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parser.py
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parser.py
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# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
"""Parser."""
import sys
from aslprep import config
def _build_parser():
"""Build parser object."""
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser
from functools import partial
from pathlib import Path
from niworkflows.utils.spaces import OutputReferencesAction, Reference
from packaging.version import Version
from aslprep.cli.version import check_latest, is_flagged
def _path_exists(path, parser):
"""Ensure a given path exists."""
if path is None or not Path(path).exists():
raise parser.error(f"Path does not exist: <{path}>.")
return Path(path).absolute()
def _is_file(path, parser):
"""Ensure a given path exists and it is a file."""
path = _path_exists(path, parser)
if not path.is_file():
raise parser.error(f"Path should point to a file (or symlink of file): <{path}>.")
return path
def _min_one(value, parser):
"""Ensure an argument is not lower than 1."""
value = int(value)
if value < 1:
raise parser.error("Argument can't be less than one.")
return value
def _to_gb(value):
scale = {"G": 1, "T": 10**3, "M": 1e-3, "K": 1e-6, "B": 1e-9}
digits = "".join([c for c in value if c.isdigit()])
units = value[len(digits) :] or "M"
return int(digits) * scale[units[0]]
def _drop_sub(value):
return value[4:] if value.startswith("sub-") else value
def _process_value(value):
import bids
if value is None:
return bids.layout.Query.NONE
elif value == "*":
return bids.layout.Query.ANY
else:
return value
def _filter_pybids_none_any(dct):
d = {}
for k, v in dct.items():
if isinstance(v, list):
d[k] = [_process_value(val) for val in v]
else:
d[k] = _process_value(v)
return d
def _bids_filter(value, parser):
from json import JSONDecodeError, loads
if value:
if Path(value).exists():
try:
return loads(Path(value).read_text(), object_hook=_filter_pybids_none_any)
except JSONDecodeError:
raise parser.error(f"JSON syntax error in: <{value}>.")
else:
raise parser.error(f"Path does not exist: <{value}>.")
verstr = f"ASLPrep v{config.environment.version}"
currentv = Version(config.environment.version)
is_release = not any((currentv.is_devrelease, currentv.is_prerelease, currentv.is_postrelease))
parser = ArgumentParser(
description=f"ASLPrep: ASL PREProcessing workflows v{config.environment.version}",
formatter_class=ArgumentDefaultsHelpFormatter,
)
PathExists = partial(_path_exists, parser=parser)
IsFile = partial(_is_file, parser=parser)
PositiveInt = partial(_min_one, parser=parser)
BIDSFilter = partial(_bids_filter, parser=parser)
# Arguments as specified by BIDS-Apps
# required, positional arguments
# IMPORTANT: they must go directly with the parser object
parser.add_argument(
"bids_dir",
action="store",
type=PathExists,
help=(
"the root folder of a BIDS valid dataset (sub-XXXXX folders should "
"be found at the top level in this folder)."
),
)
parser.add_argument(
"output_dir",
action="store",
type=Path,
help="the output path for the outcomes of preprocessing and visual reports",
)
parser.add_argument(
"analysis_level",
choices=["participant"],
help=(
'processing stage to be run, only "participant" in the case of '
"ASLPREP (see BIDS-Apps specification)."
),
)
# optional arguments
g_bids = parser.add_argument_group("Options for filtering BIDS queries")
g_bids.add_argument(
"--skip_bids_validation",
"--skip-bids-validation",
action="store_true",
default=False,
help="assume the input dataset is BIDS compliant and skip the validation",
)
g_bids.add_argument(
"--participant-label",
"--participant_label",
action="store",
nargs="+",
type=_drop_sub,
help=(
"A space delimited list of participant identifiers or a single identifier "
"(the sub- prefix can be removed)"
),
)
# Re-enable when option is actually implemented
# g_bids.add_argument('-s', '--session-id', action='store', default='single_session',
# help='select a specific session to be processed')
# Re-enable when option is actually implemented
# g_bids.add_argument('-r', '--run-id', action='store', default='single_run',
# help='select a specific run to be processed')
# g_bids.add_argument(
# "-t", "--task-id", action="store", help="select a specific task to be processed"
# )
g_bids.add_argument(
"--bids-filter-file",
dest="bids_filters",
action="store",
type=BIDSFilter,
metavar="FILE",
help=(
"A JSON file describing custom BIDS input filters using PyBIDS. "
"For further details, please check out "
"https://aslprep.readthedocs.io/en/"
f"{currentv.base_version if is_release else 'latest'}/faq.html#"
"how-do-I-select-only-certain-files-to-be-input-to-ASLPrep"
),
)
g_bids.add_argument(
"-d",
"--derivatives",
action="store",
metavar="PATH",
type=Path,
nargs="*",
help="Search PATH(s) for pre-computed derivatives.",
)
g_bids.add_argument(
"--bids-database-dir",
metavar="PATH",
type=Path,
help=(
"Path to a PyBIDS database folder, for faster indexing "
"(especially useful for large datasets). "
"Will be created if not present."
),
)
g_perfm = parser.add_argument_group("Options to handle performance")
g_perfm.add_argument(
"--nprocs",
"--nthreads",
"--n_cpus",
"--n-cpus",
dest="nprocs",
action="store",
type=PositiveInt,
help="maximum number of threads across all processes",
)
g_perfm.add_argument(
"--omp-nthreads",
action="store",
type=PositiveInt,
help="maximum number of threads per-process",
)
g_perfm.add_argument(
"--mem",
"--mem_mb",
"--mem-mb",
dest="memory_gb",
action="store",
type=_to_gb,
help="upper bound memory limit for ASLPrep processes",
)
g_perfm.add_argument(
"--low-mem",
action="store_true",
help="attempt to reduce memory usage (will increase disk usage in working directory)",
)
g_perfm.add_argument(
"--use-plugin",
"--nipype-plugin-file",
action="store",
metavar="FILE",
type=IsFile,
help="nipype plugin configuration file",
)
g_perfm.add_argument(
"--sloppy",
action="store_true",
default=False,
help="Use low-quality tools for speed - TESTING ONLY",
)
g_subset = parser.add_argument_group("Options for performing only a subset of the workflow")
g_subset.add_argument("--anat-only", action="store_true", help="run anatomical workflows only")
g_subset.add_argument(
"--level",
action="store",
default="full",
choices=["minimal", "resampling", "full"],
help=(
"Processing level; may be 'minimal' (nothing that can be recomputed), "
"'resampling' (recomputable targets that aid in resampling) "
"or 'full' (all target outputs). "
),
)
g_subset.add_argument(
"--boilerplate-only",
"--boilerplate_only",
action="store_true",
default=False,
help="generate boilerplate only",
)
g_subset.add_argument(
"--reports-only",
action="store_true",
default=False,
help=(
"only generate reports, don't run workflows. This will only rerun report "
"aggregation, not reportlet generation for specific nodes."
),
)
g_conf = parser.add_argument_group("Workflow configuration")
g_conf.add_argument(
"--ignore",
required=False,
action="store",
nargs="+",
default=[],
choices=["fieldmaps", "sbref", "t2w", "flair", "fmap-jacobian"],
help=(
"ignore selected aspects of the input dataset to disable corresponding "
"parts of the workflow (a space delimited list)"
),
)
g_conf.add_argument(
"--output-spaces",
nargs="*",
action=OutputReferencesAction,
help="""\
Standard and non-standard spaces to resample anatomical and functional images to. \
Standard spaces may be specified by the form \
``<SPACE>[:cohort-<label>][:res-<resolution>][...]``, where ``<SPACE>`` is \
a keyword designating a spatial reference, and may be followed by optional, \
colon-separated parameters. \
Non-standard spaces imply specific orientations and sampling grids. \
Important to note, the ``res-*`` modifier does not define the resolution used for \
the spatial normalization. To generate no ASL outputs, use this option without specifying \
any spatial references.""",
)
g_conf.add_argument(
"--longitudinal",
action="store_true",
help="treat dataset as longitudinal - may increase runtime",
)
g_conf.add_argument(
"--asl2t1w-init",
action="store",
default="register",
choices=["register", "header"],
help=(
'Either "register" (the default) to initialize volumes at center or "header" '
"to use the header information when coregistering ASL to T1w images."
),
)
g_conf.add_argument(
"--asl2t1w-dof",
action="store",
default=6,
choices=[6, 9, 12],
type=int,
help=(
"Degrees of freedom when registering ASL to T1w images. "
"6 degrees (rotation and translation) are used by default."
),
)
g_use_bbr = g_conf.add_mutually_exclusive_group()
g_use_bbr.add_argument(
"--force-bbr",
action="store_true",
dest="use_bbr",
default=False,
help="Always use boundary-based registration (no goodness-of-fit checks)",
)
g_use_bbr.add_argument(
"--force-no-bbr",
action="store_false",
dest="use_bbr",
default=None,
help="Do not use boundary-based registration (no goodness-of-fit checks)",
)
g_conf.add_argument(
"--dummy-scans",
required=False,
action="store",
default=None,
type=int,
help=(
"Number of non-steady-state volumes. "
"Note that this indicates the number of volumes, not the number of control-label "
"pairs in the ASL file."
),
)
g_conf.add_argument(
"--random-seed",
dest="_random_seed",
action="store",
type=int,
default=None,
help="Initialize the random seed for the workflow",
)
g_use_ge = g_conf.add_mutually_exclusive_group()
g_use_ge.add_argument(
"--force-ge",
action="store_true",
dest="use_ge",
default=None,
help="Always use boundary-based registration (no goodness-of-fit checks)",
)
g_use_ge.add_argument(
"--force-no-ge",
action="store_false",
dest="use_ge",
default=None,
help="Do not use boundary-based registration (no goodness-of-fit checks)",
)
g_conf.add_argument(
"--m0_scale",
required=False,
action="store",
default=1,
type=float,
help=(
"Relative scale between ASL and M0. "
"M0 scans are multiplied by m0_scale before calculating CBF. "
"It is important to note, however, that BIDS expects ASL and M0 data to scaled in "
"the raw dataset, so this parameter should only be used if your dataset does not "
"have pre-scaled data."
),
)
g_conf.add_argument(
"--smooth_kernel",
action="store",
default=5,
type=float,
help="Smoothing kernel for the M0 image(s)",
)
g_conf.add_argument(
"--scorescrub",
action="store_true",
default=False,
help="Apply Sudipto Dolui's algorithms for denoising CBF",
)
g_conf.add_argument(
"--basil",
action="store_true",
default=False,
help="FSL's CBF computation with spatial regularization and partial volume correction",
)
g_outputs = parser.add_argument_group("Options for modulating outputs")
g_outputs.add_argument(
"--medial-surface-nan",
required=False,
action="store_true",
default=False,
help=(
"Replace medial wall values with NaNs on functional GIFTI files. "
"Only performed for GIFTI files mapped to a freesurfer subject "
"(fsaverage or fsnative)."
),
)
g_conf.add_argument(
"--project-goodvoxels",
required=False,
action="store_true",
default=False,
help=(
"Exclude voxels whose timeseries have locally high coefficient of variation "
"from surface resampling. "
"Only performed for GIFTI files mapped to a freesurfer subject "
"(fsaverage or fsnative)."
),
)
g_outputs.add_argument(
"--md-only-boilerplate",
action="store_true",
default=False,
help="Skip generation of HTML and LaTeX formatted citation with pandoc",
)
g_outputs.add_argument(
"--cifti-output",
nargs="?",
const="91k",
default=False,
choices=("91k", "170k"),
type=str,
help=(
"Output preprocessed BOLD as a CIFTI dense timeseries. "
"Optionally, the number of grayordinate can be specified "
"(default is 91k, which equates to 2mm resolution)"
),
)
g_outputs.add_argument(
"--no-msm",
action="store_false",
dest="run_msmsulc",
help="Disable Multimodal Surface Matching surface registration.",
)
# ANTs options
g_ants = parser.add_argument_group("Specific options for ANTs registrations")
g_ants.add_argument(
"--skull-strip-template",
default="OASIS30ANTs",
type=Reference.from_string,
help="select a template for skull-stripping with antsBrainExtraction",
)
g_ants.add_argument(
"--skull-strip-fixed-seed",
action="store_true",
help=(
"do not use a random seed for skull-stripping - will ensure "
"run-to-run replicability when used with --omp-nthreads 1 and "
"matching --random-seed <int>"
),
)
g_ants.add_argument(
"--skull-strip-t1w",
action="store",
choices=("auto", "skip", "force"),
default="force",
help=(
"determiner for T1-weighted skull stripping ('force' ensures skull "
"stripping, 'skip' ignores skull stripping, and 'auto' applies brain extraction "
"based on the outcome of a heuristic to check whether the brain is already masked)."
),
)
# Fieldmap options
g_fmap = parser.add_argument_group("Specific options for handling fieldmaps")
g_fmap.add_argument(
"--fmap-bspline",
action="store_true",
default=False,
help="fit a B-Spline field using least-squares (experimental)",
)
g_fmap.add_argument(
"--fmap-no-demean",
action="store_false",
default=True,
help="do not remove median (within mask) from fieldmap",
)
# SyN-unwarp options
g_syn = parser.add_argument_group("Specific options for SyN distortion correction")
g_syn.add_argument(
"--use-syn-sdc",
action="store_true",
default=False,
help="EXPERIMENTAL: Use fieldmap-free distortion correction",
)
g_syn.add_argument(
"--force-syn",
action="store_true",
default=False,
help=(
"EXPERIMENTAL/TEMPORARY: Use SyN correction in addition to "
"fieldmap correction, if available"
),
)
# FreeSurfer options
g_fs = parser.add_argument_group("Specific options for FreeSurfer preprocessing")
g_fs.add_argument(
"--fs-license-file",
metavar="FILE",
type=IsFile,
help=(
"Path to FreeSurfer license key file. Get it (for free) by registering "
"at https://surfer.nmr.mgh.harvard.edu/registration.html"
),
)
g_fs.add_argument(
"--fs-subjects-dir",
metavar="PATH",
type=Path,
help=(
"Path to existing FreeSurfer subjects directory to reuse. "
"(default: OUTPUT_DIR/freesurfer)"
),
)
g_fs.add_argument(
"--no-submm-recon",
action="store_false",
dest="hires",
help="Disable sub-millimeter (hires) reconstruction",
)
g_fs.add_argument(
"--fs-no-reconall",
action="store_false",
dest="run_reconall",
help="Disable FreeSurfer surface preprocessing.",
)
g_other = parser.add_argument_group("Other options")
g_other.add_argument("--version", action="version", version=verstr)
g_other.add_argument(
"-v",
"--verbose",
dest="verbose_count",
action="count",
default=0,
help="increases log verbosity for each occurrence, debug level is -vvv",
)
g_other.add_argument(
"-w",
"--work-dir",
action="store",
type=Path,
default=Path("work").absolute(),
help="path where intermediate results should be stored",
)
g_other.add_argument(
"--clean-workdir",
action="store_true",
default=False,
help=(
"Clears working directory of contents. Use of this flag is not"
"recommended when running concurrent processes of aslprep."
),
)
g_other.add_argument(
"--resource-monitor",
action="store_true",
default=False,
help="enable Nipype's resource monitoring to keep track of memory and CPU usage",
)
g_other.add_argument(
"--config-file",
action="store",
metavar="FILE",
help=(
"Use pre-generated configuration file. Values in file will be overridden "
"by command-line arguments."
),
)
g_other.add_argument(
"--write-graph",
action="store_true",
default=False,
help="Write workflow graph.",
)
g_other.add_argument(
"--stop-on-first-crash",
action="store_true",
default=False,
help="Force stopping on first crash, even if a work directory was specified.",
)
g_other.add_argument(
"--notrack",
action="store_true",
default=False,
help=(
"Opt-out of sending tracking information of this run to "
"the aslprep developers. This information helps to "
"improve aslprep and provides an indicator of real "
"world usage crucial for obtaining funding."
),
)
g_other.add_argument(
"--debug",
action="store",
nargs="+",
choices=config.DEBUG_MODES + ("all",),
help="Debug mode(s) to enable. 'all' is alias for all available modes.",
)
latest = check_latest()
if latest is not None and currentv < latest:
print(
f"""\
You are using aslprep-{currentv}, and a newer version of aslprep is available: {latest}.
Please check out our documentation about how and when to upgrade:
https://aslprep.readthedocs.io/en/latest/faq.html#upgrading""",
file=sys.stderr,
)
_blist = is_flagged()
if _blist[0]:
_reason = _blist[1] or "unknown"
print(
f"""\
WARNING: Version {config.environment.version} of aslprep (current) has been FLAGGED
(reason: {_reason}).
That means some severe flaw was found in it and we strongly
discourage its usage.""",
file=sys.stderr,
)
return parser
def parse_args(args=None, namespace=None):
"""Parse args and run further checks on the command line."""
import logging
from niworkflows.utils.spaces import Reference, SpatialReferences
parser = _build_parser()
opts = parser.parse_args(args, namespace)
if opts.config_file:
skip = {} if opts.reports_only else {"execution": ("run_uuid",)}
config.load(opts.config_file, skip=skip, init=False)
config.loggers.cli.info(f"Loaded previous configuration file {opts.config_file}")
config.execution.log_level = int(max(25 - 5 * opts.verbose_count, logging.DEBUG))
config.from_dict(vars(opts), init=["nipype"])
# Initialize --output-spaces if not defined
if config.execution.output_spaces is None:
config.execution.output_spaces = SpatialReferences(
[Reference("MNI152NLin2009cAsym", {"res": "native"})]
)
# Retrieve logging level
build_log = config.loggers.cli
# Load base plugin_settings from file if --use-plugin
if opts.use_plugin is not None:
import yaml
with open(opts.use_plugin) as f:
plugin_settings = yaml.load(f, Loader=yaml.FullLoader)
_plugin = plugin_settings.get("plugin")
if _plugin:
config.nipype.plugin = _plugin
config.nipype.plugin_args = plugin_settings.get("plugin_args", {})
config.nipype.nprocs = opts.nprocs or config.nipype.plugin_args.get(
"n_procs", config.nipype.nprocs
)
# 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
if 1 < config.nipype.nprocs < config.nipype.omp_nthreads:
build_log.warning(
f"Per-process threads (--omp-nthreads={config.nipype.omp_nthreads}) exceed "
f"total threads (--nthreads/--n_cpus={config.nipype.nprocs})"
)
# Inform the user about the risk of using brain-extracted images
if config.workflow.skull_strip_t1w == "auto":
build_log.warning(
"""\
Option ``--skull-strip-t1w`` was set to 'auto'. A heuristic will be \
applied to determine whether the input T1w image(s) have already been skull-stripped.
If that were the case, brain extraction and INU correction will be skipped for those T1w \
inputs. Please, BEWARE OF THE RISKS TO THE CONSISTENCY of results when using varying \
processing workflows across participants. To determine whether a participant has been run \
through the shortcut pipeline (meaning, brain extraction was skipped), please check the \
citation boilerplate. When reporting results with varying pipelines, please make sure you \
mention this particular variant of aslprep listing the participants for which it was \
applied."""
)
bids_dir = config.execution.bids_dir
output_dir = config.execution.output_dir
work_dir = config.execution.work_dir
version = config.environment.version
if config.execution.fs_subjects_dir is None:
config.execution.fs_subjects_dir = output_dir / "sourcedata" / "freesurfer"
if config.execution.aslprep_dir is None:
config.execution.aslprep_dir = output_dir
# Wipe out existing work_dir
if opts.clean_workdir and work_dir.exists():
from niworkflows.utils.misc import clean_directory
build_log.info(f"Clearing previous aslprep working directory: {work_dir}")
if not clean_directory(work_dir):
build_log.warning(f"Could not clear all contents of working directory: {work_dir}")
# Update the config with an empty dict to trigger initialization of all config
# sections (we used `init=False` above).
# This must be done after cleaning the work directory, or we could delete an
# open SQLite database
config.from_dict({})
# Ensure input and output folders are not the same
if output_dir == bids_dir:
rec_path = bids_dir / "derivatives" / f"aslprep-{version.split('+')[0]}"
parser.error(
"The selected output folder is the same as the input BIDS folder. "
f"Please modify the output path (suggestion: {rec_path})."
)
if bids_dir in work_dir.parents:
parser.error(
"The selected working directory is a subdirectory of the input BIDS folder. "
"Please modify the output path."
)
# Validate inputs
if not opts.skip_bids_validation:
from aslprep.utils.bids import validate_input_dir
build_log.info(
"Making sure the input data is BIDS compliant (warnings can be ignored in most cases)."
)
validate_input_dir(config.environment.exec_env, opts.bids_dir, opts.participant_label)
# Setup directories
config.execution.log_dir = config.execution.aslprep_dir / "logs"
# Check and create output and working directories
config.execution.log_dir.mkdir(exist_ok=True, parents=True)
output_dir.mkdir(exist_ok=True, parents=True)
work_dir.mkdir(exist_ok=True, parents=True)
# Force initialization of the BIDSLayout
config.execution.init()
all_subjects = config.execution.layout.get_subjects()
if config.execution.participant_label is None:
config.execution.participant_label = all_subjects
participant_label = set(config.execution.participant_label)
missing_subjects = participant_label - set(all_subjects)
if missing_subjects:
parser.error(
"One or more participant labels were not found in the BIDS directory: "
f"{', '.join(missing_subjects)}."
)
config.execution.participant_label = sorted(participant_label)
config.workflow.skull_strip_template = config.workflow.skull_strip_template[0]