def test_empty_confounds(self):
'''Expect that clean_image will receive None as value for confounds
keyword when conf_prep is empty confounds table.'''
denoise = Denoise(
fmri_prep=self.fmri_prep,
conf_prep=self.conf_prep,
pipeline=self.pipeline,
output_dir=self.out_dir.name,
)
denoise._load_confouds()
self.assertEqual(denoise._confounds, None)
def test_non_empty_confounds(self):
'''Expect that clean_image will receive correctly loaded confounds as
numpy.ndarray.'''
conf_prep = pd.DataFrame(np.random.random((100, 2)))
conf_prep.to_csv(self.conf_prep, sep='\t', index=False)
denoise = Denoise(
fmri_prep=self.fmri_prep,
conf_prep=self.conf_prep,
pipeline=self.pipeline,
output_dir=self.out_dir.name,
)
denoise._load_confouds()
self.assertEqual(denoise._confounds.shape, (100, 2))