def test_blip_distcor():
# good data to use
s3_prefix = "s3://fcp-indi/data/Projects/HBN/MRI/Site-CBIC/sub-NDARAB708LM5"
s3_paths = [
"func/sub-NDARAB708LM5_task-rest_run-1_bold.nii.gz",
"fmap/sub-NDARAB708LM5_dir-PA_acq-fMRI_epi.nii.gz",
"fmap/sub-NDARAB708LM5_dir-AP_acq-fMRI_epi.nii.gz"
]
wf, ds, local_paths = setup_test_wf(s3_prefix, s3_paths,
"test_blip_distcor",
workdirs_to_keep=["func_preproc_automask"])
func_preproc = create_func_preproc(tool='fsl',
wf_name='func_preproc_automask')
func_preproc.inputs.inputspec.func = local_paths["func/sub-NDARAB708LM5_task-rest_run-1_bold.nii.gz"]
blip = blip_distcor_wf("blip_distcor")
blip.inputs.inputspec.opposite_pe_epi = local_paths["fmap/sub-NDARAB708LM5_dir-PA_acq-fMRI_epi.nii.gz"]
blip.inputs.inputspec.same_pe_epi = local_paths["fmap/sub-NDARAB708LM5_dir-AP_acq-fMRI_epi.nii.gz"]
wf.connect(func_preproc, 'outputspec.func_mean',
blip, 'inputspec.func_mean')
wf.connect(blip, 'outputspec.blip_warp', ds, 'source_warp')
wf.connect(blip, 'outputspec.new_func_mean', ds, 'new_func_mean')
wf.connect(blip, 'outputspec.new_func_mask', ds, 'new_func_mask')
wf.run()
def connect_func_preproc(workflow, strat_list, c):
from CPAC.func_preproc.func_preproc import create_func_preproc
new_strat_list = []
for num_strat, strat in enumerate(strat_list):
for tool in c.functionalMasking:
tool = tool.lower()
new_strat = strat.fork()
func_preproc = create_func_preproc(tool=tool,
wf_name='func_preproc_%s_%d' %
(tool, num_strat))
node, out_file = new_strat.get_leaf_properties()
workflow.connect(node, out_file, func_preproc, 'inputspec.func')
func_preproc.inputs.inputspec.twopass = \
getattr(c, 'functional_volreg_twopass', True)
new_strat.append_name(func_preproc.name)
new_strat.set_leaf_properties(func_preproc,
'outputspec.preprocessed')
new_strat.update_resource_pool({
'mean_functional': (func_preproc, 'outputspec.func_mean'),
'functional_preprocessed_mask':
(func_preproc, 'outputspec.preprocessed_mask'),
'movement_parameters':
(func_preproc, 'outputspec.movement_parameters'),
'max_displacement':
(func_preproc, 'outputspec.max_displacement'),
'functional_preprocessed':
(func_preproc, 'outputspec.preprocessed'),
'functional_brain_mask': (func_preproc, 'outputspec.mask'),
'motion_correct': (func_preproc, 'outputspec.motion_correct'),
'coordinate_transformation': (func_preproc,
'outputspec.oned_matrix_save'),
})
new_strat_list.append(new_strat)
return workflow, new_strat_list
def connect_func_preproc(workflow, strat_list, c):
from CPAC.func_preproc.func_preproc import create_func_preproc
new_strat_list = []
for num_strat, strat in enumerate(strat_list):
nodes = strat.get_nodes_names()
for skullstrip_tool in c.functionalMasking:
skullstrip_tool = skullstrip_tool.lower()
new_strat = strat.fork()
func_preproc = create_func_preproc(
skullstrip_tool=skullstrip_tool,
n4_correction=c.n4_correct_mean_EPI,
wf_name='func_preproc_%s_%d' % (skullstrip_tool, num_strat))
node, out_file = new_strat.get_leaf_properties()
workflow.connect(node, out_file, func_preproc, 'inputspec.func')
node, out_file = strat['anatomical_reorient']
workflow.connect(node, out_file, func_preproc,
'inputspec.anat_skull')
node, out_file = strat['anatomical_brain_mask']
workflow.connect(node, out_file, func_preproc,
'inputspec.anatomical_brain_mask')
func_preproc.inputs.inputspec.twopass = \
getattr(c, 'functional_volreg_twopass', True)
new_strat.append_name(func_preproc.name)
new_strat.set_leaf_properties(func_preproc,
'outputspec.preprocessed')
if 'gen_motion_stats_before_stc' in nodes:
new_strat.update_resource_pool({
'mean_functional': (func_preproc, 'outputspec.func_mean'),
'functional_preprocessed_mask':
(func_preproc, 'outputspec.preprocessed_mask'),
'functional_preprocessed':
(func_preproc, 'outputspec.preprocessed'),
'functional_brain_mask': (func_preproc, 'outputspec.mask'),
'motion_correct':
(func_preproc, 'outputspec.motion_correct'),
})
else:
new_strat.update_resource_pool({
'mean_functional': (func_preproc, 'outputspec.func_mean'),
'functional_preprocessed_mask':
(func_preproc, 'outputspec.preprocessed_mask'),
'movement_parameters':
(func_preproc, 'outputspec.movement_parameters'),
'max_displacement':
(func_preproc, 'outputspec.max_displacement'),
'functional_preprocessed': (func_preproc,
'outputspec.preprocessed'),
'functional_brain_mask': (func_preproc, 'outputspec.mask'),
'motion_correct': (func_preproc,
'outputspec.motion_correct'),
'coordinate_transformation':
(func_preproc, 'outputspec.transform_matrices'),
})
new_strat_list.append(new_strat)
return workflow, new_strat_list