def Run(argv):
if len(argv) < 2:
print "Usage: %s <model_file>" % argv[0]
model = json_model.JSONModel(argv[1])
if not model.valid:
print "Failed to load model"
return
model_specification = model.model_specification
simulation_parameters = pyncs.SimulationParameters()
simulation_parameters.thisown = False;
simulation = pyncs.Simulation(model_specification,
simulation_parameters)
if not simulation.init(pyncs.string_list(argv)):
print "Failed to initialize simulator."
return
print "Injecting pre-specified inputs."
for name, group in model.input_groups.items():
simulation.addInput(group)
print "Injection complete."
print "Adding reports."
sinks = {}
for name, report in model.reports.items():
source = simulation.addReport(report)
if not source:
print "Failed to add report %s" % name
return
#sinks[name] = pyncs.NullSink(source)
#sinks[name] = pyncs.AsciiStreamSink(source)
#sinks[name] = pyncs.AsciiFileSink(source, "/dev/fd/0")
sinks[name] = pyncs.AsciiFileSink(source, "/dev/fd/0")
print "Starting simulation."
for i in range(0,100):
simulation.step()
del simulation
def Run(argv):
if len(argv) < 2:
print "Usage: %s <model_file>" % argv[0]
model = json_model.JSONModel(argv[1])
if not model.valid:
print "Failed to load model"
return
model_specification = model.model_specification
simulation_parameters = pyncs.SimulationParameters()
simulation_parameters.thisown = False
simulation = pyncs.Simulation(model_specification, simulation_parameters)
if not simulation.init(pyncs.string_list(argv)):
print "Failed to initialize simulator."
return
print "Injecting pre-specified inputs."
for name, group in model.input_groups.items():
simulation.addInput(group)
print "Injection complete."
print "Adding reports."
sinks = {}
for name, report in model.reports.items():
source = simulation.addReport(report)
if not source:
print "Failed to add report %s" % name
return
#sinks[name] = pyncs.NullSink(source)
#sinks[name] = pyncs.AsciiStreamSink(source)
#sinks[name] = pyncs.AsciiFileSink(source, "/dev/fd/0")
sinks[name] = pyncs.AsciiFileSink(source, "/dev/fd/0")
print "Starting simulation."
for i in range(0, 100):
simulation.step()
del simulation
def addStimulus(self,
type_name,
parameters,
groups,
probability,
start_time,
end_time):
if not self.simulation.isMaster():
return True
group_list = None
if isinstance(groups, list):
group_list = list(groups)
else:
group_list = [groups]
group_names = []
for group in group_list:
if isinstance(group, str):
if group not in self.cell_aliases:
print "Cell group or alias %s was never registered." % group
return False
group_names.append(group)
elif isinstance(group, CellAlias):
if not group.name:
print "Anonymous CellAlias cannot be used for input."
return False
group_names.append(group.name)
elif isinstance(group, CellGroup):
if not group.name:
print "Anonymous CellGroup cannot be used for input."
return False
group_names.append(group.name)
else:
print "Unknown input group type."
return False
if not group_names:
print "No groups specified for Input."
return False
model_parameters = self.buildModelParameters_(type_name, parameters)
if not model_parameters:
print "Failed to build model parameters for input"
return False
model_parameters.thisown = False
input_group = pyncs.InputGroup(pyncs.string_list(group_names),
model_parameters,
probability,
start_time,
end_time)
return self.simulation.addInput(input_group)
def BuildReports_(self):
self.reports = {}
for name, spec in self.report_definitions.items():
target = pyncs.Report.Unknown
target_string = str(spec["target"])
if target_string == "neuron":
target = pyncs.Report.Neuron
elif target_string == "synapse":
target = pyncs.Report.Synapse
else:
print "invalid target specified in report %s" % name
return False
percentage = float(spec["percentage"])
aliases = [str(x) for x in spec["aliases"]]
report = pyncs.Report(pyncs.string_list(aliases), target,
str(spec["attribute"]), percentage)
self.reports[str(name)] = report
return True
def addStimulus(self, type_name, parameters, groups, probability,
start_time, end_time):
if not self.simulation.isMaster():
return True
group_list = None
if isinstance(groups, list):
group_list = list(groups)
else:
group_list = [groups]
group_names = []
for group in group_list:
if isinstance(group, str):
if group not in self.cell_aliases:
print "Cell group or alias %s was never registered." % group
return False
group_names.append(group)
elif isinstance(group, CellAlias):
if not group.name:
print "Anonymous CellAlias cannot be used for input."
return False
group_names.append(group.name)
elif isinstance(group, CellGroup):
if not group.name:
print "Anonymous CellGroup cannot be used for input."
return False
group_names.append(group.name)
else:
print "Unknown input group type."
return False
if not group_names:
print "No groups specified for Input."
return False
model_parameters = self.buildModelParameters_(type_name, parameters)
if not model_parameters:
print "Failed to build model parameters for input"
return False
model_parameters.thisown = False
input_group = pyncs.InputGroup(pyncs.string_list(group_names),
model_parameters, probability,
start_time, end_time)
return self.simulation.addInput(input_group)
def BuildReports_(self):
self.reports = {}
for name, spec in self.report_definitions.items():
target = pyncs.Report.Unknown
target_string = str(spec["target"])
if target_string == "neuron":
target = pyncs.Report.Neuron
elif target_string == "synapse":
target = pyncs.Report.Synapse
else:
print "invalid target specified in report %s" % name
return False
percentage = float(spec["percentage"])
aliases = [ str(x) for x in spec["aliases"] ]
report = pyncs.Report(pyncs.string_list(aliases),
target,
str(spec["attribute"]),
percentage)
self.reports[str(name)] = report
return True
def addReport(self, targets, target_type, attribute, probability, start_time, end_time):
if not self.simulation.isMaster():
return EmptyReport()
target = pyncs.Report.Unknown
target_list = None
if isinstance(targets, list):
target_list = list(targets)
else:
target_list = [targets]
target_names = None
if target_type == "neuron":
target = pyncs.Report.Neuron
alias = CellAlias(None, targets)
if not self.resolveCellAlias_(alias):
print "A target was ill-defined."
return None
target_names = [ x.name for x in alias.subgroups ]
elif target_type == "synapse":
target = pyncs.Report.Synapse
alias = ConnectionAlias(None, targets)
if not self.resolveConnectionAlias_(alias):
print "A target was ill-defined."
return None
target_names = [ x.name for x in alias.subgroups ]
else:
print "Invalid target specified."
return None
report = pyncs.Report(pyncs.string_list(target_names),
target,
attribute,
probability,
start_time,
end_time)
data_source = self.simulation.addReport(report)
if not data_source:
print "Failed to add report."
return None
return Report(data_source)
def addReport(self, targets, target_type, attribute, probability,
start_time, end_time):
if not self.simulation.isMaster():
return EmptyReport()
target = pyncs.Report.Unknown
target_list = None
if isinstance(targets, list):
target_list = list(targets)
else:
target_list = [targets]
target_names = None
if target_type == "neuron":
target = pyncs.Report.Neuron
alias = CellAlias(None, targets)
if not self.resolveCellAlias_(alias):
print "A target was ill-defined."
return None
target_names = [x.name for x in alias.subgroups]
elif target_type == "synapse":
target = pyncs.Report.Synapse
alias = ConnectionAlias(None, targets)
if not self.resolveConnectionAlias_(alias):
print "A target was ill-defined."
return None
target_names = [x.name for x in alias.subgroups]
else:
print "Invalid target specified."
return None
report = pyncs.Report(pyncs.string_list(target_names), target,
attribute, probability, start_time, end_time)
data_source = self.simulation.addReport(report)
if not data_source:
print "Failed to add report."
return None
return Report(data_source)
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))