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>
MobaXterm has been tested to work: https://mobaxterm.mobatek.net/download.html


== Jupyter Notebook Over a Remote Connection ==
== Jupyter Notebook Over a Remote Connection ==
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jupyter notebook --no-browser --port=8887
jupyter notebook --no-browser --port=8887


2) Copy the output of the notebook (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
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


[[file:JupyterAws2.png]]
[[file:JupyterAws2.png]]


3) Use the jupyter notebook to analyze MEG data with python tools
[[File:TestJupyter.png]]
[[File:TestJupyter.png]]


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== Installed software ==
== Installed software ==
Human Neocortical Neurosolver
'''Human Neocortical Neurosolver ''' <br>
HNN website: https://hnn.brown.edu/
conda deactivate
hnn
hnn
#hnn is installed in the system level python >> may need to conda deactivate first


MNE python, Eelbrain, PyCTF
'''MNE python, Eelbrain, PyCTF''' <br>
MNE website: https://mne.tools/stable/index.html <br>
⚫
conda activate workshop (This environment has MNE, Eelbrain, and PyCtf installed)
Eelbrain website: https://eelbrain.readthedocs.io/en/stable/ <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
ipython
import eelbrain, mne, pyctf


CTF software
'''CTF software'''
singularity shell /opt/ctf/ctf.img
singularity shell /opt/ctf/ctf.img
$ctf_command
$ctf_command
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singularity exec /opt/ctf/ctf.img $ctf_command
singularity exec /opt/ctf/ctf.img $ctf_command


SAM version 5
'''SAM version 5'''
sam_cov ...
sam_cov ...
sam_3d ...
sam_3d ...


Afni
'''Afni'''
afni -dset $MRI_file
afni -dset $MRI_file




# Server Config
## google > fedora aws > select the AMI number for N.Virginia
## In AWS > launch instance > search for AMI number > (Under community) > Launch
### https://alt.fedoraproject.org/cloud/
#Determine an image (search for fedora in community)
#Create a keypair and download the key
##The download will be in the form of a .pem file
## We will need to distribute this key to the users
#Launch the instance
#Log into the instance using ssh



# Freesurfer
# MNE python
# pyctf
Done # SAM v5
# Afni ###INSTALL ME neurodebian
# singularity ? >> CTF (need to use workstation version of fedora) << may need to compile for ubuntu or use 2.6
# Eelbrain (conda forge)
# Jupyter
Done# Forward sim HNN software
# FSL ###Install outside of neurodebian
# Brainstorm (compiled)
⚫
<br>
'''Matlab Based'''
# Brainstorm
# Fieldtrip

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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