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@yarikoptic yarikoptic released this 27 Aug 16:24
· 262 commits to master since this release

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