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Fixed structural-only processing logic
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@TheChymera
TheChymera committed Feb 15, 2024
1 parent ce8396a commit 1f14439
Showing 1 changed file with 82 additions and 62 deletions.
144 changes: 82 additions & 62 deletions samri/pipelines/preprocess.py
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Original file line number Diff line number Diff line change
Expand Up @@ -405,64 +405,88 @@ def generic(bids_base, template,
if not n_jobs:
n_jobs = max(int(round(mp.cpu_count()*n_jobs_percentage)),2)

find_physio = pe.Node(name='find_physio', interface=util.Function(function=corresponding_physiofile,input_names=inspect.getfullargspec(corresponding_physiofile)[0], output_names=['physiofile','meta_physiofile']))

get_f_scan = pe.Node(name='get_f_scan', interface=util.Function(function=get_bids_scan,input_names=inspect.getfullargspec(get_bids_scan)[0], output_names=['scan_path','scan_type','task', 'nii_path', 'nii_name', 'events_name', 'subject_session', 'metadata_filename', 'dict_slice', 'ind_type']))
get_f_scan.inputs.ignore_exception = True
get_f_scan.inputs.data_selection = data_selection
get_f_scan.inputs.bids_base = bids_base
get_f_scan.iterables = ("ind_type", func_ind)

dummy_scans = pe.Node(name='dummy_scans', interface=util.Function(function=force_dummy_scans,input_names=inspect.getfullargspec(force_dummy_scans)[0], output_names=['out_file','deleted_scans']))
dummy_scans.inputs.desired_dummy_scans = enforce_dummy_scans

events_file = pe.Node(name='events_file', interface=util.Function(function=write_bids_events_file,input_names=inspect.getfullargspec(write_bids_events_file)[0], output_names=['out_file']))

datasink = pe.Node(nio.DataSink(), name='datasink')
datasink.inputs.base_directory = out_dir
datasink.inputs.parameterization = False

workflow_connections = [
(get_f_scan, dummy_scans, [('nii_path', 'in_file')]),
(dummy_scans, events_file, [('deleted_scans', 'forced_dummy_scans')]),
(get_f_scan, events_file, [
('nii_path', 'timecourse_file'),
('task', 'task'),
('scan_path', 'scan_dir')
]),
(get_f_scan, find_physio, [('nii_path', 'nii_path')]),
(events_file, datasink, [('out_file', 'func.@events')]),
(find_physio, datasink, [('physiofile', 'func.@physio')]),
(find_physio, datasink, [('meta_physiofile', 'func.@meta_physio')]),
(get_f_scan, events_file, [('events_name', 'out_file')]),
(get_f_scan, datasink, [(('subject_session',ss_to_path), 'container')]),
]
workflow_connections = []

if realign == "space":
realigner = pe.Node(interface=spm.Realign(), name="realigner")
realigner.inputs.register_to_mean = True
workflow_connections.extend([
(dummy_scans, realigner, [('out_file', 'in_file')]),
])
#ADDING SELECTABLE NODES AND EXTENDING WORKFLOW AS APPROPRIATE:
s_biascorrect, f_biascorrect = real_size_nodes()

if not functional_scan_types.any():
functional_registration_method = False

if functional_scan_types.any():
find_physio = pe.Node(name='find_physio', interface=util.Function(function=corresponding_physiofile,input_names=inspect.getfullargspec(corresponding_physiofile)[0], output_names=['physiofile','meta_physiofile']))

elif realign == "spacetime":
realigner = pe.Node(interface=nipy.SpaceTimeRealigner(), name="realigner")
realigner.inputs.slice_times = "asc_alt_2"
realigner.inputs.tr = tr
realigner.inputs.slice_info = 3 #3 for coronal slices (2 for horizontal, 1 for sagittal)
workflow_connections.extend([
(dummy_scans, realigner, [('out_file', 'in_file')]),
(find_physio, datasink, [('physiofile', 'func.@physio')]),
(find_physio, datasink, [('meta_physiofile', 'func.@meta_physio')]),
])

elif realign == "time":
realigner = pe.Node(interface=fsl.SliceTimer(), name="slicetimer")
realigner.inputs.time_repetition = tr
get_f_scan = pe.Node(name='get_f_scan', interface=util.Function(function=get_bids_scan,input_names=inspect.getfullargspec(get_bids_scan)[0], output_names=['scan_path','scan_type','task', 'nii_path', 'nii_name', 'events_name', 'subject_session', 'metadata_filename', 'dict_slice', 'ind_type']))
get_f_scan.inputs.ignore_exception = True
get_f_scan.inputs.data_selection = data_selection
get_f_scan.inputs.bids_base = bids_base
get_f_scan.iterables = ("ind_type", func_ind)

dummy_scans = pe.Node(name='dummy_scans', interface=util.Function(function=force_dummy_scans,input_names=inspect.getfullargspec(force_dummy_scans)[0], output_names=['out_file','deleted_scans']))
dummy_scans.inputs.desired_dummy_scans = enforce_dummy_scans

events_file = pe.Node(name='events_file', interface=util.Function(function=write_bids_events_file,input_names=inspect.getfullargspec(write_bids_events_file)[0], output_names=['out_file']))

workflow_connections.extend([
(dummy_scans, realigner, [('out_file', 'in_file')]),
(get_f_scan, dummy_scans, [('nii_path', 'in_file')]),
(dummy_scans, events_file, [('deleted_scans', 'forced_dummy_scans')]),
(get_f_scan, events_file, [
('nii_path', 'timecourse_file'),
('task', 'task'),
('scan_path', 'scan_dir')
]),
(get_f_scan, find_physio, [('nii_path', 'nii_path')]),
(events_file, datasink, [('out_file', 'func.@events')]),
(get_f_scan, events_file, [('events_name', 'out_file')]),
(get_f_scan, datasink, [(('subject_session',ss_to_path), 'container')]),
])

#ADDING SELECTABLE NODES AND EXTENDING WORKFLOW AS APPROPRIATE:
s_biascorrect, f_biascorrect = real_size_nodes()
if realign == "space":
realigner = pe.Node(interface=spm.Realign(), name="realigner")
realigner.inputs.register_to_mean = True
workflow_connections.extend([
(dummy_scans, realigner, [('out_file', 'in_file')]),
])

elif realign == "spacetime":
realigner = pe.Node(interface=nipy.SpaceTimeRealigner(), name="realigner")
realigner.inputs.slice_times = "asc_alt_2"
realigner.inputs.tr = tr
realigner.inputs.slice_info = 3 #3 for coronal slices (2 for horizontal, 1 for sagittal)
workflow_connections.extend([
(dummy_scans, realigner, [('out_file', 'in_file')]),
])

elif realign == "time":
realigner = pe.Node(interface=fsl.SliceTimer(), name="slicetimer")
realigner.inputs.time_repetition = tr
workflow_connections.extend([
(dummy_scans, realigner, [('out_file', 'in_file')]),
])

if functional_blur_xy:
blur = pe.Node(interface=afni.preprocess.BlurToFWHM(), name="blur")
blur.inputs.fwhmxy = functional_blur_xy
workflow_connections.extend([
(get_f_scan, blur, [('nii_name','out_file')]),
(f_warp, blur, [('output_image', 'in_file')]),
(blur, datasink, [('out_file', 'func')]),
])
else:
workflow_connections.extend([
(get_f_scan, f_warp, [('nii_name','output_image')]),
(f_warp, datasink, [('output_image', 'func')]),
])


if structural_scan_types.any():
s_data_selection = deepcopy(data_selection)
Expand All @@ -473,6 +497,8 @@ def generic(bids_base, template,
get_s_scan.inputs.ignore_exception = True
get_s_scan.inputs.data_selection = s_data_selection
get_s_scan.inputs.bids_base = bids_base
if not functional_scan_types.any():
get_s_scan.iterables = ("ind_type", struct_ind)

s_register, s_warp, f_register, f_warp = generic_registration(template,
structural_mask=registration_mask,
Expand All @@ -493,8 +519,12 @@ def generic(bids_base, template,
(s_warp, datasink, [('output_image', 'anat')]),
])

if functional_scan_types.any():
workflow_connections.extend([
(get_f_scan, get_s_scan, [('subject_session', 'selector')]),
])

workflow_connections.extend([
(get_f_scan, get_s_scan, [('subject_session', 'selector')]),
(get_s_scan, s_warp, [('nii_name','output_image')]),
(get_s_scan, s_biascorrect, [('nii_path', 'input_image')]),
])
Expand Down Expand Up @@ -598,19 +628,6 @@ def generic(bids_base, template,
])


if functional_blur_xy:
blur = pe.Node(interface=afni.preprocess.BlurToFWHM(), name="blur")
blur.inputs.fwhmxy = functional_blur_xy
workflow_connections.extend([
(get_f_scan, blur, [('nii_name','out_file')]),
(f_warp, blur, [('output_image', 'in_file')]),
(blur, datasink, [('out_file', 'func')]),
])
else:
workflow_connections.extend([
(get_f_scan, f_warp, [('nii_name','output_image')]),
(f_warp, datasink, [('output_image', 'func')]),
])


workflow_config = {'execution': {'crashdump_dir': path.join(out_base,'crashdump'),}}
Expand Down Expand Up @@ -743,8 +760,11 @@ def common_select(bids_base, out_base, workflow_name, template, registration_mas
functional_scan_types = data_selection.loc[data_selection['type'] == 'func']['acq'].values
structural_scan_types = data_selection.loc[data_selection['type'] == 'anat']['acq'].values
except KeyError:
functional_scan_types = data_selection.loc[data_selection['datatype'] == 'func']['acquisition'].values
structural_scan_types = data_selection.loc[data_selection['datatype'] == 'anat']['acquisition'].values
try:
functional_scan_types = data_selection.loc[data_selection['datatype'] == 'func']['acquisition'].values
structural_scan_types = data_selection.loc[data_selection['datatype'] == 'anat']['acquisition'].values
except KeyError:
pass
# we start to define nipype workflow elements (nodes, connections, meta)
subjects_sessions = data_selection[["subject","session"]].drop_duplicates().values.tolist()

Expand Down

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