def _run_interface(self, runtime):
import bids
from bids.analysis import auto_model
models = self.inputs.model
if not isinstance(models, list):
# model is not yet standardized, so validate=False
layout = bids.BIDSLayout(self.inputs.bids_dir, validate=False)
if not isdefined(models):
models = layout.get(suffix='smdl', return_type='file')
if not models:
raise ValueError("No models found")
elif models == 'default':
models = auto_model(layout)
models = [_ensure_model(m) for m in models]
if self.inputs.selectors:
# This is almost certainly incorrect
models = [
model for model in models
if all(val in model['input'].get(key, [val])
for key, val in self.inputs.selectors.items())
]
self._results['model_spec'] = models
return runtime
def _run_interface(self, runtime):
import bids
from bids.analysis import auto_model
models = self.inputs.model
if not isinstance(models, list):
database_path = self.inputs.database_path
layout = bids.BIDSLayout.load(database_path=database_path)
if not isdefined(models):
# model is not yet standardized, so validate=False
# Ignore all subject directories and .git/ and .datalad/ directories
small_layout = bids.BIDSLayout(
layout.root, derivatives=[d.root for d in layout.derivatives.values()],
validate=False,
ignore=[re.compile(r'sub-'),
re.compile(r'\.(git|datalad)')])
# PyBIDS can double up, so find unique models
models = list(set(small_layout.get(suffix='smdl', return_type='file')))
if not models:
raise ValueError("No models found")
elif models == 'default':
models = auto_model(layout)
models = [_ensure_model(m) for m in models]
if self.inputs.selectors:
# This is almost certainly incorrect
models = [model for model in models
if all(val in model['input'].get(key, [val])
for key, val in self.inputs.selectors.items())]
self._results['model_spec'] = models
return runtime
def _run_interface(self, runtime):
models = self.inputs.model
if not isinstance(models, list):
layout = gb.BIDSLayout(self.inputs.bids_dir)
if not isdefined(models):
models = layout.get(type='model')
if not models:
raise ValueError("No models found")
elif models == 'default':
models = ba.auto_model(layout)
models = [_ensure_model(m) for m in models]
if self.inputs.selectors:
# This is almost certainly incorrect
models = [
model for model in models
if all(val in model['input'].get(key, [val])
for key, val in self.inputs.selectors.items())
]
self._results['model_spec'] = models
return runtime
def run_fitlins(argv=None):
warnings.showwarning = _warn_redirect
opts = get_parser().parse_args(argv)
if opts.debug:
logger.setLevel(logging.DEBUG)
subject_list = None
if opts.participant_label is not None:
subject_list = bids.collect_participants(
opts.bids_dir, participant_label=opts.participant_label)
ncpus = opts.n_cpus
if ncpus < 1:
ncpus = cpu_count()
plugin_settings = {
'plugin': 'MultiProc',
'plugin_args': {
'n_procs': ncpus,
'raise_insufficient': False,
'maxtasksperchild': 1,
}
}
# Build main workflow
logger.log(25, INIT_MSG(
version=__version__,
subject_list=subject_list)
)
model = default_path(opts.model, opts.bids_dir, 'model.json')
if opts.model in (None, 'default') and not op.exists(model):
model = 'default'
preproc_dir = default_path(opts.preproc_dir,
op.join(opts.bids_dir, 'derivatives'),
'fmriprep')
if not op.exists(preproc_dir):
preproc_dir = default_path(opts.preproc_dir, opts.output_dir, 'fmriprep')
if not op.exists(preproc_dir):
raise RuntimeError("Preprocessed data could not be found")
pipeline_name = 'fitlins'
if opts.derivative_label:
pipeline_name += '_' + opts.derivative_label
deriv_dir = op.join(opts.output_dir, pipeline_name)
os.makedirs(deriv_dir, exist_ok=True)
bids.write_derivative_description(opts.bids_dir, deriv_dir)
work_dir = mkdtemp() if opts.work_dir is None else opts.work_dir
fitlins_wf = init_fitlins_wf(
opts.bids_dir, preproc_dir, deriv_dir, opts.space, model=model,
participants=subject_list, base_dir=work_dir,
include_pattern=opts.include, exclude_pattern=opts.exclude
)
retcode = 0
try:
fitlins_wf.run(**plugin_settings)
except Exception:
retcode = 1
layout = BIDSLayout(opts.bids_dir)
models = auto_model(layout) if model == 'default' else [model]
run_context = {'version': __version__,
'command': ' '.join(sys.argv),
'timestamp': time.strftime('%Y-%m-%d %H:%M:%S %z'),
}
for model in models:
analysis = Analysis(layout, model=model)
report_dicts = parse_directory(deriv_dir, work_dir, analysis)
write_report('unknown', report_dicts, run_context, deriv_dir)
return retcode
def run_fitlins(argv=None):
import re
from nipype import logging as nlogging
warnings.showwarning = _warn_redirect
opts = get_parser().parse_args(argv)
force_index = [
# If entry looks like `/<pattern>/`, treat `<pattern>` as a regex
re.compile(ign[1:-1]) if (ign[0], ign[-1]) == ('/', '/') else ign
# Iterate over empty tuple if undefined
for ign in opts.force_index or ()
]
ignore = [
# If entry looks like `/<pattern>/`, treat `<pattern>` as a regex
re.compile(ign[1:-1]) if (ign[0], ign[-1]) == ('/', '/') else ign
# Iterate over empty tuple if undefined
for ign in opts.ignore or ()
]
log_level = 25 + 5 * (opts.quiet - opts.verbose)
logger.setLevel(log_level)
nlogging.getLogger('nipype.workflow').setLevel(log_level)
nlogging.getLogger('nipype.interface').setLevel(log_level)
nlogging.getLogger('nipype.utils').setLevel(log_level)
if not opts.space:
# make it an explicit None
opts.space = None
if not opts.desc_label:
# make it an explicit None
opts.desc_label = None
ncpus = opts.n_cpus
if ncpus < 1:
ncpus = cpu_count()
plugin_settings = {
'plugin': 'MultiProc',
'plugin_args': {
'n_procs': ncpus,
'raise_insufficient': False,
'maxtasksperchild': 1,
}
}
if opts.mem_gb:
plugin_settings['plugin_args']['memory_gb'] = opts.mem_gb
model = default_path(opts.model, opts.bids_dir, 'model-default_smdl.json')
if opts.model in (None, 'default') and not op.exists(model):
model = 'default'
derivatives = True if not opts.derivatives else opts.derivatives
# Need this when specifying args directly (i.e. neuroscout)
# god bless neuroscout, but let's make it work for others!
if isinstance(derivatives, list) and len(derivatives) == 1:
# WRONG AND EVIL to those who have spaces in their paths... bad bad practice
# TODO - fix neuroscout
derivatives = derivatives[0].split(" ")
pipeline_name = 'fitlins'
if opts.derivative_label:
pipeline_name += '_' + opts.derivative_label
deriv_dir = op.join(opts.output_dir, pipeline_name)
os.makedirs(deriv_dir, exist_ok=True)
bids.write_derivative_description(opts.bids_dir, deriv_dir)
work_dir = mkdtemp() if opts.work_dir is None else opts.work_dir
# Go ahead and initialize the layout database
if opts.database_path is None:
database_path = Path(work_dir) / 'dbcache'
reset_database = True
else:
database_path = opts.database_path
reset_database = False
layout = BIDSLayout(opts.bids_dir,
derivatives=derivatives,
ignore=ignore,
force_index=force_index,
database_path=database_path,
reset_database=reset_database)
subject_list = None
if opts.participant_label is not None:
subject_list = bids.collect_participants(
layout, participant_label=opts.participant_label)
# Build main workflow
logger.log(25, INIT_MSG(version=__version__, subject_list=subject_list))
fitlins_wf = init_fitlins_wf(
database_path,
deriv_dir,
analysis_level=opts.analysis_level,
model=model,
space=opts.space,
desc=opts.desc_label,
participants=subject_list,
base_dir=work_dir,
smoothing=opts.smoothing,
drop_missing=opts.drop_missing,
)
fitlins_wf.config = deepcopy(config.get_fitlins_config()._sections)
if opts.work_dir:
# dump crashes in working directory (non /tmp)
fitlins_wf.config['execution']['crashdump_dir'] = opts.work_dir
retcode = 0
if not opts.reports_only:
try:
fitlins_wf.run(**plugin_settings)
except Exception:
retcode = 1
models = auto_model(layout) if model == 'default' else [model]
run_context = {
'version': __version__,
'command': ' '.join(sys.argv),
'timestamp': time.strftime('%Y-%m-%d %H:%M:%S %z'),
}
selectors = {'desc': opts.desc_label, 'space': opts.space}
if subject_list is not None:
selectors['subject'] = subject_list
for model in models:
analysis = Analysis(layout, model=model)
analysis.setup(**selectors)
report_dict = build_report_dict(deriv_dir, work_dir, analysis)
write_full_report(report_dict, run_context, deriv_dir)
return retcode
def run_fitlins(argv=None):
warnings.showwarning = _warn_redirect
opts = get_parser().parse_args(argv)
if opts.debug:
logger.setLevel(logging.DEBUG)
if not opts.space:
# make it an explicit None
opts.space = None
subject_list = None
if opts.participant_label is not None:
subject_list = bids.collect_participants(
opts.bids_dir, participant_label=opts.participant_label)
ncpus = opts.n_cpus
if ncpus < 1:
ncpus = cpu_count()
plugin_settings = {
'plugin': 'MultiProc',
'plugin_args': {
'n_procs': ncpus,
'raise_insufficient': False,
'maxtasksperchild': 1,
}
}
# Build main workflow
logger.log(25, INIT_MSG(
version=__version__,
subject_list=subject_list)
)
model = default_path(opts.model, opts.bids_dir, 'model-default_smdl.json')
if opts.model in (None, 'default') and not op.exists(model):
model = 'default'
derivatives = True if not opts.derivatives else opts.derivatives
# Need this when specifying args directly (i.e. neuroscout)
# god bless neuroscout, but let's make it work for others!
if isinstance(derivatives, list) and len(derivatives) == 1:
# WRONG AND EVIL to those who have spaces in their paths... bad bad practice
# TODO - fix neuroscout
derivatives = derivatives[0].split(" ")
pipeline_name = 'fitlins'
if opts.derivative_label:
pipeline_name += '_' + opts.derivative_label
deriv_dir = op.join(opts.output_dir, pipeline_name)
os.makedirs(deriv_dir, exist_ok=True)
bids.write_derivative_description(opts.bids_dir, deriv_dir)
work_dir = mkdtemp() if opts.work_dir is None else opts.work_dir
fitlins_wf = init_fitlins_wf(
opts.bids_dir, derivatives, deriv_dir,
analysis_level=opts.analysis_level, model=model,
space=opts.space, desc=opts.desc_label,
participants=subject_list, base_dir=work_dir,
force_index=opts.force_index, ignore=opts.ignore,
smoothing=opts.smoothing,
)
if opts.work_dir:
# dump crashes in working directory (non /tmp)
fitlins_wf.config['execution']['crashdump_dir'] = opts.work_dir
# easy to read crashfiles
fitlins_wf.config['execution']['crashfile_format'] = 'txt'
retcode = 0
if not opts.reports_only:
try:
fitlins_wf.run(**plugin_settings)
except Exception:
retcode = 1
layout = BIDSLayout(opts.bids_dir, derivatives=derivatives)
models = auto_model(layout) if model == 'default' else [model]
run_context = {'version': __version__,
'command': ' '.join(sys.argv),
'timestamp': time.strftime('%Y-%m-%d %H:%M:%S %z'),
}
selectors = {'desc': opts.desc_label}
if opts.space is not None:
selectors['space'] = opts.space
if subject_list is not None:
selectors['subject'] = subject_list
for model in models:
analysis = Analysis(layout, model=model)
analysis.setup(**selectors)
report_dict = build_report_dict(deriv_dir, work_dir, analysis)
write_full_report(report_dict, run_context, deriv_dir)
return retcode