def test_connect_with_array_weights(self, sim=sim):
C = connectors.AllToAllConnector(safe=False)
syn = sim.StaticSynapse(weight=np.arange(0.0, 2.0, 0.1).reshape(4, 5), delay=0.5)
prj = sim.Projection(self.p1, self.p2, C, syn)
assert_array_almost_equal(
np.array(prj.get(["weight", "delay"], format='list')),
np.array([
(0, 0, 0.0, 0.5),
(1, 0, 0.5, 0.5),
(2, 0, 1.0, 0.5),
(3, 0, 1.5, 0.5),
(0, 1, 0.1, 0.5),
(1, 1, 0.6, 0.5),
(2, 1, 1.1, 0.5),
(3, 1, 1.6, 0.5),
(0, 2, 0.2, 0.5),
(1, 2, 0.7, 0.5),
(2, 2, 1.2, 0.5),
(3, 2, 1.7, 0.5),
(0, 3, 0.3, 0.5),
(1, 3, 0.8, 0.5),
(2, 3, 1.3, 0.5),
(3, 3, 1.8, 0.5),
(0, 4, 0.4, 0.5),
(1, 4, 0.9, 0.5),
(2, 4, 1.4, 0.5),
(3, 4, 1.9, 0.5)]
)
)
assert_array_almost_equal(prj.get('weight', format='array'),
np.array([[0., 0.1, 0.2, 0.3, 0.4],
[0.5, 0.6, 0.7, 0.8, 0.9],
[1., 1.1, 1.2, 1.3, 1.4],
[1.5, 1.6, 1.7, 1.8, 1.9]]),
9)
def test_connect_with_random_weights_parallel_safe(self, sim=sim):
rd = random.RandomDistribution(
'uniform', (0, 1), rng=MockRNG(delta=1.0, parallel_safe=True))
syn = sim.StaticSynapse(weight=rd, delay=0.5)
C = connectors.AllToAllConnector(safe=False)
prj = sim.Projection(self.p1, self.p2, C, syn)
# note that the outer loop is over the post-synaptic cells, the inner loop over the pre-synaptic
self.assertEqual(prj.get(["weight", "delay"], format='list'),
[(0, 0, 0.0, 0.5),
(1, 0, 1.0, 0.5),
(2, 0, 2.0, 0.5),
(3, 0, 3.0, 0.5),
(0, 1, 4.0, 0.5),
(1, 1, 5.0, 0.5),
(2, 1, 6.0, 0.5),
(3, 1, 7.0, 0.5),
(0, 2, 8.0, 0.5),
(1, 2, 9.0, 0.5),
(2, 2, 10.0, 0.5),
(3, 2, 11.0, 0.5),
(0, 3, 12.0, 0.5),
(1, 3, 13.0, 0.5),
(2, 3, 14.0, 0.5),
(3, 3, 15.0, 0.5),
(0, 4, 16.0, 0.5),
(1, 4, 17.0, 0.5),
(2, 4, 18.0, 0.5),
(3, 4, 19.0, 0.5)])
assert_array_almost_equal(prj.get('weight', format='array'),
np.array([[0., 4., 8., 12., 16.],
[1., 5., 9., 13., 17.],
[2., 6., 10., 14., 18.],
[3., 7., 11., 15., 19.]]),
9)
def test_connect_with_delays_None(self):
syn = sim.StaticSynapse(weight=0.1, delay=None)
C = connectors.AllToAllConnector()
assert C.safe
assert C.allow_self_connections
prj = sim.Projection(self.p1, self.p2, C, syn)
self.assertEqual(prj.get(["weight", "delay"], format='list', gather=False)[0][3], prj._simulator.state.min_delay)
def test_connect_with_list_delays_too_small(self):
delays = numpy.ones((self.p1.size, self.p2.size), float)
delays[2, 3] = sim.Projection._simulator.state.min_delay - 0.01
syn = sim.StaticSynapse(weight=0.1, delay=delays)
C = connectors.AllToAllConnector()
self.assertRaises(errors.ConnectionError, sim.Projection, self.p1,
self.p2, C, syn)
def test_connect_with_scalar_weights_and_delays(self, sim=sim):
C = connectors.AllToAllConnector(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'),
[(0, 0, 5.0, 0.5),
(1, 0, 5.0, 0.5),
(2, 0, 5.0, 0.5),
(3, 0, 5.0, 0.5),
(0, 1, 5.0, 0.5),
(1, 1, 5.0, 0.5),
(2, 1, 5.0, 0.5),
(3, 1, 5.0, 0.5),
(0, 2, 5.0, 0.5),
(1, 2, 5.0, 0.5),
(2, 2, 5.0, 0.5),
(3, 2, 5.0, 0.5),
(0, 3, 5.0, 0.5),
(1, 3, 5.0, 0.5),
(2, 3, 5.0, 0.5),
(3, 3, 5.0, 0.5),
(0, 4, 5.0, 0.5),
(1, 4, 5.0, 0.5),
(2, 4, 5.0, 0.5),
(3, 4, 5.0, 0.5)])
assert_array_equal(prj.get('weight', format='array'),
np.array([[5.0, 5.0, 5.0, 5.0, 5.0],
[5.0, 5.0, 5.0, 5.0, 5.0],
[5.0, 5.0, 5.0, 5.0, 5.0],
[5.0, 5.0, 5.0, 5.0, 5.0]]))
def test_connect_with_distance_dependent_weights_and_delays(self, sim=sim):
syn = sim.StaticSynapse(weight="d+100", delay="0.2+2*d")
C = connectors.AllToAllConnector(safe=False)
prj = sim.Projection(self.p1, self.p2, C, syn)
self.assertEqual(prj.get(["weight", "delay"], format='list'),
[(0, 0, 100.0, 0.2),
(1, 0, 101.0, 2.2),
(2, 0, 102.0, 4.2),
(3, 0, 103.0, 6.2),
(0, 1, 101.0, 2.2),
(1, 1, 100.0, 0.2),
(2, 1, 101.0, 2.2),
(3, 1, 102.0, 4.2),
(0, 2, 102.0, 4.2),
(1, 2, 101.0, 2.2),
(2, 2, 100.0, 0.2),
(3, 2, 101.0, 2.2),
(0, 3, 103.0, 6.2),
(1, 3, 102.0, 4.2),
(2, 3, 101.0, 2.2),
(3, 3, 100.0, 0.2),
(0, 4, 104.0, 8.2),
(1, 4, 103.0, 6.2),
(2, 4, 102.0, 4.2),
(3, 4, 101.0, 2.2)])
def test_connect_with_delays_None(self):
C = connectors.AllToAllConnector(weights=0.1, delays=None)
assert_equal(C.weights, 0.1)
assert_equal(C.delays, None)
assert C.safe
assert C.allow_self_connections
C.connect(self.prj)
assert_equal(self.prj.connections[0][3],
self.prj._simulator.state.min_delay)
def test_connect_with_distance_dependent_weights_and_delays(self):
syn = sim.StaticSynapse(weight="d+100", delay="0.2+2*d")
C = connectors.AllToAllConnector(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
[(0, 1, 101.0, 2.2), (1, 1, 100.0, 0.2), (2, 1, 101.0, 2.2),
(3, 1, 102.0, 4.2), (0, 3, 103.0, 6.2), (1, 3, 102.0, 4.2),
(2, 3, 101.0, 2.2), (3, 3, 100.0, 0.2)])
def test_connect_with_scalar_weights_and_delays(self):
C = connectors.AllToAllConnector(weights=5.0, delays=0.5, safe=False)
C.progressbar = Mock()
C.progression = Mock()
C.connect(self.prj)
assert_equal(
set(self.prj.connections),
set([(17, 80, 5.0, 0.5), (17, 82, 5.0, 0.5), (18, 80, 5.0, 0.5),
(18, 82, 5.0, 0.5), (19, 80, 5.0, 0.5), (19, 82, 5.0, 0.5),
(20, 80, 5.0, 0.5), (20, 82, 5.0, 0.5)]))
def test_connect_with_scalar_weights_and_delays(self):
C = connectors.AllToAllConnector(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
[(0, 1, 5.0, 0.5), (1, 1, 5.0, 0.5), (2, 1, 5.0, 0.5),
(3, 1, 5.0, 0.5), (0, 3, 5.0, 0.5), (1, 3, 5.0, 0.5),
(2, 3, 5.0, 0.5), (3, 3, 5.0, 0.5)])
def test_connect_with_distance_dependent_weights(self, sim=sim):
d_expr = "d+100"
syn = sim.StaticSynapse(weight=d_expr, delay=0.5)
C = connectors.AllToAllConnector(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
[(0, 1, 101.0, 0.5), (1, 1, 100.0, 0.5), (2, 1, 101.0, 0.5),
(3, 1, 102.0, 0.5), (0, 3, 103.0, 0.5), (1, 3, 102.0, 0.5),
(2, 3, 101.0, 0.5), (3, 3, 100.0, 0.5)])
def test_connect_with_random_weights_parallel_safe(self):
rd = random.RandomDistribution(
rng=MockRNG(delta=1.0, parallel_safe=True))
syn = sim.StaticSynapse(weight=rd, delay=0.5)
C = connectors.AllToAllConnector(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
[(0, 1, 4.0, 0.5), (1, 1, 5.0, 0.5), (2, 1, 6.0, 0.5),
(3, 1, 7.0, 0.5), (0, 3, 12.0, 0.5), (1, 3, 13.0, 0.5),
(2, 3, 14.0, 0.5), (3, 3, 15.0, 0.5)])
def test_connect_with_random_weights_parallel_safe(self):
rd = random.RandomDistribution(rng=MockRNG(num_processes=2, delta=1.0))
C = connectors.AllToAllConnector(weights=rd, delays=0.5, safe=False)
C.progressbar = Mock()
C.progression = Mock()
C.connect(self.prj)
assert_equal(self.prj.connections, [(17, 80, 1.0, 0.5),
(17, 82, 3.0, 0.5),
(18, 80, 6.0, 0.5),
(18, 82, 8.0, 0.5),
(19, 80, 11.0, 0.5),
(19, 82, 13.0, 0.5),
(20, 80, 16.0, 0.5),
(20, 82, 18.0, 0.5)])
def test_connect_with_array_weights(self, sim=sim):
C = connectors.AllToAllConnector(safe=False)
syn = sim.StaticSynapse(weight=np.arange(0.0, 2.0, 0.1).reshape(4, 5),
delay=0.5)
prj = sim.Projection(self.p1, self.p2, C, syn)
assert_array_almost_equal(
# use gather False because we are faking the MPI
np.array(prj.get(["weight", "delay"], format='list',
gather=False)),
np.array([(0, 1, 0.1, 0.5), (1, 1, 0.6, 0.5), (2, 1, 1.1, 0.5),
(3, 1, 1.6, 0.5), (0, 3, 0.3, 0.5), (1, 3, 0.8, 0.5),
(2, 3, 1.3, 0.5), (3, 3, 1.8, 0.5)]))
nan = np.nan
assert_array_almost_equal(
prj.get('weight', format='array', gather=False),
np.array([[nan, 0.1, nan, 0.3, nan], [nan, 0.6, nan, 0.8, nan],
[nan, 1.1, nan, 1.3, nan], [nan, 1.6, nan, 1.8, nan]]),
9)
def test_connect_with_distance_dependent_weights_parallel_safe(self):
d_expr = "d+100"
C = connectors.AllToAllConnector(weights=d_expr,
delays=0.5,
safe=False)
C.progressbar = Mock()
C.progression = Mock()
C.connect(self.prj)
assert_equal(
self.prj.connections,
[
(17, 80, 163.0, 0.5), # 100+|17-80|
(17, 82, 165.0, 0.5), # 100+|17-82|
(18, 80, 162.0, 0.5), # etc.
(18, 82, 164.0, 0.5),
(19, 80, 161.0, 0.5),
(19, 82, 163.0, 0.5),
(20, 80, 160.0, 0.5),
(20, 82, 162.0, 0.5)
])
def test_connect_with_random_weights_parallel_safe(self, sim=sim):
rd = random.RandomDistribution('uniform', (0, 1),
rng=MockRNG(delta=1.0,
parallel_safe=True))
syn = sim.StaticSynapse(weight=rd, delay=0.5)
C = connectors.AllToAllConnector(safe=False)
prj = sim.Projection(self.p1, self.p2, C, syn)
# note that the outer loop is over the post-synaptic cells, the inner loop over the pre-synaptic
self.assertEqual(
prj.get(["weight", "delay"], format='list', gather=False
), # use gather False because we are faking the MPI
[(0, 1, 4.0, 0.5), (1, 1, 5.0, 0.5), (2, 1, 6.0, 0.5),
(3, 1, 7.0, 0.5), (0, 3, 12.0, 0.5), (1, 3, 13.0, 0.5),
(2, 3, 14.0, 0.5), (3, 3, 15.0, 0.5)])
nan = np.nan
assert_array_almost_equal(
prj.get('weight', format='array', gather=False),
np.array([[nan, 4.0, nan, 12.0, nan], [nan, 5.0, nan, 13.0, nan],
[nan, 6.0, nan, 14.0, nan], [nan, 7.0, nan, 15.0, nan]]),
9)
def test_connect_with_delays_too_small(self):
C = connectors.AllToAllConnector(weights=0.1, delays=0.0)
assert_raises(errors.ConnectionError, C.connect, self.prj)
def test_connect_with_delays_too_small(self):
C = connectors.AllToAllConnector()
syn = sim.StaticSynapse(weight=0.1, delay=0.0)
self.assertRaises(errors.ConnectionError, sim.Projection, self.p1, self.p2, C, syn)
def test_connect_with_list_delays_too_small(self):
C = connectors.AllToAllConnector(
weights=0.1, delays=[1.0, 1.0, 0.0, 0.0, 3.0, 1.5, 2.3, 0.9])
assert_raises(errors.ConnectionError, C.connect, self.prj)
