def outputs(self, recurse = True):
outputs = NeuroObject.outputs(self, recurse)
if self.sendsOutput:
outputs += [self.region]
if self.receivesInput:
outputs += [self.neurite]
return outputs
def outputs(self, recurse = True):
outputs = NeuroObject.outputs(self, recurse)
if self.region1Projects:
outputs += [self.region2]
if self.region2Projects:
outputs += [self.region1]
return outputs
def outputs(self, recurse = True):
"""
Return a list of all objects that receive information from 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:`innervations <Network.Innervation.Innervation>` or :class:`synapses <Network.Synapse.Synapse>`.
"""
return NeuroObject.outputs(self, recurse)
def outputs(self, recurse = True):
"""
Return a list of all objects that receive information from 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:`innervations <Network.Innervation.Innervation>` or :class:`synapses <Network.Synapse.Synapse>`.
"""
return NeuroObject.outputs(self, recurse)
def outputs(self, recurse = True):
"""
Return a list of all objects that receive information from 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:`innervations <Network.Innervation.Innervation>` or :class:`synapses <Network.Synapse.Synapse>`.
"""
outputs = NeuroObject.outputs(self, recurse) + self.gapJunctions(False) + self.innervations(False) + self.synapses(includePost = False, recurse = False)
if self.arborization is not None and self.arborization.sendsOutput:
outputs += [self.arborization]
return outputs
def outputs(self, recurse = True):
outputs = NeuroObject.outputs(self, recurse)
for pathway in self.pathways:
if pathway.region1 == self and pathway.region1Projects or pathway.region2 == self and pathway.region2Projects:
outputs.append(pathway)
for arborization in self.arborizations:
if arborization.receivesInput:
outputs.append(arborization)
if recurse:
for subRegion in self.subRegions:
outputs += subRegion.outputs()
return outputs
def outputs(self, recurse=True):
"""
Return a list of all objects that receive information from 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:`innervations <Network.Innervation.Innervation>` or :class:`synapses <Network.Synapse.Synapse>`.
"""
outputs = (
NeuroObject.outputs(self, recurse)
+ self.gapJunctions(False)
+ self.innervations(False)
+ self.synapses(includePost=False, recurse=False)
)
if self.arborization is not None and self.arborization.sendsOutput:
outputs += [self.arborization]
return outputs
def outputs(self, recurse = True):
return NeuroObject.outputs(self, recurse) + list(self._neurites)
def outputs(self, recurse = True):
return NeuroObject.outputs(self, recurse) + self.postSynapticPartners
def outputs(self, recurse=True):
return NeuroObject.outputs(self, recurse) + [self.muscle]
def outputs(self, recurse = True):
return NeuroObject.outputs(self, recurse) + [self.muscle]
