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About the environment of NARPS Open Pipelines

The Docker container 🐳

The NARPS Open Pipelines project is build upon several dependencies, such as Nipype but also the original software packages used by the pipelines (SPM, FSL, AFNI...). Therefore we recommend to use the nipype/nipype Docker image that contains all the required software dependencies.

The simplest way to start the container is by using the command below :

docker run -it nipype/nipype

From this command line, you need to add volumes to be able to link with your local files (code repository).

# Replace PATH_TO_THE_REPOSITORY in the following command (e.g.: with /home/user/dev/narps_open_pipelines/)
docker run -it \
           -v PATH_TO_THE_REPOSITORY:/home/neuro/code/ \
           nipype/nipype

Use Jupyter with the container

If you wish to use Jupyter to run the code, a port forwarding is needed :

docker run -it \
           -v PATH_TO_THE_REPOSITORY:/home/neuro/code/ \
           -p 8888:8888 \
           nipype/nipype

Then, from inside the container :

jupyter notebook --port=8888 --no-browser --ip=0.0.0.0

You can now access Jupyter using the address provided by the command line.

Note

Find useful information on the Docker documentation page. Here is a cheat sheet with Docker commands

Create a custom Docker image

The elodiegermani/open_pipeline Docker image is based on Neurodocker. It was created using the following command line :

docker run --rm repronim/neurodocker:0.7.0 generate docker \
           --base neurodebian:stretch-non-free --pkg-manager apt \
           --install git \
           --fsl version=6.0.3 \
           --afni version=latest method=binaries install_r=true install_r_pkgs=true install_python2=true install_python3=true \
           --spm12 version=r7771 method=binaries \
           --user=neuro \
           --workdir /home \
           --miniconda create_env=neuro \
                       conda_install="python=3.8 traits jupyter nilearn graphviz nipype scikit-image" \
                       pip_install="matplotlib" \
                       activate=True \
           --env LD_LIBRARY_PATH="/opt/miniconda-latest/envs/neuro:$LD_LIBRARY_PATH" \
           --run-bash "source activate neuro" \
           --user=root \
           --run 'chmod 777 -Rf /home' \
           --run 'chown -R neuro /home' \
           --user=neuro \
           --run 'mkdir -p ~/.jupyter && echo c.NotebookApp.ip = \"0.0.0.0\" > ~/.jupyter/jupyter_notebook_config.py' > Dockerfile

If you wish to create your own custom environment, make changes to the parameters, and build your custom image from the generated Dockerfile.

# Replace IMAGE_NAME in the following command
docker build --tag IMAGE_NAME - < Dockerfile

Good to know

To use SPM inside the container, use this command at the beginning of your script:

from nipype.interfaces import spm

matlab_cmd = '/opt/spm12-r7771/run_spm12.sh /opt/matlabmcr-2010a/v713/ script'

spm.SPMCommand.set_mlab_paths(matlab_cmd=matlab_cmd, use_mcr=True)