Scinet Summer School 2020: Introduction to Brain Network Modeling
Developed by
- John Griffiths
( With essential contributions from: Julie Courtiol, Amanda Easson, Kelly Shen, Jerry Jeyachandra )
If you're using SciNet's JupyterHub System
-
Log into on the scinet jupyterhub website
-
First time only: add the course's conda env to your conda envs list:
Open up a terminal from the jupyterhub landing page
module load intelpython3
conda config --append envs_dirs /scinet/course/ss2020/8_brainnetwork/env
Return the the landing page and refresh the browser. You should see the ss2020_tvb
option now when clicking the new
menu on the top right
- Also first time only: clone the github repo for the course in a terminal
git clone https://github.com/JohnGriffiths/ScinetSS2020_BrainNetworkModelling
- Navigate to the
notebooks
folder in the downloaded github repo folder, and open up the course notebooks
If you're using Binder
Click on the Open In Binder
badge above, and wait patiently for the image and environment to be built and initiated.
If you're using Google Colab
Click on the Open In Colab
badge above, and wait patiently for the environment to be initiated.
Note - in google colab you need to pip install
non-standard libraries. Each of the notebooks has a commented out section that needs to be un-commented and run in order to make the libraries available on Colab.
For course attendees:
Login information
See here for the scinet course webpage
To access the jupyterhub:
- Click 'log in' in the top right. Enter your login details
- From the course website, click 'login information for cluster'
- Follow the instructions: go to the scinet jupyterhub site, and enter the uname/pwd displayed on the previous page
- Follow the jupyterhub instructions above
Homework assignment
The homework assignment for the course can be found in notebooks/homework_assignment.ipynb
This follows on from the intro_to_whole_brain_modelling.ipynb
notebook, which is the basis of the practical session.
Completed assignments should be uploaded to the designated folder on the course website.
These should take the form of jupyter notebooks that are extended from homework_assignment.ipynb
.