[pymvpa] normalization: zscore by example?

[Yaroslav Halchenko]

nothing is impossible... but why would you like to do that? quick
situation/answers pairs

* I care only about classification performance and don't do any feature
  (voxel) diagnosticity analysis such as searchlight

  well -- then zscoring is legit... but I don't think we have builtin
  mapper/function for it, since if you don't have any groups of voxels
  to care about zscoring independently, then it is as simple to in
  pure python as

  ds.samples -= np.mean(ds, axis=1)[:, None]
  ds.samples /= np.std(ds, axis=1)[:, None]

* I do care about per-voxel estimates of diagnosticity

  DO NOT ZSCORE ACROSS FEATURES (VOXELS)! ;)

On Mon, 07 Nov 2011, Mike E. Klein wrote:

>    Hi all,
>    I realize now (after a boneheaded mistake), that PyMVPA's zscore()
>    function is normalizing for all the values across a chunk (looking at each
>    voxel individually). I'm wondering if it's possible to, instead, find the
>    zscores for all the voxels in a single volume (against each voxel's
>    resting state), considering each 3d volume separately.�
>    Thanks,
>    Mike

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