def test_cifti2_labeltable():
lt = ci.Cifti2LabelTable()
assert_equal(len(lt), 0)
assert_raises(ci.Cifti2HeaderError, lt.to_xml)
assert_raises(ci.Cifti2HeaderError, lt._to_xml_element)
label = ci.Cifti2Label(label='Test', key=0)
lt[0] = label
assert_equal(len(lt), 1)
assert_equal(dict(lt), {label.key: label})
lt.clear()
lt.append(label)
assert_equal(len(lt), 1)
assert_equal(dict(lt), {label.key: label})
lt.clear()
test_tuple = (label.label, label.red, label.green, label.blue, label.alpha)
lt[label.key] = test_tuple
assert_equal(len(lt), 1)
v = lt[label.key]
assert_equal((v.label, v.red, v.green, v.blue, v.alpha), test_tuple)
assert_raises(ValueError, lt.__setitem__, 1, label)
assert_raises(ValueError, lt.__setitem__, 0, test_tuple[:-1])
assert_raises(ValueError, lt.__setitem__, 0, ('foo', 1.1, 0, 0, 1))
assert_raises(ValueError, lt.__setitem__, 0, ('foo', 1.0, -1, 0, 1))
assert_raises(ValueError, lt.__setitem__, 0, ('foo', 1.0, 0, -0.1, 1))
def test_cifti2_label():
lb = ci.Cifti2Label()
lb.label = 'Test'
lb.key = 0
assert_equal(lb.rgba, (0, 0, 0, 0))
assert_true(
compare_xml_leaf(
lb.to_xml().decode('utf-8'),
"<Label Key='0' Red='0' Green='0' Blue='0' Alpha='0'>Test</Label>")
)
lb.red = 0
lb.green = 0.1
lb.blue = 0.2
lb.alpha = 0.3
assert_equal(lb.rgba, (0, 0.1, 0.2, 0.3))
assert_true(
compare_xml_leaf(
lb.to_xml().decode('utf-8'),
"<Label Key='0' Red='0' Green='0.1' Blue='0.2' Alpha='0.3'>Test</Label>"
))
lb.red = 10
assert_raises(ci.Cifti2HeaderError, lb.to_xml)
lb.red = 0
lb.key = 'a'
assert_raises(ci.Cifti2HeaderError, lb.to_xml)
lb.key = 0
def test_cifti2_label():
lb = ci.Cifti2Label()
lb.label = 'Test'
lb.key = 0
assert lb.rgba == (0, 0, 0, 0)
assert compare_xml_leaf(
lb.to_xml().decode('utf-8'),
"<Label Key='0' Red='0' Green='0' Blue='0' Alpha='0'>Test</Label>")
lb.red = 0
lb.green = 0.1
lb.blue = 0.2
lb.alpha = 0.3
assert lb.rgba == (0, 0.1, 0.2, 0.3)
assert compare_xml_leaf(
lb.to_xml().decode('utf-8'),
"<Label Key='0' Red='0' Green='0.1' Blue='0.2' Alpha='0.3'>Test</Label>"
)
lb.red = 10
with pytest.raises(ci.Cifti2HeaderError):
lb.to_xml()
lb.red = 0
lb.key = 'a'
with pytest.raises(ci.Cifti2HeaderError):
lb.to_xml()
lb.key = 0
def yeo_to_91k(dlabel, medial_wall, reference, out):
"""Convert Yeo-style dlabels (Yeo and Schaefer parcellations) to 91k
grayordinate space
The Yeo lab generates dlabel's inclusive of medial wall vertices and only
for the cortical surfaces. This is different from how typical dlabels are
formatted, which exclude medial wall vertices and include voxels from all
subcortical and cerebellar structures (i.e. the full 91k grayordinate
space). This function corrects Yeo dlabels to proper 91k grayordinates.
Parameters
----------
dlabel : str
A Yeo-style .dlabel.nii atlas
medial_wall : str
HCP medial wall mask (.dlabel.nii)
reference : str
A reference .dlabel.nii file with 91k grayordinates and all brain
models included
out : str
Output 91k grayordinate .dlabel.nii file
"""
dlabel = nib.load(dlabel)
medial_wall = nib.load(medial_wall)
ref = nib.load(reference)
# remove medial wall vertices
array = dlabel.get_fdata()
corrected_array = array[np.logical_not(medial_wall.get_fdata())]
# expand to 91k
grayordinates = np.zeros(ref.shape)
grayordinates[0, :corrected_array.shape[0]] = corrected_array
# make header
labels = dlabel.header.get_axis(index=0).label[0]
label_table = ci.Cifti2LabelTable()
for key, (tag, rgba) in labels.items():
label_table[key] = ci.Cifti2Label(key, tag, *rgba)
maps = [ci.Cifti2NamedMap('labels', ci.Cifti2MetaData({}), label_table)]
label_map = ci.Cifti2MatrixIndicesMap(
applies_to_matrix_dimension=(0, ),
indices_map_to_data_type='CIFTI_INDEX_TYPE_LABELS',
maps=maps)
model_map = ci.Cifti2MatrixIndicesMap(
applies_to_matrix_dimension=(1, ),
indices_map_to_data_type='CIFTI_INDEX_TYPE_BRAIN_MODELS',
maps=list(ref.header.get_index_map(1).brain_models))
model_map.volume = ref.header.get_index_map(1).volume
matrix = ci.Cifti2Matrix()
matrix.append(label_map)
matrix.append(model_map)
hdr = ci.Cifti2Header(matrix)
out_dtseries = ci.Cifti2Image(grayordinates, hdr)
out_dtseries.to_filename(out)
return out
def create_label_map(applies_to_matrix_dimension):
maps = []
for name, meta, label in labels:
label_table = ci.Cifti2LabelTable()
for key, (tag, rgba) in label.items():
label_table[key] = ci.Cifti2Label(key, tag, *rgba)
maps.append(
ci.Cifti2NamedMap(name, ci.Cifti2MetaData(meta), label_table))
return ci.Cifti2MatrixIndicesMap(applies_to_matrix_dimension,
'CIFTI_INDEX_TYPE_LABELS',
maps=maps)
def test_cifti2_labeltable():
lt = ci.Cifti2LabelTable()
assert len(lt) == 0
with pytest.raises(ci.Cifti2HeaderError):
lt.to_xml()
with pytest.raises(ci.Cifti2HeaderError):
lt._to_xml_element()
label = ci.Cifti2Label(label='Test', key=0)
lt[0] = label
assert len(lt) == 1
assert dict(lt) == {label.key: label}
lt.clear()
lt.append(label)
assert len(lt) == 1
assert dict(lt) == {label.key: label}
lt.clear()
test_tuple = (label.label, label.red, label.green, label.blue, label.alpha)
lt[label.key] = test_tuple
assert len(lt) == 1
v = lt[label.key]
assert (v.label, v.red, v.green, v.blue, v.alpha) == test_tuple
with pytest.raises(ValueError):
lt[1] = label
with pytest.raises(ValueError):
lt[0] = test_tuple[:-1]
with pytest.raises(ValueError):
lt[0] = ('foo', 1.1, 0, 0, 1)
with pytest.raises(ValueError):
lt[0] = ('foo', 1.0, -1, 0, 1)
with pytest.raises(ValueError):
lt[0] = ('foo', 1.0, 0, -0.1, 1)
