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_annotation(self):
file_path = get_data_file(
self.subject, self.annot_path, "lh.aparc.annot")
annotation = IOUtils.read_annotation(file_path)
out_annotation_path = self.temp_file_path("lh-test.aparc.annot")
IOUtils.write_annotation(out_annotation_path, annotation)
new_annotation = IOUtils.read_annotation(out_annotation_path)
self.assertEqual(annotation.region_names, new_annotation.region_names)
def annot_to_conn_conf(self, annot_path, type, conn_conf_path, first_idx=0):
annotation_lh = IOUtils.read_annotation(os.path.join(annot_path, "lh." + type + ".annot"))
annotation_rh = IOUtils.read_annotation(os.path.join(annot_path, "rh." + type + ".annot"))
with open(conn_conf_path, 'w') as fd:
for id, name in enumerate(annotation_lh.region_names):
if type == "aparc" and name != "unknown":
name = "lh-" + name
fd.write('%d\t%s\n' % (id + first_idx, name))
first_idx += len(annotation_lh.region_names)
for id, name in enumerate(annotation_rh.region_names):
if (name == "unknown"):
first_idx -= 1
continue
if type == "aparc" and name != "unknown":
name = "rh-" + name
fd.write('%d\t%s\n' % (id + first_idx, name))
return first_idx + len(annotation_rh.region_names)
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 annot_to_lut(self, annot_path, lut_path=None, subject=None, prefix=''):
"""
This function creates from an annotation a new lut_file, or adds new
entries to an existing lut file. In the latter case, new entries have
labels greater than the maximum alredy existing label inside the lut
file.
Parameters
----------
annot_path : str, os.PathLike
path to annotation.
lut_path : str, os.PathLike
path to existing or new LUT file.
subject : str, optional
subject name if provided, otherwise env var $SUBJECT is used
prefiw : str, optional
prefix for region names (i.e., "ctx-lh-")
"""
annotation = IOUtils.read_annotation(annot_path)
subject = subject or os.environ['SUBJECT']
# If this is an already existing lut file:
lut_path = lut_path or default_lut_path()
if os.path.isfile(lut_path):
# ...find the maximum label in it and add 1
add_lbl = 1 + \
numpy.max(self.read_lut(
lut_path=lut_path, key_mode='label')[0])
else:
# ...else, set it to 0
add_lbl = 0
with open(lut_path, 'a') as fd:
if add_lbl == 0:
# TODO: we should include an environment variable for
# freesurfer version, and print it here
fd.write("#$Id: %s %s\n\n" % (lut_path, datetime.now()))
fd.write('#No.\tLabel Name: \tR G B A \n')
else:
fd.write('\n')
fd.write("""
#Patient: {subject}
#User: {user}
#Annotation path: {annot_path}
#Time: {time}
""".format(subject=subject,
user=os.path.split(os.path.expanduser('~'))[-1],
annot_path=annot_path,
time=datetime.now()))
# TODO: align columns
# NOTE!!! that the fourth and fifth columns of color_table are not
# used in the lut file!!!
for name, (r, g, b, dummy1, dummy2), lbl in \
zip(annotation.region_names, annotation.regions_color_table,
list(range(len(annotation.region_names)))):
fd.write('%d\t%s\t%d %d %d %d\n' %
(lbl + add_lbl, prefix + name, r, g, b, 0))
def annot_to_conn_conf(self,
annot_path,
type,
conn_conf_path,
first_idx=0):
annotation_lh = IOUtils.read_annotation(
os.path.join(annot_path, "lh." + type + ".annot"))
annotation_rh = IOUtils.read_annotation(
os.path.join(annot_path, "rh." + type + ".annot"))
with open(conn_conf_path, 'w') as fd:
for id, name in enumerate(annotation_lh.region_names):
if type == "aparc" and name != "unknown":
name = "lh-" + name
fd.write('%d\t%s\n' % (id + first_idx, name))
first_idx += len(annotation_lh.region_names)
for id, name in enumerate(annotation_rh.region_names):
if (name == "unknown"):
first_idx -= 1
continue
if type == "aparc" and name != "unknown":
name = "rh-" + name
fd.write('%d\t%s\n' % (id + first_idx, name))
return first_idx + len(annotation_rh.region_names)
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 test_aseg_surf_conc_annot(self,):
out_surf_path = get_temporary_files_path("out_aseg")
out_annot_path = get_temporary_files_path("out_annot")
labels = "10 11"
colorLUT = get_data_file("colorLUT.txt")
self.service.aseg_surf_conc_annot(
data_path, out_surf_path, out_annot_path, labels, colorLUT)
self.assertTrue(os.path.exists(out_surf_path))
self.assertTrue(os.path.exists(out_annot_path))
surface_parser = FreesurferIO()
surface = surface_parser.read(out_surf_path, False)
self.assertEqual(len(surface.vertices), 5714)
self.assertEqual(len(surface.triangles), 11420)
annotation = IOUtils.read_annotation(out_annot_path)
assert_array_equal(
annotation.regions_color_table,
[[0, 118, 14, 0, 947712], [122, 186, 220, 0, 14465658]])
def test_parse_h5_annotation(self):
h5_path = get_data_file('head2', 'RegionMapping.h5')
annotation = IOUtils.read_annotation(h5_path)
self.assertEqual(annotation.region_mapping.size, 16)
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 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 test_parse_annotation(self):
file_path = get_data_file(
self.subject, self.annot_path, "lh.aparc.annot")
annot = IOUtils.read_annotation(file_path)
self.assertEqual(_expected_region_names, annot.region_names)
def annot_to_lut(self,
annot_path,
lut_path=None,
subject=None,
prefix=''):
"""
This function creates from an annotation a new lut_file, or adds new
entries to an existing lut file. In the latter case, new entries have
labels greater than the maximum alredy existing label inside the lut
file.
Parameters
----------
annot_path : str, os.PathLike
path to annotation.
lut_path : str, os.PathLike
path to existing or new LUT file.
subject : str, optional
subject name if provided, otherwise env var $SUBJECT is used
prefiw : str, optional
prefix for region names (i.e., "ctx-lh-")
"""
annotation = IOUtils.read_annotation(annot_path)
subject = subject or os.environ['SUBJECT']
# If this is an already existing lut file:
lut_path = lut_path or default_lut_path()
if os.path.isfile(lut_path):
# ...find the maximum label in it and add 1
add_lbl = 1 + \
numpy.max(self.read_lut(
lut_path=lut_path, key_mode='label')[0])
else:
# ...else, set it to 0
add_lbl = 0
with open(lut_path, 'a') as fd:
if add_lbl == 0:
# TODO: we should include an environment variable for
# freesurfer version, and print it here
fd.write("#$Id: %s %s\n\n" % (lut_path, datetime.now()))
fd.write('#No.\tLabel Name: \tR G B A \n')
else:
fd.write('\n')
fd.write("""
#Patient: {subject}
#User: {user}
#Annotation path: {annot_path}
#Time: {time}
""".format(
subject=subject,
user=os.path.split(os.path.expanduser('~'))[-1],
annot_path=annot_path,
time=datetime.now())
)
# TODO: align columns
# NOTE!!! that the fourth and fifth columns of color_table are not
# used in the lut file!!!
for name, (r, g, b, dummy1, dummy2), lbl in \
zip(annotation.region_names, annotation.regions_color_table,
list(range(len(annotation.region_names)))):
fd.write('%d\t%s\t%d %d %d %d\n' %
(lbl + add_lbl, prefix + name, r, g, b, 0))
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
import os
import sys
from tvb.recon.algo.service.mapping_service import MappingService
from tvb.recon.io.factory import IOUtils
from tvb.recon.io.generic import GenericIO
if __name__ == "__main__":
direc = sys.argv[1]
out_file = sys.argv[2]
annot_cort_lh = IOUtils.read_annotation(os.path.join(direc, "lh.aparc.annot"))
annot_cort_rh = IOUtils.read_annotation(os.path.join(direc, "rh.aparc.annot"))
annot_subcort_lh = IOUtils.read_annotation(os.path.join(direc, "lh.aseg.annot"))
annot_subcort_rh = IOUtils.read_annotation(os.path.join(direc, "rh.aseg.annot"))
mapping = MappingService(annot_cort_lh, annot_cort_rh, annot_subcort_lh, annot_subcort_rh)
dict_fs_custom = mapping.get_mapping_for_connectome_generation()
genericIO = GenericIO()
genericIO.write_dict_to_txt_file(dict_fs_custom, out_file)
def annot_to_conn_conf(self, annot_path, conn_conf_path):
annotation = IOUtils.read_annotation(annot_path)
with open(conn_conf_path, 'w') as fd:
for id, name in enumerate(annotation.region_names):
fd.write('%d\t%s\n' % (id, name))
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))
