def test_simple(self):
nodes = nest.Create('iaf_psc_alpha', 5)
nest.Connect(nodes, nodes, 'one_to_one')
nest.DisconnectOneToOne(nodes[0], nodes[0], 'static_synapse')
self.assertEqual(nest.GetKernelStatus('num_connections'), 4)
def test_synapse_deletion_one_to_one_no_sp(self):
for syn_model in nest.Models('synapses'):
if syn_model not in self.exclude_synapse_model:
nest.ResetKernel()
print(syn_model)
nest.SetKernelStatus({
'resolution': 0.1,
'total_num_virtual_procs': self.num_procs
})
neurons = nest.Create('iaf_psc_alpha', 4)
syn_dict = {'model': syn_model}
nest.Connect([neurons[0]], [neurons[2]], "one_to_one",
syn_dict)
nest.Connect([neurons[1]], [neurons[3]], "one_to_one",
syn_dict)
# Delete existent connection
conns = nest.GetConnections([neurons[0]], [neurons[2]],
syn_model)
if mpi_test:
conns = self.comm.allgather(conns)
conns = filter(None, conns)
assert len(list(conns)) == 1
nest.DisconnectOneToOne(neurons[0], neurons[2], syn_dict)
conns = nest.GetConnections([neurons[0]], [neurons[2]],
syn_model)
if mpi_test:
conns = self.comm.allgather(conns)
conns = filter(None, conns)
assert len(list(conns)) == 0
# Assert that one can not delete a non existent connection
conns1 = nest.GetConnections([neurons[0]], [neurons[1]],
syn_model)
if mpi_test:
conns1 = self.comm.allgather(conns1)
conns1 = filter(None, conns1)
assert len(list(conns1)) == 0
try:
nest.DisconnectOneToOne(neurons[0], neurons[1], syn_dict)
assert False
except nest.kernel.NESTError:
print("Synapse deletion ok: " + syn_model)
def test_single_synapse_deletion_sp(self):
for syn_model in nest.Models('synapses'):
if syn_model not in self.exclude_synapse_model:
nest.ResetKernel()
nest.CopyModel('static_synapse', 'my_static_synapse')
syn_dict = {
'model': syn_model,
'pre_synaptic_element': 'SE1',
'post_synaptic_element': 'SE2'
}
# nest.SetKernelStatus(
# {'structural_plasticity_synapses': {'syn1': syn_dict}}
# )
neurons = nest.Create(
'iaf_psc_alpha', 2, {
'synaptic_elements': {
'SE1': {
'z': 0.0,
'growth_rate': 0.0
},
'SE2': {
'z': 0.0,
'growth_rate': 0.0
}
}
})
nest.Connect(neurons, neurons, "all_to_all", syn_dict)
nest.Connect(neurons, neurons, "all_to_all",
{'model': 'my_static_synapse'})
# Test if the connected synaptic elements before the simulation
# are correct
status = nest.GetStatus(neurons, 'synaptic_elements')
for st_neuron in status:
self.assertEqual(2, st_neuron['SE1']['z_connected'])
self.assertEqual(2, st_neuron['SE2']['z_connected'])
srcId = 0
targId = 1
conns = nest.GetConnections([neurons[srcId]],
[neurons[targId]], syn_model)
assert conns
nest.DisconnectOneToOne(neurons[srcId], neurons[targId],
syn_dict)
status = nest.GetStatus(neurons, 'synaptic_elements')
self.assertEqual(1, status[srcId]['SE1']['z_connected'])
self.assertEqual(2, status[srcId]['SE2']['z_connected'])
self.assertEqual(2, status[targId]['SE1']['z_connected'])
self.assertEqual(1, status[targId]['SE2']['z_connected'])
conns = nest.GetConnections([neurons[srcId]],
[neurons[targId]], syn_model)
assert not conns
def test_synapse_deletion_one_to_one_no_sp(self):
for syn_model in nest.Models('synapses'):
if syn_model not in self.exclude_synapse_model:
nest.ResetKernel()
nest.CopyModel('static_synapse', 'my_static_synapse')
neurons = nest.Create('iaf_neuron', 2)
syn_dict = {'model': syn_model}
nest.Connect(neurons, neurons, "all_to_all", syn_dict)
srcId = 0
targId = 1
conns = nest.GetConnections([neurons[srcId]],[neurons[targId]],syn_model)
assert len(conns) == 1
nest.DisconnectOneToOne(neurons[srcId], neurons[targId], syn_dict)
conns = nest.GetConnections([neurons[srcId]],[neurons[targId]],syn_model)
assert len(conns) == 0
