def test_get_plasticity_attribute_as_list(self, sim=sim):
U_distr = random.RandomDistribution('uniform',
low=0.4,
high=0.6,
rng=MockRNG(start=0.5,
delta=0.001))
depressing = sim.TsodyksMarkramSynapse(U=U_distr,
tau_rec=lambda d: 80.0 + d,
tau_facil=0.0)
prj = sim.Projection(self.p1,
self.p2,
connector=self.all2all,
synapse_type=depressing)
U = prj.get("U", format="list")
U = _sort_by_column(U, 1)[:5]
U_target = numpy.array([
(0, 0, 0.5),
(1, 0, 0.501),
(2, 0, 0.502),
(3, 0, 0.503),
(4, 0, 0.504),
])
assert_array_equal(U, U_target)
tau_rec = prj.get("tau_rec", format="list")
tau_rec = _sort_by_column(tau_rec, 1)[:5]
tau_rec_target = numpy.array([
(0, 0, 80),
(1, 0, 81),
(2, 0, 82),
(3, 0, 83),
(4, 0, 84),
])
assert_array_equal(tau_rec, tau_rec_target)
def test_create_with_fast_synapse_dynamics(self, sim=sim):
depressing = sim.TsodyksMarkramSynapse(U=0.5,
tau_rec=80.0,
tau_facil=0.0)
prj = sim.Projection(self.p1,
self.p2,
connector=self.all2all,
synapse_type=depressing)
def setUp(self, sim=sim, **extra):
sim.setup(**extra)
self.p1 = sim.Population(7, sim.IF_cond_exp())
self.p2 = sim.Population(4, sim.IF_cond_exp())
self.p3 = sim.Population(5, sim.IF_curr_alpha())
self.syn1 = sim.StaticSynapse(weight=0.006, delay=0.5)
self.random_connect = sim.FixedNumberPostConnector(n=2)
self.syn2 = sim.StaticSynapse(weight=0.012, delay=0.4)
self.all2all = sim.AllToAllConnector()
self.syn3 = sim.TsodyksMarkramSynapse(weight=0.012, delay=0.6, U=0.2, tau_rec=50)
def test_create_with_default_receptor_type(self, sim=sim):
prj = sim.Projection(self.p1, self.p3, connector=self.all2all,
synapse_type=sim.StaticSynapse())
self.assertEqual(prj.receptor_type, "excitatory")
prj = sim.Projection(self.p1, self.p3, connector=self.all2all,
synapse_type=sim.TsodyksMarkramSynapse(weight=0.5))
self.assertEqual(prj.receptor_type, "excitatory")
prj = sim.Projection(self.p1, self.p3, connector=self.all2all,
synapse_type=sim.StaticSynapse(weight=lambda d: -0.1 * d))
self.assertEqual(prj.receptor_type, "inhibitory")
def test_parameter_TsodyksMarkramSynapse_random_distribution(
self, sim=sim):
U_distr = random.RandomDistribution('uniform',
low=0.4,
high=0.6,
rng=MockRNG(start=0.5,
delta=0.001))
depressing = sim.TsodyksMarkramSynapse(U=U_distr,
tau_rec=lambda d: 80.0 + d,
tau_facil=0.0)
self.assertEqual(U_distr.next(), 0.5)
def test_with_plastic_synapse(self):
connection_list = [
(0, 0, 0.1, 0.1, 100, 400),
(3, 0, 0.2, 0.11, 101, 500),
(2, 3, 0.3, 0.12, 102, 600), # local
(2, 2, 0.4, 0.13, 103, 700),
(0, 1, 0.5, 0.14, 104, 800), # local
]
C = connectors.FromListConnector(connection_list, column_names=["weight", "delay", "U", "tau_rec"])
syn = sim.TsodyksMarkramSynapse(U=99, tau_facil=88.8)
prj = sim.Projection(self.p1, self.p2, C, syn)
self.assertEqual(prj.get(["weight", "delay", "tau_facil", "tau_rec", "U"], format='list', gather=False), # use gather False because we are faking the MPI
[(0, 1, 0.5, 0.14, 88.8, 800.0, 104.0),
(2, 3, 0.3, 0.12, 88.8, 600.0, 102.0)])
def test_with_plastic_synapses_not_distributed(self, sim=sim):
connection_list = [
(0, 0, 0.1, 0.1, 100, 100),
(3, 0, 0.2, 0.11, 110, 99),
(2, 3, 0.3, 0.12, 120, 98), # local
(2, 2, 0.4, 0.13, 130, 97),
(0, 1, 0.5, 0.14, 140, 96), # local
]
file = recording.files.StandardTextFile("test.connections.2", mode='wb')
file.write(connection_list, {"columns": ["i", "j", "weight", "delay", "U", "tau_rec"]})
C = connectors.FromFileConnector("test.connections.2", distributed=False)
syn = sim.TsodyksMarkramSynapse(tau_facil=88.8)
prj = sim.Projection(self.p1, self.p2, C, syn)
self.assertEqual(prj.get(["weight", "delay", "U", "tau_rec", "tau_facil"], format='list', gather=False), # use gather False because we are faking the MPI
[(0, 1, 0.5, 0.14, 140.0, 96.0, 88.8),
(2, 3, 0.3, 0.12, 120.0, 98.0, 88.8)])
