def convert_fs_subj_to_tvb_surf(self, subject: Optional[str]=None):
"""
Merge surfaces and roi maps. Write out in TVB format.
"""
subjects_dir = os.environ['SUBJECTS_DIR']
if subject is None:
subject = os.environ['SUBJECT']
lh_surf_path = os.path.join(subjects_dir, subject, 'surf', 'lh.pial')
rh_surf_path = os.path.join(subjects_dir, subject, 'surf', 'rh.pial')
lh_annot_path = os.path.join(
subjects_dir, subject, 'label', 'lh.aparc.annot')
rh_annot_path = os.path.join(
subjects_dir, subject, 'label', 'rh.aparc.annot')
lh_surface = IOUtils.read_surface(lh_surf_path, False)
rh_surface = IOUtils.read_surface(rh_surf_path, False)
lh_annot = IOUtils.read_annotation(lh_annot_path)
rh_annot = IOUtils.read_annotation(rh_annot_path)
surface, region_mapping = self.surface_service.merge_lh_rh(lh_surface, rh_surface, lh_annot.region_mapping,
rh_annot.region_mapping)
numpy.savetxt('%s_ctx_roi_map.txt' %
(subject,), region_mapping.flat[:], '%i')
TVBWriter().write_surface_zip('%s_pial_surf.zip' % (subject,), surface)
def test_write_fs_surface():
file_path = get_data_file(TEST_FS_SUBJECT, TEST_SURFACE_FOLDER, "lh.pial")
original_surface = IOUtils.read_surface(file_path, False)
triangles_number = len(original_surface.triangles)
output_file_path = get_temporary_files_path("lh-test.pial")
IOUtils.write_surface(output_file_path, original_surface)
new_surface = IOUtils.read_surface(output_file_path, False)
assert triangles_number == len(new_surface.triangles) == 327680
def test_write_fs_surface():
file_path = get_data_file(TEST_FS_SUBJECT, TEST_SURFACE_FOLDER, "lh.pial")
original_surface = IOUtils.read_surface(file_path, False)
triangles_number = len(original_surface.triangles)
output_file_path = get_temporary_files_path("lh-test.pial")
IOUtils.write_surface(output_file_path, original_surface)
new_surface = IOUtils.read_surface(output_file_path, False)
assert triangles_number == len(new_surface.triangles) == 327680
def test_merge_surfaces(self,):
h5_surface_path = get_data_file("head2", "SurfaceCortical.h5")
h5_surface = IOUtils.read_surface(h5_surface_path, False)
vtx = h5_surface.vertices
tri = h5_surface.triangles
nv = vtx.size
nt = tri.size
nv2 = int(nv / 2)
nt2 = int(nt / 2)
lh_surface = Surface(vtx[:nv2], tri[:nt2])
rh_surface = Surface(vtx[nv2:], tri[nt2:])
# h5_region_mapping_path = get_data_file("head2", "RegionMapping.h5")
# annotation = IOUtils.read_annotation(h5_region_mapping_path)
#
# lh_region_mapping = annotation.region_mapping[:len(annotation.region_mapping) / 2]
# rh_region_mapping = annotation.region_mapping[len(annotation.region_mapping) / 2:]
out_surface = self.service.merge_surfaces([lh_surface, rh_surface])
self.assertEqual(len(out_surface.vertices),
len(lh_surface.vertices) + len(rh_surface.vertices))
self.assertEqual(len(out_surface.triangles),
len(lh_surface.triangles) + len(rh_surface.triangles))
def overlap_volume_surfaces(self, volume_background: os.PathLike, surfaces_path: os.PathLike,
use_center_surface: bool, use_cc_point: bool, snapshot_name: str=SNAPSHOT_NAME):
volume = IOUtils.read_volume(volume_background)
if use_cc_point:
ras = self.generic_io.get_ras_coordinates(
self.read_t1_affine_matrix())
else:
ras = volume.get_center_point()
surfaces = [IOUtils.read_surface(os.path.expandvars(surface), use_center_surface) for surface in
surfaces_path]
for projection in PROJECTIONS:
try:
x, y, background_matrix = volume.slice_volume(projection, ras)
except IndexError:
ras = volume.get_center_point()
x, y, background_matrix = volume.slice_volume(projection, ras)
self.logger.info("The volume center point has been used for %s snapshot of %s and %s.", projection,
volume_background, surfaces_path)
clear_flag = True
for surface_index, surface in enumerate(surfaces):
surf_x_array, surf_y_array = surface.cut_by_plane(
projection, ras)
self.writer.write_matrix_and_surfaces(x, y, background_matrix, surf_x_array, surf_y_array,
surface_index, clear_flag)
clear_flag = False
self.writer.save_figure(
self.generate_file_name(projection, snapshot_name))
def test_write_write_brain_visa_surf():
surface_path = get_data_file(
TEST_FS_SUBJECT, TEST_SURFACE_FOLDER, "lh.pial")
out_path = get_temporary_files_path("lh.pial.tri")
surface = IOUtils.read_surface(surface_path, False)
IOUtils.write_surface(out_path, surface)
assert os.path.exists(out_path)
def test_write_write_brain_visa_surf():
surface_path = get_data_file(TEST_FS_SUBJECT, TEST_SURFACE_FOLDER,
"lh.pial")
out_path = get_temporary_files_path("lh.pial.tri")
surface = IOUtils.read_surface(surface_path, False)
IOUtils.write_surface(out_path, surface)
assert os.path.exists(out_path)
def overlap_surface_annotation(self,
surface_path,
annotation,
snapshot_name=SNAPSHOT_NAME):
annotation = IOUtils.read_annotation(annotation)
surface = IOUtils.read_surface(surface_path, False)
self.writer.write_surface_with_annotation(
surface, annotation,
self.generate_file_name('surface_annotation', snapshot_name))
def test_overlap_surface_annotation(self):
writer = ImageWriter(SNAPSHOTS_DIRECTORY)
surface_path = get_data_file(self.head2, "SurfaceCortical.h5")
surface = IOUtils.read_surface(surface_path, False)
annot_path = get_data_file(self.head2, "RegionMapping.h5")
annot = IOUtils.read_annotation(annot_path)
annot.region_names = ['reg1', 'reg2']
annot.regions_color_table = numpy.array(
[[200, 200, 200, 255, 30567], [100, 150, 200, 255, 30568]])
resulted_file_name = self.processor.generate_file_name(
'surface_annotation', SNAPSHOT_NAME)
writer.write_surface_with_annotation(surface, annot, resulted_file_name)
fname = '%s0' % (resulted_file_name, )
self._assert_writer_path_exists(fname)
def compute_gdist_mat(self, surf_name='pial', max_distance=40.0):
max_distance = float(max_distance) # in case passed from sys.argv
for h in 'rl':
subjects_dir = os.environ['SUBJECTS_DIR']
subject = os.environ['SUBJECT']
surf_path = '%s/%s/surf/%sh.%s' % (subjects_dir, subject, h,
surf_name)
surface = IOUtils.read_surface(surf_path, False)
mat_path = '%s/%s/surf/%sh.%s.gdist.mat' % (subjects_dir, subject,
h, surf_name)
mat = gdist.local_gdist_matrix(surface.vertices,
surface.triangles.astype('<i4'),
max_distance=max_distance)
scipy.io.savemat(mat_path, {'gdist': mat})
def compute_gdist_mat(self, surf_name: str='pial', max_distance: float=40.0) -> numpy.ndarray:
max_distance = float(max_distance) # in case passed from sys.argv
for h in 'rl':
subjects_dir = os.environ['SUBJECTS_DIR']
subject = os.environ['SUBJECT']
surf_path = '%s/%s/surf/%sh.%s' % (subjects_dir,
subject, h, surf_name)
surface = IOUtils.read_surface(surf_path, False)
mat_path = '%s/%s/surf/%sh.%s.gdist.mat' % (
subjects_dir, subject, h, surf_name)
mat = gdist.local_gdist_matrix(
surface.vertices, surface.triangles.astype('<i4'), max_distance=max_distance)
scipy.io.savemat(mat_path, {'gdist': mat})
return mat
def overlap_volume_surfaces(self,
volume_background,
surfaces_path,
use_center_surface,
use_cc_point,
snapshot_name=SNAPSHOT_NAME):
volume = IOUtils.read_volume(volume_background)
if use_cc_point:
ras = self.generic_io.get_ras_coordinates(
self.read_t1_affine_matrix())
else:
ras = volume.get_center_point()
surfaces = [
IOUtils.read_surface(os.path.expandvars(surface),
use_center_surface)
for surface in surfaces_path
]
for projection in PROJECTIONS:
try:
x, y, background_matrix = volume.slice_volume(projection, ras)
except IndexError:
ras = volume.get_center_point()
x, y, background_matrix = volume.slice_volume(projection, ras)
self.logger.info(
"The volume center point has been used for %s snapshot of %s and %s.",
projection, volume_background, surfaces_path)
clear_flag = True
for surface_index, surface in enumerate(surfaces):
surf_x_array, surf_y_array = surface.cut_by_plane(
projection, ras)
self.writer.write_matrix_and_surfaces(x, y, background_matrix,
surf_x_array,
surf_y_array,
surface_index,
clear_flag)
clear_flag = False
self.writer.save_figure(
self.generate_file_name(projection, snapshot_name))
def aseg_surf_conc_annot(self,
surf_path,
out_surf_path,
annot_path,
label_indices,
lut_path=None):
"""
Concatenate surfaces of one specific label of interest each, to create a single annotated surface.
"""
lut_path = lut_path or default_lut_path()
label_names, color_table = self.annotation_service.lut_to_annot_names_ctab(
lut_path=lut_path, labels=label_indices)
label_indices = numpy.array(label_indices.split()).astype('i')
# verts tri area_mask cras
surfaces = []
out_annotation = Annotation([], [], [])
label_number = -1
for label_index in label_indices:
this_surf_path = surf_path + "-%06d" % int(label_index)
if os.path.exists(this_surf_path):
ind_l, = numpy.where(label_indices == label_index)
out_annotation.add_region_names_and_colors(
numpy.array(label_names)[ind_l], color_table[ind_l, :])
label_number += 1
surfaces.append(IOUtils.read_surface(this_surf_path, False))
out_annotation.add_region_mapping(label_number * numpy.ones(
(surfaces[-1].n_vertices, ), dtype='int64'))
out_surface = self.merge_surfaces(surfaces)
#out_annotation.regions_color_table = numpy.squeeze(numpy.array(out_annotation.regions_color_table).astype('i'))
IOUtils.write_surface(out_surf_path, out_surface)
IOUtils.write_annotation(annot_path, out_annotation)
def aseg_surf_conc_annot(self, surf_path: str, out_surf_path: str, annot_path: str,
label_indices: Union[numpy.ndarray, list], lut_path: Optional[str]=None) -> Surface:
"""
Concatenate surfaces of one specific label of interest each, to create a single annotated surface.
"""
lut_path = lut_path or default_lut_path()
label_names, color_table = self.annotation_service.lut_to_annot_names_ctab(lut_path=lut_path,
labels=label_indices)
label_indices = numpy.array(label_indices.split()).astype('i')
# verts tri area_mask cras
surfaces = []
out_annotation = Annotation([], [], [])
label_number = -1
for label_index in label_indices:
# TODO: This is hardcoded: /aseg-%06d here and also in pegasus dax generator
this_surf_path = surf_path + "/aseg-%06d" % int(label_index)
if os.path.exists(this_surf_path):
ind_l, = numpy.where(label_indices == label_index)
out_annotation.add_region_names_and_colors(
label_names[int(ind_l)],
color_table[ind_l, :])
label_number += 1
surfaces.append(IOUtils.read_surface(this_surf_path, False))
out_annotation.add_region_mapping(
label_number * numpy.ones((surfaces[-1].n_vertices,), dtype='int64'))
out_surface = self.merge_surfaces(surfaces)
# out_annotation.regions_color_table = numpy.squeeze(numpy.array(out_annotation.regions_color_table).astype('i'))
IOUtils.write_surface(out_surf_path, out_surface)
IOUtils.write_annotation(annot_path, out_annotation)
return out_surface
def test_parse_fs_surface():
file_path = get_data_file(TEST_FS_SUBJECT, TEST_SURFACE_FOLDER, "lh.pial")
surf = IOUtils.read_surface(file_path, False)
assert len(surf.triangles) == 327680
def test_parse_not_existing_fs_surface():
file_path = "not_existing_surface.pial"
with pytest.raises(IOError):
IOUtils.read_surface(file_path, False)
def test_parse_not_existing_fs_surface():
file_path = "not_existing_surface.pial"
with pytest.raises(IOError):
IOUtils.read_surface(file_path, False)
def test_parse_fs_surface():
file_path = get_data_file(TEST_FS_SUBJECT, TEST_SURFACE_FOLDER, "lh.pial")
surf = IOUtils.read_surface(file_path, False)
assert len(surf.triangles) == 327680
def merge_surfs(surf_lh, surf_rh, out_surf_path):
s_lh = IOUtils.read_surface(surf_lh, False)
s_rh = IOUtils.read_surface(surf_rh, False)
surf = surfaceService.merge_surfaces([s_lh, s_rh])
IOUtils.write_surface(out_surf_path, surf)
def test_parse_h5_surface():
h5_path = get_data_file('head2', 'SurfaceCortical.h5')
surface = IOUtils.read_surface(h5_path, False)
assert len(surface.vertices) == 16
assert len(surface.triangles) == 24
def test_parse_not_existing_gifti_surface():
file_path = "not_existing_surface.gii"
with pytest.raises(FileNotFoundError):
IOUtils.read_surface(file_path, False)
def test_parse_gifti_centered_surface():
file_path = get_data_file(
TEST_MODIF_SUBJECT, TEST_SURFACE_FOLDER, "lh.pial.gii")
surf = IOUtils.read_surface(file_path, True)
assert len(surf.triangles) == 327680
def test_parse_not_surface():
file_path = get_data_file(TEST_FS_SUBJECT, "label", "lh.aparc.annot")
with pytest.raises(ValueError):
IOUtils.read_surface(file_path, False)
def sample_vol_on_surf(self,
surf_path,
vol_path,
annot_path,
out_surf_path,
cras_path,
add_string='',
vertex_neighbourhood=1,
add_lbl=[],
lut_path=None):
"""
Sample a volume of a specific label on a surface, by keeping only those surface vertices, the nearest voxel of
which is of the given label (+ of possibly additional target labels, such as white matter).
Allow optionally for vertices within a given voxel distance vn from the target voxels.
"""
lut_path = lut_path or default_lut_path()
# Read the inputs
surface = IOUtils.read_surface(surf_path, False)
annotation = IOUtils.read_annotation(annot_path)
labels = self.annotation_service.annot_names_to_labels(
annotation.region_names, add_string=add_string, lut_path=lut_path)
region_mapping_indexes = numpy.unique(annotation.region_mapping)
volume_parser = VolumeIO()
volume = volume_parser.read(vol_path)
ras2vox_affine_matrix = numpy.linalg.inv(volume.affine_matrix)
cras = numpy.loadtxt(cras_path)
grid, n_grid = self.__prepare_grid(vertex_neighbourhood)
# Initialize the output mask:
verts_out_mask = numpy.repeat([False], surface.vertices.shape[0])
for label_index in range(len(region_mapping_indexes)):
self.logger.info("%s",
add_string + annotation.region_names[label_index])
# Get the indexes of the vertices corresponding to this label:
verts_indices_of_label, = numpy.where(
annotation.region_mapping[:] ==
region_mapping_indexes[label_index])
verts_indices_of_label_size = verts_indices_of_label.size
if verts_indices_of_label_size == 0:
continue
# Add any additional labels
all_labels = [labels[label_index]] + add_lbl
# get the vertices for current label and add cras to take them to
# scanner ras
verts_of_label = surface.vertices[verts_indices_of_label, :]
verts_of_label += numpy.repeat(numpy.expand_dims(cras, 1).T,
verts_indices_of_label_size,
axis=0)
# Compute the nearest voxel coordinates using the affine transform
ijk = numpy.round(
ras2vox_affine_matrix.dot(numpy.c_[verts_of_label, numpy.ones(verts_indices_of_label_size)].T)[:3].T) \
.astype('i')
# Get the labels of these voxels:
surf_vxls = volume.data[ijk[:, 0], ijk[:, 1], ijk[:, 2]]
# Vertex mask to keep: those that correspond to voxels of one of
# the target labels
# surf_vxls==lbl if only one target label
verts_keep, = numpy.where(numpy.in1d(surf_vxls, all_labels))
verts_out_mask[verts_indices_of_label[verts_keep]] = True
if vertex_neighbourhood > 0:
# These are now the remaining indexes to be checked for
# neighboring voxels
verts_indices_of_label = numpy.delete(verts_indices_of_label,
verts_keep)
ijk = numpy.delete(ijk, verts_keep, axis=0)
for vertex_index in range(verts_indices_of_label.size):
# Generate the specific grid centered at the voxel ijk
ijk_grid = grid + \
numpy.tile(ijk[vertex_index, :], (n_grid, 1))
# Remove voxels outside the volume
indexes_within_limits = numpy.all(
[(ijk_grid[:, 0] >= 0),
(ijk_grid[:, 0] < volume.dimensions[0]),
(ijk_grid[:, 1] >= 0),
(ijk_grid[:, 1] < volume.dimensions[1]),
(ijk_grid[:, 2] >= 0),
(ijk_grid[:, 2] < volume.dimensions[2])],
axis=0)
ijk_grid = ijk_grid[indexes_within_limits, :]
surf_vxls = volume.data[ijk_grid[:, 0], ijk_grid[:, 1],
ijk_grid[:, 2]]
# If any of the neighbors is of the target labels include
# the current vertex
# surf_vxls==lbl if only one target label
if numpy.any(numpy.in1d(surf_vxls, all_labels)):
verts_out_mask[
verts_indices_of_label[vertex_index]] = True
# Vertex indexes and vertices to keep:
verts_out_indices, = numpy.where(verts_out_mask)
verts_out = surface.vertices[verts_out_indices]
# TODO maybe: make sure that all voxels of this label correspond to at least one vertex.
# Create a similar mask for faces by picking only triangles of which
# all 3 vertices are included
face_out_mask = numpy.c_[verts_out_mask[surface.triangles[:, 0]],
verts_out_mask[surface.triangles[:, 1]],
verts_out_mask[surface.triangles[:, 2]]].all(
axis=1)
faces_out = surface.triangles[face_out_mask]
# The old vertices' indexes of faces have to be transformed to the new
# vrtx_out_inds:
for iF in range(faces_out.shape[0]):
for vertex_index in range(3):
faces_out[iF, vertex_index], = numpy.where(
faces_out[iF, vertex_index] == verts_out_indices)
surface.vertices = verts_out
surface.triangles = faces_out
# Write the output surfaces and annotations to files. Also write files
# with the indexes of vertices to keep.
IOUtils.write_surface(out_surf_path, surface)
annotation.set_region_mapping(
annotation.get_region_mapping_by_indices([verts_out_indices]))
IOUtils.write_annotation(out_surf_path + ".annot", annotation)
numpy.save(out_surf_path + "-idx.npy", verts_out_indices)
numpy.savetxt(out_surf_path + "-idx.txt", verts_out_indices, fmt='%d')
def convert_fs_to_brain_visa(self, in_surf_path):
surface = IOUtils.read_surface(in_surf_path, False)
IOUtils.write_surface(in_surf_path + '.tri', surface)
def generate_surface_zip(in_file, out_file):
surface = IOUtils.read_surface(in_file, False)
IOUtils.write_surface(out_file, surface)
def sample_vol_on_surf(self, surf_path: str, vol_path: str, annot_path: str, out_surf_path: str,
cras_path: str, add_string: str='', vertex_neighbourhood: int=1,
add_lbl: list=[], lut_path: Optional[str]=None) -> (Surface, Annotation):
"""
Sample a volume of a specific label on a surface, by keeping only those surface vertices, the nearest voxel of
which is of the given label (+ of possibly additional target labels, such as white matter).
Allow optionally for vertices within a given voxel distance vn from the target voxels.
"""
lut_path = lut_path or default_lut_path()
# Read the inputs
surface = IOUtils.read_surface(surf_path, False)
annotation = IOUtils.read_annotation(annot_path)
labels = self.annotation_service.annot_names_to_labels(annotation.region_names,
add_string=add_string, lut_path=lut_path)
region_mapping_indexes = numpy.unique(annotation.region_mapping)
volume_parser = VolumeIO()
volume = volume_parser.read(vol_path)
ras2vox_affine_matrix = numpy.linalg.inv(volume.affine_matrix)
cras = numpy.loadtxt(cras_path)
grid, n_grid = self.__prepare_grid(vertex_neighbourhood)
# Initialize the output mask:
verts_out_mask = numpy.repeat([False], surface.vertices.shape[0])
for label_index in range(len(region_mapping_indexes)):
self.logger.info("%s", add_string +
annotation.region_names[label_index])
# Get the indexes of the vertices corresponding to this label:
verts_indices_of_label, = numpy.where(
annotation.region_mapping[:] == region_mapping_indexes[label_index])
verts_indices_of_label_size = verts_indices_of_label.size
if verts_indices_of_label_size == 0:
continue
# Add any additional labels
all_labels = [labels[label_index]] + add_lbl
# get the vertices for current label and add cras to take them to
# scanner ras
verts_of_label = surface.vertices[verts_indices_of_label, :]
verts_of_label += numpy.repeat(numpy.expand_dims(
cras, 1).T, verts_indices_of_label_size, axis=0)
# Compute the nearest voxel coordinates using the affine transform
ijk = numpy.round(
ras2vox_affine_matrix.dot(numpy.c_[verts_of_label, numpy.ones(verts_indices_of_label_size)].T)[:3].T) \
.astype('i')
# Get the labels of these voxels:
surf_vxls = volume.data[ijk[:, 0], ijk[:, 1], ijk[:, 2]]
# Vertex mask to keep: those that correspond to voxels of one of
# the target labels
# surf_vxls==lbl if only one target label
verts_keep, = numpy.where(numpy.in1d(surf_vxls, all_labels))
verts_out_mask[verts_indices_of_label[verts_keep]] = True
if vertex_neighbourhood > 0:
# These are now the remaining indexes to be checked for
# neighboring voxels
verts_indices_of_label = numpy.delete(
verts_indices_of_label, verts_keep)
ijk = numpy.delete(ijk, verts_keep, axis=0)
for vertex_index in range(verts_indices_of_label.size):
# Generate the specific grid centered at the voxel ijk
ijk_grid = grid + \
numpy.tile(ijk[vertex_index, :], (n_grid, 1))
# Remove voxels outside the volume
indexes_within_limits = numpy.all([(ijk_grid[:, 0] >= 0), (ijk_grid[:, 0] < volume.dimensions[0]),
(ijk_grid[:, 1] >= 0), (ijk_grid[
:, 1] < volume.dimensions[1]),
(ijk_grid[:, 2] >= 0), (ijk_grid[:, 2] < volume.dimensions[2])],
axis=0)
ijk_grid = ijk_grid[indexes_within_limits, :]
surf_vxls = volume.data[
ijk_grid[:, 0], ijk_grid[:, 1], ijk_grid[:, 2]]
# If any of the neighbors is of the target labels include
# the current vertex
# surf_vxls==lbl if only one target label
if numpy.any(numpy.in1d(surf_vxls, all_labels)):
verts_out_mask[
verts_indices_of_label[vertex_index]] = True
# Vertex indexes and vertices to keep:
verts_out_indices, = numpy.where(verts_out_mask)
verts_out = surface.vertices[verts_out_indices]
# TODO maybe: make sure that all voxels of this label correspond to at least one vertex.
# Create a similar mask for faces by picking only triangles of which
# all 3 vertices are included
face_out_mask = numpy.c_[
verts_out_mask[surface.triangles[:, 0]], verts_out_mask[surface.triangles[:, 1]], verts_out_mask[
surface.triangles[:, 2]]].all(axis=1)
faces_out = surface.triangles[face_out_mask]
# The old vertices' indexes of faces have to be transformed to the new
# vrtx_out_inds:
for iF in range(faces_out.shape[0]):
for vertex_index in range(3):
faces_out[iF, vertex_index], = numpy.where(
faces_out[iF, vertex_index] == verts_out_indices)
surface.vertices = verts_out
surface.triangles = faces_out
# Write the output surfaces and annotations to files. Also write files
# with the indexes of vertices to keep.
IOUtils.write_surface(out_surf_path, surface)
annotation.set_region_mapping(
annotation.get_region_mapping_by_indices([verts_out_indices]))
IOUtils.write_annotation(out_surf_path + ".annot", annotation)
numpy.save(out_surf_path + "-idx.npy", verts_out_indices)
numpy.savetxt(out_surf_path + "-idx.txt", verts_out_indices, fmt='%d')
return surface, annotation
def test_parse_gifti_centered_surface():
file_path = get_data_file(TEST_MODIF_SUBJECT, TEST_SURFACE_FOLDER,
"lh.pial.gii")
surf = IOUtils.read_surface(file_path, True)
assert len(surf.triangles) == 327680
def test_parse_centered_fs_surface():
file_path = get_data_file(TEST_MODIF_SUBJECT, TEST_SURFACE_FOLDER,
"lh-centered.pial")
surf = IOUtils.read_surface(file_path, False)
assert surf.center_ras == [0, 0, 0]
def test_parse_h5_surface():
h5_path = get_data_file('head2', 'SurfaceCortical.h5')
surface = IOUtils.read_surface(h5_path, False)
assert len(surface.vertices) == 16
assert len(surface.triangles) == 24
def test_parse_not_surface():
file_path = get_data_file(TEST_FS_SUBJECT, "label", "lh.aparc.annot")
with pytest.raises(ValueError):
IOUtils.read_surface(file_path, False)
def test_parse_centered_fs_surface():
file_path = get_data_file(
TEST_MODIF_SUBJECT, TEST_SURFACE_FOLDER, "lh-centered.pial")
surf = IOUtils.read_surface(file_path, False)
assert surf.center_ras == [0, 0, 0]
def test_parse_not_existing_gifti_surface():
file_path = "not_existing_surface.gii"
with pytest.raises(FileNotFoundError):
IOUtils.read_surface(file_path, False)
def compute_region_details(atlas_suffix: AtlasSuffix, fs_color_lut: os.PathLike, t1: os.PathLike, lh_cort: os.PathLike,
rh_cort: os.PathLike, lh_cort_annot: os.PathLike, rh_cort_annot: os.PathLike,
lh_subcort: os.PathLike, rh_subcort: os.PathLike, lh_subcort_annot: os.PathLike,
rh_subcort_annot: os.PathLike):
annot_cort_lh = IOUtils.read_annotation(lh_cort_annot)
annot_cort_rh = IOUtils.read_annotation(rh_cort_annot)
annot_subcort_lh = IOUtils.read_annotation(lh_subcort_annot)
annot_subcort_rh = IOUtils.read_annotation(rh_subcort_annot)
mapping = MappingService(atlas_suffix, annot_cort_lh, annot_cort_rh, annot_subcort_lh, annot_subcort_rh)
mapping.generate_region_mapping_for_cort_annot(annot_cort_lh, annot_cort_rh)
mapping.generate_region_mapping_for_subcort_annot(annot_subcort_lh, annot_subcort_rh)
surface_service = SurfaceService()
surf_cort_lh = IOUtils.read_surface(lh_cort, False)
surf_cort_rh = IOUtils.read_surface(rh_cort, False)
full_cort_surface = surface_service.merge_surfaces([surf_cort_lh, surf_cort_rh])
surf_subcort_lh = IOUtils.read_surface(lh_subcort, False)
surf_subcort_rh = IOUtils.read_surface(rh_subcort, False)
full_subcort_surface = surface_service.merge_surfaces([surf_subcort_lh, surf_subcort_rh])
genericIO.write_list_to_txt_file(mapping.cort_region_mapping, AsegFiles.RM_CORT_TXT.value.replace("%s", atlas_suffix))
genericIO.write_list_to_txt_file(mapping.subcort_region_mapping,
AsegFiles.RM_SUBCORT_TXT.value.replace("%s", atlas_suffix))
vox2ras_file = "vox2ras.txt"
subprocess.call(["mri_info", "--vox2ras", t1, "--o", vox2ras_file])
surf_subcort_filename = "surface_subcort.zip"
IOUtils.write_surface(surf_subcort_filename, full_subcort_surface)
surf_cort_filename = "surface_cort.zip"
IOUtils.write_surface(surf_cort_filename, full_cort_surface)
os.remove(vox2ras_file)
cort_subcort_full_surf = surface_service.merge_surfaces([full_cort_surface, full_subcort_surface])
cort_subcort_full_region_mapping = mapping.cort_region_mapping + mapping.subcort_region_mapping
dict_fs_custom = mapping.get_mapping_for_connectome_generation()
genericIO.write_dict_to_txt_file(dict_fs_custom, AsegFiles.FS_CUSTOM_TXT.value.replace("%s", atlas_suffix))
region_areas = surface_service.compute_areas_for_regions(mapping.get_all_regions(), cort_subcort_full_surf,
cort_subcort_full_region_mapping)
genericIO.write_list_to_txt_file(region_areas, AsegFiles.AREAS_TXT.value.replace("%s", atlas_suffix))
region_centers = surface_service.compute_centers_for_regions(mapping.get_all_regions(), cort_subcort_full_surf,
cort_subcort_full_region_mapping)
cort_subcort_lut = mapping.get_entire_lut()
region_names = list(cort_subcort_lut.values())
with open(AsegFiles.CENTERS_TXT.value.replace("%s", atlas_suffix), "w") as f:
for idx, (val_x, val_y, val_z) in enumerate(region_centers):
f.write("%s %.2f %.2f %.2f\n" % (region_names[idx], val_x, val_y, val_z))
region_orientations = surface_service.compute_orientations_for_regions(mapping.get_all_regions(),
cort_subcort_full_surf,
cort_subcort_full_region_mapping)
lh_region_centers = surface_service.compute_centers_for_regions(mapping.get_lh_regions(), surf_cort_lh,
mapping.lh_region_mapping)
lh_region_orientations = surface_service.compute_orientations_for_regions(mapping.get_lh_regions(), surf_cort_lh,
mapping.lh_region_mapping)
with open(AsegFiles.LH_DIPOLES_TXT.value.replace("%s", atlas_suffix), "w") as f:
for idx, (val_x, val_y, val_z) in enumerate(lh_region_centers):
f.write("%.2f %.2f %.2f %.2f %.2f %.2f\n" % (
val_x, val_y, val_z, lh_region_orientations[idx][0], lh_region_orientations[idx][1],
lh_region_orientations[idx][2]))
rh_region_centers = surface_service.compute_centers_for_regions(mapping.get_rh_regions(), surf_cort_rh,
mapping.rh_region_mapping)
rh_region_orientations = surface_service.compute_orientations_for_regions(mapping.get_rh_regions(), surf_cort_rh,
mapping.rh_region_mapping)
with open(AsegFiles.RH_DIPOLES_TXT.value.replace("%s", atlas_suffix), "w") as f:
for idx, (val_x, val_y, val_z) in enumerate(rh_region_centers):
f.write("%.2f %.2f %.2f %.2f %.2f %.2f\n" % (
val_x, val_y, val_z, rh_region_orientations[idx][0], rh_region_orientations[idx][1],
rh_region_orientations[idx][2]))
numpy.savetxt(AsegFiles.ORIENTATIONS_TXT.value.replace("%s", atlas_suffix), region_orientations, fmt='%.2f %.2f %.2f')
annotation_service = AnnotationService()
lut_dict, _, _ = annotation_service.read_lut(fs_color_lut, "name")
rm_index_dict = mapping.get_mapping_for_aparc_aseg(lut_dict)
genericIO.write_dict_to_txt_file(rm_index_dict, AsegFiles.RM_TO_APARC_ASEG_TXT.value.replace("%s", atlas_suffix))
genericIO.write_list_to_txt_file(mapping.is_cortical_region_mapping(),
AsegFiles.CORTICAL_TXT.value.replace("%s", atlas_suffix))
def overlap_surface_annotation(
self, surface_path: os.PathLike, annotation_path: os.PathLike, snapshot_name: str=SNAPSHOT_NAME):
annotation = IOUtils.read_annotation(annotation_path)
surface = IOUtils.read_surface(surface_path, False)
self.writer.write_surface_with_annotation(surface, annotation,
self.generate_file_name('surface_annotation', snapshot_name))
def convert_fs_to_brain_visa(self, in_surf_path: str, out_surf_path: Optional[str]=None):
surface = IOUtils.read_surface(in_surf_path, False)
if out_surf_path is None:
out_surf_path = in_surf_path + '.tri'
IOUtils.write_surface(out_surf_path, surface)
