Source code for blenderneuron.nrn.neuronsection

from blenderneuron.section import Section
from neuron import h
import numpy as np

[docs]class NeuronSection(Section):
[docs] def from_updated_blender_root(self, blender_section): self.update_coords_and_radii(blender_section) self.segments_3D = [] for i, blender_child in enumerate(blender_section["children"]): section = self.children[i] section.from_updated_blender_root(blender_child)
[docs] def from_skeletal_blender_root(self, source_section, group): try: sec_name = group.node.rank_section_name(source_section["name"]) if sec_name is not None: self.from_nrn_section(group.node.section_index[sec_name], group) except KeyError: raise Exception("Could not find section: " + sec_name + " loaded in NEURON")
[docs] def from_nrn_section(self, nrn_section, group): = group self.nrn_section = nrn_section = for nrn_child_sec in nrn_section.children(): child = NeuronSection() child.from_nrn_section(nrn_child_sec, group) self.children.append(child) self.get_coords_and_radii() parent_seg = nrn_section.parentseg() self.parent_connection_loc = parent_seg.x if parent_seg is not None else None self.connection_end = nrn_section.orientation() self.segments_3D = []
[docs] def update_coords_and_radii(self, blender_section): self.nseg = blender_section["nseg"] self.point_count = blender_section["point_count"] self.coords = blender_section["coords"] self.radii = blender_section["radii"] nrn_section = self.nrn_section # Use 3D points as the L and diam sources h.pt3dconst(1,sec=nrn_section) # Clear the existing points - and allocate room for the incoming points h.pt3dclear(self.point_count, sec=nrn_section) # Use vectorization to add the points to section coords = np.array(self.coords).reshape((-1, 3)) diams = np.array(self.radii) * 2.0 xvec = h.Vector(coords[:,0]) yvec = h.Vector(coords[:,1]) zvec = h.Vector(coords[:,2]) dvec = h.Vector(diams) h.pt3dadd(xvec, yvec, zvec, dvec, sec=nrn_section)
[docs] def get_coords_and_radii(self): nrn_section = self.nrn_section # Count 3D points point_count = int(h.n3d(sec=nrn_section)) # Let NEURON create them if missing if point_count == 0: h.define_shape(sec=self.nrn_section) point_count = int(h.n3d(sec=self.nrn_section)) # Collect the coordinates coords = [None] * point_count * 3 # 3 for xy and z radii = [None] * point_count for c in range(point_count): ci = c * 3 coords[ci] = h.x3d(c, sec=nrn_section) coords[ci + 1] = h.y3d(c, sec=nrn_section) coords[ci + 2] = h.z3d(c, sec=nrn_section) radii[c] = h.diam3d(c, sec=nrn_section) / 2.0 self.nseg = int(nrn_section.nseg) self.point_count = point_count self.coords = coords self.radii = radii
[docs] def collect_segments_recursive(self): """ Recursively collects the values of segments of a root section. Segments are given sequential 0-based names similar to NEURON cells and sections. For example, TestCell[0].dend[3][4] refers to first TestCell, 4th dendrite, 5th segment. Segment order is determined by the order in which they appear in NEURON's xyz3d() function. :return: None """ for seg in self.segments_3D: seg.collect( for child in self.children(): child.collect_segments_recursive()
[docs] def collect(self, recursive=True): """ Recursively collects the section midpoint values of a group's collect_variable (e.g. 'v') :param recursive: Whether to collect child section values (otherwise stop at root/soma) :return: None """ value = getattr(self.nrn_section(0.5), self.activity.values.append(value) if recursive: for child in self.children: child.collect(recursive=True)