def test_tnet_make_parcellation():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
bids_suffix='preproc',
bids_tags={
'sub': '001',
'task': 'a',
'run': 'alpha'
},
raw_data_exists=False)
# Set the confound pipeline in fmriprep
tnet.make_parcellation('gordon2014_333+sub-maxprob-thr25-1mm')
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
bids_suffix='preproc',
bids_tags={
'sub': '001',
'task': 'a',
'run': 'alpha'
},
raw_data_exists=False)
tnet.make_parcellation('gordon2014_333')
tnet.load_data('parcellation')
# Hard coded facts about dummy data
assert tnet.parcellation_data_[0].shape == (2, 333)
def test_tnet_make_parcellation():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
last_analysis_step='preproc',
subjects='001',
tasks='a',
runs='alpha',
raw_data_exists=False)
# Set the confound pipeline in fmriprep
tnet.make_parcellation('gordon2014_333+sub-maxprob-thr25-1mm')
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
last_analysis_step='preproc',
subjects='001',
tasks='a',
runs='alpha',
raw_data_exists=False)
tnet.make_parcellation('gordon2014_333')
tnet.load_parcellation_data()
# Hard coded facts about dummy data
assert tnet.parcellation_data_.max() == 1
assert tnet.parcellation_data_.shape == (1, 333, 2)
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
last_analysis_step='preproc',
subjects='001',
tasks='a',
runs='alpha',
raw_data_exists=False)
def test_define():
dataset_path = teneto.__path__[0] + '/data/testdata/dummybids/'
tnet = teneto.TenetoBIDS(dataset_path,
pipeline='fmriprep',
raw_data_exists=False)
assert len(tnet.get_selected_files(quiet=1)) == 6
tnet = teneto.TenetoBIDS(dataset_path,
pipeline='fmriprep',
raw_data_exists=False)
assert len(tnet.get_selected_files(quiet=1, forfile={'sub': '001'})) == 3
fname = 'sub-001_task-a_run-beta_bold_preproc.nii.gz'
assert len(tnet.get_selected_files(quiet=1, forfile=fname)) == 1
def test_get_pipeline_subdir_alternatives():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests', bids_tags={'task': 'a'}, raw_data_exists=True)
subdir = tnet.get_pipeline_subdir_alternatives()
if not 'parcellation' in subdir:
raise AssertionError()
if not 'tvc' in subdir:
raise AssertionError()
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', bids_tags={'task': 'a'}, raw_data_exists=True)
subdir = tnet.get_pipeline_subdir_alternatives()
if not subdir is None:
raise AssertionError()
def test_tnet_derive():
# load parc file with data
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
pipeline_subdir='parcellation',
bids_suffix='roi',
bids_tags={
'sub': '001',
'task': 'a',
'run': 'alpha'
},
raw_data_exists=False)
tnet.load_data('parcellation')
tnet.set_confound_pipeline('fmriprep')
# Turn the confound_corr_report to True once matplotlib works withconcurrent
tnet.derive({
'method': 'jackknife',
'dimord': 'node,time'
},
update_pipeline=True,
confound_corr_report=False)
tnet.load_data('tvc')
parcdata = tnet.parcellation_data_[0]
parcdata.drop('0', axis=1, inplace=True)
R_jc = parcdata.transpose().corr().values[0, 1] * -1
jc = float(tnet.tvc_data_[0][(tnet.tvc_data_[0]['i'] == 0)
& (tnet.tvc_data_[0]['j'] == 1) &
(tnet.tvc_data_[0]['t'] == 0)]['weight'])
assert np.round(R_jc, 12) == np.round(jc, 12)
def test_tnet_scrubbing_and_spline():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
pipeline_subdir='parcellation',
bids_suffix='roi',
bids_tags={
'sub': '001',
'task': 'a',
'run': 'alpha'
},
raw_data_exists=False)
# Set the confound pipeline in fmriprep
tnet.load_data('parcellation')
dat_orig = np.squeeze(tnet.parcellation_data_[0].values)
tnet.set_confound_pipeline('fmriprep')
alt = tnet.get_confound_alternatives()
tnet.set_exclusion_timepoint('confound1', '>1', replace_with='cubicspline')
tnet.load_data('parcellation')
dat_scrub = tnet.parcellation_data_[0].values
targ = np.array([[0, 0, 1, 1], [4, 5, 4, 5]])
# Make sure there is a difference
assert np.sum(dat_scrub != dat_orig)
# Show that the difference between the original data at scrubbed time point is larger in data_orig
assert np.sum(
np.abs(np.diff(dat_orig[0])) - np.abs(np.diff(dat_scrub[0]))) > 0
def test_halftests():
#these tests could be made better
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
tasks='a',
raw_data_exists=False)
tnet.get_space_alternatives()
def test_tnet_derive_with_removeconfounds():
# load parc file with data
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
pipeline_subdir='parcellation',
bids_suffix='roi',
bids_tags={
'sub': '001',
'task': 'a',
'run': '01'
},
raw_data_exists=False)
# Set the confound pipeline in fmriprep
tnet.set_confound_pipeline('fmriprep')
alt = tnet.get_confound_alternatives()
if not 'confound1' in alt:
raise AssertionError()
if not 'confound2' in alt:
raise AssertionError()
# Set the confounds
tnet.set_confounds('confound1')
# Remove confounds
tnet.removeconfounds(transpose=True)
f = tnet.get_selected_files()[0]
f = f.replace('.tsv', '.json')
with open(f) as fs:
sidecar = json.load(fs)
if not 'confoundremoval' in sidecar:
raise AssertionError()
def test_tnet_checksidecar():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
bids_suffix='bold',
bids_tags={
'sub': '001',
'task': 'a',
'run': '01',
'desc': 'preproc'
},
raw_data_exists=False)
tnet.make_parcellation(atlas='Schaefer2018',
atlas_desc='400Parcels17Networks')
tnet.load_data('parcellation')
tnet.set_confound_pipeline('fmriprep')
tnet.set_exclusion_timepoint('confound1', '<=0', replace_with='nan')
with open(
teneto.__path__[0] +
'/data/testdata/dummybids/derivatives/teneto_' +
teneto.__version__ +
'/sub-001/func/parcellation/sub-001_task-a_run-01_desc-preproc_roi.json'
) as fs:
sidecar = json.load(fs)
# Check both steps are in sidecar
if not 'parcellation' in sidecar.keys():
raise AssertionError()
if not 'scrubbed_timepoints' in sidecar.keys():
raise AssertionError()
def test_communitydetection():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
pipeline_subdir='tvc',
last_analysis_step='tvc',
subjects='001',
tasks='b',
runs='alpha',
raw_data_exists=False)
community_detection_params = {
'resolution_parameter': 1,
'interslice_weight': 0,
'quality_function': 'ReichardtBornholdt2006'
}
tnet.communitydetection(community_detection_params, 'temporal')
# Compensating for data not being in a versioen directory
tnet.set_pipeline('teneto_' + teneto.__version__)
tnet.load_community_data('temporal')
C = np.squeeze(tnet.community_data_)
assert C[0, 0] == C[1, 0] == C[2, 0]
assert C[3, 0] == C[4, 0] == C[5, 0]
assert C[0, 2] == C[1, 2] == C[2, 2] == C[3, 2]
assert C[4, 2] == C[5, 2]
assert C[3, 0] != C[0, 0]
assert C[4, 2] != C[0, 2]
def test_define_run_then_sub():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
runs='alpha',
raw_data_exists=False)
assert len(tnet.get_selected_files(quiet=1)) == 4
tnet.set_subjects('001')
assert len(tnet.get_selected_files(quiet=1)) == 2
def test_set_space_error():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
tasks='a',
raw_data_exists=False,
njobs=1)
with pytest.raises(ValueError):
tnet.set_space('bla')
def test_set_bad_subjects():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
tasks='a',
raw_data_exists=False)
tnet.set_bad_subjects('001')
tnet.set_bad_subjects(['002'])
assert len(tnet.bad_subjects) == 2
def test_define_task_then_run():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
tasks='a',
raw_data_exists=False)
assert len(tnet.get_selected_files(quiet=1)) == 4
tnet.set_runs('beta')
assert len(tnet.get_selected_files(quiet=1)) == 2
def test_define_run_then_sub():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
bids_tags={'run': 'alpha'},
raw_data_exists=False)
assert len(tnet.get_selected_files(quiet=1)) == 4
tnet.set_bids_tags({'sub': '001'})
assert len(tnet.get_selected_files(quiet=1)) == 2
def test_define_sub_then_task():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
subjects='001',
raw_data_exists=False)
assert len(tnet.get_selected_files(quiet=1)) == 3
tnet.set_tasks('a')
assert len(tnet.get_selected_files(quiet=1)) == 2
def test_define_task_then_run():
tnet = teneto.TenetoBIDS(teneto.__path__[
0] + '/data/testdata/dummybids/', pipeline='fmriprep', bids_tags={'task': 'a'}, raw_data_exists=False)
if not len(tnet.get_selected_files(quiet=1)) == 4:
raise AssertionError()
tnet.set_bids_tags({'run': '02'})
if not len(tnet.get_selected_files(quiet=1)) == 2:
raise AssertionError()
def test_get_pipeline_alternatives():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests', bids_tags={'task': 'a'}, raw_data_exists=False)
pipeline = tnet.get_pipeline_alternatives()
if not 'fmriprep' in pipeline:
raise AssertionError()
if not 'teneto-tests' in pipeline:
raise AssertionError()
def test_get_pipeline_alternatives():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
tasks='a',
raw_data_exists=False)
pipeline = tnet.get_pipeline_alternatives()
assert 'fmriprep' in pipeline
assert 'teneto-tests' in pipeline
def test_tnet_io():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='fmriprep',
bids_suffix='preproc', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.save_aspickle(teneto.__path__[0] +
'/data/testdata/dummybids/teneosave.pkl')
tnet2 = teneto.TenetoBIDS.load_frompickle(
teneto.__path__[0] + '/data/testdata/dummybids/teneosave.pkl')
if not tnet2.get_selected_files() == tnet.get_selected_files():
raise AssertionError()
def test_communitydetection():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='tvc', bids_suffix='tvcconn', bids_tags={'sub': '001', 'task': 'b', 'run': 'alpha'}, raw_data_exists=False)
community_detection_params = {'resolution': 1,
'intersliceweight': 0}
tnet.communitydetection(community_detection_params, 'temporal')
# Compensating for data not being in a versioen directory
tnet.set_pipeline('teneto_' + teneto.__version__)
tnet.load_data('communities')
def test_make_fc_and_tvc():
# Load parc data, make FC JC method
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.load_data('parcellation')
r = tnet.make_functional_connectivity(returngroup=True)[0, 1]
fc_files = tnet.get_selected_files(pipeline='functionalconnectivity')
if not '_conn.tsv' in fc_files[0]:
raise AssertionError()
if not len(fc_files) == 1:
raise AssertionError()
R = tnet.parcellation_data_[0].transpose().corr().values[0, 1]
tnet.derive_temporalnetwork({'method': 'jackknife', 'dimord': 'node,time',
'postpro': 'standardize'}, update_pipeline=True, confound_corr_report=False)
tnet.load_data('tvc')
JC = tnet.tvc_data_[0].iloc[0].values[-1]
# Load parc data, make FC JC method with FC dual weighting
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.derive_temporalnetwork({'method': 'jackknife', 'dimord': 'node,time', 'weight-mean': 'from-subject-fc',
'weight-var': 'from-subject-fc'}, update_pipeline=True, confound_corr_report=False)
tnet.load_data('tvc')
JCw = tnet.tvc_data_[0].iloc[0].values[-1]
# Load parc data, make FC JC method with FC mean weighting
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.derive_temporalnetwork({'method': 'jackknife', 'dimord': 'node,time',
'weight-mean': 'from-subject-fc'}, update_pipeline=True, confound_corr_report=False)
tnet.load_data('tvc')
JCm = tnet.tvc_data_[0].iloc[0].values[-1]
# Load parc data, make FC JC method with FC variance weighting
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.derive_temporalnetwork({'method': 'jackknife', 'dimord': 'node,time',
'weight-var': 'from-subject-fc'}, update_pipeline=True, confound_corr_report=False)
tnet.load_data('tvc')
JCv = tnet.tvc_data_[0].iloc[0].values[-1]
if not np.round(JCw, 15) == np.round((JC*r)+R, 15):
raise AssertionError()
if not np.round(JCv, 15) == np.round((JC*r), 15):
raise AssertionError()
if not np.round(JCm, 15) == np.round((JC)+R, 15):
raise AssertionError()
def test_tnet_scrubbing():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
# Set the confound pipeline in fmriprep
tnet.set_confound_pipeline('fmriprep')
tnet.set_exclusion_timepoint('confound1', '>1', replace_with='nan')
tnet.load_data('parcellation')
dat = np.where(np.isnan(np.squeeze(tnet.parcellation_data_[0].values)))
targ = np.array([[0, 0, 1, 1], [4, 5, 4, 5]])
if not np.all(targ == dat):
raise AssertionError()
def test_savesnapshot():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
pipeline_subdir='parcellation',
bids_suffix='roi',
bids_tags={
'sub': '001',
'task': 'a',
'run': '01'
},
raw_data_exists=False)
tnet.save_tenetobids_snapshot(teneto.__path__[0])
with open(teneto.__path__[0] + '/TenetoBIDS_snapshot.json') as f:
params = json.load(f)
tnet2 = teneto.TenetoBIDS(**params)
for n in tnet2.__dict__:
if tnet.__dict__[n] != tnet2.__dict__[n]:
raise AssertionError()
if tnet2.__dict__.keys() != tnet.__dict__.keys():
raise AssertionError()
def test_networkmeasure():
# calculate and load a network measure
bids_path = teneto.__path__[0] + '/data/testdata/dummybids/'
pipeline = 'teneto_' + teneto.__version__
tags = {'sub': '001', 'task': 'a', 'run': 'alpha'}
tnet = teneto.TenetoBIDS(bids_path, pipeline=pipeline, pipeline_subdir='tvc',
bids_suffix='tvcconn', bids_tags=tags,
raw_data_exists=False)
tnet.networkmeasures('volatility', {'calc': 'time'}, tag='time')
tnet.load_data('temporalnetwork', measure='volatility', tag='time')
if not tnet.temporalnetwork_data_['volatility'][0].shape == (19, 1):
raise AssertionError()
def test_setanalysisstep():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto-tests',
tasks='a',
raw_data_exists=False)
tnet.set_analysis_steps('a')
tnet.set_analysis_steps('b', add_step=True)
assert tnet.analysis_steps == ['a', 'b']
tnet.set_analysis_steps(['a', 'b'])
assert tnet.analysis_steps == ['a', 'b']
tnet.set_analysis_steps(['c', 'd'], add_step=True)
assert tnet.analysis_steps == ['a', 'b', 'c', 'd']
def test_tnet_scrubbing_and_exclusion_options():
# <=
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.set_confound_pipeline('fmriprep')
tnet.set_exclusion_timepoint('confound1', '<=0', replace_with='nan')
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.set_confound_pipeline('fmriprep')
tnet.set_exclusion_file('confound2', '<=1')
# <
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.set_confound_pipeline('fmriprep')
tnet.set_exclusion_timepoint('confound1', '<0', replace_with='nan')
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.set_confound_pipeline('fmriprep')
tnet.set_exclusion_file('confound2', '<1')
# >=
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.set_confound_pipeline('fmriprep')
tnet.set_exclusion_timepoint('confound2', '>=2', replace_with='nan')
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
tnet.set_confound_pipeline('fmriprep')
tnet.set_exclusion_file('confound2', '>=1')
def test_tnet_io():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='fmriprep',
last_analysis_step='preproc',
subjects='001',
tasks='a',
runs='alpha',
raw_data_exists=False)
tnet.save_aspickle(teneto.__path__[0] +
'/data/testdata/dummybids/teneosave.pkl')
tnet2 = teneto.TenetoBIDS.load_frompickle(
teneto.__path__[0] + '/data/testdata/dummybids/teneosave.pkl')
assert tnet2.get_selected_files() == tnet.get_selected_files()
def test_networkmeasure():
# calculate and load a network measure
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/',
pipeline='teneto_' + teneto.__version__,
pipeline_subdir='tvc',
last_analysis_step='tvc',
subjects='001',
tasks='a',
runs='alpha',
raw_data_exists=False)
tnet.networkmeasures('volatility', {'calc': 'time'}, save_tag='time')
tnet.load_network_measure('volatility', tag='time')
assert tnet.networkmeasure_.shape == (1, 19)
def test_tnet_set_bad_files():
tnet = teneto.TenetoBIDS(teneto.__path__[0] + '/data/testdata/dummybids/', pipeline='teneto-tests',
pipeline_subdir='parcellation', bids_suffix='roi', bids_tags={'sub': '001', 'task': 'a', 'run': 'alpha'}, raw_data_exists=False)
# Set the confound pipeline in fmriprep
tnet.load_data('parcellation')
tnet.set_confound_pipeline('fmriprep')
tnet.set_exclusion_file('confound2', '>0.5')
if not len(tnet.bad_files) == 1:
raise AssertionError()
if not tnet.bad_files[0] == tnet.BIDS_dir + 'derivatives/' + tnet.pipeline + \
'/sub-001/func/' + tnet.pipeline_subdir + \
'/sub-001_task-a_run-alpha_roi.tsv':
raise AssertionError()
