def _clip_pair(self):
handlers = self._cell_pair.handlers
assert(all(handlers))
gids = self._cell_pair.gids
morphologies = self._cell_pair.morphologies
handlers[0].apply(_NeuronClipping().clipAll().unclipEfferentBranches(
gids[0], morphologies[0], self._synapses))
handlers[1].apply(_NeuronClipping().clipAll().unclipAfferentBranches(
gids[1], morphologies[1], self._synapses))
def _pick_first_cell(self, gid):
to_pick = self._cell_to_pick
def other(cell_to_pick):
return 1 - cell_to_pick
neurons = self._scene.objects[0]
# Loading synapses
circuit = self._scene.circuit
if to_pick == self.POSTSYNAPTIC_CELL:
synapses = circuit.afferent_synapses([gid])
else:
synapses = circuit.efferent_synapses([gid])
self._synapses = synapses
# Hiding all the cells
neurons.attributes.mode = _rtneuron.RepresentationMode.NO_DISPLAY
neurons.update()
# Highlighting the cell picked and displaying it in detailed mode.
selected = neurons.query([gid])
selected.attributes.mode = \
_rtneuron.RepresentationMode.WHOLE_NEURON
selected.attributes.color_scheme = _rtneuron.ColorScheme.SOLID
selected.attributes.primary_color = self._cell_colors[to_pick]
selected.update()
# Make sure the cell is unclipped at this point.
selected.apply(_NeuronClipping().unclipAll())
# Finding the connected cells and grouping the synapses per connection.
if to_pick == self.PRESYNAPTIC_CELL:
connected = synapses.post_gids()
else:
connected = synapses.pre_gids()
connected = _np.unique(connected)
connections = dict()
for i in connected:
pre = [gid if to_pick == self.PRESYNAPTIC_CELL else int(i)]
post = [int(i) if to_pick == self.PRESYNAPTIC_CELL else gid]
connections[i] = circuit.projected_synapses(pre, post)
# Setting the mask for making only the connected cells selectable.
mask = _np.setdiff1d(neurons.object, connected)
self._base_selection_mask = mask
connected = neurons.query(connected)
# Adding one synapes set per connection. Doing this instead
# of adding a single set makes it easier to apply a different color
# to each synapse subset.
functors = [_rtneuron.Scene.addEfferentSynapses,
_rtneuron.Scene.addAfferentSynapses]
attributes = _rtneuron.AttributeMap()
attributes.radius = self._synapse_radius
self._synapse_handlers = dict()
_rtneuron.engine.pause()
for key, synapses in connections.items():
self._synapse_handlers[key] = \
functors[to_pick](self._scene, synapses, attributes)
_rtneuron.engine.resume()
# Applying the coloring based on the user selection
self._coloring_handler.set_target_cells(
connected, self._cell_colors[other(to_pick)],
visible=self._show_connected_cells)
self._coloring_handler.set_target_synapses(
self._synapse_handlers, self._synapse_colors[to_pick])
self._coloring_handler.colorize()
# Updating state variables
self._cell_pair.handlers[to_pick] = selected
self._cell_pair.gids[to_pick] = gid
self._connected_cells = connected
self._cell_to_pick = other(to_pick)
self._update_connection_info.emit()
self._connected_cells_hideable.emit(True)
# Setting the new home position for the view
position = list(map(float, circuit.positions([gid])[0]))
view = _rtneuron.engine.views[0]
view.cameraManipulator.setHomePosition(
view.camera.getView()[0], position, [0, 1, 0])
def _unclip_pair(self):
for handler in self._cell_pair.handlers:
handler.apply(_NeuronClipping().unclipAll())