def test_connect_with_default_args_again(self, sim=sim):
C = connectors.FixedProbabilityConnector(p_connect=0.5,
rng=MockRNG2(1 - np.array([1, 0, 0, 1,
0, 0, 0, 1,
1, 1, 0, 0,
1, 0, 1, 0,
1, 1, 0, 1]),
parallel_safe=True))
syn = sim.StaticSynapse()
prj = sim.Projection(self.p1, self.p2, C, syn)
# 20 possible connections. Due to the mock RNG, only the following
# are created (0,0), (3,0), (3,1), (0,2), (1,2), (0,3), (2,3), (0,4), (1,4), (3,4)
# (note that the outer loop is over post-synaptic cells (columns), the inner loop over pre-synaptic (rows))
assert_array_almost_equal(prj.get('delay', format='array'),
np.array([[0.123, nan, 0.123, 0.123, 0.123],
[nan, nan, 0.123, nan, 0.123],
[nan, nan, nan, 0.123, nan],
[0.123, 0.123, nan, nan, 0.123]]),
9)
self.assertEqual(prj.get(["weight", "delay"], format='list'),
[(0, 0, 0.0, 0.123),
(3, 0, 0.0, 0.123),
(3, 1, 0.0, 0.123),
(0, 2, 0.0, 0.123),
(1, 2, 0.0, 0.123),
(0, 3, 0.0, 0.123),
(2, 3, 0.0, 0.123),
(0, 4, 0.0, 0.123),
(1, 4, 0.0, 0.123),
(3, 4, 0.0, 0.123)
])
def test_connect_with_probability_one(self, sim=sim):
C = connectors.FixedProbabilityConnector(p_connect=1.)
syn = sim.StaticSynapse()
prj = sim.Projection(self.p1, self.p2, C, syn)
self.assertEqual(prj.get(["weight", "delay"], format='list'),
[(0, 0, 0.0, 0.123),
(1, 0, 0.0, 0.123),
(2, 0, 0.0, 0.123),
(3, 0, 0.0, 0.123),
(0, 1, 0.0, 0.123),
(1, 1, 0.0, 0.123),
(2, 1, 0.0, 0.123),
(3, 1, 0.0, 0.123),
(0, 2, 0.0, 0.123),
(1, 2, 0.0, 0.123),
(2, 2, 0.0, 0.123),
(3, 2, 0.0, 0.123),
(0, 3, 0.0, 0.123),
(1, 3, 0.0, 0.123),
(2, 3, 0.0, 0.123),
(3, 3, 0.0, 0.123),
(0, 4, 0.0, 0.123),
(1, 4, 0.0, 0.123),
(2, 4, 0.0, 0.123),
(3, 4, 0.0, 0.123),
])
def test_connect_with_default_args_again(self):
C = connectors.FixedProbabilityConnector(p_connect=0.5,
rng=MockRNG2(1 - numpy.array([1, 0, 0, 1,
0, 0, 0, 1,
1, 1, 0, 0,
1, 0, 1, 0,
1, 1, 0, 1]),
parallel_safe=True))
syn = sim.StaticSynapse()
prj = sim.Projection(self.p1, self.p2, C, syn)
# 20 possible connections. Due to the mock RNG, only the following
# are created (0,0), (3,0), (3,1), (0,2), (1,2), (0,3), (2,3), (0,4), (1,4), (3,4)
# of these, (3,1), (0,3), (2,3) are created on this node
# (note that the outer loop is over post-synaptic cells (columns), the inner loop over pre-synaptic (rows))
nan = numpy.nan
assert_array_almost_equal(prj.get('delay', format='array', gather=False),
numpy.array([[nan, nan, nan, 0.123, nan],
[nan, nan, nan, nan, nan],
[nan, nan, nan, 0.123, nan],
[nan, 0.123, nan, nan, nan]]),
9)
self.assertEqual(prj.get(["weight", "delay"], format='list', gather=False), # use gather False because we are faking the MPI
[(3, 1, 0.0, 0.123),
(0, 3, 0.0, 0.123),
(2, 3, 0.0, 0.123)])
def test_connect_with_random_delays_parallel_safe(self):
rd = random.RandomDistribution('uniform', [0.1, 1.1], rng=MockRNG(start=1.0, delta=0.2, parallel_safe=True))
syn = sim.StaticSynapse(delay=rd)
C = connectors.FixedProbabilityConnector(p_connect=0.75, rng=MockRNG(delta=0.1))
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, 0.0, 1.0+0.2*4),
(1, 1, 0.0, 1.0+0.2*5),
(2, 1, 0.0, 1.0+0.2*6),
(3, 1, 0.0, 1.0+0.2*7)])
def test_connect_with_weight_function(self):
C = connectors.FixedProbabilityConnector(p_connect=0.75,
rng=MockRNG(delta=0.1))
syn = sim.StaticSynapse(weight=lambda d: 0.1*d)
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, 0.1, 0.123),
(1, 1, 0.0, 0.123),
(2, 1, 0.1, 0.123),
(3, 1, 0.2, 0.123)])
def test_connect_with_default_args(self):
C = connectors.FixedProbabilityConnector(p_connect=0.75)
C.progressbar = Mock()
C.progression = Mock()
C.connect(self.prj)
# 20 possible connections. Due to the mock RNG, only the
# first 8 are created (17, 79), (17, 80), (17,81), (17,82), (17,83), (18,79), (18,80), (18,81)
# of these, (17,80), (17,82), (18,80) are created on this node
assert_equal(self.prj.connections, [(17, 80, 0.0, MIN_DELAY),
(17, 82, 0.0, MIN_DELAY),
(18, 80, 0.0, MIN_DELAY)])
def test_connect_with_default_args(self):
C = connectors.FixedProbabilityConnector(p_connect=0.75,
rng=MockRNG(delta=0.1, parallel_safe=True))
syn = sim.StaticSynapse()
prj = sim.Projection(self.p1, self.p2, C, syn)
# 20 possible connections. Due to the mock RNG, only the
# first 8 are created (0,0), (1,0), (2,0), (3,0), (0,1), (1,1), (2,1), (3,1)
# of these, (0,1), (1,1), (2,1), (3,1) are created on this node
self.assertEqual(prj.get(["weight", "delay"], format='list', gather=False), # use gather False because we are faking the MPI
[(0, 1, 0.0, 0.123),
(1, 1, 0.0, 0.123),
(2, 1, 0.0, 0.123),
(3, 1, 0.0, 0.123)])
def test_connect_with_probability_1(self, sim=sim):
# see https://github.com/NeuralEnsemble/PyNN/issues/309
C = connectors.FixedProbabilityConnector(p_connect=1,
rng=MockRNG(
delta=0.01,
parallel_safe=True))
syn = sim.StaticSynapse()
prj = sim.Projection(self.p1, self.p2, C, syn)
# 20 connections, only some of which are created on this node
self.assertEqual(
prj.get(["weight", "delay"], format='list', gather=False
), # use gather False because we are faking the MPI
[(0, 1, 0.0, 0.123), (1, 1, 0.0, 0.123), (2, 1, 0.0, 0.123),
(3, 1, 0.0, 0.123), (0, 3, 0.0, 0.123), (1, 3, 0.0, 0.123),
(2, 3, 0.0, 0.123), (3, 3, 0.0, 0.123)])
def test_connect_weight_function_and_one_post_synaptic_neuron_not_connected(self, sim=sim):
C = connectors.FixedProbabilityConnector(p_connect=0.8,
rng=MockRNG(delta=0.05))
syn = sim.StaticSynapse(weight=lambda d: 0.1 * d)
prj = sim.Projection(self.p1, self.p2, C, syn)
assert_array_almost_equal(prj.get(["weight", "delay"], format='array'),
np.array([
[[0., 0.1, 0.2, 0.3, nan],
[0.1, 0., 0.1, 0.2, nan],
[0.2, 0.1, 0.0, 0.1, nan],
[0.3, 0.2, 0.1, 0.0, nan]],
[[0.123, 0.123, 0.123, 0.123, nan],
[0.123, 0.123, 0.123, 0.123, nan],
[0.123, 0.123, 0.123, 0.123, nan],
[0.123, 0.123, 0.123, 0.123, nan]]
]),
9)
def test_connect_with_random_delays_parallel_safe(self):
rd = random.RandomDistribution('uniform', low=0.1, high=1.1, rng=MockRNG(start=1.0, delta=0.2, parallel_safe=True))
syn = sim.StaticSynapse(delay=rd)
C = connectors.FixedProbabilityConnector(p_connect=0.5,
rng=MockRNG2(1 - numpy.array([1, 0, 0, 1,
0, 0, 0, 1,
1, 1, 0, 0,
1, 0, 1, 0,
1, 1, 0, 1]),
parallel_safe=True))
prj = sim.Projection(self.p1, self.p2, C, syn)
nan = numpy.nan
assert_array_almost_equal(prj.get('delay', format='array', gather=False),
numpy.array([[nan, nan, nan, 2.0, nan],
[nan, nan, nan, nan, nan],
[nan, nan, nan, 2.2, nan],
[nan, 1.4, nan, nan, nan]]),
9)
def test_connect_with_default_args(self, sim=sim):
C = connectors.FixedProbabilityConnector(p_connect=0.85,
rng=MockRNG(delta=0.1, parallel_safe=True))
syn = sim.StaticSynapse()
prj = sim.Projection(self.p1, self.p2, C, syn)
# 20 possible connections. Due to the mock RNG, only the
# first 9 are created (0,0), (1,0), (2,0), (3,0), (0,1), (1,1), (2,1), (3,1), (0,2)
self.assertEqual(prj.get(["weight", "delay"], format='list'),
[(0, 0, 0.0, 0.123),
(1, 0, 0.0, 0.123),
(2, 0, 0.0, 0.123),
(3, 0, 0.0, 0.123),
(0, 1, 0.0, 0.123),
(1, 1, 0.0, 0.123),
(2, 1, 0.0, 0.123),
(3, 1, 0.0, 0.123),
(0, 2, 0.0, 0.123)
])
def test_connect_with_weight_function(self, sim=sim):
C = connectors.FixedProbabilityConnector(p_connect=0.85,
rng=MockRNG(delta=0.1))
syn = sim.StaticSynapse(weight=lambda d: 0.1 * d)
prj = sim.Projection(self.p1, self.p2, C, syn)
# 20 possible connections. Due to the mock RNG, only the
# first 9 are created (0,0), (1,0), (2,0), (3,0), (0,1), (1,1), (2,1), (3,1), (0,2)
assert_array_almost_equal(prj.get(["weight", "delay"], format='array'),
np.array([
[[0., 0.1, 0.2, nan, nan],
[0.1, 0., nan, nan, nan],
[0.2, 0.1, nan, nan, nan],
[0.3, 0.2, nan, nan, nan]],
[[0.123, 0.123, 0.123, nan, nan],
[0.123, 0.123, nan, nan, nan],
[0.123, 0.123, nan, nan, nan],
[0.123, 0.123, nan, nan, nan]]
]),
9)
def test_connect_with_random_delays_parallel_safe(self, sim=sim):
rd = random.RandomDistribution('uniform', low=0.1, high=1.1,
rng=MockRNG(start=1.0, delta=0.2, parallel_safe=True))
syn = sim.StaticSynapse(delay=rd)
C = connectors.FixedProbabilityConnector(p_connect=0.5,
rng=MockRNG2(1 - np.array([1, 0, 0, 1,
0, 0, 0, 1,
1, 1, 0, 0,
1, 0, 1, 0,
1, 1, 0, 1]),
parallel_safe=True))
prj = sim.Projection(self.p1, self.p2, C, syn)
# 20 possible connections. Due to the mock RNG, only the following
# are created (0,0), (3,0), (3,1), (0,2), (1,2), (0,3), (2,3), (0,4), (1,4), (3,4)
# (note that the outer loop is over post-synaptic cells (columns), the inner loop over pre-synaptic (rows))
assert_array_almost_equal(prj.get('delay', format='array'),
np.array([[1.0, nan, 1.6, 2.0, 2.4],
[nan, nan, 1.8, nan, 2.6],
[nan, nan, nan, 2.2, nan],
[1.2, 1.4, nan, nan, 2.8]]),
9)
