[Mne_analysis] Grand average of evoked files?

Denis-Alexander Engemann denis.engemann at gmail.com
Thu Sep 11 12:09:14 EDT 2014
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.... Hari, sorry, I was misreading your question. Of course you will need
to devide by the number of subjects if you use sum.
I was just refering to the functional way to add together a list of evokeds.
np.mean will try to devide the summed evoked by an int, which is not
implemented for evoked types.
To complete the operation, what you have to do is this:

grand_ave = np.sum(evokeds)
grand_ave.data /= len(evokeds)



2014-09-11 17:58 GMT+02:00 Denis-Alexander Engemann <
denis.engemann at gmail.com>:

> Btw. the same logic applies to Label objects,
>
> huge_mega_label = np.sum(label_list)
>
> 2014-09-11 17:52 GMT+02:00 Denis-Alexander Engemann <
> denis.engemann at gmail.com>:
>
>>
>>
>> 2014-09-11 17:49 GMT+02:00 Hari Bharadwaj <hari at nmr.mgh.harvard.edu>:
>>
>>> quick question: why np.sum(.) and not np.mean(.)?
>>>
>>>
>> np.sum accesses the evoked.__iadd__ and eovked.__add__ magic methods.
>>
>> a sum is a reduction function, the same as
>>
>> reduce(operator.add, [a, b, c, d, e])
>>
>> if you think of it in terms of iteration,
>> at each step two evokeds are added as specified by their __add__ method.
>>
>>
>>
>>> On Thu, September 11, 2014 11:47 am, Denis-Alexander Engemann wrote:
>>> > Hi,
>>> >
>>> > 2014-09-11 17:14 GMT+02:00 Maria Hakonen <maria.hakonen at gmail.com>:
>>> >
>>> >> Hi,
>>> >>
>>> >> Is there any function that returns the evoked data array?
>>> >>
>>> >
>>> > If you have evokeds saved in a fiff you can just read them.
>>> > If you know the exact condition you want you can pass it to the
>>> condition
>>> > parameter in mne.read_evokeds and the evoked will be returned without
>>> the
>>> > list.
>>> >
>>> > You can also compute the grand average on a list of evokeds
>>> >
>>> > grand_evoked = np.sum(evokeds)
>>> >
>>> >
>>> >> I have made ica on epochs, evoked them and saved the evoked data. Can
>>> I
>>> >> use the evoked files in mne python analyses (I would like to try for
>>> >> example permutation t-test on source data with spatio-temporal
>>> >> clustering
>>> >> and plot grand averages) or should I make ica on raw data?
>>> >>
>>> >
>>> > I would compute ICA on raw data which you can then apply at any later
>>> > stage
>>> > (raw, epochs, evoked).
>>> >
>>> > -Denis
>>> >
>>> >
>>> >>
>>> >> -Maria
>>> >>
>>> >>
>>> >> 2014-09-11 17:36 GMT+03:00 Denis-Alexander Engemann <
>>> >> denis.engemann at gmail.com>:
>>> >>
>>> >>> Maria,
>>> >>>
>>> >>> I think your trouble is related to the fact that you add together
>>> >>> lists,
>>> >>> not evokeds.
>>> >>> The read_evokeds function returns a list by default. This is because
>>> it
>>> >>> assumes to find multiple evokeds in one file.
>>> >>>
>>> >>> HTH,
>>> >>> Denis
>>> >>>
>>> >>> 2014-09-11 16:31 GMT+02:00 Maria Hakonen <maria.hakonen at gmail.com>:
>>> >>>
>>> >>>> Hi,
>>> >>>>
>>> >>>> Thank you for answers!
>>> >>>>
>>> >>>> I tried Mainak's solution but it gives
>>> >>>>
>>> >>>> grand_ave = evoked1+evoked2 +evoked3
>>> >>>>
>>> >>>> grand_ave:
>>> >>>> [<Evoked  |  comment : 'Unknown', time : [-0.099994, 0.499968],
>>> >>>> n_epochs
>>> >>>> : 160, n_channels x n_times : 306 x 721>,
>>> >>>>  <Evoked  |  comment : 'Unknown', time : [-0.099994, 0.499968],
>>> >>>> n_epochs
>>> >>>> : 160, n_channels x n_times : 306 x 721>,
>>> >>>>  <Evoked  |  comment : 'Unknown', time : [-0.099994, 0.499968],
>>> >>>> n_epochs
>>> >>>> : 160, n_channels x n_times : 306 x 721>]
>>> >>>>
>>> >>>> I think that I should get only one evoked if this works correctly.
>>> >>>>
>>> >>>> Maybe I should try Stephen's solution if there is no simpler ones.
>>> >>>>
>>> >>>> -Maria
>>> >>>>
>>> >>>>
>>> >>>> 2014-09-11 14:58 GMT+03:00 Stephen Politzer-Ahles <spa268 at nyu.edu>:
>>> >>>>
>>> >>>>> Hello Maria,
>>> >>>>>
>>> >>>>> I haven't done this with evoked sensor data, only with STCs.
>>> However,
>>> >>>>> as long as evoked data also have an 'add' method, I imagine
>>> something
>>> >>>>> like
>>> >>>>> this should work for you as well:
>>> >>>>>
>>> >>>>>
>>> >>>>>
>>> >>>>> stc_avgs = dict()
>>> >>>>>
>>> >>>>>
>>> >>>>> # get a grand average for each condition (I defined a dictionary of
>>> >>>>> conditions earlier)
>>> >>>>> for condition in conditions.keys():
>>> >>>>>
>>> >>>>> # where all my STCs for each participant in this condition are
>>> stored
>>> >>>>> stcdir = os.environ['SAMPLE'] + '/stcs_ica/' + condition
>>> >>>>>
>>> >>>>> # template for the names of the STCs (I'm only doing left hemi
>>> here)
>>> >>>>> fname = os.path.join( stcdir, '%s-' + condition + '-free-lh.stc' )
>>> >>>>>
>>> >>>>> # use a list comprehension to read in the STC for each subject; I
>>> >>>>> defined a list of participants earlier)
>>> >>>>> stcs = [mne.read_source_estimate(fname % subject) for subject in
>>> >>>>> participants]
>>> >>>>>
>>> >>>>> # math out the grand average
>>> >>>>> stc_avg = reduce(add, stcs)
>>> >>>>> stc_avg /= len(stcs)
>>> >>>>>
>>> >>>>> # put the grand average for this condition into a dictionary of all
>>> >>>>> the
>>> >>>>> conditions
>>> >>>>> stc_avg.subject = 'fsaverage'
>>> >>>>> stc_avgs[condition] = stc_avg
>>> >>>>>
>>> >>>>>
>>> >>>>>
>>> >>>>> (however, Mainak's solution, if it works, looks much simpler!)
>>> >>>>>
>>> >>>>>
>>> >>>>>
>>> >>>>>
>>> >>>>>
>>> >>>>> Stephen Politzer-Ahles
>>> >>>>> New York University, Abu Dhabi
>>> >>>>> Neuroscience of Language Lab
>>> >>>>> http://www.nyu.edu/projects/politzer-ahles/
>>> >>>>>
>>> >>>>> On Thu, Sep 11, 2014 at 3:47 PM, Maria Hakonen
>>> >>>>> <maria.hakonen at gmail.com
>>> >>>>> > wrote:
>>> >>>>>
>>> >>>>>> Hi all,
>>> >>>>>>
>>> >>>>>> I would like to compute a grand average of evoked files.
>>> >>>>>>
>>> >>>>>> It seems to work as: grand_ave = np.mean([evoked1.data,
>>> >>>>>> evoked2.data,
>>> >>>>>> evoked3.data],1)
>>> >>>>>>
>>> >>>>>> However, the problem is that if the evoked data is saved as:
>>> >>>>>>
>>> >>>>>> evoked.save("filename-ave.fif")
>>> >>>>>>
>>> >>>>>> and loaded as:
>>> >>>>>>
>>> >>>>>> evoked = mne.read_evokeds("filename-ave.fif")
>>> >>>>>>
>>> >>>>>> evoked doesn't have attribute data.
>>> >>>>>>
>>> >>>>>> I also tried:
>>> >>>>>> grand_ave = np.mean([evoked1, evoked2, evoked3],1)
>>> >>>>>>
>>> >>>>>> but this gives an error:
>>> >>>>>>
>>> >>>>>> TypeError                                 Traceback (most recent
>>> >>>>>> call
>>> >>>>>> last)
>>> >>>>>> /scratch/braindata/mhhakone/intell/<ipython-input-65-f6e26a212f6a>
>>> >>>>>> in
>>> >>>>>> <module>()
>>> >>>>>> ----> 1 grand_ave = np.mean([evoked1, evoked2, evoked3],1)
>>> >>>>>>
>>> >>>>>> /usr/lib/python2.7/dist-packages/numpy/core/fromnumeric.pyc in
>>> >>>>>> mean(a,
>>> >>>>>> axis, dtype, out)
>>> >>>>>>    2371         mean = a.mean
>>> >>>>>>    2372     except AttributeError:
>>> >>>>>> -> 2373         return _wrapit(a, 'mean', axis, dtype, out)
>>> >>>>>>    2374     return mean(axis, dtype, out)
>>> >>>>>>    2375
>>> >>>>>>
>>> >>>>>> /usr/lib/python2.7/dist-packages/numpy/core/fromnumeric.pyc in
>>> >>>>>> _wrapit(obj, method, *args, **kwds)
>>> >>>>>>      35     except AttributeError:
>>> >>>>>>      36         wrap = None
>>> >>>>>> ---> 37     result = getattr(asarray(obj),method)(*args, **kwds)
>>> >>>>>>      38     if wrap:
>>> >>>>>>      39         if not isinstance(result, mu.ndarray):
>>> >>>>>>
>>> >>>>>> TypeError: unsupported operand type(s) for /: 'Evoked' and 'float'
>>> >>>>>>
>>> >>>>>>
>>> >>>>>>
>>> >>>>>> How can I get data from -ave.fif files? (The -ave.fif files I have
>>> >>>>>> saved seems to open correctly in xFit, Matlab and mne_analyze.)
>>> >>>>>> Or is there some better way to calculate the grand average of
>>> >>>>>> -ave.fif
>>> >>>>>> files?
>>> >>>>>>
>>> >>>>>> Thanks already in advance!
>>> >>>>>>
>>> >>>>>> Regards,
>>> >>>>>> Maria
>>> >>>>>>
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>>>
>>> --
>>> Hari Bharadwaj
>>> Post-doctoral Associate,
>>> Center for Computational Neuroscience
>>>   and Neural Technology (CompNet),
>>> Boston University
>>> 677 Beacon St.,
>>> Boston, MA 02215
>>>
>>> Martinos Center for Biomedical Imaging,
>>> Massachusetts General Hospital
>>> 149 Thirteenth Street,
>>> Charlestown, MA 02129
>>>
>>> hari at nmr.mgh.harvard.edu
>>> Ph: 734-883-5954
>>> www.haribharadwaj.com
>>>
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>>
>>
>
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