Analysis AWS

For Workshop members without access to computing resources - Preconfigured Amazon Web Services servers can be used

Accessing compute resources on AWS:

Speak with Jeff Stout to get the current IP address and PEM key

 chmod 400 AWS.pem

${PATH} is the path to the PEM key provided to you

 ssh -X -i AWS.pem user1@ec2-3-230-155-59.compute-1.amazonaws.com

Windows Laptops do not have X11 installed natively. Download an Xterm software for visualization.
MobaXterm has been tested to work: https://mobaxterm.mobatek.net/download.html

Jupyter Notebook Over a Remote Connection

1) Run one terminal to start the notebook and forward the outputs to local web browser:

 ssh -i AWS.pem -L 8887:localhost:8887  ubuntu@IP_ADDRESS
 conda activate workshop  
 jupyter notebook --no-browser --port=8887

2) Copy the output of the jupyter notebook command (see example below) and enter into your laptop web browser (Firefox, Chrome, etc.). Do not click on the link - it will try to launch on the AWS computer

3) Use the jupyter notebook to analyze MEG data with python tools

Installed software

Human Neocortical Neurosolver
HNN website: https://hnn.brown.edu/

 conda deactivate
 hnn

MNE python, Eelbrain, PyCTF
MNE website: https://mne.tools/stable/index.html
Eelbrain website: https://eelbrain.readthedocs.io/en/stable/
PyCTF website: https://megcore.nih.gov/index.php/MEG_Software_and_Analysis#MEG_Core_pyctf_tools_ported_to_Python_3

 conda activate workshop  # This conda environment has the MNE, Eelbrain, and PyCtf toolboxes installed
 ipython
 import eelbrain, mne, pyctf

CTF software

 singularity shell /opt/ctf/ctf.img
 $ctf_command

 singularity exec /opt/ctf/ctf.img $ctf_command

SAM version 5

 sam_cov ...
 sam_3d ...

Afni

 afni -dset $MRI_file