def process(source: str,
destination: str,
plugin_file: str = "",
plugin_opt: dict = {},
sub_list: list = [],
sub_skip_tsv: bool = False,
sub_skip_dir: bool = False,
ses_skip_dir: bool = False,
part_template: str = "",
bidsmapfile: str = "bidsmap.yaml",
dry_run: bool = False) -> None:
"""
Process bidsified dataset before the bidsification.
Can be used to produce derivatives, convertion
anonymisation with adventage of recording identification
by bidsmap.yaml
Essentually it is identical to bidsification but without
bidsification itself.
Only subjects in source/participants.tsv are treated,
this list can be narrowed using sub_list, sub_skip_tsv
and sub_skip_dir options
Parameters
----------
source: str
folder containing source dataset
destination: str
folder for prepeared dataset
plugin_file: str
path to the plugin file to use
plugin_opt: dict
named options passed to plugin
sub_list: list
list of subject to process. Subjects
are checked after plugin and must
start with 'sub-', as in destination
folder
sub_skip_tsv: bool
if set to True, subjects found in
destination/participants.tsv will be
ignored
sub_skip_dir: bool
if set to true, subjects with already
created directories will be ignored
Can conflict with sub_no_dir
ses_skip_dir: bool
if set to True, sessions with already
created directories will be ignored
Can conflict with ses_no_dir
part_template: str
path to template json file, from whitch
participants.tsv will be modeled. If unset
the defeault one "source/participants.tsv"
is used. Setting this variable may break
workflow
bidsmapfile: str
The name of bidsmap file, will be searched for
in destination/code/bidsmap directory, unless
path is absolute
dry_run: bool
if set to True, no disk writing operations
will be performed
"""
logger.info("-------------- Processing data -------------")
logger.info("Source directory: {}".format(source))
logger.info("Destination directory: {}".format(destination))
# Input checking
# source = os.path.abspath(source)
if not os.path.isdir(source):
logger.critical("Source directory {} don't exists".format(source))
raise NotADirectoryError(source)
if not os.path.isdir(destination):
logger.critical(
"Destination directory {} don't exists".format(destination))
raise NotADirectoryError(destination)
# Input checking & defaults
bidscodefolder = os.path.join(destination, 'code', 'bidsme')
# Create a code/bidsme subfolder
os.makedirs(bidscodefolder, exist_ok=True)
# Check for dataset description file
dataset_file = os.path.join(destination, 'dataset_description.json')
if not os.path.isfile(dataset_file):
logger.warning("Dataset description file 'dataset_description.json' "
"not found in '{}'".format(destination))
# Check for README file
readme_file = os.path.join(destination, 'README')
if not os.path.isfile(readme_file):
logger.warning("Dataset readme file 'README' "
"not found in '{}'".format(destination))
# Get the bidsmap heuristics from the bidsmap YAML-file
fname = paths.findFile(bidsmapfile, bidscodefolder, paths.local,
paths.config)
if not fname:
logger.critical('Bidsmap file {} not found.'.format(bidsmapfile))
raise FileNotFoundError(bidsmapfile)
else:
bidsmapfile = fname
logger.info("loading bidsmap {}".format(bidsmapfile))
bidsmap = Bidsmap(bidsmapfile)
ntotal, ntemplate, nunchecked = bidsmap.countRuns()
logger.debug("Map contains {} runs".format(ntotal))
if ntemplate != 0:
logger.warning("Map contains {} template runs".format(ntemplate))
if nunchecked != 0:
logger.critical("Map contains {} unchecked runs".format(nunchecked))
raise Exception("Unchecked runs present")
###############
# Plugin setup
###############
if plugin_file:
plugins.ImportPlugins(plugin_file)
plugins.InitPlugin(source=source,
destination=destination,
dry=dry_run,
**plugin_opt)
###############################
# Checking participants list
###############################
if not part_template:
part_template = os.path.join(source, "participants.json")
else:
logger.warning(
"Loading exterior participant template {}".format(part_template))
BidsSession.loadSubjectFields(part_template)
new_sub_file = os.path.join(source, "participants.tsv")
df_sub = pandas.read_csv(new_sub_file, sep="\t", header=0,
na_values="n/a").drop_duplicates()
df_dupl = df_sub.duplicated("participant_id")
if df_dupl.any():
logger.critical("Participant list contains one or several duplicated "
"entries: {}".format(", ".join(
df_sub[df_dupl]["participant_id"])))
raise Exception("Duplicated subjects")
dupl_file = os.path.join(source, "__duplicated.tsv")
if os.path.isfile(dupl_file):
logger.critical("Found unmerged file with duplicated subjects")
raise FileExistsError(dupl_file)
new_sub_json = os.path.join(source, "participants.json")
if not tools.checkTsvDefinitions(df_sub, new_sub_json):
raise Exception("Incompatible sidecar json")
old_sub_file = os.path.join(destination, "participants.tsv")
old_sub = None
if os.path.isfile(old_sub_file):
old_sub = pandas.read_csv(old_sub_file,
sep="\t",
header=0,
na_values="n/a")
if not old_sub.columns.equals(df_sub.columns):
logger.warning("Source participant.tsv has different columns "
"from destination dataset")
old_sub = old_sub["participant_id"]
##############################
# Subjects loop
##############################
n_subjects = len(df_sub["participant_id"])
for index, sub_row in df_sub.iterrows():
sub_no = index + 1
sub_id = sub_row["participant_id"]
sub_dir = os.path.join(source, sub_id)
if not os.path.isdir(sub_dir):
logger.error("{}: Not found in {}".format(sub_id, source))
continue
scan = BidsSession()
scan.in_path = sub_dir
scan.subject = sub_id
#################################################
# Cloning df_sub row values in scans sub_values
#################################################
for column in df_sub.columns:
scan.sub_values[column] = sub_row[column]
# locking subjects here forbids renaming in process
# as it will be unclear how manage folders with data
scan.lock_subject()
if plugins.RunPlugin("SubjectEP", scan) < 0:
logger.warning("Subject {} discarded by {}".format(
scan.subject, "SubjectEP"))
continue
if not scan.isSubValid():
logger.error("{}: Subject id '{}' is not valid".format(
sub_id, scan.subject))
continue
if tools.skipEntity(scan.subject, sub_list,
old_sub if sub_skip_tsv else None,
destination if sub_skip_dir else ""):
logger.info("Skipping subject '{}'".format(scan.subject))
continue
ses_dirs = tools.lsdirs(sub_dir, 'ses-*')
if not ses_dirs:
logger.error("{}: No sessions found in: {}".format(
scan.subject, sub_dir))
continue
for ses_dir in ses_dirs:
scan.in_path = ses_dir
logger.info("{} ({}/{}): Scanning folder {}".format(
scan.subject, sub_no, n_subjects, ses_dir))
scan.unlock_session()
scan.session = os.path.basename(ses_dir)
if plugins.RunPlugin("SessionEP", scan) < 0:
logger.warning("Session {} discarded by {}".format(
scan.session, "SessionEP"))
continue
scan.lock()
if ses_skip_dir and tools.skipEntity(
scan.session, [], None,
os.path.join(destination, scan.subject)):
logger.info("Skipping session '{}'".format(scan.session))
continue
for module in Modules.selector.types_list:
mod_dir = os.path.join(ses_dir, module)
if not os.path.isdir(mod_dir):
logger.debug("Module {} not found in {}".format(
module, ses_dir))
continue
for run in tools.lsdirs(mod_dir):
scan.in_path = run
cls = Modules.select(run, module)
if cls is None:
logger.error(
"Failed to identify data in {}".format(run))
continue
recording = cls(rec_path=run)
if not recording or len(recording.files) == 0:
logger.error(
"unable to load data in folder {}".format(run))
continue
recording.setBidsSession(scan)
coin(destination, recording, bidsmap, dry_run)
plugins.RunPlugin("SessionEndEP", scan)
scan.in_path = sub_dir
plugins.RunPlugin("SubjectEndEP", scan)
##################################
# Merging the participants table
##################################
df_processed = BidsSession.exportAsDataFrame()
col_mismatch = False
if not df_processed.columns.equals(df_sub.columns):
col_mismatch = True
logger.warning("Modified participant table do not match "
"original table. This is discouraged and can "
"break future preparation and process steps")
for col in df_processed.columns.difference(df_sub.columns):
df_sub[col] = None
df_sub = df_sub[BidsSession.getSubjectColumns()]
df_sub.drop_duplicates(inplace=True)
df_res = pandas.concat([df_sub, df_processed],
join="inner",
keys=("original", "processed"),
names=("stage", "ID"))
df_res = df_res.drop_duplicates()
df_dupl = df_res.duplicated("participant_id", keep=False)
if df_dupl.any():
logger.info("Updating participants values")
df_dupl = df_dupl.drop(["processed"])
df_res.drop(df_dupl[df_dupl].index, inplace=True)
df_dupl = df_res.duplicated("participant_id")
if df_dupl.any():
logger.error("Participant list contains one or several duplicated "
"entries: {}".format(", ".join(
df_res[df_dupl]["participant_id"])))
##################################
# Saving the participants table
##################################
if not dry_run:
df_res[~df_dupl].to_csv(new_sub_file,
sep='\t',
na_rep="n/a",
index=False,
header=True)
if df_dupl.any():
logger.info("Saving the list to be merged manually to {}".format(
dupl_file))
df_res[df_dupl].to_csv(dupl_file,
sep='\t',
na_rep="n/a",
index=False,
header=True)
json_file = tools.change_ext(new_sub_file, "json")
if col_mismatch or not os.path.isfile(json_file):
BidsSession.exportDefinitions(json_file)
plugins.RunPlugin("FinaliseEP")
def mapper(source: str, destination: str,
plugin_file: str = "",
plugin_opt: dict = {},
sub_list: list = [],
sub_skip_tsv: bool = False,
sub_skip_dir: bool = False,
ses_skip_dir: bool = False,
bidsmapfile: str = "bidsmap.yaml",
map_template: str = "bidsmap_template.yaml",
dry_run: bool = False
) -> None:
"""
Generates bidsmap.yaml from prepeared dataset and
map template.
Only subjects in source/participants.tsv are treated,
this list can be narrowed using sub_list, sub_skip_tsv
and sub_skip_dir options
Parameters
----------
source: str
folder containing source dataset
destination: str
folder for prepeared dataset
plugin_file: str
path to the plugin file to use
plugin_opt: dict
named options passed to plugin
sub_list: list
list of subject to process. Subjects
are checked after plugin and must
start with 'sub-', as in destination
folder
sub_skip_tsv: bool
if set to True, subjects found in
destination/participants.tsv will be
ignored
sub_skip_dir: bool
if set to true, subjects with already
created directories will be ignored
Can conflict with sub_no_dir
ses_skip_dir: bool
if set to True, sessions with already
created directories will be ignored
Can conflict with ses_no_dir
bidsmapfile: str
The name of bidsmap file, will be searched for
in destination/code/bidsmap directory, unless
path is absolute
map_template: str
The name of template map. The file is searched
in heuristics folder
dry_run: bool
if set to True, no disk writing operations
will be performed
"""
logger.info("------------ Generating bidsmap ------------")
logger.info("Current directory: {}".format(os.getcwd()))
logger.info("Source directory: {}".format(source))
logger.info("Destination directory: {}".format(destination))
# Input checking
if not os.path.isdir(source):
logger.critical("Source directory {} don't exists"
.format(source))
raise NotADirectoryError(source)
if not os.path.isdir(destination):
logger.critical("Destination directory {} don't exists"
.format(destination))
raise NotADirectoryError(destination)
bidscodefolder = os.path.join(destination, 'code', 'bidsme')
os.makedirs(bidscodefolder, exist_ok=True)
# Get the heuristics for filling the new bidsmap
logger.info("loading template bidsmap {}".format(map_template))
fname = paths.findFile(map_template,
paths.local,
paths.config,
paths.heuristics)
if not fname:
logger.warning("Unable to find template map {}"
.format(map_template))
template = bidsmap.Bidsmap(fname)
fname = paths.findFile(bidsmapfile,
bidscodefolder,
paths.local,
paths.config
)
if not fname:
bidsmapfile = os.path.join(bidscodefolder, bidsmapfile)
else:
bidsmapfile = fname
logger.info("loading working bidsmap {}".format(bidsmapfile))
bidsmap_new = bidsmap.Bidsmap(bidsmapfile)
logger.debug("Creating bidsmap for unknown modalities")
# removing old unknown files
bidsunknown = os.path.join(bidscodefolder, 'unknown.yaml')
if os.path.isfile(bidsunknown):
os.remove(bidsunknown)
bidsmap_unk = bidsmap.Bidsmap(bidsunknown)
###############
# Plugin setup
###############
if plugin_file:
plugins.ImportPlugins(plugin_file)
plugins.InitPlugin(source=source,
destination=destination,
dry=True,
**plugin_opt)
###############################
# Checking participants list
###############################
new_sub_file = os.path.join(source, "participants.tsv")
df_sub = pandas.read_csv(new_sub_file,
sep="\t", header=0,
na_values="n/a")
df_dupl = df_sub.duplicated("participant_id")
if df_dupl.any():
logger.critical("Participant list contains one or several duplicated "
"entries: {}"
.format(", ".join(df_sub[df_dupl]["participant_id"]))
)
raise Exception("Duplicated subjects")
new_sub_json = os.path.join(source, "participants.json")
if not tools.checkTsvDefinitions(df_sub, new_sub_json):
raise Exception("Incompatible sidecar json")
BidsSession.loadSubjectFields(new_sub_json)
old_sub_file = os.path.join(destination, "participants.tsv")
old_sub = None
if os.path.isfile(old_sub_file):
old_sub = pandas.read_csv(old_sub_file, sep="\t", header=0,
na_values="n/a")
df_res = df_sub
if old_sub is not None:
if not old_sub.columns.equals(df_sub.columns):
logger.critical("Participant.tsv has differenrt columns "
"from destination dataset")
raise Exception("Participants column mismatch")
df_res = old_sub.append(df_sub, ignore_index=True).drop_duplicates()
df_dupl = df_res.duplicated("participant_id")
if df_dupl.any():
logger.critical("Joined participant list contains one or "
"several duplicated entries: {}"
.format(", ".join(
df_sub[df_dupl]["participant_id"])
)
)
raise Exception("Duplicated subjects")
old_sub = old_sub["participant_id"]
##############################
# Subjects loop
##############################
n_subjects = len(df_sub["participant_id"])
for sub_no, sub_id in enumerate(df_sub["participant_id"], 1):
sub_dir = os.path.join(source, sub_id)
if not os.path.isdir(sub_dir):
logger.error("{}: Not found in {}"
.format(sub_id, source))
continue
scan = BidsSession()
scan.in_path = sub_dir
scan.subject = sub_id
if plugins.RunPlugin("SubjectEP", scan) < 0:
logger.warning("Subject {} discarded by {}"
.format(scan.subject, "SubjectEP"))
continue
scan.lock_subject()
if not scan.isSubValid():
logger.error("{}: Subject id '{}' is not valid"
.format(sub_id, scan.subject))
continue
if tools.skipEntity(scan.subject, sub_list,
old_sub if sub_skip_tsv else None,
destination if sub_skip_dir else ""):
logger.info("Skipping subject '{}'"
.format(scan.subject))
continue
ses_dirs = tools.lsdirs(sub_dir, 'ses-*')
if not ses_dirs:
logger.error("{}: No sessions found in: {}"
.format(scan.subject, sub_dir))
continue
for ses_dir in ses_dirs:
scan.in_path = ses_dir
logger.info("{} ({}/{}): Scanning folder {}"
.format(scan.subject,
sub_no,
n_subjects,
ses_dir))
scan.unlock_session()
scan.session = os.path.basename(ses_dir)
if plugins.RunPlugin("SessionEP", scan) < 0:
logger.warning("Session {} discarded by {}"
.format(scan.session, "SessionEP"))
continue
scan.lock()
if ses_skip_dir and tools.skipEntity(scan.session,
[], None,
os.path.join(destination,
scan.subject)):
logger.info("Skipping session '{}'"
.format(scan.session))
continue
for module in Modules.selector.types_list:
mod_dir = os.path.join(ses_dir, module)
if not os.path.isdir(mod_dir):
logger.debug("Module {} not found in {}"
.format(module, ses_dir))
continue
for run in tools.lsdirs(mod_dir):
cls = Modules.selector.select(run, module)
if cls is None:
logger.error("Failed to identify data in {}"
.format(mod_dir))
continue
recording = cls(rec_path=run)
if not recording or len(recording.files) == 0:
logger.error("unable to load data in folder {}"
.format(run))
recording.setBidsSession(scan)
createmap(recording, bidsmap_new, template, bidsmap_unk)
if not dry_run:
# Save the bidsmap to the bidsmap YAML-file
bidsmap_new.save(bidsmapfile, empty_attributes=False)
ntotal, ntemplate, nunchecked = bidsmap_new.countRuns()
logger.info("Map contains {} runs".format(ntotal))
if ntemplate != 0:
logger.warning("Map contains {} template runs"
.format(ntemplate))
if nunchecked != 0:
logger.warning("Map contains {} unchecked runs"
.format(nunchecked))
# Scanning unknowing and exporting them to yaml file
unkn_recordings = bidsmap_unk.countRuns()[0]
if unkn_recordings > 0:
logger.error("Was unable to identify {} recordings. "
"See {} for details"
.format(unkn_recordings, bidsunknown))
if not dry_run:
bidsmap_unk.save(bidsunknown)
def SubjectEP(session: BidsSession) -> int:
"""
Subject determination and initialisation
1. Checks if subject not in balck list
2. Loads demographics from subject table
3. Creates session parcing dictionary
Parameters
----------
session: BidsSession
Returns
-------
int:
if 0, plugin succesfull
if > 0, plugin failed, an exception will be raised
if < 0, plugin failed, and subject will be skipped
"""
#################################
# Skipping if in the black list #
#################################
if session.subject in sub_black_list:
logger.info("Subject '{}' is in black_list"
.format(session.subject))
return -1
################################
# Retriving subject from table #
################################
try:
# in case if folder name in source dataset
# cannot be converted to integer
sub_id = int(session.subject)
except ValueError as e:
logger.error("Subject {}: Can't determine subject Id for: {}"
.format(session.subject, e))
return -1
# storing bidsified subject id into session object
# optional, but useful as reference
session.sub_values["participant_id"] = "sub-" + session.subject
# looking for subject in dataframe
prefix = "pat"
index = df_subjects.loc[df_subjects[prefix] == sub_id].index
# storing participant group in session
session.sub_values["group"] = "patient"
if len(index) == 0:
# Subject not in patient list, looking in control
prefix = "cnt"
index = df_subjects.loc[df_subjects[prefix] == sub_id].index
session.sub_values["group"] = "control"
if len(index) == 0:
raise KeyError("Subject {} not found in table"
.format(sub_id))
if len(index) > 1:
logger.warning("Subject {}: several column entries present"
.format(sub_id))
index = index[0]
# retrieving demographics
sex = df_subjects.loc[index, prefix + "_sex"]
age = df_subjects.loc[index, prefix + "_age"]
education = df_subjects.loc[index, prefix + "_edu"]
# session initialised values are Null
# fill them only if they are retrieved from table
if pandas.notna(sex):
session.sub_values["sex"] = sex
if pandas.notna(age):
session.sub_values["age"] = float(age)
if pandas.notna(education):
session.sub_values["education"] = float(education)
# looking for pairing
paired = df_subjects.loc[index, sub_prefix[prefix == "cnt"]]
if pandas.notna(paired):
session.sub_values["paired"] = "sub-{:03}".format(int(paired))
#################################
# determining order of sessions #
#################################
scans_map.clear()
scans_order = sorted([os.path.basename(s) for s in
tools.lsdirs(os.path.join(rawfolder,
session.subject),
"s*")
])
# looping over session defined in columns
for ind, s in enumerate(("_1", "_2", "_3")):
v = "ses-" + str(df_subjects.loc[index, prefix + s]).strip()
ses = "ses" + s
if v == "ses-nan":
# Session not defined in table, but existing
# in source dataset
session.sub_values[ses] = ""
logger.warning("Subject {}({}): missing {} value"
.format(session.sub_values["participant_id"],
session.sub_values["group"],
ses)
)
elif v == "ses-OUT":
# participant left study
logger.warning("Subject {}({}): seems to be abandoned study"
.format(session.sub_values["participant_id"],
session.sub_values["group"]
)
)
return -1
elif v not in Series:
# invalid session name
logger.critical("Subject {}({}): Invalid {}: {}"
.format(session.sub_values["participant_id"],
session.sub_values["group"],
ses,
session.sub_values[ses])
)
raise KeyError("Invalid {}: {}"
.format(ses, v))
else:
# session retrieved, storing values
session.sub_values[ses] = v
scans_map[scans_order[ind]] = v
# checking if all scans are identifyable
# if not, additional scans will be stored
# with original names
for scan in scans_order:
if scan not in scans_map:
logger.error("Subject {}({}): Can't identify session {}"
.format(session.sub_values["participant_id"],
session.sub_values["group"],
scan))
scans_map[scan] = scan
# opional, the sub- prefix added automatically
# if not present
session.subject = "sub-" + session.subject
def prepare(source: str, destination: str,
plugin_file: str = "",
plugin_opt: dict = {},
sub_list: list = [],
sub_skip_tsv: bool = False,
sub_skip_dir: bool = False,
ses_skip_dir: bool = False,
part_template: str = "",
sub_prefix: str = "",
ses_prefix: str = "",
sub_no_dir: bool = False,
ses_no_dir: bool = False,
data_dirs: dict = {},
dry_run: bool = False
) -> None:
"""
Prepare data from surce folder and place it in
sestination folder.
Source folder is expected to have structure
source/[subId/][sesId/][data/]file.
Absence of subId and sesId levels must be communicated
via sub_no_dir and ses_no_dir options. List of data
folders must be given in data_dirs.
Prepeared data will have structure
destination/sub-<subId>/ses-<sesId>/<type>/<sequence>/file
A list of treated subjects will be created/updated
in destination/participants.tsv file
Parameters
----------
source: str
folder containing source dataset
destination: str
folder for prepeared dataset
plugin_file: str
path to the plugin file to use
plugin_opt: dict
named options passed to plugin
sub_list: list
list of subject to process. Subjects
are checked after plugin and must
start with 'sub-', as in destination
folder
sub_skip_tsv: bool
if set to True, subjects found in
destination/participants.tsv will be
ignored
sub_skip_dir: bool
if set to true, subjects with already
created directories will be ignored
Can conflict with sub_no_dir
ses_skip_dir: bool
if set to True, sessions with already
created directories will be ignored
Can conflict with ses_no_dir
part_template: str
path to template json file, from whitch
participants.tsv will be modeled. Must be
formated as usual BIDS sidecar json file
for tsv files
sub_prefix: str
prefix for subject folders in source dataset.
If set, subject folders without prefix will
be ignored, and will be stripped from subject
Ids: sub001 -> 001 if sub_prefix==sub
Option has no effect if sub_no_dir==True
ses_prefix: str
prefix for session folders in source dataset.
If set, session folders without prefix will
be ignored, and will be stripped from session
Ids: sesTest -> Test if ses_prefix==ses
Option has no effect if ses_no_dir==True
sub_no_dir: bool
if set to True, source dataset will not be
expected to have subject folders.
ses_no_dir: bool
if set to True, source dataset will not be
expected to have session folders.
data_dirs: dict
dictionary containing list of folders with
recording data as key and data type as value.
If folder contain several types of data,
then value must be set to empty string
dry_run: bool
if set to True, no disk writing operations
will be performed
"""
logger.info("-------------- Prepearing data -------------")
logger.info("Source directory: {}".format(source))
logger.info("Destination directory: {}".format(destination))
# Input checking
# source = os.path.abspath(source)
if not os.path.isdir(source):
logger.critical("Source directory {} don't exists"
.format(source))
raise NotADirectoryError(source)
if not os.path.isdir(destination):
logger.critical("Destination directory {} don't exists"
.format(destination))
raise NotADirectoryError(destination)
if sub_no_dir and sub_skip_dir:
logger.warning("Both sub_no_dir and sub_skip_dir are set. "
"Subjects will not be skipped "
"unless subId defined in plugin")
if ses_no_dir and ses_skip_dir:
logger.warning("Both ses_no_dir and ses_skip_dir are set. "
"Sessions will not be skipped "
"unless sesId defined in plugin")
###############
# Plugin setup
###############
if plugin_file:
plugins.ImportPlugins(plugin_file)
plugins.InitPlugin(source=source,
destination=destination,
dry=dry_run,
**plugin_opt)
###############################
# Checking participants list
###############################
new_sub_json = os.path.join(destination, "participants.json")
if not part_template:
if os.path.isfile(new_sub_json):
part_template = new_sub_json
BidsSession.loadSubjectFields(part_template)
old_sub_file = os.path.join(destination, "participants.tsv")
old_sub = None
if os.path.isfile(old_sub_file):
old_sub = pandas.read_csv(old_sub_file, sep="\t", header=0,
na_values="n/a")
if not BidsSession.checkDefinitions(old_sub):
raise Exception("Destination participant.tsv incompatible "
"with given columns definitions")
dupl_file = os.path.join(destination, "__duplicated.tsv")
if os.path.isfile(dupl_file):
logger.critical("Found unmerged file with duplicated subjects")
raise FileExistsError(dupl_file)
###############
# Subject loop
###############
sub_prefix_dir, sub_prefix = os.path.split(sub_prefix)
ses_prefix_dir, ses_prefix = os.path.split(ses_prefix)
if not sub_no_dir:
sub_dirs = tools.lsdirs(
os.path.join(source, sub_prefix_dir),
sub_prefix + '*')
else:
sub_dirs = [source]
if not sub_dirs:
logger.warning("No subject folders found")
if not data_dirs:
data_dirs = {}
for sub_dir in sub_dirs:
scan = BidsSession()
scan.in_path = sub_dir
# get name of subject from folder name
if not sub_no_dir:
scan.subject = os.path.basename(sub_dir)
scan.subject = scan.subject[len(sub_prefix):]
if plugins.RunPlugin("SubjectEP", scan) < 0:
logger.warning("Subject {} discarded by {}"
.format(scan.subject, "SubjectEP"))
continue
scan.lock_subject()
if scan.subject is not None:
if tools.skipEntity(scan.subject, sub_list,
old_sub if sub_skip_tsv else None,
destination if sub_skip_dir else ""):
logger.info("Skipping subject '{}'"
.format(scan.subject))
continue
if not ses_no_dir:
ses_dirs = tools.lsdirs(
os.path.join(sub_dir, ses_prefix_dir),
ses_prefix + '*')
else:
ses_dirs = [sub_dir]
if not ses_dirs:
logger.warning("No session folders found")
for ses_dir in ses_dirs:
scan.in_path = ses_dir
logger.info("Scanning folder {}".format(ses_dir))
if not ses_no_dir:
scan.unlock_session()
scan.session = os.path.basename(ses_dir)
scan.session = scan.session[len(ses_prefix):]
else:
scan.unlock_session()
scan.session = ""
if plugins.RunPlugin("SessionEP", scan) < 0:
logger.warning("Session {} discarded by {}"
.format(scan.session, "SessionEP"))
continue
scan.lock()
if scan.session is not None:
skip = False
if ses_skip_dir:
if os.path.isdir(os.path.join(destination,
scan.session)):
logger.debug("{} dir exists".format(scan.session))
skip = True
if skip:
logger.info("Skipping session '{}'"
.format(scan.session))
continue
if not data_dirs:
data_dirs[""] = ""
for rec_dirs, rec_type in data_dirs.items():
rec_dirs = tools.lsdirs(ses_dir, rec_dirs)
for rec_dir in rec_dirs:
if not os.path.isdir(rec_dir):
logger.warning("Sub: '{}', Ses: '{}': "
"'{}' don't exists "
"or not a folder"
.format(scan.subject,
scan.session,
rec_dir))
continue
cls = Modules.select(rec_dir, rec_type)
if cls is None:
logger.warning("Unable to identify data in folder {}"
.format(rec_dir))
continue
recording = cls(rec_path=rec_dir)
if not recording or len(recording.files) == 0:
logger.warning("unable to load data in folder {}"
.format(rec_dir))
sortsession(destination, scan, recording, dry_run)
plugins.RunPlugin("SessionEndEP", scan)
scan.in_path = sub_dir
plugins.RunPlugin("SubjectEndEP", scan)
df_processed = BidsSession.exportAsDataFrame()
if old_sub is not None:
df_res = pandas.concat([old_sub, df_processed],
sort=False,
ignore_index=True)
else:
df_res = df_processed
df_res = df_res[BidsSession.getSubjectColumns()].drop_duplicates()
df_dupl = df_res.duplicated("participant_id")
if df_dupl.any():
logger.critical("Participant list contains one or several duplicated "
"entries: {}"
.format(", ".join(df_res[df_dupl]["participant_id"]))
)
if not dry_run:
df_res[~df_dupl].to_csv(old_sub_file,
sep='\t', na_rep="n/a",
index=False, header=True)
if df_dupl.any():
logger.info("Saving the list to be merged manually to {}"
.format(dupl_file))
df_res[df_dupl].to_csv(dupl_file,
sep='\t', na_rep="n/a",
index=False, header=True)
new_sub_json = os.path.join(destination, "participants.json")
if not os.path.isfile(new_sub_json):
BidsSession.exportDefinitions(new_sub_json)
plugins.RunPlugin("FinaliseEP")