Note
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Convert MNE sample data to BIDS format¶
This example demonstrates how to convert your existing files into a BIDS-compatible folder.
# Authors: Mainak Jas <mainak.jas@telecom-paristech.fr>
# Alexandre Gramfort <alexandre.gramfort@telecom-paristech.fr>
# Teon Brooks <teon.brooks@gmail.com>
# Stefan Appelhoff <stefan.appelhoff@mailbox.org>
#
# License: BSD (3-clause)
Let us import mne_bids
import os.path as op
from datetime import datetime
import mne
from mne.datasets import sample
from mne_bids import write_raw_bids, read_raw_bids, make_bids_basename
from mne_bids.utils import print_dir_tree
And define the paths and event_id dictionary.
data_path = sample.data_path()
event_id = {'Auditory/Left': 1, 'Auditory/Right': 2, 'Visual/Left': 3,
'Visual/Right': 4, 'Smiley': 5, 'Button': 32}
raw_fname = op.join(data_path, 'MEG', 'sample', 'sample_audvis_raw.fif')
events_data = op.join(data_path, 'MEG', 'sample', 'sample_audvis_raw-eve.fif')
output_path = op.join(data_path, '..', 'MNE-sample-data-bids')
Specify the raw_file and events_data and run the BIDS conversion.
raw = mne.io.read_raw_fif(raw_fname)
bids_basename = make_bids_basename(subject='01', session='01',
task='audiovisual', run='01')
write_raw_bids(raw, bids_basename, output_path, events_data=events_data,
event_id=event_id, overwrite=True)
Out:
Opening raw data file /home/stefanappelhoff/mne_data/MNE-sample-data/MEG/sample/sample_audvis_raw.fif...
Read a total of 3 projection items:
PCA-v1 (1 x 102) idle
PCA-v2 (1 x 102) idle
PCA-v3 (1 x 102) idle
Range : 25800 ... 192599 = 42.956 ... 320.670 secs
Ready.
Current compensation grade : 0
Opening raw data file /home/stefanappelhoff/mne_data/MNE-sample-data/MEG/sample/sample_audvis_raw.fif...
Read a total of 3 projection items:
PCA-v1 (1 x 102) idle
PCA-v2 (1 x 102) idle
PCA-v3 (1 x 102) idle
Range : 25800 ... 192599 = 42.956 ... 320.670 secs
Ready.
Current compensation grade : 0
Creating folder: /home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/meg
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/participants.tsv'...
participant_id age sex
sub-01 n/a n/a
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/participants.json'...
{
"participant_id": {
"Description": "Unique participant identifier"
},
"age": {
"Description": "Age of the participant at time of testing",
"Units": "years"
},
"sex": {
"Description": "Biological sex of the participant",
"Levels": {
"F": "female",
"M": "male"
}
}
}
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/sub-01_ses-01_scans.tsv'...
filename acq_time
meg/sub-01_ses-01_task-audiovisual_run-01_meg.fif 2002-12-03T20:01:10
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_coordsystem.json'...
{
"MEGCoordinateSystem": "Elekta",
"MEGCoordinateUnits": "m",
"HeadCoilCoordinates": {
"NAS": [
3.725290298461914e-09,
0.10260561108589172,
4.190951585769653e-09
],
"LPA": [
-0.07137660682201385,
0.0,
5.122274160385132e-09
],
"RPA": [
0.07526767998933792,
0.0,
5.587935447692871e-09
],
"coil1": [
0.032922741025686264,
0.09897983074188232,
0.07984329760074615
],
"coil2": [
-0.06998106092214584,
0.06771647930145264,
0.06888450682163239
],
"coil3": [
-0.07260829955339432,
-0.02086828649044037,
0.0971473976969719
],
"coil4": [
0.04996863007545471,
-0.007233052980154753,
0.1228904277086258
]
},
"HeadCoilCoordinateSystem": "RAS",
"HeadCoilCoordinateUnits": "m"
}
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_task-audiovisual_run-01_events.tsv'...
onset duration trial_type value sample
3.6246181587150867 0.0 Auditory/Right 2 2177
4.237323479067476 0.0 Visual/Left 3 2545
4.946596485779753 0.0 Auditory/Left 1 2971
5.692498614904401 0.0 Visual/Right 4 3419
6.41342634238425 0.0 Auditory/Right 2 3852
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/dataset_description.json'...
{
"Name": " ",
"BIDSVersion": "1.2.0"
}
/home/stefanappelhoff/Desktop/bids/mne-bids/mne_bids/write.py:407: UserWarning: No line frequency found, defaulting to 50 Hz
warn('No line frequency found, defaulting to 50 Hz')
Reading 0 ... 166799 = 0.000 ... 277.714 secs...
/home/stefanappelhoff/miniconda3/envs/mne_bids3/lib/python3.6/site-packages/mne/utils/docs.py:830: DeprecationWarning: Function read_montage is deprecated; ``read_montage`` is deprecated and will be removed in v0.20. Please use ``read_dig_fif``, ``read_dig_egi``, ``read_custom_montage``, or ``read_dig_captrack`` to read a digitization based on your needs instead; or ``make_standard_montage`` to create ``DigMontage`` based on template; or ``make_dig_montage`` to create a ``DigMontage`` out of np.arrays
warnings.warn(msg, category=DeprecationWarning)
/home/stefanappelhoff/miniconda3/envs/mne_bids3/lib/python3.6/site-packages/mne/utils/docs.py:813: DeprecationWarning: Class Montage is deprecated; Montage class is deprecated and will be removed in v0.20. Please use DigMontage instead.
warnings.warn(msg, category=DeprecationWarning)
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_task-audiovisual_run-01_meg.json'...
{
"TaskName": "audiovisual",
"Manufacturer": "Elekta",
"PowerLineFrequency": 50,
"SamplingFrequency": 600.614990234375,
"SoftwareFilters": "n/a",
"RecordingDuration": 277.7136813300495,
"RecordingType": "continuous",
"DewarPosition": "n/a",
"DigitizedLandmarks": false,
"DigitizedHeadPoints": false,
"MEGChannelCount": 306,
"MEGREFChannelCount": 0,
"EEGChannelCount": 60,
"EOGChannelCount": 1,
"ECGChannelCount": 0,
"EMGChannelCount": 0,
"MiscChannelCount": 0,
"TriggerChannelCount": 9
}
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_task-audiovisual_run-01_channels.tsv'...
name type units low_cutoff high_cutoff description sampling_frequency status
MEG 0113 MEGGRADPLANAR T/m 0.10000000149011612 172.17630004882812 Planar Gradiometer 600.614990234375 good
MEG 0112 MEGGRADPLANAR T/m 0.10000000149011612 172.17630004882812 Planar Gradiometer 600.614990234375 good
MEG 0111 MEGMAG T 0.10000000149011612 172.17630004882812 Magnetometer 600.614990234375 good
MEG 0122 MEGGRADPLANAR T/m 0.10000000149011612 172.17630004882812 Planar Gradiometer 600.614990234375 good
MEG 0123 MEGGRADPLANAR T/m 0.10000000149011612 172.17630004882812 Planar Gradiometer 600.614990234375 good
Copying data files to /home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_task-audiovisual_run-01_meg.fif
Overwriting existing file.
Writing /home/stefanappelhoff/mne_data/MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_task-audiovisual_run-01_meg.fif
Closing /home/stefanappelhoff/mne_data/MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_task-audiovisual_run-01_meg.fif [done]
'/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids'
Specify some empty room data and run BIDS conversion on it.
er_raw_fname = op.join(data_path, 'MEG', 'sample', 'ernoise_raw.fif')
er_raw = mne.io.read_raw_fif(er_raw_fname)
# For empty room data we need to specify that the subject ID is
# 'emptyroom', and that the task is 'noise'.
# We also need to specify the recording date in the format YYYYMMDD for the
# session id.
er_date = datetime.fromtimestamp(
er_raw.info['meas_date'][0]).strftime('%Y%m%d')
er_bids_basename = 'sub-emptyroom_ses-{0}_task-noise'.format(er_date)
write_raw_bids(er_raw, er_bids_basename, output_path, overwrite=True)
Out:
Opening raw data file /home/stefanappelhoff/mne_data/MNE-sample-data/MEG/sample/ernoise_raw.fif...
Isotrak not found
Read a total of 3 projection items:
PCA-v1 (1 x 102) idle
PCA-v2 (1 x 102) idle
PCA-v3 (1 x 102) idle
Range : 19800 ... 85867 = 32.966 ... 142.965 secs
Ready.
Current compensation grade : 0
Opening raw data file /home/stefanappelhoff/mne_data/MNE-sample-data/MEG/sample/ernoise_raw.fif...
Isotrak not found
Read a total of 3 projection items:
PCA-v1 (1 x 102) idle
PCA-v2 (1 x 102) idle
PCA-v3 (1 x 102) idle
Range : 19800 ... 85867 = 32.966 ... 142.965 secs
Ready.
Current compensation grade : 0
Creating folder: /home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-emptyroom/ses-20021206/meg
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/participants.tsv'...
participant_id age sex
sub-01 n/a n/a
sub-emptyroom n/a n/a
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/participants.json'...
{
"participant_id": {
"Description": "Unique participant identifier"
},
"age": {
"Description": "Age of the participant at time of testing",
"Units": "years"
},
"sex": {
"Description": "Biological sex of the participant",
"Levels": {
"F": "female",
"M": "male"
}
}
}
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-emptyroom/ses-20021206/sub-emptyroom_ses-20021206_scans.tsv'...
filename acq_time
meg/sub-emptyroom_ses-20021206_task-noise_meg.fif 2002-12-06T16:16:18
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/dataset_description.json'...
{
"Name": " ",
"BIDSVersion": "1.2.0"
}
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-emptyroom/ses-20021206/meg/sub-emptyroom_ses-20021206_task-noise_meg.json'...
{
"TaskName": "noise",
"Manufacturer": "Elekta",
"PowerLineFrequency": 50,
"SamplingFrequency": 600.614990234375,
"SoftwareFilters": "n/a",
"RecordingDuration": 109.9989195644601,
"RecordingType": "continuous",
"DewarPosition": "n/a",
"DigitizedLandmarks": false,
"DigitizedHeadPoints": false,
"MEGChannelCount": 306,
"MEGREFChannelCount": 0,
"EEGChannelCount": 0,
"EOGChannelCount": 0,
"ECGChannelCount": 0,
"EMGChannelCount": 0,
"MiscChannelCount": 0,
"TriggerChannelCount": 9
}
Writing '/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-emptyroom/ses-20021206/meg/sub-emptyroom_ses-20021206_task-noise_channels.tsv'...
name type units low_cutoff high_cutoff description sampling_frequency status
MEG 0113 MEGGRADPLANAR T/m 0.10000000149011612 172.17630004882812 Planar Gradiometer 600.614990234375 good
MEG 0112 MEGGRADPLANAR T/m 0.10000000149011612 172.17630004882812 Planar Gradiometer 600.614990234375 good
MEG 0111 MEGMAG T 0.10000000149011612 172.17630004882812 Magnetometer 600.614990234375 good
MEG 0122 MEGGRADPLANAR T/m 0.10000000149011612 172.17630004882812 Planar Gradiometer 600.614990234375 good
MEG 0123 MEGGRADPLANAR T/m 0.10000000149011612 172.17630004882812 Planar Gradiometer 600.614990234375 good
Copying data files to /home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-emptyroom/ses-20021206/meg/sub-emptyroom_ses-20021206_task-noise_meg.fif
Writing /home/stefanappelhoff/mne_data/MNE-sample-data-bids/sub-emptyroom/ses-20021206/meg/sub-emptyroom_ses-20021206_task-noise_meg.fif
Closing /home/stefanappelhoff/mne_data/MNE-sample-data-bids/sub-emptyroom/ses-20021206/meg/sub-emptyroom_ses-20021206_task-noise_meg.fif [done]
'/home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids'
Now let’s see the structure of the BIDS folder we created.
print_dir_tree(output_path)
Out:
|MNE-sample-data-bids/
|--- participants.tsv
|--- dataset_description.json
|--- participants.json
|--- sub-emptyroom/
|------ ses-20021206/
|--------- sub-emptyroom_ses-20021206_scans.tsv
|--------- meg/
|------------ sub-emptyroom_ses-20021206_task-noise_meg.json
|------------ sub-emptyroom_ses-20021206_task-noise_channels.tsv
|------------ sub-emptyroom_ses-20021206_task-noise_meg.fif
|--- sub-01/
|------ ses-01/
|--------- sub-01_ses-01_scans.tsv
|--------- meg/
|------------ sub-01_ses-01_coordsystem.json
|------------ sub-01_ses-01_task-audiovisual_run-01_meg.json
|------------ sub-01_ses-01_task-audiovisual_run-01_channels.tsv
|------------ sub-01_ses-01_task-audiovisual_run-01_meg.fif
|------------ sub-01_ses-01_task-audiovisual_run-01_events.tsv
|--------- anat/
|------------ sub-01_ses-01_T1w.nii.gz
|------------ sub-01_ses-01_T1w.json
Finally, we can read the BIDS data we created as well.
bids_fname = bids_basename + '_meg.fif'
raw = read_raw_bids(bids_fname, output_path)
Out:
Opening raw data file /home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_task-audiovisual_run-01_meg.fif...
Read a total of 3 projection items:
PCA-v1 (1 x 102) idle
PCA-v2 (1 x 102) idle
PCA-v3 (1 x 102) idle
Range : 25800 ... 192599 = 42.956 ... 320.670 secs
Ready.
Current compensation grade : 0
Reading events from /home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_task-audiovisual_run-01_events.tsv.
Reading channel info from /home/stefanappelhoff/mne_data/MNE-sample-data/../MNE-sample-data-bids/sub-01/ses-01/meg/sub-01_ses-01_task-audiovisual_run-01_channels.tsv.
/home/stefanappelhoff/Desktop/bids/mne-bids/mne_bids/read.py:165: RuntimeWarning: The unit for channel(s) STI 001, STI 002, STI 003, STI 004, STI 005, STI 006, STI 014, STI 015, STI 016 has changed from V to NA.
raw.set_channel_types(channel_type_dict)
The data is already in a convenient form to create epochs and evokeds.
events, event_id = mne.events_from_annotations(raw)
epochs = mne.Epochs(raw, events, event_id)
epochs['Auditory'].average().plot()
Out:
Used Annotations descriptions: ['Auditory/Left', 'Auditory/Right', 'Button', 'Smiley', 'Visual/Left', 'Visual/Right']
320 matching events found
Applying baseline correction (mode: mean)
Not setting metadata
Created an SSP operator (subspace dimension = 3)
3 projection items activated
<Figure size 640x500 with 3 Axes>
Total running time of the script: ( 0 minutes 4.256 seconds)
