Skip to content

Commit

Permalink
Correcting bugs
Browse files Browse the repository at this point in the history
  • Loading branch information
@elodiegermani1
elodiegermani1 committed Feb 13, 2024
1 parent b527df1 commit 60e17d8
Show file tree
Hide file tree
Showing 2 changed files with 97 additions and 127 deletions.
2 changes: 1 addition & 1 deletion narps_open/pipelines/__init__.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -16,7 +16,7 @@
'0JO0': None,
'16IN': None,
'1K0E': None,
'1KB2': None,
'1KB2': 'PipelineTeam1KB2',
'1P0Y': None,
'27SS': None,
'2T6S': 'PipelineTeam2T6S',
Expand Down
222 changes: 96 additions & 126 deletions narps_open/pipelines/team_1KB2.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -485,21 +485,23 @@ def get_run_level_analysis(self):
])

return l1_analysis

def get_registration(self):
""" Return a Nipype workflow describing the registration part of the pipeline """


def get_subject_level_analysis(self):
""" Return a Nipype workflow describing the subject level analysis part of the pipeline """

# [INFO] The following part stays the same for all pipelines

# Infosource Node - To iterate on subjects
info_source = Node(
IdentityInterface(
fields = ['subject_id', 'contrast_id', 'run_id'],
fields = ['subject_id', 'contrast_id'],
),
name='info_source',
)
info_source.iterables = [
('subject_id', self.subject_list),
('contrast_id', self.contrast_list),
('run_id', self.run_list)
('contrast_id', self.contrast_list)
]

# Templates to select files node
Expand All @@ -508,14 +510,14 @@ def get_registration(self):
'cope': join(
self.directories.output_dir,
'run_level_analysis',
'_run_id_{run_id}_subject_id_{subject_id}',
'_contrast_id_{contrast_id}_run_id_*_subject_id_{subject_id}',
'results',
'cope{contrast_id}.nii.gz',
),
'varcope': join(
self.directories.output_dir,
'run_level_analysis',
'_run_id_{run_id}_subject_id_{subject_id}',
'_contrast_id_{contrast_id}_run_id_*_subject_id_{subject_id}',
'results',
'varcope{contrast_id}.nii.gz',
),
Expand Down Expand Up @@ -549,7 +551,15 @@ def get_registration(self):
),
name = 'data_sink'
)


# Generate design matrix
specify_model = Node(
L2Model(
num_copes = len(self.run_list)
),
name='l2model'
)

warpall_cope = MapNode(
ApplyWarp(
interp='spline'
Expand All @@ -572,110 +582,6 @@ def get_registration(self):
warpall_varcope.inputs.ref_file = Info.standard_image('MNI152_T1_2mm_brain.nii.gz')
warpall_varcope.inputs.mask_file = Info.standard_image('MNI152_T1_2mm_brain_mask.nii.gz')

# Create registration workflow and connect its nodes
registration = Workflow(
base_dir = self.directories.working_dir,
name = "registration"
)

registration.connect([
(
info_source,
select_files,
[('subject_id', 'subject_id'),
('run_id', 'run_id'),
('contrast_id', 'contrast_id')]
),
(
select_files,
warpall_cope,
[('func2anat_transform', 'premat'),
('anat2target_transform', 'field_file'),
('cope', 'in_file')]
),
(
select_files,
warpall_varcope,
[('func2anat_transform', 'premat'),
('anat2target_transform', 'field_file'),
('varcope', 'in_file')]
),
(
warpall_cope,
data_sink,
[('out_file', 'registration.@reg_cope')]
),
(
warpall_varcope,
data_sink,
[('out_file', 'registration.@reg_varcope')]
)
])

return registration


def get_subject_level_analysis(self):
""" Return a Nipype workflow describing the subject level analysis part of the pipeline """

# [INFO] The following part stays the same for all pipelines

# Infosource Node - To iterate on subjects
info_source = Node(
IdentityInterface(
fields = ['subject_id', 'contrast_id'],
),
name='info_source',
)
info_source.iterables = [
('subject_id', self.subject_list),
('contrast_id', self.contrast_list)
]

# Templates to select files node
# [TODO] Change the name of the files depending on the filenames of results of preprocessing
templates = {
'cope': join(
self.directories.output_dir,
'registration',
'_contrast_id_{contrast_id}_run_id_*_subject_id_{subject_id}',
'_warpall_cope0',
'cope{contrast_id}_warp.nii.gz',
),
'varcope': join(
self.directories.output_dir,
'registration',
'_contrast_id_{contrast_id}_run_id_*_subject_id_{subject_id}',
'_warpall_varcope0',
'varcope{contrast_id}_warp.nii.gz',
)
}

# SelectFiles node - to select necessary files
select_files = Node(
SelectFiles(
templates,
base_directory = self.directories.dataset_dir
),
name = 'select_files'
)

# DataSink Node - store the wanted results in the wanted repository
data_sink = Node(
DataSink(
base_directory = self.directories.output_dir
),
name = 'data_sink'
)

# Generate design matrix
specify_model = Node(
L2Model(
num_copes = len(self.run_list)
),
name='l2model'
)

# Merge copes and varcopes files for each subject
merge_copes = Node(
Merge(
Expand Down Expand Up @@ -717,13 +623,27 @@ def get_subject_level_analysis(self):
),
(
select_files,
warpall_cope,
[('func2anat_transform', 'premat'),
('anat2target_transform', 'field_file'),
('cope', 'in_file')]
),
(
select_files,
warpall_varcope,
[('func2anat_transform', 'premat'),
('anat2target_transform', 'field_file'),
('varcope', 'in_file')]
),
(
warpall_cope,
merge_copes,
[('cope', 'in_files')]
[('out_file', 'in_files')]
),
(
select_files,
warpall_varcope,
merge_varcopes,
[('varcope', 'in_files')]
[('out_file', 'in_files')]
),
(
merge_copes,
Expand Down Expand Up @@ -854,8 +774,11 @@ def get_regressors(
# with a list of the size of the number of participants
if method == 'equalRange':
regressors = dict(group_mean = [1 for i in range(len(equal_range_id))])
group = [1 for i in equal_range_id]

elif method == 'equalIndifference':
regressors = dict(group_mean = [1 for i in range(len(equal_indifference_id))])
group = [1 for i in equal_indifference_id]

# For two sample t-test, creates 2 lists:
# - one for equal range group,
Expand All @@ -880,7 +803,9 @@ def get_regressors(
equalIndifference = equalIndifference_reg
)

return regressors
group = [1 if i == 1 else 2 for i in equalRange_reg]

return regressors, group

def get_group_level_analysis(self):
"""
Expand Down Expand Up @@ -934,22 +859,20 @@ def get_group_level_analysis_sub_workflow(self, method):
}
select_files = Node(
SelectFiles(
templates,
base_directory = self.directories.results_dir,
template,
base_directory = self.directories.dataset_dir,
force_list = True
),
name = 'select_files',
)

# Datasink node - to save important files
data_sink = Node(
DataSink(
base_directory = self.directories.output_dir
),
DataSink(base_directory = self.directories.output_dir),
name = 'data_sink',
)

contrasts = Node(
subgroups_contrasts = Node(
Function(
input_names=['copes', 'varcopes', 'subject_ids', 'participants_file'],
output_names=[
Expand All @@ -975,7 +898,10 @@ def get_group_level_analysis_sub_workflow(self, method):
'method',
'subject_list',
],
output_names = ['regressors'],
output_names = [
'regressors',
'group'
],
function = self.get_regressors,
),
name = 'regs',
Expand Down Expand Up @@ -1095,12 +1021,12 @@ def get_group_level_analysis_sub_workflow(self, method):
group_level_analysis.connect([
(
subgroups_contrasts,
merge_copes_3rdlevel,
merge_copes,
[('copes_equalRange', 'in_files')]
),
(
subgroups_contrasts,
merge_varcopes_3rdlevel,
merge_varcopes,
[('varcopes_equalRange', 'in_files')]
)
])
Expand Down Expand Up @@ -1168,3 +1094,47 @@ def get_group_level_analysis_sub_workflow(self, method):

# [INFO] Here we simply return the created workflow
return group_level_analysis

def get_hypotheses_outputs(self):
""" Return the names of the files used by the team to answer the hypotheses of NARPS. """

nb_sub = len(self.subject_list)
files = [
join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
'_contrast_id_1', 'randomise_tfce_corrp_tstat1.nii.gz'),
join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
'_contrast_id_1', 'zstat1.nii.gz'),
join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
'_contrast_id_1', 'randomise_tfce_corrp_tstat1.nii.gz'),
join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
'_contrast_id_1', 'zstat1.nii.gz'),
join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
'_contrast_id_1', 'randomise_tfce_corrp_tstat1.nii.gz'),
join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
'_contrast_id_1', 'zstat1.nii.gz'),
join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
'_contrast_id_1', 'randomise_tfce_corrp_tstat1.nii.gz'),
join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
'_contrast_id_1', 'zstat1.nii.gz'),
join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
'_contrast_id_2', 'randomise_tfce_corrp_tstat2.nii.gz'),
join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
'_contrast_id_2', 'zstat2.nii.gz'),
join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
'_contrast_id_2', 'randomise_tfce_corrp_tstat2.nii.gz'),
join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
'_contrast_id_2', 'zstat2.nii.gz'),
join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
'_contrast_id_2', 'randomise_tfce_corrp_tstat1.nii.gz'),
join(f'group_level_analysis_equalIndifference_nsub_{nb_sub}',
'_contrast_id_2', 'zstat1.nii.gz'),
join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
'_contrast_id_2', 'randomise_tfce_corrp_tstat1.nii.gz'),
join(f'group_level_analysis_equalRange_nsub_{nb_sub}',
'_contrast_id_2', 'zstat1.nii.gz'),
join(f'group_level_analysis_groupComp_nsub_{nb_sub}',
'_contrast_id_2', 'randomise_tfce_corrp_tstat1.nii.gz'),
join(f'group_level_analysis_groupComp_nsub_{nb_sub}',
'_contrast_id_2', 'zstat1.nii.gz')
]
return [join(self.directories.output_dir, f) for f in files]

0 comments on commit 60e17d8

Please sign in to comment.