[Mne_analysis] ctf file issues
Denis-Alexander Engemann
denis.engemann at gmail.com
Wed Jul 30 14:37:03 EDT 2014
Hi Will,
I meanwhile opened an issue on github. People interested in the solution
can follow the development there.
Best,
Denis
On Wed, Jul 30, 2014 at 8:17 PM, Denis-Alexander Engemann <
denis.engemann at gmail.com> wrote:
> 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
>> >>
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