) to work with
    CustomPartitioner
  • Fixed SmartVersion to not infinitely loop upon receiving an awkward
    version string
• New functionality
  • :class:~mvpa2.algorithms.searchlight_hyperalignment.SearchlightHyperalignment
    to carry out full-datset/brain hyperalignment of functional data while
    honoring spatial neighborhoods.
    See :ref:Guntupalli et al., Cerebral Cortex (2016) <GHH+16> A Model of
    Representational Spaces in Human Cortex for more information
  • :class:~mvpa2.measures.rsa.Regression measure to compute regularized
    regression (Ridge or Lasso) on the computed neural dissimilarity matrix
  • :class:~mvpa2.misc.surfing.queryengine.SurfaceRingQueryEngine
• Enhancements
  • The ofmotionqc command line command has been renamed to
    plotmotionqc. It no longer requires a dataset formatted in
    OpenFMRI-style, but works with any organization of input data
  • SplitRFE docstring example reordered suggested mappers (l2 -> abs -> mean)
  • Show only summary of representation of internal _src2aux of
    VolumeMaskDictionary object, which otherwise could be too big to print

2.4.1

• 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

2.4.0

* 2.4.0 (Mon, 11 May 2015)

  * New functionality

    - Support for CoSMoMVPA (http://cosmomvpa.org) 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
      :meth:`~mvpa2.datasets.base.Dataset.select`)
      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
      :mod:`~mvpa2.datasets.cosmo`.

2.3.1

* 2.3.1 (Tue, 20 May 2014)

  Primarily a bugfix release pushed out to avoid mvpa2.suite meltdown
  if new scipy 1.4.0 is used.

  * API changes

    - Deprecation: :class:`~mvpa2.base.param.Parameter` now uses `constraints` argument
      of type :class:`~mvpa2.base.constraints.Constraint` instead of string
      `allowedtype`.  `allowedtype` argument will be removed completely in the
      future 2.4 release.

  * New changes

    - :mod:`~mvpa2.clfs.dummies` now provides utterly useful
      :class:`~mvpa2.clfs.dummies.RandomClassifier` and others for code testing
      which could also be used to verify absent double-dipping etc.

  * Enhancements

    - :class:`~mvpa2.mappers.fx.FxMapper` now will provide consistent order
      of groups of items.  It also got a new argument `order` with available
      value of 'occurrence' to that groups would get ordered by their occurance
      in the original dataset.

  * Fixes

    - :class:`~mvpa2.mappers.corrstability.CorrStability` should be able to
      deal with other sample attributes (not only 'targets') and should divide
      by variance correctly to provide correlation coefficient as output.
    - robustify check scipy's rdist which should avoid crash upon import of
      mvpa2.suite because of stripped down scipy 1.4.0 API.
    - various typos in docstrings (we do welcome contributions ;) ).

2.3.0

upstream/2.3.0

Rushed out 2.3.0 release, probably to be followed with rapid 2.3.1