[Mne_analysis] epochs

[Eric Larson]

        External Email - Use Caution        

You can look at `epochs.drop_log` or `epochs.plot_drop_log` to see why. See
for example:

https://mne.tools/dev/auto_tutorials/epochs/plot_10_epochs_overview.html#creating-epoched-data-from-a-raw-object

Eric


On Tue, Apr 14, 2020 at 9:37 AM Andrade Rey René <rene.andrade at edu.uah.es>
wrote:

>         External Email - Use Caution
>
> Dear experts:
> I am trying to run a tutorial recommended.
> https://mne.tools/dev/auto_tutorials/preprocessing/plot_20_rejecting_bad_data.html#rejecting-epochs-based-on-channel-amplitude
>
> My data is not from the tutorial. It is an EEG. Also I have this outputs.
> Of course I use evoked = epochs.average() and it says less than one epoch.
> What can I do?
>
> >>> print(events)
> [[     0      0  65536]
>  [ 18275      0    128]
>  [ 19387      0      2]
>  [ 20422      0      2]
>  [ 32156      0    128]
>  [ 46029      0    128]
>  [ 46873      0      2]
>  [ 47522      0      4]
>  [ 72924      0    128]
>  [ 73666      0      2]
>  [ 74230      0      2]
>  [ 92717      0    128]
>  [ 94025      0      2]
>  [ 94590      0      2]
>  [108211      0    128]
>  [109532      0      2]
>  [110110      0      4]
>  [130866      0    128]
>  [131605      0      4]
>  [132900      0      2]
>  [156301      0    128]
>  [157153      0      2]
>  [157843      0      4]
>  [176353      0    128]
>  [177182      0      2]
>  [177821      0      2]
>  [191436      0    128]
>  [192495      0      4]
>  [193129      0      2]
>  [233638      0    128]
>  [234323      0      4]
>  [234936      0      4]
>  [248375      0    128]
>  [249218      0      2]
>  [249817      0      2]
>  [255773      0    128]
>  [256493      0      2]
>  [257060      0      4]
>  [286302      0    128]
>  [287009      0      4]
>  [287601      0      2]
>  [320684      0    128]
>  [321413      0      4]
>  [340579      0    128]
>  [341369      0      4]
>  [342650      0      2]
>  [383286      0    128]
>  [384166      0      2]
>  [384810      0      2]
>  [406476      0    128]
>  [407297      0      2]
>  [407956      0      4]
>  [409017      0      2]
>  [444348      0    128]
>  [445107      0      2]
>  [445683      0      4]
>  [446969      0      2]
>  [482043      0    128]
>  [482761      0      2]
>  [483421      0      2]
>  [521536      0    128]
>  [522365      0      2]
>  [523009      0      2]
>  [535415      0    128]
>  [536091      0      4]
>  [536691      0      2]
>  [573609      0    128]
>  [574341      0      4]
>  [574916      0      2]
>  [588192      0    128]
>  [588973      0      4]
>  [589524      0      2]
>  [611318      0    128]
>  [612110      0      2]
>  [612703      0      4]
>  [613416      0      2]
>  [634153      0    128]
>  [635029      0      2]
>  [635592      0      2]
>  [636193      0      2]
>  [662819      0    128]
>  [663674      0      2]
>  [664355      0      4]
>  [665003      0      2]
>  [677292      0    128]
>  [678266      0      2]
>  [678926      0      2]
>  [679619      0      2]]
>
>
>
> >>> epochs = mne.Epochs(raw, events, event_id=dict(aud=65536, vis=2,
> aud2=4, vis2=128), tmin=-0.2, tmax=0.5,reject=dict(eeg=100e-6),
> flat=dict(eeg=1e-6),preload=True)
>
> 88 matching events found
> Applying baseline correction (mode: mean)
> Not setting metadata
> 0 projection items activated
> Loading data for 88 events and 180 original time points ...
>
>
> …
>
>
> 88 bad epochs dropped
>
>
>
> Sincerely,
> Andrade.
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