generate_dockerfiles.sh

#!/usr/bin/env bash
#
# Generate base and main Dockerfiles for Nipype.

set -e

USAGE="usage: $(basename $0) [-h] [-b] [-m]"

function Help {
  cat <<USAGE
Generate base and/or main Dockerfiles for Nipype.

Usage:

$(basename $0) [-h] [-b] [-m]

Options:

    -h : display this help message and exit
    -b : generate base Dockerfile
    -m : generate main Dockerfile

USAGE
}

# No command-line options passed.
if [ -z "$1" ]; then
  echo "$USAGE"
  exit 1
fi

# Get command-line options.
# Used the antsRegistrationSyN.sh as an example.
# https://github.com/ANTsX/ANTs/blob/master/Scripts/antsRegistrationSyN.sh
while getopts "hbm" OPT
do
  case $OPT in
    h)
      Help
      exit 0
    ;;
    b)
      GENERATE_BASE="1"
    ;;
    m)
      GENERATE_MAIN="1"
    ;;
    \?)
      echo "$USAGE" >&2
      exit 1
    ;;
  esac
done

# neurodocker version 0.5.0-3-g1788917
NEURODOCKER_IMAGE="kaczmarj/neurodocker:master@sha256:ac2085702daac716481daae5da055e2062be52075f8f3881672e958e0cd53e6b"
# neurodebian:stretch-non-free pulled on September 19, 2018
BASE_IMAGE="neurodebian:stretch-non-free@sha256:7cd978427d7ad215834fee221d0536ed7825b3cddebc481eba2d792dfc2f7332"

NIPYPE_BASE_IMAGE="nipype/nipype:base"
PKG_MANAGER="apt"
DIR="$(dirname "$0")"

function generate_base_dockerfile() {
  docker run --rm "$NEURODOCKER_IMAGE" generate docker \
    --base "$BASE_IMAGE" --pkg-manager "$PKG_MANAGER" \
    --label maintainer="The nipype developers https://github.com/nipy/nipype" \
    --spm12 version=r7219 \
    --env 'LD_LIBRARY_PATH=/lib/x86_64-linux-gnu:$LD_LIBRARY_PATH' \
    --freesurfer version=6.0.0-min \
    --dcm2niix version=v1.0.20190902 method=source \
    --run 'echo "cHJpbnRmICJrcnp5c3p0b2YuZ29yZ29sZXdza2lAZ21haWwuY29tCjUxNzIKICpDdnVtdkVWM3pUZmcKRlM1Si8yYzFhZ2c0RQoiID4gL29wdC9mcmVlc3VyZmVyLTYuMC4wLW1pbi9saWNlbnNlLnR4dA==" | base64 -d | sh' \
    --install afni ants apt-utils bzip2 convert3d file fsl-core \
              fsl-mni152-templates fusefat g++ git graphviz make python ruby \
              unzip xvfb git-annex-standalone liblzma-dev \
              gfortran libreadline-dev libx11-dev libxt-dev libpng-dev libjpeg-dev libcairo2-dev libssl-dev libxml2-dev libudunits2-dev libgdal-dev libbz2-dev libzstd-dev liblzma-dev libpcre2-dev \
    --add-to-entrypoint "source /etc/fsl/fsl.sh && source /etc/afni/afni.sh" \
    --env ANTSPATH='/usr/lib/ants' \
          PATH='/usr/lib/ants:$PATH' \
    --run "gem install fakes3" \
    > "$DIR/Dockerfile.base"
}


function generate_main_dockerfile() {
  docker run --rm "$NEURODOCKER_IMAGE" generate docker \
    --base "$NIPYPE_BASE_IMAGE" --pkg-manager "$PKG_MANAGER" \
    --label maintainer="The nipype developers https://github.com/nipy/nipype" \
    --env MKL_NUM_THREADS=1 \
          OMP_NUM_THREADS=1 \
    --arg PYTHON_VERSION_MAJOR=3 PYTHON_VERSION_MINOR=8 R_VERSION_MAJOR=4 R_VERSION_MINOR=1 R_VERSION_PATCH=0 R_CONFIGURE_OPTS=CONFIGURE_OPTIONS="--with-cairo --with-jpeglib --enable-R-shlib --with-blas --with-lapack" BUILD_DATE VCS_REF VERSION \
    --run 'curl -LO https://cran.rstudio.com/src/base/R-${R_VERSION_MAJOR}/R-${R_VERSION_MAJOR}.${R_VERSION_MINOR}.${R_VERSION_PATCH}.tar.gz
  && tar zxvf R-${R_VERSION_MAJOR}.${R_VERSION_MINOR}.${R_VERSION_PATCH}.tar.gz
  && rm R-${R_VERSION_MAJOR}.${R_VERSION_MINOR}.${R_VERSION_PATCH}.tar.gz 
  && cd R-${R_VERSION_MAJOR}.${R_VERSION_MINOR}.${R_VERSION_PATCH}
  && ./configure ${CONFIGURE_OPTIONS}
  && make && make install && cd .. && rm -rf R-${R_VERSION_MAJOR}.${R_VERSION_MINOR}.${R_VERSION_PATCH}
  && echo '"'"'options(repos = c(CRAN = "https://cran.rstudio.com/"), download.file.method = "libcurl")'"'"' >> /usr/local/lib/R/etc/Rprofile.site
  && Rscript -e "source('"'"'https://neuroconductor.org/neurocLite.R'"'"'); neuro_install(c('"'"'WhiteStripe'"'"'));"' \
    --user neuro \
    --workdir /home/neuro \
    --miniconda create_env=neuro \
                conda_install='python=${PYTHON_VERSION_MAJOR}.${PYTHON_VERSION_MINOR}
                               libxml2 libxslt matplotlib mkl "numpy!=1.16.0" paramiko
                               pandas psutil scikit-learn scipy traits rdflib' \
                pip_install="pytest-xdist" \
                activate=true \
    --copy docker/files/run_builddocs.sh docker/files/run_examples.sh \
           docker/files/run_pytests.sh nipype/external/fsl_imglob.py /usr/bin/ \
    --copy . /src/nipype \
    --user root \
    --run 'chown -R neuro /src
  && chmod +x /usr/bin/fsl_imglob.py /usr/bin/run_*.sh
  && . /etc/fsl/fsl.sh
  && ln -sf /usr/bin/fsl_imglob.py ${FSLDIR}/bin/imglob
  && mkdir /work
  && chown neuro /work' \
    --user neuro \
    --miniconda use_env=neuro \
                pip_opts="-e" \
                pip_install="/src/nipype[all] https://github.com/bids-standard/pybids/tarball/0.7.0" \
    --miniconda use_env=neuro \
                pip_install='"niflow-nipype1-workflows>=0.4.0"' \
    --workdir /work \
    --label org.label-schema.build-date='$BUILD_DATE' \
            org.label-schema.name="NIPYPE" \
            org.label-schema.description="NIPYPE - Neuroimaging in Python: Pipelines and Interfaces" \
            org.label-schema.url="http://nipype.readthedocs.io" \
            org.label-schema.vcs-ref='$VCS_REF' \
            org.label-schema.vcs-url="https://github.com/nipy/nipype" \
            org.label-schema.version='$VERSION' \
            org.label-schema.schema-version="1.0"
}


if [ "$GENERATE_BASE" == 1 ]; then
  generate_base_dockerfile > "$DIR/Dockerfile.base"
fi
if [ "$GENERATE_MAIN" == 1 ]; then
  generate_main_dockerfile > "$DIR/../Dockerfile"
fi