[Mne_analysis] No digitization found - ICA

[Eric Larson]

        External Email - Use Caution        

The error is trying to tell you that the type(events) is not an ndarray,
but rather a tuple. If you print(type(events)), you should see "tuple".
This is because events_from_annotations returns two values:

https://mne.tools/stable/generated/mne.events_from_annotations.html

And those two values really come in a tuple. So you need:

events, event_ids_annot = mne.events_from_annotations(...)

or something like that. For more information, see:

https://mne.tools/stable/auto_tutorials/intro/plot_20_events_from_raw.html#converting-between-events-arrays-and-annotations-objects

Eric


On Wed, Sep 23, 2020 at 8:15 PM Daniel Cabral <dac0069 at auburn.edu> wrote:

>         External Email - Use Caution
>
> Hi,
> Thanks for the response. It worked perfectly. I do have one more question
> though.
> I have been struggling to find the events from my files. Here is what I've
> got so far:
> I am attaching a vhdr file with the markers
> import mne
>
> mne.set_log_level('WARNING')
> fname = "go.nogo.01.vhdr"
> raw = mne.io.read_raw_brainvision(fname, preload=True)
>
> montage =
> mne.channels.make_standard_montage('standard_1020')raw.set_montage(montage,
> raise_if_subset = False)
>
> ica = mne.preprocessing.ICA(n_components=15, random_state=97)
> ica.fit(raw.copy().filter(1,40))
> ica.plot_sources(raw);
> ica.plot_components()
>
> raw = ica.apply(raw.copy(), exclude = ica.exclude)
>
> raw.plot();
>
> events = mne.events_from_annotations(raw, event_id='auto')
> events;
> tmin, tmax = -0.2, 0.5
>
> events_nogo_sed = [88,89,90,91,92,93,94,95,96,97,98,99,100,
>                           101,102,103,104,105,106,107,108,109,110,
>                           111,112,113]
>
> epochs = mne.Epochs(raw, events, events_nogo_sed, tmin, tmax)
>
> TypeError: events should be a NumPy array of integers, got <class 'tuple'>
>
>
>
>
> ------------------------------
> *From:* mne_analysis-bounces at nmr.mgh.harvard.edu <
> mne_analysis-bounces at nmr.mgh.harvard.edu> on behalf of Eric Larson <
> larson.eric.d at gmail.com>
> *Sent:* Monday, September 21, 2020 7:05 AM
> *To:* Discussion and support forum for the users of MNE Software <
> mne_analysis at nmr.mgh.harvard.edu>
> *Subject:* Re: [Mne_analysis] No digitization found - ICA
>
>
>         External Email - Use Caution
>
> Your channels appear to use the 10-20 system. Something like this should
> work:
>
> import mne
> fname = "go.nogo.01.vhdr"
> raw = mne.io.read_raw_brainvision(fname, preload=True)
> raw.filter(1, 40)
> montage = mne.channels.make_standard_montage('standard_1020')
> raw.set_montage(montage, on_missing='ignore')  # RIghtEar missing
> ica = mne.preprocessing.ICA(n_components=15, random_state=97)
> ica.fit(raw)
> ica.plot_sources(raw)
> ica.plot_components()
>
> See for more information:
>
>
> https://mne.tools/dev/auto_tutorials/intro/plot_40_sensor_locations.html?highlight=set_montage
>
> Eric
>
>
> On Mon, Sep 21, 2020 at 8:37 AM Daniel Cabral <dac0069 at auburn.edu> wrote:
>
>         External Email - Use Caution
>
> Hi,
> I am trying to work with a .vhdr file from brainvision. I loaded the data,
> and did some plots. Then, I tried the ICA, but I ended up with the
> following error: "No digitization points found". I'm guessing this is
> related to the set montage. I did a lot of searching, and I noticed a lot
> of people have the same issue. Still, I can't seem to find a way to solve
> this.  I am also attaching the file, in case you need. For now, I just want
> to be able to run the ICA and to properly do the set the montage (if
> needed). I looked all over the MNE website for solutions, but I simply
> can't work this out.
>
> PS: MNE is amazing!
>
> Here is what I've got so far:
>
> import mne
>
> mne.set_log_level('WARNING')
> fname = "go.nogo.01.vhdr"
> raw = mne.io.read_raw_brainvision(fname, preload=True)
>
> raw.plot_psd(fmax = 50)
>
> raw.plot()
>
> raw.filter(1,40)
>
> raw.plot()
>
> raw_new_ref = mne.add_reference_channels(raw, ref_channels=['RightEar'])
> raw_new_ref.plot()
>
> ica = mne.preprocessing.ICA(n_components=15, random_state=97)
> ica.fit(raw)
> ica.plot_sources(raw)
>
> ica.plot_components()
>
>
>
> *Daniel Cabral.*
>
> PhD student
> Graduate Teaching Assistant
> Performance and Exercise Psychophysiology lab
> School of Kinesiology
> Auburn University
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