Analysis AWS: Difference between revisions

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== Accessing compute resources on AWS: ==
== Accessing compute resources on AWS: ==
Speak with Jeff Stout to get the current IP address and PEM key <br>
Speak with Jeff Stout to get the current IP address and PEM key <br>
<br>
chmod 400 AWS.pem
${PATH} is the path to the PEM key provided to you
${PATH} is the path to the PEM key provided to you
ssh -X -i ${PATH}/AWS.pem ubuntu@IP_ADDRESS_PROVIDED
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. <br>
'''Windows Laptops''' do not have X11 installed natively. Download an Xterm software for visualization. <br>
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PyCTF website: https://megcore.nih.gov/index.php/MEG_Software_and_Analysis#MEG_Core_pyctf_tools_ported_to_Python_3 <br>
PyCTF website: https://megcore.nih.gov/index.php/MEG_Software_and_Analysis#MEG_Core_pyctf_tools_ported_to_Python_3 <br>
conda activate workshop # This conda environment has the MNE, Eelbrain, and PyCtf toolboxes installed
conda activate workshop # This conda environment has the MNE, Eelbrain, and PyCtf toolboxes installed
ipython
import eelbrain, mne, pyctf


'''CTF software'''
'''CTF software'''
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'''Afni'''
'''Afni'''
afni -dset $MRI_file
afni -dset $MRI_file

==Done==
SAM v5
singularity ? >> CTF
Afni
Jupyter
HNN


==TODO==
Freesurfer
Reinstall MNE python
Pyctf
FSL
Brainstorm
Fieldtrip
Spyder

Latest revision as of 11:15, 7 November 2019

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
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