def run(argv):
args = argparser().parse_args(argv)
delay = args.delay * un.ms
# Import of nest needs to be after arguments have been passed as it kills
# them before the SLI interpreter tries to read them.
if args.simulator == 'nest':
from pype9.simulate.nest import CellMetaClass, Simulation # @IgnorePep8 @UnusedImport
elif args.simulator == 'neuron':
from pype9.simulate.neuron import CellMetaClass, Simulation # @IgnorePep8 @Reimport
else:
raise Exception("Unrecognised simulator '{}' (can be either 'nest' or "
"'neuron')".format(args.simulator))
# Get and combine 9ML models
input_model = ninemlcatalog.load('input/ConstantRate', 'ConstantRate')
liaf_model = ninemlcatalog.load('neuron/LeakyIntegrateAndFire',
'LeakyIntegrateAndFire')
alpha_model = ninemlcatalog.load('postsynapticresponse/Alpha', 'Alpha')
weight_model = ninemlcatalog.load('plasticity/Static', 'Static')
multi_model = MultiDynamics(name="test_alpha_syn",
sub_components={
'cell': liaf_model,
'psr': alpha_model,
'pls': weight_model
},
port_connections=[('psr', 'i_synaptic', 'cell',
'i_synaptic'),
('pls', 'fixed_weight',
'psr', 'weight')],
port_exposures=[('psr', 'input_spike'),
('cell', 'spike_output')])
# Add connection weight
conn_params = []
if args.connection_weight:
conn_params.append(
ConnectionParameterSet('input_spike__psr',
[multi_model.parameter('weight__pls')]))
# Reinterpret the multi-component model as one containing synapses that can
# be set by connection weights
w_syn_model = WithSynapses.wrap(multi_model,
connection_parameter_sets=conn_params)
# Generate Pype9 classes
Input = CellMetaClass(input_model, build_mode=args.build_mode)
Cell = CellMetaClass(w_syn_model, build_mode=args.build_mode)
# Create instances
rate = args.rate * un.Hz
weight = args.weight * un.nA
cell_params = {
'tau__cell': args.tau * un.ms,
'R__cell': 1.5 * un.Mohm,
'refractory_period__cell': 2.0 * un.ms,
'v_threshold__cell': args.threshold * un.mV,
'v_reset__cell': 0.0 * un.mV,
'tau__psr': 0.5 * un.ms,
'regime_': 'subthreshold___sole___sole',
'b__psr': 0.0 * un.nA,
'a__psr': 0.0 * un.nA,
'v__cell': 0.0 * un.mV,
'refractory_end__cell': 0.0 * un.ms
}
# If PSR weight is part of the cell dynamics (as opposed to the connection)
if args.connection_weight:
conn_properties = [Property('weight__pls', weight)]
else:
cell_params['weight__pls'] = weight
conn_properties = []
with Simulation(args.timestep * un.ms, min_delay=delay) as sim:
input = Input(rate=rate, t_next=(1 * un.unitless) /
rate) # @ReservedAssignment @IgnorePep8
cell = Cell(**cell_params)
# Connect cells together
cell.connect(input,
'spike_output',
'input_spike__psr',
delay,
properties=conn_properties)
# Set up recorders
cell.record('spike_output__cell')
cell.record_regime()
cell.record('v__cell')
# Run simulation
sim.run(args.simtime * un.ms)
# Plot recordings
plot(cell.recordings(),
save=args.save_fig,
show=(not args.save_fig),
title='Leaky Integrate and Fire with Alpha Synapse')
print("Finished simulation.")
