def BuildNeuronAliases_(self):
self.neuron_aliases = {}
for name, spec in self.neuron_alias_definitions.items():
visited_aliases = set()
neuron_subgroups = set()
to_visit = list()
to_visit.append(name)
while to_visit:
subgroup_name = to_visit.pop()
if subgroup_name in visited_aliases:
print "In neuron_alias %s:" % name
print " Loop detected with subgroup %s" % subgroup_name
return False
if subgroup_name in self.neuron_groups:
neuron_subgroups.add(self.neuron_groups[subgroup_name])
elif subgroup_name in self.neuron_alias_definitions:
visited_aliases.add(subgroup_name)
subgroups = self.neuron_alias_definitions[subgroup_name]["subgroups"]
to_visit = to_visit + subgroups
else:
print "In neuron_alias %s:" % name
print " subgroup %s is neither an alias or group" % subgroup_name
return False
neuron_alias = (
pyncs.NeuronAlias(pyncs.neuron_group_list(list(neuron_subgroups)))
)
self.neuron_aliases[str(name)] = neuron_alias
for name, group in self.neuron_groups.items():
neuron_alias = (
pyncs.NeuronAlias(pyncs.neuron_group_list([group]))
)
self.neuron_aliases[str(name)] = neuron_alias
return True
def BuildNeuronAliases_(self):
self.neuron_aliases = {}
for name, spec in self.neuron_alias_definitions.items():
visited_aliases = set()
neuron_subgroups = set()
to_visit = list()
to_visit.append(name)
while to_visit:
subgroup_name = to_visit.pop()
if subgroup_name in visited_aliases:
print "In neuron_alias %s:" % name
print " Loop detected with subgroup %s" % subgroup_name
return False
if subgroup_name in self.neuron_groups:
neuron_subgroups.add(self.neuron_groups[subgroup_name])
elif subgroup_name in self.neuron_alias_definitions:
visited_aliases.add(subgroup_name)
subgroups = self.neuron_alias_definitions[subgroup_name][
"subgroups"]
to_visit = to_visit + subgroups
else:
print "In neuron_alias %s:" % name
print " subgroup %s is neither an alias or group" % subgroup_name
return False
neuron_alias = (pyncs.NeuronAlias(
pyncs.neuron_group_list(list(neuron_subgroups))))
self.neuron_aliases[str(name)] = neuron_alias
for name, group in self.neuron_groups.items():
neuron_alias = (pyncs.NeuronAlias(pyncs.neuron_group_list([group
])))
self.neuron_aliases[str(name)] = neuron_alias
return True
def BuildSynapseGroups_(self):
self.synapse_groups = {}
for name, spec in self.synapse_group_definitions.items():
model_name = str(spec["specification"])
presynaptic_name = str(spec["presynaptic"])
probability = float(spec["probability"])
presynaptic_groups = list()
if presynaptic_name in self.neuron_groups:
presynaptic_groups.append(self.neuron_groups[presynaptic_name])
elif presynaptic_name in self.neuron_aliases:
for subgroup in self.neuron_aliases[
presynaptic_name].getSubgroups():
presynaptic_groups.append(subgroup)
else:
print "For synapse_group %s:" % name
print " %s is not a neuron_group or neuron_alias" % presynaptic_name
return False
postsynaptic_name = str(spec["postsynaptic"])
postsynaptic_groups = list()
if postsynaptic_name in self.neuron_groups:
postsynaptic_groups.append(
self.neuron_groups[postsynaptic_name])
elif postsynaptic_name in self.neuron_aliases:
for subgroup in self.neuron_aliases[
postsynaptic_name].getGroups():
postsynaptic_groups.append(subgroup)
else:
print "For synapse_group %s:" % name
print " %s is not a neuron_group or neuron_alias" % postsynaptic_name
return False
if model_name not in self.model_parameters:
print "For synapse_group %s" % name
print " %s is not a defined model_parameters" % model_name
return False
parameters = self.model_parameters[model_name]
synapse_group = (pyncs.SynapseGroup(
pyncs.neuron_group_list(presynaptic_groups),
pyncs.neuron_group_list(postsynaptic_groups), parameters,
probability))
self.synapse_groups[str(name)] = synapse_group
return True
def BuildSynapseGroups_(self):
self.synapse_groups = {}
for name, spec in self.synapse_group_definitions.items():
model_name = str(spec["specification"])
presynaptic_name = str(spec["presynaptic"])
probability = float(spec["probability"])
presynaptic_groups = list()
if presynaptic_name in self.neuron_groups:
presynaptic_groups.append(self.neuron_groups[presynaptic_name])
elif presynaptic_name in self.neuron_aliases:
for subgroup in self.neuron_aliases[presynaptic_name].getSubgroups():
presynaptic_groups.append(subgroup)
else:
print "For synapse_group %s:" % name
print " %s is not a neuron_group or neuron_alias" % presynaptic_name
return False
postsynaptic_name = str(spec["postsynaptic"])
postsynaptic_groups = list()
if postsynaptic_name in self.neuron_groups:
postsynaptic_groups.append(self.neuron_groups[postsynaptic_name])
elif postsynaptic_name in self.neuron_aliases:
for subgroup in self.neuron_aliases[postsynaptic_name].getGroups():
postsynaptic_groups.append(subgroup)
else:
print "For synapse_group %s:" % name
print " %s is not a neuron_group or neuron_alias" % postsynaptic_name
return False
if model_name not in self.model_parameters:
print "For synapse_group %s" % name
print " %s is not a defined model_parameters" % model_name
return False
parameters = self.model_parameters[model_name]
synapse_group = (
pyncs.SynapseGroup(pyncs.neuron_group_list(presynaptic_groups),
pyncs.neuron_group_list(postsynaptic_groups),
parameters,
probability)
)
self.synapse_groups[str(name)] = synapse_group
return True
def init(self, argv):
self.model_specification = pyncs.ModelSpecification()
self.model_specification.thisown = False
#self.model_specification.model_parameters = (
# pyncs.string_to_model_parameters_map(self.model_parameters)
# )
neuron_group_map = {}
for name, cell_group in self.cell_groups.items():
model_parameters = self.getNeuronParameters(cell_group.parameters)
if not model_parameters:
print "ModelParameters %s not found" % cell_group.parameters
return False
neuron_group = pyncs.NeuronGroup(cell_group.count,
model_parameters,
cell_group.geometry)
cell_group.neuron_group = neuron_group
neuron_group.thisown = False
neuron_group_map[name] = neuron_group
self.model_specification.neuron_groups = (
pyncs.string_to_neuron_group_map(neuron_group_map))
for name, alias in self.cell_aliases.items():
if not alias.resolved:
if not self.resolveCellAlias_(alias):
print "Failed to resolve CellAlias %s" % name
return False
neuron_groups = [x.neuron_group for x in alias.subgroups]
neuron_group_list = pyncs.neuron_group_list(neuron_groups)
alias.neuron_alias = pyncs.NeuronAlias(neuron_group_list)
neuron_alias_map = {
n: a.neuron_alias
for n, a in self.cell_aliases.items()
}
self.model_specification.neuron_aliases = (
pyncs.string_to_neuron_alias_map(neuron_alias_map))
connection_map = {}
for name, connection in self.connections.items():
if not connection.presynaptic.resolved:
if not self.resolveCellAlias_(connection.presynaptic):
print "Invalid presynaptic group in connection %s" % name
return False
if not connection.postsynaptic.resolved:
if not self.resolveCellAlias_(connection.postsynaptic):
print "Invalid postsynaptic group in connection %s" % name
return False
model_parameters = self.getSynapseParameters(connection.parameters)
if not model_parameters:
print "ModelParameters %s not found" % connection.parameters
return False
group = pyncs.neuron_group_list
presynaptic_neuron_groups = [
x.neuron_group for x in connection.presynaptic.subgroups
]
presynaptic = group(
[x.neuron_group for x in connection.presynaptic.subgroups])
postsynaptic = group(
[x.neuron_group for x in connection.postsynaptic.subgroups])
synapse_group = pyncs.SynapseGroup(presynaptic, postsynaptic,
model_parameters,
connection.probability)
connection.synapse_group = synapse_group
synapse_group.thisown = False
connection_map[name] = synapse_group
self.model_specification.synapse_groups = (
pyncs.string_to_synapse_group_map(connection_map))
for name, alias in self.connection_aliases.items():
if not alias.resolved:
if not self.resolveConnectionAlias_(alias):
print "Failed to resolve ConnectionAlias %s" % name
return False
synapse_groups = [x.synapse_group for x in alias.subgroups]
synapse_group_list = pyncs.synapse_group_list(synapse_groups)
alias.synapse_alias = pyncs.SynapseAlias(synapse_group_list)
synapse_alias_map = {
n: a.synapse_alias
for n, a in self.connection_aliases.items()
}
self.model_specification.synapse_aliases = (
pyncs.string_to_synapse_alias_map(synapse_alias_map))
self.simulation = pyncs.Simulation(self.model_specification,
self.simulaton_parameters)
return self.simulation.init(pyncs.string_list(argv))
def init(self, argv):
self.model_specification = pyncs.ModelSpecification()
self.model_specification.thisown = False
#self.model_specification.model_parameters = (
# pyncs.string_to_model_parameters_map(self.model_parameters)
# )
neuron_group_map = {}
for name, cell_group in self.cell_groups.items():
model_parameters = self.getNeuronParameters(cell_group.parameters)
if not model_parameters:
print "ModelParameters %s not found" % cell_group.parameters
return False
neuron_group = pyncs.NeuronGroup(cell_group.count,
model_parameters,
cell_group.geometry)
cell_group.neuron_group = neuron_group
neuron_group.thisown = False
neuron_group_map[name] = neuron_group
self.model_specification.neuron_groups = (
pyncs.string_to_neuron_group_map(neuron_group_map)
)
for name, alias in self.cell_aliases.items():
if not alias.resolved:
if not self.resolveCellAlias_(alias):
print "Failed to resolve CellAlias %s" % name
return False
neuron_groups = [x.neuron_group for x in alias.subgroups]
neuron_group_list = pyncs.neuron_group_list(neuron_groups)
alias.neuron_alias = pyncs.NeuronAlias(neuron_group_list)
neuron_alias_map = { n : a.neuron_alias
for n, a in self.cell_aliases.items() }
self.model_specification.neuron_aliases = (
pyncs.string_to_neuron_alias_map(neuron_alias_map)
)
connection_map = {}
for name, connection in self.connections.items():
if not connection.presynaptic.resolved:
if not self.resolveCellAlias_(connection.presynaptic):
print "Invalid presynaptic group in connection %s" % name
return False
if not connection.postsynaptic.resolved:
if not self.resolveCellAlias_(connection.postsynaptic):
print "Invalid postsynaptic group in connection %s" % name
return False
model_parameters = self.getSynapseParameters(connection.parameters)
if not model_parameters:
print "ModelParameters %s not found" % connection.parameters
return False
group = pyncs.neuron_group_list
presynaptic_neuron_groups = [x.neuron_group
for x in connection.presynaptic.subgroups]
presynaptic = group([x.neuron_group
for x in connection.presynaptic.subgroups])
postsynaptic = group([x.neuron_group
for x in connection.postsynaptic.subgroups])
synapse_group = pyncs.SynapseGroup(presynaptic,
postsynaptic,
model_parameters,
connection.probability)
connection.synapse_group = synapse_group
synapse_group.thisown = False
connection_map[name] = synapse_group
self.model_specification.synapse_groups = (
pyncs.string_to_synapse_group_map(connection_map)
)
for name, alias in self.connection_aliases.items():
if not alias.resolved:
if not self.resolveConnectionAlias_(alias):
print "Failed to resolve ConnectionAlias %s" % name
return False
synapse_groups = [x.synapse_group for x in alias.subgroups]
synapse_group_list = pyncs.synapse_group_list(synapse_groups)
alias.synapse_alias = pyncs.SynapseAlias(synapse_group_list)
synapse_alias_map = { n : a.synapse_alias
for n, a in self.connection_aliases.items() }
self.model_specification.synapse_aliases = (
pyncs.string_to_synapse_alias_map(synapse_alias_map)
)
self.simulation = pyncs.Simulation(self.model_specification,
self.simulaton_parameters)
return self.simulation.init(pyncs.string_list(argv))