Source code for tvb.adapters.datatypes.h5.surface_h5

# -*- coding: utf-8 -*-
#
#
# TheVirtualBrain-Framework Package. This package holds all Data Management, and
# Web-UI helpful to run brain-simulations. To use it, you also need to download
# TheVirtualBrain-Scientific Package (for simulators). See content of the
# documentation-folder for more details. See also http://www.thevirtualbrain.org
#
# (c) 2012-2024, Baycrest Centre for Geriatric Care ("Baycrest") and others
#
# This program is free software: you can redistribute it and/or modify it under the
# terms of the GNU General Public License as published by the Free Software Foundation,
# either version 3 of the License, or (at your option) any later version.
# This program is distributed in the hope that it will be useful, but WITHOUT ANY
# WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
# PARTICULAR PURPOSE.  See the GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along with this
# program.  If not, see <http://www.gnu.org/licenses/>.
#
#
#   CITATION:
# When using The Virtual Brain for scientific publications, please cite it as explained here:
# https://www.thevirtualbrain.org/tvb/zwei/neuroscience-publications
#
#

import numpy
from tvb.basic.logger.builder import get_logger
from tvb.basic.neotraits.api import NArray, Int, Attr
from tvb.core.neotraits.h5 import H5File, DataSet, Scalar, Json
from tvb.datatypes.surfaces import Surface

LOG = get_logger(__name__)

# Slices are for vertices [0.....SPLIT_MAX_SIZE + SPLIT_BUFFER_SIZE]
# [SPLIT_MAX_SIZE ..... 2 * SPLIT_BUFFER_SIZE + SPLIT_BUFFER_SIZE]
# Triangles [0, 1, 2], [3, 4, 5], [6, 7, 8].....
# Vertices -  no of triangles * 3

SPLIT_MAX_SIZE = 40000
SPLIT_BUFFER_SIZE = 15000
SPLIT_PICK_MAX_TRIANGLE = 20000

KEY_TRIANGLES = "triangles"
KEY_VERTICES = "vertices"
KEY_HEMISPHERE = "hemisphere"
KEY_START = "start_idx"
KEY_END = "end_idx"

HEMISPHERE_LEFT = "LEFT"
HEMISPHERE_RIGHT = "RIGHT"
HEMISPHERE_UNKNOWN = "NONE"


[docs] class SurfaceH5(H5File): def __init__(self, path): super(SurfaceH5, self).__init__(path) self.vertices = DataSet(Surface.vertices, self) self.triangles = DataSet(Surface.triangles, self) self.vertex_normals = DataSet(Surface.vertex_normals, self) self.triangle_normals = DataSet(Surface.triangle_normals, self) self.number_of_vertices = Scalar(Surface.number_of_vertices, self) self.number_of_triangles = Scalar(Surface.number_of_triangles, self) self.edge_mean_length = Scalar(Surface.edge_mean_length, self) self.edge_min_length = Scalar(Surface.edge_min_length, self) self.edge_max_length = Scalar(Surface.edge_max_length, self) self.zero_based_triangles = Scalar(Surface.zero_based_triangles, self) self.split_triangles = DataSet(NArray(dtype=int), self, name="split_triangles") self.number_of_split_slices = Scalar(Int(), self, name="number_of_split_slices") self.split_slices = Json(Attr(field_type=dict), self, name="split_slices") self.bi_hemispheric = Scalar(Surface.bi_hemispheric, self) self.surface_type = Scalar(Surface.surface_type, self) self.valid_for_simulations = Scalar(Surface.valid_for_simulations, self) # cached header like information, needed to interpret the rest of the file # Load the data that is required in order to interpret the file format # number_of_vertices and split_slices are needed for the get_vertices_slice read call if not self.is_new_file: self._split_slices = self.split_slices.load() self._split_triangles = self.split_triangles.load() self._number_of_vertices = self.number_of_vertices.load() self._number_of_triangles = self.number_of_triangles.load() self._number_of_split_slices = self.number_of_split_slices.load() self._bi_hemispheric = self.bi_hemispheric.load() # else: this is a new file
[docs] def store(self, datatype, scalars_only=False, store_references=True): # type: (Surface, bool, bool) -> None super(SurfaceH5, self).store(datatype, scalars_only=scalars_only, store_references=store_references) # When any of the header fields change we have to update our cache of them # As they are an invariant of SurfaceH5 we don't do that in the accessors but here. # This implies that direct public writes to them via the accessors will break the invariant. # todo: should we make the accessors private? In complex formats like this one they are private # for this type direct writes to accessors should not be done self._number_of_vertices = datatype.number_of_vertices self._number_of_triangles = datatype.number_of_triangles self._bi_hemispheric = datatype.bi_hemispheric self.prepare_slices(datatype) self.number_of_split_slices.store(self._number_of_split_slices) self.split_slices.store(self._split_slices) self.split_triangles.store(self._split_triangles)
[docs] def read_subtype_attr(self): return self.surface_type.load()
[docs] def center(self): """ Compute the center of the surface as the mean spot on all the three axes. """ # is this different from return numpy.mean(self.vertices, axis=0) ? return [float(numpy.mean(self.vertices[:, 0])), float(numpy.mean(self.vertices[:, 1])), float(numpy.mean(self.vertices[:, 2]))]
[docs] def get_number_of_split_slices(self): return self._number_of_split_slices
[docs] def prepare_slices(self, datatype): """ Before storing Surface in H5, make sure vertices/triangles are split in slices that are readable by WebGL. WebGL only supports triangle indices in interval [0.... 2^16] """ # Do not split when size is conveniently small: if self._number_of_vertices <= SPLIT_MAX_SIZE + SPLIT_BUFFER_SIZE and not self._bi_hemispheric: self._number_of_split_slices = 1 self._split_slices = {0: {KEY_TRIANGLES: {KEY_START: 0, KEY_END: self._number_of_triangles}, KEY_VERTICES: {KEY_START: 0, KEY_END: self._number_of_vertices}, KEY_HEMISPHERE: HEMISPHERE_UNKNOWN}} self._split_triangles = numpy.array([], dtype=numpy.int32) return # Compute the number of split slices: left_hemisphere_slices = 0 left_hemisphere_vertices_no = 0 if self._bi_hemispheric: # when more than one hemisphere right_hemisphere_vertices_no = numpy.count_nonzero(datatype.hemisphere_mask) left_hemisphere_vertices_no = self._number_of_vertices - right_hemisphere_vertices_no LOG.debug("Right %d Left %d" % (right_hemisphere_vertices_no, left_hemisphere_vertices_no)) left_hemisphere_slices = self._get_slices_number(left_hemisphere_vertices_no) self._number_of_split_slices = left_hemisphere_slices self._number_of_split_slices += self._get_slices_number(right_hemisphere_vertices_no) LOG.debug("Hemispheres Total %d Left %d" % (self._number_of_split_slices, left_hemisphere_slices)) else: # when a single hemisphere self._number_of_split_slices = self._get_slices_number(self._number_of_vertices) LOG.debug("Start to compute surface split triangles and vertices") split_triangles = [] ignored_triangles_counter = 0 self._split_slices = {} for i in range(self._number_of_split_slices): split_triangles.append([]) if not self._bi_hemispheric: self._split_slices[i] = {KEY_VERTICES: {KEY_START: i * SPLIT_MAX_SIZE, KEY_END: min(self._number_of_vertices, (i + 1) * SPLIT_MAX_SIZE + SPLIT_BUFFER_SIZE)}, KEY_HEMISPHERE: HEMISPHERE_UNKNOWN} else: if i < left_hemisphere_slices: self._split_slices[i] = {KEY_VERTICES: {KEY_START: i * SPLIT_MAX_SIZE, KEY_END: min(left_hemisphere_vertices_no, (i + 1) * SPLIT_MAX_SIZE + SPLIT_BUFFER_SIZE)}, KEY_HEMISPHERE: HEMISPHERE_LEFT} else: self._split_slices[i] = {KEY_VERTICES: {KEY_START: left_hemisphere_vertices_no + (i - left_hemisphere_slices) * SPLIT_MAX_SIZE, KEY_END: min(self._number_of_vertices, left_hemisphere_vertices_no + SPLIT_MAX_SIZE * (i + 1 - left_hemisphere_slices) + SPLIT_BUFFER_SIZE)}, KEY_HEMISPHERE: HEMISPHERE_RIGHT} # Iterate Triangles and find the slice where it fits best, based on its vertices indexes: for i in range(self._number_of_triangles): current_triangle = [datatype.triangles[i][j] for j in range(3)] fit_slice, transformed_triangle = self._find_slice(current_triangle) if fit_slice is not None: split_triangles[fit_slice].append(transformed_triangle) else: # triangle ignored, as it has vertices over multiple slices. ignored_triangles_counter += 1 continue final_split_triangles = [] last_triangles_idx = 0 # Concatenate triangles, to be stored in a single HDF5 array. for slice_idx, split_ in enumerate(split_triangles): self._split_slices[slice_idx][KEY_TRIANGLES] = {KEY_START: last_triangles_idx, KEY_END: last_triangles_idx + len(split_)} final_split_triangles.extend(split_) last_triangles_idx += len(split_) self._split_triangles = numpy.array(final_split_triangles, dtype=numpy.int32) if ignored_triangles_counter > 0: LOG.warning("Ignored triangles from multiple hemispheres: " + str(ignored_triangles_counter)) LOG.debug("End compute surface split triangles and vertices " + str(self._split_slices))
@staticmethod def _get_slices_number(vertices_number): """ Slices are for vertices [SPLIT_MAX_SIZE * i ... SPLIT_MAX_SIZE * (i + 1) + SPLIT_BUFFER_SIZE] Slices will overlap : |........SPLIT_MAX_SIZE|...SPLIT_BUFFER_SIZE| <-- split 1 |......... SPLIT_MAX_SIZE|...SPLIT_BUFFER_SIZE| <-- split 2 If we have trailing data smaller than the SPLIT_BUFFER_SIZE, then we no longer split but we need to have at least 1 slice. """ slices_number, trailing = divmod(vertices_number, SPLIT_MAX_SIZE) if trailing > SPLIT_BUFFER_SIZE or (slices_number == 0 and trailing > 0): slices_number += 1 return slices_number def _find_slice(self, triangle): mn = min(triangle) mx = max(triangle) for i in range(self._number_of_split_slices): v = self._split_slices[i][KEY_VERTICES] # extracted for performance slice_start = v[KEY_START] if slice_start <= mn and mx < v[KEY_END]: return i, [triangle[j] - slice_start for j in range(3)] return None, triangle
[docs] def get_slice_vertex_boundaries(self, slice_idx): if str(slice_idx) in self._split_slices: start_idx = max(0, self._split_slices[str(slice_idx)][KEY_VERTICES][KEY_START]) end_idx = min(self._split_slices[str(slice_idx)][KEY_VERTICES][KEY_END], self._number_of_vertices) return start_idx, end_idx else: LOG.warning("Could not access slice indices, possibly due to an incompatibility with code update!") return 0, min(SPLIT_BUFFER_SIZE, self._number_of_vertices)
def _get_slice_triangle_boundaries(self, slice_idx): if str(slice_idx) in self._split_slices: start_idx = max(0, self._split_slices[str(slice_idx)][KEY_TRIANGLES][KEY_START]) end_idx = min(self._split_slices[str(slice_idx)][KEY_TRIANGLES][KEY_END], self._number_of_triangles) return start_idx, end_idx else: LOG.warning("Could not access slice indices, possibly due to an incompatibility with code update!") return 0, self._number_of_triangles
[docs] def get_vertices_slice(self, slice_number=0): """ Read vertices slice, to be used by WebGL visualizer. """ slice_number = int(slice_number) start_idx, end_idx = self.get_slice_vertex_boundaries(slice_number) return self.vertices[start_idx: end_idx: 1]
[docs] def get_vertex_normals_slice(self, slice_number=0): """ Read vertex-normal slice, to be used by WebGL visualizer. """ slice_number = int(slice_number) start_idx, end_idx = self.get_slice_vertex_boundaries(slice_number) return self.vertex_normals[start_idx: end_idx: 1]
[docs] def get_triangles_slice(self, slice_number=0): """ Read split-triangles slice, to be used by WebGL visualizer. """ if self._number_of_split_slices == 1: return self.triangles.load() slice_number = int(slice_number) start_idx, end_idx = self._get_slice_triangle_boundaries(slice_number) return self._split_triangles[start_idx: end_idx: 1]
[docs] def get_lines_slice(self, slice_number=0): """ Read the gl lines values for the current slice number. """ return Surface._triangles_to_lines(self.get_triangles_slice(slice_number))
[docs] def get_slices_to_hemisphere_mask(self): """ :return: a vector af length number_of_slices, with 1 when current chunk belongs to the Right hemisphere """ if not self._bi_hemispheric or self._split_slices is None: return None result = [1] * self._number_of_split_slices for key, value in self._split_slices.items(): if value[KEY_HEMISPHERE] == HEMISPHERE_LEFT: result[int(key)] = 0 return result
# todo: many of these do not belong in the data access layer but higher, adapter or gui layer ####################################### Split for Picking #######################################
[docs] def get_pick_vertices_slice(self, slice_number=0): """ Read vertices slice, to be used by WebGL visualizer with pick. """ slice_number = int(slice_number) slice_triangles = self.triangles[ slice_number * SPLIT_PICK_MAX_TRIANGLE: min(self._number_of_triangles, (slice_number + 1) * SPLIT_PICK_MAX_TRIANGLE) ] result_vertices = [] cache_vertices = self.vertices.load() for triang in slice_triangles: result_vertices.append(cache_vertices[triang[0]]) result_vertices.append(cache_vertices[triang[1]]) result_vertices.append(cache_vertices[triang[2]]) return numpy.array(result_vertices)
[docs] def get_pick_vertex_normals_slice(self, slice_number=0): """ Read vertex-normals slice, to be used by WebGL visualizer with pick. """ slice_number = int(slice_number) slice_triangles = self.triangles[ slice_number * SPLIT_PICK_MAX_TRIANGLE: min(self.number_of_triangles.load(), (slice_number + 1) * SPLIT_PICK_MAX_TRIANGLE) ] result_normals = [] cache_vertex_normals = self.vertex_normals.load() for triang in slice_triangles: result_normals.append(cache_vertex_normals[triang[0]]) result_normals.append(cache_vertex_normals[triang[1]]) result_normals.append(cache_vertex_normals[triang[2]]) return numpy.array(result_normals)
[docs] def get_pick_triangles_slice(self, slice_number=0): """ Read triangles slice, to be used by WebGL visualizer with pick. """ slice_number = int(slice_number) no_of_triangles = (min(self._number_of_triangles, (slice_number + 1) * SPLIT_PICK_MAX_TRIANGLE) - slice_number * SPLIT_PICK_MAX_TRIANGLE) triangles_array = numpy.arange(no_of_triangles * 3).reshape((no_of_triangles, 3)) return triangles_array
# The h5 file format is not different for these surface subtypes # so we should not create a new h5file # If we will create a self.load -> Surface then that method should # polymorphically decide on what surface subtype to construct # class CorticalSurfaceH5(SurfaceH5):