def assertStatEqual(self,
stat,
dataset_name,
target,
study_name,
subject=None,
visit=None,
frequency='per_session'):
try:
NiAnalysisNodeMixin.load_module('mrtrix')
except NiAnalysisModulesNotInstalledException:
pass
val = float(
sp.check_output('mrstats {} -output {}'.format(
self.output_file_path(dataset_name,
study_name,
subject=subject,
visit=visit,
frequency=frequency), stat),
shell=True))
self.assertEqual(
val, target,
("{} value of '{}' ({}) does not equal target ({}) "
"for subject {} visit {}".format(stat, dataset_name, val, target,
subject, visit)))
def test_multi_multi_study(self):
study = self.create_study(
MultiMultiStudy, 'multi_multi',
[DatasetMatch('ss1_x', mrtrix_format, 'ones'),
DatasetMatch('ss1_y', mrtrix_format, 'ones'),
DatasetMatch('full_a', mrtrix_format, 'ones'),
DatasetMatch('full_b', mrtrix_format, 'ones'),
DatasetMatch('full_c', mrtrix_format, 'ones'),
DatasetMatch('partial_a', mrtrix_format, 'ones'),
DatasetMatch('partial_b', mrtrix_format, 'ones'),
DatasetMatch('partial_c', mrtrix_format, 'ones')],
options=[Option('full_required_op', 'product'),
Option('partial_ss2_product_op', 'product')])
g = study.data('g')[0]
if self.mrtrix_req is not None:
NiAnalysisNodeMixin.load_module(*self.mrtrix_req)
try:
g_mean = float(sp.check_output(
'mrstats {} -output mean'.format(g.path),
shell=True))
self.assertEqual(g_mean, 11.0)
finally:
if self.mrtrix_req is not None:
NiAnalysisNodeMixin.unload_module(*self.mrtrix_req)
# Test option values in MultiStudy
self.assertEqual(study.data('full_p1'), 100)
self.assertEqual(study.data('full_p2'), '200')
self.assertEqual(study.data('full_p3'), 300.0)
self.assertEqual(study.data('full_q1'), 150)
self.assertEqual(study.data('full_q2'), '250')
self.assertEqual(study.data('full_required_op'),
'product')
# Test option values in SubStudy
ss1 = study.sub_study('full').sub_study('ss1')
self.assertEqual(ss1.data('o1'), 100)
self.assertEqual(ss1.data('o2'), '200')
self.assertEqual(ss1.data('o3'), 300.0)
ss2 = study.sub_study('full').sub_study('ss2')
self.assertEqual(ss2.data('o1'), 150)
self.assertEqual(ss2.data('o2'), '250')
self.assertEqual(ss2.data('o3'), 300.0)
self.assertEqual(ss2.data('product_op'), 'product')
# Test option values in MultiStudy
self.assertEqual(study.data('partial_p1'), 1000)
self.assertEqual(study.data('partial_ss1_o2'), '2')
self.assertEqual(study.data('partial_ss1_o3'), 3.0)
self.assertEqual(study.data('partial_ss2_o2'), '20')
self.assertEqual(study.data('partial_ss2_o3'), 30.0)
self.assertEqual(
study.partial_ss2_product_op, 'product')
# Test option values in SubStudy
ss1 = study.sub_study('partial').sub_study('ss1')
self.assertEqual(ss1.data('o1'), 1000)
self.assertEqual(ss1.data('o2'), '2')
self.assertEqual(ss1.data('o3'), 3.0)
ss2 = study.sub_study('partial').sub_study('ss2')
self.assertEqual(ss2.data('o1'), 1000)
self.assertEqual(ss2.data('o2'), '20')
self.assertEqual(ss2.data('o3'), 30.0)
self.assertEqual(ss2.data('product_op'), 'product')
def setUp(self):
super(TestMulti, self).setUp()
# Calculate MRtrix module required for 'mrstats' commands
try:
self.mrtrix_req = Requirement.best_requirement(
[mrtrix3_req], NiAnalysisNodeMixin.available_modules(),
NiAnalysisNodeMixin.preloaded_modules())
except NiAnalysisModulesNotInstalledException:
self.mrtrix_req = None
def test_partial_multi_study(self):
study = self.create_study(
PartialMultiStudy, 'partial',
[DatasetMatch('a', mrtrix_format, 'ones'),
DatasetMatch('b', mrtrix_format, 'ones'),
DatasetMatch('c', mrtrix_format, 'ones')],
options=[Option('ss2_product_op', 'product')])
ss1_z = study.data('ss1_z')[0]
ss2_y = study.data('ss2_y')[0]
ss2_z = study.data('ss2_z')[0]
if self.mrtrix_req is not None:
NiAnalysisNodeMixin.load_module(*self.mrtrix_req)
try:
ss1_z_mean = float(sp.check_output(
'mrstats {} -output mean'.format(ss1_z.path),
shell=True))
self.assertEqual(ss1_z_mean, 2.0)
ss2_y_mean = float(sp.check_output(
'mrstats {} -output mean'.format(ss2_y.path),
shell=True))
self.assertEqual(ss2_y_mean, 3.0)
ss2_z_mean = float(sp.check_output(
'mrstats {} -output mean'.format(ss2_z.path),
shell=True))
self.assertEqual(ss2_z_mean, 6.0)
finally:
if self.mrtrix_req is not None:
NiAnalysisNodeMixin.unload_module(*self.mrtrix_req)
# Test option values in MultiStudy
self.assertEqual(study.data('p1'), 1000)
self.assertEqual(study.data('ss1_o2'), '2')
self.assertEqual(study.data('ss1_o3'), 3.0)
self.assertEqual(study.data('ss2_o2'), '20')
self.assertEqual(study.data('ss2_o3'), 30.0)
self.assertEqual(study.data('ss2_product_op'), 'product')
# Test option values in SubStudy
ss1 = study.sub_study('ss1')
self.assertEqual(ss1.data('o1'), 1000)
self.assertEqual(ss1.data('o2'), '2')
self.assertEqual(ss1.data('o3'), 3.0)
ss2 = study.sub_study('ss2')
self.assertEqual(ss2.data('o1'), 1000)
self.assertEqual(ss2.data('o2'), '20')
self.assertEqual(ss2.data('o3'), 30.0)
self.assertEqual(ss2.data('product_op'), 'product')
def test_full_multi_study(self):
study = self.create_study(
FullMultiStudy, 'full',
[DatasetMatch('a', mrtrix_format, 'ones'),
DatasetMatch('b', mrtrix_format, 'ones'),
DatasetMatch('c', mrtrix_format, 'ones')],
options=[Option('required_op', 'product')])
d = study.data('d', subject_id='SUBJECT', visit_id='VISIT')
e = study.data('e')[0]
f = study.data('f')[0]
if self.mrtrix_req is not None:
NiAnalysisNodeMixin.load_module(*self.mrtrix_req)
try:
d_mean = float(sp.check_output(
'mrstats {} -output mean'.format(d.path),
shell=True))
self.assertEqual(d_mean, 2.0)
e_mean = float(sp.check_output(
'mrstats {} -output mean'.format(e.path),
shell=True))
self.assertEqual(e_mean, 3.0)
f_mean = float(sp.check_output(
'mrstats {} -output mean'.format(f.path),
shell=True))
self.assertEqual(f_mean, 6.0)
finally:
if self.mrtrix_req is not None:
NiAnalysisNodeMixin.unload_module(*self.mrtrix_req)
# Test option values in MultiStudy
self.assertEqual(study.data('p1'), 100)
self.assertEqual(study.data('p2'), '200')
self.assertEqual(study.data('p3'), 300.0)
self.assertEqual(study.data('q1'), 150)
self.assertEqual(study.data('q2'), '250')
self.assertEqual(study.data('required_op'), 'product')
# Test option values in SubStudy
ss1 = study.sub_study('ss1')
self.assertEqual(ss1.data('o1'), 100)
self.assertEqual(ss1.data('o2'), '200')
self.assertEqual(ss1.data('o3'), 300.0)
ss2 = study.sub_study('ss2')
self.assertEqual(ss2.data('o1'), 150)
self.assertEqual(ss2.data('o2'), '250')
self.assertEqual(ss2.data('o3'), 300.0)
self.assertEqual(ss2.data('product_op'), 'product')
def test_project_summary(self):
self.study.data('project_summary')
# Get mean value from resultant image (should be the same as the
# number of sessions as the original image is full of ones and
# all sessions have been summed together
if self.mrtrix_req is not None:
NiAnalysisNodeMixin.load_module(*self.mrtrix_req)
try:
mean_val = float(
sp.check_output('mrstats {} -output mean'.format(
self.output_file_path('project_summary.mif',
self.study.name,
frequency='per_project')),
shell=True))
self.assertEqual(mean_val,
len(self.SUBJECT_IDS) * len(self.SESSION_IDS))
finally:
if self.mrtrix_req is not None:
NiAnalysisNodeMixin.unload_module(*self.mrtrix_req)
def setUp(self):
self.reset_dirs()
for subject_id in self.SUBJECT_IDS:
for visit_id in self.SESSION_IDS:
self.add_session(self.project_dir, subject_id, visit_id)
self.study = self.create_study(
TestStudy,
'dummy',
inputs=[
DatasetMatch('start', nifti_gz_format, 'start'),
DatasetMatch('ones_slice', mrtrix_format, 'ones_slice')
],
options={'pipeline_option': True})
# Calculate MRtrix module required for 'mrstats' commands
try:
self.mrtrix_req = Requirement.best_requirement(
[mrtrix3_req], NiAnalysisNodeMixin.available_modules(),
NiAnalysisNodeMixin.preloaded_modules())
except NiAnalysisModulesNotInstalledException:
self.mrtrix_req = None
def tearDown(self):
try:
NiAnalysisNodeMixin.unload_module('mrtrix')
except NiAnalysisModulesNotInstalledException:
pass