[Mne_analysis] cluster permutation connectivity matrix

[Chris Holdgraf]

I think we should clarify this is the docstring, add a check for the input
and raise an error, and maybe add an example. Wdyt? I can open a pr if that
sounds good.

On Fri, Sep 22, 2017, 12:43 PM Alexandre Gramfort <
alexandre.gramfort at inria.fr> wrote:

> hi yvonne,
>
> connectivity must be a sparse matrix not a numpy array
>
> from scipy import sparse
> connectivity = sparse.eye(numChan)
>
> HTH
> Alex
>
>
> On Wed, Sep 20, 2017 at 10:00 PM, Yvonne Fonken <yfonken at berkeley.edu>
> wrote:
>
>> Hi Alex,
>>
>> Thank you for your reply.
>>
>> This is my code, with two versions of a diagonal connectivity matrix
>> (using version 14.1 of MNE):
>> # Implement cluster permutation
>> numChan = Data.shape[1] # Data is shaped: Trials (115) x channels (217) x
>> timepoints (30) numpy array
>> #connectivity =  np.diagflat( range(0,numChan), k = 0)
>> connectivity =  np.diagflat( np.ones((1,numChan)), k = 0) # N x N
>> diagonal matrix with N being # of electrodes
>> TestData = np.swapaxes(Data, 1,2) # trials x time x space (electrodes)
>> T_obs, clusters, p_values, H0 =
>> mne.stats.permutation_cluster_1samp_test(TestData, n_permutations = 500,
>> tail = 0, connectivity = connectivity)
>>
>> Both versions of the connectivity matrix now give me the following error:
>> 'numpy.ndarray' object has no attribute 'tocsr'
>>
>> Thanks,
>> Yvonne
>>
>> On Tue, Sep 19, 2017 at 1:02 AM, Alexandre Gramfort <
>> alexandre.gramfort at inria.fr> wrote:
>>
>>> Hi Yvonne
>>>
>>> I would have said that a sparse diagonal matrix should work.
>>>
>>> can you share the code snippet you used?
>>>
>>> Alex
>>>
>>>
>>> On Tue, Sep 19, 2017 at 3:17 AM, Yvonne Fonken <yfonken at berkeley.edu>
>>> wrote:
>>> > Hi all,
>>> >
>>> > I am trying to apply the cluster permutation function in MNE on
>>> intracranial
>>> > data (electrodes by time points), either by using
>>> > mne.stats.permutation_cluster_test, or
>>> > mne.stats.permutation_cluster_1samp_test. In this case, I do not want
>>> to
>>> > cluster across electrodes, but I want to include this dimension in
>>> order to
>>> > correct for multiple comparisons.
>>> >
>>> > My question is: how do I specify to only cluster over time, and not
>>> > electrodes? Can I do this using the connectivity matrix, and if yes,
>>> what
>>> > would a connectivity matrix look like when all electrodes do not have
>>> > neighbors? I've tried using diagonal matrices already, but I still get
>>> > clusters spanning multiple electrodes.
>>> >
>>> > Thanks,
>>> > Yvonne
>>> >
>>> > --
>>> > Yvonne Fonken
>>> > PhD Candidate
>>> > Helen Wills Neuroscience Institute
>>> > University of California, Berkeley
>>> >
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>>
>>
>>
>> --
>> Yvonne Fonken
>> Graduate student
>> Helen Wills Neuroscience Institute
>> University of California, Berkeley
>>
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