def build_workflow(opts, retval):
"""
Create the Nipype Workflow that supports the whole execution graph, given the inputs.
All the checks and the construction of the workflow are done
inside this function that has pickleable inputs and output
dictionary (``retval``) to allow isolation using a
``multiprocessing.Process`` that allows smriprep to enforce
a hard-limited memory-scope.
"""
from shutil import copyfile
from os import cpu_count
import uuid
from time import strftime
from subprocess import check_call, CalledProcessError, TimeoutExpired
from pkg_resources import resource_filename as pkgrf
import json
from bids import BIDSLayout
from nipype import logging, config as ncfg
from niworkflows.utils.bids import collect_participants
from ..__about__ import __version__
from ..workflows.base import init_smriprep_wf
logger = logging.getLogger('nipype.workflow')
INIT_MSG = """
Running sMRIPrep version {version}:
* BIDS dataset path: {bids_dir}.
* Participant list: {subject_list}.
* Run identifier: {uuid}.
{spaces}
""".format
# Set up some instrumental utilities
run_uuid = '%s_%s' % (strftime('%Y%m%d-%H%M%S'), uuid.uuid4())
# First check that bids_dir looks like a BIDS folder
bids_dir = opts.bids_dir.resolve()
layout = BIDSLayout(str(bids_dir), validate=False)
subject_list = collect_participants(
layout, participant_label=opts.participant_label)
bids_filters = json.loads(
opts.bids_filter_file.read_text()) if opts.bids_filter_file else None
# Load base plugin_settings from file if --use-plugin
if opts.use_plugin is not None:
from yaml import load as loadyml
with open(opts.use_plugin) as f:
plugin_settings = loadyml(f)
plugin_settings.setdefault('plugin_args', {})
else:
# Defaults
plugin_settings = {
'plugin': 'MultiProc',
'plugin_args': {
'raise_insufficient': False,
'maxtasksperchild': 1,
}
}
# Resource management options
# Note that we're making strong assumptions about valid plugin args
# This may need to be revisited if people try to use batch plugins
nprocs = plugin_settings['plugin_args'].get('n_procs')
# Permit overriding plugin config with specific CLI options
if nprocs is None or opts.nprocs is not None:
nprocs = opts.nprocs
if nprocs is None or nprocs < 1:
nprocs = cpu_count()
plugin_settings['plugin_args']['n_procs'] = nprocs
if opts.mem_gb:
plugin_settings['plugin_args']['memory_gb'] = opts.mem_gb
omp_nthreads = opts.omp_nthreads
if omp_nthreads == 0:
omp_nthreads = min(nprocs - 1 if nprocs > 1 else cpu_count(), 8)
if 1 < nprocs < omp_nthreads:
logger.warning(
'Per-process threads (--omp-nthreads=%d) exceed total '
'available CPUs (--nprocs/--ncpus=%d)', omp_nthreads, nprocs)
# Set up directories
output_dir = opts.output_dir.resolve()
log_dir = output_dir / 'smriprep' / 'logs'
work_dir = opts.work_dir.resolve()
# Check and create output and working directories
log_dir.mkdir(parents=True, exist_ok=True)
work_dir.mkdir(parents=True, exist_ok=True)
# Nipype config (logs and execution)
ncfg.update_config({
'logging': {
'log_directory': str(log_dir),
'log_to_file': True
},
'execution': {
'crashdump_dir': str(log_dir),
'crashfile_format': 'txt',
'get_linked_libs': False,
'stop_on_first_crash': opts.stop_on_first_crash,
},
'monitoring': {
'enabled': opts.resource_monitor,
'sample_frequency': '0.5',
'summary_append': True,
}
})
if opts.resource_monitor:
ncfg.enable_resource_monitor()
retval['return_code'] = 0
retval['plugin_settings'] = plugin_settings
retval['bids_dir'] = str(bids_dir)
retval['output_dir'] = str(output_dir)
retval['work_dir'] = str(work_dir)
retval['subject_list'] = subject_list
retval['run_uuid'] = run_uuid
retval['workflow'] = None
# Called with reports only
if opts.reports_only:
from niworkflows.reports import generate_reports
logger.log(25, 'Running --reports-only on participants %s',
', '.join(subject_list))
if opts.run_uuid is not None:
run_uuid = opts.run_uuid
retval['return_code'] = generate_reports(subject_list,
str(output_dir),
run_uuid,
packagename="smriprep")
return retval
logger.log(
25,
INIT_MSG(version=__version__,
bids_dir=bids_dir,
subject_list=subject_list,
uuid=run_uuid,
spaces=opts.output_spaces))
# Build main workflow
retval['workflow'] = init_smriprep_wf(
debug=opts.sloppy,
fast_track=opts.fast_track,
freesurfer=opts.run_reconall,
fs_subjects_dir=opts.fs_subjects_dir,
hires=opts.hires,
layout=layout,
longitudinal=opts.longitudinal,
low_mem=opts.low_mem,
omp_nthreads=omp_nthreads,
output_dir=str(output_dir),
run_uuid=run_uuid,
skull_strip_fixed_seed=opts.skull_strip_fixed_seed,
skull_strip_mode=opts.skull_strip_mode,
skull_strip_template=opts.skull_strip_template[0],
spaces=opts.output_spaces,
subject_list=subject_list,
work_dir=str(work_dir),
bids_filters=bids_filters,
)
retval['return_code'] = 0
boilerplate = retval['workflow'].visit_desc()
(log_dir / 'CITATION.md').write_text(boilerplate)
logger.log(
25, 'Works derived from this sMRIPrep execution should '
'include the following boilerplate:\n\n%s', boilerplate)
# Generate HTML file resolving citations
cmd = [
'pandoc', '-s', '--bibliography',
pkgrf('smriprep',
'data/boilerplate.bib'), '--filter', 'pandoc-citeproc',
'--metadata', 'pagetitle="sMRIPrep citation boilerplate"',
str(log_dir / 'CITATION.md'), '-o',
str(log_dir / 'CITATION.html')
]
try:
check_call(cmd, timeout=10)
except (FileNotFoundError, CalledProcessError, TimeoutExpired):
logger.warning('Could not generate CITATION.html file:\n%s',
' '.join(cmd))
# Generate LaTex file resolving citations
cmd = [
'pandoc', '-s', '--bibliography',
pkgrf('smriprep', 'data/boilerplate.bib'), '--natbib',
str(log_dir / 'CITATION.md'), '-o',
str(log_dir / 'CITATION.tex')
]
try:
check_call(cmd, timeout=10)
except (FileNotFoundError, CalledProcessError, TimeoutExpired):
logger.warning('Could not generate CITATION.tex file:\n%s',
' '.join(cmd))
else:
copyfile(pkgrf('smriprep', 'data/boilerplate.bib'),
str(log_dir / 'CITATION.bib'))
return retval
def build_workflow(opts, retval):
"""
Create the Nipype Workflow that supports the whole execution
graph, given the inputs.
All the checks and the construction of the workflow are done
inside this function that has pickleable inputs and output
dictionary (``retval``) to allow isolation using a
``multiprocessing.Process`` that allows fmriprep to enforce
a hard-limited memory-scope.
"""
from bids import BIDSLayout
from nipype import logging as nlogging, config as ncfg
from niworkflows.utils.bids import collect_participants
from niworkflows.reports import generate_reports
from ..__about__ import __version__
from ..workflows.base import init_fmriprep_wf
build_log = nlogging.getLogger('nipype.workflow')
INIT_MSG = """
Running fMRIPREP version {version}:
* BIDS dataset path: {bids_dir}.
* Participant list: {subject_list}.
* Run identifier: {uuid}.
""".format
bids_dir = opts.bids_dir.resolve()
output_dir = opts.output_dir.resolve()
work_dir = opts.work_dir.resolve()
retval['return_code'] = 1
retval['workflow'] = None
retval['bids_dir'] = str(bids_dir)
retval['output_dir'] = str(output_dir)
retval['work_dir'] = str(work_dir)
if output_dir == bids_dir:
build_log.error(
'The selected output folder is the same as the input BIDS folder. '
'Please modify the output path (suggestion: %s).', bids_dir /
'derivatives' / ('fmriprep-%s' % __version__.split('+')[0]))
retval['return_code'] = 1
return retval
output_spaces = parse_spaces(opts)
# Set up some instrumental utilities
run_uuid = '%s_%s' % (strftime('%Y%m%d-%H%M%S'), uuid.uuid4())
retval['run_uuid'] = run_uuid
# First check that bids_dir looks like a BIDS folder
layout = BIDSLayout(str(bids_dir),
validate=False,
ignore=("code", "stimuli", "sourcedata", "models",
"derivatives", re.compile(r'^\.')))
subject_list = collect_participants(
layout, participant_label=opts.participant_label)
retval['subject_list'] = subject_list
# Load base plugin_settings from file if --use-plugin
if opts.use_plugin is not None:
from yaml import load as loadyml
with open(opts.use_plugin) as f:
plugin_settings = loadyml(f)
plugin_settings.setdefault('plugin_args', {})
else:
# Defaults
plugin_settings = {
'plugin': 'MultiProc',
'plugin_args': {
'raise_insufficient': False,
'maxtasksperchild': 1,
}
}
# Resource management options
# Note that we're making strong assumptions about valid plugin args
# This may need to be revisited if people try to use batch plugins
nthreads = plugin_settings['plugin_args'].get('n_procs')
# Permit overriding plugin config with specific CLI options
if nthreads is None or opts.nthreads is not None:
nthreads = opts.nthreads
if nthreads is None or nthreads < 1:
nthreads = cpu_count()
plugin_settings['plugin_args']['n_procs'] = nthreads
if opts.mem_mb:
plugin_settings['plugin_args']['memory_gb'] = opts.mem_mb / 1024
omp_nthreads = opts.omp_nthreads
if omp_nthreads == 0:
omp_nthreads = min(nthreads - 1 if nthreads > 1 else cpu_count(), 8)
if 1 < nthreads < omp_nthreads:
build_log.warning(
'Per-process threads (--omp-nthreads=%d) exceed total '
'threads (--nthreads/--n_cpus=%d)', omp_nthreads, nthreads)
retval['plugin_settings'] = plugin_settings
# Set up directories
log_dir = output_dir / 'fmriprep' / 'logs'
# Check and create output and working directories
output_dir.mkdir(exist_ok=True, parents=True)
log_dir.mkdir(exist_ok=True, parents=True)
work_dir.mkdir(exist_ok=True, parents=True)
# Nipype config (logs and execution)
ncfg.update_config({
'logging': {
'log_directory': str(log_dir),
'log_to_file': True
},
'execution': {
'crashdump_dir': str(log_dir),
'crashfile_format': 'txt',
'get_linked_libs': False,
'stop_on_first_crash': opts.stop_on_first_crash,
},
'monitoring': {
'enabled': opts.resource_monitor,
'sample_frequency': '0.5',
'summary_append': True,
}
})
if opts.resource_monitor:
ncfg.enable_resource_monitor()
# Called with reports only
if opts.reports_only:
build_log.log(25, 'Running --reports-only on participants %s',
', '.join(subject_list))
if opts.run_uuid is not None:
run_uuid = opts.run_uuid
retval['run_uuid'] = run_uuid
retval['return_code'] = generate_reports(subject_list,
output_dir,
work_dir,
run_uuid,
packagename='fmriprep')
return retval
# Build main workflow
build_log.log(
25,
INIT_MSG(version=__version__,
bids_dir=bids_dir,
subject_list=subject_list,
uuid=run_uuid))
retval['workflow'] = init_fmriprep_wf(
anat_only=opts.anat_only,
aroma_melodic_dim=opts.aroma_melodic_dimensionality,
bold2t1w_dof=opts.bold2t1w_dof,
cifti_output=opts.cifti_output,
debug=opts.sloppy,
dummy_scans=opts.dummy_scans,
echo_idx=opts.echo_idx,
err_on_aroma_warn=opts.error_on_aroma_warnings,
fmap_bspline=opts.fmap_bspline,
fmap_demean=opts.fmap_no_demean,
force_syn=opts.force_syn,
freesurfer=opts.run_reconall,
hires=opts.hires,
ignore=opts.ignore,
layout=layout,
longitudinal=opts.longitudinal,
low_mem=opts.low_mem,
medial_surface_nan=opts.medial_surface_nan,
omp_nthreads=omp_nthreads,
output_dir=str(output_dir),
output_spaces=output_spaces,
run_uuid=run_uuid,
regressors_all_comps=opts.return_all_components,
regressors_fd_th=opts.fd_spike_threshold,
regressors_dvars_th=opts.dvars_spike_threshold,
skull_strip_fixed_seed=opts.skull_strip_fixed_seed,
skull_strip_template=opts.skull_strip_template,
subject_list=subject_list,
t2s_coreg=opts.t2s_coreg,
task_id=opts.task_id,
use_aroma=opts.use_aroma,
use_bbr=opts.use_bbr,
use_syn=opts.use_syn_sdc,
work_dir=str(work_dir),
)
retval['return_code'] = 0
logs_path = Path(output_dir) / 'fmriprep' / 'logs'
boilerplate = retval['workflow'].visit_desc()
if boilerplate:
citation_files = {
ext: logs_path / ('CITATION.%s' % ext)
for ext in ('bib', 'tex', 'md', 'html')
}
# To please git-annex users and also to guarantee consistency
# among different renderings of the same file, first remove any
# existing one
for citation_file in citation_files.values():
try:
citation_file.unlink()
except FileNotFoundError:
pass
citation_files['md'].write_text(boilerplate)
build_log.log(
25, 'Works derived from this fMRIPrep execution should '
'include the following boilerplate:\n\n%s', boilerplate)
return retval
def build_workflow(config_file, retval):
"""Create the Nipype Workflow that supports the whole execution graph."""
from niworkflows.utils.bids import collect_participants, check_pipeline_version
from niworkflows.utils.misc import check_valid_fs_license
from niworkflows.reports import generate_reports
from .. import config
from ..utils.misc import check_deps
from ..workflows.base import init_fmriprep_wf
config.load(config_file)
build_log = config.loggers.workflow
output_dir = config.execution.output_dir
version = config.environment.version
retval["return_code"] = 1
retval["workflow"] = None
# warn if older results exist: check for dataset_description.json in output folder
msg = check_pipeline_version(
version, output_dir / "fmriprep-rodents" / "dataset_description.json")
if msg is not None:
build_log.warning(msg)
# Please note this is the input folder's dataset_description.json
dset_desc_path = config.execution.bids_dir / "dataset_description.json"
if dset_desc_path.exists():
from hashlib import sha256
desc_content = dset_desc_path.read_bytes()
config.execution.bids_description_hash = sha256(
desc_content).hexdigest()
# First check that bids_dir looks like a BIDS folder
subject_list = collect_participants(
config.execution.layout,
participant_label=config.execution.participant_label)
# Called with reports only
if config.execution.reports_only:
from pkg_resources import resource_filename as pkgrf
build_log.log(25, "Running --reports-only on participants %s",
", ".join(subject_list))
retval["return_code"] = generate_reports(
subject_list,
config.execution.output_dir,
config.execution.run_uuid,
config=pkgrf("fmriprep_rodents", "data/reports-spec.yml"),
packagename="fmriprep-rodents",
)
return retval
# Build main workflow
init_msg = f"""
Running fMRIPREP version {config.environment.version}:
* BIDS dataset path: {config.execution.bids_dir}.
* Participant list: {subject_list}.
* Run identifier: {config.execution.run_uuid}.
* Output spaces: {config.execution.output_spaces}."""
if config.execution.anat_derivatives:
init_msg += f"""
* Anatomical derivatives: {config.execution.anat_derivatives}."""
if config.execution.fs_subjects_dir:
init_msg += f"""
* Pre-run FreeSurfer's SUBJECTS_DIR: {config.execution.fs_subjects_dir}."""
build_log.log(25, init_msg)
retval["workflow"] = init_fmriprep_wf()
# Check for FS license after building the workflow
if not check_valid_fs_license():
build_log.critical("""\
ERROR: a valid license file is required for FreeSurfer to run. fMRIPrep looked for an existing \
license file at several paths, in this order: 1) command line argument ``--fs-license-file``; \
2) ``$FS_LICENSE`` environment variable; and 3) the ``$FREESURFER_HOME/license.txt`` path. Get it \
(for free) by registering at https://surfer.nmr.mgh.harvard.edu/registration.html"""
)
retval["return_code"] = 126 # 126 == Command invoked cannot execute.
return retval
# Check workflow for missing commands
missing = check_deps(retval["workflow"])
if missing:
build_log.critical(
"Cannot run fMRIPrep. Missing dependencies:%s",
"\n\t* ".join(
[""] +
[f"{cmd} (Interface: {iface})" for iface, cmd in missing]),
)
retval["return_code"] = 127 # 127 == command not found.
return retval
config.to_filename(config_file)
build_log.info(
"fMRIPrep workflow graph with %d nodes built successfully.",
len(retval["workflow"]._get_all_nodes()),
)
retval["return_code"] = 0
return retval
def build_workflow(opts, retval):
"""
Create the Nipype Workflow that supports the whole execution
graph, given the inputs.
All the checks and the construction of the workflow are done
inside this function that has pickleable inputs and output
dictionary (``retval``) to allow isolation using a
``multiprocessing.Process`` that allows fmriprep to enforce
a hard-limited memory-scope.
"""
from subprocess import check_call, CalledProcessError, TimeoutExpired
from pkg_resources import resource_filename as pkgrf
from shutil import copyfile
from nipype import logging, config as ncfg
from niworkflows.utils.bids import collect_participants
from ..__about__ import __version__
from ..workflows.base import init_fmriprep_wf
from ..viz.reports import generate_reports
logger = logging.getLogger('nipype.workflow')
INIT_MSG = """
Running fMRIPREP version {version}:
* BIDS dataset path: {bids_dir}.
* Participant list: {subject_list}.
* Run identifier: {uuid}.
""".format
output_spaces = opts.output_space or []
# Validity of some inputs
# ERROR check if use_aroma was specified, but the correct template was not
if opts.use_aroma and (opts.template != 'MNI152NLin2009cAsym'
or 'template' not in output_spaces):
output_spaces.append('template')
logger.warning(
'Option "--use-aroma" requires functional images to be resampled to MNI space. '
'The argument "template" has been automatically added to the list of output '
'spaces (option "--output-space").')
if opts.cifti_output and (opts.template != 'MNI152NLin2009cAsym'
or 'template' not in output_spaces):
output_spaces.append('template')
logger.warning(
'Option "--cifti-output" requires functional images to be resampled to MNI space. '
'The argument "template" has been automatically added to the list of output '
'spaces (option "--output-space").')
# Check output_space
if 'template' not in output_spaces and (opts.use_syn_sdc
or opts.force_syn):
msg = [
'SyN SDC correction requires T1 to MNI registration, but '
'"template" is not specified in "--output-space" arguments.',
'Option --use-syn will be cowardly dismissed.'
]
if opts.force_syn:
output_spaces.append('template')
msg[1] = (
' Since --force-syn has been requested, "template" has been added to'
' the "--output-space" list.')
logger.warning(' '.join(msg))
# Set up some instrumental utilities
run_uuid = '%s_%s' % (strftime('%Y%m%d-%H%M%S'), uuid.uuid4())
# First check that bids_dir looks like a BIDS folder
bids_dir = os.path.abspath(opts.bids_dir)
subject_list = collect_participants(
bids_dir, participant_label=opts.participant_label)
# Load base plugin_settings from file if --use-plugin
if opts.use_plugin is not None:
from yaml import load as loadyml
with open(opts.use_plugin) as f:
plugin_settings = loadyml(f)
plugin_settings.setdefault('plugin_args', {})
else:
# Defaults
plugin_settings = {
'plugin': 'MultiProc',
'plugin_args': {
'raise_insufficient': False,
'maxtasksperchild': 1,
}
}
# Resource management options
# Note that we're making strong assumptions about valid plugin args
# This may need to be revisited if people try to use batch plugins
nthreads = plugin_settings['plugin_args'].get('n_procs')
# Permit overriding plugin config with specific CLI options
if nthreads is None or opts.nthreads is not None:
nthreads = opts.nthreads
if nthreads is None or nthreads < 1:
nthreads = cpu_count()
plugin_settings['plugin_args']['n_procs'] = nthreads
if opts.mem_mb:
plugin_settings['plugin_args']['memory_gb'] = opts.mem_mb / 1024
omp_nthreads = opts.omp_nthreads
if omp_nthreads == 0:
omp_nthreads = min(nthreads - 1 if nthreads > 1 else cpu_count(), 8)
if 1 < nthreads < omp_nthreads:
logger.warning(
'Per-process threads (--omp-nthreads=%d) exceed total '
'threads (--nthreads/--n_cpus=%d)', omp_nthreads, nthreads)
# Set up directories
output_dir = op.abspath(opts.output_dir)
log_dir = op.join(output_dir, 'fmriprep', 'logs')
work_dir = op.abspath(opts.work_dir or 'work') # Set work/ as default
# Check and create output and working directories
os.makedirs(output_dir, exist_ok=True)
os.makedirs(log_dir, exist_ok=True)
os.makedirs(work_dir, exist_ok=True)
# Nipype config (logs and execution)
ncfg.update_config({
'logging': {
'log_directory': log_dir,
'log_to_file': True
},
'execution': {
'crashdump_dir':
log_dir,
'crashfile_format':
'txt',
'get_linked_libs':
False,
'stop_on_first_crash':
opts.stop_on_first_crash or opts.work_dir is None,
},
'monitoring': {
'enabled': opts.resource_monitor,
'sample_frequency': '0.5',
'summary_append': True,
}
})
if opts.resource_monitor:
ncfg.enable_resource_monitor()
retval['return_code'] = 0
retval['plugin_settings'] = plugin_settings
retval['bids_dir'] = bids_dir
retval['output_dir'] = output_dir
retval['work_dir'] = work_dir
retval['subject_list'] = subject_list
retval['run_uuid'] = run_uuid
retval['workflow'] = None
# Called with reports only
if opts.reports_only:
logger.log(25, 'Running --reports-only on participants %s',
', '.join(subject_list))
if opts.run_uuid is not None:
run_uuid = opts.run_uuid
retval['return_code'] = generate_reports(subject_list, output_dir,
work_dir, run_uuid)
return retval
# Build main workflow
logger.log(
25,
INIT_MSG(version=__version__,
bids_dir=bids_dir,
subject_list=subject_list,
uuid=run_uuid))
template_out_grid = opts.template_resampling_grid
if opts.output_grid_reference is not None:
logger.warning(
'Option --output-grid-reference is deprecated, please use '
'--template-resampling-grid')
template_out_grid = template_out_grid or opts.output_grid_reference
if opts.debug:
logger.warning('Option --debug is deprecated and has no effect')
retval['workflow'] = init_fmriprep_wf(
subject_list=subject_list,
task_id=opts.task_id,
echo_idx=opts.echo_idx,
run_uuid=run_uuid,
ignore=opts.ignore,
debug=opts.sloppy,
low_mem=opts.low_mem,
anat_only=opts.anat_only,
longitudinal=opts.longitudinal,
t2s_coreg=opts.t2s_coreg,
omp_nthreads=omp_nthreads,
skull_strip_template=opts.skull_strip_template,
skull_strip_fixed_seed=opts.skull_strip_fixed_seed,
work_dir=work_dir,
output_dir=output_dir,
bids_dir=bids_dir,
freesurfer=opts.run_reconall,
output_spaces=output_spaces,
template=opts.template,
medial_surface_nan=opts.medial_surface_nan,
cifti_output=opts.cifti_output,
template_out_grid=template_out_grid,
hires=opts.hires,
use_bbr=opts.use_bbr,
bold2t1w_dof=opts.bold2t1w_dof,
fmap_bspline=opts.fmap_bspline,
fmap_demean=opts.fmap_no_demean,
use_syn=opts.use_syn_sdc,
force_syn=opts.force_syn,
use_aroma=opts.use_aroma,
aroma_melodic_dim=opts.aroma_melodic_dimensionality,
ignore_aroma_err=opts.ignore_aroma_denoising_errors,
)
retval['return_code'] = 0
logs_path = Path(output_dir) / 'fmriprep' / 'logs'
boilerplate = retval['workflow'].visit_desc()
if boilerplate:
(logs_path / 'CITATION.md').write_text(boilerplate)
logger.log(
25, 'Works derived from this fMRIPrep execution should '
'include the following boilerplate:\n\n%s', boilerplate)
# Generate HTML file resolving citations
cmd = [
'pandoc', '-s', '--bibliography',
pkgrf('fmriprep',
'data/boilerplate.bib'), '--filter', 'pandoc-citeproc',
'--metadata', 'pagetitle="fMRIPrep citation boilerplate"',
str(logs_path / 'CITATION.md'), '-o',
str(logs_path / 'CITATION.html')
]
try:
check_call(cmd, timeout=10)
except (FileNotFoundError, CalledProcessError, TimeoutExpired):
logger.warning('Could not generate CITATION.html file:\n%s',
' '.join(cmd))
# Generate LaTex file resolving citations
cmd = [
'pandoc', '-s', '--bibliography',
pkgrf('fmriprep', 'data/boilerplate.bib'), '--natbib',
str(logs_path / 'CITATION.md'), '-o',
str(logs_path / 'CITATION.tex')
]
try:
check_call(cmd, timeout=10)
except (FileNotFoundError, CalledProcessError, TimeoutExpired):
logger.warning('Could not generate CITATION.tex file:\n%s',
' '.join(cmd))
else:
copyfile(pkgrf('fmriprep', 'data/boilerplate.bib'),
(logs_path / 'CITATION.bib'))
return retval
def build_workflow(config_file, retval):
"""Create the Nipype Workflow that supports the whole execution graph."""
from niworkflows.utils.bids import collect_participants, check_pipeline_version
from niworkflows.reports import generate_reports
from .. import config
from ..utils.misc import check_deps
from ..workflows.base import init_fmriprep_wf
config.load(config_file)
build_log = config.loggers.workflow
output_dir = config.execution.output_dir
version = config.environment.version
retval["return_code"] = 1
retval["workflow"] = None
# warn if older results exist: check for dataset_description.json in output folder
msg = check_pipeline_version(
version, output_dir / "fmriprep" / "dataset_description.json")
if msg is not None:
build_log.warning(msg)
# Please note this is the input folder's dataset_description.json
dset_desc_path = config.execution.bids_dir / "dataset_description.json"
if dset_desc_path.exists():
from hashlib import sha256
desc_content = dset_desc_path.read_bytes()
config.execution.bids_description_hash = sha256(
desc_content).hexdigest()
# First check that bids_dir looks like a BIDS folder
subject_list = collect_participants(
config.execution.layout,
participant_label=config.execution.participant_label)
# Called with reports only
if config.execution.reports_only:
from pkg_resources import resource_filename as pkgrf
build_log.log(25, "Running --reports-only on participants %s",
", ".join(subject_list))
retval["return_code"] = generate_reports(
subject_list,
config.execution.output_dir,
config.execution.run_uuid,
config=pkgrf("fmriprep", "data/reports-spec.yml"),
packagename="fmriprep",
)
return retval
# Build main workflow
init_msg = f"""
Running fMRIPREP version {config.environment.version}:
* BIDS dataset path: {config.execution.bids_dir}.
* Participant list: {subject_list}.
* Run identifier: {config.execution.run_uuid}.
* Output spaces: {config.execution.output_spaces}."""
if config.execution.anat_derivatives:
init_msg += f"""
* Anatomical derivatives: {config.execution.anat_derivatives}."""
if config.execution.fs_subjects_dir:
init_msg += f"""
* Pre-run FreeSurfer's SUBJECTS_DIR: {config.execution.fs_subjects_dir}."""
build_log.log(25, init_msg)
retval["workflow"] = init_fmriprep_wf()
# Check workflow for missing commands
missing = check_deps(retval["workflow"])
if missing:
build_log.critical(
"Cannot run fMRIPrep. Missing dependencies:%s",
"\n\t* ".join(
[""] +
[f"{cmd} (Interface: {iface})" for iface, cmd in missing]),
)
retval["return_code"] = 127 # 127 == command not found.
return retval
config.to_filename(config_file)
build_log.info(
"fMRIPrep workflow graph with %d nodes built successfully.",
len(retval["workflow"]._get_all_nodes()),
)
retval["return_code"] = 0
return retval
def build_workflow(config_file, retval):
"""Create the Nipype Workflow that supports the whole execution graph."""
from niworkflows.utils.bids import collect_participants, check_pipeline_version
from niworkflows.reports import generate_reports
from .. import config
from ..utils.misc import check_deps
from ..workflows.base import init_fmriprep_wf
config.load(config_file)
build_log = config.loggers.workflow
output_dir = config.execution.output_dir
version = config.environment.version
retval['return_code'] = 1
retval['workflow'] = None
# warn if older results exist: check for dataset_description.json in output folder
msg = check_pipeline_version(
version, output_dir / 'fmriprep' / 'dataset_description.json')
if msg is not None:
build_log.warning(msg)
# Please note this is the input folder's dataset_description.json
dset_desc_path = config.execution.bids_dir / 'dataset_description.json'
if dset_desc_path.exists():
from hashlib import sha256
desc_content = dset_desc_path.read_bytes()
config.execution.bids_description_hash = sha256(
desc_content).hexdigest()
# First check that bids_dir looks like a BIDS folder
subject_list = collect_participants(
config.execution.layout,
participant_label=config.execution.participant_label)
# Called with reports only
if config.execution.reports_only:
from pkg_resources import resource_filename as pkgrf
build_log.log(25, 'Running --reports-only on participants %s',
', '.join(subject_list))
retval['return_code'] = generate_reports(subject_list,
config.execution.output_dir,
config.execution.work_dir,
config.execution.run_uuid,
config=pkgrf(
'fmriprep',
'data/reports-spec.yml'),
packagename='fmriprep')
return retval
# Build main workflow
INIT_MSG = """
Running fMRIPREP version {version}:
* BIDS dataset path: {bids_dir}.
* Participant list: {subject_list}.
* Run identifier: {uuid}.
* Output spaces: {spaces}.
""".format
build_log.log(
25,
INIT_MSG(version=config.environment.version,
bids_dir=config.execution.bids_dir,
subject_list=subject_list,
uuid=config.execution.run_uuid,
spaces=config.execution.output_spaces))
retval['workflow'] = init_fmriprep_wf()
# Check workflow for missing commands
missing = check_deps(retval['workflow'])
if missing:
build_log.critical(
"Cannot run fMRIPrep. Missing dependencies:%s", '\n\t* %s'.join([
"{} (Interface: {})".format(cmd, iface)
for iface, cmd in missing
]))
retval['return_code'] = 127 # 127 == command not found.
return retval
config.to_filename(config_file)
build_log.info("fMRIPrep workflow graph with %d nodes built successfully.",
len(retval['workflow']._get_all_nodes()))
retval['return_code'] = 0
return retval
def build_workflow(opts, retval):
"""
Create the Nipype Workflow that supports the whole execution
graph, given the inputs.
All the checks and the construction of the workflow are done
inside this function that has pickleable inputs and output
dictionary (``retval``) to allow isolation using a
``multiprocessing.Process`` that allows fmriprep to enforce
a hard-limited memory-scope.
"""
from subprocess import check_call, CalledProcessError, TimeoutExpired
from pkg_resources import resource_filename as pkgrf
from shutil import copyfile
from nipype import logging, config as ncfg
from niworkflows.utils.bids import collect_participants
from ..__about__ import __version__
from ..workflows.base import init_fmriprep_wf
from ..viz.reports import generate_reports
logger = logging.getLogger('nipype.workflow')
INIT_MSG = """
Running fMRIPREP version {version}:
* BIDS dataset path: {bids_dir}.
* Participant list: {subject_list}.
* Run identifier: {uuid}.
""".format
output_spaces = opts.output_space or []
# Validity of some inputs
# ERROR check if use_aroma was specified, but the correct template was not
if opts.use_aroma and (opts.template != 'MNI152NLin2009cAsym' or
'template' not in output_spaces):
output_spaces.append('template')
logger.warning(
'Option "--use-aroma" requires functional images to be resampled to MNI space. '
'The argument "template" has been automatically added to the list of output '
'spaces (option "--output-space").'
)
if opts.cifti_output and (opts.template != 'MNI152NLin2009cAsym' or
'template' not in output_spaces):
output_spaces.append('template')
logger.warning(
'Option "--cifti-output" requires functional images to be resampled to MNI space. '
'The argument "template" has been automatically added to the list of output '
'spaces (option "--output-space").'
)
# Check output_space
if 'template' not in output_spaces and (opts.use_syn_sdc or opts.force_syn):
msg = ['SyN SDC correction requires T1 to MNI registration, but '
'"template" is not specified in "--output-space" arguments.',
'Option --use-syn will be cowardly dismissed.']
if opts.force_syn:
output_spaces.append('template')
msg[1] = (' Since --force-syn has been requested, "template" has been added to'
' the "--output-space" list.')
logger.warning(' '.join(msg))
# Set up some instrumental utilities
run_uuid = '%s_%s' % (strftime('%Y%m%d-%H%M%S'), uuid.uuid4())
# First check that bids_dir looks like a BIDS folder
bids_dir = os.path.abspath(opts.bids_dir)
subject_list = collect_participants(
bids_dir, participant_label=opts.participant_label)
# Load base plugin_settings from file if --use-plugin
if opts.use_plugin is not None:
from yaml import load as loadyml
with open(opts.use_plugin) as f:
plugin_settings = loadyml(f)
plugin_settings.setdefault('plugin_args', {})
else:
# Defaults
plugin_settings = {
'plugin': 'MultiProc',
'plugin_args': {
'raise_insufficient': False,
'maxtasksperchild': 1,
}
}
# Resource management options
# Note that we're making strong assumptions about valid plugin args
# This may need to be revisited if people try to use batch plugins
nthreads = plugin_settings['plugin_args'].get('n_procs')
# Permit overriding plugin config with specific CLI options
if nthreads is None or opts.nthreads is not None:
nthreads = opts.nthreads
if nthreads is None or nthreads < 1:
nthreads = cpu_count()
plugin_settings['plugin_args']['n_procs'] = nthreads
if opts.mem_mb:
plugin_settings['plugin_args']['memory_gb'] = opts.mem_mb / 1024
omp_nthreads = opts.omp_nthreads
if omp_nthreads == 0:
omp_nthreads = min(nthreads - 1 if nthreads > 1 else cpu_count(), 8)
if 1 < nthreads < omp_nthreads:
logger.warning(
'Per-process threads (--omp-nthreads=%d) exceed total '
'threads (--nthreads/--n_cpus=%d)', omp_nthreads, nthreads)
# Set up directories
output_dir = op.abspath(opts.output_dir)
log_dir = op.join(output_dir, 'fmriprep', 'logs')
work_dir = op.abspath(opts.work_dir or 'work') # Set work/ as default
# Check and create output and working directories
os.makedirs(output_dir, exist_ok=True)
os.makedirs(log_dir, exist_ok=True)
os.makedirs(work_dir, exist_ok=True)
# Nipype config (logs and execution)
ncfg.update_config({
'logging': {
'log_directory': log_dir,
'log_to_file': True
},
'execution': {
'crashdump_dir': log_dir,
'crashfile_format': 'txt',
'get_linked_libs': False,
'stop_on_first_crash': opts.stop_on_first_crash or opts.work_dir is None,
},
'monitoring': {
'enabled': opts.resource_monitor,
'sample_frequency': '0.5',
'summary_append': True,
}
})
if opts.resource_monitor:
ncfg.enable_resource_monitor()
retval['return_code'] = 0
retval['plugin_settings'] = plugin_settings
retval['bids_dir'] = bids_dir
retval['output_dir'] = output_dir
retval['work_dir'] = work_dir
retval['subject_list'] = subject_list
retval['run_uuid'] = run_uuid
retval['workflow'] = None
# Called with reports only
if opts.reports_only:
logger.log(25, 'Running --reports-only on participants %s', ', '.join(subject_list))
if opts.run_uuid is not None:
run_uuid = opts.run_uuid
retval['return_code'] = generate_reports(subject_list, output_dir, work_dir, run_uuid)
return retval
# Build main workflow
logger.log(25, INIT_MSG(
version=__version__,
bids_dir=bids_dir,
subject_list=subject_list,
uuid=run_uuid)
)
template_out_grid = opts.template_resampling_grid
if opts.output_grid_reference is not None:
logger.warning(
'Option --output-grid-reference is deprecated, please use '
'--template-resampling-grid')
template_out_grid = template_out_grid or opts.output_grid_reference
if opts.debug:
logger.warning('Option --debug is deprecated and has no effect')
retval['workflow'] = init_fmriprep_wf(
subject_list=subject_list,
task_id=opts.task_id,
echo_idx=opts.echo_idx,
run_uuid=run_uuid,
ignore=opts.ignore,
debug=opts.sloppy,
low_mem=opts.low_mem,
anat_only=opts.anat_only,
longitudinal=opts.longitudinal,
t2s_coreg=opts.t2s_coreg,
omp_nthreads=omp_nthreads,
skull_strip_template=opts.skull_strip_template,
skull_strip_fixed_seed=opts.skull_strip_fixed_seed,
work_dir=work_dir,
output_dir=output_dir,
bids_dir=bids_dir,
freesurfer=opts.run_reconall,
output_spaces=output_spaces,
template=opts.template,
medial_surface_nan=opts.medial_surface_nan,
cifti_output=opts.cifti_output,
template_out_grid=template_out_grid,
hires=opts.hires,
use_bbr=opts.use_bbr,
bold2t1w_dof=opts.bold2t1w_dof,
fmap_bspline=opts.fmap_bspline,
fmap_demean=opts.fmap_no_demean,
use_syn=opts.use_syn_sdc,
force_syn=opts.force_syn,
use_aroma=opts.use_aroma,
aroma_melodic_dim=opts.aroma_melodic_dimensionality,
ignore_aroma_err=opts.ignore_aroma_denoising_errors,
)
retval['return_code'] = 0
logs_path = Path(output_dir) / 'fmriprep' / 'logs'
boilerplate = retval['workflow'].visit_desc()
if boilerplate:
(logs_path / 'CITATION.md').write_text(boilerplate)
logger.log(25, 'Works derived from this fMRIPrep execution should '
'include the following boilerplate:\n\n%s', boilerplate)
# Generate HTML file resolving citations
cmd = ['pandoc', '-s', '--bibliography',
pkgrf('fmriprep', 'data/boilerplate.bib'),
'--filter', 'pandoc-citeproc',
str(logs_path / 'CITATION.md'),
'-o', str(logs_path / 'CITATION.html')]
try:
check_call(cmd, timeout=10)
except (FileNotFoundError, CalledProcessError, TimeoutExpired):
logger.warning('Could not generate CITATION.html file:\n%s',
' '.join(cmd))
# Generate LaTex file resolving citations
cmd = ['pandoc', '-s', '--bibliography',
pkgrf('fmriprep', 'data/boilerplate.bib'),
'--natbib', str(logs_path / 'CITATION.md'),
'-o', str(logs_path / 'CITATION.tex')]
try:
check_call(cmd, timeout=10)
except (FileNotFoundError, CalledProcessError, TimeoutExpired):
logger.warning('Could not generate CITATION.tex file:\n%s',
' '.join(cmd))
else:
copyfile(pkgrf('fmriprep', 'data/boilerplate.bib'),
(logs_path / 'CITATION.bib'))
return retval
def build_workflow(opts, retval):
"""
Create the Nipype Workflow that supports the whole execution graph, given the inputs.
All the checks and the construction of the workflow are done
inside this function that has pickleable inputs and output
dictionary (``retval``) to allow isolation using a
``multiprocessing.Process`` that allows smriprep to enforce
a hard-limited memory-scope.
"""
from shutil import copyfile
from os import cpu_count
import uuid
from time import strftime
from subprocess import check_call, CalledProcessError, TimeoutExpired
from pkg_resources import resource_filename as pkgrf
import json
from bids import BIDSLayout
from nipype import logging, config as ncfg
from niworkflows.utils.bids import collect_participants
from ..__about__ import __version__
from ..workflows.base import init_smriprep_wf
logger = logging.getLogger("nipype.workflow")
INIT_MSG = """
Running sMRIPrep version {version}:
* BIDS dataset path: {bids_dir}.
* Participant list: {subject_list}.
* Run identifier: {uuid}.
{spaces}
""".format
# Set up some instrumental utilities
run_uuid = "%s_%s" % (strftime("%Y%m%d-%H%M%S"), uuid.uuid4())
# First check that bids_dir looks like a BIDS folder
bids_dir = opts.bids_dir.resolve()
layout = BIDSLayout(str(bids_dir), validate=False)
subject_list = collect_participants(
layout, participant_label=opts.participant_label)
bids_filters = (json.loads(opts.bids_filter_file.read_text())
if opts.bids_filter_file else None)
# Load base plugin_settings from file if --use-plugin
if opts.use_plugin is not None:
from yaml import load as loadyml
with open(opts.use_plugin) as f:
plugin_settings = loadyml(f)
plugin_settings.setdefault("plugin_args", {})
else:
# Defaults
plugin_settings = {
"plugin": "MultiProc",
"plugin_args": {
"raise_insufficient": False,
"maxtasksperchild": 1,
},
}
# Resource management options
# Note that we're making strong assumptions about valid plugin args
# This may need to be revisited if people try to use batch plugins
nprocs = plugin_settings["plugin_args"].get("n_procs")
# Permit overriding plugin config with specific CLI options
if nprocs is None or opts.nprocs is not None:
nprocs = opts.nprocs
if nprocs is None or nprocs < 1:
nprocs = cpu_count()
plugin_settings["plugin_args"]["n_procs"] = nprocs
if opts.mem_gb:
plugin_settings["plugin_args"]["memory_gb"] = opts.mem_gb
omp_nthreads = opts.omp_nthreads
if omp_nthreads == 0:
omp_nthreads = min(nprocs - 1 if nprocs > 1 else cpu_count(), 8)
if 1 < nprocs < omp_nthreads:
logger.warning(
"Per-process threads (--omp-nthreads=%d) exceed total "
"available CPUs (--nprocs/--ncpus=%d)",
omp_nthreads,
nprocs,
)
# Set up directories
output_dir = opts.output_dir.resolve()
log_dir = output_dir / "smriprep" / "logs"
work_dir = opts.work_dir.resolve()
# Check and create output and working directories
log_dir.mkdir(parents=True, exist_ok=True)
work_dir.mkdir(parents=True, exist_ok=True)
# Nipype config (logs and execution)
ncfg.update_config({
"logging": {
"log_directory": str(log_dir),
"log_to_file": True
},
"execution": {
"crashdump_dir": str(log_dir),
"crashfile_format": "txt",
"get_linked_libs": False,
"stop_on_first_crash": opts.stop_on_first_crash,
},
"monitoring": {
"enabled": opts.resource_monitor,
"sample_frequency": "0.5",
"summary_append": True,
},
})
if opts.resource_monitor:
ncfg.enable_resource_monitor()
retval["return_code"] = 0
retval["plugin_settings"] = plugin_settings
retval["bids_dir"] = str(bids_dir)
retval["output_dir"] = str(output_dir)
retval["work_dir"] = str(work_dir)
retval["subject_list"] = subject_list
retval["run_uuid"] = run_uuid
retval["workflow"] = None
# Called with reports only
if opts.reports_only:
from niworkflows.reports import generate_reports
logger.log(25, "Running --reports-only on participants %s",
", ".join(subject_list))
if opts.run_uuid is not None:
run_uuid = opts.run_uuid
retval["return_code"] = generate_reports(subject_list,
str(output_dir),
run_uuid,
packagename="smriprep")
return retval
output_spaces = opts.output_spaces
if not output_spaces.is_cached():
output_spaces.checkpoint()
logger.log(
25,
INIT_MSG(
version=__version__,
bids_dir=bids_dir,
subject_list=subject_list,
uuid=run_uuid,
spaces=output_spaces,
),
)
# Build main workflow
retval["workflow"] = init_smriprep_wf(
debug=opts.sloppy,
fast_track=opts.fast_track,
freesurfer=opts.run_reconall,
fs_subjects_dir=opts.fs_subjects_dir,
hires=opts.hires,
layout=layout,
longitudinal=opts.longitudinal,
low_mem=opts.low_mem,
omp_nthreads=omp_nthreads,
output_dir=str(output_dir),
run_uuid=run_uuid,
skull_strip_fixed_seed=opts.skull_strip_fixed_seed,
skull_strip_mode=opts.skull_strip_mode,
skull_strip_template=opts.skull_strip_template[0],
spaces=output_spaces,
subject_list=subject_list,
work_dir=str(work_dir),
bids_filters=bids_filters,
)
retval["return_code"] = 0
boilerplate = retval["workflow"].visit_desc()
(log_dir / "CITATION.md").write_text(boilerplate)
logger.log(
25,
"Works derived from this sMRIPrep execution should "
"include the following boilerplate:\n\n%s",
boilerplate,
)
# Generate HTML file resolving citations
cmd = [
"pandoc",
"-s",
"--bibliography",
pkgrf("smriprep", "data/boilerplate.bib"),
"--citeproc",
"--metadata",
'pagetitle="sMRIPrep citation boilerplate"',
str(log_dir / "CITATION.md"),
"-o",
str(log_dir / "CITATION.html"),
]
try:
check_call(cmd, timeout=10)
except (FileNotFoundError, CalledProcessError, TimeoutExpired):
logger.warning("Could not generate CITATION.html file:\n%s",
" ".join(cmd))
# Generate LaTex file resolving citations
cmd = [
"pandoc",
"-s",
"--bibliography",
pkgrf("smriprep", "data/boilerplate.bib"),
"--natbib",
str(log_dir / "CITATION.md"),
"-o",
str(log_dir / "CITATION.tex"),
]
try:
check_call(cmd, timeout=10)
except (FileNotFoundError, CalledProcessError, TimeoutExpired):
logger.warning("Could not generate CITATION.tex file:\n%s",
" ".join(cmd))
else:
copyfile(pkgrf("smriprep", "data/boilerplate.bib"),
str(log_dir / "CITATION.bib"))
return retval
def build_workflow(opts, retval):
from nipype import logging as nlogging, config as ncfg
from niworkflows.utils.bids import collect_participants
from niworkflows.reports import generate_reports
from ..__about__ import __version__
from time import strftime
import uuid
from ..workflows.base import init_base_wf
build_log = nlogging.getLogger('nipype.workflow')
INIT_MSG = """
# Running atlasTransform version {version}:
# * BIDS dataset path: {bids_dir}.
# * Participant list: {subject_list}.
# * Run identifier: {uuid}.
# """.format
pass
bids_dir = opts.bids_dir.resolve()
output_dir = opts.output_dir.resolve()
work_dir = opts.work_dir.resolve()
retval['return_code'] = 1
retval['workflow'] = None
retval['bids_dir'] = str(bids_dir)
retval['output_dir'] = str(output_dir)
retval['work_dir'] = str(work_dir)
if output_dir == bids_dir:
build_log.error(
'The selected output folder is the same as the input BIDS folder. '
'Please modify the output path (suggestion: %s).', bids_dir /
'derivatives' / ('atlasTransform-%s' % __version__.split('+')[0]))
retval['return_code'] = 1
return retval
# Set up some instrumental utilities
run_uuid = '%s_%s' % (strftime('%Y%m%d-%H%M%S'), uuid.uuid4())
retval['run_uuid'] = run_uuid
# First check that bids_dir looks like a BIDS folder
layout = BIDSLayout(str(bids_dir),
validate=False,
ignore=("code", "stimuli", "sourcedata", "models",
"derivatives", re.compile(r'^\.')))
subject_list = collect_participants(
layout, participant_label=opts.participant_label)
retval['subject_list'] = subject_list
# Load base plugin_settings from file if --use-plugin
if opts.use_plugin is not None:
from yaml import load as loadyml
with open(opts.use_plugin) as f:
plugin_settings = loadyml(f)
plugin_settings.setdefault('plugin_args', {})
else:
# Defaults
plugin_settings = {
'plugin': 'MultiProc',
'plugin_args': {
'raise_insufficient': False,
'maxtasksperchild': 1,
}
}
# Resource management options
# Note that we're making strong assumptions about valid plugin args
# This may need to be revisited if people try to use batch plugins
nthreads = plugin_settings['plugin_args'].get('n_procs')
# Permit overriding plugin config with specific CLI options
if nthreads is None or opts.nthreads is not None:
nthreads = opts.nthreads
if nthreads is None or nthreads < 1:
nthreads = cpu_count()
plugin_settings['plugin_args']['n_procs'] = nthreads
if opts.mem_mb:
plugin_settings['plugin_args']['memory_gb'] = opts.mem_mb / 1024
omp_nthreads = opts.omp_nthreads
if omp_nthreads == 0:
omp_nthreads = min(nthreads - 1 if nthreads > 1 else cpu_count(), 8)
if 1 < nthreads < omp_nthreads:
build_log.warning(
'Per-process threads (--omp-nthreads=%d) exceed total '
'threads (--nthreads/--n_cpus=%d)', omp_nthreads, nthreads)
retval['plugin_settings'] = plugin_settings
# Set up directories
log_dir = output_dir / 'atlasTransform' / 'logs'
# Check and create output and working directories
output_dir.mkdir(exist_ok=True, parents=True)
log_dir.mkdir(exist_ok=True, parents=True)
work_dir.mkdir(exist_ok=True, parents=True)
# Nipype config (logs and execution)
ncfg.update_config({
'logging': {
'log_directory': str(log_dir),
'log_to_file': True
},
'execution': {
'crashdump_dir': str(log_dir),
'crashfile_format': 'txt',
'get_linked_libs': False,
'stop_on_first_crash': opts.stop_on_first_crash,
},
'monitoring': {
'enabled': opts.resource_monitor,
'sample_frequency': '0.5',
'summary_append': True,
}
})
if opts.resource_monitor:
ncfg.enable_resource_monitor()
# Called with reports only
if opts.reports_only:
build_log.log(25, 'Running --reports-only on participants %s',
', '.join(subject_list))
if opts.run_uuid is not None:
run_uuid = opts.run_uuid
retval['run_uuid'] = run_uuid
retval['return_code'] = generate_reports(subject_list,
output_dir,
work_dir,
run_uuid,
packagename='atlasTransform')
return retval
# Build main workflow
build_log.log(
25,
INIT_MSG(version=__version__,
bids_dir=bids_dir,
subject_list=subject_list,
uuid=run_uuid))
retval['workflow'] = init_base_wf(
opts=opts,
layout=layout,
run_uuid=run_uuid,
subject_list=subject_list,
work_dir=str(work_dir),
output_dir=str(output_dir),
)
retval['return_code'] = 0
logs_path = Path(output_dir) / 'atlasTransform' / 'logs'
boilerplate = retval['workflow'].visit_desc()
if boilerplate:
citation_files = {
ext: logs_path / ('CITATION.%s' % ext)
for ext in ('bib', 'tex', 'md', 'html')
}
# To please git-annex users and also to guarantee consistency
# among different renderings of the same file, first remove any
# existing one
for citation_file in citation_files.values():
try:
citation_file.unlink()
except FileNotFoundError:
pass
citation_files['md'].write_text(boilerplate)
build_log.log(
25, 'Works derived from this atlasTransform execution should '
'include the following boilerplate:\n\n%s', boilerplate)
return retval
