Command line

See also

Whole BIDS datasets shows the Python equivalents of these commands.

Installing meeg-utils provides the meu command.

Quality control

meu qc /data/bids --out qc/ -j 8            # every MEG/EEG recording of a BIDS dataset
meu qc sub-01_task-rest_eeg.vhdr --out qc/  # selected recordings
meu qc /data/bids --out qc/ --checks amplitude,bridging,impedance
meu qc /data/bids --out qc/ --fail-on fail  # exit status 2 if any check fails

For each recording meu qc writes <name>_qc.json (metrics and findings) and <name>_qc.html (report with figures; --no-report skips it); for the dataset, qc_summary.csv and qc_overview.png. Outlying recordings and errors are printed.

Preprocessing

meu run --preset had-meeg --datatype eeg --sources /data/bids \
    --out /data/bids/derivatives/meu -j 8
meu run pipeline.yaml --sources rec1_raw.fif rec2_raw.fif --out derivatives/
meu run pipeline.yaml --sources /data/bids --datatype meg --out derivatives/ --skip-existing

Preset options are passed with --option KEY=VALUE (values are read as YAML). For the MEG presets the system is detected from the first recording unless --option system=... is given:

meu run --preset meg-erp --sources /data/bids --datatype meg --out derivatives/
meu run --preset meg-erp --option stage=epochs --option "event_id=[face, house]" \
    --sources derivatives/sub-*/meg/*_desc-preproc_meg.fif --out derivatives/ --desc epochs
meu run --preset eeg-rest --option stage=epochs --option epoch_duration=2 ...

With --epochs the sources must be one BIDS root, and every session is taken through preprocessing, epoching and combination of its runs (meeg_utils.process_dataset(); existing outputs are skipped, so the command resumes). --epochs alone uses the epochs stage of --preset; --epochs epochs.yaml a configuration file. The log of every run and session is written to <out>/meu_batch.csv.

Step parameters are changed with --set STEP__PARAM=VALUE (as pipe.set_params), e.g. --set ica__threshold=0.9 or --set bridged__large_groups=bad.

pipeline.yaml is written by meeg_utils.Pipeline.to_yaml(). Each recording is processed separately (meeg_utils.process()); the exit status is 1 if any recording failed.

-v shows debug messages, -q only warnings and errors.

Presets

meu preset                                         # names, summaries, options
meu preset meg-erp --option system=ctf -o pipeline.yaml
meu run pipeline.yaml --sources /data/bids --datatype meg --out derivatives/

meu preset NAME writes the preset as a pipeline configuration (to the screen, or to -o FILE) so it can be edited before meu run.

Reports of saved results

meu report derivatives/sub-01/meg/sub-01_task-faces_run-01_desc-preproc_meg.fif
meu report derivatives/ --desc preproc

For one derivative, meu report writes an HTML report next to it: the pipeline and its parameters, every step’s QC metrics and warnings, the provenance and views of the data (the fitted steps are not saved, so their own figures are only in reports built right after processing, see meeg_utils.report.build()). For a folder, it collects the QC metrics of every derivative into derivatives_summary.csv and derivatives_summary.html, flagging runs whose value of a metric is an outlier (modified z > 3.5), e.g. a run with many more bad channels or rejected epochs than the others.