You can either run everything on your computer after following the environment setup below (recommended), or you can access the lecture Jupyter notebook simply by clicking on the "Launch Binder" badge (cf instructions below)).
To run the lecture Jupyter notebook online on Binder:
- Click on the "Launch binder" badge above (better to right click and then open in a new tab)
- Once the notebook is ready, display a terminal by:
- selecting on the top left
File
-->Open...
- selecting on the top right of the newly displayed page
New
-->Terminal
- selecting on the top left
- You can follow along the notebook, and in the terminal you could type bash commands indicated in the notebook
- Install Visual Studio Code (prefer deb or repository installation)
- Install Miniconda
- Please indicate any problem during installation on Slack (after your very first message, please immediately hover on it and click on the chat buble to
Reply in thread
for all your messages to be in a single thread)
- Open a terminal and type
echo $0
. If the output does not indicatebash
this means you need to set your default shell asbash
. You can do it by following the instructions here (see section "Using System Preferences" if you prefer using the graphical interface) - Install
homebrew
as indicated here - Update
bash
as described here - May be a good idea to restart ? Please let me know if you don't restart and have issues (so that i update these instructions)
- Install Visual Studio Code
- Install Miniconda
- Please indicate any problem during installation on Slack (after your very first message, please immediately hover on it and click on the chat buble to
Reply in thread
for all your messages to be in a single thread)
- Make sure you have installed the latest OS updates (Windows menu ->
Check for Updates
) - Install WSL2 as indicated here (you may also need info from here), then install the Ubuntu 20.04 app from the Microsoft store as indicated in the first link (it is recommended to also install the Windows Terminal app as suggested in that link)
- Install Visual Studio Code
- Start VS Code, and inside the program accept the suggestion of installing "VS Code Remote Pack" to use with WSL2 (for more information please see these instructions)
- Start a terminal with WSL 2
- (Preferred) If you installed the Windows Terminal App as indicated previously:
- Start this app (search for "Windows Terminal" in the Windows search bar at the bottom left of your screen, and then click on the app)
- By default you will see a Windows PowerShell, that IS NOT what we want. To open a Linux shell with the Ubuntu 20.04 OS you installed previously, click on the downward arrow head (⌄) next to the tab Title, and choose "Ubuntu 20.04": that IS what we want (see here to change the default profile to Ubuntu so that you don't always have to do this every time you start a terminal)
- (Alternative) Start the Ubuntu 20.04 app by searching for "Ubuntu" in the Windows search bar at the bottom left of your screen and then clicking on the app
- (Preferred) If you installed the Windows Terminal App as indicated previously:
- Install Miniconda making sure to follow the Linux instructions (so make sure sure to use the link i indicated and not using the instructions for Windows: your WSL 2 terminal is using a Linux kernel and you have to install Miniconda there !). For clarity these instructions are repeated below but may become outdated (the link just provided takes precedence over the instructions below):
- Go to the terminal you opened in the previous step
- Via the terminal navigate to the place where you downloaded the miniconda file. Keep in mind that any path to directory and files on a Windows C drive are accessible via WSL 2 at the path
/mnt/c
, so for example:- If your username on Windows is
smartuser
and you downloaded the file to your WindowsDownloads
directory, on the WSL 2 terminal you can navigate to that directory with:cd /mnt/c/Users/smartuser/Downloads
- If for some reason your data is on a Windows drive with letter F and you downloaded the miniconda install script on your Dekstop, you will need to type in your WSL 2 terminal:
cd /mnt/f/Users/smartuser/Desktop
- Etc.
- If your username on Windows is
- Make sure the miniconda install script is indeed in the directory you just navigate (at this time the script is called
Miniconda3-latest-Linux-x86_64.sh
but it can change later) :ls Miniconda3-latest-Linux-x86_64.sh
- If the previous command gives you an error, it means you are not in the right directory or you did not provided the correct filename to
ls
- Now follow the Linux instructions on the miniconda link above. For clarity these instructions which are few at this time are repeated here:
bash Miniconda3-latest-Linux-x86_64.sh
- Accept all the default values and the license agreement
- Please indicate any problem during installation on Slack (after your very first message, please immediately hover on it and click on the chat buble to
Reply in thread
for all your messages to be in a single thread)
- Now on the command line in a terminal (WSL 2 for Windows):
- Update your local environment:
source ~/.bashrc
- Configure the conda-forge channel to be BEFORE any defaults in
~/.condarc
:
conda config --prepend channels conda-forge
- Update your conda version to the latest:
conda update -n base -c defaults conda
- Install Jupyter notebook in the
base
environment (this is the "core" conda environment where I would advise not to install any other packages than essential ones and always create other environments for your projects):
conda install -n base nb_conda_kernels jupyter
- Note: when creating a new environment, cf example below, you will need to install the
ipykernel
module in each other conda python environment for Jupyter to find your environments automatically
- Note: when creating a new environment, cf example below, you will need to install the
- Create a neuroimaging data science environment, for example as below:
conda create -n ni38 python=3.8 conda install -n ni38 numpy cython ipython scipy scikit-learn \ pandas xlrd matplotlib seaborn lxml ipykernel \ yapf sphinx numpydoc mypy pytest imageio pylint \ nilearn heudiconv pybids
- FOR WINDOWS ONLY
- Make sure you are in the
base
conda environment
conda activate base
- Generate Jupyter notebook configuration
jupyter notebook --generate-config
- Edit
~/.jupyter/jupyter_notebook_config.py
(for example with VS Code) to make sure to have the following two configuration statements (no#
in front) inside that file (asuming you have Chrome installed, otherwise change the path below to the location of your Internet browser executable):c.NotebookApp.use_redirect_file = False
c.NotebookApp.browser = u'/mnt/c/Program\ Files\ \(x86\)/Google/Chrome/Application/chrome.exe %s'
- Make sure you are in the
- Update your local environment:
- For all OS, to start a new project, you could do something like:
- Create a new project directory
my_proj
inside a parent directorymy_projects
cd mkdir my_projects cd my_projects mkdir my_proj
- Start Visual Studio code, create a new file, save it inside
my_proj
as a Python file (i.e. with.py
extension, e.g.analysis.py
) - In a terminal (a linux terminal but not the one provided by VS Code to keep it free), start a Jupyter notebook after making sure you are in the default
base
conda environment:conda activate base jupyter notebook
- A page should automatically open in your internet browser. If you cannot find it or it does not happen, read the output on the terminal and copy the URL indicated inside a tab of your internet browser
- To start a new notebook, in the Jupyter page in your browser, click in the top right on
New
and then choose the conda environment you want (the python process which will interpret your commands is called a kernel)
- Create a new project directory
- For all OS, to run the examples from the course, you could do something like:
- Create a directory
NIDS
then clone the python lectures inside itcd mkdir NIDS cd NIDS git clone https://github.com/NIDS2020-instructor/preproc.git
- Start Visual Studio code, click on
File
-->Open Folder
and then choosepreproc
(insideNIDS
), clickOK
- In a terminal (a linux terminal but not the one provided by VS Code to keep it free), start a Jupyter notebook after making sure you are in the default
base
conda environment:cd cd NIDS cd preproc conda activate base jupyter notebook
- A page should automatically open in your internet browser. If you cannot find it or it does not happen, read the output on the terminal and copy the URL indicated inside a tab of your internet browser
- To start a Python lecture notebook, click on its name in the list of files which is displayed in the Jupyter page of your browser (e.g. choose
preproc.ipynb
) - Then choose the right conda environment by clicking on
Kernel
->Change Kernel
and selecting an environment with all the required packages
- Create a directory
In case of any problem or if you have any question, please ask on Slack (after your very first message, please immediately hover on it and click on the chat buble to Reply in thread
for all your messages to be in a single thread), thank you !