[Mne_analysis] ctf file issues
Denis-Alexander Engemann
denis.engemann at gmail.com
Wed Jul 30 14:17:48 EDT 2014
Hi Will,
sorry for the confusion.
This line would work (crop makes a copy by default and `None` is only valid
for Epochs and Evokeds):
raw.crop(0, 0.1, copy=False)
raw.save('my-ctf-raw.fif')
# should fit into an email as attachment
Since I don't know the CTF system very well the channels don't help as
such. It's more relevant what's in the raw.info dict, actually the type
information used inside the plotting routine is not inferred from the
channels names.
Denis
On Wed, Jul 30, 2014 at 8:09 PM, <wgraves at psychology.rutgers.edu> wrote:
> Hi Denis,
>
> Thanks for the suggestions, and for being willing to take a look at a
> snippet of data. Unfortunatley, when I run the first command you have as
> written, this happens:
>
> ---------------------------------------------------------------------------
> ValueError Traceback (most recent call last)
> <ipython-input-55-ddfaa452efda> in <module>()
> ----> 1 raw.crop(None, 0.1)
>
> /home/wgraves/data/ld_meg/scripts/src/mne/mne/fiff/base.pyc in crop(self,
> tmin, tmax, copy)
> 606 raise ValueError('tmin must be less than tmax')
> 607 if tmin < 0.0:
> --> 608 raise ValueError('tmin must be >= 0')
> 609 elif tmax > max_time:
> 610 raise ValueError('tmax must be less than or equal to
> the max raw '
>
> ValueError: tmin must be >= 0
>
>
> So I tried this instead, which seems to work:
> In [56]: raw.crop(1,1.1)
> Out[56]: <Raw | n_channels x n_times : 303 x 61>
>
> However, when I run:
> raw.save('test-ctf_raw.fif')
>
> it proceeds to save all 370 seconds of the file.
>
> Anyway, I guess you must be right about the channel names, because when I
> run:
> In [54]: raw.ch_names
>
> I get this:
> Out[54]:
> ['UPPT001',
> 'SCLK01-177',
> 'BG1-3805',
> 'BG2-3805',
> 'BG3-3805',
> 'BP1-3805',
> 'BP2-3805',
> 'BP3-3805',
> 'BR1-3805',
> 'BR2-3805',
> 'BR3-3805',
> 'G11-3805',
> 'G12-3805',
> 'G13-3805',
> 'G22-3805',
> 'G23-3805',
> 'P11-3805',
> 'P12-3805',
> 'P13-3805',
> 'P22-3805',
> 'P23-3805',
> 'Q11-3805',
> 'Q12-3805',
> 'Q13-3805',
> 'Q22-3805',
> 'Q23-3805',
> 'R11-3805',
> 'R12-3805',
> 'R13-3805',
> 'R22-3805',
> 'R23-3805',
> 'MLC11-3805',
> 'MLC12-3805',
> 'MLC13-3805',
> 'MLC14-3805',
> 'MLC15-3805',
> 'MLC16-3805',
> 'MLC17-3805',
> 'MLC21-3805',
> 'MLC22-3805',
> 'MLC23-3805',
> 'MLC24-3805',
> 'MLC25-3805',
> 'MLC31-3805',
> 'MLC32-3805',
> 'MLC41-3805',
> 'MLC42-3805',
> 'MLC51-3805',
> 'MLC52-3805',
> 'MLC53-3805',
> 'MLC54-3805',
> 'MLC55-3805',
> 'MLC61-3805',
> 'MLC62-3805',
> 'MLC63-3805',
> 'MLF11-3805',
> 'MLF12-3805',
> 'MLF13-3805',
> 'MLF14-3805',
> 'MLF21-3805',
> 'MLF22-3805',
> 'MLF23-3805',
> 'MLF24-3805',
> 'MLF25-3805',
> 'MLF31-3805',
> 'MLF32-3805',
> 'MLF33-3805',
> 'MLF34-3805',
> 'MLF35-3805',
> 'MLF41-3805',
> 'MLF42-3805',
> 'MLF43-3805',
> 'MLF44-3805',
> 'MLF45-3805',
>
> and so on... with nothing that looks like those nice, sensible channel
> names you listed.
>
> I suppose I somehow need to pair the CTF channle selections file with this
> dataset, but outside of the interactive mne_browse_raw interace, I don't
> know how to do that.
>
> Thanks,
> Will
>
>
> > Hi will,
> >
> > could you share a small snippet (e.g. 100 ms) of your data like that:
> >
> > raw.crop(None, 0.1)
> > raw.save('my-ctf-raw.fif')
> >
> > I suspect there is some channel type in your data whic is not classified
> > as
> > one of these:
> >
> > ['eeg', 'eog', 'ecg', 'emg', 'ref_meg', 'stim', 'resp', 'misc', 'chpi',
> > 'syst', 'ias', 'exci']
> >
> > Maybe your reference channels are not marked as such.
> > You could try to identify them by name and remove them just for the
> > purpose
> > of plotting using
> >
> > `raw.drop_channels(channel_names)`
> >
> > Best,
> > Denis
> >
> > On Wed, Jul 30, 2014 at 6:00 PM, <wgraves at psychology.rutgers.edu> wrote:
> >
> >> Hello MNE Experts,
> >>
> >> In trying to deal with CTF files for the first, time I'm running into
> >> some
> >> issues that I don't understand and hope someone can easily help with. I
> >> used the mne_ctf2fiff command to convert to fiff, but I can't visualize
> >> the resulting file in mne_browse_raw (it loads without error but just
> >> looks blank). Similarly, all the steps for loading a segment of the file
> >> as raw data in mne_python work without error, until I do "raw.plot()",
> >> when I get this error:
> >>
> >> In [20]: raw.plot()
> >>
> ---------------------------------------------------------------------------
> >> RuntimeError Traceback (most recent call
> >> last)
> >> <ipython-input-20-d4ffb847f525> in <module>()
> >> ----> 1 raw.plot()
> >>
> >> /home/wgraves/data/ld_meg/scripts/src/mne/mne/fiff/base.pyc in plot(raw,
> >> events, duration, start, n_channels, bgcolor, color, bad_color,
> >> event_color, scalings, remove_dc, order, show_options, title, show,
> >> block)
> >> 846 return plot_raw(raw, events, duration, start,
> >> n_channels,
> >> bgcolor,
> >> 847 color, bad_color, event_color, scalings,
> >> remove_dc,
> >> --> 848 order, show_options, title, show, block)
> >> 849
> >> 850 @verbose
> >>
> >> /home/wgraves/data/ld_meg/scripts/src/mne/mne/viz.pyc in plot_raw(raw,
> >> events, duration, start, n_channels, bgcolor, color, bad_color,
> >> event_color, scalings, remove_dc, order, show_options, title, show,
> >> block)
> >> 2778 inds = np.concatenate(inds).astype(int)
> >> 2779 if not len(inds) == len(info['ch_names']):
> >> -> 2780 raise RuntimeError('Some channels not classified, please
> >> report '
> >> 2781 'this problem')
> >> 2782
> >>
> >> RuntimeError: Some channels not classified, please report this problem
> >>
> >> Unfortunately, the data were collected in short epochs keyed to the
> >> events
> >> rather than continuously. My original plan was to use
> >> mne.fiff.concatenate_raws to concatenate across epochs/events, but I
> >> couldn't figure out how to make that work either (perhaps because I
> >> don't
> >> know what the "raw" argument is supposed to look like, and I can't find
> >> an
> >> example).
> >>
> >> Anyway, I would gratly appreciate any help or insight anyone can share.
> >>
> >> Thanks,
> >> Will
> >>
> >> _______________________________________________
> >> Mne_analysis mailing list
> >> Mne_analysis at nmr.mgh.harvard.edu
> >> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> >>
> >>
> >> The information in this e-mail is intended only for the person to whom
> >> it
> >> is
> >> addressed. If you believe this e-mail was sent to you in error and the
> >> e-mail
> >> contains patient information, please contact the Partners Compliance
> >> HelpLine at
> >> http://www.partners.org/complianceline . If the e-mail was sent to you
> >> in
> >> error
> >> but does not contain patient information, please contact the sender and
> >> properly
> >> dispose of the e-mail.
> >>
> >>
> > _______________________________________________
> > Mne_analysis mailing list
> > Mne_analysis at nmr.mgh.harvard.edu
> > https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
> >
> >
> > The information in this e-mail is intended only for the person to whom it
> > is
> > addressed. If you believe this e-mail was sent to you in error and the
> > e-mail
> > contains patient information, please contact the Partners Compliance
> > HelpLine at
> > http://www.partners.org/complianceline . If the e-mail was sent to you
> in
> > error
> > but does not contain patient information, please contact the sender and
> > properly
> > dispose of the e-mail.
> >
>
>
> _______________________________________________
> Mne_analysis mailing list
> Mne_analysis at nmr.mgh.harvard.edu
> https://mail.nmr.mgh.harvard.edu/mailman/listinfo/mne_analysis
>
-------------- next part --------------
An HTML attachment was scrubbed...
URL: http://mail.nmr.mgh.harvard.edu/pipermail/mne_analysis/attachments/20140730/cd33b3cc/attachment.html
More information about the Mne_analysis
mailing list