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RF: Remove datasinks already reimplemented elsewhere
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‎fmriprep/workflows/bold/outputs.py

Lines changed: 0 additions & 339 deletions
Original file line numberDiff line numberDiff line change
@@ -961,351 +961,12 @@ def init_func_derivatives_wf(
961961
raw_sources = pe.Node(niu.Function(function=_bids_relative), name='raw_sources')
962962
raw_sources.inputs.bids_root = bids_root
963963

964-
ds_ref_t1w_xfm = pe.Node(
965-
DerivativesDataSink(
966-
base_directory=output_dir,
967-
to='T1w',
968-
mode='image',
969-
suffix='xfm',
970-
extension='.txt',
971-
dismiss_entities=('echo',),
972-
**{'from': 'scanner'},
973-
),
974-
name='ds_ref_t1w_xfm',
975-
run_without_submitting=True,
976-
)
977-
ds_ref_t1w_inv_xfm = pe.Node(
978-
DerivativesDataSink(
979-
base_directory=output_dir,
980-
to='scanner',
981-
mode='image',
982-
suffix='xfm',
983-
extension='.txt',
984-
dismiss_entities=('echo',),
985-
**{'from': 'T1w'},
986-
),
987-
name='ds_t1w_tpl_inv_xfm',
988-
run_without_submitting=True,
989-
)
990964
# fmt:off
991965
workflow.connect([
992966
(inputnode, raw_sources, [('all_source_files', 'in_files')]),
993-
(inputnode, ds_ref_t1w_xfm, [('source_file', 'source_file'),
994-
('bold2anat_xfm', 'in_file')]),
995-
(inputnode, ds_ref_t1w_inv_xfm, [('source_file', 'source_file'),
996-
('anat2bold_xfm', 'in_file')]),
997-
])
998-
# fmt:on
999-
1000-
# Output HMC and reference volume
1001-
ds_bold_hmc_xfm = pe.Node(
1002-
DerivativesDataSink(
1003-
base_directory=output_dir,
1004-
to='boldref',
1005-
mode='image',
1006-
suffix='xfm',
1007-
extension='.txt',
1008-
dismiss_entities=('echo',),
1009-
**{'from': 'scanner'},
1010-
),
1011-
name='ds_bold_hmc_xfm',
1012-
run_without_submitting=True,
1013-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1014-
)
1015-
1016-
ds_bold_native_ref = pe.Node(
1017-
DerivativesDataSink(
1018-
base_directory=output_dir, suffix='boldref', compress=True, dismiss_entities=("echo",)
1019-
),
1020-
name='ds_bold_native_ref',
1021-
run_without_submitting=True,
1022-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1023-
)
1024-
1025-
# fmt:off
1026-
workflow.connect([
1027-
(inputnode, ds_bold_hmc_xfm, [('source_file', 'source_file'),
1028-
('hmc_xforms', 'in_file')]),
1029-
(inputnode, ds_bold_native_ref, [('source_file', 'source_file'),
1030-
('bold_native_ref', 'in_file')])
1031967
])
1032968
# fmt:on
1033969

1034-
# Resample to T1w space
1035-
if nonstd_spaces.intersection(('T1w', 'anat')):
1036-
ds_bold_t1 = pe.Node(
1037-
DerivativesDataSink(
1038-
base_directory=output_dir,
1039-
space='T1w',
1040-
desc='preproc',
1041-
compress=True,
1042-
SkullStripped=masked,
1043-
TaskName=metadata.get('TaskName'),
1044-
**timing_parameters,
1045-
),
1046-
name='ds_bold_t1',
1047-
run_without_submitting=True,
1048-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1049-
)
1050-
ds_bold_t1_ref = pe.Node(
1051-
DerivativesDataSink(
1052-
base_directory=output_dir,
1053-
space='T1w',
1054-
suffix='boldref',
1055-
compress=True,
1056-
dismiss_entities=("echo",),
1057-
),
1058-
name='ds_bold_t1_ref',
1059-
run_without_submitting=True,
1060-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1061-
)
1062-
ds_bold_mask_t1 = pe.Node(
1063-
DerivativesDataSink(
1064-
base_directory=output_dir,
1065-
space='T1w',
1066-
desc='brain',
1067-
suffix='mask',
1068-
compress=True,
1069-
dismiss_entities=("echo",),
1070-
),
1071-
name='ds_bold_mask_t1',
1072-
run_without_submitting=True,
1073-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1074-
)
1075-
# fmt:off
1076-
workflow.connect([
1077-
(inputnode, ds_bold_t1, [('source_file', 'source_file'),
1078-
('bold_t1', 'in_file')]),
1079-
(inputnode, ds_bold_t1_ref, [('source_file', 'source_file'),
1080-
('bold_t1_ref', 'in_file')]),
1081-
(inputnode, ds_bold_mask_t1, [('source_file', 'source_file'),
1082-
('bold_mask_t1', 'in_file')]),
1083-
(raw_sources, ds_bold_mask_t1, [('out', 'RawSources')]),
1084-
])
1085-
# fmt:on
1086-
if freesurfer:
1087-
ds_bold_aseg_t1 = pe.Node(
1088-
DerivativesDataSink(
1089-
base_directory=output_dir,
1090-
space='T1w',
1091-
desc='aseg',
1092-
suffix='dseg',
1093-
compress=True,
1094-
dismiss_entities=("echo",),
1095-
),
1096-
name='ds_bold_aseg_t1',
1097-
run_without_submitting=True,
1098-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1099-
)
1100-
ds_bold_aparc_t1 = pe.Node(
1101-
DerivativesDataSink(
1102-
base_directory=output_dir,
1103-
space='T1w',
1104-
desc='aparcaseg',
1105-
suffix='dseg',
1106-
compress=True,
1107-
dismiss_entities=("echo",),
1108-
),
1109-
name='ds_bold_aparc_t1',
1110-
run_without_submitting=True,
1111-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1112-
)
1113-
# fmt:off
1114-
workflow.connect([
1115-
(inputnode, ds_bold_aseg_t1, [('source_file', 'source_file'),
1116-
('bold_aseg_t1', 'in_file')]),
1117-
(inputnode, ds_bold_aparc_t1, [('source_file', 'source_file'),
1118-
('bold_aparc_t1', 'in_file')]),
1119-
])
1120-
# fmt:on
1121-
if multiecho:
1122-
ds_t2star_t1 = pe.Node(
1123-
DerivativesDataSink(
1124-
base_directory=output_dir,
1125-
space='T1w',
1126-
suffix='T2starmap',
1127-
compress=True,
1128-
dismiss_entities=("echo",),
1129-
**t2star_meta,
1130-
),
1131-
name='ds_t2star_t1',
1132-
run_without_submitting=True,
1133-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1134-
)
1135-
# fmt:off
1136-
workflow.connect([
1137-
(inputnode, ds_t2star_t1, [('source_file', 'source_file'),
1138-
('t2star_t1', 'in_file')]),
1139-
(raw_sources, ds_t2star_t1, [('out', 'RawSources')]),
1140-
])
1141-
# fmt:on
1142-
1143-
if getattr(spaces, '_cached') is None:
1144-
return workflow
1145-
1146-
# Store resamplings in standard spaces when listed in --output-spaces
1147-
if spaces.cached.references:
1148-
from niworkflows.interfaces.space import SpaceDataSource
1149-
1150-
spacesource = pe.Node(SpaceDataSource(), name='spacesource', run_without_submitting=True)
1151-
spacesource.iterables = (
1152-
'in_tuple',
1153-
[(s.fullname, s.spec) for s in spaces.cached.get_standard(dim=(3,))],
1154-
)
1155-
1156-
fields = ['template', 'bold_std', 'bold_std_ref', 'bold_mask_std']
1157-
if multiecho:
1158-
fields.append('t2star_std')
1159-
select_std = pe.Node(
1160-
KeySelect(fields=fields),
1161-
name='select_std',
1162-
run_without_submitting=True,
1163-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1164-
)
1165-
1166-
ds_bold_std = pe.Node(
1167-
DerivativesDataSink(
1168-
base_directory=output_dir,
1169-
desc='preproc',
1170-
compress=True,
1171-
SkullStripped=masked,
1172-
TaskName=metadata.get('TaskName'),
1173-
**timing_parameters,
1174-
),
1175-
name='ds_bold_std',
1176-
run_without_submitting=True,
1177-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1178-
)
1179-
ds_bold_std_ref = pe.Node(
1180-
DerivativesDataSink(
1181-
base_directory=output_dir,
1182-
suffix='boldref',
1183-
compress=True,
1184-
dismiss_entities=("echo",),
1185-
),
1186-
name='ds_bold_std_ref',
1187-
run_without_submitting=True,
1188-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1189-
)
1190-
ds_bold_mask_std = pe.Node(
1191-
DerivativesDataSink(
1192-
base_directory=output_dir,
1193-
desc='brain',
1194-
suffix='mask',
1195-
compress=True,
1196-
dismiss_entities=("echo",),
1197-
),
1198-
name='ds_bold_mask_std',
1199-
run_without_submitting=True,
1200-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1201-
)
1202-
# fmt:off
1203-
workflow.connect([
1204-
(inputnode, ds_bold_std, [('source_file', 'source_file')]),
1205-
(inputnode, ds_bold_std_ref, [('source_file', 'source_file')]),
1206-
(inputnode, ds_bold_mask_std, [('source_file', 'source_file')]),
1207-
(inputnode, select_std, [('bold_std', 'bold_std'),
1208-
('bold_std_ref', 'bold_std_ref'),
1209-
('bold_mask_std', 'bold_mask_std'),
1210-
('t2star_std', 't2star_std'),
1211-
('template', 'template'),
1212-
('spatial_reference', 'keys')]),
1213-
(spacesource, select_std, [('uid', 'key')]),
1214-
(select_std, ds_bold_std, [('bold_std', 'in_file')]),
1215-
(spacesource, ds_bold_std, [('space', 'space'),
1216-
('cohort', 'cohort'),
1217-
('resolution', 'resolution'),
1218-
('density', 'density')]),
1219-
(select_std, ds_bold_std_ref, [('bold_std_ref', 'in_file')]),
1220-
(spacesource, ds_bold_std_ref, [('space', 'space'),
1221-
('cohort', 'cohort'),
1222-
('resolution', 'resolution'),
1223-
('density', 'density')]),
1224-
(select_std, ds_bold_mask_std, [('bold_mask_std', 'in_file')]),
1225-
(spacesource, ds_bold_mask_std, [('space', 'space'),
1226-
('cohort', 'cohort'),
1227-
('resolution', 'resolution'),
1228-
('density', 'density')]),
1229-
(raw_sources, ds_bold_mask_std, [('out', 'RawSources')]),
1230-
])
1231-
# fmt:on
1232-
if freesurfer:
1233-
select_fs_std = pe.Node(
1234-
KeySelect(fields=['bold_aseg_std', 'bold_aparc_std', 'template']),
1235-
name='select_fs_std',
1236-
run_without_submitting=True,
1237-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1238-
)
1239-
ds_bold_aseg_std = pe.Node(
1240-
DerivativesDataSink(
1241-
base_directory=output_dir,
1242-
desc='aseg',
1243-
suffix='dseg',
1244-
compress=True,
1245-
dismiss_entities=("echo",),
1246-
),
1247-
name='ds_bold_aseg_std',
1248-
run_without_submitting=True,
1249-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1250-
)
1251-
ds_bold_aparc_std = pe.Node(
1252-
DerivativesDataSink(
1253-
base_directory=output_dir,
1254-
desc='aparcaseg',
1255-
suffix='dseg',
1256-
compress=True,
1257-
dismiss_entities=("echo",),
1258-
),
1259-
name='ds_bold_aparc_std',
1260-
run_without_submitting=True,
1261-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1262-
)
1263-
# fmt:off
1264-
workflow.connect([
1265-
(spacesource, select_fs_std, [('uid', 'key')]),
1266-
(inputnode, select_fs_std, [('bold_aseg_std', 'bold_aseg_std'),
1267-
('bold_aparc_std', 'bold_aparc_std'),
1268-
('template', 'template'),
1269-
('spatial_reference', 'keys')]),
1270-
(select_fs_std, ds_bold_aseg_std, [('bold_aseg_std', 'in_file')]),
1271-
(spacesource, ds_bold_aseg_std, [('space', 'space'),
1272-
('cohort', 'cohort'),
1273-
('resolution', 'resolution'),
1274-
('density', 'density')]),
1275-
(select_fs_std, ds_bold_aparc_std, [('bold_aparc_std', 'in_file')]),
1276-
(spacesource, ds_bold_aparc_std, [('space', 'space'),
1277-
('cohort', 'cohort'),
1278-
('resolution', 'resolution'),
1279-
('density', 'density')]),
1280-
(inputnode, ds_bold_aseg_std, [('source_file', 'source_file')]),
1281-
(inputnode, ds_bold_aparc_std, [('source_file', 'source_file')])
1282-
])
1283-
# fmt:on
1284-
if multiecho:
1285-
ds_t2star_std = pe.Node(
1286-
DerivativesDataSink(
1287-
base_directory=output_dir,
1288-
suffix='T2starmap',
1289-
compress=True,
1290-
dismiss_entities=("echo",),
1291-
**t2star_meta,
1292-
),
1293-
name='ds_t2star_std',
1294-
run_without_submitting=True,
1295-
mem_gb=DEFAULT_MEMORY_MIN_GB,
1296-
)
1297-
# fmt:off
1298-
workflow.connect([
1299-
(inputnode, ds_t2star_std, [('source_file', 'source_file')]),
1300-
(select_std, ds_t2star_std, [('t2star_std', 'in_file')]),
1301-
(spacesource, ds_t2star_std, [('space', 'space'),
1302-
('cohort', 'cohort'),
1303-
('resolution', 'resolution'),
1304-
('density', 'density')]),
1305-
(raw_sources, ds_t2star_std, [('out', 'RawSources')]),
1306-
])
1307-
# fmt:on
1308-
1309970
fs_outputs = spaces.cached.get_fs_spaces()
1310971
if freesurfer and fs_outputs:
1311972
from niworkflows.interfaces.surf import Path2BIDS

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