MNE Python Tutorial 2021: Difference between revisions
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=Steps to prepare prior to tutorial= |
=Steps to prepare prior to tutorial= |
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Prepare python environment <br> |
Prepare python environment - For 3D rendering and interactive plots, this should be installed on your local computer <br> |
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!!IF YOU DO NOT HAVE MINICONDA/ANACONDA INSTALLED - have IT install miniconda under your user account!! |
!!IF YOU DO NOT HAVE MINICONDA/ANACONDA INSTALLED - have IT install miniconda under your user account!! |
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!!If you already have an mne environment, you can use another name for the environment and adjust accordingly!! |
!!If you already have an mne environment, you can use another name for the environment and adjust accordingly!! |
Revision as of 11:40, 24 September 2021
Steps to prepare prior to tutorial
Prepare python environment - For 3D rendering and interactive plots, this should be installed on your local computer
!!IF YOU DO NOT HAVE MINICONDA/ANACONDA INSTALLED - have IT install miniconda under your user account!! !!If you already have an mne environment, you can use another name for the environment and adjust accordingly!! conda activate base conda install -n base mamba -c conda-forge -y mamba create -n mne conda-forge::mne main::pip main:jupyter -y
conda activate mne
Download the sample data
NIMH Users: Download here
scp <USERNAME>@helix.nih.gov:/data/NIMH_scratch/mne_tutorial/mne_tutorial.tar.gz <NEW PATH> cd <NEW PATH> tar -xvf mne_tutorial.tar.gz
NON-NIH MEG Users: Download from MEG Data server
The data is located on the MEG data server and is accessible by all users with accounts An email will be sent with the path to the data
Start Jupyter Notebook
cd <NEW PATH>/nimh_tutorial_data jupyter notebook mne_tutorial_10_01_21.ipynb
Prep Non-tutorial Data
Run Freesurfer on Dataset: recon-all -all -i <MRI Used w/ MEG> -s <SUBJECT> Run mne.bem.make_watershed_bem() on your subject