Developing/Debugging XCP

The easiest way to debug or develop XCP is to download the source code from GitHub and mount it in an xcpEngine Docker or Singularity container. If you are on a laptop you will want to use Docker, whereas if you are on a HPC cluster you will want to use Singularity.

Downloading the source code

To download the master branch from GitHub, you can do the following:

git clone

Now you can edit or add to the code however you’d like. xcpEngine depends on number of dependencies including ANTS, FSL, c3d, AFNI, R and Python packages. The main R packages require are RNifti, optparse, pracma, signal, and python packages require are numpy,nibabel,niworkflows, nilearn and matplotlib.

The enviroment should be set as follow in the bash profile:


After setting the enviroment, it is require to reset the xcpEngine to link to those dependencies:

source ${XCPEDIR}/xcpReset

You can use docker or singularity image.

Patching a local copy of xcpEngine into a container

Assuming you’re in the same directory as when you ran git clone, you can now mount your local copy of xcpEngine into the container.:

docker run -it \
    -v `pwd`/xcpEngine:/xcpEngine \
    --entrypoint bash \

This will drop you into a shell inside the container, which contains all of xcpEngine’s dependencies and your local copy of the xcpEngine code. You can run the pipeline directly from inside this shell, but you will need to be certain that it has access to your data. Suppose your data is located on your laptop in /data/fmriprep, your cohort file is at /data/fmriprep/cohort.csv, the working directory should be /data/work and you want the output to go in /data/xcpOutput. You have to start Docker so that you can read and write from these locations. Do this by mounting your data directory in the container:

docker run -it \
  -v /data/fmriprep:/inputs \
  -v /data/xcpOutput:/output \
  -v /data/work:/work \
  -v `pwd`/xcpEngine:/xcpEngine \
  --entrypoint bash \

Then you can run xcpEngine in the container:

xcpEngine \
  -d /xcpEngine/designs/fc-36p.dsn \
  -c /inputs/cohort.csv \
  -i /work \
  -o /output

and the pipeline should run using the code in your local copy of xcpEngine.

Using singularity

Mounting directories in a container is not as simple using Singularity. Suppose you created a Singularity image using something like::

singularity build xcpEngine-latest.simg docker://pennbbl/xcpengine:latest

Assuming your data is in all the same locations as the laptop Docker example above, you can patch the local copy of the xcpEngine source code by:

singularity shell -B `pwd`/xcpEngine:/xcpEngine xcpEngine-latest.simg

Mounting data directories is somewhat trickier because the mount point must exist inside the container. One convenient location for binding data is /mnt.:

singularity shell \
  -B /data:/mnt \
  -B `pwd`/xcpEngine:/xcpEngine \

and you can make the call to xcpengine from inside the shell:

  -d /xcpEngine/designs/fc-36p.dsn \
  -c /mnt/fmriprep/cohort.csv \
  -i /mnt/work \
  -o /mnt/xcpOutput

This way you can make quick changes to the xcp source code and see how they would impact your pipeline without needing to create a new Singularity image.