def test_hdf5():
for ext in ('.hdf5', '.zarr'):
with tempdir():
nifti_image().to_filename('test.nii.gz')
arr = gifti_arr()
write_gifti('test.shape.gii', [arr], brain_structure='CortexLeft')
go = greyordinate.parse_greyordinate('*****@*****.**')
assert len(go.brain_model_axis) == 2
go.to_filename('full' + ext)
go2 = go.from_filename('full' + ext)
testing.assert_equal(go.data, go2.data)
assert go.brain_model_axis == go2.brain_model_axis
assert go2.data.shape == (2, )
func = greyordinate.GreyOrdinates.empty_zarr if ext == '.zarr' else greyordinate.GreyOrdinates.empty_hdf5
with func('empty' + ext,
(go.brain_model_axis, go.brain_model_axis)) as go:
arr = np.random.randn(2, 2)
go.data[:] = arr
go2 = greyordinate.parse_greyordinate('empty' + ext)
assert (np.array(go2.data) == arr).all()
assert go2.brain_model_axis == go.brain_model_axis
assert go2.other_axes == (go.brain_model_axis, )
print(ext)
print(go2.data.chunks)
if ext == '.zarr':
print(go2.data.compressor)
def run_roi_dist_gifti(surf_fn, roi, brain_structure, project=None):
with tempdir():
write_gifti('roi.shape.gii', [roi], brain_structure)
if project is not None:
write_gifti('in_project.shape.gii', [project], brain_structure)
cmd_project = [
'-p', 'in_project.shape.gii', 'out_project.shape.gii'
]
else:
cmd_project = []
directories([
'surface',
'roi_dist_gifti',
str(surf_fn),
'roi.shape.gii',
'-od',
'dist.shape.gii',
'-ocv',
'closest.shape.gii',
'-opv',
'pred.shape.gii',
] + cmd_project)
res = (
nib.load('dist.shape.gii').darrays[0].data,
nib.load('closest.shape.gii').darrays[0].data,
nib.load('pred.shape.gii').darrays[0].data,
)
if project is not None:
res = res + (nib.load('out_project.shape.gii').darrays[0].data, )
return res
def test_cifti():
with tempdir():
nifti_image().to_filename('test.nii.gz')
arr = gifti_arr()
write_gifti('test.shape.gii', [arr], brain_structure='CortexLeft')
go = greyordinate.parse_greyordinate('*****@*****.**')
assert len(go.brain_model_axis) == 2
go.to_filename('full.dscalar.nii')
go2 = go.from_filename('full.dscalar.nii')
testing.assert_equal(go.data[None, :], go2.data)
assert go.brain_model_axis == go2.brain_model_axis
assert go2.data.shape == (1, 2)
with greyordinate.GreyOrdinates.empty_cifti(
'empty.dconn.nii',
(go.brain_model_axis, go.brain_model_axis)) as go:
arr = np.random.randn(2, 2)
go.data[:] = arr
go2 = greyordinate.parse_greyordinate('empty.dconn.nii')
assert (np.array(go2.data) == arr).all()
assert go2.brain_model_axis == go.brain_model_axis
assert go2.other_axes == (go.brain_model_axis, )
def run_from_args(args):
"""
Runs the script based on a Namespace containing the command line arguments
"""
surface = CorticalMesh.read(args.surface)
arr = nib.load(args.depth).darrays[0].data
if args.flip:
arr *= -1
use = np.isfinite(arr) & (arr != 0)
if args.Nparcels is not None:
segments = run(
surface[use],
arr[use],
min_depth=args.min_depth,
min_size=args.min_size,
fill_ridge=args.fill_ridge,
)
else:
segments = run_nparcels(
surface[use],
arr[use],
nparcels=args.Nparcels,
min_size=args.min_size,
fill_ridge=args.fill_ridge,
)
full_segment = np.zeros(arr.size, dtype='i4')
full_segment[use] = segments
write_gifti(args.out, [full_segment],
color_map='default',
brain_structure=surface.anatomy)
def run_from_args(args):
"""
Runs the script based on a Namespace containing the command line arguments
"""
surface = CorticalMesh.read(args.surface)
sulcal_depth = nib.load(args.sulcal_depth).darrays[0].data
to_extract = nib.load(args.extract).darrays[0].data
values = run(surface, sulcal_depth, to_extract, args.minimum)
write_gifti(args.out, [values], surface.anatomy)
def test_writable():
with tempdir():
nifti_image().to_filename('test.nii.gz')
arr = gifti_arr()
write_gifti('test.shape.gii', [arr], brain_structure='CortexLeft')
go = greyordinate.parse_greyordinate('*****@*****.**')
for ext in ('.dscalar.nii', '.hdf5', '.zarr'):
go.to_filename('data' + ext)
img = go.from_filename('data' + ext, writable=True)
img.data[..., 0] = np.pi * 3
del img
assert (go.from_filename('data' + ext).data[...,
0] == np.pi * 3).all()
def run_from_args(args):
"""
Runs the script based on a Namespace containing the command line arguments
"""
if (
args.output_dist is None and
args.output_closest_vertex is None and
args.output_predecessor_vertex is None and
args.project is None
):
raise ValueError("No output files requested, set at least one of -p, -od, -orv, or -onv")
surface = CorticalMesh.read(args.surface)
roi = nib.load(args.roi).darrays[0].data != 0
if args.project is not None:
to_project = nib.load(args.project[0]).darrays[0].data
distance, predecessor, closest_vertex = run(
surface, roi
)
if args.output_dist is not None:
write_gifti(args.output_dist, [distance], brain_structure=surface.anatomy)
if args.output_closest_vertex is not None:
write_gifti(args.output_closest_vertex, [closest_vertex], brain_structure=surface.anatomy)
if args.output_predecessor_vertex is not None:
write_gifti(args.output_predecessor_vertex, [predecessor], brain_structure=surface.anatomy)
if args.project is not None:
projected = to_project[closest_vertex]
write_gifti(args.project[1], [projected], brain_structure=surface.anatomy)
def run_from_args(args):
"""
Runs the script based on a Namespace containing the command line arguments
"""
surf = CorticalMesh.read(args.surface)
go = GreyOrdinates.from_filename(args.features)
features = go.surface(surf.anatomy)
mask = np.isfinite(features)
res = run(
surf[mask],
features,
n_iter=args.iter,
metric=args.metric,
method=args.cluster,
)
full_res = np.zeros(surf.nvertices)
full_res[mask] = res
write_gifti(args.output, [full_res], surf.anatomy)
def run_from_args(args):
"""
Runs the script based on a Namespace containing the command line arguments
"""
surface = CorticalMesh.read(args.surface)
go = GreyOrdinates.from_filename(args.features)
features = go.surface(surface.anatomy)
mask = np.isfinite(features)
labels = run(
surface[mask],
features[..., mask],
metric=args.metric,
method=args.cluster,
n_clusters=args.n_clusters,
)
full_labels = -np.ones(surface.nvertices, dtype=labels.dtype)
full_labels[mask] = labels
write_gifti(args.output, [full_labels],
brain_structure=surface.anatomy,
color_map={-1: ('???', (0, 0, 0, 0))})
def test_gifti():
with tempdir():
for shape in (), (2, ), (1, 2):
arr = gifti_arr(shape)
write_gifti('test.shape.gii', [arr], brain_structure='CortexLeft')
go = greyordinate.GreyOrdinates.from_filename('test.shape.gii')
assert len(go.brain_model_axis) == 1
assert go.data.shape == shape + (1, )
new_arr = go.surface('left_cortex')
testing.assert_equal(new_arr.shape, arr.shape)
testing.assert_equal(new_arr[..., 1], arr[..., 1])
assert np.isfinite(new_arr).sum() == np.prod(shape)
with raises(ValueError):
go.surface('CortexRight')
with raises(ValueError):
go.volume()
go.to_filename('test2.shape.gii')
cmp('test.shape.gii', 'test2.shape.gii', shallow=False)