[pymvpa] AttributePermutator: Permute within chunks (& subjects) but only training labels

[Richard Dinga]

Hi,
Does this answer your question?
http://www.pymvpa.org/tutorial_significance.html#avoiding-the-trap-or-advanced-magic-101


On Fri, May 19, 2017 at 8:18 PM, Michael Bannert <mbannert at tuebingen.mpg.de>
wrote:

> Dear all,
>
> I would like to use permutation testing for spatially aligned
> across-subject decoding. I have one vector of beta estimates per run
> (aka chunks) and per subject. Hence I figured it would be wise to
> permute within subjects and runs.
>
> I can achieve this (I think) if I use AttributePermutator in this way:
>
> permutator = AttributePermutator(attr='targets', limit=['subject',
> 'chunks'], count=n_perm)
>
> According to the debugging information provided when setting the 'APERM'
> option, the permutations that are produced look reasonable.
>
> However, I would also like to permute only the training data. How can I
> accomplish this?
>
> I tried something like this:
>
> permutator = AttributePermutator(attr='targets', limit={
>          'partitions': 1, 'subject': range(n_subj), 'chunks':
> ['run%02.f' % j for j in range(1, n_runs + 1)]},
>           count=1)
>
> ... but it doesn't work.
>
> I guess I am not very clear on what the documentation of
> AttributePermutator has to say about the limit argument.
>
> Could anyone help?
>
> Thanks & best,
> Michael
>
>
>
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