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)
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)
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.
Thanks for answering. There indeed is a bug somewhere - more particularly there is a bug if the data was not preloaded.
So for now my problem is solved, because if I preload all the files using concatenate_raws(raws_list, preload=True) then I have access to all the correct data.
Ill create a github account and post a bug issue once my deadline is over !
