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|
#!/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:$LD_LIBRARY_PATH' \
--freesurfer version=6.0.0-min \
--dcm2niix version=v1.0.20190902 method=source \
--run 'echo "cHJpbnRmICJrcnp5c3p0b2YuZ29yZ29sZXdza2lAZ21haWwuY29tCjUxNzIKICpDdnVtdkVWM3pUZmcKRlM1Si8yYzFhZ2c0RQoiID4gL29wdC9mcmVlc3VyZmVyLTYuMC4wLW1pbi9saWNlbnNlLnR4dA==" | base64 -d | sh' \
--install afni ants apt-utils bzip2 convert3d file fsl-core \
fsl-mni152-templates fusefat g++ git graphviz make python ruby \
unzip xvfb git-annex-standalone liblzma-dev \
--add-to-entrypoint "source /etc/fsl/fsl.sh && source /etc/afni/afni.sh" \
--env ANTSPATH='/usr/lib/ants' \
PATH='/usr/lib/ants:$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 BUILD_DATE VCS_REF VERSION \
--user neuro \
--run 'git config --global user.name nipybot
&& git config --global user.email "nipybot@gmail.com"' \
--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
|
