This repository contains all documents for the workshop in Mumbai, July 2018.
Most of it's content is based on the Nipype Tutorial and the Workshop in Cambridge in September 2018. But many things were shortend or left out, to fit everything in a 4h webinar.
The webinar will cover:
- Conda and Docker
- Dataset handling/BIDS introduction
- Nilearn & Nibabel
- Introduction to Nipype
- Nipype basics
- Nipype hands-on
- Machine learning with nilearn, PyMPVA & keras
There are three ways on how you can access the content of this workshop.
All the notebooks (but not the slides) can be looked at via Jupyter nbviewer. Like this you can see everything but cannot really interact with the scripts or run the code.
We recommend that you install Docker on your machine to access the content of this workshop in an interactive way. To install Docker on your system, follow one of those links:
- Ubuntu or Debian
- Windows 7/8/9/10 or Windows 10Pro
- OS X (from El Capitan 10.11 on) or OS X (before El Capitan 10.11).
Once Docker is installed, open up the docker terminal and test if it works with the command:
docker run hello-world
Note: Linux users might need to use sudo
to run docker
commands or follow post-installation steps.
Once this worked proceed with the following steps to download and open the docker container for this workshop:
- Run the following command in a terminal:
docker run -it --rm -p 8888:8888 miykael/workshop_mumbai
- Copy paste the link that looks like
http://20f109eba8e4:8888/?token=0312c1ef3b61d7a44ff5346d3d150c23249a548850e13868
into your webbrowser. - Replace the hash number
20f109eba8e4
afterhttp://
withlocalhost
or your local IP (probably192.168.99.100
) if you're on windows. - Once Jupyter Notebook is open, click on the
program.ipynb
notebook, and you're good to go.
Note: For more information about how to run docker on your machine, checkout this section of the Nipype Tutorial.
It's of course also possible to run the workshop content without a docker container, by installing all the required softwares on your systems yourself. To setup the right Python environment, you need to do the following steps:
- Download and Install Miniconda on your system, if you don't have conda already on your system.
- Download the
requirements.yml
file from here - Open up a terminal and create a new conda environment with the provided
requirements.yml
file:conda env create --name workshop --file /path/to/requirements.yml
Perfect! Now you should have all Python packages that are required for the workshop. As a next step, let's get all the necessary content on your system. For this, you need to:
- Download the workshop content with this link. This file also contains the
dataset_ML.nii.gz
file that you need for the machine-learning notebook - Download the fMRI raw data.
Now, as a last step, if you want to run the Nipype notebooks, you also need to make sure that you have FSL on your system. For this, follow this instructions.
Once all this is setup, just go into the folder where you have the prgoram.ipynb
notebook, run jupyter notebook
. And you should be all set.
The dataset that we use in this workshop differs from previous workshops and focuses on resting-state fMRI data. We will be using part of the dataset from Zang et al.. The original data can be download here.
The docker container that we will be using for this workshop contains the raw data of the first three subjects, all that we need for the workshop. We've also added the pre-processed dataset and prepared the data of 48 subjects for the machine-learning part.