def inputs(self, recurse = True): inputs = NeuroObject.inputs(self, recurse) if self.region1Projects: inputs += [self.region1] if self.region2Projects: inputs += [self.region2] return inputs
def inputs(self, recurse = True): inputs = NeuroObject.inputs(self, recurse) if self.sendsOutput: inputs += [self.neurite] if self.receivesInput: inputs += [self.region] return inputs
def inputs(self, recurse = True): """ Return a list of all objects that send information into this neuron and optionally any extending :class:`neurites <Network.Neurite.Neurite>`. The list may contain any number of :class:`arborizations <Network.Arborization.Arborization>`, :class:`gap junctions <Network.GapJunction.GapJunction>`, :class:`stimuli <Network.Stimulus.Stimulus>` or :class:`synapses <Network.Synapse.Synapse>`. """ return NeuroObject.inputs(self, recurse) + self._synapses
def inputs(self, recurse = True): """ Return a list of all objects that send information into this neurite and optionally any extending neurites. The list may contain any number of :class:`arborizations <Network.Arborization.Arborization>`, :class:`gap junctions <Network.GapJunction.GapJunction>`, :class:`stimuli <Network.Stimulus.Stimulus>` or :class:`synapses <Network.Synapse.Synapse>`. """ inputs = NeuroObject.inputs(self, recurse) + self.gapJunctions(False) + self.synapses(includePre = False, recurse = False) if self.arborization is not None and self.arborization.receivesInput: inputs += [self.arborization] return inputs
def inputs(self, recurse = True): inputs = NeuroObject.inputs(self, recurse) for pathway in self.pathways: if pathway.region1 == self and pathway.region2Projects or pathway.region2 == self and pathway.region1Projects: inputs.append(pathway) for arborization in self.arborizations: if arborization.sendsOutput: inputs.append(arborization) if recurse: for subRegion in self.subRegions: inputs += subRegion.inputs() return inputs
def inputs(self, recurse=True): """ Return a list of all objects that send information into this neurite and optionally any extending neurites. The list may contain any number of :class:`arborizations <Network.Arborization.Arborization>`, :class:`gap junctions <Network.GapJunction.GapJunction>`, :class:`stimuli <Network.Stimulus.Stimulus>` or :class:`synapses <Network.Synapse.Synapse>`. """ inputs = ( NeuroObject.inputs(self, recurse) + self.gapJunctions(False) + self.synapses(includePre=False, recurse=False) ) if self.arborization is not None and self.arborization.receivesInput: inputs += [self.arborization] return inputs
def inputs(self, recurse = True): return NeuroObject.inputs(self, recurse) + list(self._neurites)
def inputs(self, recurse=True): return NeuroObject.inputs(self, recurse) + self._innervations
def inputs(self, recurse = True): return NeuroObject.inputs(self, recurse) + [self.preSynapticNeurite]
def inputs(self, recurse = True): return NeuroObject.inputs(self, recurse) + self._innervations
def inputs(self, recurse=True): return NeuroObject.inputs(self, recurse) + [self.neurite]
def inputs(self, recurse = True): return NeuroObject.inputs(self, recurse) + [self.neurite]