def t4():
print 'Loading Forth XML File (iaf-2coba-Model)'
print '----------------------------------------'
component = readers.XMLReader.read_component(
Join(tenml_dir, 'iaf_2coba.10ml'), component_name='iaf')
writers.XMLWriter.write(component, '/tmp/nineml_toxml4.xml', )
model = readers.XMLReader.read_component(Join(tenml_dir, 'iaf_2coba.10ml'))
from nineml.abstraction_layer.flattening import flatten
from nineml.abstraction_layer.component_modifiers import ComponentModifier
flatcomponent = flatten(model, componentname='iaf_2coba')
ComponentModifier.close_analog_port(component=flatcomponent, port_name='iaf_iSyn', value='0')
writers.XMLWriter.write(flatcomponent, '/tmp/nineml_out_iaf_2coba.9ml')
import pyNN.neuron as sim
from pyNN.utility import init_logging
init_logging(None, debug=True)
sim.setup(timestep=0.1, min_delay=0.1)
print 'Attempting to simulate From Model:'
print '----------------------------------'
celltype_cls = pyNNml.nineml_celltype_from_model(
name="iaf_2coba",
nineml_model=flatcomponent,
synapse_components=[
pyNNml.CoBaSyn(namespace='cobaExcit', weight_connector='q'),
pyNNml.CoBaSyn(namespace='cobaInhib', weight_connector='q'),
]
)
parameters = {
'iaf.cm': 1.0,
'iaf.gl': 50.0,
'iaf.taurefrac': 5.0,
'iaf.vrest': -65.0,
'iaf.vreset': -65.0,
'iaf.vthresh': -50.0,
'cobaExcit.tau': 2.0,
'cobaInhib.tau': 5.0,
'cobaExcit.vrev': 0.0,
'cobaInhib.vrev': -70.0,
}
parameters = ComponentFlattener.flatten_namespace_dict(parameters)
cells = sim.Population(1, celltype_cls, parameters)
cells.initialize('iaf_V', parameters['iaf_vrest'])
cells.initialize('tspike', -1e99) # neuron not refractory at start
cells.initialize('regime', 1002) # temporary hack
input = sim.Population(2, sim.SpikeSourcePoisson, {'rate': 100})
connector = sim.OneToOneConnector(weights=1.0, delays=0.5)
conn = [sim.Projection(input[0:1], cells, connector, target='cobaExcit'),
sim.Projection(input[1:2], cells, connector, target='cobaInhib')]
cells._record('iaf_V')
cells._record('cobaExcit_g')
cells._record('cobaInhib_g')
cells._record('cobaExcit_I')
cells._record('cobaInhib_I')
cells.record()
sim.run(100.0)
cells.recorders['iaf_V'].write("Results/nineml_neuron.V", filter=[cells[0]])
cells.recorders['cobaExcit_g'].write("Results/nineml_neuron.g_exc", filter=[cells[0]])
cells.recorders['cobaInhib_g'].write("Results/nineml_neuron.g_inh", filter=[cells[0]])
cells.recorders['cobaExcit_I'].write("Results/nineml_neuron.g_exc", filter=[cells[0]])
cells.recorders['cobaInhib_I'].write("Results/nineml_neuron.g_inh", filter=[cells[0]])
t = cells.recorders['iaf_V'].get()[:, 1]
v = cells.recorders['iaf_V'].get()[:, 2]
gInh = cells.recorders['cobaInhib_g'].get()[:, 2]
gExc = cells.recorders['cobaExcit_g'].get()[:, 2]
IInh = cells.recorders['cobaInhib_I'].get()[:, 2]
IExc = cells.recorders['cobaExcit_I'].get()[:, 2]
import pylab
pylab.subplot(311)
pylab.ylabel('Voltage')
pylab.plot(t, v)
pylab.subplot(312)
pylab.ylabel('Conductance')
pylab.plot(t, gInh)
pylab.plot(t, gExc)
pylab.subplot(313)
pylab.ylabel('Current')
pylab.plot(t, IInh)
pylab.plot(t, IExc)
pylab.suptitle("From Tree-Model Pathway")
pylab.show()
sim.end()
