This is a library to automatically reject bad trials and repair bad sensors in magneto-/electroencephalography (M/EEG) data.

References:

• Mainak Jas et.al.Autoreject: Automated artifact rejection for MEG and EEG data NeuroImage, 2017 159, 417-429. PubMed |  Journal

• autoreject Main Site:Main Site

• Module Name: autoreject (see the modules page for more information)

  autoreject is installed as a singularity container, which means it came with it's own python environment.

  It could be run as command line or through jupyter notebook.

• Environment variables set
  • $AUTOREJECT_TEST_DATA

Allocate an interactive session and run the program.
Sample session (user input in bold):

[user@biowulf]$ sinteractive --cpus-per-task=10 --mem=10G --gres=lscratch:200 --tunnel
salloc.exe: Pending job allocation 46116226
salloc.exe: job 46116226 queued and waiting for resources
salloc.exe: job 46116226 has been allocated resources
salloc.exe: Granted job allocation 46116226
salloc.exe: Waiting for resource configuration
salloc.exe: Nodes cn3144 are ready for job
Created 1 generic SSH tunnel(s) from this compute node to                  
biowulf for your use at port numbers defined                               
in the $PORTn ($PORT1, ...) environment variables.                         
                                                                           
                                                                           
Please create a SSH tunnel from your workstation to these ports on biowulf.
On Linux/MacOS, open a terminal and run:                                   
                                                                           
    ssh  -L 33327:localhost:33327 biowulf.nih.gov                          
                                                                           
For Windows instructions, see https://hpc.nih.gov/docs/tunneling          
[user@cn3144]$ module load autoreject
[user@cn3144]$ python -c "import autoreject"
[user@cn3144]$ cd /lscratch/$SLURM_JOB_ID
[user@cn3144]$ cp -r ${AUTOREJECT_TEST_DATA:-none}/mne_data .
[user@cn3144]$ jupyter notebook --ip localhost --port $PORT1 --no-browser 
[I 17:11:40.505 NotebookApp] Serving notebooks from local directory
[I 17:11:40.505 NotebookApp] Jupyter Notebook 6.4.10 is running at:
[I 17:11:40.505 NotebookApp] http://localhost:37859/?token=xxxxxxxx
[I 17:11:40.506 NotebookApp]  or http://127.0.0.1:37859/?token=xxxxxxx
[I 17:11:40.506 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 17:11:40.512 NotebookApp]

    To access the notebook, open this file in a browser:
        file:///home/apptest1/.local/share/jupyter/runtime/nbserver-29841-open.html
    Or copy and paste one of these URLs:
        http://localhost:37859/?token=xxxxxxx
     or http://127.0.0.1:37859/?token=xxxxxxx

Then you can open a browser from your computer to connect to the jupyter notebook:

[user@cn3144 ~]$ exit
salloc.exe: Relinquishing job allocation 46116226
[user@biowulf ~]$

Create a batch input file (e.g. autoreject.sh). For example:

#!/bin/bash
#SBATCH --cpus-per-task=10
#SBATCH --mem=10G
#SBATCH --time=2:00:00
#SBATCH --partition=norm

set -e
module load autoreject
# command 

Submit the job:

sbatch autoreject.sh

Create a swarmfile (e.g. job.swarm). For example:

cmd1
cmd2
cmd3

    

Submit this job using the swarm command.

swarm -f job.swarm [-g #] --module autoreject