def print_failed_images(cli_name, image_ids):
"""Print missing images in CAPS folder after a RuntimeError from Nipype."""
import datetime
from colorama import Fore
from .filemanip import extract_subjects_sessions_from_filename
from .stream import cprint
from clinica.utils.participant import get_unique_subjects
list_participant_id, list_session_id = extract_subjects_sessions_from_filename(
image_ids)
unique_participants, sessions_per_participant = get_unique_subjects(
list_participant_id, list_session_id)
now = datetime.datetime.now().strftime('%H:%M:%S')
cprint('\n%s[%s] The %s pipeline finished with errors.%s\n' %
(Fore.RED, now, cli_name, Fore.RESET))
cprint('%sCAPS outputs were not found for %s image(s):%s' %
(Fore.RED, len(image_ids), Fore.RESET))
for i in range(0, min(len(unique_participants), LINES_TO_DISPLAY)):
sessions_i_th_participant = ', '.join(
s_id for s_id in sessions_per_participant[i])
cprint("\t%s%s | %s%s" % (Fore.RED, unique_participants[i],
sessions_i_th_participant, Fore.RESET))
if len(unique_participants) > LINES_TO_DISPLAY:
cprint("\t...")
sessions_last_participant = ', '.join(
s_id for s_id in sessions_per_participant[-1])
cprint("\t%s%s | %s%s" % (Fore.RED, unique_participants[-1],
sessions_last_participant, Fore.RESET))
def get_processed_images(caps_directory, subjects, sessions):
import os
import re
from clinica.utils.input_files import T1_FS_T_DESTRIEUX
from clinica.utils.inputs import clinica_file_reader
from clinica.utils.longitudinal import get_long_id
from clinica.utils.participant import get_unique_subjects
[list_participant_id, list_list_session_ids] = get_unique_subjects(
subjects, sessions
)
list_long_id = [
get_long_id(list_session_ids) for list_session_ids in list_list_session_ids
]
image_ids = []
if os.path.isdir(caps_directory):
t1_freesurfer_files = clinica_file_reader(
list_participant_id,
list_long_id,
caps_directory,
T1_FS_T_DESTRIEUX,
False,
)
image_ids = [
re.search(r"(sub-[a-zA-Z0-9]+)_(long-[a-zA-Z0-9]+)", file).group()
for file in t1_freesurfer_files
]
return image_ids
def print_failed_images(cli_name, image_ids):
"""Print missing images in CAPS folder after a RuntimeError from Nipype."""
from clinica.utils.participant import get_unique_subjects
from .filemanip import extract_subjects_sessions_from_filename
from .stream import cprint
list_participant_id, list_session_id = extract_subjects_sessions_from_filename(
image_ids)
unique_participants, sessions_per_participant = get_unique_subjects(
list_participant_id, list_session_id)
cprint(msg=f"The {cli_name} pipeline finished with errors.", lvl="error")
cprint(msg=f"CAPS outputs were not found for {len(image_ids)} image(s):",
lvl="error")
for i in range(0, min(len(unique_participants), LINES_TO_DISPLAY)):
sessions_i_th_participant = ", ".join(
s_id for s_id in sessions_per_participant[i])
cprint(msg=f"{unique_participants[i]} | {sessions_i_th_participant}",
lvl="error")
if len(unique_participants) > LINES_TO_DISPLAY:
sessions_last_participant = ", ".join(
s_id for s_id in sessions_per_participant[-1])
cprint(msg=f"{unique_participants[-1]} | {sessions_last_participant}",
lvl="error")
def print_images_to_process(list_participant_id, list_session_id):
"""Print which images will be processed by the pipeline."""
from .stream import cprint
from clinica.utils.participant import get_unique_subjects
unique_participants, sessions_per_participant = get_unique_subjects(
list_participant_id, list_session_id)
cprint('The pipeline will be run on the following %s image(s):' %
len(list_participant_id))
for i in range(0, min(len(unique_participants), LINES_TO_DISPLAY)):
sessions_i_th_participant = ', '.join(
s_id for s_id in sessions_per_participant[i])
cprint("\t%s | %s," %
(unique_participants[i], sessions_i_th_participant))
if len(unique_participants) > LINES_TO_DISPLAY:
cprint("\t...")
sessions_last_participant = ', '.join(
s_id for s_id in sessions_per_participant[-1])
cprint("\t%s | %s" %
(unique_participants[-1], sessions_last_participant))
def print_images_to_process(list_participant_id, list_session_id):
"""Print which images will be processed by the pipeline."""
from clinica.utils.participant import get_unique_subjects
from .stream import cprint
unique_participants, sessions_per_participant = get_unique_subjects(
list_participant_id, list_session_id)
cprint(
f"The pipeline will be run on the following {len(list_participant_id)} image(s):"
)
for i in range(0, min(len(unique_participants), LINES_TO_DISPLAY)):
sessions_i_th_participant = ", ".join(
s_id for s_id in sessions_per_participant[i])
cprint(f"\t{unique_participants[i]} | {sessions_i_th_participant},")
if len(unique_participants) > LINES_TO_DISPLAY:
cprint("\t...")
sessions_last_participant = ", ".join(
s_id for s_id in sessions_per_participant[-1])
cprint(f"\t{unique_participants[-1]} | {sessions_last_participant},")
def print_failed_images(cli_name, image_ids):
"""Print missing images in CAPS folder after a RuntimeError from Nipype."""
import datetime
from colorama import Fore
from clinica.utils.participant import get_unique_subjects
from .filemanip import extract_subjects_sessions_from_filename
from .stream import cprint
list_participant_id, list_session_id = extract_subjects_sessions_from_filename(
image_ids)
unique_participants, sessions_per_participant = get_unique_subjects(
list_participant_id, list_session_id)
now = datetime.datetime.now().strftime("%H:%M:%S")
cprint(
f"\n{Fore.RED}[{now}] The {cli_name} pipeline finished with errors.{Fore.RESET}\n"
)
cprint(
f"{Fore.RED}CAPS outputs were not found for {len(image_ids)} image(s):{Fore.RESET}"
)
for i in range(0, min(len(unique_participants), LINES_TO_DISPLAY)):
sessions_i_th_participant = ", ".join(
s_id for s_id in sessions_per_participant[i])
cprint(
f"\t{Fore.RED}{unique_participants[i]} | {sessions_i_th_participant}{Fore.RESET}"
)
if len(unique_participants) > LINES_TO_DISPLAY:
cprint("\t...")
sessions_last_participant = ", ".join(
s_id for s_id in sessions_per_participant[-1])
cprint(
f"\t{Fore.RED}{unique_participants[-1]} | {sessions_last_participant}{Fore.RESET}"
)
def build_input_node(self):
"""Build and connect an input node to the pipeline."""
import os
import nipype.interfaces.utility as nutil
import nipype.pipeline.engine as npe
from clinica.utils.exceptions import ClinicaCAPSError, ClinicaException
from clinica.utils.filemanip import extract_subjects_sessions_from_filename
from clinica.utils.input_files import T1_FS_DESTRIEUX
from clinica.utils.inputs import clinica_file_reader
from clinica.utils.longitudinal import (
get_long_id,
get_participants_long_id,
read_sessions,
)
from clinica.utils.participant import (
get_unique_subjects,
unique_subjects_sessions_to_subjects_sessions,
)
from clinica.utils.stream import cprint
from .longitudinal_utils import (
extract_participant_long_ids_from_filename,
save_part_sess_long_ids_to_tsv,
)
# Display image(s) already present in CAPS folder
# ===============================================
output_ids = self.get_processed_images(
self.caps_directory, self.subjects, self.sessions
)
(
processed_participants,
processed_long_sessions,
) = extract_participant_long_ids_from_filename(output_ids)
if len(processed_participants) > 0:
cprint(
msg=(
f"Clinica found {len(processed_participants)} participant(s) "
"already processed in CAPS directory:"
),
lvl="warning",
)
for p_id, l_id in zip(processed_participants, processed_long_sessions):
cprint(f"{p_id} | {l_id}", lvl="warning")
if self.overwrite_caps:
output_folder = "<CAPS>/subjects/<participant_id>/<long_id>/freesurfer_unbiased_template/"
cprint(f"Output folders in {output_folder} will be recreated.", lvl="warning")
else:
cprint("Participant(s) will be ignored by Clinica.", lvl="warning")
input_ids = [
p_id + "_" + s_id
for p_id, s_id in zip(self.subjects, self.sessions)
]
processed_sessions_per_participant = [
read_sessions(self.caps_directory, p_id, l_id)
for (p_id, l_id) in zip(
processed_participants, processed_long_sessions
)
]
participants, sessions = unique_subjects_sessions_to_subjects_sessions(
processed_participants, processed_sessions_per_participant
)
processed_ids = [
p_id + "_" + s_id for p_id, s_id in zip(participants, sessions)
]
to_process_ids = list(set(input_ids) - set(processed_ids))
self.subjects, self.sessions = extract_subjects_sessions_from_filename(
to_process_ids
)
# Check that t1-freesurfer has run on the CAPS directory
try:
clinica_file_reader(
self.subjects, self.sessions, self.caps_directory, T1_FS_DESTRIEUX
)
except ClinicaException as e:
err_msg = (
"Clinica faced error(s) while trying to read files in your CAPS directory.\n"
+ str(e)
)
raise ClinicaCAPSError(err_msg)
# Save subjects to process in <WD>/<Pipeline.name>/participants.tsv
folder_participants_tsv = os.path.join(self.base_dir, self.name)
long_ids = get_participants_long_id(self.subjects, self.sessions)
save_part_sess_long_ids_to_tsv(
self.subjects, self.sessions, long_ids, folder_participants_tsv
)
[list_participant_id, list_list_session_ids] = get_unique_subjects(
self.subjects, self.sessions
)
list_long_id = [
get_long_id(list_session_ids) for list_session_ids in list_list_session_ids
]
def print_images_to_process(
unique_part_list, per_part_session_list, list_part_long_id
):
cprint(
f"The pipeline will be run on the following {len(unique_part_list)} participant(s):"
)
for (part_id, list_sess_id, list_id) in zip(
unique_part_list, per_part_session_list, list_part_long_id
):
sessions_participant = ", ".join(s_id for s_id in list_sess_id)
cprint(f"\t{part_id} | {sessions_participant} | {list_id}")
if len(self.subjects):
# TODO: Generalize long IDs to the message display
print_images_to_process(
list_participant_id, list_list_session_ids, list_long_id
)
cprint(
"List available in %s"
% os.path.join(folder_participants_tsv, "participants.tsv")
)
cprint("The pipeline will last approximately 10 hours per participant.")
read_node = npe.Node(
name="ReadingFiles",
iterables=[
("participant_id", list_participant_id),
("list_session_ids", list_list_session_ids),
],
synchronize=True,
interface=nutil.IdentityInterface(fields=self.get_input_fields()),
)
# fmt: off
self.connect(
[
(read_node, self.input_node, [("participant_id", "participant_id")]),
(read_node, self.input_node, [("list_session_ids", "list_session_ids")]),
]
)
def build_input_node(self):
"""Build and connect an input node to the pipeline."""
import os
from colorama import Fore
import nipype.interfaces.utility as nutil
import nipype.pipeline.engine as npe
from clinica.utils.exceptions import ClinicaException, ClinicaCAPSError
from clinica.utils.filemanip import extract_subjects_sessions_from_filename
from clinica.utils.inputs import clinica_file_reader
from clinica.utils.input_files import T1_FS_DESTRIEUX
from clinica.utils.longitudinal import get_long_id, read_sessions, get_participants_long_id
from clinica.utils.participant import get_unique_subjects, unique_subjects_sessions_to_subjects_sessions
from clinica.utils.stream import cprint
from .longitudinal_utils import extract_participant_long_ids_from_filename, save_part_sess_long_ids_to_tsv
# Display image(s) already present in CAPS folder
# ===============================================
output_ids = self.get_processed_images(self.caps_directory,
self.subjects, self.sessions)
processed_participants, processed_long_sessions = extract_participant_long_ids_from_filename(
output_ids)
if len(processed_participants) > 0:
cprint(
"%sClinica found %s participant(s) already processed in CAPS directory:%s"
% (Fore.YELLOW, len(processed_participants), Fore.RESET))
for p_id, l_id in zip(processed_participants,
processed_long_sessions):
cprint("%s\t%s | %s%s" % (Fore.YELLOW, p_id, l_id, Fore.RESET))
if self.overwrite_caps:
output_folder = "<CAPS>/subjects/<participant_id>/<long_id>/freesurfer_unbiased_template/"
cprint("%s\nOutput folders in %s will be recreated.\n%s" %
(Fore.YELLOW, output_folder, Fore.RESET))
else:
cprint("%s\nParticipant(s) will be ignored by Clinica.\n%s" %
(Fore.YELLOW, Fore.RESET))
input_ids = [
p_id + '_' + s_id
for p_id, s_id in zip(self.subjects, self.sessions)
]
processed_sessions_per_participant = [
read_sessions(self.caps_directory, p_id, l_id)
for (p_id, l_id) in zip(processed_participants,
processed_long_sessions)
]
participants, sessions = unique_subjects_sessions_to_subjects_sessions(
processed_participants, processed_sessions_per_participant)
processed_ids = [
p_id + '_' + s_id
for p_id, s_id in zip(participants, sessions)
]
to_process_ids = list(set(input_ids) - set(processed_ids))
self.subjects, self.sessions = extract_subjects_sessions_from_filename(
to_process_ids)
# Check that t1-freesurfer has run on the CAPS directory
try:
clinica_file_reader(self.subjects, self.sessions,
self.caps_directory, T1_FS_DESTRIEUX)
except ClinicaException as e:
err_msg = 'Clinica faced error(s) while trying to read files in your CAPS directory.\n' + str(
e)
raise ClinicaCAPSError(err_msg)
# Save subjects to process in <WD>/<Pipeline.name>/participants.tsv
folder_participants_tsv = os.path.join(self.base_dir, self.name)
long_ids = get_participants_long_id(self.subjects, self.sessions)
save_part_sess_long_ids_to_tsv(self.subjects, self.sessions, long_ids,
folder_participants_tsv)
[list_participant_id,
list_list_session_ids] = get_unique_subjects(self.subjects,
self.sessions)
list_long_id = [
get_long_id(list_session_ids)
for list_session_ids in list_list_session_ids
]
def print_images_to_process(unique_part_list, per_part_session_list,
list_part_long_id):
cprint(
'The pipeline will be run on the following %s participant(s):'
% len(unique_part_list))
for (part_id, list_sess_id,
list_id) in zip(unique_part_list, per_part_session_list,
list_part_long_id):
sessions_participant = ', '.join(s_id for s_id in list_sess_id)
cprint("\t%s | %s | %s" %
(part_id, sessions_participant, list_id))
if len(self.subjects):
# TODO: Generalize long IDs to the message display
print_images_to_process(list_participant_id, list_list_session_ids,
list_long_id)
cprint('List available in %s' %
os.path.join(folder_participants_tsv, 'participants.tsv'))
cprint(
'The pipeline will last approximately 10 hours per participant.'
)
read_node = npe.Node(
name="ReadingFiles",
iterables=[
('participant_id', list_participant_id),
('list_session_ids', list_list_session_ids),
],
synchronize=True,
interface=nutil.IdentityInterface(fields=self.get_input_fields()))
self.connect([
(read_node, self.input_node, [('participant_id', 'participant_id')
]),
(read_node, self.input_node, [('list_session_ids',
'list_session_ids')]),
])
