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 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]
