Analysis AWS: Difference between revisions
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To access the system: |
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ssh -X -i ~/Downloads/AWS.pem ubuntu@IP_ADDRESS_PROVIDED |
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== Accessing compute resources on AWS: == |
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Speak with Jeff Stout to get the current IP address and PEM key <br> |
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#hnn is installed in the system level python >> may need to conda deactivate first |
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chmod 400 AWS.pem |
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${PATH} is the path to the PEM key provided to you |
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ssh -X -i AWS.pem user1@ec2-3-230-155-59.compute-1.amazonaws.com |
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'''Windows Laptops''' do not have X11 installed natively. Download an Xterm software for visualization. <br> |
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MobaXterm has been tested to work: https://mobaxterm.mobatek.net/download.html |
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== Jupyter Notebook Over a Remote Connection == |
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1) Run one terminal to start the notebook and forward the outputs to local web browser: |
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ssh -i AWS.pem -L 8887:localhost:8887 ubuntu@IP_ADDRESS |
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conda activate workshop |
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--OR-- |
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jupyter notebook --no-browser --port=8887 |
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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 |
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Afni |
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[[file:JupyterAws2.png]] |
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3) Use the jupyter notebook to analyze MEG data with python tools |
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[[File:TestJupyter.png]] |
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<br> |
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== Installed software == |
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# Server Config |
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## google > fedora aws > select the AMI number for N.Virginia |
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HNN website: https://hnn.brown.edu/ |
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## In AWS > launch instance > search for AMI number > (Under community) > Launch |
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conda deactivate |
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### https://alt.fedoraproject.org/cloud/ |
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#Determine an image (search for fedora in community) |
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#Create a keypair and download the key |
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##The download will be in the form of a .pem file |
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## We will need to distribute this key to the users |
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#Launch the instance |
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#Log into the instance using ssh |
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MNE website: https://mne.tools/stable/index.html <br> |
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Eelbrain website: https://eelbrain.readthedocs.io/en/stable/ <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> |
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ipython |
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import eelbrain, mne, pyctf |
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Conda installed |
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Conda deactivate >> hnn |
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Conda activate nih >> mne or eelbrain..... |
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'''SAM version 5''' |
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# Freesurfer |
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sam_cov ... |
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# MNE python |
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sam_3d ... |
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# pyctf |
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Done # SAM v5 |
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'''Afni''' |
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# Afni ###INSTALL ME neurodebian |
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# singularity ? >> CTF (need to use workstation version of fedora) << may need to compile for ubuntu or use 2.6 |
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# Eelbrain (conda forge) |
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# Jupyter |
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Done# Forward sim HNN software |
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# FSL ###Install outside of neurodebian |
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# Brainstorm (compiled) |
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'''Matlab Based''' |
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# Brainstorm |
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# 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