def create_dummy_preproc_path(n_subjects, n_sessions):
preproc_dir = tempfile.mkdtemp()
subjects = ['sub-%s' % (d + 1) for d in range(n_subjects)]
sessions = ['sess-%s' % (d + 1) for d in range(n_sessions)]
for subject in subjects:
for session in sessions:
for modality in ['anat', 'dwi']:
os.makedirs(op.join(preproc_dir, subject, session, modality))
# Make some dummy data:
aff = np.eye(4)
data = np.ones((10, 10, 10, 6))
bvecs = np.vstack([np.eye(3), np.eye(3)])
bvecs[0] = 0
bvals = np.ones(6) * 1000.
bvals[0] = 0
np.savetxt(op.join(preproc_dir, subject, session, 'dwi',
'dwi.bvals'),
bvals)
np.savetxt(op.join(preproc_dir, subject, session, 'dwi',
'dwi.bvecs'),
bvecs)
nib.save(nib.Nifti1Image(data, aff),
op.join(preproc_dir, subject, session, 'dwi',
'dwi.nii.gz'))
nib.save(nib.Nifti1Image(data, aff),
op.join(preproc_dir, subject, session, 'anat',
'T1w.nii.gz'))
nib.save(nib.Nifti1Image(data, aff),
op.join(preproc_dir, subject, session, 'anat',
'aparc+aseg.nii.gz'))
return preproc_dir
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