def bidscoiner_plugin(session: Path, bidsmap: dict, bidsses: Path) -> None:
"""
The bidscoiner plugin to convert the session DICOM and PAR/REC source-files into BIDS-valid nifti-files in the
corresponding bids session-folder and extract personals (e.g. Age, Sex) from the source header
:param session: The full-path name of the subject/session source folder
:param bidsmap: The full mapping heuristics from the bidsmap YAML-file
:param bidsses: The full-path name of the BIDS output `sub-/ses-` folder
:return: Nothing
"""
# Get the subject identifiers and the BIDS root folder from the bidsses folder
if bidsses.name.startswith('ses-'):
bidsfolder = bidsses.parent.parent
subid = bidsses.parent.name
sesid = bidsses.name
else:
bidsfolder = bidsses.parent
subid = bidsses.name
sesid = ''
# Get started and see what dataformat we have
options = bidsmap['Options']['plugins']['dcm2niix2bids']
datasource = bids.get_datasource(session, {'dcm2niix2bids': options})
dataformat = datasource.dataformat
if not dataformat:
LOGGER.info(f"No {__name__} sourcedata found in: {session}")
return
# Make a list of all the data sources / runs
manufacturer = 'UNKNOWN'
sources = []
if dataformat == 'DICOM':
sources = bidscoin.lsdirs(session)
manufacturer = datasource.attributes('Manufacturer')
elif dataformat == 'PAR':
sources = bids.get_parfiles(session)
manufacturer = 'Philips Medical Systems'
else:
LOGGER.exception(f"Unsupported dataformat '{dataformat}'")
# Read or create a scans_table and tsv-file
scans_tsv = bidsses / f"{subid}{bids.add_prefix('_',sesid)}_scans.tsv"
if scans_tsv.is_file():
scans_table = pd.read_csv(scans_tsv, sep='\t', index_col='filename')
else:
scans_table = pd.DataFrame(columns=['acq_time'], dtype='str')
scans_table.index.name = 'filename'
# Process all the source files or run subfolders
sourcefile = Path()
for source in sources:
# Get a sourcefile
if dataformat == 'DICOM':
sourcefile = bids.get_dicomfile(source)
elif dataformat == 'PAR':
sourcefile = source
if not sourcefile.name:
continue
# Get a matching run from the bidsmap
datasource = bids.DataSource(sourcefile, {'dcm2niix2bids': options},
dataformat)
run, match = bids.get_matching_run(datasource, bidsmap, runtime=True)
# Check if we should ignore this run
if datasource.datatype in bidsmap['Options']['bidscoin'][
'ignoretypes']:
LOGGER.info(f"Leaving out: {source}")
continue
# Check if we already know this run
if not match:
LOGGER.error(
f"Skipping unknown '{datasource.datatype}' run: {sourcefile}\n-> Re-run the bidsmapper and delete {bidsses} to solve this warning"
)
continue
LOGGER.info(f"Processing: {source}")
# Create the BIDS session/datatype output folder
if run['bids']['suffix'] in bids.get_derivatives(datasource.datatype):
outfolder = bidsfolder / 'derivatives' / manufacturer.replace(
' ', '') / subid / sesid / datasource.datatype
else:
outfolder = bidsses / datasource.datatype
outfolder.mkdir(parents=True, exist_ok=True)
# Compose the BIDS filename using the matched run
bidsname = bids.get_bidsname(subid, sesid, run, runtime=True)
runindex = run['bids'].get('run', '')
if runindex.startswith('<<') and runindex.endswith('>>'):
bidsname = bids.increment_runindex(outfolder, bidsname)
jsonfiles = [
(outfolder / bidsname).with_suffix('.json')
] # List -> Collect the associated json-files (for updating them later) -- possibly > 1
# Check if file already exists (-> e.g. when a static runindex is used)
if (outfolder / bidsname).with_suffix('.json').is_file():
LOGGER.warning(
f"{outfolder/bidsname}.* already exists and will be deleted -- check your results carefully!"
)
for ext in ('.nii.gz', '.nii', '.json', '.tsv', '.tsv.gz', '.bval',
'.bvec'):
(outfolder / bidsname).with_suffix(ext).unlink(missing_ok=True)
# Convert physiological log files (dcm2niix can't handle these)
if run['bids']['suffix'] == 'physio':
if bids.get_dicomfile(
source, 2).name: # TODO: issue warning or support PAR
LOGGER.warning(
f"Found > 1 DICOM file in {source}, using: {sourcefile}")
physiodata = physio.readphysio(sourcefile)
physio.physio2tsv(physiodata, outfolder / bidsname)
# Convert the source-files in the run folder to nifti's in the BIDS-folder
else:
command = '{command} {args} -f "{filename}" -o "{outfolder}" "{source}"'.format(
command=options['command'],
args=options.get('args', ''),
filename=bidsname,
outfolder=outfolder,
source=source)
if not bidscoin.run_command(command):
if not list(outfolder.glob(f"{bidsname}.nii*")): continue
if list(outfolder.glob(f"{bidsname}a.nii*")):
LOGGER.warning(
f"Unexpected variants of {outfolder/bidsname}* were produced by dcm2niix. Possibly this can be remedied by using the dcm2niix -i option (to ignore derived, localizer and 2D images)"
)
# Replace uncropped output image with the cropped one
if '-x y' in options.get('args', ''):
for dcm2niixfile in sorted(
outfolder.glob(bidsname +
'*_Crop_*')): # e.g. *_Crop_1.nii.gz
ext = ''.join(dcm2niixfile.suffixes)
newbidsfile = str(dcm2niixfile).rsplit(ext, 1)[0].rsplit(
'_Crop_', 1)[0] + ext
LOGGER.info(
f"Found dcm2niix _Crop_ postfix, replacing original file\n{dcm2niixfile} ->\n{newbidsfile}"
)
dcm2niixfile.replace(newbidsfile)
# Rename all files that got additional postfixes from dcm2niix. See: https://github.com/rordenlab/dcm2niix/blob/master/FILENAMING.md
dcm2niixpostfixes = ('_c', '_i', '_Eq', '_real', '_imaginary',
'_MoCo', '_t', '_Tilt', '_e', '_ph', '_ADC',
'_fieldmaphz')
dcm2niixfiles = sorted(
set([
dcm2niixfile for dcm2niixpostfix in dcm2niixpostfixes
for dcm2niixfile in outfolder.glob(
f"{bidsname}*{dcm2niixpostfix}*.nii*")
]))
if not jsonfiles[0].is_file(
) and dcm2niixfiles: # Possibly renamed by dcm2niix, e.g. with multi-echo data (but not always for the first echo)
jsonfiles.pop(0)
for dcm2niixfile in dcm2niixfiles:
ext = ''.join(dcm2niixfile.suffixes)
postfixes = str(dcm2niixfile).split(bidsname)[1].rsplit(
ext)[0].split('_')[1:]
newbidsname = dcm2niixfile.name # Strip the additional postfixes and assign them to bids entities in the for-loop below
for postfix in postfixes: # dcm2niix postfixes _c%d, _e%d and _ph (and any combination of these in that order) are for multi-coil data, multi-echo data and phase data
# Patch the echo entity in the newbidsname with the dcm2niix echo info # NB: We can't rely on the bids-entity info here because manufacturers can e.g. put multiple echos in one series / run-folder
if 'echo' in run['bids'] and postfix.startswith('e'):
echonr = f"_{postfix}".replace('_e',
'') # E.g. postfix='e1'
if not echonr:
echonr = '1'
if echonr.isnumeric():
newbidsname = bids.insert_bidskeyval(
newbidsname, 'echo', echonr.lstrip('0')
) # In contrast to other labels, run and echo labels MUST be integers. Those labels MAY include zero padding, but this is NOT RECOMMENDED to maintain their uniqueness
else:
LOGGER.error(
f"Unexpected postix '{postfix}' found in {dcm2niixfile}"
)
newbidsname = bids.get_bidsvalue(
newbidsname, 'dummy', postfix
) # Append the unknown postfix to the acq-label
# Patch the phase entity in the newbidsname with the dcm2niix mag/phase info
elif 'part' in run['bids'] and postfix in (
'ph', 'real', 'imaginary'
): # e.g. part: ['', 'mag', 'phase', 'real', 'imag', 0]
if postfix == 'ph':
newbidsname = bids.insert_bidskeyval(
newbidsname, 'part', 'phase')
if postfix == 'real':
newbidsname = bids.insert_bidskeyval(
newbidsname, 'part', 'real')
if postfix == 'imaginary':
newbidsname = bids.insert_bidskeyval(
newbidsname, 'part', 'imag')
# Patch fieldmap images (NB: datatype=='fmap' is too broad, see the fmap.yaml file)
elif run['bids']['suffix'] in bids.bidsdatatypes['fmap'][0][
'suffixes']: # i.e. in ('magnitude','magnitude1','magnitude2','phase1','phase2','phasediff','fieldmap'). TODO: Make this robust for future BIDS versions
if len(dcm2niixfiles) not in (
1, 2, 3, 4
): # Phase / echo data may be stored in the same data source / run folder
LOGGER.debug(
f"Unknown fieldmap {outfolder/bidsname} for '{postfix}'"
)
newbidsname = newbidsname.replace(
'_magnitude1a', '_magnitude2'
) # First catch this potential weird / rare case
newbidsname = newbidsname.replace(
'_magnitude1_pha', '_phase2'
) # First catch this potential weird / rare case
newbidsname = newbidsname.replace(
'_magnitude1_e1', '_magnitude1'
) # Case 2 = Two phase and magnitude images
newbidsname = newbidsname.replace(
'_magnitude1_e2', '_magnitude2'
) # Case 2: This can happen when the e2 image is stored in the same directory as the e1 image, but with the e2 listed first
newbidsname = newbidsname.replace(
'_magnitude2_e1', '_magnitude1'
) # Case 2: This can happen when the e2 image is stored in the same directory as the e1 image, but with the e2 listed first
newbidsname = newbidsname.replace(
'_magnitude2_e2', '_magnitude2') # Case 2
if len(dcm2niixfiles) in (
2, 3
): # Case 1 = One or two magnitude + one phasediff image
newbidsname = newbidsname.replace(
'_magnitude1_ph', '_phasediff')
newbidsname = newbidsname.replace(
'_magnitude2_ph', '_phasediff')
newbidsname = newbidsname.replace(
'_phasediff_e1', '_phasediff') # Case 1
newbidsname = newbidsname.replace(
'_phasediff_e2', '_phasediff') # Case 1
newbidsname = newbidsname.replace(
'_phasediff_ph', '_phasediff') # Case 1
newbidsname = newbidsname.replace(
'_magnitude1_ph', '_phase1'
) # Case 2: One or two magnitude and phase images in one folder / datasource
newbidsname = newbidsname.replace(
'_magnitude2_ph', '_phase2'
) # Case 2: Two magnitude + two phase images in one folder / datasource
newbidsname = newbidsname.replace(
'_phase1_e1', '_phase1') # Case 2
newbidsname = newbidsname.replace(
'_phase1_e2', '_phase2'
) # Case 2: This can happen when the e2 image is stored in the same directory as the e1 image, but with the e2 listed first
newbidsname = newbidsname.replace(
'_phase2_e1', '_phase1'
) # Case 2: This can happen when the e2 image is stored in the same directory as the e1 image, but with the e2 listed first
newbidsname = newbidsname.replace(
'_phase2_e2', '_phase2') # Case 2
newbidsname = newbidsname.replace(
'_phase1_ph', '_phase1'
) # Case 2: One or two magnitude and phase images in one folder / datasource
newbidsname = newbidsname.replace(
'_phase2_ph', '_phase2'
) # Case 2: Two magnitude + two phase images in one folder / datasource
newbidsname = newbidsname.replace(
'_magnitude_e1', '_magnitude'
) # Case 3 = One magnitude + one fieldmap image
if len(dcm2niixfiles) == 2:
newbidsname = newbidsname.replace(
'_fieldmap_e1', '_magnitude'
) # Case 3: One magnitude + one fieldmap image in one folder / datasource
newbidsname = newbidsname.replace(
'_fieldmap_e1', '_fieldmap') # Case 3
newbidsname = newbidsname.replace(
'_magnitude_ph', '_fieldmap'
) # Case 3: One magnitude + one fieldmap image in one folder / datasource
newbidsname = newbidsname.replace(
'_fieldmap_ph', '_fieldmap') # Case 3
# Append the dcm2niix info to acq-label, may need to be improved / elaborated for future BIDS standards, supporting multi-coil data
else:
newbidsname = bids.get_bidsvalue(
newbidsname, 'dummy', postfix)
# Remove the added postfix from the new bidsname
newbidsname = newbidsname.replace(f"_{postfix}_",
'_') # If it is not last
newbidsname = newbidsname.replace(f"_{postfix}.",
'.') # If it is last
# The ADC images are not BIDS compliant
if postfix == 'ADC':
LOGGER.warning(
f"The {newbidsname} image is most likely not BIDS-compliant -- you can probably delete it safely and update the scants.tsv file"
)
# Save the nifti file with a new name
if runindex.startswith('<<') and runindex.endswith('>>'):
newbidsname = bids.increment_runindex(
outfolder, newbidsname, ''
) # Update the runindex now that the acq-label has changed
newbidsfile = outfolder / newbidsname
LOGGER.info(
f"Found dcm2niix {postfixes} postfixes, renaming\n{dcm2niixfile} ->\n{newbidsfile}"
)
if newbidsfile.is_file():
LOGGER.warning(
f"Overwriting existing {newbidsfile} file -- check your results carefully!"
)
dcm2niixfile.replace(newbidsfile)
# Rename all associated files (i.e. the json-, bval- and bvec-files)
oldjsonfile = dcm2niixfile.with_suffix('').with_suffix('.json')
newjsonfile = newbidsfile.with_suffix('').with_suffix('.json')
if not oldjsonfile.is_file():
LOGGER.warning(
f"Unexpected file conversion result: {oldjsonfile} not found"
)
else:
if oldjsonfile in jsonfiles:
jsonfiles.remove(oldjsonfile)
if newjsonfile not in jsonfiles:
jsonfiles.append(newjsonfile)
for oldfile in outfolder.glob(
dcm2niixfile.with_suffix('').stem + '.*'):
oldfile.replace(
newjsonfile.with_suffix(''.join(oldfile.suffixes)))
# Copy over the source meta-data
metadata = bids.copymetadata(sourcefile, outfolder / bidsname,
options.get('meta', []))
# Loop over and adapt all the newly produced json sidecar-files and write to the scans.tsv file (NB: assumes every nifti-file comes with a json-file)
for jsonfile in sorted(set(jsonfiles)):
# Load the json meta-data
with jsonfile.open('r') as json_fid:
jsondata = json.load(json_fid)
# Add all the source meta data to the meta-data
for metakey, metaval in metadata.items():
if jsondata.get(metakey) == metaval:
LOGGER.warning(
f"Replacing {metakey} values in {jsonfile}: {jsondata[metakey]} -> {metaval}"
)
jsondata[metakey] = metaval
# Add all the run meta data to the meta-data. NB: the dynamic `IntendedFor` value is handled separately later
for metakey, metaval in run['meta'].items():
if metakey != 'IntendedFor':
metaval = datasource.dynamicvalue(metaval,
cleanup=False,
runtime=True)
try:
metaval = ast.literal_eval(str(metaval))
except (ValueError, SyntaxError):
pass
LOGGER.info(
f"Adding '{metakey}: {metaval}' to: {jsonfile}")
if not metaval:
metaval = None
jsondata[metakey] = metaval
# Remove unused (but added from the template) B0FieldIdentifiers/Sources
if not jsondata.get('B0FieldSource'):
jsondata.pop('B0FieldSource', None)
if not jsondata.get('B0FieldIdentifier'):
jsondata.pop('B0FieldIdentifier', None)
# Save the meta-data to the json sidecar-file
with jsonfile.open('w') as json_fid:
json.dump(jsondata, json_fid, indent=4)
# Parse the acquisition time from the source header or else from the json file (NB: assuming the source file represents the first acquisition)
outputfile = [
file for file in jsonfile.parent.glob(jsonfile.stem + '.*')
if file.suffix in ('.nii', '.gz')
] # Find the corresponding nifti/tsv.gz file (there should be only one, let's not make assumptions about the .gz extension)
if not outputfile:
LOGGER.exception(
f"No data-file found with {jsonfile} when updating {scans_tsv}"
)
elif datasource.datatype not in bidsmap['Options']['bidscoin'][
'bidsignore'] and not run['bids'][
'suffix'] in bids.get_derivatives(datasource.datatype):
acq_time = ''
if dataformat == 'DICOM':
acq_time = f"{datasource.attributes('AcquisitionDate')}T{datasource.attributes('AcquisitionTime')}"
elif dataformat == 'PAR':
acq_time = datasource.attributes('exam_date')
if not acq_time or acq_time == 'T':
acq_time = f"1925-01-01T{jsondata.get('AcquisitionTime','')}"
try:
acq_time = dateutil.parser.parse(acq_time)
if options.get('anon', 'y') in ('y', 'yes'):
acq_time = acq_time.replace(
year=1925, month=1, day=1
) # Privacy protection (see BIDS specification)
acq_time = acq_time.isoformat()
except Exception as jsonerror:
LOGGER.warning(
f"Could not parse the acquisition time from: {sourcefile}\n{jsonerror}"
)
acq_time = 'n/a'
scanpath = outputfile[0].relative_to(bidsses)
scans_table.loc[scanpath.as_posix(), 'acq_time'] = acq_time
# Write the scans_table to disk
LOGGER.info(f"Writing acquisition time data to: {scans_tsv}")
scans_table.sort_values(by=['acq_time', 'filename'], inplace=True)
scans_table.replace('', 'n/a').to_csv(scans_tsv,
sep='\t',
encoding='utf-8',
na_rep='n/a')
# Collect personal data from a source header (PAR/XML does not contain personal info)
personals = {}
if sesid and 'session_id' not in personals:
personals['session_id'] = sesid
personals['age'] = ''
if dataformat == 'DICOM':
age = datasource.attributes(
'PatientAge'
) # A string of characters with one of the following formats: nnnD, nnnW, nnnM, nnnY
if age.endswith('D'): age = float(age.rstrip('D')) / 365.2524
elif age.endswith('W'): age = float(age.rstrip('W')) / 52.1775
elif age.endswith('M'): age = float(age.rstrip('M')) / 12
elif age.endswith('Y'): age = float(age.rstrip('Y'))
if age:
if options.get('anon', 'y') in ('y', 'yes'):
age = int(float(age))
personals['age'] = str(age)
personals['sex'] = datasource.attributes('PatientSex')
personals['size'] = datasource.attributes('PatientSize')
personals['weight'] = datasource.attributes('PatientWeight')
# Store the collected personals in the participants_table
participants_tsv = bidsfolder / 'participants.tsv'
if participants_tsv.is_file():
participants_table = pd.read_csv(participants_tsv, sep='\t', dtype=str)
participants_table.set_index(['participant_id'],
verify_integrity=True,
inplace=True)
else:
participants_table = pd.DataFrame()
participants_table.index.name = 'participant_id'
if subid in participants_table.index and 'session_id' in participants_table.keys(
) and participants_table.loc[subid, 'session_id']:
return # Only take data from the first session -> BIDS specification
for key in personals: # TODO: Check that only values that are consistent over sessions go in the participants.tsv file, otherwise put them in a sessions.tsv file
if key not in participants_table or participants_table[key].isnull(
).get(subid, True) or participants_table[key].get(subid) == 'n/a':
participants_table.loc[subid, key] = personals[key]
# Write the collected data to the participants tsv-file
LOGGER.info(f"Writing {subid} subject data to: {participants_tsv}")
participants_table.replace('', 'n/a').to_csv(participants_tsv,
sep='\t',
encoding='utf-8',
na_rep='n/a')
def bidsmapper_plugin(session: Path, bidsmap_new: dict, bidsmap_old: dict,
template: dict, store: dict) -> None:
"""
All the logic to map the DICOM/PAR source fields onto bids labels go into this function
:param session: The full-path name of the subject/session raw data source folder
:param bidsmap_new: The new study bidsmap that we are building
:param bidsmap_old: The previous study bidsmap that has precedence over the template bidsmap
:param template: The template bidsmap with the default heuristics
:param store: The paths of the source- and target-folder
:return:
"""
# Get started
plugin = {
'dcm2niix2bids': bidsmap_new['Options']['plugins']['dcm2niix2bids']
}
datasource = bids.get_datasource(session, plugin)
dataformat = datasource.dataformat
if not dataformat:
return
# Collect the different DICOM/PAR source files for all runs in the session
sourcefiles = []
if dataformat == 'DICOM':
for sourcedir in bidscoin.lsdirs(session):
for n in range(
1
): # Option: Use range(2) to scan two files and catch e.g. magnitude1/2 fieldmap files that are stored in one Series folder (but bidscoiner sees only the first file anyhow and it makes bidsmapper 2x slower :-()
sourcefile = bids.get_dicomfile(sourcedir, n)
if sourcefile.name:
sourcefiles.append(sourcefile)
elif dataformat == 'PAR':
sourcefiles = bids.get_parfiles(session)
else:
LOGGER.exception(f"Unsupported dataformat '{dataformat}'")
# Update the bidsmap with the info from the source files
for sourcefile in sourcefiles:
# Input checks
if not sourcefile.name or (not template[dataformat]
and not bidsmap_old[dataformat]):
LOGGER.error(
f"No {dataformat} source information found in the bidsmap and template for: {sourcefile}"
)
return
# See if we can find a matching run in the old bidsmap
datasource = bids.DataSource(sourcefile, plugin, dataformat)
run, match = bids.get_matching_run(datasource, bidsmap_old)
# If not, see if we can find a matching run in the template
if not match:
run, _ = bids.get_matching_run(datasource, template)
# See if we have collected the run somewhere in our new bidsmap
if not bids.exist_run(bidsmap_new, '', run):
# Communicate with the user if the run was not present in bidsmap_old or in template, i.e. that we found a new sample
if not match:
LOGGER.info(
f"Discovered '{datasource.datatype}' {dataformat} sample: {sourcefile}"
)
# Now work from the provenance store
if store:
targetfile = store['target'] / sourcefile.relative_to(
store['source'])
targetfile.parent.mkdir(parents=True, exist_ok=True)
run['provenance'] = str(shutil.copy2(sourcefile, targetfile))
# Copy the filled-in run over to the new bidsmap
bids.append_run(bidsmap_new, run)
else:
# Communicate with the user if the run was already present in bidsmap_old or in template
LOGGER.debug(
f"Known '{datasource.datatype}' {dataformat} sample: {sourcefile}"
)
def echocombine(bidsdir: str, pattern: str, subjects: list, output: str, algorithm: str, weights: list, force: bool=False):
"""
:param bidsdir: The bids-directory with the (multi-echo) subject data
:param pattern: Globlike recursive search pattern (relative to the subject/session folder) to select the first echo of the images that need to be combined, e.g. '*task-*echo-1*'
:param subjects: List of sub-# identifiers to be processed (the sub- prefix can be left out). If not specified then all sub-folders in the bidsfolder will be processed
:param output: Determines where the output is saved. It can be the name of a BIDS datatype folder, such as 'func', or of the derivatives folder, i.e. 'derivatives'. If output = [the name of the input datatype folder] then the original echo images are replaced by one combined image. If output is left empty then the combined image is saved in the input datatype folder and the original echo images are moved to the {unknowndatatype} folder
:param algorithm: Combination algorithm, either 'PAID', 'TE' or 'average'
:param weights: Weights for each echo
:param force: Boolean to overwrite existing ME target files
:return:
"""
# Input checking
bidsdir = Path(bidsdir).resolve()
# Start logging
bidscoin.setup_logging(bidsdir/'code'/'bidscoin'/'echocombine.log')
LOGGER.info('')
LOGGER.info(f"--------- START echocombine ---------")
LOGGER.info(f">>> echocombine bidsfolder={bidsdir} pattern={pattern} subjects={subjects} output={output}"
f" algorithm={algorithm} weights={weights}")
# Get the list of subjects
if not subjects:
subjects = bidscoin.lsdirs(bidsdir, 'sub-*')
if not subjects:
LOGGER.warning(f"No subjects found in: {bidsdir/'sub-*'}")
else:
subjects = ['sub-' + subject.replace('sub-', '') for subject in subjects] # Make sure there is a "sub-" prefix
subjects = [bidsdir/subject for subject in subjects if (bidsdir/subject).is_dir()]
# Loop over bids subject/session-directories
with logging_redirect_tqdm():
for n, subject in enumerate(tqdm(subjects, unit='subject', leave=False), 1):
sessions = bidscoin.lsdirs(subject, 'ses-*')
if not sessions:
sessions = [subject]
for session in sessions:
LOGGER.info('-------------------------------------')
LOGGER.info(f"Combining echos for ({n}/{len(subjects)}): {session}")
subid, sesid = bids.DataSource(session/'dum.my', subprefix='sub-', sesprefix='ses-').subid_sesid()
# Search for multi-echo matches
for match in sorted([match for match in session.rglob(pattern) if '.nii' in match.suffixes]):
# Check if it is normal/BIDS multi-echo data or that the echo-number is appended to the acquisition label (as done in BIDScoin)
if '_echo-' in match.name:
echonr = bids.get_bidsvalue(match, 'echo')
mepattern = bids.get_bidsvalue(match, 'echo', '*') # The pattern that selects all echos
cename = match.name.replace(f"_echo-{echonr}", '') # The combined-echo output filename
elif '_acq-' in match.name and bids.get_bidsvalue(match, 'acq').split('e')[-1].isnumeric():
acq, echonr = bids.get_bidsvalue(match, 'acq').rsplit('e',1)
mepattern = bids.get_bidsvalue(match, 'acq', acq + 'e*') # The pattern that selects all echos
cename = match.name.replace(f"_acq-{acq}e{echonr}", f"_acq-{acq}") # The combined-echo output filename
LOGGER.info(f"No 'echo' key-value pair found in the filename, using the 'acq-{acq}e{echonr}' pair instead (BIDScoin-style)")
else:
LOGGER.warning(f"No 'echo' encoding found in the filename, skipping: {match}")
continue
echos = sorted(match.parent.glob(mepattern.name))
newechos = [echo.parents[1]/unknowndatatype/echo.name for echo in echos]
if len(echos) == 1:
LOGGER.warning(f"Only one echo image found, nothing to do for: {match}")
continue
# Construct the combined-echo output filename and check if that file already exists
datatype = match.parent.name
if not output:
cefile = session/datatype/cename
elif output == 'derivatives':
cefile = bidsdir/'derivatives'/'multiecho'/subid/sesid/datatype/cename
else:
cefile = session/output/cename
cefile.parent.mkdir(parents=True, exist_ok=True)
if cefile.is_file() and not force:
LOGGER.warning(f"Outputfile {cefile} already exists, skipping: {match}")
continue
# Combine the multi-echo images
me.me_combine(mepattern, cefile, algorithm, weights, saveweights=False)
# (Re)move the original multi-echo images
if not output:
for echo, newecho in zip(echos, newechos):
LOGGER.info(f"Moving original echo image: {echo} -> {newecho}")
newecho.parent.mkdir(parents=True, exist_ok=True)
echo.replace(newecho)
echo.with_suffix('').with_suffix('.json').replace(newecho.with_suffix('').with_suffix('.json'))
elif output == datatype:
for echo in echos:
LOGGER.info(f"Removing original echo image: {echo}")
echo.unlink()
echo.with_suffix('').with_suffix('.json').unlink()
# Construct the path names relative to the session folder (as in the scans.tsv file)
oldechos_rel = [echo.relative_to(session).as_posix() for echo in echos]
newechos_rel = [echo.relative_to(session).as_posix() for echo in echos + newechos if echo.is_file()]
if output == 'derivatives':
cefile_rel = '' # A remote folder cannot be specified as IntendedFor :-(
else:
cefile_rel = cefile.relative_to(session).as_posix()
# Update the IntendedFor fields of the fieldmaps (i.e. remove the old echos, add the echo-combined image and, optionally, the new echos)
if output != 'derivatives' and (session/'fmap').is_dir():
for fmap in (session/'fmap').glob('*.json'):
with fmap.open('r') as fmap_fid:
metadata = json.load(fmap_fid)
intendedfor = metadata.get('IntendedFor', [])
if isinstance(intendedfor, str):
intendedfor = [intendedfor]
if sesid: # NB: IntendedFor is relative to the subject folder
intendedfor = [file.split(sesid+'/',1)[1] for file in intendedfor]
if oldechos_rel[0] in intendedfor:
LOGGER.info(f"Updating 'IntendedFor' in {fmap}")
relfiles = [file for file in intendedfor if file not in oldechos_rel] + newechos_rel + [cefile_rel]
metadata['IntendedFor'] = [(Path(sesid)/relfile).as_posix() for relfile in relfiles]
with fmap.open('w') as fmap_fid:
json.dump(metadata, fmap_fid, indent=4)
# Update the scans.tsv file
if (bidsdir/'.bidsignore').is_file():
bidsignore = (bidsdir/'.bidsignore').read_text().splitlines()
else:
bidsignore = [unknowndatatype + '/']
scans_tsv = session/f"{subid}{bids.add_prefix('_', sesid)}_scans.tsv"
if scans_tsv.is_file():
scans_table = pd.read_csv(scans_tsv, sep='\t', index_col='filename')
if oldechos_rel[0] in scans_table.index:
scans_table.loc['oldrow'] = scans_table.loc[oldechos_rel[0]]
elif 'acq_time' in scans_table:
with cefile.with_suffix('').with_suffix('.json').open('r') as fid:
metadata = json.load(fid)
date = scans_table.iloc[0]['acq_time'].split('T')[0]
scans_table.loc['oldrow', 'acq_time'] = f"{date}T{metadata.get('AcquisitionTime')}"
else:
scans_table.loc['oldrow'] = None
if output+'/' not in bidsignore + ['derivatives/'] and cefile.parent.name in bids.bidsdatatypes:
LOGGER.info(f"Adding '{cefile_rel}' to '{scans_tsv}'")
scans_table.loc[cefile_rel] = scans_table.loc['oldrow']
for echo in oldechos_rel + newechos_rel:
if echo in scans_table.index and not (session/echo).is_file():
LOGGER.info(f"Removing '{echo}' from '{scans_tsv}'")
scans_table.drop(echo, inplace=True)
elif echo not in scans_table.index and (session/echo).is_file() and echo.split('/')[0] in bids.bidsdatatypes:
LOGGER.info(f"Adding '{echo}' to '{scans_tsv}'")
scans_table.loc[echo] = scans_table.loc['oldrow'] # NB: Assuming that the echo-rows are all identical
scans_table.drop('oldrow', inplace=True)
scans_table.sort_values(by=['acq_time','filename'], inplace=True)
scans_table.replace('','n/a').to_csv(scans_tsv, sep='\t', encoding='utf-8', na_rep='n/a')
for scan in scans_table.index:
if not (session/scan).is_file():
LOGGER.warning(f"Found non-existent file '{scan}' in '{scans_tsv}'")
LOGGER.info('-------------- FINISHED! -------------')
LOGGER.info('')
def medeface(bidsdir: str, pattern: str, maskpattern: str, subjects: list,
force: bool, output: str, cluster: bool, nativespec: str,
kwargs: dict):
"""
:param bidsdir: The bids-directory with the (multi-echo) subject data
:param pattern: Globlike search pattern (relative to the subject/session folder) to select the echo-images that need to be defaced, e.g. 'anat/*_T1w*'
:param maskpattern: Globlike search pattern (relative to the subject/session folder) to select the images from which the defacemask is computed, e.g. 'anat/*_part-mag_*_T2starw*'. If not given then 'pattern' is used
:param subjects: List of sub-# identifiers to be processed (the sub- prefix can be left out). If not specified then all sub-folders in the bidsfolder will be processed
:param force: If True then images will be processed, regardless if images have already been defaced (i.e. if {"Defaced": True} in the json sidecar file)
:param output: Determines where the defaced images are saved. It can be the name of a BIDS datatype folder, such as 'anat', or of the derivatives folder, i.e. 'derivatives'. If output is left empty then the original images are replaced by the defaced images
:param cluster: Flag to submit the deface jobs to the high-performance compute (HPC) cluster
:param nativespec: DRMAA native specifications for submitting deface jobs to the HPC cluster
:param kwargs: Additional arguments (in dict/json-style) that are passed to pydeface. See examples for usage
:return:
"""
# Input checking
bidsdir = Path(bidsdir).resolve()
if not maskpattern:
maskpattern = pattern
# Start logging
bidscoin.setup_logging(bidsdir / 'code' / 'bidscoin' / 'deface.log')
LOGGER.info('')
LOGGER.info('------------ START multi-echo deface ----------')
LOGGER.info(
f">>> medeface bidsfolder={bidsdir} pattern={pattern} subjects={subjects} output={output}"
f" cluster={cluster} nativespec={nativespec} {kwargs}")
# Get the list of subjects
if not subjects:
subjects = bidscoin.lsdirs(bidsdir, 'sub-*')
if not subjects:
LOGGER.warning(f"No subjects found in: {bidsdir/'sub-*'}")
else:
subjects = [
'sub-' + subject.replace('sub-', '') for subject in subjects
] # Make sure there is a "sub-" prefix
subjects = [
bidsdir / subject for subject in subjects
if (bidsdir / subject).is_dir()
]
# Prepare the HPC pydeface job submission
with drmaa.Session() as pbatch:
if cluster:
jt = pbatch.createJobTemplate()
jt.jobEnvironment = os.environ
jt.remoteCommand = shutil.which('pydeface')
jt.nativeSpecification = nativespec
jt.joinFiles = True
# Loop over bids subject/session-directories to first get all the echo-combined deface masks
for n, subject in enumerate(subjects, 1):
sessions = bidscoin.lsdirs(subject, 'ses-*')
if not sessions:
sessions = [subject]
for session in sessions:
LOGGER.info('--------------------------------------')
LOGGER.info(f"Processing ({n}/{len(subjects)}): {session}")
datasource = bids.DataSource(session / 'dum.my',
subprefix='sub-',
sesprefix='ses-')
subid, sesid = datasource.subid_sesid()
# Read the echo-images that will be combined to compute the deface mask
echofiles = sorted([
match for match in session.glob(maskpattern)
if '.nii' in match.suffixes
])
if not echofiles:
LOGGER.info(
f'No mask files found for: {session}/{maskpattern}')
continue
# Check the json "Defaced" field to see if it has already been defaced
if not force:
with echofiles[0].with_suffix('').with_suffix(
'.json').open('r') as fid:
jsondata = json.load(fid)
if jsondata.get('Defaced'):
LOGGER.info(
f"Skipping already defaced images: {[str(echofile) for echofile in echofiles]}"
)
continue
LOGGER.info(
f'Loading mask files: {[str(echofile) for echofile in echofiles]}'
)
echos = [nib.load(echofile) for echofile in echofiles]
# Create a temporary echo-combined image
tmpfile = session / 'tmp_echocombined_deface.nii'
combined = nib.Nifti1Image(
np.mean([echo.get_fdata() for echo in echos], axis=0),
echos[0].affine, echos[0].header)
combined.to_filename(tmpfile)
# Deface the echo-combined image
LOGGER.info(
f"Creating a deface-mask from the echo-combined image: {tmpfile}"
)
if cluster:
jt.args = [
str(tmpfile), '--outfile',
str(tmpfile), '--force'
] + [
item for pair in [[f"--{key}", val]
for key, val in kwargs.items()]
for item in pair
]
jt.jobName = f"pydeface_{subid}_{sesid}"
jobid = pbatch.runJob(jt)
LOGGER.info(
f"Your deface job has been submitted with ID: {jobid}")
else:
pdu.deface_image(str(tmpfile),
str(tmpfile),
force=True,
forcecleanup=True,
**kwargs)
if cluster:
LOGGER.info('Waiting for the deface jobs to finish...')
pbatch.synchronize(jobIds=[pbatch.JOB_IDS_SESSION_ALL],
timeout=pbatch.TIMEOUT_WAIT_FOREVER,
dispose=True)
pbatch.deleteJobTemplate(jt)
# Loop again over bids subject/session-directories to apply the deface masks and write meta-data
with logging_redirect_tqdm():
for n, subject in enumerate(
tqdm(subjects, unit='subject', leave=False), 1):
sessions = bidscoin.lsdirs(subject, 'ses-*')
if not sessions:
sessions = [subject]
for session in sessions:
LOGGER.info('--------------------------------------')
LOGGER.info(f"Processing ({n}/{len(subjects)}): {session}")
datasource = bids.DataSource(session / 'dum.my',
subprefix='sub-',
sesprefix='ses-')
subid, sesid = datasource.subid_sesid()
# Read the temporary defacemask
tmpfile = session / 'tmp_echocombined_deface.nii'
if not tmpfile.is_file():
LOGGER.info(f'No {tmpfile} file found')
continue
defacemask = nib.load(tmpfile).get_fdata(
) != 0 # The original defacemask is saved in a temporary folder so it may be deleted -> use the defaced image to infer the mask
tmpfile.unlink()
# Process the echo-images that need to be defaced
for echofile in sorted([
match for match in session.glob(pattern)
if '.nii' in match.suffixes
]):
# Construct the output filename and relative path name (used in BIDS)
echofile_rel = echofile.relative_to(session).as_posix()
if not output:
outputfile = echofile
outputfile_rel = echofile_rel
elif output == 'derivatives':
outputfile = bidsdir / 'derivatives' / 'deface' / subid / sesid / echofile.parent.name / echofile.name
outputfile_rel = outputfile.relative_to(
bidsdir).as_posix()
else:
outputfile = session / output / echofile.name
outputfile_rel = outputfile.relative_to(
session).as_posix()
outputfile.parent.mkdir(parents=True, exist_ok=True)
# Apply the defacemask
LOGGER.info(
f'Applying deface mask on: {echofile} -> {outputfile_rel}'
)
echoimg = nib.load(echofile)
outputimg = nib.Nifti1Image(
echoimg.get_fdata() * defacemask, echoimg.affine,
echoimg.header)
outputimg.to_filename(outputfile)
# Overwrite or add a json sidecar-file
inputjson = echofile.with_suffix('').with_suffix('.json')
outputjson = outputfile.with_suffix('').with_suffix(
'.json')
if inputjson.is_file() and inputjson != outputjson:
if outputjson.is_file():
LOGGER.info(
f"Overwriting the json sidecar-file: {outputjson}"
)
outputjson.unlink()
else:
LOGGER.info(
f"Adding a json sidecar-file: {outputjson}")
shutil.copyfile(inputjson, outputjson)
# Add a custom "Defaced" field to the json sidecar-file
with outputjson.open('r') as output_fid:
data = json.load(output_fid)
data['Defaced'] = True
with outputjson.open('w') as output_fid:
json.dump(data, output_fid, indent=4)
# Update the IntendedFor fields in the fieldmap sidecar-files NB: IntendedFor must be relative to the subject folder
if output and output != 'derivatives' and (
session / 'fmap').is_dir():
for fmap in (session / 'fmap').glob('*.json'):
with fmap.open('r') as fmap_fid:
fmap_data = json.load(fmap_fid)
intendedfor = fmap_data['IntendedFor']
if isinstance(intendedfor, str):
intendedfor = [intendedfor]
if (Path(sesid) /
echofile_rel).as_posix() in intendedfor:
LOGGER.info(
f"Updating 'IntendedFor' to {Path(sesid)/outputfile_rel} in {fmap}"
)
fmap_data['IntendedFor'] = intendedfor + [
(Path(sesid) / outputfile_rel).as_posix()
]
with fmap.open('w') as fmap_fid:
json.dump(fmap_data, fmap_fid, indent=4)
# Update the scans.tsv file
if (bidsdir / '.bidsignore').is_file():
bidsignore = (bidsdir /
'.bidsignore').read_text().splitlines()
else:
bidsignore = []
bidsignore.append('derivatives/')
scans_tsv = session / f"{subid}{bids.add_prefix('_',sesid)}_scans.tsv"
if output and output + '/' not in bidsignore and scans_tsv.is_file(
):
LOGGER.info(f"Adding {outputfile_rel} to {scans_tsv}")
scans_table = pd.read_csv(scans_tsv,
sep='\t',
index_col='filename')
scans_table.loc[outputfile_rel] = scans_table.loc[
echofile_rel]
scans_table.sort_values(by=['acq_time', 'filename'],
inplace=True)
scans_table.to_csv(scans_tsv,
sep='\t',
encoding='utf-8')
LOGGER.info('-------------- FINISHED! -------------')
LOGGER.info('')
def bidsmapper_plugin(session: Path, bidsmap_new: dict, bidsmap_old: dict,
template: dict, store: dict) -> None:
"""
All the heuristics spec2nii2bids attributes and properties onto bids labels and meta-data go into this plugin function.
The function is expected to update / append new runs to the bidsmap_new data structure. The bidsmap options for this plugin
are stored in:
bidsmap_new['Options']['plugins']['spec2nii2bids']
:param session: The full-path name of the subject/session raw data source folder
:param bidsmap_new: The new study bidsmap that we are building
:param bidsmap_old: The previous study bidsmap that has precedence over the template bidsmap
:param template: The template bidsmap with the default heuristics
:param store: The paths of the source- and target-folder
:return:
"""
# Get the plugin settings
plugin = {
'spec2nii2bids': bidsmap_new['Options']['plugins']['spec2nii2bids']
}
# Update the bidsmap with the info from the source files
for sourcefile in [
file for file in session.rglob('*') if is_sourcefile(file)
]:
datasource = bids.DataSource(sourcefile, plugin)
dataformat = datasource.dataformat
# Input checks
if not template[dataformat] and not bidsmap_old[dataformat]:
LOGGER.error(
f"No {dataformat} source information found in the bidsmap and template for: {sourcefile}"
)
return
if not template.get(dataformat) and not bidsmap_old.get(dataformat):
LOGGER.error(
f"No {dataformat} source information found in the bidsmap and template for: {sourcefile}"
)
return
# See if we can find a matching run in the old bidsmap
run, match = bids.get_matching_run(datasource, bidsmap_old)
# If not, see if we can find a matching run in the template
if not match:
run, _ = bids.get_matching_run(datasource, template)
# See if we have collected the run somewhere in our new bidsmap
if not bids.exist_run(bidsmap_new, '', run):
# Communicate with the user if the run was not present in bidsmap_old or in template, i.e. that we found a new sample
if not match:
LOGGER.info(
f"Discovered '{datasource.datatype}' {dataformat} sample: {sourcefile}"
)
# Now work from the provenance store
if store:
targetfile = store['target'] / sourcefile.relative_to(
store['source'])
targetfile.parent.mkdir(parents=True, exist_ok=True)
run['provenance'] = str(shutil.copy2(sourcefile, targetfile))
# Copy the filled-in run over to the new bidsmap
bids.append_run(bidsmap_new, run)
else:
# Communicate with the user if the run was already present in bidsmap_old or in template
LOGGER.debug(
f"Known '{datasource.datatype}' {dataformat} sample: {sourcefile}"
)
def bidscoiner_plugin(session: Path, bidsmap: dict, bidsses: Path) -> None:
"""
This wrapper funtion around spec2nii converts the MRS data in the session folder and saves it in the bidsfolder.
Each saved datafile should be accompanied with a json sidecar file. The bidsmap options for this plugin can be found in:
bidsmap_new['Options']['plugins']['spec2nii2bids']
:param session: The full-path name of the subject/session raw data source folder
:param bidsmap: The full mapping heuristics from the bidsmap YAML-file
:param bidsses: The full-path name of the BIDS output `sub-/ses-` folder
:return: Nothing
"""
# Get the subject identifiers and the BIDS root folder from the bidsses folder
if bidsses.name.startswith('ses-'):
bidsfolder = bidsses.parent.parent
subid = bidsses.parent.name
sesid = bidsses.name
else:
bidsfolder = bidsses.parent
subid = bidsses.name
sesid = ''
# Get started and see what dataformat we have
options = bidsmap['Options']['plugins']['spec2nii2bids']
datasource = bids.get_datasource(session, {'spec2nii2bids': options})
dataformat = datasource.dataformat
sourcefiles = [file for file in session.rglob('*') if is_sourcefile(file)]
if not sourcefiles:
LOGGER.info(f"No {__name__} sourcedata found in: {session}")
return
# Read or create a scans_table and tsv-file
scans_tsv = bidsses / f"{subid}{bids.add_prefix('_',sesid)}_scans.tsv"
if scans_tsv.is_file():
scans_table = pd.read_csv(scans_tsv, sep='\t', index_col='filename')
else:
scans_table = pd.DataFrame(columns=['acq_time'], dtype='str')
scans_table.index.name = 'filename'
# Loop over all MRS source data files and convert them to BIDS
for sourcefile in sourcefiles:
# Get a data source, a matching run from the bidsmap
datasource = bids.DataSource(sourcefile, {'spec2nii2bids': options})
run, index = bids.get_matching_run(datasource, bidsmap, runtime=True)
# Check if we should ignore this run
if datasource.datatype in bidsmap['Options']['bidscoin'][
'ignoretypes']:
LOGGER.info(f"Leaving out: {sourcefile}")
continue
# Check that we know this run
if index is None:
LOGGER.error(
f"Skipping unknown '{datasource.datatype}' run: {sourcefile}\n-> Re-run the bidsmapper and delete the MRS output data in {bidsses} to solve this warning"
)
continue
LOGGER.info(f"Processing: {sourcefile}")
# Create the BIDS session/datatype output folder
outfolder = bidsses / datasource.datatype
outfolder.mkdir(parents=True, exist_ok=True)
# Compose the BIDS filename using the matched run
bidsname = bids.get_bidsname(subid, sesid, run, runtime=True)
runindex = run['bids'].get('run', '')
if runindex.startswith('<<') and runindex.endswith('>>'):
bidsname = bids.increment_runindex(outfolder, bidsname)
jsonfile = (outfolder / bidsname).with_suffix('.json')
# Check if file already exists (-> e.g. when a static runindex is used)
if jsonfile.is_file():
LOGGER.warning(
f"{outfolder/bidsname}.* already exists and will be deleted -- check your results carefully!"
)
for ext in ('.nii.gz', '.nii', '.json', '.bval', '.bvec',
'.tsv.gz'):
(outfolder / bidsname).with_suffix(ext).unlink(missing_ok=True)
# Run spec2nii to convert the source-files in the run folder to nifti's in the BIDS-folder
arg = ''
args = options.get('args', OPTIONS['args'])
if args is None:
args = ''
if dataformat == 'SPAR':
dformat = 'philips'
arg = f'"{sourcefile.with_suffix(".SDAT")}"'
elif dataformat == 'Twix':
dformat = 'twix'
arg = '-e image'
elif dataformat == 'Pfile':
dformat = 'ge'
else:
LOGGER.exception(f"Unsupported dataformat: {dataformat}")
command = options.get("command", "spec2nii")
if not bidscoin.run_command(
f'{command} {dformat} -j -f "{bidsname}" -o "{outfolder}" {args} {arg} "{sourcefile}"'
):
if not list(outfolder.glob(f"{bidsname}.nii*")): continue
# Load and adapt the newly produced json sidecar-file (NB: assumes every nifti-file comes with a json-file)
with jsonfile.open('r') as json_fid:
jsondata = json.load(json_fid)
# Copy over the source meta-data
metadata = bids.copymetadata(sourcefile, outfolder / bidsname,
options.get('meta', []))
for metakey, metaval in metadata.items():
if jsondata.get(metakey) == metaval:
LOGGER.warning(
f"Replacing {metakey} values in {jsonfile}: {jsondata[metakey]} -> {metaval}"
)
jsondata[metakey] = metaval
# Add all the meta data to the json-file
for metakey, metaval in run['meta'].items():
metaval = datasource.dynamicvalue(metaval,
cleanup=False,
runtime=True)
try:
metaval = ast.literal_eval(str(metaval))
except (ValueError, SyntaxError):
pass
LOGGER.info(f"Adding '{metakey}: {metaval}' to: {jsonfile}")
if not metaval:
metaval = None
jsondata[metakey] = metaval
# Save the meta data to disk
with jsonfile.open('w') as json_fid:
json.dump(jsondata, json_fid, indent=4)
# Parse the acquisition time from the source header or else from the json file (NB: assuming the source file represents the first acquisition)
if datasource.datatype not in bidsmap['Options']['bidscoin'][
'bidsignore'] and not run['bids'][
'suffix'] in bids.get_derivatives(datasource.datatype):
acq_time = ''
if dataformat == 'SPAR':
acq_time = datasource.attributes('scan_date')
elif dataformat == 'Twix':
acq_time = f"{datasource.attributes('AcquisitionDate')}T{datasource.attributes('AcquisitionTime')}"
elif dataformat == 'Pfile':
acq_time = f"{datasource.attributes('rhr_rh_scan_date')}T{datasource.attributes('rhr_rh_scan_time')}"
if not acq_time or acq_time == 'T':
acq_time = f"1925-01-01T{jsondata.get('AcquisitionTime','')}"
try:
acq_time = dateutil.parser.parse(acq_time)
if options.get('anon', OPTIONS['anon']) in ('y', 'yes'):
acq_time = acq_time.replace(
year=1925, month=1,
day=1) # Privacy protection (see BIDS specification)
acq_time = acq_time.isoformat()
except Exception as jsonerror:
LOGGER.warning(
f"Could not parse the acquisition time from: {sourcefile}\n{jsonerror}"
)
acq_time = 'n/a'
scans_table.loc[jsonfile.with_suffix('.nii.gz').
relative_to(bidsses).as_posix(),
'acq_time'] = acq_time
# Write the scans_table to disk
LOGGER.info(f"Writing acquisition time data to: {scans_tsv}")
scans_table.sort_values(by=['acq_time', 'filename'], inplace=True)
scans_table.replace('', 'n/a').to_csv(scans_tsv,
sep='\t',
encoding='utf-8',
na_rep='n/a')
# Collect personal data from a source header
personals = {}
if sesid and 'session_id' not in personals:
personals['session_id'] = sesid
age = ''
if sesid and 'session_id' not in personals:
personals['session_id'] = sesid
if dataformat == 'Twix':
personals['sex'] = datasource.attributes('PatientSex')
personals['size'] = datasource.attributes('PatientSize')
personals['weight'] = datasource.attributes('PatientWeight')
age = datasource.attributes(
'PatientAge'
) # A string of characters with one of the following formats: nnnD, nnnW, nnnM, nnnY
elif dataformat == 'Pfile':
sex = datasource.attributes('rhe_patsex')
if sex == '0': personals['sex'] = 'O'
elif sex == '1': personals['sex'] = 'M'
elif sex == '2': personals['sex'] = 'F'
age = dateutil.parser.parse(
datasource.attributes('rhr_rh_scan_date')) - dateutil.parser.parse(
datasource.attributes('rhe_dateofbirth'))
age = str(age.days) + 'D'
if age.endswith('D'): age = float(age.rstrip('D')) / 365.2524
elif age.endswith('W'): age = float(age.rstrip('W')) / 52.1775
elif age.endswith('M'): age = float(age.rstrip('M')) / 12
elif age.endswith('Y'): age = float(age.rstrip('Y'))
if age and options.get('anon', OPTIONS['anon']) in ('y', 'yes'):
age = int(float(age))
personals['age'] = str(age)
# Store the collected personals in the participants_table
participants_tsv = bidsfolder / 'participants.tsv'
if participants_tsv.is_file():
participants_table = pd.read_csv(participants_tsv, sep='\t', dtype=str)
participants_table.set_index(['participant_id'],
verify_integrity=True,
inplace=True)
else:
participants_table = pd.DataFrame()
participants_table.index.name = 'participant_id'
if subid in participants_table.index and 'session_id' in participants_table.keys(
) and participants_table.loc[subid, 'session_id']:
return # Only take data from the first session -> BIDS specification
for key in personals: # TODO: Check that only values that are consistent over sessions go in the participants.tsv file, otherwise put them in a sessions.tsv file
if key not in participants_table or participants_table[key].isnull(
).get(subid, True) or participants_table[key].get(subid) == 'n/a':
participants_table.loc[subid, key] = personals[key]
# Write the collected data to the participants tsv-file
LOGGER.info(f"Writing {subid} subject data to: {participants_tsv}")
participants_table.replace('', 'n/a').to_csv(participants_tsv,
sep='\t',
encoding='utf-8',
na_rep='n/a')
def bidsparticipants(rawfolder: str, bidsfolder: str, keys: str, bidsmapfile: str='bidsmap.yaml', dryrun: bool=False) -> None:
"""
Main function that processes all the subjects and session in the sourcefolder to (re)generate the particpants.tsv file in the BIDS folder.
:param rawfolder: The root folder-name of the sub/ses/data/file tree containing the source data files
:param bidsfolder: The name of the BIDS root folder
:param keys: The keys that are extracted fro mthe source data when populating the participants.tsv file
:param bidsmapfile: The name of the bidsmap YAML-file. If the bidsmap pathname is relative (i.e. no "/" in the name) then it is assumed to be located in bidsfolder/code/bidscoin
:param dryrun: Boolean to just display the participants info
:return: Nothing
"""
# Input checking & defaults
rawfolder = Path(rawfolder).resolve()
bidsfolder = Path(bidsfolder).resolve()
# Start logging
if dryrun:
bidscoin.setup_logging()
else:
bidscoin.setup_logging(bidsfolder/'code'/'bidscoin'/'bidsparticipants.log')
LOGGER.info('')
LOGGER.info(f"-------------- START bidsparticipants {bidscoin.version()} ------------")
LOGGER.info(f">>> bidsparticipants sourcefolder={rawfolder} bidsfolder={bidsfolder} bidsmap={bidsmapfile}")
# Get the bidsmap sub-/ses-prefix from the bidsmap YAML-file
bidsmap,_ = bids.load_bidsmap(Path(bidsmapfile), bidsfolder/'code'/'bidscoin')
subprefix = bidsmap['Options']['bidscoin']['subprefix']
sesprefix = bidsmap['Options']['bidscoin']['sesprefix']
# Get the table & dictionary of the subjects that have been processed
participants_tsv = bidsfolder/'participants.tsv'
participants_json = participants_tsv.with_suffix('.json')
if participants_tsv.is_file():
participants_table = pd.read_csv(participants_tsv, sep='\t')
participants_table.set_index(['participant_id'], verify_integrity=True, inplace=True)
else:
participants_table = pd.DataFrame()
participants_table.index.name = 'participant_id'
if participants_json.is_file():
with participants_json.open('r') as json_fid:
participants_dict = json.load(json_fid)
else:
participants_dict = {'participant_id': {'Description': 'Unique participant identifier'}}
# Get the list of subjects
subjects = bidscoin.lsdirs(bidsfolder, 'sub-*')
if not subjects:
LOGGER.warning(f"No subjects found in: {bidsfolder}")
# Remove obsolete participants from the participants table
for participant in participants_table.index:
if participant not in [sub.name for sub in subjects]:
participants_table = participants_table.drop(participant)
# Loop over all subjects in the bids-folder and add them to the participants table
with logging_redirect_tqdm():
for n, subject in enumerate(tqdm(subjects, unit='subject', leave=False), 1):
LOGGER.info(f"------------------- Subject {n}/{len(subjects)} -------------------")
personals = dict()
subject = rawfolder/subject.name.replace('sub-', subprefix.replace('*','')) # TODO: This assumes e.g. that the subject-ids in the rawfolder did not contain BIDS-invalid characters (such as '_')
sessions = bidscoin.lsdirs(subject, (sesprefix if sesprefix!='*' else '') + '*')
if not subject.is_dir():
LOGGER.error(f"Could not find source-folder: {subject}")
continue
if not sessions:
sessions = [subject]
for session in sessions:
# Only take data from the first session -> BIDS specification
subid, sesid = bids.DataSource(session/'dum.my', subprefix='sub-', sesprefix='ses-').subid_sesid()
if sesprefix and sesid and 'session_id' not in personals:
personals['session_id'] = sesid
participants_dict['session_id'] = {'Description': 'Session identifier'}
# Unpack the data in a temporary folder if it is tarballed/zipped and/or contains a DICOMDIR file
sesfolders, unpacked = bids.unpack(session)
for sesfolder in sesfolders:
# Update / append the personal source data
LOGGER.info(f"Scanning session: {sesfolder}")
success = scanpersonals(bidsmap, sesfolder, personals)
# Clean-up the temporary unpacked data
if unpacked:
shutil.rmtree(sesfolder)
if success:
break
# Store the collected personals in the participant_table. TODO: Check that only values that are consistent over sessions go in the participants.tsv file, otherwise put them in a sessions.tsv file
for key in keys:
if key not in participants_dict:
participants_dict[key] = dict(LongName = 'Long (unabbreviated) name of the column',
Description = 'Description of the the column',
Levels = dict(Key='Value (This is for categorical variables: a dictionary of possible values (keys) and their descriptions (values))'),
Units = 'Measurement units. [<prefix symbol>]<unit symbol> format following the SI standard is RECOMMENDED')
participants_table.loc[subid, key] = personals.get(key)
# Write the collected data to the participant files
LOGGER.info(f"Writing subject data to: {participants_tsv}")
if not dryrun:
participants_table.replace('','n/a').to_csv(participants_tsv, sep='\t', encoding='utf-8', na_rep='n/a')
LOGGER.info(f"Writing subject data dictionary to: {participants_json}")
if not dryrun:
with participants_json.open('w') as json_fid:
json.dump(participants_dict, json_fid, indent=4)
print(participants_table)
LOGGER.info('-------------- FINISHED! ------------')
LOGGER.info('')
bidscoin.reporterrors()
def bidscoiner_plugin(session: Path, bidsmap: dict, bidsses: Path) -> None:
"""
This wrapper funtion around phys2bids converts the physio data in the session folder and saves it in the bidsfolder.
Each saved datafile should be accompanied with a json sidecar file. The bidsmap options for this plugin can be found in:
bidsmap_new['Options']['plugins']['phys2bidscoin']
See also the dcm2niix2bids plugin for reference implementation
:param session: The full-path name of the subject/session raw data source folder
:param bidsmap: The full mapping heuristics from the bidsmap YAML-file
:param bidsses: The full-path name of the BIDS output `sub-/ses-` folder
:return: Nothing
"""
# Get the subject identifiers and the BIDS root folder from the bidsses folder
if bidsses.name.startswith('ses-'):
bidsfolder = bidsses.parent.parent
subid = bidsses.parent.name
sesid = bidsses.name
else:
bidsfolder = bidsses.parent
subid = bidsses.name
sesid = ''
# Get started
plugin = {'phys2bidscoin': bidsmap['Options']['plugins']['phys2bidscoin']}
datasource = bids.get_datasource(session, plugin)
sourcefiles = [file for file in session.rglob('*') if is_sourcefile(file)]
if not sourcefiles:
LOGGER.info(f"No {__name__} sourcedata found in: {session}")
return
# Loop over all source data files and convert them to BIDS
for sourcefile in sourcefiles:
# Get a data source, a matching run from the bidsmap
datasource = bids.DataSource(sourcefile, plugin, datasource.dataformat)
run, match = bids.get_matching_run(datasource, bidsmap, runtime=True)
# Check if we should ignore this run
if datasource.datatype in bidsmap['Options']['bidscoin'][
'ignoretypes']:
LOGGER.info(f"Leaving out: {sourcefile}")
continue
# Check that we know this run
if not match:
LOGGER.error(
f"Skipping unknown '{datasource.datatype}' run: {sourcefile}\n-> Re-run the bidsmapper and delete the physiological output data in {bidsses} to solve this warning"
)
continue
LOGGER.info(f"Processing: {sourcefile}")
# Get an ordered list of the func runs from the scans.tsv file (which should have a standardized datetime format)
scans_tsv = bidsses / f"{subid}{bids.add_prefix('_', sesid)}_scans.tsv"
if scans_tsv.is_file():
scans_table = pd.read_csv(scans_tsv,
sep='\t',
index_col='filename')
scans_table.sort_values(by=['acq_time', 'filename'], inplace=True)
else:
LOGGER.error(
f"Could not read the TR's for phys2bids due to a missing '{scans_tsv}' file"
)
continue
funcscans = []
for index, row in scans_table.iterrows():
if index.startswith('func/'):
funcscans.append(index)
# Then read the TR's from the associated func sidecar files
tr = []
for funcscan in funcscans:
with (bidsses /
funcscan).with_suffix('.json').open('r') as json_fid:
jsondata = json.load(json_fid)
tr.append(jsondata['RepetitionTime'])
# Create a heuristic function for phys2bids
heur_str = ('def heur(physinfo, run=""):\n'
' info = {}\n'
f' if physinfo == "{sourcefile.name}":')
for key, val in run['bids'].items():
heur_str = (f'{heur_str}' f'\n info["{key}"] = "{val}"')
heur_str = f'{heur_str}\n return info'
# Write heuristic function as file in temporary folder
heur_file = Path(
tempfile.mkdtemp()) / f'heuristic_sub-{subid}_ses-{sesid}.py'
heur_file.write_text(heur_str)
# Run phys2bids
physiofiles = phys2bids(
filename=str(sourcefile),
outdir=str(bidsfolder),
heur_file=str(heur_file),
sub=subid,
ses=sesid,
chtrig=int(run['meta'].get('TriggerChannel', 0)),
num_timepoints_expected=run['meta'].get('ExpectedTimepoints',
None),
tr=tr,
pad=run['meta'].get('Pad', 9),
ch_name=run['meta'].get('ChannelNames', []),
yml='',
debug=True,
quiet=False)
# Add user-specified meta-data to the newly produced json files (NB: assumes every physio-file comes with a json-file)
for physiofile in physiofiles:
jsonfile = Path(physiofile).with_suffix('.json')
if not jsonfile.is_file():
LOGGER.error(
f"Could not find the expected json sidecar-file: '{jsonfile}'"
)
continue
with jsonfile.open('r') as json_fid:
jsondata = json.load(json_fid)
for metakey, metaval in run['meta'].items():
metaval = datasource.dynamicvalue(metaval,
cleanup=False,
runtime=True)
try:
metaval = ast.literal_eval(str(metaval))
except (ValueError, SyntaxError):
pass
LOGGER.info(f"Adding '{metakey}: {metaval}' to: {jsonfile}")
if not metaval:
metaval = None
jsondata[metakey] = metaval
with jsonfile.open('w') as json_fid:
json.dump(jsondata, json_fid, indent=4)
def rawmapper(rawfolder,
outfolder: Path = Path(),
sessions: tuple = (),
rename: bool = False,
force: bool = False,
dicomfield: tuple = ('PatientComments', ),
wildcard: str = '*',
subprefix: str = 'sub-',
sesprefix: str = 'ses-',
dryrun: bool = False) -> None:
"""
:param rawfolder: The root folder-name of the sub/ses/data/file tree containing the source data files
:param outfolder: The name of the folder where the mapping-file is saved (default = sourcefolder)
:param sessions: Space separated list of selected sub-#/ses-# names / folders to be processed. Otherwise all sessions in the bidsfolder will be selected
:param rename: Flag for renaming the sub-subid folders to sub-dicomfield
:param force: Flag to rename the directories, even if the target-directory already exists
:param dicomfield: The names of the dicomfields that are mapped (/ renamed to sub-dcmval/ses-dcmval)
:param wildcard: The Unix style pathname pattern expansion that is used by glob to select the series from which the dicomfield is being mapped
:param subprefix: The prefix common for all source subject-folders
:param sesprefix: The prefix common for all source session-folders
:param dryrun: Flag for dry-running renaming the sub-subid folders
:return: Nothing
"""
# Input checking
rawfolder = Path(rawfolder).resolve()
if not outfolder:
outfolder = rawfolder
print(f"Outfolder: {outfolder}")
outfolder = Path(outfolder).resolve()
# Write the header of the mapper logfile
mapperfile = outfolder / f"rawmapper_{'_'.join(dicomfield)}.tsv"
if not dryrun:
if rename and not mapperfile.is_file(): # Write the header once
mapperfile.write_text('subid\tsesid\tnewsubid\tnewsesid\n')
else: # Write the header once
mapperfile.write_text('subid\tsesid\tseriesname\t{}\n'.format(
'\t'.join(dicomfield)))
# Map the sessions in the sourcefolder
if not sessions:
sessions = list(rawfolder.glob(f"{subprefix}*/{sesprefix}*"))
if not sessions:
sessions = list(rawfolder.glob(
f"{subprefix}*")) # Try without session-subfolders
else:
sessions = [
sessionitem for session in sessions
for sessionitem in rawfolder.glob(session)
]
sessions = [session for session in sessions if session.is_dir()]
# Loop over the selected sessions in the sourcefolder
for session in sessions:
# Get the subject and session identifiers from the sub/ses session folder
datasource = bids.DataSource(session / 'dum.my',
subprefix=subprefix,
sesprefix=sesprefix)
subid, sesid = datasource.subid_sesid()
subid = subid.replace('sub-', subprefix)
sesid = sesid.replace('ses-', sesprefix)
# Parse the new subject and session identifiers from the dicomfield
series = bidscoin.lsdirs(session, wildcard)
if not series:
series = ''
dcmval = ''
else:
series = series[
0] # NB: Assumes the first folder contains a dicom file and that all folders give the same info
dcmval = ''
for dcmfield in dicomfield:
dcmval = dcmval + '/' + str(
bids.get_dicomfield(dcmfield, bids.get_dicomfile(series)))
dcmval = dcmval[1:]
# Rename the session subfolder in the sourcefolder and print & save this info
if rename:
# Get the new subid and sesid
if not dcmval or dcmval == 'None':
warnings.warn(
f"Skipping renaming because the dicom-field was empty for: {session}"
)
continue
else:
if '/' in dcmval: # Allow for different sub/ses delimiters that could be entered at the console (i.e. in PatientComments)
delim = '/'
elif '\\' in dcmval:
delim = '\\'
else:
delim = '\r\n'
newsubsesid = [val for val in dcmval.split(delim)
if val] # Skip empty lines / entries
newsubid = subprefix + bids.cleanup_value(
re.sub(f'^{subprefix}', '', newsubsesid[0]))
if newsubid == subprefix or newsubid == subprefix + 'None':
newsubid = subid
warnings.warn(
f"Could not rename {subid} because the dicom-field was empty for: {session}"
)
if len(newsubsesid) == 1:
newsesid = sesid
elif len(newsubsesid) == 2:
newsesid = sesprefix + bids.cleanup_value(
re.sub(f'^{sesprefix}', '', newsubsesid[1]))
else:
warnings.warn(
f"Skipping renaming of {session} because the dicom-field '{dcmval}' could not be parsed into [subid, sesid]"
)
continue
if newsesid == sesprefix or newsesid == subprefix + 'None':
newsesid = sesid
warnings.warn(
f"Could not rename {sesid} because the dicom-field was empty for: {session}"
)
# Save the dicomfield / sub-ses mapping in the mapper logfile and rename the session subfolder (but skip if it already exists)
newsession = rawfolder / newsubid / newsesid
print(f"{session} -> {newsession}")
if newsession == session:
continue
if not force and (newsession.is_dir() or newsession.is_file()):
warnings.warn(
f"{newsession} already exists, skipping renaming of {session} (you can use the '-c' option to override this)"
)
elif not dryrun:
with mapperfile.open('a') as fid:
fid.write(f"{subid}\t{sesid}\t{newsubid}\t{newsesid}\n")
if newsession.is_dir():
for item in session.iterdir():
shutil.move(item, newsession / item.name)
session.rmdir()
else:
shutil.move(session, newsession)
# Print & save the dicom values in the mapper logfile
else:
print('{}/{}/{}\t-> {}'.format(subid, sesid, series.name,
'\t'.join(dcmval.split('/'))))
if not dryrun:
with mapperfile.open('a') as fid:
fid.write('{}\t{}\t{}\t{}\n'.format(
subid, sesid, series.name,
'\t'.join(dcmval.split('/'))))
def bidsmapper_plugin(session: Path, bidsmap_new: dict, bidsmap_old: dict,
template: dict, store: dict) -> None:
"""
All the logic to map the Nibabel header fields onto bids labels go into this function
:param session: The full-path name of the subject/session raw data source folder
:param bidsmap_new: The new study bidsmap that we are building
:param bidsmap_old: The previous study bidsmap that has precedence over the template bidsmap
:param template: The template bidsmap with the default heuristics
:param store: The paths of the source- and target-folder
:return:
"""
# Get started
plugin = {
'nibabel2bids': bidsmap_new['Options']['plugins']['nibabel2bids']
}
datasource = bids.get_datasource(session, plugin, recurse=2)
if not datasource.dataformat:
return
if not (template[datasource.dataformat]
or bidsmap_old[datasource.dataformat]):
LOGGER.error(
f"No {datasource.dataformat} source information found in the bidsmap and template"
)
return
# Collect the different DICOM/PAR source files for all runs in the session
for sourcefile in [
file for file in session.rglob('*') if is_sourcefile(file)
]:
# See if we can find a matching run in the old bidsmap
datasource = bids.DataSource(sourcefile, plugin, datasource.dataformat)
run, match = bids.get_matching_run(datasource, bidsmap_old)
# If not, see if we can find a matching run in the template
if not match:
run, _ = bids.get_matching_run(datasource, template)
# See if we have collected the run somewhere in our new bidsmap
if not bids.exist_run(bidsmap_new, '', run):
# Communicate with the user if the run was not present in bidsmap_old or in template, i.e. that we found a new sample
if not match:
LOGGER.info(
f"Discovered '{datasource.datatype}' {datasource.dataformat} sample: {sourcefile}"
)
# Now work from the provenance store
if store:
targetfile = store['target'] / sourcefile.relative_to(
store['source'])
targetfile.parent.mkdir(parents=True, exist_ok=True)
run['provenance'] = str(shutil.copy2(sourcefile, targetfile))
# Copy the filled-in run over to the new bidsmap
bids.append_run(bidsmap_new, run)
else:
# Communicate with the user if the run was already present in bidsmap_old or in template
LOGGER.debug(
f"Known '{datasource.datatype}' {datasource.dataformat} sample: {sourcefile}"
)
def bidscoiner_plugin(session: Path, bidsmap: dict, bidsses: Path) -> None:
"""
The bidscoiner plugin to convert the session Nibabel source-files into BIDS-valid nifti-files in the
corresponding bids session-folder
:param session: The full-path name of the subject/session source folder
:param bidsmap: The full mapping heuristics from the bidsmap YAML-file
:param bidsses: The full-path name of the BIDS output `sub-/ses-` folder
:return: Nothing
"""
# Get the subject identifiers and the BIDS root folder from the bidsses folder
if bidsses.name.startswith('ses-'):
bidsfolder = bidsses.parent.parent
subid = bidsses.parent.name
sesid = bidsses.name
else:
bidsfolder = bidsses.parent
subid = bidsses.name
sesid = ''
# Get started
options = bidsmap['Options']['plugins']['nibabel2bids']
ext = options.get('ext', OPTIONS['ext'])
meta = options.get('meta', [])
sourcefiles = [file for file in session.rglob('*') if is_sourcefile(file)]
if not sourcefiles:
LOGGER.info(f"No {__name__} sourcedata found in: {session}")
return
# Read or create a scans_table and tsv-file
scans_tsv = bidsses / f"{subid}{bids.add_prefix('_', sesid)}_scans.tsv"
if scans_tsv.is_file():
scans_table = pd.read_csv(scans_tsv, sep='\t', index_col='filename')
else:
scans_table = pd.DataFrame(columns=['acq_time'], dtype='str')
scans_table.index.name = 'filename'
# Collect the different Nibabel source files for all files in the session
for sourcefile in sourcefiles:
datasource = bids.DataSource(sourcefile, {'nibabel2bids': options})
run, match = bids.get_matching_run(datasource, bidsmap, runtime=True)
# Check if we should ignore this run
if datasource.datatype in bidsmap['Options']['bidscoin'][
'ignoretypes']:
LOGGER.info(f"Leaving out: {sourcefile}")
continue
# Check if we already know this run
if not match:
LOGGER.error(
f"Skipping unknown '{datasource.datatype}' run: {sourcefile}\n-> Re-run the bidsmapper and delete {bidsses} to solve this warning"
)
continue
LOGGER.info(f"Processing: {sourcefile}")
# Create the BIDS session/datatype output folder
outfolder = bidsses / datasource.datatype
outfolder.mkdir(parents=True, exist_ok=True)
# Compose the BIDS filename using the matched run
bidsname = bids.get_bidsname(subid, sesid, run, runtime=True)
runindex = run['bids'].get('run', '')
if runindex.startswith('<<') and runindex.endswith('>>'):
bidsname = bids.increment_runindex(outfolder, bidsname)
bidsfile = (outfolder / bidsname).with_suffix(ext)
# Check if file already exists (-> e.g. when a static runindex is used)
if bidsfile.is_file():
LOGGER.warning(
f"{bidsfile}.* already exists and will be deleted -- check your results carefully!"
)
bidsfile.with_suffix('').with_suffix(ext).unlink()
# Save the sourcefile as a BIDS nifti file
nib.save(nib.load(sourcefile), bidsfile)
# Copy over the source meta-data
jsonfile = bidsfile.with_suffix('').with_suffix('.json')
jsondata = bids.copymetadata(sourcefile, bidsfile, meta)
# Add all the meta data to the meta-data. NB: the dynamic `IntendedFor` value is handled separately later
for metakey, metaval in run['meta'].items():
if metakey != 'IntendedFor':
metaval = datasource.dynamicvalue(metaval,
cleanup=False,
runtime=True)
try:
metaval = ast.literal_eval(str(metaval))
except (ValueError, SyntaxError):
pass
LOGGER.info(f"Adding '{metakey}: {metaval}' to: {jsonfile}")
if not metaval:
metaval = None
jsondata[metakey] = metaval
# Remove unused (but added from the template) B0FieldIdentifiers/Sources
if not jsondata.get('B0FieldSource'):
jsondata.pop('B0FieldSource', None)
if not jsondata.get('B0FieldIdentifier'):
jsondata.pop('B0FieldIdentifier', None)
# Save the meta-data to the json sidecar-file
with jsonfile.open('w') as json_fid:
json.dump(jsondata, json_fid, indent=4)
# Add an entry to the scans_table (we typically don't have useful data to put there)
acq_time = dateutil.parser.parse(
f"1925-01-01T{jsondata.get('AcquisitionTime', '')}")
scans_table.loc[bidsfile.relative_to(bidsses).as_posix(),
'acq_time'] = acq_time.isoformat()
# Write the scans_table to disk
LOGGER.info(f"Writing data to: {scans_tsv}")
scans_table.replace('', 'n/a').to_csv(scans_tsv,
sep='\t',
encoding='utf-8',
na_rep='n/a')
# Add an (empty) entry to the participants_table (we don't have useful data to put there)
participants_tsv = bidsfolder / 'participants.tsv'
if participants_tsv.is_file():
participants_table = pd.read_csv(participants_tsv, sep='\t', dtype=str)
participants_table.set_index(['participant_id'],
verify_integrity=True,
inplace=True)
else:
participants_table = pd.DataFrame()
participants_table.index.name = 'participant_id'
if subid in participants_table.index and 'session_id' in participants_table.keys(
) and participants_table.loc[subid, 'session_id']:
return # Only take data from the first session -> BIDS specification
participants_table.loc[subid, 'session_id'] = sesid if sesid else None
# Write the collected data to the participants tsv-file
LOGGER.info(f"Writing {subid} subject data to: {participants_tsv}")
participants_table.replace('', 'n/a').to_csv(participants_tsv,
sep='\t',
encoding='utf-8',
na_rep='n/a')
