def test_fail_fetch_atlas_harvard_oxford():
# specify non-existing atlas item
assert_raises_regex(ValueError, 'Invalid atlas name',
atlas.fetch_atlas_harvard_oxford,
'not_inside')
# specify existing atlas item
target_atlas = 'cort-maxprob-thr0-1mm'
target_atlas_fname = 'HarvardOxford-' + target_atlas + '.nii.gz'
ho_dir = os.path.join(tst.tmpdir, 'fsl', 'data', 'atlases')
os.makedirs(ho_dir)
nifti_dir = os.path.join(ho_dir, 'HarvardOxford')
os.makedirs(nifti_dir)
target_atlas_nii = os.path.join(nifti_dir, target_atlas_fname)
struct.load_mni152_template().to_filename(target_atlas_nii)
dummy = open(os.path.join(ho_dir, 'HarvardOxford-Cortical.xml'), 'w')
dummy.write("<?xml version='1.0' encoding='us-ascii'?> "
"<metadata>"
"</metadata>")
dummy.close()
ho = atlas.fetch_atlas_harvard_oxford(target_atlas,
data_dir=tst.tmpdir)
assert_true(isinstance(nibabel.load(ho.maps), nibabel.Nifti1Image))
assert_true(isinstance(ho.labels, np.ndarray))
assert_true(len(ho.labels) > 0)
def test_fail_fetch_atlas_harvard_oxford():
# specify non-existing atlas item
assert_raises_regex(ValueError, 'Invalid atlas name',
atlas.fetch_atlas_harvard_oxford, 'not_inside')
# specify existing atlas item
target_atlas = 'cort-maxprob-thr0-1mm'
target_atlas_fname = 'HarvardOxford-' + target_atlas + '.nii.gz'
ho_dir = os.path.join(tmpdir, 'fsl', 'data', 'atlases')
os.makedirs(ho_dir)
nifti_dir = os.path.join(ho_dir, 'HarvardOxford')
os.makedirs(nifti_dir)
target_atlas_nii = os.path.join(nifti_dir, target_atlas_fname)
struct.load_mni152_template().to_filename(target_atlas_nii)
dummy = open(os.path.join(ho_dir, 'HarvardOxford-Cortical.xml'), 'w')
dummy.write("<?xml version='1.0' encoding='us-ascii'?> "
"<metadata>"
"</metadata>")
dummy.close()
ho = atlas.fetch_atlas_harvard_oxford(target_atlas, data_dir=tmpdir)
assert_true(isinstance(nibabel.load(ho.maps), nibabel.Nifti1Image))
assert_true(isinstance(ho.labels, np.ndarray))
assert_true(len(ho.labels) > 0)
def test_fail_fetch_atlas_harvard_oxford():
# specify non-existing atlas item
assert_raises_regex(ValueError, "Invalid atlas name", atlas.fetch_atlas_harvard_oxford, "not_inside")
# specify existing atlas item
target_atlas = "cort-maxprob-thr0-1mm"
target_atlas_fname = "HarvardOxford-" + target_atlas + ".nii.gz"
ho_dir = os.path.join(tmpdir, "fsl", "data", "atlases")
os.makedirs(ho_dir)
nifti_dir = os.path.join(ho_dir, "HarvardOxford")
os.makedirs(nifti_dir)
target_atlas_nii = os.path.join(nifti_dir, target_atlas_fname)
struct.load_mni152_template().to_filename(target_atlas_nii)
dummy = open(os.path.join(ho_dir, "HarvardOxford-Cortical.xml"), "w")
dummy.write("<?xml version='1.0' encoding='us-ascii'?> " "<metadata>" "</metadata>")
dummy.close()
ho = atlas.fetch_atlas_harvard_oxford(target_atlas, data_dir=tmpdir)
assert_true(isinstance(nibabel.load(ho.maps), nibabel.Nifti1Image))
assert_true(isinstance(ho.labels, np.ndarray))
assert_true(len(ho.labels) > 0)
def test_load_mni152_template():
# All subjects
template_nii_1mm = struct.load_mni152_template(resolution=1)
template_nii_2mm = struct.load_mni152_template()
assert template_nii_1mm.shape == (197, 233, 189)
assert template_nii_2mm.shape == (99, 117, 95)
assert template_nii_1mm.header.get_zooms() == (1.0, 1.0, 1.0)
assert template_nii_2mm.header.get_zooms() == (2.0, 2.0, 2.0)
def test_load_mni152_template():
# All subjects
template_nii = struct.load_mni152_template()
assert_equal(template_nii.shape, (91, 109, 91))
assert_equal(template_nii.get_header().get_zooms(), (2.0, 2.0, 2.0))
def test_fetch_icbm152_brain_gm_mask():
dataset = struct.fetch_icbm152_2009(data_dir=tst.tmpdir, verbose=0)
struct.load_mni152_template().to_filename(dataset.gm)
grey_matter_img = struct.fetch_icbm152_brain_gm_mask(data_dir=tst.tmpdir,
verbose=0)
assert_true(isinstance(grey_matter_img, nibabel.Nifti1Image))
def test_load_mni152_template():
# All subjects
template_nii = struct.load_mni152_template()
assert_equal(template_nii.shape, (91, 109, 91))
assert_equal(template_nii.header.get_zooms(), (2.0, 2.0, 2.0))
def test_fetch_icbm152_brain_gm_mask(tmp_path, request_mocker):
dataset = struct.fetch_icbm152_2009(data_dir=str(tmp_path), verbose=0)
struct.load_mni152_template().to_filename(dataset.gm)
grey_matter_img = struct.fetch_icbm152_brain_gm_mask(
data_dir=str(tmp_path), verbose=0)
assert isinstance(grey_matter_img, nibabel.Nifti1Image)
def test_load_mni152_template():
# All subjects
template_nii = struct.load_mni152_template()
assert template_nii.shape == (91, 109, 91)
assert template_nii.header.get_zooms() == (2.0, 2.0, 2.0)
def test_fetch_icbm152_brain_gm_mask():
dataset = struct.fetch_icbm152_2009(data_dir=tst.tmpdir, verbose=0)
struct.load_mni152_template().to_filename(dataset.gm)
grey_matter_img = struct.fetch_icbm152_brain_gm_mask(data_dir=tst.tmpdir,
verbose=0)
assert_true(isinstance(grey_matter_img, nibabel.Nifti1Image))
