def test_connect_with_scalar_weights_and_delays(self):
connections = numpy.array([
[0, 1, 1, 0],
[1, 1, 0, 1],
[0, 0, 1, 0],
])
C = connectors.ArrayConnector(connections, safe=False)
syn = sim.StaticSynapse(weight=5.0, delay=0.5)
prj = sim.Projection(self.p1, self.p2, C, syn)
self.assertEqual(prj.get(["weight", "delay"], format='list', gather=False), # use gather False because we are faking the MPI
[(1, 0, 5.0, 0.5),
(0, 2, 5.0, 0.5),
(2, 2, 5.0, 0.5)])
def test_connect_with_random_weights_parallel_safe(self):
rd_w = random.RandomDistribution(rng=MockRNG(delta=1.0, parallel_safe=True))
rd_d = random.RandomDistribution(rng=MockRNG(start=1.0, delta=0.1, parallel_safe=True))
syn = sim.StaticSynapse(weight=rd_w, delay=rd_d)
connections = numpy.array([
[0, 1, 1, 0],
[1, 1, 0, 1],
[0, 0, 1, 0],
])
C = connectors.ArrayConnector(connections, safe=False)
prj = sim.Projection(self.p1, self.p2, C, syn)
self.assertEqual(prj.get(["weight", "delay"], format='list', gather=False), # use gather False because we are faking the MPI
[(1, 0, 0.0, 1.0),
(0, 2, 3.0, 1.3),
(2, 2, 4.0, 1.4000000000000001)]) # better to do an "almost-equal" check
def test_connect_with_scalar_weights_and_delays(self, sim=sim):
connections = np.array([
[0, 1, 1, 0],
[1, 1, 0, 1],
[0, 0, 1, 0],
], dtype=bool)
C = connectors.ArrayConnector(connections, safe=False)
syn = sim.StaticSynapse(weight=5.0, delay=0.5)
prj = sim.Projection(self.p1, self.p2, C, syn)
self.assertEqual(prj.get(["weight", "delay"], format='list'),
[(1, 0, 5.0, 0.5),
(0, 1, 5.0, 0.5),
(1, 1, 5.0, 0.5),
(0, 2, 5.0, 0.5),
(2, 2, 5.0, 0.5),
(1, 3, 5.0, 0.5)])
def test_connect_with_random_weights_parallel_safe(self, sim=sim):
rd_w = random.RandomDistribution(
'uniform', (0, 1), rng=MockRNG(delta=1.0, parallel_safe=True))
rd_d = random.RandomDistribution('uniform', (0, 1), rng=MockRNG(
start=1.0, delta=0.1, parallel_safe=True))
syn = sim.StaticSynapse(weight=rd_w, delay=rd_d)
connections = np.array([
[0, 1, 1, 0],
[1, 1, 0, 1],
[0, 0, 1, 0],
], dtype=bool)
C = connectors.ArrayConnector(connections, safe=False)
prj = sim.Projection(self.p1, self.p2, C, syn)
rec = prj.get(["weight", "delay"], format='list')
assert_array_almost_equal([tuple(r) for r in rec],
[(1, 0, 0.0, 1.0),
(0, 1, 1.0, 1.1),
(1, 1, 2.0, 1.2),
(0, 2, 3.0, 1.3),
(2, 2, 4.0, 1.4),
(1, 3, 5.0, 1.5)])
