[Mne_analysis] concatenation brainvision raws issue

[Eric Larson]

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Sounds like a bug. Can you open an issue on the MNE-Python Issues page on
GitHub so we don't forget to fix it? It would also help if you could write
a minimal example using one of the `mne-testing-data` BV files
<https://github.com/mne-tools/mne-testing-data/tree/master/Brainvision>.

Eric


On Sat, Sep 8, 2018 at 2:41 PM Marianne DUYCK <marianne.duyck at gmail.com>
wrote:

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>
> Dear mne_analysers,
>
> I’m new to mne and ran into a problem I can’t seem to solve in a timely
> manner so I’m hoping you might have some suggestions.
>
> To analyse an eeg experiment (brainvision), I need to concatenate several
> experimental blocks (each participant ran several blocks of different
> lengths and different number of triggers).
>
> If I load each block separately
> *mne.io.read_raw_brainvision(block_nb_path)* and I *block_nb.get_data()*,
> I have no problem accessing the data and the ‘STI 014’ channel has the
> correct trigger data of the correct length.
> When I concatenate them using:
> *    blocks = [mne.io.read_raw_brainvision(block_path)
> for block_path in blocks_paths]*
> *    pooled_blocks = concatenate_raws(blocks)*
> Still no errors.
>
> However, when I try accessing the data with *pooled_blocks.get_data() *I
> have a concatenation error (details attached). After tracking it down
> carefully it seems that when the successive segments of data are read, the
> trigger channel data used is the one of the first block for all the blocks
> (therefore the error because some later blocks are shorter than the first
> one).
>
> So I am wondering if I have done something wrong and how I could find a
> solution to that issue. One idea I had to get around that problem was to
> add a concatenated event list as an argument to the concatenate_raws
>  function but I am not sure if it’s a viable solution and how to actually
> do it.
>
> Thanks a lot in advance for any input,
>
> Marianne
>
> PS: I’m using mne 0.16.2 (anaconda and python 3.6)
>
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