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_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)
# Create false atlas
atlas_data = np.zeros((10, 10, 10), dtype=int)
# Create an interhemispheric map
atlas_data[:, :2, :] = 1
# Create a left map
atlas_data[:5, 3:5, :] = 2
# Create a right map, with one voxel on the left side
atlas_data[5:, 7:9, :] = 3
atlas_data[4, 7, 0] = 3
nibabel.Nifti1Image(atlas_data, np.eye(4) * 3).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'?>\n"
"<data>\n"
'<label index="0" x="48" y="94" z="35">R1</label>\n'
'<label index="1" x="25" y="70" z="32">R2</label>\n'
'<label index="2" x="33" y="73" z="63">R3</label>\n'
"</data>")
dummy.close()
ho = atlas.fetch_atlas_harvard_oxford(target_atlas,
data_dir=tst.tmpdir,
symmetric_split=True)
assert_true(isinstance(ho.maps, nibabel.Nifti1Image))
assert_true(isinstance(ho.labels, list))
assert_equal(len(ho.labels), 5)
assert_equal(ho.labels[0], "Background")
assert_equal(ho.labels[1], "R1, left part")
assert_equal(ho.labels[2], "R1, right part")
assert_equal(ho.labels[3], "R2")
assert_equal(ho.labels[4], "R3")
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)
# Create false atlas
atlas_data = np.zeros((10, 10, 10), dtype=int)
# Create an interhemispheric map
atlas_data[:, :2, :] = 1
# Create a left map
atlas_data[:5, 3:5, :] = 2
# Create a right map, with one voxel on the left side
atlas_data[5:, 7:9, :] = 3
atlas_data[4, 7, 0] = 3
nibabel.Nifti1Image(atlas_data, np.eye(4) * 3).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'?>\n"
"<data>\n"
'<label index="0" x="48" y="94" z="35">R1</label>\n'
'<label index="1" x="25" y="70" z="32">R2</label>\n'
'<label index="2" x="33" y="73" z="63">R3</label>\n'
"</data>")
dummy.close()
# when symmetric_split=False (by default), then atlas fetcher should
# have maps as string and n_labels=4 with background. Since, we relay on xml
# file to retrieve labels.
ho_wo_symm = atlas.fetch_atlas_harvard_oxford(target_atlas,
data_dir=tst.tmpdir)
assert_true(isinstance(ho_wo_symm.maps, _basestring))
assert_true(isinstance(ho_wo_symm.labels, list))
assert_equal(ho_wo_symm.labels[0], "Background")
assert_equal(ho_wo_symm.labels[1], "R1")
assert_equal(ho_wo_symm.labels[2], "R2")
assert_equal(ho_wo_symm.labels[3], "R3")
# This section tests with lateralized version. In other words,
# symmetric_split=True
# Dummy xml file for lateralized control of cortical atlas images
# shipped with FSL 5.0. Atlases are already lateralized in this version
# for cortical type atlases denoted with maxprob but not full prob and but
# not also with subcortical.
# So, we test the fetcher with symmetric_split=True by creating a new
# dummy local file and fetch them and test the output variables
# accordingly.
dummy2 = open(os.path.join(ho_dir, 'HarvardOxford-Cortical-Lateralized.xml'), 'w')
dummy2.write("<?xml version='1.0' encoding='us-ascii'?>\n"
"<data>\n"
'<label index="0" x="63" y="86" z="49">Left R1</label>\n'
'<label index="1" x="21" y="86" z="33">Right R1</label>\n'
'<label index="2" x="64" y="69" z="32">Left R2</label>\n'
'<label index="3" x="26" y="70" z="32">Right R2</label>\n'
'<label index="4" x="47" y="75" z="66">Left R3</label>\n'
'<label index="5" x="43" y="80" z="61">Right R3</label>\n'
"</data>")
dummy2.close()
# Here, with symmetric_split=True, atlas maps are returned as nibabel Nifti
# image but not string. Now, with symmetric split number of labels should be
# more than without split and contain Left and Right tags in the labels.
# Create dummy image files too with cortl specified for symmetric split.
split_atlas_fname = 'HarvardOxford-' + 'cortl-maxprob-thr0-1mm' + '.nii.gz'
nifti_target_split = os.path.join(nifti_dir, split_atlas_fname)
nibabel.Nifti1Image(atlas_data, np.eye(4) * 3).to_filename(
nifti_target_split)
ho = atlas.fetch_atlas_harvard_oxford(target_atlas,
data_dir=tst.tmpdir,
symmetric_split=True)
assert_true(isinstance(ho.maps, nibabel.Nifti1Image))
assert_true(isinstance(ho.labels, list))
assert_equal(len(ho.labels), 7)
assert_equal(ho.labels[0], "Background")
assert_equal(ho.labels[1], "Left R1")
assert_equal(ho.labels[2], "Right R1")
assert_equal(ho.labels[3], "Left R2")
assert_equal(ho.labels[4], "Right R2")
assert_equal(ho.labels[5], "Left R3")
assert_equal(ho.labels[6], "Right R3")
def test_fail_fetch_atlas_harvard_oxford(tmp_path, request_mocker):
# specify non-existing atlas item
with pytest.raises(ValueError, match='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 = str(tmp_path / '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)
# Create false atlas
atlas_data = np.zeros((10, 10, 10), dtype=int)
# Create an interhemispheric map
atlas_data[:, :2, :] = 1
# Create a left map
atlas_data[:5, 3:5, :] = 2
# Create a right map, with one voxel on the left side
atlas_data[5:, 7:9, :] = 3
atlas_data[4, 7, 0] = 3
nibabel.Nifti1Image(atlas_data,
np.eye(4) * 3).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'?>\n"
"<data>\n"
'<label index="0" x="48" y="94" z="35">R1</label>\n'
'<label index="1" x="25" y="70" z="32">R2</label>\n'
'<label index="2" x="33" y="73" z="63">R3</label>\n'
"</data>")
dummy.close()
# when symmetric_split=False (by default), then atlas fetcher should
# have maps as string and n_labels=4 with background. Since, we relay on xml
# file to retrieve labels.
ho_wo_symm = atlas.fetch_atlas_harvard_oxford(target_atlas,
data_dir=str(tmp_path))
assert isinstance(ho_wo_symm.maps, str)
assert isinstance(ho_wo_symm.labels, list)
assert ho_wo_symm.labels[0] == "Background"
assert ho_wo_symm.labels[1] == "R1"
assert ho_wo_symm.labels[2] == "R2"
assert ho_wo_symm.labels[3] == "R3"
# This section tests with lateralized version. In other words,
# symmetric_split=True
# Dummy xml file for lateralized control of cortical atlas images
# shipped with FSL 5.0. Atlases are already lateralized in this version
# for cortical type atlases denoted with maxprob but not full prob and but
# not also with subcortical.
# So, we test the fetcher with symmetric_split=True by creating a new
# dummy local file and fetch them and test the output variables
# accordingly.
dummy2 = open(
os.path.join(ho_dir, 'HarvardOxford-Cortical-Lateralized.xml'), 'w')
dummy2.write("<?xml version='1.0' encoding='us-ascii'?>\n"
"<data>\n"
'<label index="0" x="63" y="86" z="49">Left R1</label>\n'
'<label index="1" x="21" y="86" z="33">Right R1</label>\n'
'<label index="2" x="64" y="69" z="32">Left R2</label>\n'
'<label index="3" x="26" y="70" z="32">Right R2</label>\n'
'<label index="4" x="47" y="75" z="66">Left R3</label>\n'
'<label index="5" x="43" y="80" z="61">Right R3</label>\n'
"</data>")
dummy2.close()
# Here, with symmetric_split=True, atlas maps are returned as nibabel Nifti
# image but not string. Now, with symmetric split number of labels should be
# more than without split and contain Left and Right tags in the labels.
# Create dummy image files too with cortl specified for symmetric split.
split_atlas_fname = 'HarvardOxford-' + 'cortl-maxprob-thr0-1mm' + '.nii.gz'
nifti_target_split = os.path.join(nifti_dir, split_atlas_fname)
nibabel.Nifti1Image(atlas_data,
np.eye(4) * 3).to_filename(nifti_target_split)
ho = atlas.fetch_atlas_harvard_oxford(target_atlas,
data_dir=str(tmp_path),
symmetric_split=True)
assert isinstance(ho.maps, nibabel.Nifti1Image)
assert isinstance(ho.labels, list)
assert len(ho.labels) == 7
assert ho.labels[0] == "Background"
assert ho.labels[1] == "Left R1"
assert ho.labels[2] == "Right R1"
assert ho.labels[3] == "Left R2"
assert ho.labels[4] == "Right R2"
assert ho.labels[5] == "Left R3"
assert ho.labels[6] == "Right R3"
