def test_build_image_petpvc_120b_binaries_xenial(self):
"""Install PETPVC binaries on Ubuntu Xenial."""
specs = {
'pkg_manager':
'apt',
'check_urls':
True,
'instructions': [
('base', 'ubuntu:xenial'),
('petpvc', {
'version': '1.2.0-b',
'use_binaries': True
}),
('user', 'neuro'),
]
}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING['petpvc_xenial']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_petpvc.sh"
assert DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
def test_build_image_miniconda_latest_shellscript_centos7(self):
"""Install latest version of Miniconda via ContinuumIO's installer
script on CentOS 7.
"""
specs = {'pkg_manager': 'yum',
'check_urls': True,
'instructions': [
('base', 'centos:7'),
('user', 'neuro'),
('miniconda', {
'env_name': 'default',
'conda_install': ['python=3.5.1', 'traits'],
'pip_install': ['https://github.com/nipy/nipype/archive/master.tar.gz'],
}),
('miniconda', {
'env_name': 'default',
'pip_install': ['pylsl'],
})
]}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING['miniconda_centos7']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_miniconda.sh"
DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
def test_build_image_dcm2niix_master_source_centos7(self):
"""Install dcm2niix from source on CentOS 7."""
specs = {
'pkg_manager':
'yum',
'check_urls':
True,
'instructions': [
('base', 'centos:7'),
('dcm2niix', {
'version': 'master'
}),
('user', 'neuro'),
]
}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING[
'dcm2niix-master_centos7']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_dcm2niix.sh"
assert DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
def test_build_image_fsl_5010_binaries_centos7(self):
"""Install FSL binaries on CentOS 7."""
specs = {
'pkg_manager':
'yum',
'check_urls':
True,
'instructions': [('base', 'centos:7'),
('fsl', {
'version': '5.0.10',
'use_binaries': True,
'eddy_5011': True
})]
}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING[
'fsl-5.0.10_centos7']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_fsl.sh"
assert DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
def test_build_image_mrtrix3_binaries_centos7(self):
"""Install MRtrix3 binaries on CentOS 7."""
specs = {
'pkg_manager':
'yum',
'check_urls':
True,
'instructions': [
('base', 'centos:7'),
('mrtrix3', {
'use_binaries': True
}),
('user', 'neuro'),
]
}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING[
'mrtrix3_centos7']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_mrtrix.sh"
assert DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
def test_build_image_convert3d_100_binaries_zesty(self):
"""Install Convert3D binaries on Ubuntu Zesty."""
specs = {
'pkg_manager':
'apt',
'check_urls':
True,
'instructions': [
('base', 'ubuntu:zesty'),
('c3d', {
'version': '1.0.0'
}),
('user', 'neuro'),
]
}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING[
'convert3d_zesty']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_convert3d.sh"
assert DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
def test_build_image_afni_latest_binaries_stretch(self):
"""Install latest AFNI binaries on Debian stretch."""
specs = {
'pkg_manager':
'apt',
'check_urls':
False,
'instructions': [
('base', 'debian:stretch'),
('afni', {
'version': 'latest',
'use_binaries': True
}),
('user', 'neuro'),
]
}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING[
'afni-latest_stretch']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_afni.sh"
assert DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
def test_build_image_freesurfer_600_min_binaries_xenial(self):
"""Install minimized FreeSurfer binaries on Ubuntu Xenial."""
specs = {
'pkg_manager':
'apt',
'check_urls':
True,
'instructions': [
('base', 'ubuntu:xenial'),
('freesurfer', {
'version': '6.0.0',
'use_binaries': True,
'min': True
}),
('user', 'neuro'),
]
}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING[
'freesurfer-min_zesty']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_freesurfer.sh"
assert DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
def generate(namespace):
"""Run `neurodocker generate`."""
specs = utils._namespace_to_specs(namespace)
df = Dockerfile(specs)
if not namespace.no_print_df:
print(df.cmd)
if namespace.output:
df.save(filepath=namespace.output)
def test___init__(self):
with pytest.raises(TypeError):
DockerImage(dict())
specs = {'pkg_manager': 'apt',
'instructions': [
('base', 'debian:jessie',)],
}
df = Dockerfile(specs=specs)
# Test that fileobj is a file object.
image = DockerImage(df)
assert image.fileobj.read()
def test_build_image_spm_12_standalone_zesty(self):
"""Install standalone SPM12 and MATLAB MCR R2017a."""
specs = {'pkg_manager': 'apt',
'check_urls': True,
'instructions': [
('base', 'ubuntu:zesty'),
('spm', {'version': '12', 'matlab_version': 'R2017a'}),
('user', 'neuro'),
]}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING['spm-12_zesty']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_spm.sh"
assert DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
def test_build_image_neurodebian_dcm2niix_xenial(self):
"""Install NeuroDebian on Ubuntu 16.04."""
specs = {'pkg_manager': 'apt',
'check_urls': False,
'instructions': [
('base', 'ubuntu:16.04'),
('neurodebian', {'os_codename': 'stretch',
'download_server': 'usa-nh',
'full': True,
'pkgs': ['dcm2niix']}),
('user', 'neuro'),
]}
df = Dockerfile(specs).cmd
dbx_path, image_name = utils.DROPBOX_DOCKERHUB_MAPPING['neurodebian_stretch']
image, push = utils.get_image_from_memory(df, dbx_path, image_name)
cmd = "bash /testscripts/test_neurodebian.sh"
assert DockerContainer(image).run(cmd, volumes=utils.volumes)
if push:
utils.push_image(image_name)
'conda_install':
'python=3.6 numpy scipy pandas jupyter scikit-learn matplotlib pytest scikit-image',
'pip_install': 'nipype nibabel nilearn nitime nipy'
}), ('ants', {
'version': '2.2.0'
}),
('freesurfer', {
'version': '6.0.0',
'license_path': 'license.txt',
'min': True
}), ('fsl', {
'version': '5.0.10',
'use_binaries': True
}),
('neurodebian', {
'os_codename': 'zesty',
'download_server': 'usa-nh',
'pkgs': ['afni', 'dcm2niix']
}), ('spm', {
'version': '12',
'matlab_version': 'R2017a'
})]
}
return specs
if __name__ == '__main__':
df = Dockerfile(set_specs())
df.save('Dockerfile')
print(df)
# download data and code
('instruction', 'RUN mkdir /data \\\n'
f' && curl -sSL --retry 5 {data} | tar zx -C /opt \\\n'
f' && curl -sSL --retry 5 {code} | tar zx -C /opt'),
('entrypoint', '/opt/antsct.sh'),
# create miniconda environment
('miniconda', {
'miniconda_version':
'4.3.31',
'env_name':
'antsct',
'conda_install':
' '.join([
'python=3.6.2', 'click=6.7', 'funcsigs=1.0.2', 'future=0.16.0',
'jinja2=2.10', 'matplotlib=2.1.1', 'mock=2.0.0',
'nibabel=2.2.1', 'numpy=1.14.0', 'packaging=16.8',
'pandas=0.21.0', 'prov=1.5.1', 'pydot=1.2.3',
'pydotplus=2.0.2', 'pytest=3.3.2', 'python-dateutil=2.6.1',
'seaborn=0.8.1', 'scikit-learn=0.19.1', 'scipy=1.0.0',
'simplejson=3.12.0', 'traits=4.6.0'
]),
'pip_install':
['nilearn==0.3.1', 'niworkflows==0.3.1', 'svgutils==0.3.0']
})
]
}
if __name__ == '__main__':
df = Dockerfile(specs)
DockerImage(df).build(tag='antsct', log_console=True)
def get_container_from_specs(specs, **kwargs):
"""Return started container. `kwargs` are for `container.start()`."""
df = Dockerfile(specs)
image = DockerImage(df).build(log_console=True)
return DockerContainer(image).start(**kwargs)