Update readme instructions

README.md

@@ -2,30 +2,45 @@
 
 [![DOI Badge](https://img.shields.io/badge/DOI-10.18112%2Fopenneuro.ds004906-blue)](https://openneuro.org/datasets/ds004906)
 [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/shimming-toolbox/rf-shimming-7t/blob/mb/neurolibre/data_processing.ipynb)
+[![Open in MyBinder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/shimming-toolbox/rf-shimming-7t/mb/neurolibre?labpath=content%2Findex.ipynb)
 
 Reproducible Notebook for the paper "RF shimming in the cervical spinal cord at 7T"
 
 ## Run with Google Colab
 
 Click on the badge "Open in Colab" ☝️. The notebook takes about 2 hours to run on Google Colab (without a paid subscription that gives access to more powerful resource).
 
-## Run with Jupyter Notebook
+## Run on a BinderHub (eg. NeuroLibre, Mybinder) or with repo2binder 
+
+Click on the badge "Open in MyBinder" ☝️. This environment setup downloads the data and the output of notebook previously run on Google Colab, and by default the notebook will only run the analysis cells (i.e. not the SCT-related commands).
+
+If you'd like to re-run the processing from scratch, change the `notebook = 'neurolibre-figures'` line in the first cell to `notebook = 'neurolibre-clean'`. This will delete the processed files and then re-run the entire processing pipeline. Note that some cells take a lot of RAM, and may fail on certain systems.
+
+## Run locally with Jupyter Notebook
 
 Install [Spinal Cord Toolbox](https://spinalcordtoolbox.com/user_section/installation.html)
 
 Clone this repository
 ~~~
 git clone https://github.com/shimming-toolbox/rf-shimming-7t.git
+git checkout mb/neurolibre
 cd rf-shimming-7t
 ~~~
 
 Install Python dependencies (assuming Python is already installed)
 ~~~
-pip install -r requirements.txt
+pip install -r binder/requirements.txt
 ~~~
 
+Download data
+~~~
+cd content
+repo2data -r ../binder/data_requirement.json
+~~~
+
+
 Run notebook
 ~~~
-jupyter notebook data_processing.ipynb
+jupyter notebook index.ipynb
 ~~~