[Eeglablist] Error while precomputing STUDY: NaN values in cluster.sets

[Nikola Vukovic]

Hmm, so there should be two option files then? In my case "which -all
eeg_options" only returns one
line: /Applications/EEGLAB/eeglab13.5.4b/functions/adminfunc/eeg_options.m


On Tue, Dec 1, 2015 at 9:46 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
wrote:

> Dear Nikokla,
>
> Try 'which -all eeg_options'. What does it say? I show mine below as an
> example of good case.
>
> >> which -all eeg_options
> /home/makoto/eeg_options.m
> /data/projects/makoto/Tools/eeglab/functions/adminfunc/eeg_options.m  %
> Shadowed
>
> Makoto
>
> On Tue, Dec 1, 2015 at 12:37 PM, Nikola Vukovic <vukovicnikola at gmail.com>
> wrote:
>
>> Hi Makoto,
>>
>> In the options pop up, precomputing ICA is checked correctly, and I think
>> also in the option file. Here's what's inside:
>>
>> % eeg_options() - eeglab option script
>> %
>> % Note: DO NOT EDIT, instead use pop_editoptions() or the menu
>> %       /File/Maximize memory in EEGLAB gui
>>
>> % STUDY and file options (set these checkboxes if you intend to work with
>> studies)
>> option_storedisk = 1 ; % If set, keep at most one dataset in memory. This
>> allows processing hundreds of datasets within studies.
>> option_savetwofiles = 1 ; % If set, save not one but two files for each
>> dataset (header and data). This allows faster data loading in studies.
>> option_saveversion6 = 1 ; % If set, write Matlab files in Matlab v6.5
>> (max compatibility). If not, write files in Matlab v7.3 (larger than 2Gb).
>> % Memory options
>> option_single = 1 ; % If set, use single precision under Matlab 7.x. This
>> saves RAM but can lead to rare numerical imprecisions.
>> option_memmapdata = 0 ; % If set, use memory mapped array under Matlab
>> 7.x. This may slow down some computation (beta).
>> option_eegobject = 0 ; % If set, use the EEGLAB EEG object instead of the
>> standard EEG structure (beta).
>> % ICA options
>> option_computeica = 1 ; % If set, precompute ICA activations. This
>> requires more RAM but allows faster plotting of component activations.
>> option_scaleicarms = 1 ; % If set, scale ICA component activities to RMS
>> (Root Mean Square) in microvolt (recommended).
>> % Folder options
>> option_rememberfolder = 1 ; % If set, when browsing to open a new dataset
>> assume the folder/directory of previous dataset.
>> % Toolbox options
>> option_donotusetoolboxes = 0 ; % If set, do not use Matlab additional
>> toolboxes functions even if they are present (need to restart EEGLAB).
>> % EEGLAB connectivity and support
>> option_checkversion = 1 ; % If set, check for new version of EEGLAB at
>> startup.
>> option_chat = 0 ; % If set, enable EEGLAB chat - currently UCSD only -
>> restart EEGLAB after changing that option.
>>
>>
>> Nikola
>>
>> On Tue, Dec 1, 2015 at 9:25 PM, Makoto Miyakoshi <mmiyakoshi at ucsd.edu>
>> wrote:
>>
>>> Dear Nikola,
>>>
>>> I've seen this. In my case at least, it was because EEGLAB's default set
>>> up file was not correctly figured out, which prevented EEGLAB from creating
>>> EEG.icaact etc (do you remember that there are some items in 'memory and
>>> other options' that determines what to do with computed ica data... maybe
>>> related to that). After fixing the default parameter file, it start to work
>>> normally.
>>>
>>> I don't know if this is also the case for you, but just in case please
>>> check it out.
>>>
>>> Makoto
>>>
>>> On Mon, Nov 23, 2015 at 3:33 PM, Nikola Vukovic <vukovicnikola at gmail.com
>>> > wrote:
>>>
>>>> Dear EEGLAB list
>>>>
>>>> I would be very grateful is someone could help me out with an error
>>>> I've been getting. When I try to precluster components in a given STUDY (it
>>>> happens for several study files), I get the following error:
>>>>
>>>> FOR CLUSTERING, YOU MAY ONLY USE DIPOLE OR SCALP MAP CLUSTERING. This is
>>>> because some datasets do not have ICA pairs. Look for NaN values in
>>>> STUDY.cluster(1).sets which indicate missing datasets. Each column in this
>>>> array indicate datasets with common ICA decompositions.
>>>>
>>>> Looking inside the cluster(1).sets, I can indeed find some NaN fields, suggesting not all files have associated ICA decomposition data. This, however, is puzzling because I made sure to do ICA on each subject's dataset *before* epoching, meaning that all sets for individual conditions share the same weights for a subject. After getting this error I even tried to copy the weights (EEG.icawinv + EEG.icasphere + EEG.icaweights + EEG.icachansind) from the unepoched set to all the epoched ones.
>>>>
>>>> Did anyone have this error too, and how could it be solved?
>>>>
>>>> Thanks for any help,
>>>>
>>>> Nikola
>>>>
>>>>
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>>>
>>>
>>>
>>> --
>>> Makoto Miyakoshi
>>> Swartz Center for Computational Neuroscience
>>> Institute for Neural Computation, University of California San Diego
>>>
>>
>>
>
>
> --
> Makoto Miyakoshi
> Swartz Center for Computational Neuroscience
> Institute for Neural Computation, University of California San Diego
>
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