neuroviz

A set of notebooks to introduce neuroscientists to concepts in information visualization.

Requirements:

docker

To use:

1. Clone or download this repository and unzip if necessary.

2. cd into the repository directory

3. Call docker: Make sure to replace [/outside_path/to/data/] with a pointer to a location on your local computer where data can be stored.

docker run -it --rm -v [/outside_path/to/data/]:/data -v $PWD:/home/neuro/test \
      -p 8888:8888 satra/ibro-workshop-2017

4. Inside Docker, first download data if you haven't. If you have mounted the external path properly, you only need to do this once. This will take some time.

cd /data
datalad install -r -g ///workshops/nih-2017/ds000114
cd

5. Start Jupyter:

$ jupyter-notebook --ip=*

to start jupyter with Xvfb enabled for the Mayavi notebook do:

$ Xvfb :1 +extension GLX -screen 0 1024x780x24 &
$ DISPLAY=:1 jupyter-notebook --ip=*

The $ represents your shell prompt inside the container.

6. Open the url in a local browser.

To recreate the docker image:

You will first need to download the cifti data and untar it.

curl -L https://www.dropbox.com/s/6povj9s96m0phc7/cifti.tgz?dl=0 | tar zx -

Then generate the Dockerfile

docker run --rm kaczmarj/neurodocker generate -b neurodebian:stretch-non-free -p apt \
--install tree git-annex-standalone vim emacs-nox nano less ncdu tig git-annex-remote-rclone \
--instruction "RUN curl -sL https://deb.nodesource.com/setup_6.x | bash -" \
--install nodejs build-essential \
--instruction "ENV LC_ALL=C.UTF-8" \
--instruction "RUN apt-get update && apt-get install -yq xvfb mesa-utils" \
--user=neuro \
--miniconda python_version=3.6 \
            conda_install="jupyter jupyterlab pandas matplotlib scikit-learn seaborn altair traitsui apptools configobj reprozip reprounzip vtk" \
            env_name="neuro" \
            pip_install="nilearn datalad mayavi" \
--instruction "RUN bash -c \"source activate neuro && pip install --pre --upgrade ipywidgets pythreejs \" " \
--instruction "RUN bash -c \"source activate neuro && pip install  --upgrade https://github.com/maartenbreddels/ipyvolume/archive/23eb91685dfcf200ee82f89ab6f7294f9214db8c.zip && jupyter nbextension install --py --sys-prefix ipyvolume && jupyter nbextension enable --py --sys-prefix ipyvolume \" " \
--instruction "RUN bash -c \"source activate neuro && conda install jupyter_contrib_nbextensions \" " \
--instruction "RUN bash -c \"source activate neuro && pip install --upgrade https://github.com/nipy/nibabel/archive/master.zip \" " \
--instruction "COPY cifti-data /cifti-data" \
--instruction "USER root" \
--instruction "RUN chmod -R a+r /cifti-data " \
--install graphviz \
--instruction "USER neuro" \
--instruction "RUN bash -c \"source activate neuro && jupyter nbextension enable rubberband/main && jupyter nbextension enable exercise2/main && jupyter nbextension enable spellchecker/main && conda install -yq bokeh scikit-image traits \" " \
--instruction "RUN bash -c \"source activate neuro && pip install --upgrade https://github.com/nipy/nipype/tarball/master https://github.com/INCF/pybids/archive/master.zip nipy duecredit \" " \
--instruction "RUN bash -c \"source activate neuro && python -c 'from nilearn import datasets; haxby_dataset = datasets.fetch_haxby()' \" " \
--workdir /home/neuro \
--no-check-urls > Dockerfile

Then build it:

docker build -t mycontainer .